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Adaptive Crisp Active Contour Method for Segmentation and Reconstruction of 3D Lung Structures

by Pedro Pedrosa Rebouc¸as Filho, Roger Moura Sarmento, Paulo C. Cortez, Antˆonio Carlos Da Silva Barros, Victor Hugo C. De Albuquerque
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 111 - Number 4
Year of Publication: 2015
Authors: Pedro Pedrosa Rebouc¸as Filho, Roger Moura Sarmento, Paulo C. Cortez, Antˆonio Carlos Da Silva Barros, Victor Hugo C. De Albuquerque
10.5120/19523-1164

Pedro Pedrosa Rebouc¸as Filho, Roger Moura Sarmento, Paulo C. Cortez, Antˆonio Carlos Da Silva Barros, Victor Hugo C. De Albuquerque . Adaptive Crisp Active Contour Method for Segmentation and Reconstruction of 3D Lung Structures. International Journal of Computer Applications. 111, 4 ( February 2015), 1-8. DOI=10.5120/19523-1164

@article{ 10.5120/19523-1164,
author = { Pedro Pedrosa Rebouc¸as Filho, Roger Moura Sarmento, Paulo C. Cortez, Antˆonio Carlos Da Silva Barros, Victor Hugo C. De Albuquerque },
title = { Adaptive Crisp Active Contour Method for Segmentation and Reconstruction of 3D Lung Structures },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 111 },
number = { 4 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume111/number4/19523-1164/ },
doi = { 10.5120/19523-1164 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:46:57.766772+05:30
%A Pedro Pedrosa Rebouc¸as Filho
%A Roger Moura Sarmento
%A Paulo C. Cortez
%A Antˆonio Carlos Da Silva Barros
%A Victor Hugo C. De Albuquerque
%T Adaptive Crisp Active Contour Method for Segmentation and Reconstruction of 3D Lung Structures
%J International Journal of Computer Applications
%@ 0975-8887
%V 111
%N 4
%P 1-8
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Computing systems have been playing an important role in various medical fields, notably in image diagnosis. Highlighted among the existing exams that allow diagnostic aids and the application of computing systems in parallel is Computed Tomography (CT). This work focuses on the segmentation and reconstruction phases of CT lung images using the Adaptive Crisp Active Contour Model 2D (ACACM) and the OpenGL library to present and analyse the results in three dimensions. The results of the proposed method were compared with those of the 3D Region Growing method and then evaluated by two pulmonologists. The results showed the superiority of the proposed method, thus confirming that that this method could integrate medical diagnostic aid systems in the pulmonology field. Finally, some applications are shown utiizando segmentation and 3D reconstruction proposals demonstrating that the proposed method can be used to aid in medical diagnosis.

References
  1. Dave Astle and Kevin Hawkins. More OpenGl Game Programming. Thomson, EUA, 2005.
  2. Dave Astle and Kevin Hawkins. Begnning OpenGl Game Programming. Thomson, EUA, 2nd edition, 2009.
  3. S. Born, Dirkiwamaru, M. Pfeile, and D. Bartz. 3-step segmentation of the lower airways with advanced leakagecontrol. IJCAI 2009 Workshop on Explanation Aware Computing, pages 239–255, 2009.
  4. H. S. Campos and A. C. M. A. Lemos. Asthma and copd in view of the pulmonologist. Brazilian Journal of Pulmonology, 35(4):301–309, 2009.
  5. Marcelo Cohen and Isabel Harb Manssour. OpenGl: Uma abordagem pr´atica e objetiva. Novatec, 2006.
  6. R. G. Congalton and K. Green. Assessing the accuracy of remotely sensed data: Principles and practices. Lewis Publishers, New York, 1999.
  7. Jos´e Silvestre Serra da Silva. Lung segmentation on studies CT scanner. Master's thesis, Department of Electronics and Telecommunications, University of Aveiro, 2005.
  8. Tarique da Silveira Cavalcante. Technique for automatic segmentation of airway in computed tomography images of the chest. Master's thesis, Universidade Federal do Cear´a, Fortaleza, Cear´a, Brasil, 2010.
  9. R. de Marco, S. Accordini, I. Cerveri, A. Corsico, J. Sunyer, F. Neukirch, N. Kunzly, B. Leynaert, C. Janson, T. Gislason, P. Vermeire, C. Svanes, J. M. Anto, and P. Burney. An international survey of chronic obstrutive pulmonary disease in young adults according to gold stages. Thorax, 59:120–125, Julho 2004.
  10. J. H. S. Felix, P. C. Cortez, and M. A. Holanda. A new algorithm for automatic segmentation of lung CT images. pages 1–6, Campos do Jord˜ao, SP, 2008. XI Congresso Brasileiro de inform´atica em Sa´ude - CBIS, Sociedade brasileira de inform ´atica em sa´ude.
  11. J. H. S. Felix, P. C. Cortez, M. A. Holanda, and R. C. S. Costa. Automatic segmentation and measurement of the lungs in healthy persons and in patients with chronic obstructive pulmonary disease in ct images. volume 18, pages 370–373, Margarita Island, Venezuela, Outubro 2007. V Latin American Congress on Biomedical Engineering 2007, Bioengineering Solutions for Latin America Health.
  12. John Heber S. Felix, P. C. Cortez, M. A. Holanda, D. F. Colac¸o, V. H. C. Albuquerque, and A. R. Alexandria. Lung and chest wall structures segmentation in CT images. pages 291–294. Computational Vision and Medical Image Processing (VIPMAGE), Outubro 2007.
  13. John Hebert Silva Felix, Paulo C´esar Cortez, Pedro Pedrosa Rebouc¸asFilho, Auzuir Ripardo de Alexandria, Rodrigo Carvalho Sousa Costa, and Marcelo Alcantara Holanda. Identification and quantification of pulmonary emphysema through pseudocolors. Lecture Notes in Computer Science, 5317:957– 964, 2008.
  14. John Hebert Silva Flix. Methods of Active Contours in Hilbert 2D image segmentation of lungs in CT of the Chest. PhD thesis, Department of Computer Engineering, Federal University of Cear, Fortaleza, Cear´a, Brasil, 2011.
  15. Simone Castelo Branco Fortaleza. Acute effects of administration of continuous positive airway pressure mode noninvasive about airing of lung parenchyma in patients with chronic obstructive pulmonary disease. Master's thesis, Department of Clinical Medicine, Federal University of Cear, Fortaleza, CE, 2006.
  16. Simon Haykin. Neural Networks: A Comprehensive Foundation. Prentice-Hall, EUA, 2nd edition, 1999.
  17. Shiying Hu, Eric A. Hoffman, and Joseph M. Reinhardt. Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images. IEEE Transactions on Medical Imaging, 20:490–498, Junho 2001.
  18. B. Irving, P. TaylorR, and A. Todd-Pokropek. 3D segmentation of the airway tree using a morphology based method. IJCAI 2009 Workshop on Explanation Aware Computing, pages 297–307, 2009.
  19. Yoshinori Itai, Hyoungseop Kim, and Seiji Ishikawa. A segmentation method of lung areas by using snakes and automatic detection of abnormal shadow on the areas. International Journal of Innovative Computing Information and Control, 3:277–284, Abril 2007.
  20. Michael Kass, Andrew Witkin, and Demetri Terzopoulos. Snakes: Active contour models. International Journal of Computer Vision, 1:321–331, 1987.
  21. Tan Kok Liang, Toshiyuki Tanaka, Hidetoshi Nakamura, Toru Shirahata, and Hiroaki Sugiura. An automated 3D emphysema extraction method using lung CT. SICE Annual Conference 2008, pages 3110–3114, 2008.
  22. S. Matsuoka, T. Yamashiro, G. R. Washko, and Y. Kurihara. Quantitative CT assessment of chronic obstructive pulmonary disease. RadioGraphics, 30:55–66, 2010.
  23. P. P. Rebouc¸as Filho, P. C. Cortez, and V. H. C. Albuquerque. 3D segmentation and visualization of lung and its structures using CT images of the thorax. Journal of Biomedical Science and Engineering, 6:1099–1108, 2013.
  24. P. P. Rebouc¸as Filho, P. C. Cortez, J. H. S. Felix, Tarique da Silveira T. S. Cavalcante, and M. A. Holanda. Adaptive 2D crisp active contour model applied to lung segmentation in CT images of the thorax of healthy volunteers and patients with pulmonary emphysema,. Brazilian Journal of Biomedical Engineering, 29:363–376, 2013.
  25. Pedro Pedrosa Rebouc¸as Filho, Paulo Cesar Cortez, Antonio Carlos da Silva Barros, and Victor Hugo Costa de Albuquerque. Novel adaptive balloon active contour method based on internal force for image segmentation - a systematic evaluation on synthetic and real images. Expert Systems with Applications, pages 7707–7721, 2014.
  26. Pedro Pedrosa Rebouc¸as Filho, Paulo C´esar Cortez, and Marcelo Alcantara Holanda. Active contour modes crisp: new technique for segmentation the lungs in CT images. Brazilian Journal of Biomedical Engineering, 27:259–272, 2011.
  27. Rushin Shojaii, Javad Alirezaie, and Paul Babyn. Automatic lung segmentation in CT images using watershed transform. IEEE International Conference on Image Processing-ICIP,, 2:1270–1273, Setembro 2005.
  28. A. Silva, J. S. Silva, B. S. Santos, and C. Ferreira. Fast pulmonary contour extraction in X-ray CT images: A methodology and quality assessment. volume 4321, pages 216–224, San Diego, EUA, 2001. Proceding SPIE Conference on Medical Imaging: Physiology and Function from Multidimensional Images, SPIE Digital Library.
  29. Arist´ofane C. Silva, Paulo Cezar P. Carvalho, Rodolfo A. Nunes, and Marcelo Gattass. Segmentation and reconstruction of the pulmonary parenchyma. pages 73–82. VI Workshop de Inform´atica M´edica - WIM, Maio 2006.
  30. Ingrid Sluimer, Mathias Prokop, and Bram van Ginneken. Toward automated segmentation of the pathological lung in CT. IEEE Transactions on Medical Imaging, 24(8):1025–1038, Agosto 2005.
  31. J. Tschirren, T. Yavarna, and J. M. Reinhardt. 3D segmentation of the airway tree using a morphology based method. IJCAI 2009 Workshop on Explanation Aware Computing, pages 227–238, 2009.
  32. WHO. Global strategy for the diagnosis, management and prevention chronic obstrutive pulmonar disease. Technical report, World Health Organization, 2014.
  33. Ge´orgia Freire Paiva Winkeler. Acute effects of administration of continuous positive airway pressure mode not about invasive pulmonary parenchyma of healthy volunteers in supine and prone positions: Changes in high resolution computed tomography. Master's thesis, Department of Clinical Medicine, Federal University of Cear, Fortaleza, 2006.
  34. X. C. Yin, C. P. Liu, and Z. Han. Feature combination using boosting. Pattern Recognition Letters, 25:2195–2205, April 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Crisp Active Contour Method Computed Tomography Image Segmentation 3D Reconstruction Lung Structures.

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