Evaluation of color based breast cancer cell images analysis

Abstract

This paper describes a simple yet effective algorithm for automatically counting stained breast cancer cell imagesbased on color contents. The procedure for the approach consists of four steps. First, the cancer cell image in red-greenblue(RGB) color space is transformed with Haar wavelet. Second, the wavelet transformed image is changed to gray-scaleimage. Next, the gray-scale image is segmented with global thresholding using Otsu’s method and morphological operationsusing opening, region filling, border clearing, and watershed segmentation. Third, the wavelet transformed image is changedto CIEL*a*b* color space. The feature, i.e. average value of b* of each isolated cell, is extracted. Finally, the classification isapplied by using the extracted feature. If the average value of b* is positive that indicates yellow, the cancer cell is a positivecell. In addition, if the average value of b* is negative that indicates blue, the cancer cell is a negative cell. Results show thatthe classified cancer cells by the proposed algorithm are in good agreement with the expert perception. In addition, thealgorithm is practical to be used by a pathologist due to its simplicity and effectiveness.

Keywords

• quantitative immunohistophathology
• biomedical image processing
• image segmentation
• wavelet transformation
• morphological operation