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CUDA Accelerated 3D Non-rigid Diffeomorphic Registration
KTH, School of Technology and Health (STH).
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
CUDA-accelererad icke-rigid diffeomorf registrering i 3D (Swedish)
Abstract [en]

Advances of magnetic resonance imaging (MRI) techniques enable visualguidance to identify the anatomical target of interest during the image guidedintervention(IGI). Non-rigid image registration is one of the crucial techniques,aligning the target tissue with the MRI preoperative image volumes. As thegrowing demand for the real-time interaction in IGI, time used for intraoperativeregistration is increasingly important. This work implements 3D diffeomorphicdemons algorithm on Nvidia GeForce GTX 1070 GPU in C++ based on CUDA8.0.61 programming environment, using which the average registration time hasaccelerated to 5s. We have also extensively evaluated GPU accelerated 3D diffeomorphicregistration against both CPU implementation and Matlab codes, and theresults show that GPU implementation performs a much better algorithm efficiency.

Place, publisher, year, edition, pages
2017. , 41 p.
Series
TRITA-STH, 2017:71
Keyword [en]
diffeopmorphic demons, non-rigid image registration, parallel programming, GPGPU, IGI
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:kth:diva-211135OAI: oai:DiVA.org:kth-211135DiVA: diva2:1127754
External cooperation
The University of Hong Kong
Subject / course
Medical Engineering
Educational program
Master of Science - Medical Engineering
Supervisors
Examiners
Available from: 2017-08-06 Created: 2017-07-19 Last updated: 2017-08-06Bibliographically approved

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AN_QU_STUDENT_THESIS(3559 kB)32 downloads
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Type fulltextMimetype application/pdf

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Medical Image Processing

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Output format
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