Article

Deep-learning quantified cell-type-specific nuclear morphology predicts genomic instability and prognosis in multiple cancer types

2023-05-15

Abstract excerpt

<h4>ABSTRACT</h4> While alterations in nucleus size, shape, and color are ubiquitous in cancer, comprehensive quantification of nuclear morphology across a whole-slide histologic image remains a challenge. Here, we describe the development of a pan-tissue, deep learning-based digital pathology pipeline for exhaustive nucleus detection, segmentation, and classification and the utility of this pipeline for nuclear...

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Literature Corpus work: 609e0d4e-e286-5505-acb6-ab1e9497e76e
DOI: 10.1101/2023.05.15.539600

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