DocumentCode :
2652716
Title :
Incorporating variance within binary flow for leukocyte tracking
Author :
Janiczek, Rob L. ; Tang, Jinshan ; Acton, Scott T.
Author_Institution :
Dept. of Electr. & Comput. Eng., Virginia Univ., Charlottesville, VA, USA
Volume :
2
fYear :
2004
fDate :
7-10 Nov. 2004
Firstpage :
1838
Abstract :
Tracking leukocytes in vivo is vital in determination of the roles and significance of integrins and selectins within the inflammation process and the effectiveness of anti-inflammatory drugs. In this paper, we propose a region-based snake for segmenting objects in the presence of inhomogeneities. We then use this geometric snake to track leukocytes in intravital microscopy. The results show that the binary flow algorithm introduced here improves upon the traditional binary flow algorithm and the gradient vector flow algorithm both in terms of percentage of frames tracked and the root mean squared error.
Keywords :
blood; cellular biophysics; image reconstruction; image segmentation; mean square error methods; medical image processing; microscopy; statistics; tracking; antiinflammatory drugs; binary flow; geometric snake; gradient vector flow algorithm; inflammation process; intravital microscopy; leukocyte tracking; object segmentation; root mean squared error; Active contours; Drugs; Image reconstruction; Image segmentation; In vivo; Microscopy; Noise reduction; Shape; Statistics; White blood cells;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2004. Conference Record of the Thirty-Eighth Asilomar Conference on
Print_ISBN :
0-7803-8622-1
Type :
conf
DOI :
10.1109/ACSSC.2004.1399482
Filename :
1399482
Link To Document :
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