3D-3D tubular organs registration based on bifurcations for the CT images

Jinghao Zhou, Sukmoon Chang, Dimitris Metaxas, Gig Mageras

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The registration of tubular organs (pulmonary tracheobronchial tree or vasculature) of 3D medical images is critical in various clinical applications such as surgical planning and radiotherapy. In this paper, we present a novel method for tubular organs registration based on the automatically detected bifurcation points of the tubular organs. We first perform a 3D tubular organ segmentation method to extract the centerlines of tubular organs and radius estimation in both planning and respiration-correlated CT (RCCT) images. This segmentation method automatically detects the bifurcation points by applying Adaboost algorithm with specially designed filters. We then apply a rigid registration method which minimizes the least square error of the corresponding bifurcation points between the planning CT images and the respiration-correlated CT images. Our method has over 96 % success rate for detecting bifurcation points. We present very promising results of our method applied to the registration of the planning and respiration-correlated CT images. On average, the mean distance and the root-meansquare error (RMSE) of the corresponding bifurcation points between the respiration-correlated images and the registered planning images are less than 2.7 mm.

Original languageEnglish (US)
Title of host publicationProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Pages5394-5397
Number of pages4
StatePublished - Dec 1 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: Aug 20 2008Aug 25 2008

Publication series

NameProceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology"

Other

Other30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
CountryCanada
CityVancouver, BC
Period8/20/088/25/08

Fingerprint

Planning
Respiration
Adaptive boosting
Bifurcation (mathematics)
Radiotherapy
Least-Squares Analysis
Lung

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

Zhou, J., Chang, S., Metaxas, D., & Mageras, G. (2008). 3D-3D tubular organs registration based on bifurcations for the CT images. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 (pp. 5394-5397). [4650434] (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").
Zhou, Jinghao ; Chang, Sukmoon ; Metaxas, Dimitris ; Mageras, Gig. / 3D-3D tubular organs registration based on bifurcations for the CT images. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. pp. 5394-5397 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").
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abstract = "The registration of tubular organs (pulmonary tracheobronchial tree or vasculature) of 3D medical images is critical in various clinical applications such as surgical planning and radiotherapy. In this paper, we present a novel method for tubular organs registration based on the automatically detected bifurcation points of the tubular organs. We first perform a 3D tubular organ segmentation method to extract the centerlines of tubular organs and radius estimation in both planning and respiration-correlated CT (RCCT) images. This segmentation method automatically detects the bifurcation points by applying Adaboost algorithm with specially designed filters. We then apply a rigid registration method which minimizes the least square error of the corresponding bifurcation points between the planning CT images and the respiration-correlated CT images. Our method has over 96 {\%} success rate for detecting bifurcation points. We present very promising results of our method applied to the registration of the planning and respiration-correlated CT images. On average, the mean distance and the root-meansquare error (RMSE) of the corresponding bifurcation points between the respiration-correlated images and the registered planning images are less than 2.7 mm.",
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Zhou, J, Chang, S, Metaxas, D & Mageras, G 2008, 3D-3D tubular organs registration based on bifurcations for the CT images. in Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08., 4650434, Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology", pp. 5394-5397, 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08, Vancouver, BC, Canada, 8/20/08.

3D-3D tubular organs registration based on bifurcations for the CT images. / Zhou, Jinghao; Chang, Sukmoon; Metaxas, Dimitris; Mageras, Gig.

Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. p. 5394-5397 4650434 (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - The registration of tubular organs (pulmonary tracheobronchial tree or vasculature) of 3D medical images is critical in various clinical applications such as surgical planning and radiotherapy. In this paper, we present a novel method for tubular organs registration based on the automatically detected bifurcation points of the tubular organs. We first perform a 3D tubular organ segmentation method to extract the centerlines of tubular organs and radius estimation in both planning and respiration-correlated CT (RCCT) images. This segmentation method automatically detects the bifurcation points by applying Adaboost algorithm with specially designed filters. We then apply a rigid registration method which minimizes the least square error of the corresponding bifurcation points between the planning CT images and the respiration-correlated CT images. Our method has over 96 % success rate for detecting bifurcation points. We present very promising results of our method applied to the registration of the planning and respiration-correlated CT images. On average, the mean distance and the root-meansquare error (RMSE) of the corresponding bifurcation points between the respiration-correlated images and the registered planning images are less than 2.7 mm.

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Zhou J, Chang S, Metaxas D, Mageras G. 3D-3D tubular organs registration based on bifurcations for the CT images. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. p. 5394-5397. 4650434. (Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - "Personalized Healthcare through Technology").