Journal of KIISE:Software and Applications (한국정보과학회논문지:소프트웨어및응용)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
권호 표지

Pulmonary Nodule Registration using Template Matching in Serial CT Scans

연속 CT 영상에서 템플릿 매칭을 이용한 폐결절 정합

  • 조현희 (서울여자대학교 미디어학부) ;
  • 홍헬렌 (서울여자대학교 미디어학부)
  • Published : 2009.08.15
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper, we propose a pulmonary nodule registration for the tracking of lung nodules in sequential CT scans. Our method consists of following five steps. First, a translational mismatch is corrected by aligning the center of optimal bounding volumes including each segmented lung. Second, coronal maximum intensity projection(MIP) images including a rib structure which has the highest intensity region in baseline and follow-up CT series are generated. Third, rigid transformations are optimized by normalized average density differences between coronal MIP images. Forth, corresponding nodule candidates are defined by Euclidean distance measure after rigid registration. Finally, template matching is performed between the nodule template in baseline CT image and the search volume in follow-up CT image for the nodule matching. To evaluate the result of our method, we performed the visual inspection, accuracy and processing time. The experimental results show that nodules in serial CT scans can be rapidly and correctly registered by coronal MIP-based rigid registration and local template matching.

본 논문에서는 연속시점에서 촬영한 CT 영상에서 대응되는 폐결절을 추적 관찰하기 위한 폐결절 정합 방법을 제안한다. 제안 방법은 다음과 같은 다섯 단계로 구생된다. 첫째, 분할된 폐를 포함하는 최적경계볼륨의 중심으로 위치 차이를 보정한다. 둘째, 초기 CT 영상과 추적 CT 영상에서 가장 높은 밝기값을 가지고 있는 갈비뼈 구조를 포함하는 관상최대강도투사 영상을 생성한다. 셋째, 두 관상최대강도투사 영상 간의 정규화된 평균 밝기값 차이를 통해 강체 변환을 최적화한다. 넷째, 강체 정합 후에 폐결절 중심 간의 유클라디안 거리 측정을 통해 대응되는 폐결절 대응 후보를 정의한다. 마지막으로, 폐결절을 매칭하기 위하여 초기 CT 영상 내에 폐결절 템플릿과 추적 CT 영상 내에 탐색 볼륨 간의 템플릿 매칭을 수행 한다. 본 제안 방법의 결과를 평가하기 위하여 육안 평가, 정확성 및 수행시간 측정을 수행하였다. 실험결과 관상최대강도투사를 기반으로 하는 강체정합과 지역적 템플릿 매칭을 이용하여 폐결절이 정확하고 빠르게 정합됨을 알 수 있었다.

Keywords

References

  1. M. Betke, H. Hong, J. P. Ko, 'Automatic 3D registration of lung surfaces in Computed Tomography Scans,' Fourth International Conference on Medical Image Computing and Computer-Assisted Intervention MICCAI, pp.725-733, 2001 https://doi.org/10.1007/3-540-45468-3
  2. M. Betke, H. Hong, D. Thomas, C. Prince, J. P. Ko, 'Landmark detection in the chest and registration of lung surfaces with an application to nodule registration,' Medical Image Analysis, vol.7, pp.265-281, 2003 https://doi.org/10.1016/S1361-8415(03)00007-0
  3. P. J. Besl and N. D. McKay, 'A method for registration of 3-D shapes,' IEEE Trans Pattern Anal Mach Intell, vol.14, no.2, pp.239-256, 1992 https://doi.org/10.1109/34.121791
  4. H. Hong, M. Betke, S. Teng, D. Thomas, J. P. Ko, 'Multilevel 3D Registration of Lung Surfaces in Computed Tomography Scans - Preliminary experience,' Proceedings of International Conference on Diagnostic Imaging and Analysis (ICDIA), pp.90-95, August 2002
  5. M. Kubo, T. Yamamoto, Y. Kawata, N. Niki, K. Eguchi, H. Ohmatsu, R. Kakinuma, M. Kaneko, M. Kusumoto, N. Moriyama, K. Mori, H. Nishiyama, 'CAD system for the assistance of a comparative reading for lung cancer using retrospective helical CT images,' MICCAI 2001, LNCS 2208, pp. 1388-1390, 2001
  6. M. N. Gurcan, R. C. Hardie, S. K. Rogers, D. E. Dozer, B. H. Allen, R. V. Burns, J. W. Hoffmeister, 'Automated global matching of temporal thoracic helical CT studies: feasibility study,' International Congress Series, vol.1256, pp.1031-1036, 2003 https://doi.org/10.1016/S0531-5131(03)00476-X
  7. Helen Hong, Jeongjin Lee, Yeny Yim, 'Automatic lung nodule matching on sequential CT images,' Computers in Biology and Medicine, vol.38, no.5, pp.623-634, 2008 https://doi.org/10.1016/j.compbiomed.2008.02.010
  8. S. Sun, G. Rubin, David Paik, Robert M. Steiner, Feng Zhuge, Sandy Napel, 'Registration of lung nodules using a semi-rigid model: Method and preliminary results,' Medical Physics, vol.34, no.2, pp.613-626, Feb. 2007 https://doi.org/10.1118/1.2432073
  9. Jiazheng Shi, Berkman Sahiner, Heang-Ping Chan, Lubomir Hadjiiski, Chuan Zhou, Yi-Ta Wu, Jun Wei, 'Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching,' Medical Physics, vol.34, no.4, pp.1336-1347, April 2007 https://doi.org/10.1118/1.2712575
  10. Jiazheng Shi, Berkman Sahiner, Heang-Ping Chan, Lubomir Hadjiiski, Chuan Zhou, Yi-Ta Wu, Jun Wei, 'Pulmonary Nodule Registration in Serial CT Scans Using Rib Anatomy and Nodule Template Matching,' Proceeding of SPIE, vol.6514, pp.65140R.1-65140R.9, 2007 https://doi.org/10.1117/12.713409
  11. W. Mullally, M. Betke, H. Hong, J. Wang, K. Mann, J. P. Ko, 'Multi-criterion 3D segmentation and registration of pulmonary nodules on CT: a preliminary investigation,' International Conference on Diagnostic Imaging and Analysis, pp.176-181, 2002
  12. Yoshinori Itai, Hyoungseop Kim, Seiji Ishikawa, Shigehiko Katsuragawa, Kunio Doi, 'A New Registration Method with Voxel-Matching Technique for Temporal Subtraction Images,' Proc. of SPIE, vol.6915, pp.69153I.1-69153I.8, 2008 https://doi.org/10.1117/12.769921
  13. Yoshinori Itai, Hyoungseop Kim, Seiji Ishikawa, Shigehiko Katsuragawa, Takayuki Ishida, Ikuo Kawashita, Kazuo Awai, Qiang Li, Kunio Doi, '3-D Elastic Matching Technique for Temporal Subtraction Employing Thorax MDCT Images,' Proc. of the World Congress on Medical Physics and Biomedical Engineering, vol.14, pp.2188-2191, 2006
  14. Helen Hong, J. J. Lee, Yeny Yim, 'Automatic lung nodule matching on sequential CT images,' Computers in Biology and Medicine, vol.38, no.5, pp.623-634, 2008 https://doi.org/10.1016/j.compbiomed.2008.02.010
  15. Yeny Yim, Helen Hong, 'Correction of segmented lung boundary for inclusion of pleural nodules and pulmonary vessels in chest CT images,' Computers in Biology and Medicine, vol.38, no.8, pp.845-857, 2008
  16. William H. Press, Brian P. Flannery, 'Numerical Recipes in C - Second Edition,' Cambridge Univ. Press, pp.412-414, 1992