Efficient convex optimization approach to 3D non-rigid MR-TRUS registration

Yue Sun, Jing Yuan, Martin Rajchl, Wu Qiu, Cesare Romagnoli, Aaron Fenster

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

24 Citations (Scopus)


In this study, we propose an efficient non-rigid MR-TRUS deformable registration method to improve the accuracy of targeting suspicious locations during a 3D ultrasound (US) guided prostate biopsy. The proposed deformable registration approach employs the multi-channel modality independent neighbourhood descriptor (MIND) as the local similarity feature across the two modalities of MR and TRUS, and a novel and efficient duality-based convex optimization based algorithmic scheme is introduced to extract the deformations which align the two MIND descriptors. The registration accuracy was evaluated using 10 patient images by measuring the TRE of manually identified corresponding intrinsic fiducials in the whole gland and peripheral zone, and performance metrics (DSC, MAD and MAXD) for the apex, mid-gland and base of the prostate were also calculated by comparing two manually segmented prostate surfaces in the registered 3D MR and TRUS images. Experimental results show that the proposed method yielded an overall mean TRE of 1.74 mm, which is favorably comparable to a clinical requirement for an error of less than 2.5 mm.
Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention – MICCAI 2013
Subtitle of host publication16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, Part I
EditorsKensaku Mori
Place of PublicationBerlin
Number of pages8
ISBN (Electronic)978-3-642-40811-3
ISBN (Print)978-3-642-40810-6
Publication statusPublished - 2013
Externally publishedYes
Event16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - Nagoya, Japan
Duration: 22 Sep 201326 Sep 2013
Conference number: 16

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013
Abbreviated titleMICCAI 2013


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