HIPS: A new hippocampus subfield segmentation method

• Published in: NeuroImage (Orlando, Fla.) Vol. 163; pp. 286 - 295
• Main Authors: Romero, José E., Coupé, Pierrick, Manjón, José V.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.12.2017; Elsevier Limited; Elsevier
• Subjects: Alzheimer's disease; Automation; Cognition & reasoning; Computer Science; Datasets; High resolution; Hippocampus; Image contrast; Image processing; Information processing; Medical Imaging; Methods; Neural networks; Neurodegenerative diseases; Neuroimaging; Neurology; NMR; Nuclear magnetic resonance; Segmentation; Studies
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2017.09.049

The importance of the hippocampus in the study of several neurodegenerative diseases such as Alzheimer's disease makes it a structure of great interest in neuroimaging. However, few segmentation methods have been proposed to measure its subfields due to its complex structure and the lack of high resolution magnetic resonance (MR) data. In this work, we present a new pipeline for automatic hippocampus subfield segmentation using two available hippocampus subfield delineation protocols that can work with both high and standard resolution data. The proposed method is based on multi-atlas label fusion technology that benefits from a novel multi-contrast patch match search process (using high resolution T1-weighted and T2-weighted images). The proposed method also includes as post-processing a new neural network-based error correction step to minimize systematic segmentation errors. The method has been evaluated on both high and standard resolution images and compared to other state-of-the-art methods showing better results in terms of accuracy and execution time. [Display omitted] •We present a novel method for hippocampus subfield segmentation on MRI.•The method consists of a fast multi-atlas non-local patch-based label fusion.•Our proposed method was shown to improve the state-of-the-art methods with a reduced temporal cost (20 mins).•The pipeline presented in this work will be made available to scientific community through our web -based platform volBrain.