Literature DB >> 25906944

Precision of image-based registration for intraoperative navigation in the presence of metal artifacts: Application to corrective osteotomy surgery.

J G G Dobbe1, F Curnier2, X Rondeau2, G J Streekstra3.   

Abstract

Navigation for corrective osteotomy surgery requires patient-to-image registration. When registration is based on intraoperative 3-D cone-beam CT (CBCT) imaging, metal landmarks may be used that deteriorate image quality. This study investigates whether metal artifacts influence the precision of image-to-patient registration, either with or without intermediate user intervention during the registration procedure, in an application for corrective osteotomy of the distal radius. A series of 3-D CBCT scans is made of a cadaver arm with and without metal landmarks. Metal artifact reduction (MAR) based on inpainting techniques is used to improve 3-D CBCT images hampered by metal artifacts. This provides three sets of images (with metal, with MAR, and without metal), which enable investigating the differences in precision of intraoperative registration. Gray-level based point-to-image registration showed a better correlation coefficient if intraoperative images with MAR are used, indicating a better image similarity. The precision of registration without intermediate user intervention during the registration procedure, expressed as the residual angulation and displacement error after repetitive registration was very low and showed no improvement when MAR was used. By adding intermediate user intervention to the registration procedure however, precision was very high but was not affected by the presence of metal artifacts in the specific application.
Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Computer-assistance; Cone-beam CT; Metal artifacts; Navigation; Registration

Mesh:

Substances:

Year:  2015        PMID: 25906944     DOI: 10.1016/j.medengphy.2015.03.008

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  2 in total

1.  A hybrid feature-based patient-to-image registration method for robot-assisted long bone osteotomy.

Authors:  Chunlei Zhang; Yu Liu; Yunguang Zhang; He Li
Journal:  Int J Comput Assist Radiol Surg       Date:  2021-06-26       Impact factor: 2.924

2.  GPU accelerated voxel-driven forward projection for iterative reconstruction of cone-beam CT.

Authors:  Yi Du; Gongyi Yu; Xincheng Xiang; Xiangang Wang
Journal:  Biomed Eng Online       Date:  2017-01-05       Impact factor: 2.819

  2 in total

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