Fig. 2: The architecture of the OMG-Net. | Communications Biology

Fig. 2: The architecture of the OMG-Net.

From: A deep learning framework deploying segment anything to detect pan-cancer mitotic figures from haematoxylin and eosin-stained slides

Fig. 2

The two-step architecture includes mask generation and mitotic figures (MF) classification. First, the post-process cell masks from patched WSIs are generated by Segment Anything (SAM) using an evenly sampled point grid as a prompt. Second, the RGB image of the segmented cell and the binary mask (presented in green) are used to classify MFs by employing an adapted ResNet18.

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