arXiv:2408.12275
Whole Slide Image Classification of Salivary Gland Tumours
원문 초록
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.
함께 살펴볼 논문
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Adversarial attacks to image classification systems using evolutionary algorithms
GNN-ViTCap: GNN-Enhanced Multiple Instance Learning with Vision Transformers for Whole Slide Image Classification and Captioning
Disentangled representations of microscopy images
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토론
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