This paper describes a study on the automated analysis of ultrasonographic prostate images. With image processing, tissue characterization in the prostate was performed to assess the probability of malignancy. During prostate examinations, images were recorded at the positions where biopsies were taken. The used samples were divided into three groups. Two of them were used for the construction of a classification tree, and the third was used for the evaluation of this classification. A sensitivity of 80.6% and specificity of 77.1% were reached retrospectively. In a prospective way, these results were 80.0% and 88.2%, respectively. The prospective predictive value for cancer detection was 85.7%. The presented prospective value for image analysis was almost twice as high as the values normally found for prostate examination.