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08/29/2023
A General-Purpose Self-Supervised Model for Computational Pathology
Tissue phenotyping is a fundamental computational pathology (CPath) task...
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07/27/2023
Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples
Human tissue and its constituent cells form a microenvironment that is f...
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07/24/2023
Towards a Visual-Language Foundation Model for Computational Pathology
The accelerated adoption of digital pathology and advances in deep learn...
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04/13/2023
Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction
Integrating whole-slide images (WSIs) and bulk transcriptomics for predi...
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01/07/2023
Weakly Supervised Joint Whole-Slide Segmentation and Classification in Prostate Cancer
The segmentation and automatic identification of histological regions of...
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10/31/2022
Embedding Space Augmentation for Weakly Supervised Learning in Whole-Slide Images
Multiple Instance Learning (MIL) is a widely employed framework for lear...
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04/26/2022
Differentiable Zooming for Multiple Instance Learning on Whole-Slide Images
Multiple Instance Learning (MIL) methods have become increasingly popula...
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11/08/2021
BRACS: A Dataset for BReAst Carcinoma Subtyping in H E Histology Images
Breast cancer is the most commonly diagnosed cancer and registers the hi...
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07/21/2021
HistoCartography: A Toolkit for Graph Analytics in Digital Pathology
Advances in entity-graph based analysis of histopathology images have br...
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03/04/2021
Learning Whole-Slide Segmentation from Inexact and Incomplete Labels using Tissue Graphs
Segmenting histology images into diagnostically relevant regions is impe...
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02/22/2021
Hierarchical Cell-to-Tissue Graph Representations for Breast Cancer Subtyping in Digital Pathology
Cancer diagnosis and prognosis for a tissue specimen are heavily influen...
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11/25/2020
Quantifying Explainers of Graph Neural Networks in Computational Pathology
Explainability of deep learning methods is imperative to facilitate thei...
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07/01/2020
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification
Cancer diagnosis, prognosis, and therapeutic response prediction are hea...
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07/01/2020
Towards Explainable Graph Representations in Digital Pathology
Explainability of machine learning (ML) techniques in digital pathology ...
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05/27/2019
FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents
In this paper, we present a new dataset for Form Understanding in Noisy ...
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04/18/2019
edGNN: a Simple and Powerful GNN for Directed Labeled Graphs
The ability of a graph neural network (GNN) to leverage both the graph t...
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11/09/2018