Statistical shape model for automatic skull-stripping of brain images
نویسندگان
چکیده
This paper presents a statistical shape model for automatic skull stripping of MR brain images. A surface model of the brain boundary is hierarchically represented by a set of overlapping surface patches, each of which has elastic properties and deformation range that is learned from a training set. The model’s deformation is hierarchical which adds robustness to local minima. Moreover, the deformation of the model is constrained and guided by global shape statistics. The model is deformed to the brain boundary by a procedure that matches the local image structures and evaluates the similarity in the whole patch rather than on a single vertex. The experimental results show high agreement between automatic and supervised skull-stripping results.
منابع مشابه
Skull Stripping of Mri Head Scans Based on Chan-vese Active Contour Model
Whole brain segmentation referred as skull stripping, it is an important process in neuriomage analysis. Automatic segmentation of brain tissues from magnetic resonance images (MRI) remains a challenging task due to variation in shape and size, use of different pulse sequences, overlapping signal intensities and imaging artifacts. Level sets and active contour methods have tremendous potential ...
متن کاملQuantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation
Background: Accurate brain tissue segmentation from magnetic resonance (MR) images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM), ...
متن کاملStatistical morphological skull stripping of adult and infant MRI data
This paper describes a novel automatic statistical morphology skull stripper (SMSS) that uniquely exploits a statistical self-similarity measure and a 2-D brain mask to delineate the brain. The result of applying SMSS to 20 MRI data set volumes, including scans of both adult and infant subjects is also described. Quantitative performance assessment was undertaken with the use of brain masks pro...
متن کاملThe preprocessed connectomes project repository of manually corrected skull-stripped T1-weighted anatomical MRI data
BACKGROUND Skull-stripping is the procedure of removing non-brain tissue from anatomical MRI data. This procedure can be useful for calculating brain volume and for improving the quality of other image processing steps. Developing new skull-stripping algorithms and evaluating their performance requires gold standard data from a variety of different scanners and acquisition methods. We complemen...
متن کاملRobust Skull Stripping of Clinical Glioblastoma Multiforme Data
Skull stripping is the first step in many neuroimaging analyses and its success is critical to all subsequent processing. Methods exist to skull strip brain images without gross deformities, such as those affected by Alzheimer's and Huntington's disease. However, there are no techniques for extracting brains affected by diseases that significantly disturb normal anatomy. Glioblastoma multiforme...
متن کامل