mlsanityData to 14 Oct 2026

Whole Slide Image Classification of Salivary Gland Tumours

arXiv 2408.12275 ↗First posted 22 Aug 2024eess.IV cs.CVcited by 0

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Abstract (arXiv)

This work shows promising results using multiple instance learning on salivary gland tumours in classifying cancers on whole slide images. Utilising CTransPath as a patch-level feature extractor and CLAM as a feature aggregator, an F1 score of over 0.88 and AUROC of 0.92 are obtained for detecting cancer in whole slide images.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 10 references that are in the map. First posted on arXiv 22 Aug 2024.

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References · 1

  1. 2018Micro-Net: A unified model for segmentation of various objects in microscopy imagescited by 56

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