Study on registration algorithm for portal images and simulation images in megavolt radiotherapy
10.3760/cma.j.issn.1004-4221.2010.03.023
- VernacularTitle:兆伏级放疗射野图像与模拟图像自动配准算法研究
- Author:
Cheng CHEN
;
Shaomin HUANG
;
Xiaowu DENG
;
Feng CHI
;
Li ZHANG
;
Lixin CHEN
- Publication Type:Journal Article
- Keywords:
Set-up errors;
Portal image;
Simulation images;
Image registration
- From:
Chinese Journal of Radiation Oncology
2010;19(3):256-260
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore a fast and precise registration algorithm for megavolt (MV) portal images(PIs) used for radiotherapy positioning verification, and find auto analysis method of set-up error using the computed image processing and mutual information comparison technology, which provide a basis for the development of automatic image guidance software. Methods MV PIs of patients undergoing radiotherapy were tested, pre-processed with noise reduction technique based on improved filtering algorithm and contrasted by gray-scale transforming using partial derivative threshold. The bone structures were then highlighted but soft tissues and the cavities were restrained simultaneously. Improved particle swarm optimization and powell hybrid algorithm were used to optimize and transform the mutual information based on wavelet multiresolution analysis when registering the Pls with digital reconstructed radiographs (DRRs) of treatment planning or X-ray simulation-film images(SIs). Application of the designed registration algorithm was verified and evaluated through simulated set-up shifts of head and neck phantom. Results The improved noise reduction algorithm satisfactorily met the requirements for contrast of bony structures in the MV PIs. The established mutual information registration method well behaved in both accuracy and speed of registration calculation. The processing of automatic registration took only 31.4 seconds averagely for the PIs and X-ray Sis of head-neck phantom. Mean errors of automatic registration of PIs and X-ray Sis in horizontal, vertical and rotational reduced by 62. 74% ,67. 32% and 66. 61% respectively compared with manual registration in the testing of 20-cases head and neck phantom. Conclusions A precise image registration algorithm and set-up error analysis method based on MV portal images is established, and it can meet the clinical application in registration accuracy and speed.
