[HTML][HTML] Cross-scale multi-instance learning for pathological image diagnosis
Analyzing high resolution whole slide images (WSIs) with regard to information across
multiple scales poses a significant challenge in digital pathology. Multi-instance learning …
multiple scales poses a significant challenge in digital pathology. Multi-instance learning …
Iib-mil: Integrated instance-level and bag-level multiple instances learning with label disambiguation for pathological image analysis
Digital pathology plays a pivotal role in the diagnosis and interpretation of diseases and has
drawn increasing attention in modern healthcare. Due to the huge gigapixel-level size and …
drawn increasing attention in modern healthcare. Due to the huge gigapixel-level size and …
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 …
Mammil: Multiple instance learning for whole slide images with state space models
Z Fang, Y Wang, Y Zhang, Z Wang, J Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
Recently, pathological diagnosis has achieved superior performance by combining deep
learning models with the multiple instance learning (MIL) framework using whole slide …
learning models with the multiple instance learning (MIL) framework using whole slide …
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 …
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 …
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 …
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 …
DT-MIL: deformable transformer for multi-instance learning on histopathological image
Learning informative representations is crucial for classification and prediction tasks on
histopathological images. Due to the huge image size, whole-slide histopathological image …
histopathological images. Due to the huge image size, whole-slide histopathological image …
Accounting for dependencies in deep learning based multiple instance learning for whole slide imaging
Multiple instance learning (MIL) is a key algorithm for classification of whole slide images
(WSI). Histology WSIs can have billions of pixels, which create enormous computational and …
(WSI). Histology WSIs can have billions of pixels, which create enormous computational and …