Literature DB >> 16751077

Evaluation of similarity measures for reconstruction-based registration in image-guided radiotherapy and surgery.

Darko Skerl1, Dejan Tomazevic, Bostjan Likar, Franjo Pernus.   

Abstract

PURPOSE: A promising patient positioning technique is based on registering computed tomographic (CT) or magnetic resonance (MR) images to cone-beam CT images (CBCT). The extra radiation dose delivered to the patient can be substantially reduced by using fewer projections. This approach results in lower quality CBCT images. The purpose of this study is to evaluate a number of similarity measures (SMs) suitable for registration of CT or MR images to low-quality CBCTs. METHODS AND MATERIALS: Using the recently proposed evaluation protocol, we evaluated nine SMs with respect to pretreatment imaging modalities, number of two-dimensional (2D) images used for reconstruction, and number of reconstruction iterations. The image database consisted of 100 X-ray and corresponding CT and MR images of two vertebral columns.
RESULTS: Using a higher number of 2D projections or reconstruction iterations results in higher accuracy and slightly lower robustness. The similarity measures that behaved the best also yielded the best registration results. The most appropriate similarity measure was the asymmetric multi-feature mutual information (AMMI).
CONCLUSIONS: The evaluation protocol proved to be a valuable tool for selecting the best similarity measure for the reconstruction-based registration. The results indicate that accurate and robust CT/CBCT or even MR/CBCT registrations are possible if the AMMI similarity measure is used.

Entities:  

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Year:  2006        PMID: 16751077     DOI: 10.1016/j.ijrobp.2006.03.005

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  7 in total

1.  Assessing the intrinsic precision of 3D/3D rigid image registration results for patient setup in the absence of a ground truth.

Authors:  Jian Wu; Martin J Murphy
Journal:  Med Phys       Date:  2010-06       Impact factor: 4.071

2.  A multistage registration method using texture features.

Authors:  Andreja Jarc; Janez Pers; Stanislav Kovacic
Journal:  J Digit Imaging       Date:  2009-01-29       Impact factor: 4.056

3.  A digitally reconstructed radiograph algorithm calculated from first principles.

Authors:  David Staub; Martin J Murphy
Journal:  Med Phys       Date:  2013-01       Impact factor: 4.071

4.  A neural network based 3D/3D image registration quality evaluator for the head-and-neck patient setup in the absence of a ground truth.

Authors:  Jian Wu; Martin J Murphy
Journal:  Med Phys       Date:  2010-11       Impact factor: 4.071

5.  Validation for 2D/3D registration. I: A new gold standard data set.

Authors:  S A Pawiro; P Markelj; F Pernus; C Gendrin; M Figl; C Weber; F Kainberger; I Nöbauer-Huhmann; H Bergmeister; M Stock; D Georg; H Bergmann; W Birkfellner
Journal:  Med Phys       Date:  2011-03       Impact factor: 4.071

6.  Registration of 2D C-Arm and 3D CT Images for a C-Arm Image-Assisted Navigation System for Spinal Surgery.

Authors:  Chih-Ju Chang; Geng-Li Lin; Alex Tse; Hong-Yu Chu; Ching-Shiow Tseng
Journal:  Appl Bionics Biomech       Date:  2015-05-28       Impact factor: 1.781

7.  Comparison of automatic image registration uncertainty for three IGRT systems using a male pelvis phantom.

Authors:  Jeffrey Barber; Jonathan R Sykes; Lois Holloway; David I Thwaites
Journal:  J Appl Clin Med Phys       Date:  2016-09-08       Impact factor: 2.102

  7 in total

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