Meeting Banner
Abstract #4124

Deep learning based whole heart T2-weighted dark blood imaging in a single breath hold

Xianghu Yan1, Lu Huang1, Lingping Ran1, Yi Luo1, Yuwei Bao1, Shuheng Zhang2, Shiyu Zhang2, Yongquan Ye3, Jian Xu3, and Liming Xia1
1Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, 2United Imaging Healthcare, Shanghai, China, 3UIH America, Inc., Houston, TX, United States


Cardiovascular magnetic resonance (CMR) T2-weighted dark blood (T2W-DB) imaging has great diagnostic value for detecting myocardial edema. In this study, a novel deep learning based acceleration framework (AI-assisted Compressed Sensing, ACS) was applied to a single-shot T2W-DB sequence for single breath-hold whole heart (9 slices) imaging. Both quantitative and qualitative assessment of the images suggested that the ACS T2-DB sequence offered better image quality with greatly reduced total scan time and the simplified scanning workflow.

This abstract and the presentation materials are available to members only; a login is required.

Join Here