Towards label-efficient automatic diagnosis and analysis: a comprehensive survey of advanced deep learning-based weakly-supervised, semi-supervised and self …
Histopathological images contain abundant phenotypic information and pathological
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
patterns, which are the gold standards for disease diagnosis and essential for the prediction …
Vision transformers for computational histopathology
Computational histopathology is focused on the automatic analysis of rich phenotypic
information contained in gigabyte whole slide images, aiming at providing cancer patients …
information contained in gigabyte whole slide images, aiming at providing cancer patients …
Bi-directional weakly supervised knowledge distillation for whole slide image classification
Computer-aided pathology diagnosis based on the classification of Whole Slide Image
(WSI) plays an important role in clinical practice, and it is often formulated as a weakly …
(WSI) plays an important role in clinical practice, and it is often formulated as a weakly …
Dgmil: Distribution guided multiple instance learning for whole slide image classification
Abstract Multiple Instance Learning (MIL) is widely used in analyzing histopathological
Whole Slide Images (WSIs). However, existing MIL methods do not explicitly model the data …
Whole Slide Images (WSIs). However, existing MIL methods do not explicitly model the data …
Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential
M Gadermayr, M Tschuchnig - Computerized Medical Imaging and …, 2024 - Elsevier
Digital whole slides images contain an enormous amount of information providing a strong
motivation for the development of automated image analysis tools. Particularly deep neural …
motivation for the development of automated image analysis tools. Particularly deep neural …
Differentiable zooming for multiple instance learning on whole-slide images
Abstract Multiple Instance Learning (MIL) methods have become increasingly popular for
classifying gigapixel-sized Whole-Slide Images (WSIs) in digital pathology. Most MIL …
classifying gigapixel-sized Whole-Slide Images (WSIs) in digital pathology. Most MIL …
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 …
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 …
Rtn: Reinforced transformer network for coronary ct angiography vessel-level image quality assessment
Abstract Coronary CT Angiography (CCTA) is susceptible to various distortions (eg, artifacts
and noise), which severely compromise the exact diagnosis of cardiovascular diseases. The …
and noise), which severely compromise the exact diagnosis of cardiovascular diseases. The …
Weakly supervised joint whole-slide segmentation and classification in prostate cancer
The identification and segmentation of histological regions of interest can provide significant
support to pathologists in their diagnostic tasks. However, segmentation methods are …
support to pathologists in their diagnostic tasks. However, segmentation methods are …