Literature DB >> 31467458

A 3D Neurovascular Bundles Segmentation Method based on MR-TRUS Deformable Registration.

Xiaofeng Yang1, Peter Rossi1, Ashesh B Jani1, Hui Mao2, Tomi Ogunleye1, Walter J Curran1, Tian Liu1.   

Abstract

In this paper, we propose a 3D neurovascular bundles (NVB) segmentation method for ultrasound (US) image by integrating MR and transrectal ultrasound (TRUS) images through MR-TRUS deformable registration. First, 3D NVB was contoured by a physician in MR images, and the 3D MR-defined NVB was then transformed into US images using a MR-TRUS registration method, which models the prostate tissue as an elastic material, and jointly estimates the boundary deformation and the volumetric deformations under the elastic constraint. This technique was validated with a clinical study of 6 patients undergoing radiation therapy (RT) treatment for prostate cancer. The accuracy of our approach was assessed through the locations of landmarks, as well as previous ultrasound Doppler images of patients. MR-TRUS registration was successfully performed for all patients. The mean displacement of the landmarks between the post-registration MR and TRUS images was less than 2 mm, and the average NVB volume Dice Overlap Coefficient was over 89%. This NVB segmentation technique could be a useful tool as we try to spare the NVB in prostate RT, monitor NVB response to RT, and potentially improve post-RT potency outcomes.

Entities:  

Keywords:  MRI-US registration; Neurovascular bundles (NVB); erectile dysfunction; segmentation

Year:  2015        PMID: 31467458      PMCID: PMC6715139          DOI: 10.1117/12.2077828

Source DB:  PubMed          Journal:  Proc SPIE Int Soc Opt Eng        ISSN: 0277-786X


  1 in total

1.  Domain adaptation for segmentation of critical structures for prostate cancer therapy.

Authors:  Anneke Meyer; Alireza Mehrtash; Marko Rak; Oleksii Bashkanov; Bjoern Langbein; Alireza Ziaei; Adam S Kibel; Clare M Tempany; Christian Hansen; Junichi Tokuda
Journal:  Sci Rep       Date:  2021-06-01       Impact factor: 4.379

  1 in total

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