A segmentation-based method incorporating fractional volume analysis for quantification of brain atrophy on magnetic resonance images

摘要

Partial volume effect is a major problem in brain tissue segmentation on digital images such as magnetic resonance (MR) images. In this paper, special attention has been paid to partial volume effect when developing a method for quantifying brain atrophy. Specifically, partial volume effect is minimized in the process of parameter estimation prior to segmentation by identifying and excluding those voxels with possible partial volume effect. A quantitative measure for partial volume effect was also introduced through developing a model that calculates fractional volumes for voxels with mixtures of two different tissues. For quantifying cerebrospinal fluid (CSF) volumes, fractional volumes are calculated for two classes of mixture involving gray matter and CSF, and white matter and CSF. Tissue segmentation is carried out using 1D and 2D thresholding techniques after images are intensity- corrected. Threshold values are estimated using the minimum error method. Morphological processing and region identification analysis are used extensively in the algorithm. As an application, the method was employed for evaluating rates of brain atrophy based on serially acquired structural brain MR images. Consistent and accurate rates of brain atrophy have been obtained for patients with Alzheimer's disease as well as for elderly subjects due to normal aging process.