Table of Contents Author Guidelines Submit a Manuscript
Computational and Mathematical Methods in Medicine
Volume 2014, Article ID 536217, 12 pages
http://dx.doi.org/10.1155/2014/536217
Research Article

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

1Department of Computer Engineering, Inje University, Injero 197, UHRC, Gimhae, Gyeongnam 621-749, Republic of Korea
2Department of Pathology, Yonsei University, Seoul 120-749, Republic of Korea
3Department of Anatomy, Gachon University, Incheon 406-799, Republic of Korea
4Centre for Image Analysis, Uppsala University, 75105 Uppsala, Sweden

Received 1 June 2014; Revised 31 August 2014; Accepted 3 September 2014; Published 9 October 2014

Academic Editor: Po-Hsiang Tsui

Copyright © 2014 Tae-Yun Kim et al. 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. M. Takahashi, D. R. Rhodes, K. A. Furge et al., “Gene expression profiling of clear cell renal cell carcinoma: gene identification and prognostic classification,” Proceedings of the National Academy of Sciences of the United States of America, vol. 98, no. 17, pp. 9754–9759, 2001. View at Publisher · View at Google Scholar · View at Scopus
  2. A. Bergkvist, A. Ljungqvist, and G. Moberger, “Classification of bladder tumours based on the cellular pattern,” Acta Chirurgica Scandinavica, vol. 130, no. 4, pp. 371–378, 1965. View at Google Scholar · View at Scopus
  3. L. H. Sobin, M. K. Gospodarowicz, and C. H. Wittekind, TNM Classification of Malignant Tumors, Wiley-Blackwell, Oxford, UK, 7th edition, 2009.
  4. D. G. Skinner, R. B. Colvin, C. D. Vermillion, R. C. Pfister, and W. F. Leadbetter, “Diagnosis and management of renal cell carcinoma. A clinical and pathologic study of 309 cases,” Cancer, vol. 28, no. 5, pp. 1165–1177, 1971. View at Publisher · View at Google Scholar · View at Scopus
  5. S. A. Fuhrman, L. C. Lasky, and C. Limas, “Prognostic significance of morphologic parameters in renal cell carcinoma,” The American Journal of Surgical Pathology, vol. 6, no. 7, pp. 655–663, 1982. View at Publisher · View at Google Scholar · View at Scopus
  6. M. Munichon, C. Lichtig, G. Tzin, and A. Weiss, “Prognostic significance of granular cell content in renal cell carcinoma,” European Urology, vol. 22, no. 3, pp. 204–208, 1992. View at Google Scholar · View at Scopus
  7. A. Huisman, L. S. Ploeger A, H. F. J. Dullens, N. Poulin, W. E. Grizzle, and P. J. van Diest, “Development of 3D chromatin texture analysis using confocal laser scanning microscopy,” Cellular Oncology, vol. 27, no. 5-6, pp. 335–345, 2005. View at Google Scholar · View at Scopus
  8. H.-J. Choi, I.-H. Choi, T.-Y. Kim, N.-H. Cho, and H.-K. Choi, “Three-dimensional visualization and quantitative analysis of cervical cell nuclei with confocal laser scanning microscopy,” Analytical and Quantitative Cytology and Histology, vol. 27, no. 3, pp. 174–180, 2005. View at Google Scholar · View at Scopus
  9. H.-J. Choi and H.-K. Choi, “Grading of renal cell carcinoma by 3D morphological analysis of cell nuclei,” Computers in Biology and Medicine, vol. 37, no. 9, pp. 1334–1341, 2007. View at Publisher · View at Google Scholar · View at Scopus
  10. N. Malpica, A. Santos, A. Tejedor et al., “Automatic quantification of viability in epithelial cell cultures by texture analysis,” Journal of Microscopy, vol. 209, no. 1, pp. 34–40, 2003. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  11. K. Rodenacker and E. Bengtsson, “A feature set for cytometry on digitized microscopic images,” Analytical Cellular Pathology, vol. 25, no. 1, pp. 1–36, 2003. View at Google Scholar · View at Scopus
  12. B. S. Manjunath and R. Chellappa, “A note on unsupervised texture segmentation,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 13, pp. 478–483, 1991. View at Google Scholar
  13. C.-M. Pun and M.-C. Lee, “Log-polar wavelet energy signatures for rotation and scale invariant texture classification,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 5, pp. 590–603, 2003. View at Publisher · View at Google Scholar · View at Scopus
  14. Y. Chen and E. R. Dougherty, “Gray-scale morphological granulometric texture classification,” Optical Engineering, vol. 33, no. 8, pp. 2713–2722, 1994. View at Publisher · View at Google Scholar · View at Scopus
  15. V. A. Kovalev, M. Petrou, and Y. S. Bondar, “Texture anisotropy in 3-D images,” IEEE Transactions on Image Processing, vol. 8, no. 3, pp. 346–360, 1999. View at Publisher · View at Google Scholar · View at Scopus
  16. A. S. Kurani, D.-H. Xu, J. Furst, and D. S. Raicu, “Co-occurrence matrices for volumetric data,” in Proceedings of the 7th IASTED International Conference on Computer Graphics and Imaging, pp. 447–452, August 2004. View at Scopus
  17. L. Semler and L. Dettori, “A comparison of wavelet, ridgelet, and curvelet-based texture classification algorithms in computed tomography,” Computers in Biology and Medicine, vol. 37, no. 4, pp. 486–498, 2007. View at Publisher · View at Google Scholar · View at Scopus
  18. N. Sebe and M. S. Lew, “Wavelet based texture classification,” in Proceedings of the 15th International Conference in Pattern Recognition (ICPR '00), vol. 3, pp. 3959–3962, Barcelona, Spain, September 2000.
  19. M. Wiltgen, M. Bloice, S. Koller, R. Hoffmann-Wellenhof, J. Smolle, and A. Gerger, “Computer-aided diagnosis of melanocytic skin tumors by use of confocal laser scanning microscopy images,” Analytical and Quantitative Cytology and Histology, vol. 33, no. 2, pp. 85–100, 2011. View at Google Scholar · View at Scopus
  20. B. Weyn, G. van de Wouer, and A. van Daele, “Automated breast tumor diagnosis and grading based on wavelet chromatin texture description,” Cytometry, vol. 33, no. 1, pp. 32–40, 1998. View at Google Scholar
  21. Y. Yoo, K. W. Lee, and B. Y. Kwon, “A comparative study of 3D DWT based space-borne image classification for different types of basis function,” Korean Journal of Remote Sensing, vol. 24, no. 1, pp. 57–64, 2008. View at Google Scholar
  22. X. Gao, Y. Qian, Y. Hui et al., “Texture-based 3D image retrieval for medical application,” in Proceedings of the International Conference e-Health, pp. 101–108, 2010.
  23. C. Tomaci and R. Mabduchi, “Bilateral filtering for gray and color images,” in Proceeding of the 6th IEEE International Conference Computer Vision, pp. 839–846, Bombay, India, January 1998. View at Publisher · View at Google Scholar
  24. D. Barash, “Bilateral filtering and anisotropic diffusion: towards a unified viewpoint,” in Scale-Space and Morphology in Computer Vision, vol. 2106 of Lecture Notes in Computer Science, pp. 273–280, 2006. View at Google Scholar
  25. E. Avci, “Comparison of wavelet families for texture classification by using wavelet packet entropy adaptive network based fuzzy inference system,” Applied Soft Computing Journal, vol. 8, no. 1, pp. 225–231, 2008. View at Publisher · View at Google Scholar · View at Scopus
  26. Z. Chen and R. Ning, “Breast volume denoising and noise characterization by 3D wavelet transform,” Computerized Medical Imaging and Graphics, vol. 28, no. 5, pp. 235–246, 2004. View at Publisher · View at Google Scholar · View at Scopus
  27. H.-G. Hwang, H.-J. Choi, B.-I. Lee, H.-K. Yoon, S.-H. Nam, and H.-K. Choi, “Multi-resolution wavelet-transformed image analysis of histological sections of breast carcinomas,” Cellular Oncology, vol. 27, no. 4, pp. 237–244, 2005. View at Google Scholar · View at Scopus
  28. R. M. Haralick, “Statistical and structural approaches to texture,” Proceeding of the IEEE, vol. 67, no. 5, pp. 786–804, 1979. View at Google Scholar
  29. H. Schulerud, G. B. Kristensen, K. Liestøl et al., “A review of caveats in statistical nuclear image analysis,” Analytical Cellular Pathology, vol. 16, no. 2, pp. 63–82, 1998. View at Google Scholar · View at Scopus
  30. R. A. Johnson, Applied Multivariate Statistical Analysis, Prentice Hall, Upper Saddle River, NJ, USA, 2002.
  31. R. Johnsonbaugh and S. Jost, Pattern Recognition and Image Analysis, Prentice-Hall, Englewood Cliffs, NJ, USA, 1996.
  32. G. A. Losa and C. Castelli, “Nuclear patterns of human breast cancer cells during apoptosis: characterisation by fractal dimension and co-occurrence matrix statistics,” Cell and Tissue Research, vol. 322, no. 2, pp. 257–267, 2005. View at Publisher · View at Google Scholar · View at Scopus
  33. T. Y. Kim, H. J. Choi, H. G. Hwang, and H. K. Choi, “Three-dimensional texture analysis of renal cell carcinoma cell nuclei for computerized automatic grading,” Journal of Medical Systems, vol. 34, no. 4, pp. 709–716, 2010. View at Publisher · View at Google Scholar · View at Scopus