본문 바로가기
KERD
논문KCI 등재

치과 임플란트 치료를 위한 평행광 CT의 움직임 에러 수정

Correction of Movement Error in Parallel-beam CT for Dental Implantology

1

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

The purpose of this study is to correct the errors that may occur because of the patients' movement during the CT scanning, and thus, to obtain more precise CT images, additionally to investigate the possible use of parallel Beam CT in the dental treatment. Materials and Methods: Applying the Radon transform using phantom image, the same image and the sinogram with the ones by CT scanning were obtained. The possible movement errors that patients may cause during the CT scan were given to the data images. The maximum width of errors was designed to reach 1 mm. The fixed point was identified in the errored CT projected images, and each projected image with errors was adjusted so that each fixed point is placed on the same axial plane, then the fixed point was traced on the sinogram. On the traced trajectory of the fixed point, the part deviated from the sinusoidal curve was modified using the Virtual Alignment Method. Results: The quality of reconstructed image was remarkably degraded when the movement errors were given. The movement errors were corrected by moving the fixed point to the center of sinogram and this relocation of fixed point did not cause any distortion of image or change of size. Conclusion: The movement errors during CT scanning were corrected using the fixed point inside of the image. The more precise CT images obtained through this method are expected to be of extensive application in the area of dental implantology.

Abstract

The purpose of this study is to correct the errors that may occur because of the patients' movement during the CT scanning, and thus, to obtain more precise CT images, additionally to investigate the possible use of parallel Beam CT in the dental treatment. Materials and Methods: Applying the Radon transform using phantom image, the same image and the sinogram with the ones by CT scanning were obtained. The possible movement errors that patients may cause during the CT scan were given to the data images. The maximum width of errors was designed to reach 1 mm. The fixed point was identified in the errored CT projected images, and each projected image with errors was adjusted so that each fixed point is placed on the same axial plane, then the fixed point was traced on the sinogram. On the traced trajectory of the fixed point, the part deviated from the sinusoidal curve was modified using the Virtual Alignment Method. Results: The quality of reconstructed image was remarkably degraded when the movement errors were given. The movement errors were corrected by moving the fixed point to the center of sinogram and this relocation of fixed point did not cause any distortion of image or change of size. Conclusion: The movement errors during CT scanning were corrected using the fixed point inside of the image. The more precise CT images obtained through this method are expected to be of extensive application in the area of dental implantology.

참고문헌 (26)

  1. Pauwels R, "Technical aspects of dental CBCT : state of the art", Dentomaxillofa Radiol, 44, pp.20140224~ (2015)
  2. Lingyun C, "Spatial resolution properties in cone beam CT : A simulation study", Med Phys, 35, pp.724~734 (2008)
  3. Doga G, "TomoPy : a framework for the analysis of synchrotron tomographic data", J Synchrotron Rad, 21, pp.1188~1193 (2014)
  4. Chien CC, "X-ray imaging of tumor growth in live mice by detecting gold-nanoparticle-loaded cells", Sci Rep, 2, pp.610~ (2012)
  5. Kamburoğlu K, "Occlusal caries detection by using a cone-beam CT with different voxel resolutions and a digital intraoral sensor", Oral Surg Oral Med Oral Pathol Oral Radiol Endod, 109, pp.e63~e69 (2010)
  6. Pickhardt PJ, "Colorectal cancer : CT colonography and colonoscopy for detection—systematic review and meta-analysis", Radiology, 259, pp.393~405 (2011)
  7. Parkinson DY, "Automatic alignment and reconstruction of images for soft X-ray tomography", J Struct Bio, 177, pp.259~266 (2012)
  8. José LC, "Cryo-X-ray tomography of vaccinia virus membranes and inner compartments", J Struct Bio, 168, pp.234~239 (2009)
  9. Marco S, "High resolution x-ray detector for synchrotron-based microtomography", Nucl Instrum Methods Phys Res A, 491, pp.291~301 (2002)
  10. Watanabe H, "A comparative study for spatial resolution and subjective image characteristics of a multi-slice CT and a cone-beam CT for dental use", Eur J Radiol, 77, pp.397~402 (2011)
  11. Hengyong Y, "Data consistency based rigid motion artifact reduction in fan-beam CT", IEEE Trans Med Imaging, 26, pp.249~260 (2007)
  12. Brüllmann D, "Spatial resolution in CBCT machines for dental", maxillofacial applications-what do we know today?, 2015, pp.44, 20140204~
  13. Schulze R, "Artefacts in CBCT : a review", Dentomaxillofac Radiol, 40, pp.265~273 (2011)
  14. Donaldson K, "Dental cone beam CT image quality possibly reduced by patient movement", Dentomaxillofac Radiol, 42, pp.91866873~ (2013)
  15. Spin-Neto R, "Radiographic observers’ability to recognize patient movement during cone beam CT", Dentomaxillofac Radiol, 43, pp.20130449~ (2014)
  16. Jing W, "Iterative image reconstruction for CBCT using edge-preserving prior", Medical Physics, 36, pp.252~260 (2009)
  17. Sun T, "Iterative CBCT reconstruction using Hessian penalty", Phys Med Biol, 60, pp.1965~1987 (2015)
  18. 임재홍, "Station for structural studies on macro objects: beamline 6C Bio Medical Imaging at the Pohang Light Source-II", Biodesign, 5(2), pp.53~61 (2017), 한국구조생물학회
  19. Donath T, "Automated determination of the center of rotation in tomography data", J Opt Soc Am A Opt Image Sci Vis, 23, pp.1048~1057 (2006)
  20. Cheng CC, "Correction of center of rotation and projection angle in synchrotron X-ray computed tomography", Sci Rep, 8, pp.9884~ (2018)
  21. Jun K, "Alignment solution for CT image reconstruction using fixed point and virtual rotation axis", Sci Rep, 7, pp.41218~ (2017)
  22. Jun K, "Virtual multi-alignment theory of parallel-beam CT image reconstruction for rigid objects", Sci Rep, 9, pp.13518~ (2019)
  23. Jun K, "Virtual multi-alignment theory of parallel-beam CT image reconstruction for elastic objects", Sci Rep, 9, pp.6847~ (2019)
  24. Yixing H, "Restoration of missing data in limited angle tomography based on Helgason–Ludwig consistency conditions", Biomed phys Eng Express, 3, pp.3~ (2017)
  25. Kourosh JK, "Radon transform orientation estimation for rotation invariant texture analysis", IEEE Trans Pattern Anal Mach Intell, 27, pp.1004~1008 (2005)
  26. Xia Y, "An improved extrapolation scheme for truncated CT data using 2D fourier-based helgason-ludwig consistency conditions", Int J Biomed Imaging, 2017, pp.1867025~ (2017)

관련 논문AI추천

이 간행물의 다른 논문 (4건)