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International Journal of Biomedical Imaging
Volume 2011 (2011), Article ID 241396, 7 pages
http://dx.doi.org/10.1155/2011/241396
Research Article

Biomedical Imaging Modality Classification Using Combined Visual Features and Textual Terms

1College of Information Science and Engineering, Ritsumeikan University, Kusatsu-Shi, 525-8577, Japan
2College of Information Sciences and Technology, The Pennsylvania State University, University Park, PA 16802, USA

Received 22 February 2011; Revised 12 May 2011; Accepted 6 July 2011

Academic Editor: Fei Wang

Copyright © 2011 Xian-Hua Han and Yen-Wei Chen. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. H. Muller, N. Michoux, D. Bandon, and A. Geissbuhler, “A review of content-based image retrieval systems in medicine clinical benefits and future directions,” International Journal of Medical Informatics, vol. 73, no. 1, pp. 1–23, 2004. View at Publisher · View at Google Scholar · View at Scopus
  2. H. Muller, T. Deselaers, T. Lehmann, P. Clough, and W. Hersh, “Overview of the ImageCLEFmed 2006 medical retrieval annotation tasks, evaluation of multilingual and multimodal information retrieval,” in Proceedings of the Seventh Workshop of the Cross-Language Evaluation Forum, (CLEF 2006), C. Peters, P. Clough, F. Gey et al., Eds., Lecture Notes in Computer Science, Alicante, Spain, 2006.
  3. W. Hersh, J. Kalpathy-Cramer, and J. Jensen, “Medical image retrieval and automated annotation: OHSU at ImageCLEF 2006,” in Proceedings of the Working Notes for the CLEF 2006 Workshop, Alicante, Spain, 2006.
  4. M. O. Güld, M. Kohnen, D. Keysers et al., “Quality of DICOM header information for image categorization,” in Proceedings of the International Society of Optics and Photonics (SPIE), vol. 4685, pp. 280–287, February 2002. View at Publisher · View at Google Scholar · View at Scopus
  5. W. Hersh, H. Muller, J. Jensen, J. Yang, P. Gorman, and P. Ruch, “Advancing biomedical image retrieval: development and analysis of a test collection,” Journal of the American Medical Informatics Association, vol. 13, no. 5, pp. 488–496, 2006. View at Google Scholar
  6. J. Kalpathy-Cramer and W. Hersh, “Automatic image modality based classification and annotation to improve medical image retrieval,” Student Health Technology Informformation, vol. 129, part 2, pp. 1334–1338, 2007. View at Google Scholar
  7. “Medical retrieval task,” http://www.imageclef.org/node/104/.
  8. A. Pentland, R. W. Picard, and S. Sclaroff, “Photobook: content-based manipulation of image databases,” International Journal of Computer Vision, vol. 18, no. 3, pp. 233–254, 1996. View at Google Scholar · View at Scopus
  9. A. Lakdashti and M. S. Moin, “A new content-based image retrieval approach based on pattern orientation histogram,” Computer Vision/Computer Graphics Collaboration Techniques, vol. 4418, pp. 587–595, 2007. View at Publisher · View at Google Scholar
  10. A. K. Jain and A. Vailaya, “Image retrieval using color and shape,” Pattern Recognition, vol. 29, no. 8, pp. 1233–1244, 1996. View at Publisher · View at Google Scholar · View at Scopus
  11. D. Lowe, “Distinctive image features from scale-invariant keypoints,” International Journal of Computer Vision, vol. 60, no. 2, pp. 91–110, 2004. View at Publisher · View at Google Scholar · View at Scopus
  12. G. Csurka, C. Dance, L. Fan, J. Willamowski, and C. Bray, “Visual categoraization with bags of keypoints,” in Proceedings of the ECCV Workshop on Statistical Learning in Computer Vision, pp. 1–16.
  13. S. Lazebnik, C. Schmid, and J. Ponce, “Beyond bags of features: spatial pyramid matching for recognizing natural scene categories,” in Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (CVPR 2006), pp. 2169–2178, June 2006. View at Publisher · View at Google Scholar · View at Scopus
  14. X. H. Han, Y. W. Chen, and X. Ruan, “Image recognition by learned linear subspace of combined bag-of-features and low-level features,” in Proceedings of the 20th International Conference on Pattern Recognition, (ICPR 2010), pp. 1049–1052, August 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. X. H. Han, Y. W. Chen, and X. Ruan, “Image categorization by learned nonlinear subspace of combined visual-words and low-level features,” in Proceedings of the 20th International Conference on Pattern Recognition, (ICPR 2010), pp. 3037–3040, August 2010. View at Publisher · View at Google Scholar · View at Scopus
  16. C. S. Won, D. K. Park, and S. J. Park, “Efficient use of MPEG-7 edge histogram descriptor,” Electronics and Telecommunications Research Institute Journal, vol. 24, no. 1, pp. 23–30, 2002. View at Google Scholar · View at Scopus
  17. H. Muller, J. Kalpathy-Cramer, I. Eggel, S. Bedrick, C. E. Kahn Jr., and W. Hersh, “Overview of the CLEF 2010 medical image retrieval track,” in Proceedings of the Working Notes of Cross-Language Evaluation Forum, (CLEF 2010), Padova, Italy, 2010.
  18. http://imageclef.org/2010/medical.