DocumentCode :
34405
Title :
Massively Parallel Energy Space Exploration for Uncluttered Visualization of Vascular Structures
Author :
Yongkweon Jeon ; Joong-Ho Won ; Sungroh Yoon
Author_Institution :
Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea
Volume :
60
Issue :
1
fYear :
2013
fDate :
Jan. 2013
Firstpage :
240
Lastpage :
244
Abstract :
Images captured using computed tomography and magnetic resonance angiography are used in the examination of the abdominal aorta and its branches. The examination of all clinically relevant branches simultaneously in a single 2-D image without any misleading overlaps facilitates the diagnosis of vascular abnormalities. This problem is called uncluttered single-image visualization (USIV). We can solve the USIV problem by assigning energy-based scores to visualization candidates and then finding the candidate that optimizes the score; this approach is similar to the manner in which the protein side-chain placement problem has been solved. To obtain near-optimum images, we need to explore the energy space extensively, which is often time consuming. This paper describes a method for exploring the energy space in a massively parallel fashion using graphics processing units. According to our experiments, in which we used 30 images obtained from five patients, the proposed method can reduce the total visualization time substantially. We believe that the proposed method can make a significant contribution to the effective visualization of abdominal vascular structures and precise diagnosis of related abnormalities.
Keywords :
biomedical MRI; computerised tomography; data visualisation; medical disorders; medical image processing; proteins; USIV problem; abdominal aorta; computed tomography; magnetic resonance angiography; massively parallel energy space exploration; protein side chain placement problem; uncluttered visualization; vascular abnormalities diagnosis; vascular structure; Graphics processing unit; Instruction sets; Libraries; Measurement; Message systems; Optimization; Visualization; Abdominal aorta; GPGPU; energy-space exploration; parallelization; single-image visualization; Algorithms; Aorta, Abdominal; Humans; Image Processing, Computer-Assisted; Magnetic Resonance Angiography; Models, Cardiovascular; Tomography, X-Ray Computed;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2012.2214386
Filename :
6276243
Link To Document :
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