Combining Different Reconstruction Kernel Responses as Preprocessing Step for Airway Tree Extraction in CT Scan

Samah Bouzidi, Fabien Baldacci, Chokri ben Amar, Pascal Desbarats

2017

Abstract

In this paper, we propose a new preprocessing procedure that combines the responses of different Computed Tomography (CT) reconstruction kernels in order to improve the segmentation of the airway tree. These filters are available in all commercial CT scanner. A broad range of preprocessing techniques have been proposed but all of them operate on images reconstructed using a single reconstruction filter. In this work, the new preprocessing approach is based on a fusion of images reconstructed using different reconstruction kernels and can be included as a preprocessing stage in every segmentation pipeline. Our approach has been applied on various CT scans and an experimental comparison study between state of the art of segmentation approaches results performed on processed and unprocessed data has been made. Results show that the fusion process improves segmentation results and removes false positives.

References

  1. Aykac, D., Hoffman, E. A., McLennan, G., and Reinhardt, J. M. (2003). Segmentation and analysis of the human airway tree from three-dimensional x-ray CT images. Medical Imaging, IEEE Transactions on, 22(8):940- 950.
  2. Bouzidi, S., Baldacci, F., Amar, C. B., and Desbarats, P. (2016). 3D segmentation of the tracheobronchial tree using multiscale morphology enhancement filter. In Proc. of 24th International Conference on Computer Graphics, Visualization and Computer Vision, pages 207-214.
  3. FabijaÁska, A. (2009). Two-pass region growing algorithm for segmenting airway tree from MDCT chest scans. Computerized Medical Imaging and Graphics, 33(7):537-546.
  4. Fetita, C. I., Grenier, P., et al. (1999). Modeling, segmentation, and caliber estimation of bronchi in high resolution computerized tomography. Journal of Electronic Imaging, 8(1):36-45.
  5. Frangi, A. F., Niessen, W. J., Vincken, K. L., and Viergever, M. A. (1998). Multiscale vessel enhancement filtering. In Medical Image Computing and ComputerAssisted Interventation MICCAI98, pages 130-137. Springer.
  6. Irving, B., Taylor, P., and Todd-Pokropek, A. (2009). 3D segmentation of the airway tree using a morphology based method. In Proceedings of 2nd international workshop on pulmonary image analysis, pages 297- 07.
  7. Kitasaka, T., Mori, K., Suenaga, Y., Hasegawa, J.-i., and Toriwaki, J.-i. (2003). A method for segmenting bronchial trees from 3Dchest x-ray ct images. In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 603-610. Springer.
  8. Krissian, K., Malandain, G., Ayache, N., Vaillant, R., and Trousset, Y. (2000). Model-based detection of tubular structures in 3D images. Computer vision and image understanding, 80(2):130-171.
  9. Lo, P., Sporring, J., Pedersen, J. J. H., and de Bruijne, M. (2009). Airway tree extraction with locally optimal paths. In Medical Image Computing and ComputerAssisted Intervention, MICCAI 2009, pages 51-58. Springer.
  10. Lo, P., Van Ginneken, B., Reinhardt, J. M., Yavarna, T., De Jong, P. A., Irving, B., Fetita, C., Ortner, M., Pinho, R., Sijbers, J., et al. (2012). Extraction of airways from CT (exact'09). Medical Imaging, IEEE Transactions on, 31(11):2093-2107.
  11. Montaudon, M., Desbarats, P., Berger, P., De Dietrich, G., Marthan, R., and Laurent, F. (2007). Assessment of bronchial wall thickness and lumen diameter in human adults using multi-detector computed tomography: comparison with theoretical models. Journal of anatomy, 211(5):579-588.
  12. Mori, K., Hasegawa, J.-i., Toriwaki, J.-i., Anno, H., and Katada, K. (1996). Recognition of bronchus in threedimensional x-ray CT images with applications to virtualized bronchoscopy system. In Pattern Recognition, 1996., Proceedings of the 13th International Conference on, volume 3, pages 528-532. IEEE.
  13. Otsu, N. (1975). A threshold selection method from graylevel histograms. Automatica, 11(285-296):23-27.
  14. Pisupati, C., Wolff, L., Zerhouni, E., and Mitzner, W. (1996). Segmentation of 3D pulmonary trees using mathematical morphology. In Mathematical morphology and its applications to image and signal processing, pages 409-416. Springer.
  15. Pu, J., Gu, S., Liu, S., Zhu, S., Wilson, D., Siegfried, J. M., and Gur, D. (2012). CT based computerized identification and analysis of human airways: a review. Medical physics, 39(5):2603-2616.
  16. Sato, Y., Nakajima, S., Atsumi, H., Koller, T., Gerig, G., Yoshida, S., and Kikinis, R. (1997). 3D multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. In CVRMedMRCAS'97, pages 213-222. Springer.
  17. Weibel, E. R. and Gomez, D. M. (1962). Architecture of the human lung. Science, 137(3530):577-585.
  18. Weinheimer, O., Achenbach, T., and D über, C. (2008). Fully automated extraction of airways from CT scans based on self-adapting region growing. Computerized Tomography, 27(1):64-74.
Download


Paper Citation


in Harvard Style

Bouzidi S., Baldacci F., ben Amar C. and Desbarats P. (2017). Combining Different Reconstruction Kernel Responses as Preprocessing Step for Airway Tree Extraction in CT Scan . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 89-97. DOI: 10.5220/0006134200890097


in Bibtex Style

@conference{visapp17,
author={Samah Bouzidi and Fabien Baldacci and Chokri ben Amar and Pascal Desbarats},
title={Combining Different Reconstruction Kernel Responses as Preprocessing Step for Airway Tree Extraction in CT Scan},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={89-97},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006134200890097},
isbn={978-989-758-225-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Combining Different Reconstruction Kernel Responses as Preprocessing Step for Airway Tree Extraction in CT Scan
SN - 978-989-758-225-7
AU - Bouzidi S.
AU - Baldacci F.
AU - ben Amar C.
AU - Desbarats P.
PY - 2017
SP - 89
EP - 97
DO - 10.5220/0006134200890097