DocumentCode :
1036084
Title :
High-throughput analysis of multispectral images of breast cancer tissue
Author :
Adiga, Umesh ; Malladi, Ravikanth ; Fernandez-Gonzalez, Rodrigo ; De Solorzano, Carlos Ortiz
Author_Institution :
Lawrence Berkeley Nat. Lab., Univ. of California at Berkeley
Volume :
15
Issue :
8
fYear :
2006
Firstpage :
2259
Lastpage :
2268
Abstract :
Statistical analysis of genetic changes within cell nuclei that are far from the primary tumor would help determine whether such changes have occurred prior to tumor invasion. To determine whether the gene amplification in cells is morphologically and/or genetically related to the primary tumor requires quantitative evaluation of a large number of cell nuclei from continuous meaningful structures such as milk-ducts, tumors, etc., located relatively far from the primary tumor. To address this issue, we have designed an integrated image analysis software system for high-throughput segmentation of nuclei. Filters such as Beltrami flow-based reaction-diffusion, directional diffusion, etc., were used to pre-process the images resulting in a better segmentation. The accurate shape of the segmented nucleus was recovered using an iterative "shrink-wrap" operation. The study of two cases of ductal carcinoma in situ in breast tissue supports the biological observation regarding the existence of a preferential intraductal invasion, and therefore a common origin, between the primary tumor and the gene amplification in the cell-nuclei lining the ductal structures in the breast
Keywords :
biological tissues; cancer; image segmentation; medical image processing; statistical analysis; breast cancer tissue; cell nuclei; ductal carcinoma; gene amplification; genetic changes; high-throughput analysis; image segmentation; integrated image analysis software system; multispectral images; statistical analysis; Breast cancer; Breast neoplasms; Filters; Genetics; Image analysis; Image segmentation; Multispectral imaging; Shape; Software systems; Statistical analysis; Cell; coherence; diffusion; segmentation; tissue;
fLanguage :
English
Journal_Title :
Image Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7149
Type :
jour
DOI :
10.1109/TIP.2006.875205
Filename :
1658090
Link To Document :
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