Brain Image Analysis and Atlas Construction

[Excerpt from the Chapter: (Without Figures; .pdf 338K, 42 pages)
(With Color Figures - 70 pages, please download from here:) [pages 1-5] [pages 6-10] [pages 11-20] [pages 21-30] [pages 31-33] [pages 34-36] [page 37] [page 38] [page 39] [pages 41-50] [pages 51-60] [pages 61-70] [NEW]

Tutorial Book Chapter in: Michael Fitzpatrick, Milan Sonka [eds.],
Handbook of Medical Image Processing and Analysis, SPIE Press, 2000 [in press]

Paul M. Thompson, Michael S. Mega, Katherine L. Narr,
Elizabeth R. Sowell, Rebecca E. Blanton, and Arthur W. Toga

Laboratory of Neuro Imaging, Department of Neurology, Division of Brain Mapping, UCLA School of Medicine, Los Angeles, California 90095

CONTENTS

In this tutorial chapter, we review some exciting developments in the field of brain image analysis and atlas construction. Brain imaging studies are expanding into ever-larger populations, and this enables digital atlases to be developed that synthesize brain data across vast numbers of subjects. Data can also be fused across multiple imaging modalities, to better understand brain structure and function in health and disease. Mathematical algorithms can exploit the data in these population-based atlases to detect pathology in an individual or patient group, to detect group features of anatomy not apparent in an individual, and to uncover powerful linkages between structure and demographic or genetic parameters. These algorithms in turn draw upon developments in the computer vision, pattern recognition, graphics, and statistical research arenas. Above all, the pace of technological development in brain imaging has clearly been matched by the rapid emergence of powerful algorithms for data analysis. The resulting armory of tools shows enormous promise in shedding light on the complex structural and functional organization of the human brain.

To obtain a reprint of our chapter, please send me an e-mail, and I'll be happy to send you a copy!

Key Words: Brain Mapping, image analysis, structure and function, image registration, deformable templates, elastic matching, statistical parametric mapping (SPM), Gaussian random fields, Magnetic Resonance Imaging

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