Three Dimensional MR-Based Morphometric Comparison of Schizophrenic and Normal Cerebral Ventricles
VBC '96 Proceedings of the 4th International Conference on Visualization in Biomedical Computing
Harvard brain atlas: a teaching and visualization tool
BIOMEDVIS '95 Proceedings of the 1995 Biomedical Visualization (BioMedVis '95)
3-d deformable registration using a statistical atlas with applications in medicine
3-d deformable registration using a statistical atlas with applications in medicine
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Journal of Cognitive Neuroscience
Automatic Segmentation of Brain Structures Based on Anatomic Atlas
ISDA '07 Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications
Combining approaches for early diagnosis of breast diseases using thermal imaging
International Journal of Innovative Computing and Applications
Segmentation of mice cerebral structures: application in Trisomy 21
International Journal of Innovative Computing and Applications
Hi-index | 0.00 |
The availability of modern computational techniques and advanced medical imaging protocols has increased the development of computer-aided diagnosis systems. This paper presents a fully automated brain structures segmentation algorithm for magnetic resonance (MR) images. Automated mechanisms reduce the excessive time consumed on manual segmentation and standardise the volumetric acquisition method. The proposed computational image segmentation method is based on a voxel-wise morphometry method, named voxel-based morphometry (VBM). The brain structure of interest of this paper is the hippocampus, a medial temporal lobe structure, precociously affected in Alzheimer's disease (AD), which represents the most common cause of dementia worldwide. We evaluated 371 subjects from OASIS database, including normal controls and probable Alzheimer's patients, splitting them in different age groups. Segmentation results demonstrated that grey matter and hippocampus volumes decrease in both groups proportionally to aging and it is more evident in AD subjects.