ZHANG Huai-wen,HU Bo,WANG Yun-lai.Automatic detection algorithm of the diaphragm motion based on Canny edge detection and wavelet transform[J].Chinese Journal of Radiological Medicine and Protection,2013,33(2):158-162
Automatic detection algorithm of the diaphragm motion based on Canny edge detection and wavelet transform
Received:November 06, 2012  
DOI:10.3760/cma.j.issn.0254-5098.2013.02.012
KeyWords:Image-guided radiotherapy  Respiratory motion  Wavelet transform  Canny edge detection algorithm
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Author NameAffiliationE-mail
ZHANG Huai-wen Department of Radiotherapy,Jiangxi Province Tumor Hospital,Nanchang 330029, China  
HU Bo 南昌航空大学无损检测技术教育部重点实验室  
WANG Yun-lai 解放军总医院放疗科 nanyangwang@163.com 
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Abstract::
      Objective To develop a new automatic detection algorithm of the diaphragm motion based on Canny edge detection and wavelet transform. Methods On-line fluoroscopic images under free breathing were enhanced by using the wavelet transform. After the wavelet transform, edge detection was carried out for the enhanced image. Canny edge detection algorithm was used to achieve the diaphragm edge. Programs were written in Matlab to track the position of the diaphragm. The diaphragm movement curves were derived to evaluate the characteristics of patients respiratory motion. Results Under calm free breathing,the amplitude and period of diaphragm motion acquired by means of the wavelet transform and Canny edge detection were in good agreement with manual measurement. There were six to seven respiratory cycles in a XVI Motion-ViewTM. The magnitude of diaphragm movement was not exactly the same in the cranio-caudal (CC) direction. The magnitude was from 6.7 mm to 8.0 mm with an average of 7.4 mm. The movements of the respiratory motion cycles had little variations in amplitude and period for the same patient between fractions except emotional excitement or cough. Conclusions The automatic diaphragm detection methods developed in this paper are precise, and can effectively reflect the characteristics of the respiratory motion. The method can save much time and improve the measure precision greatly compared with the manual measurement.
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