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Deep Learning for Coronary Stenosis Detection in Heavily Calcified Plaques at Coronary CT Angiography: A Stepwise, Multicenter Study

Year: 2025

Type: article

Abstract: The proposed deep learning model automatically quantified coronary luminal stenosis in patients with heavily calcified plaques at coronary CT angiography and improved radiologists’ diagnostic performance.

Source: Radiology Artificial Intelligence

DOI: 10.1148/ryai.250109

Authors: Rui Wang, Siwen Wang, LiBo Zhang, U. Joseph Schoepf, Fandong Zhang, Wei Chen, Zhen Zhou, Zhe Fang, Bin Hu, Yizhou Yu, Jiayin Zhang, Ximing Wang, Longjiang Zhang, Lei Xu

Institutions: Capital Medical University, Beijing Anzhen Hospital, Southern Medical University, Medical University of South Carolina, University of Hong Kong, Shanghai Jiao Tong University, Shanghai First People's Hospital, Shandong Provincial Hospital, Shandong First Medical University

Language: English

Topic: Cardiac Imaging and Diagnostics

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Funders: National Natural Science Foundation of China, Natural Science Foundation of Beijing Municipality, Beijing Municipal Administration of Hospitals, National Key Research and Development Program of China

Awards: G104504094, G4813441660, G6767715092, G7925468688

OpenAlex ID: W4417433251

FWCI: 0.529

Cites: 31

Cited by: 1

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