Title :
GPU-based segmentation of cervical vertebra in X-Ray images
Author :
Mahmoudi, Sidi Ahmed ; Lecron, Fabian ; Manneback, Pierre ; Benjelloun, Mohammed ; Mahmoudi, Säid
Author_Institution :
Comput. Sci. Dept., Univ. of Mons, Mons, Belgium
Abstract :
The segmentation of cervical vertebra in X-Ray radiographs can give valuable information for the study of the vertebral mobility. One particular characteristic of the X-Ray images is that they present very low grey level variation and makes the segmentation difficult to perform. In this paper, we propose a segmentation procedure based on the Active Shape Model to deal with this issue. However, this application is seriously hampered by its considerable computation time. We present how vertebra extraction can efficiently be performed in exploiting the vast processing power of the Graphics Processing Units (GPU). We propose a CUDA-based GPU implementation of the most intensive processing steps enabling to boost performance. Experimentations have been conducted using a set of high resolution X-Ray medical images, showing a global speedup ranging from 15 to 21, by comparison with the CPU implementation.
Keywords :
X-ray imaging; computer graphics; image colour analysis; image resolution; image segmentation; medical image processing; radiography; shape recognition; CUDA-based GPU implementation; GPU-based segmentation; X-ray medical image; X-ray radiograph; active shape model; cervical vertebra; graphics processing unit; grey level variation; image resolution; image segmentation; vertebra extraction; vertebral mobility; Biomedical imaging; Graphics processing unit; Image edge detection; Image segmentation; Pixel; Shape; Active Shape Model; CUDA; Edge Detection; GPU; Vertebra Segmentation; X-Ray Medical Images;
Conference_Titel :
Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS), 2010 IEEE International Conference on
Conference_Location :
Heraklion, Crete
Print_ISBN :
978-1-4244-8395-2
Electronic_ISBN :
978-1-4244-8397-6
DOI :
10.1109/CLUSTERWKSP.2010.5613102