Rapid 3D breath-hold MR cholangiopancreatography using deep learning-constrained compressed sensing reconstruction.

Yu ZhangWanlin PengYi XiaoYue MingKehang MaSixian HuWen ZengLingming ZengZejun LiangXiaoyong ZhangChunchao XiaZhen-Lin Li

Published in: European radiology (2022)

• 3D breath-hold MRCP with deep learning reconstruction (3D DL-CS-MRCP) demonstrated improved image quality compared with that of 3D MRCP with compressed sensing or GRASE. • Compared with 2D MRCP, 3D DL-CS-MRCP had superior performance in SNR and CNR, better visualization of the left second-level intrahepatic bile ducts, and comparable overall image quality, but an inferior main pancreatic duct.

Keyphrases

image quality
deep learning
computed tomography
dual energy
artificial intelligence
convolutional neural network
machine learning
magnetic resonance imaging