start jupyter book

EMBRYOS.md

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+# Confocal and Light Sheet imaged Embryonic cells
+
+## Ascadian Embryo
+In this example we consider a dataset imaged using Light sheet fused from four angles to create a single channel 3D image of Phallusia Mammillata Embryo created using live SPIM imaging. The training data can be found [here](https://figshare.com/articles/dataset/Astec-half-Pm1_Cut_at_2-cell_stage_half_Phallusia_mammillata_embryo_live_SPIM_imaging_stages_6-16_/11309570?backTo=/s/765d4361d1b073beedd5). For this imaging modality we trained only a [UNet model](https://zenodo.org/record/6337699) to segment the interior region of the cells and by using ```slice_merge=True``` and 
+```expand_labels=True``` in the VollSeg parameter setting we obtained the following segmentation result along with the metrics compared to the ground truth.
+<img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Ascadian_raw.png"  title="Raw Ascadian Embryo" width="200">
+<img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Ascadian_pred.png" title="Prediction Ascadian Embryo" width="200" > | <img src="https://github.com/kapoorlab/vollseg-napari/blob/main/vollseg_napari/images/Metrics_Ascadian.png" title="Metrics Ascadian Embryo" width="200" > 

README.md

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 [![Twitter Badge](https://badgen.net/badge/icon/twitter?icon=twitter&label)](https://twitter.com/entracod)
 
 
+VollSeg is not just one segmentation algorithm but is a crafted modular segmentation tool for different model organisms and imaging modalities. For some imaged samples just using U-Net may do the job while for others it could be just StarDist and for some others it could be a combination of the two with or without any denoising or region of interest model. The only choice that remains is how to choose the VollSeg combination for your dataset and that is what we answer in our documentation.
+
+
 This project provides the [napari](https://napari.org/) plugin for [VollSeg](https://github.com/kapoorlab/vollseg), a deep learning based 2D and 3D segmentation tool for irregular shaped cells. VollSeg has originally been developed (see [papers](http://conference.scipy.org/proceedings/scipy2021/varun_kapoor.html)) for the segmentation of densely packed membrane labelled cells in challenging images with low signal-to-noise ratios. The plugin allows to apply pretrained and custom trained models from within napari.
 For detailed demo of the plugin see these [videos](https://www.youtube.com/watch?v=W_gKrLWKNpQ) and a short video about the [parameter selection](https://www.youtube.com/watch?v=7tQMn_u8_7s&t=1s) 
 
 
+
 ## Installation & Usage
 
 Install the plugin with `pip install vollseg-napari` or from within napari via `Plugins > Install/Uninstall Package(s)…`. If you want GPU-accelerated prediction, please read the more detailed [installation instructions](https://github.com/kapoorlab/vollseg-napari#gpu_installation) for VollSeg.

_config.yml

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+# Book settings
+# Learn more at https://jupyterbook.org/customize/config.html
+
+title: Segmentation using VollSeg
+author: Varun Kapoor
+logo: images/kapoorlogo.png
+
+# Force re-execution of notebooks on each build.
+# See https://jupyterbook.org/content/execute.html
+execute:
+  execute_notebooks: force
+
+# Define the name of the latex output file for PDF builds
+latex:
+  latex_documents:
+    targetname: vollseg-napari.tex
+
+# Add a bibtex file so that we can create citations
+bibtex_bibfiles:
+  - references.bib
+
+# Information about where the book exists on the web
+repository:
+  url: https://github.com/Kapoorlabs-CAPED/vollseg-napari/ # Online location of your book
+  path_to_book: docs  # Optional path to your book, relative to the repository root
+  branch: master  # Which branch of the repository should be used when creating links (optional)
+
+# Add GitHub buttons to your book
+# See https://jupyterbook.org/customize/config.html#add-a-link-to-your-repository
+html:
+  use_issues_button: true
+  use_repository_button: true

_toc.yml

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+# Table of contents
+# Learn more at https://jupyterbook.org/customize/toc.html
+
+format: jb-book
+root: README
+
+chapters:
+    - file: EMBRYOS
+    - file: MAMMARYGLAND
+    - file: XENOPUS
+    - file: SPHEROIDS
+    - file: MICROTUBULES