Gabriel Ramos-Llordén1, Rodrigo A. Lobos2, Tae Hyung Kim1, Qiyuan Tian1, Slimane Tounetki1, Thomas Witzel3, Boris Keil4, Anatasia Yendiki1, Berkin Bilgic1,5, Justin P. Haldar2, and Susie Huang1,5
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Masachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, 2Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, 3Q Bio Inc, San Carlos, CA, United States, 4Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Sciences, Giessen, Germany, 5Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Masachusetts General Hospital, Harvard Medical School, Charlestown, MA, United States, 2Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, United States, 3Q Bio Inc, San Carlos, CA, United States, 4Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Sciences, Giessen, Germany, 5Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
Structured Low Rank matrix k-space reconstruction can significantly reduce ghosting artifacts in 3D multi-shot EPI diffusion MRI with high diffusion-encoding gradients, which otherwise persist with conventional reconstruction techniques.
Two representative sagittal slices reconstructed with linear phase correction, SENSE, and LORAKS-based reconstruction. Note the marked ghosting reduction obtained with LORAKS-based k-space reconstruction.
