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Domain Generalisation for Mitosis Detection Exploting Preprocessing Homogenizers
Journal
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN
03029743
Date Issued
2022-01-01
Author(s)
Almahfouz Nasser, Sahar
Kurian, Nikhil Cherian
Sethi, Amit
Abstract
The detection of mitotic figures in histological tumor images plays a vital role in the decision-making of the appropriate therapy. However, tissue preparation and image acquisition methods degrade the performances of the deep learning-based approaches for mitotic figures detection. MIDOG challenge addresses the domain-shift problem of this detection task. In an endeavour to reduce this domain shift, we propose a pre-processing autoencoder that is trained adversarially to the sources of domain variations. The output of this autoencoder, exhibiting a uniform domain appearance, is finally given as input to the retina-net based mitosis detection module.
Volume
13166 LNCS
Subjects