mlsanityData to 14 Oct 2026

Semi-Supervised Segmentation of Functional Tissue Units at the Cellular Level

arXiv 2305.02148 ↗First posted 3 May 2023eess.IV cs.CV cs.LGcited by 0

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Abstract (arXiv)

We present a new method for functional tissue unit segmentation at the cellular level, which utilizes the latest deep learning semantic segmentation approaches together with domain adaptation and semi-supervised learning techniques. This approach allows for minimizing the domain gap, class imbalance, and captures settings influence between HPA and HubMAP datasets. The presented approach achieves comparable with state-of-the-art-result in functional tissue unit segmentation at the cellular level. The source code is available at https://github.com/VSydorskyy/hubmap_2022_htt_solution

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 19 of its 44 references that are in the map. First posted on arXiv 3 May 2023.

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19 of 44 references.

References · 19

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7 more
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