Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide images
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917588848607232 |
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| author | Habis, Antoine Nathanson, Roy Rosman Meas-Yedid, Vannary Angelini, Elsa D. Olivo-Marin, Jean-Christophe |
| author_facet | Habis, Antoine Nathanson, Roy Rosman Meas-Yedid, Vannary Angelini, Elsa D. Olivo-Marin, Jean-Christophe |
| contents | 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). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_08333 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide images Habis, Antoine Nathanson, Roy Rosman Meas-Yedid, Vannary Angelini, Elsa D. Olivo-Marin, Jean-Christophe Computer Vision and Pattern Recognition 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). |
| title | Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide images |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2402.08333 |