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Kapoorlabs-CAPED · Sep 3, 2023 · 7b41ba7 · 7b41ba7
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diff --git a/MAMMARYGLAND.md b/MAMMARYGLAND.md
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 VollSeg specializes with its seed pooling approach to segment irregular shapes of 
 
-![Mammary Gland Cells](images/Seg_pipe-git.png) 
+![Mammary Gland Cells](images/Seg_compare-big.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.
diff --git a/images/Seg_compare-big.png b/images/Seg_compare-big.png