DocumentCode :
2136233
Title :
A hybrid watershed method for cell image segmentation
Author :
Ao, Jingqi ; Mitra, Sunanda ; Long, Rodney ; Nutter, Brian ; Antani, Sameer
Author_Institution :
Texas Tech Univ., Lubbock, TX, USA
fYear :
2012
fDate :
22-24 April 2012
Firstpage :
29
Lastpage :
32
Abstract :
In cytological evaluation of cells, the nuclear characteristics present significant opportunities for early detection of abnormalities arising from various types of cancer. Accurate representation of cell nuclear structure by traditional manual inspection is difficult and time-consuming. In this paper, we introduce a new semi-automated cell segmentation algorithm combining a histogram-based global approach with local watershed segmentation. The procedure requires very little prior knowledge or user interaction. Preliminary results of accurate segmentation of the nucleus from the cell are presented to demonstrate potential application of this algorithm in cytological evaluation of abnormal nuclear structure.
Keywords :
cancer; cellular biophysics; image segmentation; medical image processing; abnormal nuclear structure; cancer; cell cytological evaluation; cell nuclear structure representation; early abnormality detection; histogram-based global approach; hybrid watershed method; local watershed segmentation; nuclear characteristics; semi-automated cell image segmentation algorithm; Biomedical imaging; Clustering algorithms; Cost function; Histograms; Image color analysis; Image segmentation; Manuals; cell segmentation; cytopathology; global histogram; local watershed;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Interpretation (SSIAI), 2012 IEEE Southwest Symposium on
Conference_Location :
Santa Fe, NM
Print_ISBN :
978-1-4673-1831-0
Electronic_ISBN :
978-1-4673-1829-7
Type :
conf
DOI :
10.1109/SSIAI.2012.6202445
Filename :
6202445
Link To Document :
بازگشت