Title :
Early Breast Cancer Identification: Which Way to Go? Microarray or Image Based Computer Aided Diagnosis!
Author :
Nahar, Jesmin ; Tickle, Kevin S. ; Ali, A. B M Shawkat ; Chen, Yi-Ping Phoebe
Author_Institution :
Sch. of Comput. Sci., Central Queensland Univ., Rockhampton, QLD, Australia
Abstract :
The goal of this research is to develop a computer aided diagnostic (CAD) system that can detect breast cancer in the early stage by using microarray and image data. We verified the performance of six well known classification algorithms with various performance matrices. Although we do not suggest a unique classifier algorithm for a CAD system, we do identify a number of algorithms whose performance is very promising. The algorithms performance was validated by 3 images dataset; two have been used for the first time in this experiment. Multidimensional image filtering is adopted for the final data extraction. The image data classification performance is compared with microarray data. Results suggest the most effective means of breast cancer identification in the early stage is a hybrid approach.
Keywords :
biological organs; cancer; filtering theory; image classification; learning (artificial intelligence); medical image processing; multidimensional signal processing; tumours; CAD system; early breast cancer identification; final data extraction; image based computer aided diagnosis; image data classification; machine learning; microarray based computer aided diagnosis; multidimensional image filtering; performance matrix; Biomedical imaging; Breast cancer; Cancer detection; Classification algorithms; Classification tree analysis; Data mining; Electronic mail; Information security; Mammography; Medical diagnostic imaging;
Conference_Titel :
Network and System Security, 2009. NSS '09. Third International Conference on
Conference_Location :
Gold Coast, QLD
Print_ISBN :
978-1-4244-5087-9
Electronic_ISBN :
978-0-7695-3838-9
DOI :
10.1109/NSS.2009.75
