From 1c1228469db023133b979e191a6f9cf06bb9e59d Mon Sep 17 00:00:00 2001 From: kapoorlab Date: Sun, 3 Sep 2023 15:28:50 +0200 Subject: [PATCH] readme links --- MAMMARYGLAND.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/MAMMARYGLAND.md b/MAMMARYGLAND.md index ac46714..6e8677a 100644 --- a/MAMMARYGLAND.md +++ b/MAMMARYGLAND.md @@ -1,3 +1,5 @@ # Segmentation of mammary gland cells -VollSeg specializes with its seed pooling approach to segment irregular shapes of [mammary gland cells](images/Seg_pipe-git.png) from human or mouse samples. In the orignal algorithm we use a CARE trained denoising model and eaither use the U-Net model for semantic segmentation or use the denoising model for the semantic segmentation depending on which model has a better prediction. For using combination of (U-Net, CARE and StarDist) model with U-Net as the model for semantic segmentation use this [script](scripts/mammary_gland_us.py) if you want to use the denoised image as the base image for creating the semantic segmentation map using Otsu threshold set the parameter ```dounet=False``` in that same script. \ No newline at end of file +VollSeg specializes with its seed pooling approach to segment irregular shapes of | Image | +| --- | +| ![Mammary Gland Cells](images/Seg_pipe-git.png) | from human or mouse samples. In the orignal algorithm we use a CARE trained denoising model and eaither use the U-Net model for semantic segmentation or use the denoising model for the semantic segmentation depending on which model has a better prediction. For using combination of (U-Net, CARE and StarDist) model with U-Net as the model for semantic segmentation use this [script](scripts/mammary_gland_us.py) if you want to use the denoised image as the base image for creating the semantic segmentation map using Otsu threshold set the parameter ```dounet=False``` in that same script. \ No newline at end of file