Neuroanatomical Segmentation in MRI: Technological Objectives

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Abstract
This paper offers a definition of precise, comprehensive, robust and practical neuroanatomical segmentation in magnetic resonance brain images with the goal of performing quantitative morphometric analyses. The main types of difficulties experienced with such problems are described, including those relating to the classification of MR signal intensities and the fact that there is insufficient information in the 2D image. To illustrate the details of obtaining a morphometric description, a case study of semi-automated methods is presented for segmenting the lateral ventricles and caudate nucleus in T1 coronal MR image data. The most significant remaining difficulties are summarized and are offered as objectives for further research.

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