Literature DB >> 1584126

Correlation of projection radiographs in radiation therapy using open curve segments and points.

J M Balter1, C A Pelizzari, G T Chen.   

Abstract

A method for determining differences in patient position between projection radiographs such as those routinely used in radiation therapy has been developed. Determination of a transformation relating two radiographs permits registration of simulation and portal images and the transfer of information between them. The algorithm is based on spatially registering segments of open curves or points seen on both images, and does not require identification of corresponding curve endpoints. The method as implemented is both fast and accurate. After user definition of the curves or points to be registered, the optimal transformation is calculated in approximately 1 s. Calculational experiments indicate that corresponding points on open curves are registered to better than 2 mm, even when random errors (FWHM 1 mm) in digitization are included. Experiments on the registration of clinical portal and simulation images (pixel size = 0.5 by 0.5 mm) indicate an accuracy on the order of 2 mm or less in translation and 2 deg or less in rotation. Analysis of portal and simulation radiographs of the brain, thorax, and pelvis indicates this algorithm to be robust and clinically applicable. The rapid and accurate registration of portal and simulation images is potentially important in the application of real time portal imaging devices in radiation therapy.

Entities:  

Mesh:

Year:  1992        PMID: 1584126     DOI: 10.1118/1.596863

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  10 in total

1.  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

2.  A frequency-based approach to locate common structure for 2D-3D intensity-based registration of setup images in prostate radiotherapy.

Authors:  Reshma Munbodh; Zhe Chen; David A Jaffray; Douglas J Moseley; Jonathan P S Knisely; James S Duncan
Journal:  Med Phys       Date:  2007-07       Impact factor: 4.071

3.  Automated 2D-3D registration of portal images and CT data using line-segment enhancement.

Authors:  Reshma Munbodh; Zhe Chen; David A Jaffray; Douglas J Moseley; Jonathan P S Knisely; James S Duncan
Journal:  Med Phys       Date:  2008-10       Impact factor: 4.071

4.  Technical note: deformable image registration on partially matched images for radiotherapy applications.

Authors:  Deshan Yang; S Murty Goddu; Wei Lu; Olga L Pechenaya; Yu Wu; Joseph O Deasy; Issam El Naqa; Daniel A Low
Journal:  Med Phys       Date:  2010-01       Impact factor: 4.071

5.  Verifying radiotherapy treatment setup by interactive image registration.

Authors:  A A Boxwala; E L Chaney; C P Friedman
Journal:  Proc AMIA Annu Fall Symp       Date:  1996

6.  A gradient feature weighted Minimax algorithm for registration of multiple portal images to 3DCT volumes in prostate radiotherapy.

Authors:  Sudhakar Chelikani; Kailasnath Purushothaman; Jonathan Knisely; Zhe Chen; Ravinder Nath; Ravi Bansal; James Duncan
Journal:  Int J Radiat Oncol Biol Phys       Date:  2006-06-01       Impact factor: 7.038

7.  A fast inverse consistent deformable image registration method based on symmetric optical flow computation.

Authors:  Deshan Yang; Hua Li; Daniel A Low; Joseph O Deasy; Issam El Naqa
Journal:  Phys Med Biol       Date:  2008-10-14       Impact factor: 3.609

8.  Guide to clinical use of electronic portal imaging.

Authors:  M G Herman; J J Kruse; C R Hagness
Journal:  J Appl Clin Med Phys       Date:  2000       Impact factor: 2.102

9.  Automatic Marker-free Longitudinal Infrared Image Registration by Shape Context Based Matching and Competitive Winner-guided Optimal Corresponding.

Authors:  Chia-Yen Lee; Hao-Jen Wang; Jhih-Hao Lai; Yeun-Chung Chang; Chiun-Sheng Huang
Journal:  Sci Rep       Date:  2017-02-01       Impact factor: 4.379

10.  Evaluation of Radiomics to Predict the Accuracy of Markerless Motion Tracking of Lung Tumors: A Preliminary Study.

Authors:  Kevin Nguyen; Maksat Haytmyradov; Hassan Mostafavi; Rakesh Patel; Murat Surucu; Alec Block; Matthew M Harkenrider; John C Roeske
Journal:  Front Oncol       Date:  2018-07-31       Impact factor: 6.244

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.