DocumentCode :
2720090
Title :
An Iterative Approach to Nucleus Segmentation for High Content Imaging in Cancer Research
Author :
Tarokh, Ashley B. ; Liu, Kuang-Yu ; Zhou, Xiaobo ; Wong, Stephen T C
Author_Institution :
Dept. of Radiol., Harvard Med. Sch., Boston, MA
fYear :
2006
fDate :
38899
Firstpage :
1
Lastpage :
2
Abstract :
We present an iterative technique for nucleus segmentation in high throughput RNA interference (RNAi) screening. This technique acts as a crucial processing step towards cell segmentation and feature extraction. Our data comes from three-channel RNAi cell images, with the nucleus information contained in a single DNA channel. Accurate segmentation of the nucleus information provides valuable prior information regarding cell counts and cell positioning, and is thus a valuable prior toward the overall goal of phenotype recognition and detection. Our iterative technique takes direct advantage of image gradient information to obtain accurate nucleus segmentations. It is particularly effective in separating nuclei that are very closely spaced, that thresholding cannot accurately segment
Keywords :
DNA; cancer; cellular biophysics; feature extraction; image segmentation; iterative methods; medical image processing; cancer research; cell counts; cell positioning; cell segmentation; feature extraction; high content imaging; high throughput RNA interference screening; image gradient information; iterative approach; nucleus segmentation; phenotype detection; phenotype recognition; single DNA channel; Cancer; Clustering algorithms; DNA; Feature extraction; Image segmentation; Interference; Iterative algorithms; Iterative methods; RNA; Throughput;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Life Science Systems and Applications Workshop, 2006. IEEE/NLM
Conference_Location :
Bethesda, MD
Print_ISBN :
1-4244-0277-8
Electronic_ISBN :
1-4244-0278-6
Type :
conf
DOI :
10.1109/LSSA.2006.250412
Filename :
4015813
Link To Document :
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