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arXiv · 2402.08333

Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide images

Antoine Habis·Roy Rosman Nathanson·Vannary Meas-Yedid·Elsa D. Angelini·Jean-Christophe Olivo-Marin
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Abstract

This paper proposes a dynamic interactive and weakly supervised segmentation method with minimal user interactions to address two major challenges in the segmentation of whole slide histopathology images. First, the lack of hand-annotated datasets to train algorithms. Second, the lack of interactive paradigms to enable a dialogue between the pathologist and the machine, which can be a major obstacle for use in clinical routine. We therefore propose a fast and user oriented method to bridge this gap by giving the pathologist control over the final result while limiting the number of interactions needed to achieve a good result (over 90\% on all our metrics with only 4 correction scribbles).

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Antoine Habis, Roy Rosman Nathanson, Vannary Meas-Yedid, Elsa D. Angelini, Jean-Christophe Olivo-Marin. 2024-02-13. Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide images. https://arxiv.org/abs/2402.08333

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