DocumentCode
1804040
Title
Robust biological image sequence analysis using graph based approaches
Author
Delibaltov, Diana ; Karthikeyan, S. ; Jagadeesh, Vignesh ; Manjunath, B.S.
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of California, Santa Barbara, Santa Barbara, CA, USA
fYear
2012
fDate
4-7 Nov. 2012
Firstpage
1588
Lastpage
1592
Abstract
Robust methods for segmentation and tracking are critical for quantitative biology. We give an overview of our recent work on graph based methods for various microscopy image analysis, including tracing over 3-D electron microscopy image stacks, tracking in time-lapse confocal image sequences, and 3D segmentation. We present results on a variety of datasets such as 3-D confocal membrane volumes of the ascidian Ciona, electron micrograph stacks from the rabbit retina, and bright field microscopy time sequence data from mouse retina.
Keywords
biological techniques; biology computing; electron microscopy; graph theory; image segmentation; image sequences; object tracking; 3D confocal membrane volumes; 3D electron microscopy image stacks; 3D segmentation; ascidian Ciona; bright field microscopy time sequence data; electron micrograph stacks; graph based approaches; image segmentation; image tracking; microscopy image analysis; mouse retina; quantitative biology; rabbit retina; robust biological image sequence analysis; time-lapse confocal image sequences;
fLanguage
English
Publisher
ieee
Conference_Titel
Signals, Systems and Computers (ASILOMAR), 2012 Conference Record of the Forty Sixth Asilomar Conference on
Conference_Location
Pacific Grove, CA
ISSN
1058-6393
Print_ISBN
978-1-4673-5050-1
Type
conf
DOI
10.1109/ACSSC.2012.6489297
Filename
6489297
Link To Document