Segmentation of multiple myeloma plasma cells in microscopy images with noisy labels

Álvaro García Faura; Dejan Štepec; Tomaž Martinčič; Danijel Skočaj

doi:10.1117/12.2607458

4 April 2022 Segmentation of multiple myeloma plasma cells in microscopy images with noisy labels

Álvaro García Faura, Dejan Štepec, Tomaž Martinčič, Danijel Skočaj

Proceedings Volume 12033, Medical Imaging 2022: Computer-Aided Diagnosis; 120330N (2022) https://doi.org/10.1117/12.2607458
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

A key component towards an improved cancer diagnosis is the development of computer-assisted tools. In this article, we present the solution that won the SegPC-2021 competition for the segmentation of multiple myeloma plasma cells in microscopy images. The labels in the competition dataset were generated semi-automatically and presented noise. To deal with it, new labels were generated from existing ones, heavy image augmentation was carried out and predictions were combined by a custom ensemble strategy. These techniques, along with state-of-the-art feature extractors and instance segmentation architectures, resulted in a mean Intersection-over-Union of 0.9389 on the SegPC-2021 final test set.

Conference Presentation

Citation Download Citation

Álvaro García Faura, Dejan Štepec, Tomaž Martinčič, and Danijel Skočaj "Segmentation of multiple myeloma plasma cells in microscopy images with noisy labels", Proc. SPIE 12033, Medical Imaging 2022: Computer-Aided Diagnosis, 120330N (4 April 2022); https://doi.org/10.1117/12.2607458

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