2024
A deep learning-based approach to nuisance signal removal from MRSI data aqcuired without suppression
Lee W, Zhuo Y, Marin T, Han P, Chi D, Fakhri G, Ma C. A deep learning-based approach to nuisance signal removal from MRSI data aqcuired without suppression. Proceedings Of The International Society For Magnetic Resonance In Medicine ... Scientific Meeting And Exhibition. 2024 DOI: 10.58530/2024/0259.Peer-Reviewed Original ResearchDeep learning-based methodsLearning-based methodsU-Net structureSignal removalIn vivo MRSI dataNeural networkU-NetMRSI dataImage reconstructionSuperior performanceData processingRobust performanceHankel matrixNetworkNuisance signalsConventional methodsPerformanceMRSI signalsSignalMethodRemove nuisance signalsRemovalHankel
2015
Removal of nuisance signals from limited and sparse 1H MRSI data using a union‐of‐subspaces model
Ma C, Lam F, Johnson C, Liang Z. Removal of nuisance signals from limited and sparse 1H MRSI data using a union‐of‐subspaces model. Magnetic Resonance In Medicine 2015, 75: 488-497. PMID: 25762370, PMCID: PMC4567537, DOI: 10.1002/mrm.25635.Peer-Reviewed Original Research