2026-09-18T23:56:53Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/341102022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
W. Eric L. Grimson and Simon K. Warfield.
Eow, Andy Khai Siang
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-09-28T15:03:42Z
2006-09-28T15:03:42Z
2005
2005
http://hdl.handle.net/1721.1/34110
67617170
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.
Includes bibliographical references (p. 101-103).
For patients with medically refractive focal epilepsy, surgical intervention to remove the epileptic foci is often the last alternative for permanent cure. The success of such surgery is highly dependent on the doctor's ability to accurately locate the epileptogenic region during the pre-surgical planning and evaluation phase. Hence the goal of this project is to provide an end-to-end quantitative analysis pipeline that fuses an array of imaging modalities including magnetic resonance imaging (MRI), diffusion tensor MRI, positron emission tomography (PET), single-photon emission computerized tomography (SPECT) as well as EEG data to build patient-specific head models and to compute prior probability maps of epileptic hotspots for more accurate EEG source localization. By improving the ability to accurately locate these epileptogenic seizure sources, patients can benefit tremendously from accurate surgical resection and consequently have a better chance for complete seizure free recovery.
by Andy Khai Siang Eow.
S.M.
103 p.
5259211 bytes
5263521 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Quantitative multi-modal analysis of pediatric focal epilepsy
Thesis
application/pdf
Publication
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unknown
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<Abstract>For patients with medically refractive focal epilepsy, surgical intervention to remove the epileptic foci is often the last alternative for permanent cure. The success of such surgery is highly dependent on the doctor's ability to accurately locate the epileptogenic region during the pre-surgical planning and evaluation phase. Hence the goal of this project is to provide an end-to-end quantitative analysis pipeline that fuses an array of imaging modalities including magnetic resonance imaging (MRI), diffusion tensor MRI, positron emission tomography (PET), single-photon emission computerized tomography (SPECT) as well as EEG data to build patient-specific head models and to compute prior probability maps of epileptic hotspots for more accurate EEG source localization. By improving the ability to accurately locate these epileptogenic seizure sources, patients can benefit tremendously from accurate surgical resection and consequently have a better chance for complete seizure free recovery.</Abstract>
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