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@@ -19,7 +19,7 @@ Matěj Pekár, Vít Musil, Rudolf Nenutil, Petr Holub, Tomáš Brázdil
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  LSP-DETR (Local Star Polygon DEtection TRansformer) is a lightweight, efficient, and end-to-end deep learning model for nuclei instance segmentation in histopathological images. It combines a DETR-based transformer decoder with star-convex polygon shape descriptors to enable accurate and fast segmentation without complex post-processing.
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  ```python
 
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  LSP-DETR (Local Star Polygon DEtection TRansformer) is a lightweight, efficient, and end-to-end deep learning model for nuclei instance segmentation in histopathological images. It combines a DETR-based transformer decoder with star-convex polygon shape descriptors to enable accurate and fast segmentation without complex post-processing.
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+ NOTE: This checkpoint was pretrained on the complete PanNuke dataset without class labels. This configuration prioritizes maximum recall, making it ideal for robust nucleus localization.
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  ```python