Transcriptomics-guided slide representation learning in computational pathology
G Jaume, L Oldenburg, A Vaidya… - Proceedings of the …, 2024 - openaccess.thecvf.com
Self-supervised learning (SSL) has been successful in building patch embeddings of small
histology images (eg 224 x 224 pixels) but scaling these models to learn slide embeddings …
histology images (eg 224 x 224 pixels) but scaling these models to learn slide embeddings …
Generalizable Whole Slide Image Classification with Fine-Grained Visual-Semantic Interaction
Abstract Whole Slide Image (WSI) classification is often formulated as a Multiple Instance
Learning (MIL) problem. Recently Vision-Language Models (VLMs) have demonstrated …
Learning (MIL) problem. Recently Vision-Language Models (VLMs) have demonstrated …
Attention-challenging multiple instance learning for whole slide image classification
Overfitting remains a significant challenge in the application of Multiple Instance Learning
(MIL) methods for Whole Slide Image (WSI) analysis. Visualizing heatmaps reveals that …
(MIL) methods for Whole Slide Image (WSI) analysis. Visualizing heatmaps reveals that …
XFibrosis: Explicit Vessel-Fiber Modeling for Fibrosis Staging from Liver Pathology Images
The increasing prevalence of non-alcoholic fatty liver disease (NAFLD) has caused public
concern in recent years. The high prevalence and risk of severe complications make …
concern in recent years. The high prevalence and risk of severe complications make …
Image distillation for safe data sharing in histopathology
Histopathology can help clinicians make accurate diagnoses, determine disease prognosis,
and plan appropriate treatment strategies. As deep learning techniques prove successful in …
and plan appropriate treatment strategies. As deep learning techniques prove successful in …
DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification
Multiple instance learning (MIL) stands as a powerful approach in weakly supervised
learning, regularly employed in histological whole slide image (WSI) classification for …
learning, regularly employed in histological whole slide image (WSI) classification for …
Prompting Whole Slide Image Based Genetic Biomarker Prediction
L Zhang, B Yun, X Xie, Q Li, X Li, Y Wang - International Conference on …, 2024 - Springer
Prediction of genetic biomarkers, eg, microsatellite instability and BRAF in colorectal cancer
is crucial for clinical decision making. In this paper, we propose a whole slide image (WSI) …
is crucial for clinical decision making. In this paper, we propose a whole slide image (WSI) …
Norma: A Noise Robust Memory-Augmented Framework for Whole Slide Image Classification
In recent years, the Whole Slide Image (WSI) classification task has achieved great
advancement due to the success of Multiple Instance Learning (MIL). However, the MIL …
advancement due to the success of Multiple Instance Learning (MIL). However, the MIL …
Preoperative Molecular Subtype Classification Prediction of Ovarian Cancer Based on Multi-Parametric Magnetic Resonance Imaging Multi-Sequence Feature Fusion …
In the study of the deep learning classification of medical images, deep learning models are
applied to analyze images, aiming to achieve the goals of assisting diagnosis and …
applied to analyze images, aiming to achieve the goals of assisting diagnosis and …
Towards Efficient Information Fusion: Concentric Dual Fusion Attention Based Multiple Instance Learning for Whole Slide Images
Y Liu, R Wu, X Shen, Z Lu, L Liang, H Zhou… - arXiv preprint arXiv …, 2024 - arxiv.org
In the realm of digital pathology, multi-magnification Multiple Instance Learning (multi-mag
MIL) has proven effective in leveraging the hierarchical structure of Whole Slide Images …
MIL) has proven effective in leveraging the hierarchical structure of Whole Slide Images …