Multiple instance learning framework with masked hard instance mining for whole slide image classification
The whole slide image (WSI) classification is often formulated as a multiple instance
learning (MIL) problem. Since the positive tissue is only a small fraction of the gigapixel WSI …
learning (MIL) problem. Since the positive tissue is only a small fraction of the gigapixel WSI …
Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning
We address the challenging problem of whole slide image (WSI) classification. WSIs have
very high resolutions and usually lack localized annotations. WSI classification can be cast …
very high resolutions and usually lack localized annotations. WSI classification can be cast …
Exploring low-rank property in multiple instance learning for whole slide image classification
The classification of gigapixel-sized whole slide images (WSIs) with slide-level labels can be
formulated as a multiple-instance-learning (MIL) problem. State-of-the-art models often …
formulated as a multiple-instance-learning (MIL) problem. State-of-the-art models often …
Boosting whole slide image classification from the perspectives of distribution, correlation and magnification
Bag-based multiple instance learning (MIL) methods have become the mainstream for
Whole Slide Image (WSI) classification. However, there are still three important issues that …
Whole Slide Image (WSI) classification. However, there are still three important issues that …
Diagnose like a pathologist: Transformer-enabled hierarchical attention-guided multiple instance learning for whole slide image classification
Multiple Instance Learning (MIL) and transformers are increasingly popular in
histopathology Whole Slide Image (WSI) classification. However, unlike human pathologists …
histopathology Whole Slide Image (WSI) classification. However, unlike human pathologists …
Remix: A general and efficient framework for multiple instance learning based whole slide image classification
Whole slide image (WSI) classification often relies on deep weakly supervised multiple
instance learning (MIL) methods to handle gigapixel resolution images and slide-level …
instance learning (MIL) methods to handle gigapixel resolution images and slide-level …
Dtfd-mil: Double-tier feature distillation multiple instance learning for histopathology whole slide image classification
Multiple instance learning (MIL) has been increasingly used in the classification of
histopathology whole slide images (WSIs). However, MIL approaches for this specific …
histopathology whole slide images (WSIs). However, MIL approaches for this specific …
Rethinking multiple instance learning for whole slide image classification: A good instance classifier is all you need
Weakly supervised whole slide image classification is usually formulated as a multiple
instance learning (MIL) problem, where each slide is treated as a bag, and the patches cut …
instance learning (MIL) problem, where each slide is treated as a bag, and the patches cut …
MuRCL: Multi-instance reinforcement contrastive learning for whole slide image classification
Multi-instance learning (MIL) is widely adop-ted for automatic whole slide image (WSI)
analysis and it usually consists of two stages, ie, instance feature extraction and feature …
analysis and it usually consists of two stages, ie, instance feature extraction and feature …
Transmil: Transformer based correlated multiple instance learning for whole slide image classification
Multiple instance learning (MIL) is a powerful tool to solve the weakly supervised
classification in whole slide image (WSI) based pathology diagnosis. However, the current …
classification in whole slide image (WSI) based pathology diagnosis. However, the current …