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Abstract #2869

Multi-Contrast 3D MR Image Reconstruction from Incomplete Measurements with Spatially Adaptive Priors

Hyunkyung Maeng1, Sugil Kim1,2, Suhyung Park1, Eun ji Lim1, and Jaeseok Park1

1Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea, 2Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea

Magnetic resonance imaging (MRI) is well established as a clinical routine in which multiple sets of data are typically acquired to produce various image contrasts such as T1, T2, FLAIR, etc. Despite the versatile nature of MRI, multi-contrast data acquisition is highly time consuming particularly when 3D encoding is needed. To address this issue, in this work we propose a novel, multi-contrast 3D MR image reconstruction with spatially adaptive priors by exploiting sharable information across the contrast dimension: edge and coil sensitivity maps. The proposed method consists of the following three steps: 1) estimation of edge maps common over all contrasts, 2) estimation of contrast-specific edge maps, and 3) multi-contrast image reconstruction with spatially adaptive, contrast-specific edge priors. In vivo experimental studies show that the proposed method enables T1, T2, and FLAIR 3D isotropic (1mm3) imaging roughly in 5-6 minutes.

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