Journal of Digital Imaging

, Volume 24, Issue 2, pp 322–330

Accuracy of an Automatic Patient-Positioning System Based on the Correlation of Two Edge Images in Radiotherapy


    • Proton Therapy CenterNational Cancer Center
  • Minho Cheong
    • Proton Therapy CenterNational Cancer Center
  • Jinsung Kim
    • Department of Radiation OncologySamsung Medical Center
  • Dong Ho Shin
    • Proton Therapy CenterNational Cancer Center
  • Sung Yong Park
    • Proton Therapy CenterNational Cancer Center
  • Se Byeong Lee
    • Proton Therapy CenterNational Cancer Center

DOI: 10.1007/s10278-009-9269-6

Cite this article as:
Yoon, M., Cheong, M., Kim, J. et al. J Digit Imaging (2011) 24: 322. doi:10.1007/s10278-009-9269-6


We have clinically evaluated the accuracy of an automatic patient-positioning system based on the image correlation of two edge images in radiotherapy. Ninety-six head & neck images from eight patients undergoing proton therapy were compared with a digitally reconstructed radiograph (DRR) of planning CT. Two edge images, a reference image and a test image, were extracted by applying a Canny edge detector algorithm to a DRR and a 2D X-ray image, respectively, of each patient before positioning. In a simulation using a humanoid phantom, performed to verify the effectiveness of the proposed method, no registration errors were observed for given ranges of rotation, pitch, and translation in the x, y, and z directions. For real patients, however, there were discrepancies between the automatic positioning method and manual positioning by physicians or technicians. Using edged head coronal- and sagittal-view images, the average differences in registration between these two methods for the x, y, and z directions were 0.11 cm, 0.09 cm and 0.11 cm, respectively, whereas the maximum discrepancies were 0.34 cm, 0.38 cm, and 0.50 cm, respectively. For rotation and pitch, the average registration errors were 0.95° and 1.00°, respectively, and the maximum errors were 3.6° and 2.3°, respectively. The proposed automatic patient-positioning system based on edge image comparison was relatively accurate for head and neck patients. However, image deformation during treatment may render the automatic method less accurate, since the test image many differ significantly from the reference image.

Key words

Automated object detectionradiotherapydigital image processing

Copyright information

© Society for Imaging Informatics in Medicine 2010