IMPROVEMENTS TO THE QUALITY OF MRI CLUSTER-ANALYSIS

Cluster analysis techniques are gaining widespread use for segmentatio n of MRI data, especially for volume measurement and 3-D display purpo ses. This paper describes four improvements to such techniques: (1) Th e use of intensity simulations to model cluster plots; (2) Correction of image nonuniformity; (3) Anisotropic smoothing of data; and (4) Aut omatic isolation of tissues of interest. Simulation of cluster plots a llows an informed choice of pulse sequence(s) and acquisition paramete rs to be made. Correction of image nonuniformity and anisotropic smoot hing reduce the spread of signal intensity from a single tissue thus p roducing significantly more compact clusters, whilst the isolation of tissues of interest prevents overlap of clusters from the tissues of i nterest with those not under consideration. These techniques may be us ed to improve the results of cluster analysis or traded off, for examp le to allow lower signal-to-noise images, shorter repetition time imag es, or fewer images to be used for segmentation.