Purely optical tomography : atlas-based reconstruction of brain activation

Diffuse Optical Tomography (DOT) is a relatively new method used to image blood volume and oxygen saturation in vivo. Because of its relatively poor spatial resolution (typically no better than 1-2 cm), DOT is increasingly combined with other imaging techniques, such as MRI, fMRI and CT, which provide high-resolution structural information to guide the characterization of the unique physiological information offered by DOT. This work aims at improving DOT by offering new strategies for a more accurate, efficient, and faster image processor. Specifically, after investigating the influence of Cerebral Spinal Fluid (CSF) properties on the optical measurements, we propose using a realistic segmented head model that includes a novel CSF segmentation approach for a more accurate solution of the DOT forward problem. Moreover, we outline the benefits and applicability of a Diffusion Approximation-based faster forward model solver. We also describe a new registration algorithm based on superficial landmarks which is an essential tool for the purely optical tomographic image process proposed here. A purely optical tomography of the brain during neural activity will greatly enhance DOT applicability and provide many advantages, in the sense that DOT low cost, portability and non-invasiveness would be fully exploited without the compromises due to the MRI role in the DOT forward image process. We achieve a purely optical tomography by using a generalized head model (or atlas) in place of the subject specific anatomical MRI. We validate the proposed imaging protocol by comparing measurements derived from the DOT forward problem solution obtained using the subject specific anatomical model versus these acquired using the atlas registered to the subject, using a database of 31 healthy human. subjects, and focusing on a set of 12 functional regions of interest.

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

2008

Author dc:creator

• Custo, Anna

Advisor dc:contributor.advisor

• W. Eric L. Grimson and William M. Wells, III.

• 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/1721.1/44446

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/44446