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Showing 501–525 of 745 papers

TitleStatusHype
BACH: Grand Challenge on Breast Cancer Histology Images—0
Balancing Privacy and Progress in Artificial Intelligence: Anonymization in Histopathology for Biomedical Research and Education—0
Rapid Artefact Removal and H&E-Stained Tissue Segmentation—0
BEL: A Bag Embedding Loss for Transformer enhances Multiple Instance Whole Slide Image Classification—0
Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise—0
Benchmarking Hierarchical Image Pyramid Transformer for the classification of colon biopsies and polyps in histopathology images—0
Benchmarking Histopathology Foundation Models for Ovarian Cancer Bevacizumab Treatment Response Prediction from Whole Slide Images—0
Beyond Classification: Whole Slide Tissue Histopathology Analysis By End-To-End Part Learning—0
Boosted EfficientNet: Detection of Lymph Node Metastases in Breast Cancer Using Convolutional Neural Network—0
BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images—0
Breast Cancer Molecular Subtypes Prediction on Pathological Images with Discriminative Patch Selecting and Multi-Instance Learning—0
Breast Tumor Cellularity Assessment using Deep Neural Networks—0
C2P-GCN: Cell-to-Patch Graph Convolutional Network for Colorectal Cancer Grading—0
CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance—0
CARMIL: Context-Aware Regularization on Multiple Instance Learning models for Whole Slide Images—0
Cascaded Cross-Attention Networks for Data-Efficient Whole-Slide Image Classification Using Transformers—0
CeliacNet: Celiac Disease Severity Diagnosis on Duodenal Histopathological Images Using Deep Residual Networks—0
Cell Maps Representation For Lung Adenocarcinoma Growth Patterns Classification In Whole Slide Images—0
CellOMaps: A Compact Representation for Robust Classification of Lung Adenocarcinoma Growth Patterns—0
Characterizing the Interpretability of Attention Maps in Digital Pathology—0
ChatEXAONEPath: An Expert-level Multimodal Large Language Model for Histopathology Using Whole Slide Images—0
CIMIL-CRC: a clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H\&E stained images—0
Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach—0
Classification of histopathology images using ConvNets to detect Lupus Nephritis—0
Classification of Nasopharyngeal Cases using DenseNet Deep Learning Architecture—0
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