Abstract—This paper presents an automated algorithm for breast cancer cell counting and its performance. The algorithm for analyzing stained breast cancer cell image consists of four procedures, i.e. image preprocessing, segmentation, feature extraction, and classification. In the image preprocessing, the wavelet transform is performed. The global thresholding and morphological operations are performed in segmentation. In the feature extraction, the average of b* in CIE L*a*b* color space is extracted. The segmented cells are classified by using extracted feature. If the average of b* is positive, the cancer cell is positive cell. In addition, if the average of b* is negative, the cancer cell is negative cell. The segmentation results show that the average performance is 85% when square-shaped structuring element and city block distance transform are used. The classification results show that the average performance is 94%.

Index Terms—Biomedical Image Processing, Quantitative Immunohistophathology, Wavelet Transform, Segmentation,Morphological Operation.

C. Primkhajeepong is with the Department of Electrical Engineering,Faculty of Engineering. Prince of Songkla University, Songkhla, Thailand(e-mail: chalit.pr@gmail.com).
P. Phukpattaranont is with the Department of Electrical Engineering,Faculty of Engineering. Prince of Songkla University, Songkhla, Thailand(e-mail: pronchai.ph@gmail.com).
S. Limsiroratana is with the Department of Computer Engineering,Faculty of Engineering. Prince of Songkla University, Songkhla, Thailand(e-mail: somchai@coe.psu.ac.th).
P. Boonyaphiphat is with the Department of Pathology, Faculty of Medicine, Prince of Songkla University, Songkhla, Thailand (e-mail:pleamjit.b@psu.ac.th).
K. Kayasut is with the Department of Pathology, Faculty of Medicine,Prince of Songkla University, Songkhla, Thailand (e-mail:K_kanita@hotmail.com).

Cite: C. Primkhajeepong, P. Phukpattaranont, S. Limsiroratana, P. Boonyaphiphat and K. Kayasut, "Performance Evaluation of Automated Algorithm for Breast Cancer Cell Counting," International Journal of Computer and
Electrical Engineering vol. 2, no. 4, pp. 637-642, 2010.