Detecting the brain surface in sparse MRI using boundary models

We introduce a framework for the detection of the brain boundary (arachnoid ) within sparse MRI. We use the term sparse to describe volumetric images i n which the sampling resolution within the imaging plane is far higher than that of the perpendicular direction. Generic boundary detection schemes do not provide good results for such data. In the scheme we propose, the boun dary is extracted using a constrained mesh surface which iteratively approx imates a 3D point set consisting of detected boundary points. Boundary dete ction is based on a database of piecewise constant models, which represent the idealised MR intensity profile of the underlying boundary anatomy. A no n-linear matching scheme is introduced to estimate the location of the boun dary points using only the intensity data within each image plane. Results are shown for a number of images and are discussed in detail. (C) 2000 Else vier Science B.V. All rights reserved.