Surface simplification for shape measurement: application to the human brain

Andy Castellano Smith; Derek L.G. Hill; David John Hawkes; C. E. Polkey; T. C.S. Cox

doi:10.1117/12.310943

24 June 1998 Surface simplification for shape measurement: application to the human brain

Andy Castellano Smith, Derek L.G. Hill, David John Hawkes, C. E. Polkey, T. C.S. Cox

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310943
Event: Medical Imaging '98, 1998, San Diego, CA, United States

Abstract

Studies of shape, degree of folding and variability of the surface of the brain can be found as early as 1967. Measuring shape and degree of folding from radiological images is, however, a relatively recent development. Our objective is to develop a framework for the study of the shape and geometric properties of the brain surface from radiological images for the purposes of studying abnormalities of cortical folding. The construction of an explicit surface model allows the calculation of local measures of intrinsic curvature and folding, and provides a means of studying connectivity and shape variation. To speed up these calculations, we have developed a surface simplification method for discrete data representing surfaces derived from MR images. This method facilitates the calculation of these measures of interest while preserving the essential features of the surface in high curvature regions.

Citation Download Citation

Andy Castellano Smith, Derek L.G. Hill, David John Hawkes, C. E. Polkey, and T. C.S. Cox "Surface simplification for shape measurement: application to the human brain", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310943

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