Using HOG-LBP features and MMP learning to recognize imaging signs of lung lesions

Proceedings - IEEE Symposium on Computer-Based Medical Systems

Volumn , Issue , 2012, Pages

  Song, Li ^a   Liu, Xiabi ^a   Ma, Ling ^a   Zhou, Chunwu ^b   Zhao, Xinming ^b   Zhao, Yanfeng ^b  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b CANCER HOSPITAL   (China)

Author keywords

[No Author keywords available]

Indexed keywords

AVERAGE SENSITIVITIES; BAG-OF-VISUAL-WORDS; CROSS VALIDATION; HISTOGRAMS OF ORIENTED GRADIENTS; LEARNING METHODS; LOCAL BINARY PATTERNS; LUNG CT; LUNG LESIONS; MAX-MIN; REGIONS OF INTEREST;

GRAPHIC METHODS;

SUPPORT VECTOR MACHINES;

EID: 84867324825     PISSN: 10637125     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CBMS.2012.6266313     Document Type: Conference Paper

References (16)

1. I. Sluimer, P. F. van Waes, M. A. Viergever, et al, "Computer-aided diagnosis in high resolution CT of the lungs," Med. Phys, vol. 30, no. 12, pp. 3081-3090, Dec. 2003.
2. M. Huber, M. Nagarajan, L. Gerda, et al, "Classification of Interstitial Lung Disease Patterns with Topological Texture Feature," in Proc. SPIE Medical Imaging, vol. 7624, pp. 2-9, Feb.2010.
3. 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. 2610-1620, Jun.2006.
4. L. Sørensen, P. Lo, H. Ashraf, et al, "Learning COPD Sensitive Filters in Pulmonary CT," in MICCAI 2009, In Yang, G.Z., Hawkes, D.J., Rueckert, D., Noble, J.A., Taylor, C.J., vol. 5762, pp. 699-706, 2009.
5. L. Sørensen, S. B. Shaker, and M. de Bruijne, "Texture Classification in Lung CT Using Local Binary Patterns," In MICCAI 2008, D. N. Metaxas, L. Axel, G. Fichtinger, and G. Székely, Eds., pp. 934-941, Sept. 2008.
6. T. Nuzhnaya, V. Megalooikonomou, H. Ling, et al, "Classification of Texture Patterns in CT Lung Imaging," in Proc. SPIE Medical Imaging, vol. 7963, 2011.
7. A. Depeursinge, J. Iavindrasana, A. Hidki, et al, "A classification framework for lung tissue categorization," In SPIE Medical Imaging, vol. 6919, Feb. 2008.
8. K. Suzuki, H. Asamura, M. Kusumoto, et al, "Early peripheral lung cancer: prognostic significance of ground glass opacity on thin-section computed tomographic scan," Ann Thorac Surg., vol. 74, pp. 1635-1639, Jun. 2002.
9. M.K. Gould, L. Ananth, P.G. Barnett, "A clinical model to estimate the pretest probability of lung cancer in patients with solitary pulmonary nodule," Chest, vol. 131, no. 2, pp. 383-388, Feb. 2007.
10. N. Dalal, B. Triggs, "Histograms of Oriented Gradients for Human Detection," In CVPR, vol. 1, pp. 886-893, 2005.
11. T. Ojala, M. Pietikainen, D. Harwood, "A Comparative Study of Texture Measures with Classification Based on Feature Distributions," Pattern Recognition, vol. 29, no. 1, pp. 51-59, 1996.
12. J. Wang, Y. G. Jiang, A. G. hauptmann, and C. W. Ngo. "Evaluating bag-of-visual-words representations in scene classification," In Proc. of the International Workshop on Multimedia Information Retrieval, pp. 197-206, 2007.
13. Liu, X., Jia, Y., Chen, X., Deng, Y., Fu, H, "Image classification using the max-min posterior pseudoprobabilities method," Technical Report BIT-CS-20080001, Beijing Institute of Technology, 2008.
14. A. Dempster, N. Laird, D. Rubin, "Maximum Likelihood from Incomplete Data via the EM Algorithm," Journal of the Royal Statistical Society, vol. 39, no. 1, pp. 1-38, 1977.
15. M.H. Hansen, B. Yu, "Model Selection and the Principle of Minimum Description Length," In Journal of American Statistical Association, vol.96, no. 454, pp.746-774, Jun. 2001.
16. Geoffrey Holmes, Andrew Donkin, and Ian H.Witten, "WEKA: a machine learning workbench," In Proc. of the Second Australia and New Zealand Conference on Intelligent Information Systems, pp. 357-361, Dec. 1994.