Our new prostate MRI CAD software provides a standardized cancer suspicion score for suspicious foci detected in DCE-MRI T1-w images. Our results suggest that it may improve radiologists' performances in prostate cancer identification, especially when they are not specialized in prostate imaging.

This new automatic prostate MRI segmentation method produces satisfactory results, even at prostate's base and apex. The method is computationally feasible and efficient.

Our method of symbolic description enables the analysis and interpretation of a vascular network obtained from angiographic images. The method provides a simplified representation of the network in the form of a skeleton, as well as a description of the corresponding information in a tree-like view.