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- Focus Your Attention: Multiple Instance Learning With Attention . . .
Computer-aided pathology diagnosis based on whole slide images, which is often formulated as a weakly supervised multiple instance learning (MIL) paradigm Curr
- 王润铭团队在计算病理诊断分类任务中取得进展
随着扫描技术的进步，传统病理组织标本已逐步数字化为全切片图像（Whole Slide Image, WSI），这一变革为计算机辅助诊断提供了新的机遇。
- Rethinking Attention-Based Multiple Instance Learning for Whole-Slide . . .
Multiple instance learning (MIL) is a robust paradigm for whole-slide pathological image (WSI) analysis, processing gigapixel-resolution images with slide-level labels
- Pseudo-label attention-based multiple instance learning for whole slide . . .
To address these problems, in this paper, we propose a novel embedding-based MIL technique called pseudo-label attention-based multiple instance learning (PAMIL) PAMIL aggregates each instance’s features regarding their contributions to improving downstream classification performance
- Focus Your Attention: Multiple Instance Learning With Attention . . .
To address these problems, this paper presents a novel MIL framework called FAMIL that focuses on inaccurate attention and refines them FAMIL adopts a dual-branch structure and incorporates two innovative online data augmentation strategies: attention-based Mixup (ABMix) and attention-based Masking (ABMask)
- GitHub - Jiashuai-Liu PAMIL: A repository for Prototype Attention-based . . .
In this paper, we propose a Prototype Attention-based Multiple Instance Learning (PAMIL) method, designed to improve the model's reasoning interpretability without compromising its classification performance at the WSI level
- Focus Your Attention: Multiple Instance Learning with Attention . . .
Focus Your Attention: Multiple Instance Learning with Attention Modification for Whole Slide Pathological Image Classification IEEE Transactions on Circuits and Systems for Video Technology ( IF 11 1 ) Pub Date : 2025-01-13 , DOI: 10 1109 tcsvt 2025 3528625
- Attention-Challenging Multiple Instance Learning for Whole Slide Image . . .
In the application of Multiple Instance Learning (MIL) methods for Whole Slide Image (WSI) classification, attention mechanisms often focus on a subset of discriminative instances, which are closely linked to overfitting
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