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A GPU approach for accelerating 3D deformable registration (DARTEL) on brain biomedical images

Published: 15 September 2013 Publication History

Abstract

Medical image processing is becoming a significant discipline in bioinformatic. Particularly, deformable registration methods are one of the field most important in the biomedical image processing, due to the valuable information provided. However, these methods consume a considerable processing time and memory requirements. Current GPUs have a high number of cores and high memory bandwidth providing an excellent platform for reducing the cost of these methods in terms of processing time. In this work, it is proposed a Graphics Processing Units (GPU)-based implementation of one of the most sophisticated deformable registration algorithms, DARTEL. The experimental results show a processing time reduction higher than 2 hours in typical cases of study. Moreover, the power consumption is also reduced in a significant amount.

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Cited By

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  • (2022)CLAIRE—Parallelized Diffeomorphic Image Registration for Large-Scale Biomedical Imaging ApplicationsJournal of Imaging10.3390/jimaging80902518:9(251)Online publication date: 16-Sep-2022
  • (2022)Towards Enhancing Coding Productivity for GPU Programming Using Static GraphsElectronics10.3390/electronics1109130711:9(1307)Online publication date: 20-Apr-2022
  • (2021)Fast GPU 3D diffeomorphic image registrationJournal of Parallel and Distributed Computing10.1016/j.jpdc.2020.11.006149(149-162)Online publication date: Mar-2021
  • Show More Cited By

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cover image ACM Other conferences
EuroMPI '13: Proceedings of the 20th European MPI Users' Group Meeting
September 2013
289 pages
ISBN:9781450319034
DOI:10.1145/2488551
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 the author(s) 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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  • ARCOS: Computer Architecture and Technology Area, Universidad Carlos III de Madrid

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 September 2013

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Author Tags

  1. CUDA
  2. DARTEL
  3. GPU
  4. biomedical image processing
  5. deformable registration

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  • Research-article

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EuroMPI '13
Sponsor:
  • ARCOS
EuroMPI '13: 20th European MPI Users's Group Meeting
September 15 - 18, 2013
Madrid, Spain

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EuroMPI '13 Paper Acceptance Rate 22 of 47 submissions, 47%;
Overall Acceptance Rate 66 of 139 submissions, 47%

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Cited By

View all
  • (2022)CLAIRE—Parallelized Diffeomorphic Image Registration for Large-Scale Biomedical Imaging ApplicationsJournal of Imaging10.3390/jimaging80902518:9(251)Online publication date: 16-Sep-2022
  • (2022)Towards Enhancing Coding Productivity for GPU Programming Using Static GraphsElectronics10.3390/electronics1109130711:9(1307)Online publication date: 20-Apr-2022
  • (2021)Fast GPU 3D diffeomorphic image registrationJournal of Parallel and Distributed Computing10.1016/j.jpdc.2020.11.006149(149-162)Online publication date: Mar-2021
  • (2020)Multi-Node Multi-GPU Diffeomorphic Image Registration for Large-Scale Imaging ProblemsSC20: International Conference for High Performance Computing, Networking, Storage and Analysis10.1109/SC41405.2020.00042(1-17)Online publication date: Nov-2020
  • (2019)BLAS-3 Optimized by OmpSs Regions (LASs Library)2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP)10.1109/EMPDP.2019.8671545(25-32)Online publication date: Feb-2019
  • (2018)Hyperspectral Image Classification Using Parallel Autoencoding Diabolo Networks on Multi-Core and Many-Core ArchitecturesElectronics10.3390/electronics71204117:12(411)Online publication date: 8-Dec-2018

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