Quantitative analysis of pulmonary emphysema using local binary patterns

IEEE Transactions on Medical Imaging

Volumn 29, Issue 2, 2010, Pages 559-569

  Sørensen, Lauge ^a   Shaker, Saher B ^b   De Bruijne, Marleen ^a,c  

^a UNIVERSITY OF COPENHAGEN   (Denmark)

^b HVIDOVRE HOSPITAL   (Denmark)

^c ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

Emphysema; Local binary patterns (LBPs); Quantitative computed tomography (CT); Texture analysis; Tissue classification

Indexed keywords

CLASSIFICATION ACCURACY; COMPUTED TOMOGRAPHY; CORRELATION COEFFICIENT; CT IMAGE; DISSIMILARITY MEASURES; EMPHYSEMA QUANTIFICATION; GAUSSIAN FILTERS; LOCAL BINARY PATTERNS; LOCAL STRUCTURE; NEAREST NEIGHBOR CLASSIFIER; NORMAL TISSUE; POSTERIOR PROBABILITY; PULMONARY EMPHYSEMA; PULMONARY FUNCTION TEST; QUANTITATIVE ANALYSIS; QUANTITATIVE COMPUTED TOMOGRAPHIES; QUANTITATIVE MEASURES; REGIONS OF INTEREST; SINGLE-INTENSITY; TEXTURE ANALYSIS; TEXTURE CLASSIFICATION; TEXTURE FEATURES; TISSUE CLASSIFICATION;

CLASSIFIERS; COMPUTERIZED TOMOGRAPHY; CONTENT BASED RETRIEVAL; FILTER BANKS; TEXTURES;

PIXELS;

ALGORITHM; ARTICLE; CLASSIFICATION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; FEMALE; HOSPITALIZATION; HUMAN; LUNG; LUNG EMPHYSEMA; LUNG FUNCTION TEST; MALE; METHODOLOGY; NORMAL DISTRIBUTION; RADIOGRAPHY; SMOKING;

ALGORITHMS; FEMALE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LUNG; MALE; NORMAL DISTRIBUTION; PULMONARY EMPHYSEMA; RESPIRATORY FUNCTION TESTS; SEVERITY OF ILLNESS INDEX; SMOKING; TOMOGRAPHY, X-RAY COMPUTED;

EID: 76249103656     PISSN: 02780062     EISSN: None     Source Type: Journal    
DOI: 10.1109/TMI.2009.2038575     Document Type: Article

References (47)

1. K. F. Rabe, S. Hurd, A. Anzueto, P. J. Barnes, S. A. Buist, P. Calverley, Y. Fukuchi, C. Jenkins, R. Rodriguez-Roisin, C. van Weel, and J. Zielinski, "Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary, " Amer. J. Respir. Crit. Care Med., vol.176, no.6, pp. 532-555, Sep. 2007.
2. J. W. Gurney, "Pathophysiology of obstructive airways disease, " Ra-diol. Clin. North Amer., vol.36, no.1, pp. 15-27, Jan. 1998.
3. N. L. Müller, C. A. Staples, R. R. Miller, and R. T. Abboud, ""Density mask". An objective method to quantitate emphysema using computed tomography, " Chest, vol.94, no.4, pp. 782-787, Oct. 1988.
4. W. R. Webb, N. Müller, and D. Naidich, High-Resolution CT of the Lung, J.-R. John, Ed., 3rd ed. Baltimore, MD: Lippincott Williams & Wilkins, 2001.
5. T. Stavngaard, S. B. Shaker, K. S. Bach, B. C. Stoel, and A. Dirksen, "Quantitative assessment of regional emphysema distribution in patients with chronic obstructive pulmonary disease (COPD), " Acta Ra-diol., vol.47, no.9, pp. 914-921, Nov. 2006.
6. A. H. Mir, M. Hanmandlu, and S. N. Tandon, "Texture analysis of CT images, " IEEE Eng. Med. Biol. Mag., vol.14, no.6, pp. 781-786, Nov. / Dec. 1995.
7. M. Tuceryan and A. K. Jain, "Texture analysis, " in The Handbook of Pattern Recognition and Computer Vision, 2nd ed. Singapore: World Scientific, 1998, pp. 207-248.
8. R. Uppaluri, T. Mitsa, M. Sonka, E. A. Hoffman, and G. McLennan, "Quantification of pulmonary emphysema from lung computed tomography images, " Amer. J. Respir. Crit. Care Med., vol.156, no.1, pp. 248-254, Jul. 1997.
9. R. Uppaluri, E. A. Hoffman, M. Sonka, P. G. Hartley, G. W. Hunning-hake, and G. McLennan, "Computer recognition of regional lung disease patterns, " Amer. J. Respir. Crit. Care Med., vol.160, no.2, pp. 648-654, Aug. 1999.
10. O. Friman, M. Borga, M. Lundberg, U. Tylén, and H. Knutsson, "Recognizing emphysema-A neural network approach, " inProc. ICPR (1), Mar. 2002, pp. 512-515.
11. F. Chabat, G.-Z. Yang, and D. M. Hansell, "Obstructive lung diseases: Texture classification for differentiation at CT, " Radiology, vol.228, no.3, pp. 871-877, Sep. 2003.
12. I. C. Sluimer, P. F. van Waes, M. A. Viergever, and B. van Ginneken, "Computer-aided diagnosis in high resolution CT of the lungs, " Med. Phys., vol.30, no.12, pp. 3081-3090, Dec. 2003.
13. I. C. Sluimer, M. Prokop, I. Hartmann, and B. van Ginneken, "Automated classification of hyperlucency, fibrosis, ground glass, solid and focal lesions in high resolution CT of the lung, " Med. Phys., vol.33, no.7, pp. 2610-2620, Jul. 2006.
14. Y. Xu, M. Sonka, G. McLennan, J. Guo, and E. A. Hoffman, "MDCT-based 3-D texture classification of emphysema and early smoking related lung pathologies, " IEEE Trans. Med. Imag., vol.25, no.4, pp. 464-475, Apr. 2006.
15. A. Depeursinge, D. Sage, A. Hidki, A. Platon, P.-A. Poletti, M. Unser, and H. Muller, "Lung tissue classification using wavelet frames, " in Proc. 29th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS 2007, Aug. 2007, pp. 6259-6262.
16. Y. S. Park, J. B. Seo, N. Kim, E. J. Chae, Y. M. Oh, S. D. Lee, Y. Lee, and S.-H. Kang, "Texture-based quantification of pulmonary emphysema on high-resolution computed tomography: Comparison with density-based quantification and correlation with pulmonary function test, " Invest Radiol., vol.43, no.6, pp. 395-402, Jun. 2008.
17. M. Prasad, A. Sowmya, and I. Koch, "Designing relevant features for continuous data sets using ICA, " Int. J. Comput. Intell. Appl., vol.7, no.4, pp. 447-468, Dec. 2008.
18. M. Prasad, A. Sowmya, and P. Wilson, "Multi-level classification of emphysema in HRCT lung images, " Pattern Anal. Appl., vol.12, no.1, pp. 9-20, Jan. 2009.
19. L. Sørensen, S. B. Shaker, and M. de Bruijne, "Texture classification in lung CT using local binary patterns, " in MICCAI (1), ser. (Lecture Notes in Computer Science 5241), D. N. Metaxas, L. Axel, G. Fichtinger, and G. Székely, Eds. New York: Springer-Verlag, Sep. 2008, pp. 934-941.
20. L. Sørensen, S. Shaker, and M. de Bruijne, "Texture based emphysema quantification in lung CT, " in Proc. 1st Int. Workshop Pulm. Image Anal., M. Brown, M. de Bruijne, B. van Ginneken, A. Kiraly, J. Kuh-nigk, C. Lorenz, K. Mori, and J. Reinhardt, Eds., Sep. 2008, pp. 5-14.
21. T. Ojala, M. Pietikäinen, and T. Mäenpää, "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns, " IEEE Trans. Pattern Anal. Mach. Intell., vol.24, no.7, pp. 971-987, Jul. 2002.
22. A. Oliver, X. Lladó, J. Freixenet, and J. Martí, "False positive reduction in mammographic mass detection using local binary patterns, " in MICCAI (1), ser. (Lecture Notes in Computer Science 4791), N. Ay-ache, S. Ourselin, and A. J. Maeder, Eds. New York: Springer-Verlag, Nov. 2007, pp. 286-293.
23. D. Unay, A. Ekin, M. Cetin, R. Jasinschi, and A. Ercil, "Robustness of local binary patterns in brain MR image analysis, " in Proc. 29th Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS 2007, Aug., pp. 2098-2101.
24. A. Jain, R. Duin, and J. Mao, "Statistical pattern recognition: A review, " IEEE Trans. Pattern Anal. Mach. Intell., vol.22, no.1, pp. 4-37, Jan. 2000.
25. R. Haralick, "Statistical and structural approaches to texture, " Proc. IEEE, vol.67, no.5, pp. 786-804, May 1979.
26. T. Ojala, M. Pietikäinen, and D. Harwood, "A comparative study of texture measures with classification based on featured distributions, " Pattern Recognit., vol.29, no.1, pp. 51-59, Jan. 1996.
27. M. J. Swain and D. H. Ballard, "Color indexing, " Int. J. Comput. Vis., vol.7, no.1, pp. 11-32, Nov. 1991.
28. R. P. W. Duin and D. M. J. Tax, "Classifier conditional posterior probabilities, " in SSPR/SPR, ser. (Lecture Notes in Computer Science 1451), A. Amin, D. Dori, P. Pudil, and H. Freeman, Eds. New York: Springer-Verlag, Aug. 1998, pp. 611-619.
29. S. Hu, E. Hoffman, and J. Reinhardt, "Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images, " IEEE Trans. Med. Imag., vol.20, no.6, pp. 490-498, Jun. 2001.
30. P. Lo, J. Sporring, J. J. H. Pedersen, and M. De Bruijne, "Airway tree extraction with locally optimal paths, " in MICCAI (1), ser. (Lecture Notes in Computer Science 5762), G.-Z. Yang, D. J. Hawkes, D. Rueckert, J. A. Noble, and C. J. Taylor, Eds. New York: Springer-Verlag, Sep. 2009, pp. 51-58.
31. M. Loog and B. Van Ginneken, "Static posterior probability fusion for signal detection: Applications in the detection of interstitial diseases in chest radiographs, " in Proc. ICPR (1), Aug. 2004, pp. 644-647.
32. S. B. Shaker, K. A. von Wachenfeldt, S. Larsson, I. Mile, S. Persdotter, M. Dahlbäck, P. Broberg, B. Stoel, K. S. Bach, M. Hestad, T. E. Fehniger, and A. Dirksen, "Identification of patients with chronic obstructive pulmonary disease (COPD) by measurement of plasma biomarkers, " Clin. Respir. J., vol.2, no.1, pp. 17-25, 2008.
33. P. Quanjer, G. Tammeling, J. Cotes, O. Pedersen, R. Peslin, and J. Yer-nault, "Lung volumes and forced ventilatory flows. Report working party standardization of lung function tests, european community for steel and coal. Official statement of the european respiratory society, " Eur. Respir. J. Suppl., vol.16, pp. 5-40, Mar. 1993.
34. X. Wei, Beijing Aeronautical Technology Research Center, "Gray level run length matrix toolbox v1. 0, " 2007
35. [Online]. Available: http://www. mathworks. com/matlabcentral/ fileexchange/17482
36. T. G. Dietterich, "Approximate statistical test for comparing supervised classification learning algorithms, " Neural Comput., vol.10, no.7, pp. 1895-1923, Oct. 1998.
37. J. V. Sickle, "Analyzing correlations between stream and watershed attributes, " J. Amer. Water Resour. As., vol.39, no.3, pp. 717-726, Jun. 2003.
38. M. Kinsella, N. L. Müller, R. T. Abboud, N. J. Morrison, and A. Dy-Buncio, "Quantitation of emphysema by computed tomography using a "density mask" program and correlation with pulmonary function tests, " Chest, vol.97, no.2, pp. 315-321, Feb. 1990.
39. G. A. Gould, A. T. Redpath, M. Ryan, P. M. Warren, J. J. Best, D. C. Flenley, and W. MacNee, "Lung CT density correlates with measurements of airflow limitation and the diffusing capacity, " Eur. Respir. J., vol.4, no.2, pp. 141-146, Feb. 1991.
40. M. Schwaiblmair, T. Beinert, M. Seemann, J. Behr, M. Reiser, and C. Vogelmeier, "Relations between cardiopulmonary exercise testing and quantitative high-resolution computed tomography associated in patients with alpha-1-antitrypsin deficiency, " Eur. J. Med. Res., vol.3, no.11, pp. 527-532, Nov. 1998.
41. K. Soejima, K. Yamaguchi, E. Kohda, K. Takeshita, Y. Ito, H. Mas-tubara, T. Oguma, T. Inoue, Y. Okubo, K. Amakawa, H. Tateno, and T. Shiomi, "Longitudinal follow-up study of smoking-induced lung density changes by high-resolution computed tomography, " Amer. J. Respir. Crit. Care Med., vol.161, no.4, pp. 1264-1273, Apr. 2000.
42. A. Dirksen, N. H. Holstein-Rathlou, F. Madsen, L. T. Skovgaard, C. S. Ulrik, T. Heckscher, and A. Kok-Jensen, "Long-range correlations of serial FEV1 measurements in emphysematous patients and normal subjects, " J. Appl. Physiol., vol.85, no.1, pp. 259-265, Jul. 1998.
43. P. W. Jones, "Health status measurement in chronic obstructive pulmonary disease, " Thorax, vol.56, no.11, pp. 880-887, Nov. 2001.
44. J. Kittler, M. Hatef, R. P. W. Duin, and J. Matas, "On combining classifiers, " IEEE Trans. Pattern Anal. Mach. Intell., vol.20, no.3, pp. 226-239, Mar. 1998.
45. H. Ashraf, P. Lo, S. Shaker, M. de Bruijne, A. Dirksen, P. Tønnesen, M. Dahlbäck, and J. H. Pedersen, "Change in smoking habits affects lung density by CT, " Am. J. Respir. Crit. Care Med., vol.179, Apr. 2009.
46. E. Pekalska and R. P. W. Duin, "Dissimilarity representations allow for building good classifiers, " Pattern Recog. Lett., vol.23, no.8, pp. 943-956, Jun. 2002.
47. G. Zhao and M. Pietikäinen, "Dynamic texture recognition using local binary patterns with an application to facial expressions, " IEEE Trans. Pattern Anal. Mach. Intell., vol.29, no.6, pp. 915-928, Jun. 2007.