![Sample our Mathematics & Statistics journals, sign in here to start your FREE access for 14 days]({"type":"image" , "src" : "/sda/5943/TOC-Subject-Sample-2021-Mathematics-Statistics.jpg"})
ABSTRACT
Hippocampus segmentation in MR images is beneficial for the diagnosis of many diseases and pathologies such as Alzheimer’s disease. Manual segmentation of the hippocampus is highly time-consuming and has low reproducibility; however, automated methods have introduced substantial gains in this regard. In this study, we used a novel level-set method for hippocampus segmentation in combination with the SBGFRLS (Selective Binary and Gaussian Filtering Regularised Level Set) and LAC (Localising Region-Based Active Contours) algorithms. The proposed method avoided the algorithms which required a large database and instead used a more complex level set approach to obtain comparable accuracy. This method was applied to a set of 36 MRI scans provided by the Alzheimer’s Disease Neuroimaging Initiative (ADNI), using the Harmonised Hippocampal Protocol (HarP) as the gold standard. In addition, the results were compared with the outputs of the Freesurfer software package. In regards to the similarity indices, the results of our algorithm (mean Dice = 0.847) were more comparable with the gold standard compared to those of Freesurfer. Classification results for AD vs control and MCI vs control showed a high degree of accuracy (91% and 75%, respectively). Therefore, this method can be an option for accurate and robust segmentation of the hippocampus.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Notes on contributors
Nazanin Safavian
Nazanin Safavian has MSc in Biomedical engineering and she is a researcher in Neuroimaging and Analysis Group (NIAG), with her main expertise in the field of Neuroimaging and image processing.
Seyed Amir Hossein Batouli
Seyed Amir Hossein Batouli is an assistant Professor, with his main expertise in the field of Neuroimaging.
Mohammad Ali Oghabian
Dr. Mohammad Ali Oghabian is a full Professor of Medical Physics and a member of Scientific Board, Tehran University of Medical Sciences. He is also head of Neuroimaging and Analysis Group (NIAG), and also Biomarker imaging Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences.