Performance evaluation of deep learning-based post-processing and diagnostic reporting system for coronary CT angiography: a clinical comparative study.

Author: Nan LUO ¹ ; Yi HE ¹ ; Jitao FAN ² ; Ning GUO ² ; Guang YANG ² ; Yuanyuan KONG ³ ; Jianyong WEI ² ; Tao BI ⁴ ; Jie ZHOU ⁴ ; Jiaxin CAO ¹ ; Xianjun HAN ¹ ; Fang LI ⁵ ; Shiyu ZHANG ¹ ; Rujing SUN ¹ ; Zhaozhao WANG ¹ ; Tian MA ¹ ; Lixue XU ¹ ; Hui CHEN ⁶ ; Hongwei LI ⁶ ; Zhenchang WANG ¹ ; Zhenghan YANG ¹
Author Information

1. Department of Radiology, Beijing Friendship Hospital of Capital Medical University, Beijing 100050, China.
2. Shukun (Beijing) Technology Company Ltd., Beijing 100102, China.
3. Statistics Section, Beijing Friendship Hospital of Capital Medical University, Beijing 100050, China.
4. Department of Radiology, Beijing Anzhen Hospital of Capital Medical University, Beijing 100011, China.
5. Department of Radiology, Beijing Chest Hospital of Capital Medical University, Beijing 100010, China.
6. Department of Cardiology, Beijing Friendship Hospital of Capital Medical University, Beijing 100050, China.
Publication Type:Journal Article
MeSH: Humans; Computed Tomography Angiography; Deep Learning; Coronary Angiography; Coronary Artery Disease; Tomography, X-Ray Computed; Coronary Stenosis/diagnosis*; Retrospective Studies; Fractional Flow Reserve, Myocardial; Predictive Value of Tests
From: Chinese Medical Journal 2022;135(19):2366-2368
CountryChina
Language:English