Automatic statistical shape analysis of cerebral asymmetry in 3D T1-weighted magnetic resonance images at vertex-level: Application to neuroleptic-naïve schizophrenia |
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Authors: | Antonietta Pepe Lu Zhao Juha Koikkalainen Jarmo Hietala Ulla Ruotsalainen Jussi Tohka |
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Institution: | 1. Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FIN-33101 Tampere, Finland;2. McConnell Brain Imaging Center, McGill University, 3801 University Street, Montréal, Québec, Canada;3. VTT Technical Research Centre of Finland, P.O. Box 1300, FIN-33101 Tampere, Finland;4. Turku PET Centre, P.O. Box 52, FIN-20521 Turku, Finland;5. Department of Psychiatry, University of Turku, FIN-20700 Turku, Finland |
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Abstract: | The study of the structural asymmetries in the human brain can assist the early diagnosis and progression of various neuropsychiatric disorders, and give insights into the biological bases of several cognitive deficits. The high inter-subject variability in cortical morphology complicates the detection of abnormal asymmetries especially if only small samples are available. This work introduces a novel automatic method for the local (vertex-level) statistical shape analysis of gross cerebral hemispheric surface asymmetries which is robust to the individual cortical variations. After segmentation of the cerebral hemispheric volumes from three-dimensional (3D) T1-weighted magnetic resonance images (MRI) and their spatial normalization to a common space, the right hemispheric masks were reflected to match with the left ones. Cerebral hemispheric surfaces were extracted using a deformable model-based algorithm which extracted the salient morphological features while establishing the point correspondence between the surfaces. The interhemispheric asymmetry, quantified by customized measures of asymmetry, was evaluated in a few thousands of corresponding surface vertices and tested for statistical significance. |
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Keywords: | Statistical shape asymmetry Automatic Neuroleptic-naï ve schizophrenia |
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