Multi-level multiple instance learning with transformer for whole slide image classification
Whole slide image (WSI) refers to a type of high-resolution scanned tissue image, which is
extensively employed in computer-assisted diagnosis (CAD). The extremely high resolution …
extensively employed in computer-assisted diagnosis (CAD). The extremely high resolution …
Tpmil: Trainable prototype enhanced multiple instance learning for whole slide image classification
Digital pathology based on whole slide images (WSIs) plays a key role in cancer diagnosis
and clinical practice. Due to the high resolution of the WSI and the unavailability of patch …
and clinical practice. Due to the high resolution of the WSI and the unavailability of patch …
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 …
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 …
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 …
Retmil: Retentive multiple instance learning for histopathological whole slide image classification
Histopathological whole slide image (WSI) analysis with deep learning has become a
research focus in computational pathology. The current paradigm is mainly based on …
research focus in computational pathology. The current paradigm is mainly based on …
Cluster-to-conquer: A framework for end-to-end multi-instance learning for whole slide image classification
In recent years, the availability of digitized Whole Slide Images (WSIs) has enabled the use
of deep learning-based computer vision techniques for automated disease diagnosis …
of deep learning-based computer vision techniques for automated disease diagnosis …
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 …
Prompt-mil: Boosting multi-instance learning schemes via task-specific prompt tuning
Whole slide image (WSI) classification is a critical task in computational pathology, requiring
the processing of gigapixel-sized images, which is challenging for current deep-learning …
the processing of gigapixel-sized images, which is challenging for current deep-learning …