Computer-Aided Prostate Cancer Detection in Ultrasonographic Images

Prostate cancer is one of the most frequent cancer in men and a major cause of mortality in developed countries. Detection of the prostate carcinoma at an early stage is crucial for a succesfull treatment. In this paper, a method for analysis of transrectal ultrasonography images aimed at computer-aided diagnosis of prostate cancer is presented. Althogh the task is extremely difficult due to a problem of imperfect supervision, we have obtained promising results indicating that valid information for the diagnostic is present in the images. Two classifiers based on k-Nearest Neighbours and Hidden Markov Models are compared.