Mambamil: Enhancing long sequence modeling with sequence reordering in computational pathology
Abstract Multiple Instance Learning (MIL) has emerged as a dominant paradigm to extract
discriminative feature representations within Whole Slide Images (WSIs) in computational …
discriminative feature representations within Whole Slide Images (WSIs) in computational …
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 …
Setmil: spatial encoding transformer-based multiple instance learning for pathological image analysis
Considering the huge size of the gigapixel whole slide image (WSI), multiple instance
learning (MIL) is normally employed to address pathological image analysis tasks, where …
learning (MIL) is normally employed to address pathological image analysis tasks, where …
[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 …
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 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 …
Additive mil: Intrinsically interpretable multiple instance learning for pathology
Abstract Multiple Instance Learning (MIL) has been widely applied in pathology towards
solving critical problems such as automating cancer diagnosis and grading, predicting …
solving critical problems such as automating cancer diagnosis and grading, predicting …
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 …
Multiple-instance learning for medical image and video analysis
G Quellec, G Cazuguel, B Cochener… - IEEE reviews in …, 2017 - ieeexplore.ieee.org
Multiple-instance learning (MIL) is a recent machine-learning paradigm that is particularly
well suited to medical image and video analysis (MIVA) tasks. Based solely on class labels …
well suited to medical image and video analysis (MIVA) tasks. Based solely on class labels …
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 …