390 citations · 541 across the 25 of their papers we have counts for
8 papers · 1 filter
Precise Location Matching Improves Dense Contrastive Learning in Digital Pathology
Jingwei Zhang, Saarthak Kapse, Ke Ma +4
Dense prediction tasks such as segmentation and detection of pathological entities hold crucial clinical value in computational pathology workflows. However, obtaining dense annota…
Learning Topological Interactions for Multi-Class Medical Image Segmentation
Saumya Gupta, Xiaoling Hu, James Kaan +10
Deep learning methods have achieved impressive performance for multi-class medical image segmentation. However, they are limited in their ability to encode topological interactions…
Gigapixel Whole-Slide Images Classification using Locally Supervised Learning
Jingwei Zhang, Xin Zhang, Ke Ma +4
Histopathology whole slide images (WSIs) play a very important role in clinical studies and serve as the gold standard for many cancer diagnoses. However, generating automatic tool…
AI and Pathology: Steering Treatment and Predicting Outcomes
Rajarsi Gupta, Jakub Kaczmarzyk, Soma Kobayashi +2
The combination of data analysis methods, increasing computing capacity, and improved sensors enable quantitative granular, multi-scale, cell-based analyses. We describe the rich s…
Evaluating histopathology transfer learning with ChampKit
Jakub R. Kaczmarzyk, Tahsin M. Kurc, Shahira Abousamra +3
Histopathology remains the gold standard for diagnosis of various cancers. Recent advances in computer vision, specifically deep learning, have facilitated the analysis of histopat…
A Novel Framework for Characterization of Tumor-Immune Spatial Relationships in Tumor Microenvironment
Mahmudul Hasan, Jakub R. Kaczmarzyk, David Paredes +9
Understanding the impact of tumor biology on the composition of nearby cells often requires characterizing the impact of biologically distinct tumor regions. Biomarkers have been d…
Federated Learning Enables Big Data for Rare Cancer Boundary Detection
Sarthak Pati, Ujjwal Baid, Brandon Edwards +276
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data. This is currently addressed by centrally shar…
Visual attention analysis of pathologists examining whole slide images of Prostate cancer
Souradeep Chakraborty, Ke Ma, Rajarsi Gupta +4
We study the attention of pathologists as they examine whole-slide images (WSIs) of prostate cancer tissue using a digital microscope. To the best of our knowledge, our study is th…