DocumentCode
2217064
Title
Implementation of medical image segmentation in CUDA
Author
Pan, Lei ; Gu, Lixu ; Xu, Jianrong
Author_Institution
Sch. of software, Shanghai Jiaotong Univ., Shanghai
fYear
2008
fDate
30-31 May 2008
Firstpage
82
Lastpage
85
Abstract
As the fast development of GPU, people tend to use it for more general purposes than its original graphic related work. The high parallel computation capabilities of GPU are welcomed by programmers who work at medical image processing which always have to deal with a large scale of voxel computation. The birth of NVIDIAreg CUDAtrade technology and CUDA-enabled GPUs brought a revolution in the general purpose GPU area. In this paper, we propose the implementation of several medical image segmentation algorithms using CUDA and CUDA-enabled GPUs, compare their performance and results to the previous implementation in old version of GPU and CPU, indicate the advantages of using CUDA technology and how to design algorithm to make full use of it.
Keywords
image segmentation; medical image processing; CUDA; GPU; medical image segmentation; region growing; Application software; Biomedical imaging; Computer applications; Computer architecture; Computer interfaces; Concurrent computing; Graphics; Image segmentation; Large-scale systems; Yarn; CUDA; GPU; Region Growing; Segmentation; Watershed;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Applications in Biomedicine, 2008. ITAB 2008. International Conference on
Conference_Location
Shenzhen
Print_ISBN
978-1-4244-2254-8
Electronic_ISBN
978-1-4244-2255-5
Type
conf
DOI
10.1109/ITAB.2008.4570542
Filename
4570542
Link To Document