Name
Abstract | ||
|---|---|---|
Alzheimer disease is a neurodegenerative disorder that impairs memory, cognitive function, and gradually leads to dementia, physical deterioration, loss of independence, and death of the affected individual. In this context, segmentation of medical images is a very important technique in the field of image analysis and Computer-Assisted Diagnosis. In this article, we introduce a new automatic method of brain images' segmentation based on the Active Contour AC model to extract the Hippocampus and the Corpus Callosum CC. Our contribution is to combine the geometric method with the statistical method of the AC. We used the Caselle Level Set and added a learning phase to build an average shape and to make the initialization task automatic. For the step of contour evolution, we used the principle of Level set and we added to it the a priori knowledge. Experimental results are very promising. © 2017 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 27, 3-11, 2017 |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1002/ima.22205 | Int. J. Imaging Systems and Technology |
Keywords | Field | DocType |
Alzheimer disease, computer-assisted diagnosis, hippo-campus, corpus callosum, active contour | Active contour model,Computer vision,Brain mri,Segmentation,Computer science,A priori and a posteriori,Level set,Artificial intelligence,Initialization,Cognition,Corpus callosum | Journal |
Volume | Issue | ISSN |
27 | 1 | 0899-9457 |
Citations | PageRank | References |
2 | 0.43 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amira Ben Rabeh | 1 | 2 | 0.43 |
| Faouzi Benzarti | 2 | 15 | 8.94 |
| Hamid Amiri | 3 | 86 | 19.36 |