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cs.CV2024
HMIL: Hierarchical Multi-Instance Learning for Fine-Grained Whole Slide Image Classification
Cheng Jin, Luyang Luo, Huangjing Lin +2
Fine-grained classification of whole slide images (WSIs) is essential in precision oncology, enabling precise cancer diagnosis and personalized treatment strategies. The core of th…
cs.CV2024
A Multimodal Knowledge-enhanced Whole-slide Pathology Foundation Model
Yingxue Xu, Yihui Wang, Fengtao Zhou +16
Remarkable strides in computational pathology have been made in the task-agnostic foundation model that advances the performance of a wide array of downstream clinical tasks. Despi…
cs.CV2023
Shapley Values-enabled Progressive Pseudo Bag Augmentation for Whole Slide Image Classification
Renao Yan, Qiehe Sun, Cheng Jin +4
In computational pathology, whole-slide image (WSI) classification presents a formidable challenge due to its gigapixel resolution and limited fine-grained annotations. Multiple-in…