Cancer cells detection and pathology quantification utilizing image analysis techniques

Author

Goudas, T. ; Maglogiannis, Ilias

Author_Institution

Dept. of Comput. Sci. & Biomed. Inf., Univ. of Central Greece, Lamia, Greece

fYear

2012

fDate

Aug. 28 2012-Sept. 1 2012

Firstpage

4418

Lastpage

4421

Abstract

This paper presents an advanced image analysis tool for the accurate and fast characterization and quantification of cancer and apoptotic cells in microscopy images utilizing adaptive thresholding and a Support Vector Machines classifier. The segmentation results are also enhanced through a Majority Voting and a Watershed technique. The proposed tool was evaluated by experts on breast cancer images and the reported results were accurate and reproducible.

Keywords

biomedical optical imaging; cancer; cellular biophysics; image classification; image enhancement; image segmentation; medical image processing; optical microscopy; support vector machines; apoptotic cells; breast cancer images; cancer cells detection; image analysis techniques; image enhancement; image segmentation; majority voting; microscopy images; optical microscopy; pathology quantification; support vector machines classifier; watershed technique; Biomedical imaging; Cancer; Drugs; Filtering; Image edge detection; Support vector machines; Tumors; Algorithms; Animals; Breast Neoplasms; Image Enhancement; Image Interpretation, Computer-Assisted; Mice; Microscopy; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Support Vector Machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE

Conference_Location

San Diego, CA

ISSN

1557-170X

Print_ISBN

978-1-4244-4119-8

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/EMBC.2012.6346946

Filename

6346946