Literature DB >> 9845314

A comparison of similarity measures for use in 2-D-3-D medical image registration.

G P Penney1, J Weese, J A Little, P Desmedt, D L Hill, D J Hawkes.   

Abstract

A comparison of six similarity measures for use in intensity-based two-dimensional-three-dimensional (2-D-3-D) image registration is presented. The accuracy of the similarity measures are compared to a "gold-standard" registration which has been accurately calculated using fiducial markers. The similarity measures are used to register a computed tomography (CT) scan of a spine phantom to a fluoroscopy image of the phantom. The registration is carried out within a region-of-interest in the fluoroscopy image which is user defined to contain a single vertebra. Many of the problems involved in this type of registration are caused by features which were not modeled by a phantom image alone. More realistic "gold-standard" data sets were simulated using the phantom image with clinical image features overlaid. Results show that the introduction of soft-tissue structures and interventional instruments into the phantom image can have a large effect on the performance of some similarity measures previously applied to 2-D-3-D image registration. Two measures were able to register accurately and robustly even when soft-tissue structures and interventional instruments were present as differences between the images. These measures were pattern intensity and gradient difference. Their registration accuracy, for all the rigid-body parameters except for the source to film translation, was within a root-mean-square (rms) error of 0.54 mm or degrees to the "gold-standard" values. No failures occurred while registering using these measures.

Mesh:

Year:  1998        PMID: 9845314     DOI: 10.1109/42.730403

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  92 in total

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Journal:  Med Phys       Date:  2010-06       Impact factor: 4.071

4.  New hybrid stochastic-deterministic technique for fast registration of dermatological images.

Authors:  S A Pavlopoulos
Journal:  Med Biol Eng Comput       Date:  2004-11       Impact factor: 2.602

5.  Automated 2D-3D registration of a radiograph and a cone beam CT using line-segment enhancement.

Authors:  Reshma Munbodh; David A Jaffray; Douglas J Moseley; Zhe Chen; Jonathan P S Knisely; Pascal Cathier; James S Duncan
Journal:  Med Phys       Date:  2006-05       Impact factor: 4.071

6.  3D/2D model-to-image registration applied to TIPS surgery.

Authors:  Julien Jomier; Elizabeth Bullitt; Mark Van Horn; Chetna Pathak; Stephen R Aylward
Journal:  Med Image Comput Comput Assist Interv       Date:  2006

7.  A Statistical Model for Rigid Image Registration Performance: The Influence of Soft-Tissue Deformation as a Confounding Noise Source.

Authors:  Michael D Ketcha; Tharindu De Silva; Runze Han; Ali Uneri; Sebastian Vogt; Gerhard Kleinszig; Jeffrey H Siewerdsen
Journal:  IEEE Trans Med Imaging       Date:  2019-03-27       Impact factor: 10.048

8.  Measuring the axial rotation of lumbar vertebrae in vivo with MR imaging.

Authors:  Victor M Haughton; Baxter Rogers; M Elizabeth Meyerand; Daniel K Resnick
Journal:  AJNR Am J Neuroradiol       Date:  2002-08       Impact factor: 3.825

9.  Pose Estimation of Periacetabular Osteotomy Fragments With Intraoperative X-Ray Navigation.

Authors:  Robert B Grupp; Rachel A Hegeman; Ryan J Murphy; Clayton P Alexander; Yoshito Otake; Benjamin A McArthur; Mehran Armand; Russell H Taylor
Journal:  IEEE Trans Biomed Eng       Date:  2019-05-06       Impact factor: 4.538

Review 10.  Spinal radiosurgery: technology and clinical outcomes.

Authors:  M Avanzo; P Romanelli
Journal:  Neurosurg Rev       Date:  2008-09-24       Impact factor: 3.042

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