Improved segmentation of cerebellar structures in children.

Journal: Journal of neuroscience methods

Volume: 262

Issue: 

Year of Publication: 2016

Affiliated Institutions:  Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; MRC/UCT Medical Imaging Research Unit, Division of Biomedical Engineering, University of Cape Town, Cape Town, South Africa. Electronic address: priyalakshmi@gmail.com. Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa. Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa. Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; MRC/UCT Medical Imaging Research Unit, Division of Biomedical Engineering, University of Cape Town, Cape Town, South Africa. Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Department of Psychiatry and Mental Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States.

Abstract summary 

Consistent localization of cerebellar cortex in a standard coordinate system is important for functional studies and detection of anatomical alterations in studies of morphometry. To date, no pediatric cerebellar atlas is available.The probabilistic Cape Town Pediatric Cerebellar Atlas (CAPCA18) was constructed in the age-appropriate National Institute of Health Pediatric Database asymmetric template space using manual tracings of 16 cerebellar compartments in 18 healthy children (9-13 years) from Cape Town, South Africa. The individual atlases of the training subjects were also used to implement multi atlas label fusion using multi atlas majority voting (MAMV) and multi atlas generative model (MAGM) approaches. Segmentation accuracy in 14 test subjects was compared for each method to 'gold standard' manual tracings.Spatial overlap between manual tracings and CAPCA18 automated segmentation was 73% or higher for all lobules in both hemispheres, except VIIb and X. Automated segmentation using MAGM yielded the best segmentation accuracy over all lobules (mean Dice Similarity Coefficient 0.76; range 0.55-0.91; mean Hausdorff distance 0.9 mm; range 0.8-2.7 mm).In all lobules, spatial overlap of CAPCA18 segmentations with manual tracings was similar or higher than those obtained with SUIT (spatially unbiased infra-tentorial template), providing additional evidence of the benefits of an age appropriate atlas. MAGM segmentation accuracy was comparable to values reported recently by Park et al. (Neuroimage 2014;95(1):217) in adults (across all lobules mean DSC=0.73, range 0.40-0.89).CAPCA18 and the associated multi-subject atlases of the training subjects yield improved segmentation of cerebellar structures in children.

Authors & Co-authors:  Narayanan Priya Lakshmi PL Warton Christopher C Rosella Boonzaier Natalie N Molteno Christopher D CD Joseph Jesuchristopher J Jacobson Joseph L JL Jacobson Sandra W SW Zöllei Lilla L Meintjes Ernesta M EM

Study Outcome 

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Statistics
Citations :  Aljabar P, Heckemann RA, Hammers A, Hajnal JV, Rueckert D. Multi-atlas based segmentation of brain images: Atlas selection and its effect on accuracy. Neuroimage. 2009;46(3):726–738.
Authors :  9
Identifiers
Doi : 10.1016/j.jneumeth.2015.12.010
SSN : 1872-678X
Study Population
Male,Female
Mesh Terms
Adolescent
Other Terms
CAPCA18;Cerebellum;Multi atlas segmentation;Pediatric probabilistic atlas
Study Design
Cross Sectional Study
Study Approach
Country of Study
South Africa
Publication Country
Netherlands