Validation of consistent inter-subject connectivity-based parcellation

Splitting the cortical surface into regions with homogeneous dMRI-based connectivity profiles is a promising but challenging topic. This paper extends the inter-subject connectivity-based cortex parcellation framework proposed by Roca [1]. In a first step, we implement the state-of-the-art algorithm...

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Bibliographic Details
Published inProceedings (International Symposium on Biomedical Imaging) pp. 923 - 926
Main Authors Lefranc, S., Roca, P., Perrot, M., Poupon, C., Coulon, O., Le Bihan, D., Hertz-Pannier, L., Mangin, J.-F, Riviere, D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2014
Subjects
Anatomical connectivity
Clustering algorithms
Human brain
Magnetic resonance imaging
Parcellation
Probabilistic logic
Probabilistic tractography
Robustness
Smoothing methods
Surface reconstruction
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Summary:Splitting the cortical surface into regions with homogeneous dMRI-based connectivity profiles is a promising but challenging topic. This paper extends the inter-subject connectivity-based cortex parcellation framework proposed by Roca [1]. In a first step, we implement the state-of-the-art algorithm with tuned parameters and, then propose a refined algorithm validated on the large high quality ARCHI database. This algorithm consists in clustering and subdividing each gyrus, in a reasonable time. Cross-validation shows that the resulting patterns are reproducible across groups. The stability is illustrated for the post-central gyrus of three different groups of subjects. Finally, the method has successfully been made robust to initial conditions: tracking type, cortical mesh characteristics and boundaries of gyri.
ISSN:1945-7928
DOI:10.1109/ISBI.2014.6868022