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. 2023 Dec 15;3:1308708. doi: 10.3389/fbinf.2023.1308708

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Copyright © 2023 Machireddy, Thibault, Loftis, Stoltz, Bueno, Smith, Riesterer, Gray and Song.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Nucleus and nucleolus segmentation results on PTT and Bx4 datasets. (A) Representative qualitative results showing input images (top row) overlaid with nucleus (green) and nucleolus (red) ground truth masks (middle row) and predicted nucleus (yellow) and nucleolus (pink) segmentation masks (bottom row) for the PTT dataset. (B) Representative qualitative results showing input images (top row) overlaid with predicted nucleus (yellow) and nucleolus (pink) segmentation masks (bottom row) for the Bx4 dataset. All 19 slices from the Bx4 dataset that had nucleolus labels were employed in the training of ResUNet, resulting in the possibility of conducting only a qualitative comparison. Numbers in the lower right-hand corner of images indicate the slice position of the image in the full image stack. Scale: horizontal image width = 25 μm.