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arXiv · 2111.05125

Segmentation of Multiple Myeloma Plasma Cells in Microscopy Images with Noisy Labels

Álvaro García Faura·Dejan Štepec·Tomaž Martinčič·Danijel Skočaj
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Abstract

A key component towards an improved and fast 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 used in the competition dataset were generated semi-automatically and presented noise. To deal with it, a heavy image augmentation procedure was carried out and predictions from several models were combined using a custom ensemble strategy. State-of-the-art feature extractors and instance segmentation architectures were used, resulting in a mean Intersection-over-Union of 0.9389 on the SegPC-2021 final test set.

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Álvaro García Faura, Dejan Štepec, Tomaž Martinčič, Danijel Skočaj. 2021-11-08. Segmentation of Multiple Myeloma Plasma Cells in Microscopy Images with Noisy Labels. https://arxiv.org/abs/2111.05125

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