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Tools for studying populations and timeseries of neuroanatomy enabled through GPU acceleration in the Computational Anatomy Gateway

Published: 17 July 2016 Publication History

Abstract

The Computational Anatomy Gateway is a software as a service tool for medical imaging researchers to quantify changes in anatomical structures over time, and through the progression of disease. GPU acceleration on the Stampede cluster has enabled the development of new tools, combining advantages of grid based and particle based methods for describing fluid flows, and scaling up analysis from single scans to populations and timeseries. We describe algorithms for estimating average anatomies, and for quantifying atrophy rate over time. We report code performance on different sized datasets, revealing that the number vertices in a triangulated surface presents a bottleneck to our computation. We show results on an example dataset, quantifying atrophy in the entorhinal cortex, a medial temporal lobe brain region whose structure is sensitive changes in early Alzheimer's disease.

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  • (2023)Statistical Shape Analysis of Corpus CallosumThe Corpus Callosum10.1007/978-3-031-38114-0_41(369-376)Online publication date: 28-Nov-2023
  • (2021)Down‐sampling template curve to accelerate LDDMM‐curve with application to shape analysis of the corpus callosumHealthcare Technology Letters10.1049/htl2.120118:3(78-83)Online publication date: 2-May-2021
  • (2019)A Large Deformation Diffeomorphic Framework for Fast Brain Image Registration via Parallel Computing and OptimizationNeuroinformatics10.1007/s12021-019-09438-7Online publication date: 7-Nov-2019
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cover image ACM Other conferences
XSEDE16: Proceedings of the XSEDE16 Conference on Diversity, Big Data, and Science at Scale
July 2016
405 pages
ISBN:9781450347556
DOI:10.1145/2949550
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 17 July 2016

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Author Tags

  1. computational anatomy
  2. medical imaging
  3. neuroscience
  4. science gateway

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Overall Acceptance Rate 129 of 190 submissions, 68%

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Cited By

View all
  • (2023)Statistical Shape Analysis of Corpus CallosumThe Corpus Callosum10.1007/978-3-031-38114-0_41(369-376)Online publication date: 28-Nov-2023
  • (2021)Down‐sampling template curve to accelerate LDDMM‐curve with application to shape analysis of the corpus callosumHealthcare Technology Letters10.1049/htl2.120118:3(78-83)Online publication date: 2-May-2021
  • (2019)A Large Deformation Diffeomorphic Framework for Fast Brain Image Registration via Parallel Computing and OptimizationNeuroinformatics10.1007/s12021-019-09438-7Online publication date: 7-Nov-2019
  • (2017)Performance of Image Matching in the Computational Anatomy GatewayPractice and Experience in Advanced Research Computing 2017: Sustainability, Success and Impact10.1145/3093338.3093361(1-7)Online publication date: 9-Jul-2017
  • (2017)Entorhinal and transentorhinal atrophy in mild cognitive impairment using longitudinal diffeomorphometryAlzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring10.1016/j.dadm.2017.07.0059:1(41-50)Online publication date: 30-Aug-2017
  • (2017)Unbiased Diffeomorphic Mapping of Longitudinal Data with Simultaneous Subject Specific Template EstimationGraphs in Biomedical Image Analysis, Computational Anatomy and Imaging Genetics10.1007/978-3-319-67675-3_12(125-136)Online publication date: 8-Sep-2017

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