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PathM3: A Multimodal Multi-Task Multiple Instance Learning Framework for Whole Slide Image Classification and Captioning
March 15, 2024, 4:45 a.m. | Qifeng Zhou, Wenliang Zhong, Yuzhi Guo, Michael Xiao, Hehuan Ma, Junzhou Huang
cs.CV updates on arXiv.org arxiv.org
Abstract: In the field of computational histopathology, both whole slide images (WSIs) and diagnostic captions provide valuable insights for making diagnostic decisions. However, aligning WSIs with diagnostic captions presents a significant challenge. This difficulty arises from two main factors: 1) Gigapixel WSIs are unsuitable for direct input into deep learning models, and the redundancy and correlation among the patches demand more attention; and 2) Authentic WSI diagnostic captions are extremely limited, making it difficult to train …
abstract arxiv captioning captions challenge classification computational cs.ai cs.cv decisions diagnostic framework however image images insights instance making multimodal multiple type
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