Multi‐modal synergistic PET and MR reconstruction using mutually weighted quadratic priors

• Published in: Magnetic resonance in medicine Vol. 81; no. 3; pp. 2120 - 2134
• Main Authors: Mehranian, Abolfazl, Belzunce, Martin A., McGinnity, Colm J., Bustin, Aurelien, Prieto, Claudia, Hammers, Alexander, Reader, Andrew J.
• Format: Journal Article
• Language: English
• Published: United States Wiley Subscription Services, Inc 01.03.2019; John Wiley and Sons Inc
• Subjects: Algorithms; Brain; Brain - diagnostic imaging; Computer Simulation; Contrast Media; Dementia - diagnostic imaging; Fluorodeoxyglucose F18; Full Papers—Computer Processing and Modeling; Gray Matter - diagnostic imaging; Healthy Volunteers; Humans; Image contrast; Image processing; Image Processing, Computer-Assisted - methods; Image quality; Image reconstruction; In vivo methods and tests; Magnetic Resonance Imaging; Models, Statistical; Multi‐modal imaging; Noise reduction; Normal Distribution; PET‐MRI; Phantoms, Imaging; Positron emission; Positron emission tomography; Regularization; Regularization methods; Signal-To-Noise Ratio; synergistic reconstruction; Tomography; Variation; White Matter - diagnostic imaging; PET-MRI; Multi-modal imaging; synergistic reconstruction

Purpose To propose a framework for synergistic reconstruction of PET‐MR and multi‐contrast MR data to improve the image quality obtained from noisy PET data and from undersampled MR data. Theory and Methods Weighted quadratic priors were devised to preserve common boundaries between PET‐MR images wh...