fMRI detection with spatial regularization

Functional Magnetic Resonant Imaging (fMRI) is a non-invasive imaging technique used to study the brain. Neuroscientists have developed various algorithms to determine which voxels of the images are active. Most of these algorithms, operating on the signal of each voxel separately, are referred to as the voxel-by-voxel detectors. Among those voxel-by-voxel detectors, paired T-test and General Linear Model (GLM) are the most popular. The Mutual Information (MI) based detector has recently been introduced. It is interesting to compare these three detectors' modeling assumptions, as well as their performance, in order to understand their advantages and shortcomings. Due to the low signal-to-noise ratio (SNR), the voxel-by-voxel detectors usually result in fragmented activation pattern, which is not in agreement with our understanding of brain activation. The biological models of brain activation suggest that adjacent locations of the brain tend to be in the same activation state. We take advantage of these models and apply a Markov Random Field (MRF) spatial prior to the statistics provided by the voxel-by-voxel algorithms. MRF has been shown to be able to overcome the effect of over-smoothing, which is the major drawback of the conventional spatial regularization models such as the Gaussian smoothing model.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2005

Author dc:creator

• Ou, Wanmei

Advisor dc:contributor.advisor

• Polina Golland.

• Electrical Engineering and Computer Science.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/33856

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/33856