Paul Thompson's Research Publications

Anatomically-Driven Strategies for High-Dimensional Brain Image Warping and Pathology Detection

Book Chapter in: A.W. Toga [ed.],
Brain Warping, Academic Press
, [in press]

Paul M. Thompson and Arthur W. Toga

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



Human brain structure is so complex and variable across subjects that engineering approaches drawn from computer vision, image analysis, computer graphics and artificial intelligence research fields are required to manipulate, analyze and communicate brain data.

In this chapter, we review current neuroimaging methods for brain image registration and computerized pathology detection. In these approaches, computer vision algorithms and statistical pattern recognition measures are integrated with anatomically-driven elastic transformations which encode complex shape differences between systems of anatomic surfaces. Image warping algorithms are central to all of these tasks. Warping algorithms can help to integrate brain data from many subjects, and to obtain objective criteria for conditions such as global or regional cerebral atrophy, as well as the gyral and sulcal anomalies specific to certain disease states.

Without the power that brain image warping provides to integrate brain data from many subjects and sources, the correlative potential of the many diverse brain mapping approaches would be underexploited. One of the most promising applications of warping algorithms is their use as a virtual sensor (Gee et al., 1993; Thompson and Toga, 1998), creating exquisitely detailed maps of anatomic differences. Maps of anatomical change can also be generated by warping scans acquired from the same subject over time (Thompson et al., 1998; Thirion et al., 1998). A 4-dimensional approach to modeling brain structure (Toga et al., 1996; Thompson et al., 1998) can provide information on local patterns and rates of tissue growth, atrophy, shearing and dilation, and in the future will enable disease and growth processes to be tracked in their full spatial and temporal complexity.

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, 3D, image registration, deformable templates, elastic matching, Magnetic Resonance Imaging

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    Paul Thompson
    73-360 Brain Research Institute
    UCLA Medical Center
    10833 Le Conte Avenue
    Westwood, Los Angeles CA 90095-1761, USA.

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