2026-09-20T00:56:38Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/744552022-01-13T07:54:36Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Alexander Slocum.
Bridgers, Loren Daniel
Massachusetts Institute of Technology. Dept. of Mechanical Engineering.
Massachusetts Institute of Technology. Department of Mechanical Engineering
2012-10-26T18:10:15Z
2012-10-26T18:10:15Z
2012
2012
http://hdl.handle.net/1721.1/74455
813318772
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 78-79).
Magnetic Resonance based architectonic segmentation aims to detect variations in brain architecture that may provide incredible insight into diseases such as epilepsy, schizophrenia, dyslexia, and autism. Data from ex vivo scans is necessary for the development of automatic methods to detect these critical variations in vivo (1) (2). The optimization of ex vivo imaging requires the design and construction of special purpose instrumentation. This thesis presents the mechanical design and construction of a 32 channel ex vivo coil assembly for use in a 7 tesla MRI. The unit will be used for research at the Athinoula A. Martinos Center for Biomedical Imaging in Charlestown, Massachusetts. Also presented is the development and implementation of two unique low-cost tools to enhance the medical instrument prototyping process: a desktop vacuum casting system, and an automatic tool-path generation program for machining directly from STL files. Finally, an improved method and apparatus for degassing the tissue samples is developed and implemented leading to improvements in MRI image quality.
by Loren Daniel Bridgers.
S.M.
88 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Mechanical Engineering.
Design and manufacture of an ultra-high field ex vivo coil assembly
Thesis
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<Abstract>Magnetic Resonance based architectonic segmentation aims to detect variations in brain architecture that may provide incredible insight into diseases such as epilepsy, schizophrenia, dyslexia, and autism. Data from ex vivo scans is necessary for the development of automatic methods to detect these critical variations in vivo (1) (2). The optimization of ex vivo imaging requires the design and construction of special purpose instrumentation. This thesis presents the mechanical design and construction of a 32 channel ex vivo coil assembly for use in a 7 tesla MRI. The unit will be used for research at the Athinoula A. Martinos Center for Biomedical Imaging in Charlestown, Massachusetts. Also presented is the development and implementation of two unique low-cost tools to enhance the medical instrument prototyping process: a desktop vacuum casting system, and an automatic tool-path generation program for machining directly from STL files. Finally, an improved method and apparatus for degassing the tissue samples is developed and implemented leading to improvements in MRI image quality.</Abstract>
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