A fully automatic method to register the prostate gland on T2-weighted and EPI-DWI images.

Massimo De Luca, Valentina Giannini, Anna Vignati, Simone Mazzetti, Christian Bracco, Michele Stasi, Enrico Armando, Filippo Russo, Enrico Bollito, Francesco Porpiglia, Daniele Regge

Research output: Contribution to journalArticlepeer-review


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.

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics


Dive into the research topics of 'A fully automatic method to register the prostate gland on T2-weighted and EPI-DWI images.'. Together they form a unique fingerprint.

Cite this