Lung Segmentation Algorithm for CAD System in CTA Images
In this study, we present a new and fast algorithm for lung segmentation using CTA images. This process is quite important especially at lung vessel segmentation, detection of pulmonary emboly, finding nodules or segmentation of airways. Applied method has been carried out at four steps. At first step, images have been applied optimal threshold. At the second one, the subsegment vessels, which have a place in lung region and which are in small dimension, have been removed. At the third one, identifying and segmentation of lungs and airway edges have been carried out. Lastly, by throwing away the airway, lung segmentation has been presented.
[1] Kiraly A. P., Pichon E., Naidich D. P., and Novak C. L., "Analysis of
arterial subtrees affected by pulmonary emboli," in Medical Imaging
2004: Image Processing. Procs of the SPIE, 5370, pp. 1720-1729,
May 2004.
[2] Y. Masutani, H. MacMahon, K. Doi, Computerized detection of
pulmonary embolism in spiral CT angiography based on volumetric
image analysis, IEEE Transactions on Medical Imaging 21 (12)
(2002) 1517-1523.
[3] E. Pichon, C.L. Novak, A.P. Kiraly, D.P. Naidich, A novel method
for pulmonary emboli visualization from high-resolution CT images,
SPIE Medical Imaging 5367 (2004) 2004.
[4] R. Uppaluri, T. Mitsa, M. Sonka, E. Hoffman, and G. McLennan,
"Quantification of pulmonary emphysema from lung computed
tomography images," Am. J. Respir. Crit. Care Med. 156, 248-254
_1997_.
[5] Y. Xu, M. Sonka, G. McLennan, J. Guo, and E. Hoffman, "MDCTbased
3-D texture classification of emphysema and early smoking
related lung pathologies," IEEE Trans. Med. Imaging 25, 464-475
_2006_.
[6] S. Armato III, M. Giger, and H. MacMahon, "Automated detection of
lung nodules in CT scans: Preliminary result," Med. Phys. 28, 1552-
1561 _2001_.
[7] Q. Li, F. Li, and K. Doi, "Computerized detection of lung nodules in
thin-section CT images by use of selective enhancement filters and an
automated rule-based classifier," Acad. Radiol. 15, 165-175 _2008_.
[8] R. Uppaluri, E. Hoffman, M. Sonka, P. Hartley, G. Hunninghake, and
G. Mclennan, "Computer recognition of regional lung disease
patterns," Am. J. Respir. Crit. Care Med. 160, 648-654 _1999_.
[9] Y. Uchiyama, S. Katsuragawa, H. Abe, J. Shiraishi, F. Li, Q. Li, C.
Zhang, K. Suzuki, and K. Doi, "Quantitative computerized analysis of
diffuse lung disease in high-resolution computed tomography," Med.
Phys. 30, 2440-2454 _2003_.
[10] I. Sluimer, P. Waes, M. Viergever, and B. Ginneken, "Computeraided
diagnosis in high resolution CT of the lungs," Med. Phys. 30,
3081-3090 _2003_.
[11] I. C. Sluimer, A. M. R. Schilham, M. Prokop, and B. van Ginneken,
Computer analysis of computed tomography scans of the lung: a
survey, IEEE Transactions on Medical Imaging 25(4), pp. 385-405,
(2006).
[12] C. Haider, B. Bartholmai, D. Holmes, J. Camp, and R. Robb,
"Quantitative characterization of lung disease," Comput. Med.
Imaging Graph. 29, 555-563 _2005_.
[13] I. Sluimer, M. Prokop, and B. Ginneken, "Toward automated
segmentation of the pathological lung in CT," IEEE Trans. Med.
Imaging 24, 1025-1038 _2005_.
[14] M. Prasad, M. Brown, S. Ahmad, F. Abtin, J. Allen, I. Costa, H. Kim,
M. Mcnitt-Gray, and J. Goldin, "Automatic segmentation of lung
parenchyma in the presence of disease based on curvature of ribs,"
Acad. Radiol. 15, 1173-1180 _2008_.
[1] Kiraly A. P., Pichon E., Naidich D. P., and Novak C. L., "Analysis of
arterial subtrees affected by pulmonary emboli," in Medical Imaging
2004: Image Processing. Procs of the SPIE, 5370, pp. 1720-1729,
May 2004.
[2] Y. Masutani, H. MacMahon, K. Doi, Computerized detection of
pulmonary embolism in spiral CT angiography based on volumetric
image analysis, IEEE Transactions on Medical Imaging 21 (12)
(2002) 1517-1523.
[3] E. Pichon, C.L. Novak, A.P. Kiraly, D.P. Naidich, A novel method
for pulmonary emboli visualization from high-resolution CT images,
SPIE Medical Imaging 5367 (2004) 2004.
[4] R. Uppaluri, T. Mitsa, M. Sonka, E. Hoffman, and G. McLennan,
"Quantification of pulmonary emphysema from lung computed
tomography images," Am. J. Respir. Crit. Care Med. 156, 248-254
_1997_.
[5] Y. Xu, M. Sonka, G. McLennan, J. Guo, and E. Hoffman, "MDCTbased
3-D texture classification of emphysema and early smoking
related lung pathologies," IEEE Trans. Med. Imaging 25, 464-475
_2006_.
[6] S. Armato III, M. Giger, and H. MacMahon, "Automated detection of
lung nodules in CT scans: Preliminary result," Med. Phys. 28, 1552-
1561 _2001_.
[7] Q. Li, F. Li, and K. Doi, "Computerized detection of lung nodules in
thin-section CT images by use of selective enhancement filters and an
automated rule-based classifier," Acad. Radiol. 15, 165-175 _2008_.
[8] R. Uppaluri, E. Hoffman, M. Sonka, P. Hartley, G. Hunninghake, and
G. Mclennan, "Computer recognition of regional lung disease
patterns," Am. J. Respir. Crit. Care Med. 160, 648-654 _1999_.
[9] Y. Uchiyama, S. Katsuragawa, H. Abe, J. Shiraishi, F. Li, Q. Li, C.
Zhang, K. Suzuki, and K. Doi, "Quantitative computerized analysis of
diffuse lung disease in high-resolution computed tomography," Med.
Phys. 30, 2440-2454 _2003_.
[10] I. Sluimer, P. Waes, M. Viergever, and B. Ginneken, "Computeraided
diagnosis in high resolution CT of the lungs," Med. Phys. 30,
3081-3090 _2003_.
[11] I. C. Sluimer, A. M. R. Schilham, M. Prokop, and B. van Ginneken,
Computer analysis of computed tomography scans of the lung: a
survey, IEEE Transactions on Medical Imaging 25(4), pp. 385-405,
(2006).
[12] C. Haider, B. Bartholmai, D. Holmes, J. Camp, and R. Robb,
"Quantitative characterization of lung disease," Comput. Med.
Imaging Graph. 29, 555-563 _2005_.
[13] I. Sluimer, M. Prokop, and B. Ginneken, "Toward automated
segmentation of the pathological lung in CT," IEEE Trans. Med.
Imaging 24, 1025-1038 _2005_.
[14] M. Prasad, M. Brown, S. Ahmad, F. Abtin, J. Allen, I. Costa, H. Kim,
M. Mcnitt-Gray, and J. Goldin, "Automatic segmentation of lung
parenchyma in the presence of disease based on curvature of ribs,"
Acad. Radiol. 15, 1173-1180 _2008_.
@article{"International Journal of Medical, Medicine and Health Sciences:64501", author = "H. Özkan and O. Osman and S. Şahin and M. M. Atasoy and H. Barutca and A. F. Boz and A. Olsun", title = "Lung Segmentation Algorithm for CAD System in CTA Images", abstract = "In this study, we present a new and fast algorithm for lung segmentation using CTA images. This process is quite important especially at lung vessel segmentation, detection of pulmonary emboly, finding nodules or segmentation of airways. Applied method has been carried out at four steps. At first step, images have been applied optimal threshold. At the second one, the subsegment vessels, which have a place in lung region and which are in small dimension, have been removed. At the third one, identifying and segmentation of lungs and airway edges have been carried out. Lastly, by throwing away the airway, lung segmentation has been presented.
", keywords = "Lung segmentation, computed tomography
angiography, computer-aided diagnostic system", volume = "5", number = "5", pages = "228-4", }
