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© Research
Publication : 2022 IEEE International Conference on Image Processing (ICIP)

Smart Learning of Click and Refine for Nuclei Segmentation on Histology Images

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in 2022 IEEE International Conference on Image Processing (ICIP) - 18 Oct 2022

Antoine Habis; Vannary Meas-Yedid; Daniel Felipe González Obando; Jean-Christophe Olivo-Marin BioImage Analysis Unit, Institut Pasteur, CNRS UMR 3691, Paris, France ; Elsa D. Angelini

Link to DOI – 10.1109/ICIP46576.2022.9897496

Deep learning has proven to be a very efficient tool to help pathologists analyze Whole Slide Images (WSI) toward automated classification or segmentation of detailed structures such as nuclei, glands or glomeruli. These objects are particularly relevant for disease diagnosis and staging. Many deep learning methods have shown impressive performance but are still imperfect, while manual segmentation has poor inter-rater agreement. In this paper, we propose a patch-level automated correction of a given baseline initial segmentation, based on deep-learning of segmentation errors and downstream local refinements. Results on the MoNuSeg and PanNuke test datasets show significant improvement of nuclei segmentation quality.

https://ieeexplore.ieee.org/abstract/document/9897496/authors#authors