results_analysis.ipynb

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  "metadata": {
    "colab": {
      "name": "results_analysis.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "0clMaOpEOc3u",
        "9s6kzIDS-sD3",
        "8fBPNj7sOlzj",
        "bj4a_f_cOtUb"
      ],
      "toc_visible": true,
      "authorship_tag": "ABX9TyMbu/a4tUSup31BnqCWtH+S",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ccosmin97/IDC-Prostate_segmentation/blob/main/results_analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Docs/refs for viz**\n",
        "\n",
        "*   [Plotly](https://plotly.com/python/box-plots/)\n",
        "*   [Creating and Updating Figures in Python](https://plotly.com/python/creating-and-updating-figures/)\n",
        "*   [Legends in Python](https://plotly.com/python/legend/)"
      ],
      "metadata": {
        "id": "lDoe6qqlDF2t"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Auth**"
      ],
      "metadata": {
        "id": "mGfJwgF9g75l"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#colab \n",
        "from google.colab import auth\n",
        "auth.authenticate_user()"
      ],
      "metadata": {
        "id": "EET-VTsJg938"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "y1ZYYVPHz_xm"
      },
      "source": [
        "## Setup GCP Project ID"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "g1EN9Dnz0CU4"
      },
      "outputs": [],
      "source": [
        "project_id = \"idc-nlst-unet-seg\" # #YOUR_PROJECT ID"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Imports**"
      ],
      "metadata": {
        "id": "4fTmSAzf0M_R"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import plotly.graph_objects as go\n",
        "import plotly.express as px\n",
        "import plotly.graph_objects as go\n",
        "import os\n",
        "import pandas as pd\n",
        "from google.cloud import bigquery\n",
        "import numpy as np\n",
        "import datetime"
      ],
      "metadata": {
        "id": "IUm_QoHy0OfP"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Dropbox setup for import csv results**"
      ],
      "metadata": {
        "id": "-FT9zGSCu7Sb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Download results experiments csv from dropbox "
      ],
      "metadata": {
        "id": "kEL7-A60Tfq9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "path_csv_root = os.path.join(os.getcwd(), \"results_csv\")\n",
        "if not os.path.exists(path_csv_root):\n",
        "  !mkdir -p $path_csv_root\n",
        "\n",
        "dropbox_links = [\"https://www.dropbox.com/s/dd25sae3iwdw4mj/prostatex_task024-promise_3dfullres_analytics_metrics.csv?dl=0\",\n",
        "                 \"https://www.dropbox.com/s/lw1l63nil195gtf/qin-rep-repeat_task024-promise_T2_3d-fullres_analysis_metrics.csv?dl=0\",\n",
        "                 \"https://www.dropbox.com/s/uz59kp1lgrv3ssz/qin-rep-repeat_task005-prostate-pz_T2_3d-fullres_analysis_metrics.csv?dl=0\",\n",
        "                 \"https://www.dropbox.com/s/v66hrmkhugfvbxd/qin-rep-repeat_task005-prostate-pz_ADC_analysis_metrics.csv?dl=0\",\n",
        "                 \"https://www.dropbox.com/s/mp81mkemebcjmrv/prostatex_task005-prostate_PZ_T2_3D_analysis_metrics.csv?dl=0\",\n",
        "                 \"https://www.dropbox.com/s/y6d1r4y9nydlxz4/prostatex_task005-prostate_TZ_T2_3D_analysis_metrics.csv?dl=0\"]\n",
        "\n",
        "for link in dropbox_links:\n",
        "  name_file = link.split('/')[-1].split('?')[0]\n",
        "  output_path = os.path.join(path_csv_root, name_file)\n",
        "  !wget -O $output_path $link"
      ],
      "metadata": {
        "id": "TqBYgRSwu9H2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "314b1a6b-781f-4396-b411-8b2cc58b9e4c"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 46723 (46K) [text/plain]\n",
            "Saving to: ‘/content/results_csv/prostatex_task005-prostate_TZ_T2_3D_analysis_metrics.csv’\n",
            "\n",
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            "\n",
            "2022-07-27 20:32:53 (526 KB/s) - ‘/content/results_csv/prostatex_task005-prostate_TZ_T2_3D_analysis_metrics.csv’ saved [46723/46723]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##setup paths\n",
        "#task024 -- promise\n",
        "promise_results_qin_rep_t2_path = os.path.join(path_csv_root, \"qin-rep-repeat_task024-promise_T2_3d-fullres_analysis_metrics.csv\")\n",
        "promise_results_prostatex_t2_path = os.path.join(path_csv_root, \"prostatex_task024-promise_3dfullres_analytics_metrics.csv\")\n",
        "#task005 -- prostate\n",
        "pz_prostate_results_qin_rep_t2_path = os.path.join(path_csv_root, \"qin-rep-repeat_task005-prostate-pz_T2_3d-fullres_analysis_metrics.csv\")\n",
        "pz_prostate_results_qin_rep_adc_path = os.path.join(path_csv_root, \"qin-rep-repeat_task005-prostate-pz_ADC_analysis_metrics.csv\")\n",
        "pz_prostate_results_prostatex_t2_path = os.path.join(path_csv_root, \"prostatex_task005-prostate_PZ_T2_3D_analysis_metrics.csv\")\n",
        "tz_prostate_results_prostatex_t2_path = os.path.join(path_csv_root, \"prostatex_task005-prostate_TZ_T2_3D_analysis_metrics.csv\")"
      ],
      "metadata": {
        "id": "ysgh2HbT0ym3"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Task 024 -- Promise -- T2 serie input**"
      ],
      "metadata": {
        "id": "0clMaOpEOc3u"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Summary\n",
        "\n"
      ],
      "metadata": {
        "id": "cU_0Hz2HFaRH"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "*   **Pre-trained model info**\n",
        "  *  **Name Task** : Task 24 Promise\n",
        "  *  **Input** : one modality : T2\n",
        "  *  **Type of model** : 3d_fullres \n",
        "*   **IDC Data**\n",
        "  * ProstateX : t2 scans only\n",
        "  * Qin-Rep-Repeatability : t2 and adc scans, 2 StudyUIDS per PatientIDs, different timestamp\n",
        "\n"
      ],
      "metadata": {
        "id": "NrV9bi2JFcD7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Import results data - task24 promise"
      ],
      "metadata": {
        "id": "ykO62jEfsDFs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "promise_qin_rep_df = pd.read_csv(promise_results_qin_rep_t2_path) \n",
        "promise_prostatex_df = pd.read_csv(promise_results_prostatex_t2_path) "
      ],
      "metadata": {
        "id": "7STfTU4-sGNt"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "promise_qin_rep_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cGev1JwMSkVo",
        "outputId": "39b203bb-2358-4aff-b9b8-3db92cbc9237"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 30 entries, 0 to 29\n",
            "Data columns (total 8 columns):\n",
            " #   Column                  Non-Null Count  Dtype  \n",
            "---  ------                  --------------  -----  \n",
            " 0   StudyInstanceUID        30 non-null     object \n",
            " 1   PatientID               30 non-null     object \n",
            " 2   dice_score              30 non-null     float64\n",
            " 3   center_mass_ref         30 non-null     object \n",
            " 4   center_mass_pred        30 non-null     object \n",
            " 5   hausdorff_dist          30 non-null     float64\n",
            " 6    ground_truth_seg_path  30 non-null     object \n",
            " 7    pred_nnnet_path        30 non-null     object \n",
            "dtypes: float64(2), object(6)\n",
            "memory usage: 2.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "promise_prostatex_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ydCSqi0mSpQR",
        "outputId": "e02c8cfb-f0f2-4b16-cf1a-bc0390e1bc55"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 66 entries, 0 to 65\n",
            "Data columns (total 8 columns):\n",
            " #   Column                  Non-Null Count  Dtype  \n",
            "---  ------                  --------------  -----  \n",
            " 0   StudyInstanceUID        66 non-null     object \n",
            " 1   PatientID               66 non-null     object \n",
            " 2   dice_score              66 non-null     float64\n",
            " 3   center_mass_ref         66 non-null     object \n",
            " 4   center_mass_pred        66 non-null     object \n",
            " 5   hausdorff_dist          66 non-null     float64\n",
            " 6    ground_truth_seg_path  66 non-null     object \n",
            " 7    pred_nnnet_path        66 non-null     object \n",
            "dtypes: float64(2), object(6)\n",
            "memory usage: 4.2+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#concat dfs\n",
        "promise_prostatex_df[\"collection\"] = [\"prostatex\" for i in range(len(promise_prostatex_df))]\n",
        "promise_qin_rep_df[\"collection\"] = [\"qin-rep-repeatability\" for i in range(len(promise_qin_rep_df))]\n",
        "promise_idc_df = pd.concat([promise_prostatex_df, promise_qin_rep_df])"
      ],
      "metadata": {
        "id": "aksU6z6bIcwy"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Viz of results"
      ],
      "metadata": {
        "id": "9s6kzIDS-sD3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Dice Score"
      ],
      "metadata": {
        "id": "-V66TbTREoP0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot using plotly\n",
        "fig = px.box(promise_idc_df,\n",
        "             x = \"collection\",\n",
        "             y=\"dice_score\",\n",
        "             points=\"all\",\n",
        "             color=\"collection\",\n",
        "             hover_data=[\"PatientID\", \"hausdorff_dist\", \"StudyInstanceUID\", \" pred_nnnet_path\", \" ground_truth_seg_path\"],\n",
        "             template=\"plotly_white\",\n",
        "             title=\"Dice Scores for prostatex and qin-rep-repeat for nnunet preds based on pre-trained model task24-promise, labelid=whole prostate\",\n",
        "             notched=True)\n",
        "  \n",
        "# initializing showlegend to \"False\"\n",
        "fig.update_layout(showlegend=False)\n",
        "  \n",
        "fig.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jG0Z3xrWF-FK",
        "outputId": "ed0b8075-69a7-45ae-dc58-21e55802de00"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Task 005 -- Prostate(Multi-modal -- T2+ADC) -- Qin-Rep-Repeatability**\n",
        "\n"
      ],
      "metadata": {
        "id": "8fBPNj7sOlzj"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Label : Peripheral Zone"
      ],
      "metadata": {
        "id": "bj4a_f_cOtUb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Import results data - task005 prostate"
      ],
      "metadata": {
        "id": "hw6cZAf2Olzk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pz_prostate_qin_rep_t2_df = pd.read_csv(pz_prostate_results_qin_rep_t2_path)\n",
        "pz_prostate_qin_rep_adc_df = pd.read_csv(pz_prostate_results_qin_rep_adc_path)\n",
        "pz_prostate_prostatex_t2_df = pd.read_csv(pz_prostate_results_prostatex_t2_path)\n",
        "# pz_prostate_results_qin_rep_adc_2d_df = pd.read_csv(pz_prostate_results_qin_rep_adc_2d_path)"
      ],
      "metadata": {
        "id": "ZCdr3uXdOlzk"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pz_prostate_qin_rep_t2_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "281ea26a-d9bf-4c8e-902f-e474871e23b3",
        "id": "SypmQszaOlzk"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 30 entries, 0 to 29\n",
            "Data columns (total 8 columns):\n",
            " #   Column                  Non-Null Count  Dtype  \n",
            "---  ------                  --------------  -----  \n",
            " 0   StudyInstanceUID        30 non-null     object \n",
            " 1   PatientID               30 non-null     object \n",
            " 2   dice_score              30 non-null     float64\n",
            " 3   center_mass_ref         30 non-null     object \n",
            " 4   center_mass_pred        30 non-null     object \n",
            " 5   hausdorff_dist          30 non-null     float64\n",
            " 6    ground_truth_seg_path  30 non-null     object \n",
            " 7    pred_nnnet_path        30 non-null     object \n",
            "dtypes: float64(2), object(6)\n",
            "memory usage: 2.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pz_prostate_qin_rep_adc_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k8XdiqwMO3kN",
        "outputId": "3c29e308-f1aa-4ee0-c9b0-47e6c89278e8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 30 entries, 0 to 29\n",
            "Data columns (total 8 columns):\n",
            " #   Column                  Non-Null Count  Dtype  \n",
            "---  ------                  --------------  -----  \n",
            " 0   StudyInstanceUID        30 non-null     object \n",
            " 1   PatientID               30 non-null     object \n",
            " 2   dice_score              30 non-null     float64\n",
            " 3   center_mass_ref         30 non-null     object \n",
            " 4   center_mass_pred        30 non-null     object \n",
            " 5   hausdorff_dist          30 non-null     float64\n",
            " 6    ground_truth_seg_path  30 non-null     object \n",
            " 7    pred_nnnet_path        30 non-null     object \n",
            "dtypes: float64(2), object(6)\n",
            "memory usage: 2.0+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#concat dfs -- qin_rep\n",
        "pz_prostate_qin_rep_t2_df[\"type_serie\"] = [\"resampled_to_T2\" for i in range(len(pz_prostate_qin_rep_t2_df))]\n",
        "pz_prostate_qin_rep_adc_df[\"type_serie\"] = [\"resampled_to_ADC\" for i in range(len(pz_prostate_qin_rep_adc_df))]\n",
        "# pz_prostate_results_qin_rep_adc_2d_df[\"type_serie\"] = [\"resampled_to_ADC_2D\" for i in range(len(pz_prostate_results_qin_rep_adc_2d_df))]\n",
        "pz_prostate_idc_df = pd.concat([pz_prostate_qin_rep_t2_df, pz_prostate_qin_rep_adc_df])#, pz_prostate_results_qin_rep_adc_2d_df])\n",
        "#concat dfs -- prostatex\n",
        "pz_prostate_prostatex_t2_df[\"type_serie\"] = [\"resampled_to_T2\" for i in range(len(pz_prostate_prostatex_t2_df))]"
      ],
      "metadata": {
        "id": "GWKeFzigOlzl"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Viz of results"
      ],
      "metadata": {
        "id": "nHe65YbvOlzl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Qin-Prostate-Repeatability"
      ],
      "metadata": {
        "id": "RbeOx4aGXpn_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Dice Score"
      ],
      "metadata": {
        "id": "XTzwoefEErED"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot using plotly\n",
        "fig = px.box(pz_prostate_idc_df,\n",
        "             x = \"type_serie\",\n",
        "             y=\"dice_score\",\n",
        "             points=\"all\",\n",
        "             color=\"type_serie\",\n",
        "             hover_data=[\"PatientID\", \"hausdorff_dist\", \"StudyInstanceUID\", \" pred_nnnet_path\", \" ground_truth_seg_path\"],\n",
        "             template=\"plotly_white\",\n",
        "             title=\"Dice Scores for qin-rep-repeat for nnunet preds based on pre-trained model task005-prostate, labelid=Peripheral Zone\",\n",
        "             notched=True)\n",
        "  \n",
        "# initializing showlegend to \"False\"\n",
        "fig.update_layout(showlegend=False)\n",
        "  \n",
        "fig.show()"
      ],
      "metadata": {
        "id": "iQA5c8qHOlzl",
        "outputId": "60a915e9-b34a-4501-dc9c-d714d3103211",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
              "        <script src=\"https://cdn.plot.ly/plotly-2.8.3.min.js\"></script>                <div id=\"4ca46e56-474e-4b06-86fc-94c71c0dd774\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"4ca46e56-474e-4b06-86fc-94c71c0dd774\")) {                    Plotly.newPlot(                        \"4ca46e56-474e-4b06-86fc-94c71c0dd774\",                        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Scores for qin-rep-repeat for nnunet preds based on pre-trained model task005-prostate, labelid=Peripheral Zone\"},\"boxmode\":\"overlay\",\"showlegend\":false},                        {\"responsive\": true}                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('4ca46e56-474e-4b06-86fc-94c71c0dd774');\n",
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              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
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              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### ProstateX"
      ],
      "metadata": {
        "id": "IWf-CvCJXwzR"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Dice Score"
      ],
      "metadata": {
        "id": "wjvQlSjRXwzS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot using plotly\n",
        "fig = px.box(pz_prostate_prostatex_t2_df,\n",
        "             x = \"type_serie\",\n",
        "             y=\"dice_score\",\n",
        "             points=\"all\",\n",
        "             color=\"type_serie\",\n",
        "             hover_data=[\"PatientID\", \"hausdorff_dist\", \"StudyInstanceUID\", \" pred_nnnet_path\", \" ground_truth_seg_path\"],\n",
        "             template=\"plotly_white\",\n",
        "             title=\"Dice Scores for qin-rep-repeat for nnunet preds based on pre-trained model task005-prostate, labelid=Peripheral Zone\",\n",
        "             notched=True)\n",
        "  \n",
        "# initializing showlegend to \"False\"\n",
        "fig.update_layout(showlegend=False)\n",
        "  \n",
        "fig.show()"
      ],
      "metadata": {
        "outputId": "3ca723a3-b72c-419c-e66e-2a6c3729e6e1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "nGkEsckHXwzS"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
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          "metadata": {}
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      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Further analysis"
      ],
      "metadata": {
        "id": "n0cCXPagCvD2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pz_prostate_idc_df[pz_prostate_idc_df[\"PatientID\"] == \"PCAMPMRI-00010\"].head()"
      ],
      "metadata": {
        "id": "krY4UF0Ug3xa",
        "outputId": "e03844f6-7d6e-452d-f26e-b415ee2fb0eb",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": null,
      "outputs": [
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          "data": {
            "text/plain": [
              "                                     StudyInstanceUID       PatientID  \\\n",
              "18  1.3.6.1.4.1.14519.5.2.1.3671.4754.217251077299...  PCAMPMRI-00010   \n",
              "19  1.3.6.1.4.1.14519.5.2.1.3671.4754.318227959935...  PCAMPMRI-00010   \n",
              "18  1.3.6.1.4.1.14519.5.2.1.3671.4754.217251077299...  PCAMPMRI-00010   \n",
              "19  1.3.6.1.4.1.14519.5.2.1.3671.4754.318227959935...  PCAMPMRI-00010   \n",
              "\n",
              "    dice_score            center_mass_ref           center_mass_pred  \\\n",
              "18    0.303778   -29.6323 26.4219 26.6483    -38.9712 19.911 28.6667   \n",
              "19    0.404431   -21.6324 27.429 -92.6414  -34.0966 25.7832 -87.7737   \n",
              "18    0.153208   -26.1119 22.9556 28.9902   -28.7709 16.9832 27.3767   \n",
              "19    0.122076  -16.5146 31.7607 -95.3018   -17.059 23.1911 -85.1679   \n",
              "\n",
              "    hausdorff_dist                              ground_truth_seg_path  \\\n",
              "18       21.738583  /content/qin_prostate_root_data/results/data_s...   \n",
              "19       28.307106  /content/qin_prostate_root_data/results/data_s...   \n",
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    {
      "cell_type": "code",
      "source": [
        "pz_prostate_idc_df.sort_values(by=['hausdorff_dist'], ascending=True).head(100)"
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      "execution_count": null,
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          "data": {
            "text/plain": [
              "                                     StudyInstanceUID       PatientID  \\\n",
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              "4   1.3.6.1.4.1.14519.5.2.1.3671.4754.162322077241...  PCAMPMRI-00003   \n",
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              "28  1.3.6.1.4.1.14519.5.2.1.3671.4754.182983245842...  PCAMPMRI-00015   \n",
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              "17  1.3.6.1.4.1.14519.5.2.1.3671.4754.864607788085...  PCAMPMRI-00009   \n",
              "\n",
              "    dice_score              center_mass_ref             center_mass_pred  \\\n",
              "2     0.802715   0.308765 -13.3908 -106.854     1.83022 -14.018 -105.434   \n",
              "5     0.752261   -0.639141 -34.9351 27.5168    -2.24821 -34.1977 27.9303   \n",
              "6     0.713306   -10.3119 -12.0416 -7.99657    -9.7745 -13.1695 -7.98419   \n",
              "4     0.728985     7.84778 -34.8263 26.4652      6.06932 -33.751 22.7927   \n",
              "7     0.762944     -16.0423 -6.1594 11.1472    -16.4799 -6.67411 10.1558   \n",
              "20    0.792099    0.176692 26.6068 -55.6962   0.0779215 26.0989 -57.6922   \n",
              "26    0.723095     15.7349 32.1164 -12.1858     15.4209 31.8166 -14.1749   \n",
              "1     0.626547    -5.74874 -4.97922 21.0434    -6.50662 -4.87997 19.0567   \n",
              "3     0.701878   -13.2565 -14.9826 -31.8808   -14.9344 -16.7749 -30.7833   \n",
              "24    0.692402    -16.5449 29.7639 -144.448     -15.7733 31.2163 -145.73   \n",
              "24    0.776823    -16.9423 30.7223 -146.584    -16.6944 30.8541 -146.015   \n",
              "25    0.771526      -19.126 31.8889 52.4774     -18.8902 32.2037 54.2824   \n",
              "6     0.701069   -9.68386 -11.5821 -11.0333    -10.3588 -13.0719 -8.3948   \n",
              "1     0.656047     -7.3182 -4.98159 20.5159    -5.88358 -4.93486 18.8287   \n",
              "21    0.734419     -14.6174 28.0243 87.3231     -17.5347 27.6106 85.7545   \n",
              "11    0.731824   -4.09767 -31.4018 -29.7797   -4.27236 -32.3209 -24.1285   \n",
              "13    0.593454    -12.1004 -23.8641 4.76032    -10.0854 -25.3127 4.53763   \n",
              "10    0.528994   -1.08953 -39.8426 -40.2913   -2.14753 -38.7655 -38.1431   \n",
              "5     0.464278    -1.80832 -30.5508 27.2564     -3.1089 -34.5841 27.9152   \n",
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              "20    0.716241   -0.129641 24.2812 -56.2548      1.3597 26.7143 -55.9385   \n",
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              "29    0.170384     -17.1948 41.5155 167.096     -34.0485 36.6213 165.647   \n",
              "14    0.234938      1.88356 28.603 -23.9376    -11.5989 24.1295 -26.6554   \n",
              "28    0.157288    -35.4293 41.3904 -27.8763    -54.5885 38.8145 -28.0472   \n",
              "22    0.000000      -18.5158 39.426 22.0864     -17.931 34.0008 0.475845   \n",
              "9     0.058911     -8.20176 -3.0184 34.9966     -25.1974 -10.396 44.9905   \n",
              "15    0.313505      24.4361 29.5221 25.6687       6.11857 25.0167 19.816   \n",
              "22    0.000000     -15.9785 47.7265 25.7011     -23.7778 32.3672 6.27459   \n",
              "23    0.000842     -23.1431 41.6491 12.7489      -41.3174 33.6892 7.1019   \n",
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              "17    0.019119     27.0365 28.9246 -55.5909     5.27737 4.95248 -67.5075   \n",
              "\n",
              "    hausdorff_dist                              ground_truth_seg_path  \\\n",
              "2         5.929271  /content/qin_prostate_root_data/results/data_s...   \n",
              "5         5.999999  /content/qin_prostate_root_data/results/data_s...   \n",
              "6         6.257421  /content/qin_prostate_root_data/results/data_s...   \n",
              "4         6.416839  /content/qin_prostate_root_data/results/data_s...   \n",
              "7         6.655881  /content/qin_prostate_root_data/results/data_s...   \n",
              "20        6.999959  /content/qin_prostate_root_data/results/data_s...   \n",
              "26        7.698455  /content/qin_prostate_root_data/results/data_s...   \n",
              "1         7.792141  /content/qin_prostate_root_data/results/data_s...   \n",
              "3         7.860897  /content/qin_prostate_root_data/results/data_s...   \n",
              "24        8.153029  /content/qin_prostate_root_data/results/data_s...   \n",
              "24        8.701683  /content/qin_prostate_root_data/results/data_s...   \n",
              "25        9.088237  /content/qin_prostate_root_data/results/data_s...   \n",
              "6         9.262025  /content/qin_prostate_root_data/results/data_s...   \n",
              "1         9.421983  /content/qin_prostate_root_data/results/data_s...   \n",
              "21        9.673880  /content/qin_prostate_root_data/results/data_s...   \n",
              "11        9.750998  /content/qin_prostate_root_data/results/data_s...   \n",
              "13       10.484548  /content/qin_prostate_root_data/results/data_s...   \n",
              "10       10.957522  /content/qin_prostate_root_data/results/data_s...   \n",
              "5        10.964882  /content/qin_prostate_root_data/results/data_s...   \n",
              "2        11.121567  /content/qin_prostate_root_data/results/data_s...   \n",
              "0        11.219577  /content/qin_prostate_root_data/results/data_s...   \n",
              "21       11.431932  /content/qin_prostate_root_data/results/data_s...   \n",
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              "7        11.527905  /content/qin_prostate_root_data/results/data_s...   \n",
              "13       12.146822  /content/qin_prostate_root_data/results/data_s...   \n",
              "12       12.161920  /content/qin_prostate_root_data/results/data_s...   \n",
              "12       12.645398  /content/qin_prostate_root_data/results/data_s...   \n",
              "3        12.884706  /content/qin_prostate_root_data/results/data_s...   \n",
              "20       12.926336  /content/qin_prostate_root_data/results/data_s...   \n",
              "26       12.989141  /content/qin_prostate_root_data/results/data_s...   \n",
              "0        13.025498  /content/qin_prostate_root_data/results/data_s...   \n",
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              "4        13.304728  /content/qin_prostate_root_data/results/data_s...   \n",
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              "14       18.223957  /content/qin_prostate_root_data/results/data_s...   \n",
              "15       18.937592  /content/qin_prostate_root_data/results/data_s...   \n",
              "8        20.025465  /content/qin_prostate_root_data/results/data_s...   \n",
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              "19       20.943554  /content/qin_prostate_root_data/results/data_s...   \n",
              "18       21.738583  /content/qin_prostate_root_data/results/data_s...   \n",
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              "19       28.307106  /content/qin_prostate_root_data/results/data_s...   \n",
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              "28       34.771858  /content/qin_prostate_root_data/results/data_s...   \n",
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              "\n",
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              "      <th>StudyInstanceUID</th>\n",
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              "      <td>PCAMPMRI-00001</td>\n",
              "      <td>0.626547</td>\n",
              "      <td>-5.74874 -4.97922 21.0434</td>\n",
              "      <td>-6.50662 -4.87997 19.0567</td>\n",
              "      <td>7.792141</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.568383070573...</td>\n",
              "      <td>PCAMPMRI-00002</td>\n",
              "      <td>0.701878</td>\n",
              "      <td>-13.2565 -14.9826 -31.8808</td>\n",
              "      <td>-14.9344 -16.7749 -30.7833</td>\n",
              "      <td>7.860897</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.211895462561...</td>\n",
              "      <td>PCAMPMRI-00013</td>\n",
              "      <td>0.692402</td>\n",
              "      <td>-16.5449 29.7639 -144.448</td>\n",
              "      <td>-15.7733 31.2163 -145.73</td>\n",
              "      <td>8.153029</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.211895462561...</td>\n",
              "      <td>PCAMPMRI-00013</td>\n",
              "      <td>0.776823</td>\n",
              "      <td>-16.9423 30.7223 -146.584</td>\n",
              "      <td>-16.6944 30.8541 -146.015</td>\n",
              "      <td>8.701683</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.245461598867...</td>\n",
              "      <td>PCAMPMRI-00013</td>\n",
              "      <td>0.771526</td>\n",
              "      <td>-19.126 31.8889 52.4774</td>\n",
              "      <td>-18.8902 32.2037 54.2824</td>\n",
              "      <td>9.088237</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.204078048920...</td>\n",
              "      <td>PCAMPMRI-00004</td>\n",
              "      <td>0.701069</td>\n",
              "      <td>-9.68386 -11.5821 -11.0333</td>\n",
              "      <td>-10.3588 -13.0719 -8.3948</td>\n",
              "      <td>9.262025</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.288848219213...</td>\n",
              "      <td>PCAMPMRI-00001</td>\n",
              "      <td>0.656047</td>\n",
              "      <td>-7.3182 -4.98159 20.5159</td>\n",
              "      <td>-5.88358 -4.93486 18.8287</td>\n",
              "      <td>9.421983</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.131608903441...</td>\n",
              "      <td>PCAMPMRI-00011</td>\n",
              "      <td>0.734419</td>\n",
              "      <td>-14.6174 28.0243 87.3231</td>\n",
              "      <td>-17.5347 27.6106 85.7545</td>\n",
              "      <td>9.673880</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.287814201869...</td>\n",
              "      <td>PCAMPMRI-00006</td>\n",
              "      <td>0.731824</td>\n",
              "      <td>-4.09767 -31.4018 -29.7797</td>\n",
              "      <td>-4.27236 -32.3209 -24.1285</td>\n",
              "      <td>9.750998</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.962865348146...</td>\n",
              "      <td>PCAMPMRI-00007</td>\n",
              "      <td>0.593454</td>\n",
              "      <td>-12.1004 -23.8641 4.76032</td>\n",
              "      <td>-10.0854 -25.3127 4.53763</td>\n",
              "      <td>10.484548</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.133806669697...</td>\n",
              "      <td>PCAMPMRI-00006</td>\n",
              "      <td>0.528994</td>\n",
              "      <td>-1.08953 -39.8426 -40.2913</td>\n",
              "      <td>-2.14753 -38.7655 -38.1431</td>\n",
              "      <td>10.957522</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.263464522348...</td>\n",
              "      <td>PCAMPMRI-00003</td>\n",
              "      <td>0.464278</td>\n",
              "      <td>-1.80832 -30.5508 27.2564</td>\n",
              "      <td>-3.1089 -34.5841 27.9152</td>\n",
              "      <td>10.964882</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.304001015100...</td>\n",
              "      <td>PCAMPMRI-00002</td>\n",
              "      <td>0.636035</td>\n",
              "      <td>0.780633 -12.8824 -106.661</td>\n",
              "      <td>-0.677253 -14.8298 -104.859</td>\n",
              "      <td>11.121567</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.121472087445...</td>\n",
              "      <td>PCAMPMRI-00001</td>\n",
              "      <td>0.587203</td>\n",
              "      <td>-1.33749 -2.28989 -10.2502</td>\n",
              "      <td>-2.9999 -4.85959 -11.6524</td>\n",
              "      <td>11.219577</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.131608903441...</td>\n",
              "      <td>PCAMPMRI-00011</td>\n",
              "      <td>0.631151</td>\n",
              "      <td>-13.0573 28.5874 86.7006</td>\n",
              "      <td>-16.9018 26.747 86.5602</td>\n",
              "      <td>11.431932</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.133806669697...</td>\n",
              "      <td>PCAMPMRI-00006</td>\n",
              "      <td>0.657104</td>\n",
              "      <td>-2.68457 -36.5379 -42.0532</td>\n",
              "      <td>-2.55914 -38.5795 -40.0472</td>\n",
              "      <td>11.461022</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.394942238206...</td>\n",
              "      <td>PCAMPMRI-00004</td>\n",
              "      <td>0.645203</td>\n",
              "      <td>-15.5915 -5.0913 10.3866</td>\n",
              "      <td>-17.0376 -6.87358 9.62098</td>\n",
              "      <td>11.527905</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.962865348146...</td>\n",
              "      <td>PCAMPMRI-00007</td>\n",
              "      <td>0.538844</td>\n",
              "      <td>-13.0794 -23.601 5.20289</td>\n",
              "      <td>-9.75347 -25.2921 5.20694</td>\n",
              "      <td>12.146822</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.240243858523...</td>\n",
              "      <td>PCAMPMRI-00007</td>\n",
              "      <td>0.446887</td>\n",
              "      <td>-6.9738 -25.5787 -9.33559</td>\n",
              "      <td>-5.39563 -29.2109 -9.93877</td>\n",
              "      <td>12.161920</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.240243858523...</td>\n",
              "      <td>PCAMPMRI-00007</td>\n",
              "      <td>0.630110</td>\n",
              "      <td>-6.61432 -28.6256 -10.1714</td>\n",
              "      <td>-5.14063 -29.5584 -8.35427</td>\n",
              "      <td>12.645398</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.568383070573...</td>\n",
              "      <td>PCAMPMRI-00002</td>\n",
              "      <td>0.722087</td>\n",
              "      <td>-14.9412 -15.1454 -31.4659</td>\n",
              "      <td>-14.6661 -17.4489 -29.4801</td>\n",
              "      <td>12.884706</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.117496148504...</td>\n",
              "      <td>PCAMPMRI-00011</td>\n",
              "      <td>0.716241</td>\n",
              "      <td>-0.129641 24.2812 -56.2548</td>\n",
              "      <td>1.3597 26.7143 -55.9385</td>\n",
              "      <td>12.926336</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.194890890650...</td>\n",
              "      <td>PCAMPMRI-00014</td>\n",
              "      <td>0.593893</td>\n",
              "      <td>15.672 32.2682 -9.5275</td>\n",
              "      <td>16.6464 31.9035 -13.4407</td>\n",
              "      <td>12.989141</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.121472087445...</td>\n",
              "      <td>PCAMPMRI-00001</td>\n",
              "      <td>0.342426</td>\n",
              "      <td>-3.60639 -0.462681 -11.6713</td>\n",
              "      <td>-2.53412 -4.08098 -10.8543</td>\n",
              "      <td>13.025498</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.287814201869...</td>\n",
              "      <td>PCAMPMRI-00006</td>\n",
              "      <td>0.455175</td>\n",
              "      <td>-3.4712 -35.8429 -33.6361</td>\n",
              "      <td>-4.30607 -32.7622 -22.62</td>\n",
              "      <td>13.210051</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.162322077241...</td>\n",
              "      <td>PCAMPMRI-00003</td>\n",
              "      <td>0.475614</td>\n",
              "      <td>7.60237 -31.8021 24.4552</td>\n",
              "      <td>5.16454 -33.6952 24.1117</td>\n",
              "      <td>13.304728</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.245461598867...</td>\n",
              "      <td>PCAMPMRI-00013</td>\n",
              "      <td>0.536656</td>\n",
              "      <td>-19.5046 28.0672 56.2158</td>\n",
              "      <td>-18.1531 32.1598 55.1548</td>\n",
              "      <td>14.630564</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.288453744990...</td>\n",
              "      <td>PCAMPMRI-00014</td>\n",
              "      <td>0.549197</td>\n",
              "      <td>-38.0829 25.7068 -77.7818</td>\n",
              "      <td>-40.7888 24.5107 -77.2241</td>\n",
              "      <td>18.026880</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.173585825705...</td>\n",
              "      <td>PCAMPMRI-00008</td>\n",
              "      <td>0.447116</td>\n",
              "      <td>2.60567 31.0052 -26.0476</td>\n",
              "      <td>-6.69029 27.5622 -28.4564</td>\n",
              "      <td>18.223957</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.266963586071...</td>\n",
              "      <td>PCAMPMRI-00008</td>\n",
              "      <td>0.320261</td>\n",
              "      <td>23.5407 29.2081 23.7555</td>\n",
              "      <td>19.8514 24.4797 21.8298</td>\n",
              "      <td>18.937592</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.233298968565...</td>\n",
              "      <td>PCAMPMRI-00005</td>\n",
              "      <td>0.037160</td>\n",
              "      <td>-12.68 3.2502 39.9752</td>\n",
              "      <td>-19.3284 -6.73937 37.605</td>\n",
              "      <td>20.025465</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.217251077299...</td>\n",
              "      <td>PCAMPMRI-00010</td>\n",
              "      <td>0.153208</td>\n",
              "      <td>-26.1119 22.9556 28.9902</td>\n",
              "      <td>-28.7709 16.9832 27.3767</td>\n",
              "      <td>20.732069</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.318227959935...</td>\n",
              "      <td>PCAMPMRI-00010</td>\n",
              "      <td>0.122076</td>\n",
              "      <td>-16.5146 31.7607 -95.3018</td>\n",
              "      <td>-17.059 23.1911 -85.1679</td>\n",
              "      <td>20.943554</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.217251077299...</td>\n",
              "      <td>PCAMPMRI-00010</td>\n",
              "      <td>0.303778</td>\n",
              "      <td>-29.6323 26.4219 26.6483</td>\n",
              "      <td>-38.9712 19.911 28.6667</td>\n",
              "      <td>21.738583</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.288453744990...</td>\n",
              "      <td>PCAMPMRI-00014</td>\n",
              "      <td>0.490561</td>\n",
              "      <td>-39.5497 26.6038 -75.542</td>\n",
              "      <td>-53.7426 25.8732 -79.3595</td>\n",
              "      <td>26.250862</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.318227959935...</td>\n",
              "      <td>PCAMPMRI-00010</td>\n",
              "      <td>0.404431</td>\n",
              "      <td>-21.6324 27.429 -92.6414</td>\n",
              "      <td>-34.0966 25.7832 -87.7737</td>\n",
              "      <td>28.307106</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.233298968565...</td>\n",
              "      <td>PCAMPMRI-00005</td>\n",
              "      <td>0.190211</td>\n",
              "      <td>-10.6723 -1.12748 37.3313</td>\n",
              "      <td>-24.6325 -8.39595 36.0783</td>\n",
              "      <td>28.779604</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.431678793261...</td>\n",
              "      <td>PCAMPMRI-00015</td>\n",
              "      <td>0.170384</td>\n",
              "      <td>-17.1948 41.5155 167.096</td>\n",
              "      <td>-34.0485 36.6213 165.647</td>\n",
              "      <td>30.733551</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.173585825705...</td>\n",
              "      <td>PCAMPMRI-00008</td>\n",
              "      <td>0.234938</td>\n",
              "      <td>1.88356 28.603 -23.9376</td>\n",
              "      <td>-11.5989 24.1295 -26.6554</td>\n",
              "      <td>32.547173</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.182983245842...</td>\n",
              "      <td>PCAMPMRI-00015</td>\n",
              "      <td>0.157288</td>\n",
              "      <td>-35.4293 41.3904 -27.8763</td>\n",
              "      <td>-54.5885 38.8145 -28.0472</td>\n",
              "      <td>34.771858</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.264231410930...</td>\n",
              "      <td>PCAMPMRI-00012</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-18.5158 39.426 22.0864</td>\n",
              "      <td>-17.931 34.0008 0.475845</td>\n",
              "      <td>35.309219</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.240823776621...</td>\n",
              "      <td>PCAMPMRI-00005</td>\n",
              "      <td>0.058911</td>\n",
              "      <td>-8.20176 -3.0184 34.9966</td>\n",
              "      <td>-25.1974 -10.396 44.9905</td>\n",
              "      <td>36.283657</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.266963586071...</td>\n",
              "      <td>PCAMPMRI-00008</td>\n",
              "      <td>0.313505</td>\n",
              "      <td>24.4361 29.5221 25.6687</td>\n",
              "      <td>6.11857 25.0167 19.816</td>\n",
              "      <td>37.507774</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.264231410930...</td>\n",
              "      <td>PCAMPMRI-00012</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-15.9785 47.7265 25.7011</td>\n",
              "      <td>-23.7778 32.3672 6.27459</td>\n",
              "      <td>38.905758</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.298665348758...</td>\n",
              "      <td>PCAMPMRI-00012</td>\n",
              "      <td>0.000842</td>\n",
              "      <td>-23.1431 41.6491 12.7489</td>\n",
              "      <td>-41.3174 33.6892 7.1019</td>\n",
              "      <td>39.545631</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.431678793261...</td>\n",
              "      <td>PCAMPMRI-00015</td>\n",
              "      <td>0.001393</td>\n",
              "      <td>-15.8833 45.1335 175.377</td>\n",
              "      <td>-32.866 29.8662 167.697</td>\n",
              "      <td>41.322624</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.240823776621...</td>\n",
              "      <td>PCAMPMRI-00005</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-9.78308 5.03822 41.3351</td>\n",
              "      <td>3.17303 -27.0851 37.5729</td>\n",
              "      <td>43.726177</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.182983245842...</td>\n",
              "      <td>PCAMPMRI-00015</td>\n",
              "      <td>0.000244</td>\n",
              "      <td>-34.3611 46.4036 -22.5741</td>\n",
              "      <td>-57.0502 28.6911 -22.6941</td>\n",
              "      <td>43.795013</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.181478254003...</td>\n",
              "      <td>PCAMPMRI-00009</td>\n",
              "      <td>0.239291</td>\n",
              "      <td>-2.78865 22.5696 -60.9726</td>\n",
              "      <td>-24.9896 15.1474 -65.87</td>\n",
              "      <td>45.482418</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.864607788085...</td>\n",
              "      <td>PCAMPMRI-00009</td>\n",
              "      <td>0.261411</td>\n",
              "      <td>24.304 25.8425 -60.1868</td>\n",
              "      <td>5.04686 16.4877 -68.7855</td>\n",
              "      <td>47.201817</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.181478254003...</td>\n",
              "      <td>PCAMPMRI-00009</td>\n",
              "      <td>0.229964</td>\n",
              "      <td>-2.42696 23.2944 -60.6744</td>\n",
              "      <td>-23.5733 12.1171 -66.8416</td>\n",
              "      <td>49.866428</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.298665348758...</td>\n",
              "      <td>PCAMPMRI-00012</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>-24.0044 39.1041 16.9835</td>\n",
              "      <td>-31.296 -15.0516 14.755</td>\n",
              "      <td>57.671749</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_T2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>1.3.6.1.4.1.14519.5.2.1.3671.4754.864607788085...</td>\n",
              "      <td>PCAMPMRI-00009</td>\n",
              "      <td>0.019119</td>\n",
              "      <td>27.0365 28.9246 -55.5909</td>\n",
              "      <td>5.27737 4.95248 -67.5075</td>\n",
              "      <td>57.672600</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>/content/qin_prostate_root_data/results/data_s...</td>\n",
              "      <td>resampled_to_ADC</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-62efcf24-9a3d-48cb-bf36-4824998cfa9b')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "        const buttonEl =\n",
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-62efcf24-9a3d-48cb-bf36-4824998cfa9b');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Label : Transition Zone"
      ],
      "metadata": {
        "id": "aSF8TbFqYS1z"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Import results data - task005 prostate"
      ],
      "metadata": {
        "id": "GbM9TUhDYS15"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "tz_prostate_prostatex_t2_df = pd.read_csv(tz_prostate_results_prostatex_t2_path)"
      ],
      "metadata": {
        "id": "T9n5ft6hYS15"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tz_prostate_prostatex_t2_df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2826fa60-2f39-4148-e525-bfc0fb469877",
        "id": "k3vP5QOAYS15"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 98 entries, 0 to 97\n",
            "Data columns (total 8 columns):\n",
            " #   Column                  Non-Null Count  Dtype  \n",
            "---  ------                  --------------  -----  \n",
            " 0   StudyInstanceUID        98 non-null     object \n",
            " 1   PatientID               98 non-null     object \n",
            " 2   dice_score              98 non-null     float64\n",
            " 3   center_mass_ref         98 non-null     object \n",
            " 4   center_mass_pred        98 non-null     object \n",
            " 5   hausdorff_dist          98 non-null     float64\n",
            " 6    ground_truth_seg_path  98 non-null     object \n",
            " 7    pred_nnnet_path        98 non-null     object \n",
            "dtypes: float64(2), object(6)\n",
            "memory usage: 6.2+ KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#concat dfs -- prostatex\n",
        "tz_prostate_prostatex_t2_df[\"type_serie\"] = [\"resampled_to_T2\" for i in range(len(tz_prostate_prostatex_t2_df))]"
      ],
      "metadata": {
        "id": "-ofkfXWJYS15"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Viz of results"
      ],
      "metadata": {
        "id": "C5UCC-noYS16"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### ProstateX"
      ],
      "metadata": {
        "id": "6eqbcfQHYS16"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Dice Score"
      ],
      "metadata": {
        "id": "b-3bR_ukYS16"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot using plotly\n",
        "fig = px.box(tz_prostate_prostatex_t2_df,\n",
        "             x = \"type_serie\",\n",
        "             y=\"dice_score\",\n",
        "             points=\"all\",\n",
        "             color=\"type_serie\",\n",
        "             hover_data=[\"PatientID\", \"hausdorff_dist\", \"StudyInstanceUID\", \" pred_nnnet_path\", \" ground_truth_seg_path\"],\n",
        "             template=\"plotly_white\",\n",
        "             title=\"Dice Scores for qin-rep-repeat for nnunet preds based on pre-trained model task005-prostate, labelid=Transition Zone\",\n",
        "             notched=True)\n",
        "  \n",
        "# initializing showlegend to \"False\"\n",
        "fig.update_layout(showlegend=False)\n",
        "  \n",
        "fig.show()"
      ],
      "metadata": {
        "outputId": "84976cab-355a-48ae-d4e7-b3f3591a0864",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "kF_89Wr_YS16"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
              "        <script src=\"https://cdn.plot.ly/plotly-2.8.3.min.js\"></script>                <div id=\"e6efb3aa-b767-4f24-a4f4-a123ab1920b0\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"e6efb3aa-b767-4f24-a4f4-a123ab1920b0\")) {                    Plotly.newPlot(                        \"e6efb3aa-b767-4f24-a4f4-a123ab1920b0\",                        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            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#**Qin-Rep-Repeatability -- Study of consistency of predictions across same PatientID at different timestamps**"
      ],
      "metadata": {
        "id": "zciZrwTNXxRs"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def calculate_time_index(row, df_input): #assumes only two studies per PatientID\n",
        "  other_study_time = df_input[(df_input[\"PatientID\"] == row[\"PatientID\"]) \n",
        "    & (df_input[\"StudyInstanceUID\"] != row[\"StudyInstanceUID\"])].StudyDate.values[0]\n",
        "  if row.StudyDate < other_study_time:\n",
        "    return \"T0\"\n",
        "  elif row.StudyDate > other_study_time:\n",
        "    return \"T1\"\n",
        "  else:\n",
        "    return \"T\""
      ],
      "metadata": {
        "id": "_PK_caJunKN_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Promise pre-trained model"
      ],
      "metadata": {
        "id": "9lwBcTbDgRbm"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "joRbZ81GWNz1"
      },
      "outputs": [],
      "source": [
        "selection_query = f\"\"\"\n",
        "SELECT\n",
        "  DISTINCT(StudyInstanceUID),\n",
        "  PatientID,\n",
        "  StudyTime,\n",
        "  StudyDate\n",
        "FROM\n",
        "  `bigquery-public-data.idc_current.dicom_all`\n",
        "WHERE\n",
        "  collection_id = 'qin_prostate_repeatability'\"\"\" "
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bq_client = bigquery.Client(project_id)\n",
        "selection_result_qin_rep_time = bq_client.query(selection_query)\n",
        "selection_result_qin_rep_time_df = selection_result_qin_rep_time.result().to_dataframe()"
      ],
      "metadata": {
        "id": "j1PtIeNJ8Qf7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "promise_qin_rep_df = promise_qin_rep_df.merge(selection_result_qin_rep_time_df[['StudyInstanceUID', 'StudyTime', 'StudyDate']],on='StudyInstanceUID', how='inner')\n",
        "promise_qin_rep_df['time_index'] = promise_qin_rep_df.apply(calculate_time_index, args = (promise_qin_rep_df, ), axis=1)\n",
        "promise_qin_rep_df[\"PID\"] = promise_qin_rep_df.apply(lambda x: \"PID_\"+x[\"PatientID\"].split('-')[1]+\"_\"+x[\"time_index\"], axis=1)\n",
        "promise_qin_rep_df = promise_qin_rep_df.sort_values(by=['PID'], ascending=True)"
      ],
      "metadata": {
        "id": "r99eu6vcgWVI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot using plotly\n",
        "fig = px.line(promise_qin_rep_df,\n",
        "             x = \"PID\",\n",
        "             y=\"dice_score\",\n",
        "            #  points=\"all\",\n",
        "             color=\"PatientID\",\n",
        "             hover_data=[\"PatientID\", \"time_index\", \"dice_score\", \"hausdorff_dist\", \"StudyInstanceUID\", \"StudyDate\", \"StudyTime\"],\n",
        "             template=\"plotly_white\",\n",
        "             title=\"Dice Scores for qin-rep-repeat for nnunet preds based on pre-trained model task024-promise, labelid=whole prostate\")\n",
        "\n",
        "            #  notched=True)\n",
        "  \n",
        "# initializing showlegend to \"False\"\n",
        "\n",
        "fig.update_layout(showlegend=False)\n",
        "\n",
        "fig.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "tqCjDXsA3JCA",
        "outputId": "664a638c-49c7-40fd-e848-067281725847"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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Scores for qin-rep-repeat for nnunet preds based on pre-trained model task024-promise, labelid=whole prostate\"},\"showlegend\":false},                        {\"responsive\": true}                    ).then(function(){\n",
              "                            \n",
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              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
              "var notebookContainer = gd.closest('#notebook-container');\n",
              "if (notebookContainer) {{\n",
              "    x.observe(notebookContainer, {childList: true});\n",
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              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Prostate-task005 pre-trained model"
      ],
      "metadata": {
        "id": "vNc7SNPNM26u"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "r6CYM8saM26u"
      },
      "outputs": [],
      "source": [
        "selection_query = f\"\"\"\n",
        "SELECT\n",
        "  DISTINCT(StudyInstanceUID),\n",
        "  PatientID,\n",
        "  StudyTime,\n",
        "  StudyDate\n",
        "FROM\n",
        "  `bigquery-public-data.idc_current.dicom_all`\n",
        "WHERE\n",
        "  collection_id = 'qin_prostate_repeatability'\"\"\" "
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "bq_client = bigquery.Client(project_id)\n",
        "selection_result_qin_rep_time = bq_client.query(selection_query)\n",
        "selection_result_qin_rep_time_df = selection_result_qin_rep_time.result().to_dataframe()"
      ],
      "metadata": {
        "id": "80hCyzgKM26v"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pz_prostate_qin_rep_t2_df = pz_prostate_qin_rep_t2_df.merge(selection_result_qin_rep_time_df[['StudyInstanceUID', 'StudyTime', 'StudyDate']],on='StudyInstanceUID', how='inner')\n",
        "pz_prostate_qin_rep_t2_df['time_index'] = pz_prostate_qin_rep_t2_df.apply(calculate_time_index, args = (pz_prostate_qin_rep_t2_df, ), axis=1)\n",
        "pz_prostate_qin_rep_t2_df[\"PID\"] = pz_prostate_qin_rep_t2_df.apply(lambda x: \"PID_\"+x[\"PatientID\"].split('-')[1]+\"_\"+x[\"time_index\"], axis=1)\n",
        "pz_prostate_qin_rep_t2_df = pz_prostate_qin_rep_t2_df.sort_values(by=['PID'], ascending=True)"
      ],
      "metadata": {
        "id": "Co8i2_Q4M26v"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# scatter plot using plotly\n",
        "fig = px.line(pz_prostate_qin_rep_t2_df,\n",
        "             x = \"PID\",\n",
        "             y=\"dice_score\",\n",
        "            #  points=\"all\",\n",
        "             color=\"PatientID\",\n",
        "             hover_data=[\"PatientID\", \"time_index\", \"dice_score\", \"hausdorff_dist\", \"StudyInstanceUID\", \"StudyDate\", \"StudyTime\"],\n",
        "             template=\"plotly_white\",\n",
        "             title=\"Dice Scores for qin-rep-repeat for nnunet preds based on pre-trained model task005-prostate, labelid=peripheral zone\")\n",
        "\n",
        "            #  notched=True)\n",
        "  \n",
        "# initializing showlegend to \"False\"\n",
        "\n",
        "fig.update_layout(showlegend=False)\n",
        "\n",
        "fig.show()"
      ],
      "metadata": {
        "id": "AVVxeFvsM26v",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "outputId": "12c2cd5f-ae20-4f16-a090-492f7b07a6b1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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