Panda-T1ρ: Integrating principal component analysis and dictionary learning for fast T1ρ mapping

Magnetic Resonance in Medicine

Volumn 73, Issue 1, 2015, Pages 263-272

  Zhu, Yanjie ^a,b   Zhang, Qinwei ^c   Liu, Qiegen ^a,b,d   Wang, Yi Xiang J ^c   Liu, Xin ^a,b   Zheng, Hairong ^a   Liang, Dong ^a,b   Yuan, Jing ^c  

^a SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY   (China)

^b Shenzhen Key Laboratory for Exascale Engineering and Scientific Computing   (China)

^c CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^d NANCHANG UNIVERSITY   (China)

Author keywords

Compressed sensing; Dictionary learning; PCA; T1 imaging

Indexed keywords

COMPRESSED SENSING; IMAGE RECONSTRUCTION; SOLDERED JOINTS;

ACCELERATING FACTORS; ACCELERATION FACTORS; DICTIONARY LEARNING; IN-VIVO EXPERIMENTS; ROTATING FRAME; SCANNING TIME; STATE-OF-ART METHODS; UNDER-SAMPLED;

LEARNING SYSTEMS;

ARTICLE; DICTIONARY LEARNING; IMAGE RECONSTRUCTION; IMAGING PHANTOM; LEARNING; PRINCIPAL COMPONENT ANALYSIS; SIGNAL NOISE RATIO; SIMULATION; ALGORITHM; ANATOMY AND HISTOLOGY; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; MACHINE LEARNING; NUCLEAR MAGNETIC RESONANCE IMAGING; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SPINAL CORD; STATISTICAL ANALYSIS; STATISTICAL MODEL; SYSTEM ANALYSIS;

ALGORITHMS; BRAIN; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MACHINE LEARNING; MAGNETIC RESONANCE IMAGING; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPINAL CORD; SUBTRACTION TECHNIQUE; SYSTEMS INTEGRATION;

EID: 84919875531     PISSN: 07403194     EISSN: 15222594     Source Type: Journal    
DOI: 10.1002/mrm.25130     Document Type: Article

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