OBJECTIVE: A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. METHODS: In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. SIGNIFICANCE: Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. RESULTS: Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset-based experiments, and has yielded promising results.
OBJECTIVE: A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. METHODS: In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. SIGNIFICANCE: Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. RESULTS: Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset-based experiments, and has yielded promising results.
Authors: Christian P Karger; Peter Hipp; Marcus Henze; Gernot Echner; Angelika Höss; Lothar Schad; Günther H Hartmann Journal: Phys Med Biol Date: 2003-01-21 Impact factor: 3.609
Authors: P G. Kluetz; C C. Meltzer; V L. Villemagne; P E. Kinahan; S Chander; M A. Martinelli; D W. Townsend Journal: Clin Positron Imaging Date: 2000-11
Authors: Florian Knoll; Thomas Koesters; Ricardo Otazo; Tobias Block; Li Feng; Kathleen Vunckx; David Faul; Johan Nuyts; Fernando Boada; Daniel K Sodickson Journal: EJNMMI Phys Date: 2014-07