Combining fuzzy experts' decisions fusion with linguistic summarization of mammograms for computer-aided breast diagnosis

The Computational Theory of Perceptions (CTP) provides capabilities for linguistic summarization of data and it aims the description of patterns emerging from these data by means of linguistic expressions. This technique is particularly well suited in applications where there is the need of understanding the information at different levels of expertise and/or when intense human-computer interaction is required. In this paper, we present a CTP-based system able to generate valuable linguistic reports from findings in breast image mammograms using the BI-RADS radiology standard. The implemented framework uses data obtained through the fusion of information provided by different medical experts on the same mammography. Then, our system automatically produces a collection of valid sentences describing: the breast lesion findings (i.e. features of masses or calcifications), the BI-RADS category rating for the analyzed mammography and the recommendations for patients. The system validation by several medical specialists has produced promising results, which make it useful for its practical deployment.