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Abstract #1608

Joint reconstruction of multi-TE diffusion MRI acquired using TDM-EPI with complementary k-space sampling

Yang Ji1,2, Congyu Liao3, William Scott Hoge4, Berkin Bilgic5, Yogesh Rathi1,4, and Lipeng Ning1
1Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States, 2Wellcome Centre for Integrative Neuroimaging, FMRIB Division, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom, 3Department of Radiology, Stanford University, Stanford, CA, United States, 4Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, United States, 5Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States


Combined diffusion-relaxometry has demonstrated promising capability to noninvasively probe tissue microstructure by joint modeling of relaxation coefficients and diffusivity. Our recent work has introduced a sequence based on the time-division multiplexing technique to accelerate the acquisition of relaxation-diffusion MRI. In this work, we further developed the TDM-EPI sequence by integrating ky-shifted k-space sampling strategies for data acquired at different TEs. Moreover, we implemented and compared several reconstruction methods to integrate complementary k-space samples to joint estimate images at different TEs. The results showed that the joint reconstruction approach can improve image quality and reduce artifact compared with conventional reconstruction methods.

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