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In this paper, we proposed a system for automated estrogen receptor status evaluation in breast carcinoma patients which consists of four stages: cell detection, positive/negative classification, weak/moderate/strong classification, and Allred scoring. As both ER and PR share similar staining characteristics, the system can be further extended to determine PR (and possibly HER2) expression in the future with minor modifications to make for a complete hormone receptor system. Flowchart for the overview of the system. The detected and classified cells are then fed to the final stage of the system, indicated by the red box and arrows, for estrogen receptor status evaluation. By computing the distribution of the strong, moderate, weak, as well as negatively stained cells within the slides or regions of interest, the estrogen receptor expression for the slide is determined by computing the Allred score [5], and compared to the pathologists’ manual scoring. Alternatively, the H-score [6] can also be used for assessing estrogen receptor status, but in this project we focus on Allred scoring as we have the ground truth available for evaluation. To the best of our knowledge, this is the first work of its kind in developing such a system with the scoring of whole-slide images, which would be a valuable tool for histopathologists in improving the reliability of tumor marker reporting as well as reducing manual intervention workload. There are some similar works found in the literature [7,8,9] working on Allred scoring of ER-IHC patches.
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