Fast, reliable and easy-to-use methods to quantify brain atrophy are of increasing importance in clinical studies on neuro-degenerative diseases. Here, ILAB 4, a new volumetry software that uses a fast semi-automated 3D segmentation of thin-slice T1-weighted 3D MR images based on a modified watershed transform and an automatic histogram analysis was evaluated. It provides the cerebral volumes: whole brain, white matter, gray matter and intracranial cavity. Inter- and intra-rater reliability and scan-rescan reproducibility were excellent in measuring whole brain volumes (coefficients of variation below 0.5%) of volunteers and patients. However, gray and white matter volumes were more susceptible to image quality. High accuracy of the absolute volume results (+/-5 ml) were shown by phantom and preparation measurements. Analysis times were 6 min for processing of 128 slices. The proposed technique is reliable and highly suitable for quantitative studies of brain atrophy, e.g., in multiple sclerosis.

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In this paper we describe a new algorithm for nonrigid registration of brain images based on an elastically deformable model. The use of registration methods has become an important tool for computer-assisted diagnosis and surgery. Our goal was to improve analysis in various applications of neurology and neurosurgery by improving nonrigid registration. A local gray level similarity measure is used to make an initial sparse displacement field estimate. The field is initially estimated at locations determined by local features, and then a linear elastic model is used to infer the volumetric deformation across the image. The associated partial differential equation is solved by a finite element approach. A model of empirically observed variability of the brain was created from a dataset of 154 young adults. Both homogeneous and inhomogeneous elasticity models were compared. The algorithm has been applied to medical applications including intraoperative images of neurosurgery showing brain shift and a study of gait and balance disorder.