Bibliographic Details
| Title: |
Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide images |
| Authors: |
Habis, Antoine, Nathanson, Roy Rosman, Meas-Yedid, Vannary, Angelini, Elsa D., Olivo-Marin, Jean-Christophe |
| Publication Year: |
2024 |
| Collection: |
Computer Science |
| Subject Terms: |
Computer Science - Computer Vision and Pattern Recognition |
| More Details: |
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). |
| Document Type: |
Working Paper |
| Access URL: |
http://arxiv.org/abs/2402.08333 |
| Accession Number: |
edsarx.2402.08333 |
| Database: |
arXiv |
