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- Title
Parallelized Seeded Region Growing Using CUDA.
- Authors
Seongjin Park; Jeongjin Lee; Hyunna Lee; Juneseuk Shin; Jinwook Seo; Kyoung Ho Lee; Yeong-Gil Shin; Bohyoung Kim
- Abstract
This paper presents a novel method for parallelizing the seeded region growing (SRG) algorithm using Compute Unified Device Architecture (CUDA) technology, with intention to overcome the theoretical weakness of SRG algorithm of its computation time being directly proportional to the size of a segmented region. The segmentation performance of the proposed CUDA-based SRG is compared with SRG implementations on single-core CPUs, quad-core CPUs, and shader language programming, using synthetic datasets and 20 body CT scans. Based on the experimental results, the CUDA-based SRG outperforms the other three implementations, advocating that it can substantially assist the segmentation during massive CT screening tests.
- Subjects
CUDA (Computer architecture); COMPUTERS in medicine; ALGORITHMS; IMAGE segmentation; DIAGNOSTIC imaging
- Publication
Computational & Mathematical Methods in Medicine, 2014, p1
- ISSN
1748-670X
- Publication type
Article
- DOI
10.1155/2014/856453