GPU IMPLEMENTATION OF MAP-MRF FOR MICROSCOPY IMAGERY SEGMENTATION

被引：1

作者：

Crookes, Danny ^{[1
]}

Miller, Paul ^{[1
]}

Gribben, Hugh ^{[1
]}

Gillan, Charles ^{[1
]}

McCaughey, Damian ^{[1
]}

机构：

[1] Queens Univ Belfast, Inst Elect Commun & Informat Technol, Belfast BT3 9DT, Antrim, North Ireland

来源：

2009 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1 AND 2 | 2009年

关键词：

Image segmentation; accelerators; UNIT;

D O I：

10.1109/ISBI.2009.5193100

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

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.

引用

页码：526 / 529

页数：4

共 4 条

[1]

GRIBBEN H, 2007, P BRIT MACH VIS C, P331

[2] Accelerating molecular modeling applications with graphics processors [J].