Title :
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
fDate :
Aug. 28 2012-Sept. 1 2012
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;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-4119-8
Electronic_ISBN :
1557-170X
DOI :
10.1109/EMBC.2012.6346946
