Abstract
The shape of anatomical structures in the brain has been adversely influenced by neurodegenerative disorders. However, the shape feature covariation between regions (e.g. subfields) of the structure and its change with disease remains unclear. In this paper, we present a first work to study the topology of the surface displacement shape feature via its persistence homology timeline features and model the polyadic interactions between the shape across the subfields of subcortical structures. Specifically, we study the caudate and pallidum structures for Shape Topology change with Parkinson’s disease. The shape topology features show statistically significant group level difference and good prediction performance in a repeated hold out stratified training experiment. These features show promise in their potential application to other neurological conditions and in clinical settings with further testing on larger data cohorts.
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Acknowledgment
Data used in the preparation of this article were obtained from the Parkinson’s Progression Markers Initiative (PPMI) database (http://www.ppmi-info.org/data). For up-to-date information on the study, visit www.ppmi-info.org. The authors acknowledge and thank the Natural Sciences and Engineering Research Council (NSERC), Michael Smith Foundation for Health Research (MSFHR), Canadian Institute of Health Research (CIHR), Brain Canada and MITACS Canada for their generous funding support.
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Garg, A., Lu, D., Popuri, K., Beg, M.F. (2017). Topology of Surface Displacement Shape Feature in Subcortical Structures. In: Cardoso, M., et al. Graphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics. GRAIL MICGen MFCA 2017 2017 2017. Lecture Notes in Computer Science(), vol 10551. Springer, Cham. https://doi.org/10.1007/978-3-319-67675-3_3
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DOI: https://doi.org/10.1007/978-3-319-67675-3_3
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