Work

Dynamic Contrast-enhanced MRI for Evaluating Breast Cancer Chemotherapy Response Using Conditional Generative Adversarial Networks

Year: 2025

Type: article

Abstract: Image-to-image conditional generative adversarial network analysis is a promising approach for standardizing pharmacokinetic analysis and reducing computational complexity in dynamic contrast-enhanced MRI modeling.

Source: Radiology Imaging Cancer

DOI: 10.1148/rycan.250110

Authors: Chad A. Arledge, Alan H. Zhao, Umit Topaloglu, Dawen Zhao

Institutions: Wake Forest University Health Sciences, Wake Forest University, University of North Carolina at Chapel Hill, National Institutes of Health, National Cancer Institute

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: diamond

Funders: Comprehensive Cancer Center at Wake Forest Baptist Medical Center, National Institutes of Health

Award: Convertible MRI Contrast Ignaling Delivery and Release of Anti-glioma Nano-drug

OpenAlex ID: W4417043031

FWCI: 0.528

Cites: 30

Cited by: 1

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