Classification of diffuse lung disease patterns on high-resolution computed tomography by a bag of words approach

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6893 LNCS, Issue PART 3, 2011, Pages 183-190

  Xu, Rui ^a   Hirano, Yasushi ^a   Tachibana, Rie ^b   Kido, Shoji ^a  

^a YAMAGUCHI UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

^b OSHIMA NATIONAL COLLEGE OF MARITIME TECHNOLOGY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

BAG OF WORDS; CT-VALUE; DETECTION AND DIAGNOSIS; DIFFUSE LUNG DISEASE; GLOBAL FEATURE; GROUND-GLASS OPACITY; HESSIAN MATRICES; HIGH-RESOLUTION COMPUTED TOMOGRAPHY; LOCAL FEATURE; NORMAL TISSUE; RECOGNITION RATES; STATISTICAL MEASURES; VISUAL INSPECTION;

BIOLOGICAL ORGANS; DIAGNOSIS; FEATURE EXTRACTION; MEDICAL COMPUTING; MEDICAL IMAGING; TISSUE; TOMOGRAPHY;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; CLASSIFICATION; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; HUMAN; IMAGE PROCESSING; LANGUAGE; LUNG DISEASE; METHODOLOGY; NORMAL DISTRIBUTION; ONCOLOGY; RADIOLOGY; REPRODUCIBILITY;

ALGORITHMS; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LANGUAGE; LUNG DISEASES; MEDICAL ONCOLOGY; NORMAL DISTRIBUTION; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; RADIOLOGY; REPRODUCIBILITY OF RESULTS; TOMOGRAPHY, X-RAY COMPUTED;

EID: 80053492004     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23626-6_23     Document Type: Conference Paper

References (17)

1. Uppaluri, R., Heitmman, E.A., Sonka, M., Hartley, P.G., Hunninghake, G.W., Mclennan, G.: Computer Recognition of Regional Lung Disease Patterns. American Journal of Respiratory and Critical Care Medicine 160(2), 648-654 (1999)
2. Kauczor, H., Heitmann, K., et al.: Automatic Detection and Quantification of Ground-glass opacities on High-resolution CT Using multiple Neural Networks: Comparison with a Density Mask. American Journal of Roentgenology 175(5), 1329-1334 (2000)
3. Manning, C.D., Schfutze, H.: Foundation of Statistical Natural Language Processing. The MIT Press, Cambridge (2001)
4. Uchiyama, Y., Katsuragawa, S., Abe, H., Shiraishi, J., Li, F., Li, Q., Zhang, C., Suzuki, K., Doi, K.: Quantitative Computerized Analysis of Diffuse Lung Disease in High-resolution Computed Tomography. Medical Physics 30(9), 2440-2454 (2003)
5. Sluimer, I.C.,Waes,P.F.V.,Viergever,M.A.,Ginneken,B.V.:Computer-aided Diagnosis in High-resolution CT of the Lungs. Medical Physics 30(12), 3081-3090 (2003)
6. Csurka, G., Dance, C.R., Fan, L., Bray, C.: Visual Categorization with Bags of Keypoints. In: Proc. of ECCV Workshop on Statistical Learning in Computer Vision, pp. 1-22 (2004)
7. Kurani, A.S., Xu, D., Furst, J.D., Raicu, D.S.: Co-occurrence matrices for volumetric data. In: 7th IASTED International Conference on Computer Graphics and Imaging, Hawai (2004)
8. Xu, D., Kurani, A.S., Furst, J.D., Raicu, D.S.: Run-length encoding for volumetric texture. In: The 4th IASTED International Conference on Visualization, Imaging, and Image Processing (2004)
9. Sluimer, I., Schilham, A., Prokop, M., Ginneken, B.V.: Computer Analysis of Computed Tomography Scans of the Lung: A Survey. IEEE Transactions on Medical Imaging 25(4), 385-405 (2006)
10. Xu, Y., Sonka, M., McLennan, G., Guo, J.F., Hoffman, E.A.: MDCT-based 3-D Texture Classification of Emphysema and Early Smoking Related Lung Pathologies. IEEE Transactions on Medical Imaging 25(4), 464-475 (2006)
11. Tuytelaars, T., Mikolaczyk, K.: Local Invarriant Feature Detectors: A Survey. Foundations and Trands in Computer Graphics and Vision 3(3), 177-280 (2007)
12. Webb, W., Müller, N.L., Naidich, D.: High Resolution CT of the Lung, 4th edn. Lippincott Williams & Wilkins, Baltimore (2008)
13. Park, S.O., Seo, J.B., Kim, N., Park, S.H., Lee, Y.K., Park, B.W., Sung, Y.S., Lee, Y., Kang, J., Lee, J., Kang, S.H.: Feasibility of Automated Quantification of Regional Disease Patterns Depicted on High-resolution Computed Tomography in Patients with Various Diffuse Lung Diseases. Korean Journal of Radiology 10(5), 455-463 (2009)
14. Lampert, C.H.: Kernel Methods in Computer Vision. Foundations and TrendsR in Computer Graphics and Vision 4(3), 193-285 (2009)
15. Gangeh, M.J., Sørensen, L., Shaker, S.B., Kamel, M.S., Bruijne, M.D., Loog, M.: A Texton-Based Approach for the Classification of Lung Parenchyma in CT Images. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010. LNCS, vol. 6363, pp. 595-602. Springer, Heidelberg (2010)
16. Sørensen, L., Shaker, S.B., De Bruijne, M.: Quantitative analysis of pulmonary emphysema using local binary patterns. IEEE Transaction on Medical Imaging 29(2), 559-569 (2010)
17. Chang, C.C., Lin, C.J.: LIBSVM : a library for support vector machines, http://www.csie.ntu.edu.tw/~cjlin/libsvm