Image processing for mitoses in sections of breast cancer: A feasibility study

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Abstract
This paper describes an image analysis technique for the counting of nuclei in mitosis in tissue sections. Five experienced pathologists scored mitoses in photographs of preselected areas of tissue sections of the breast. Objects consistently labelled as mitotic cells by all five pathologists were considered “mitoses” in the analysis. In total, there were 45 mitotic nuclei, 68 possible mitotic nuclei and 1,172 nonmitotic nuclei.The image analysis procedure was designed to give priority to a low false negative rate, i.e., misclassification of mitoses. The procedure consists of three steps: Segmentation of the image. Reduction of the number of nonmitotic nuclei by using feature values based on the brightness histogram of the objects. Fully automatic classification of the remaining objects using contour features. The objects remaining after the first two steps were visualized in a composite display for interactive evaluation: 10% of the mitotic nuclei were missed, and 85% of the nonmitotic nuclei were eliminated. The result of the fully automatic procedure described in this paper is rather disappointing and gave a loss of 37% of the mitoses while 5% of the nonmitotic nuclei remained.