Currently, mammography is the best method for the detection of breast cancer. However, the radiologist
fails to detect 10 to 30% of cancer cases in first trial, with two-thirds of them being detected retrospectively. It is believed that computerized analysis of radiographic images will assist the radiologist as a "second opinion" in detecting lesions and in making improved diagnostic decisions. It is also expected that the automated analysis of radiographic images using digital-neural technology will increase the efficiency and effectiveness of wide range, massive mammographic screening. In this presentation we examine the state-of-the-art in Computer-Aided Diagnosis (CADx) technology for breast cancer detection and classification, and we briefly report on our own research on this subject.
Έρευνα για την έγκαιρη διάγνωση του καρκίνου του μαστού με επεξεργασία ακτινογραφιών από ηλεκτρονικό υπολογιστή. Πιστεύεται ότι η μέθοδος αυτή θα βελτιώσει σημαντικά την αξιοπιστία των διαγνώσεων.
