Annotation-free 3D segmentation of prostate glands enabled with deep-learning image translation

Weisi Xie; Adam K. Glaser; Nicholas Reder; Nadia Postupna; Chenyi Mao; Can Koyuncu; Patrick Leo; Robert Serafin; Hongyi Huang; Anant Madabhushi; Lawrence True; Jonathan T. C. Liu

doi:10.1117/12.2576965

5 March 2021 Annotation-free 3D segmentation of prostate glands enabled with deep-learning image translation

Weisi Xie, Adam K. Glaser, Nicholas Reder, Nadia Postupna, Chenyi Mao, Can Koyuncu, Patrick Leo, Robert Serafin, Hongyi Huang, Anant Madabhushi, Lawrence True, Jonathan T. C. Liu

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Proceedings Volume 11631, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XIX; 116310M (2021) https://doi.org/10.1117/12.2576965
Event: SPIE BiOS, 2021, Online Only

Abstract

Glandular architecture is currently the basis for the Gleason grading of prostate biopsies. To visualize and computationally analyze glandular features in large 3D pathology datasets, we developed an annotation-free segmentation method for 3D prostate glands that relies upon synthetic 3D immunofluorescence (IF) enabled by generative adversarial networks. By using a fluorescent analog of H and E (cheap and fast stain) as an input, our strategy allows for accurate glandular segmentation that does not rely upon subjective and tedious human annotations or slow and expensive 3D immunolabeling. We aim to demonstrate that this 3D segmentation will enable improved prostate cancer prognostication.

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Weisi Xie, Adam K. Glaser, Nicholas Reder, Nadia Postupna, Chenyi Mao, Can Koyuncu, Patrick Leo, Robert Serafin, Hongyi Huang, Anant Madabhushi, Lawrence True, and Jonathan T. C. Liu "Annotation-free 3D segmentation of prostate glands enabled with deep-learning image translation", Proc. SPIE 11631, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XIX, 116310M (5 March 2021); https://doi.org/10.1117/12.2576965

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KEYWORDS

Image segmentation

3D image processing

Prostate

3D modeling

Tumor growth modeling

Prostate cancer

Tissues

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