Work

TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs

Year: 2024

Type: article

Source: Medical Image Analysis

DOI: 10.1016/j.media.2024.103373

Authors: Fan Wang, Zhilin Zou, Nicole Sakla, Luke Partyka, Nil Rawal, Gagandeep Singh, Wei Zhao, Haibin Ling, Chuan Huang, Prateek Prasanna, Chao Chen

Institutions: State University of New York, Stony Brook University, Newark Beth Israel Medical Center, Columbia University Irving Medical Center, Georgia Institute of Technology, Emory University

Language: English

Topic: MRI in cancer diagnosis

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: bronze

Funders: National Science Foundation, National Institutes of Health, National Cancer Institute, National Institute of Neurological Disorders and Stroke, Division of Information and Intelligent Systems

Awards: RI:Small: Improve Visual Tracking by Large Scale Learning, Diagnosis, and Evaluation, G1147993643, G1525668854, Early Treatment Response Detection Using Highly Accurate and Reliable Breast Density Measure Derived From MRI, G2872097602, Collaborative Research: RI: Small: Shape Configuration Learning and Its Applications, Computerized platform for interactive annotation and topological characterization of tumor associated vasculature for predicting response to immunotherapy in lung cancer, G3600941176, G5104926131, SCH: Topological Methods for Breast Tissue Quantification, CAREER: Topology-Driven Learning for Biomedical Imaging Informatics, CRCNS: TopoVess: A Topology-Infomred Vasculature Analysis Platform for Neuroscience

OpenAlex ID: W4403466400

FWCI: 3.554

Cites: 89

Cited by: 14

Related to: 10