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dc.contributor.advisorKawin Setsompop.en_US
dc.contributor.authorIyer, Siddharth(Siddharth Srinivasan)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2019-11-04T19:53:59Z
dc.date.available2019-11-04T19:53:59Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/122700
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 41-42).en_US
dc.description.abstractMagnetic 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.en_US
dc.description.statementofresponsibilityby Siddharth Iyer.en_US
dc.format.extent42 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleRapid time-resolved brain imaging with multiple clinical contrasts using wave-shufflingen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.identifier.oclc1124925088en_US
dc.description.collectionS.M. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienceen_US
dspace.imported2019-11-04T19:53:58Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentEECSen_US


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