2026-09-18T21:14:24Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1227002021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Kawin Setsompop.
Iyer, Siddharth(Siddharth Srinivasan)
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2019-11-04T19:53:59Z
2019-11-04T19:53:59Z
2019
2019
https://hdl.handle.net/1721.1/122700
1124925088
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 41-42).
Magnetic Resonance Imaging (MRI) is a non-invasive but slow biomedical imaging modality that produces images of multiple desirable contrasts. Currently, multiple receive channels are used in MRI to exploit redundancy and sample fewer data points for faster acquisition. Wave-CAIPI is a recently introduced technique that modifies the acquisition scheme in a manner that improves the effectiveness of the receive channels, allowing for higher rates of acceleration. In this work, the principle behind Wave-CAIPI is applied to a compressed-sensing technique called Shuffling. In Shuffling, the spatial and temporal axis are randomly sampled and the data is reconstructed with temporal subspace constraints, yielding a time-series of images with desirable contrast. Combining Wave-CAIPI and Shuffling achieves rapid, time-resolved imaging of brain at 1mm-isotropic spatial resolution in clinically feasible times.
by Siddharth Iyer.
S.M.
S.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science
42 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Rapid time-resolved brain imaging with multiple clinical contrasts using wave-shuffling
Thesis
application/pdf
2019-11-04T19:53:58Z
Publication
Master
EECS
unknown
unknown
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<Abstract>Magnetic Resonance Imaging (MRI) is a non-invasive but slow biomedical imaging modality that produces images of multiple desirable contrasts. Currently, multiple receive channels are used in MRI to exploit redundancy and sample fewer data points for faster acquisition. Wave-CAIPI is a recently introduced technique that modifies the acquisition scheme in a manner that improves the effectiveness of the receive channels, allowing for higher rates of acceleration. In this work, the principle behind Wave-CAIPI is applied to a compressed-sensing technique called Shuffling. In Shuffling, the spatial and temporal axis are randomly sampled and the data is reconstructed with temporal subspace constraints, yielding a time-series of images with desirable contrast. Combining Wave-CAIPI and Shuffling achieves rapid, time-resolved imaging of brain at 1mm-isotropic spatial resolution in clinically feasible times.</Abstract>
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