Title :
GPU implementation of map-MRF for microscopy imagery segmentation
Author :
Crookes, Danny ; Miller, Paul ; Gribben, Hugh ; Gillan, Charles ; McCaughey, Damian
Author_Institution :
Inst. of Electron., Commun. & Inf. Technol. (ECIT), Queen´´s Univ. Belfast, Belfast, UK
fDate :
June 28 2009-July 1 2009
Abstract :
Recent developments in 3D low-light level CCD (L3CCD) image capture have enabled the study of the dynamics of biomedical bodies within cells. This paper firstly presents an improved algorithm for automatic segmentation of such imagery. It allows for the specific nature of noise in L3CCD data. Secondly, the massive volume of data produced by continuous real time 3D scans requires a high performance computation facility for automatic segmentation and tracking. The paper presents details and results of a GPU implementation of a version of the segmentation algorithm, and shows that on an NVIDIA GeForce 8800GTX, coded in CUDA C, the algorithm runs around 550 times faster than the Matlab version of the algorithm running on a PC.
Keywords :
CCD image sensors; biomedical optical imaging; cellular biophysics; computer graphics; image segmentation; medical image processing; optical microscopy; 3D low-light level CCD; CUD C; NVIDIA GeForce 8800GTX; automatic segmentation; automatic tracking; biomedical bodies; cells; image capture; microscopy; Biomedical computing; Biomedical image processing; Charge coupled devices; Electron microscopy; Gaussian distribution; High performance computing; Image segmentation; Information technology; Layout; Statistical distributions; Image segmentation; accelerators;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-3931-7
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2009.5193100
