HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

A comparison of accurate automatic hippocampal segmentation methods

Abstract : The hippocampus is one of the first brain structures affected by Alzheimer's disease (AD). While many automatic methods for hippocampal segmentation exist, few studies have compared them on the same data. In this study, we compare four fully automated hippocampal segmentation methods in terms of their conformity with manual segmentation and their ability to be used as an AD biomarker in clinical settings. We also apply error correction to the four automatic segmentation methods, and complete a comprehensive validation to investigate differences between the methods. The effect size and classification performance is measured for AD versus normal control (NC) groups and for stable mild cognitive impairment (sMCI) versus progressive mild cognitive impairment (pMCI) groups. Our study shows that the nonlinear patch-based segmentation method with error correction is the most accurate automatic segmentation method and yields the most conformity with manual segmentation (κ=0.894 ). The largest effect size between AD versus NC and sMCI versus pMCI is produced by FreeSurfer with error correction. We further show that, using only hippocampal volume, age, and sex as features, the area under the receiver operating characteristic curve reaches up to 0.8813 for AD versus NC and 0.6451 for sMCI versus pMCI. However, the automatic segmentation methods are not significantly different in their performance.
Complete list of metadata

Cited literature [54 references]  Display  Hide  Download

Contributor : Pierrick Coupé Connect in order to contact the contributor
Submitted on : Tuesday, May 9, 2017 - 5:44:34 PM
Last modification on : Friday, January 7, 2022 - 3:55:04 AM
Long-term archiving on: : Thursday, August 10, 2017 - 1:52:53 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International License




Azar Zandifar, Vladimir Fonov, Pierrick Coupé, Jens Pruessner, D Louis Collins. A comparison of accurate automatic hippocampal segmentation methods. NeuroImage, Elsevier, 2017, ⟨10.1016/j.neuroimage.2017.04.018⟩. ⟨hal-01520108⟩



Record views


Files downloads