A comparative study of segmentation techniques for the quantification of brain subcortical volume
| Autor: | Brian Hallahan, Emma McDermott, Helen Casey, Colm McDonald, Leila Nabulsi, Peter Dockery, Theophilus N. Akudjedu, Joanne Kenney, Srinath Ambati, Cathy Scanlon, Dara M. Cannon, Sarah Hehir, Migle Makelyte, Stefani O'Donoghue, Liam Kilmartin |
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| Rok vydání: | 2018 |
| Předmět: |
Adult
Male Adolescent Intraclass correlation Cognitive Neuroscience Stereology Pattern Recognition Automated 030218 nuclear medicine & medical imaging Young Adult 03 medical and health sciences Behavioral Neuroscience Cellular and Molecular Neuroscience 0302 clinical medicine Consistency (statistics) Image Processing Computer-Assisted medicine Humans Radiology Nuclear Medicine and imaging Segmentation Partial correlation Neuroradiology Mathematics medicine.diagnostic_test business.industry Mental Disorders Brain Magnetic resonance imaging Organ Size Gold standard (test) Middle Aged Magnetic Resonance Imaging Psychiatry and Mental health Neurology Female Neurology (clinical) Nuclear medicine business Software 030217 neurology & neurosurgery |
| Zdroj: | Brain Imaging and Behavior. 12:1678-1695 |
| ISSN: | 1931-7565 1931-7557 |
| Popis: | Manual tracing of magnetic resonance imaging (MRI) represents the gold standard for segmentation in clinical neuropsychiatric research studies, however automated approaches are increasingly used due to its time limitations. The accuracy of segmentation techniques for subcortical structures has not been systematically investigated in large samples. We compared the accuracy of fully automated [(i) model-based: FSL-FIRST; (ii) patch-based: volBrain], semi-automated (FreeSurfer) and stereological (Measure®) segmentation techniques with manual tracing (ITK-SNAP) for delineating volumes of the caudate (easy-to-segment) and the hippocampus (difficult-to-segment). High resolution 1.5 T T1-weighted MR images were obtained from 177 patients with major psychiatric disorders and 104 healthy participants. The relative consistency (partial correlation), absolute agreement (intraclass correlation coefficient, ICC) and potential technique bias (Bland-Altman plots) of each technique was compared with manual segmentation. Each technique yielded high correlations (0.77-0.87, p |
| Databáze: | OpenAIRE |
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