Prostate adenocarcinoma (PCa) is the most frequent noncutaneous cancer among men in developed countries. Magnetic Resonance (MR) has been used to detect PCa and several clinical trials report on the accuracy of the test. Multiparametric MR imaging (mpMRI) is defined as the integration of information from different morphological and functional datasets. mpMRI could be used to increase the performances of prostate MR, therefore allowing a more accurate assessment of the tumor gland extent, while reducing reporting time and interobserver variability. The first step to perform such a multiparametric analysis is to correct for voluntary and involuntary movements during the acquisitions, as well as for image distortion in the Diffusion Weighted (DWI) images. The aim of this work is to present a fully automatic registration algorithm between T2w and DWI images, able to realign the images and to correct the distortions in the DWI. Results showed a good overlap after registration and a strong decrease of mean surface distance in both the central gland and peripheral zone. These promising results suggest that the algorithm could be integrated in a CAD system which will combine the pharmacokinetic parameters derived from DCE-MRI, T2w MRI and DWI MR to generate one comprehensive value assessing the risk of malignancy. However to perform such a multiparametric analysis, it is necessary to correct for voluntary and involuntary (breathing, heart beating) movements during the DCE-MRI acquisition, and to realign also the DCE-MRI sequence to the T2w sequence.