Automatic 3-D segmentation of internal structures of the head in MR images using a combination of similarity and free-form transformations: Part II, validation on severely atrophied brains.

Studies aimed at quantifying neuroanatomical differences between populations require the volume measurements of individual brain structures. If the study contains a large number of images, manual segmentation is not practical. This study tests the hypothesis that a fully automatic, atlas-based segmentation method can be used to quantify atrophy indexes derived from the brain and cerebellum volumes in normal subjects and chronic alcoholics. This is accomplished by registering an atlas volume with a subject volume, first using a global transformation, and then improving the registration using a local transformation. Segmented structures in the atlas volume are then mapped to the corresponding structures in the subject volume using the combined global and local transformations. This technique has been applied to seven normal and seven alcoholic subjects. Three magnetic resonance volumes were obtained for each subject and each volume was segmented automatically, using the atlas-based method. Accuracy was assessed by manually segmenting regions and measuring the similarity between corresponding regions obtained automatically. Repeatability was determined by comparing volume measurements of segmented structures from each acquisition of the same subject. Results demonstrate that the method is accurate, that the results are repeatable, and that it can provide a method for automatic quantification of brain atrophy, even when the degree of atrophy is large.

Image-guided MR spectroscopy volume of interest localization for longitudinal studies.

Longitudinal magnetic resonance spectroscopy (MRS) studies require accurate repositioning of the volume of interest (VOI) over which measurements are made. In this work we present and evaluate a method for the image-guided repositioning of brain volumes of interest. The point-based registration technique we developed allows the repositioning to be performed on-line (i.e. while the patient is in the scanner). MR image volumes were acquired from six subjects, three scans each over the course of a month. During the first scan, two spectroscopy VOIs are visually selected: one in the frontal white matter, the other in the superior cerebellar vermis. The coordinates of 13 internal brain landmarks are also identified. During both subsequent scans, the same 13 landmarks are identified, and the transformation that registers the first set of landmarks to the subsequent set is computed. This result is used to automatically map the position of the spectroscopy VOIs from the first volume to the current volume. For the six subjects evaluated to date, we show an average repositioning error of the spectroscopy VOIs in the order of 1 mm. This accuracy allows us to conclude that any variations in the MR spectra are unlikely to be due to repositioning error.