RETRIEVAL IN DERMATOLOGY USING INTELLIGENT TECHNIQUES

Ganasigamony W. Jiji and Peter Savariraj J.D. Raj

References

  1. [1] M.E. Celebi, H.A. Kingravi, B. Uddin, H. Iyatomi, Y.A. Aslandogan, W.V. Stoecker, and R.H. Moss, A methodological approach to the classification of dermoscopy images, Computerized Medical Imaging and Graphics, 31(6), 2007, 362–373.
  2. [2] K. Hoffmann, T. Gambichler, A. Rick, M. Kreutz, M. Anschuetz, T. Grünendick, A. Orlikov, S. Gehlen, R. Perotti, L. Andreassi, J.N. Bishop, J-P. Césarini, T. Fischer, P.J. Frosch, R. Lindskov, R. Mackie, D. Nashan, A. Sommer, M. Neumann, J.P. Ortonne, P. Bahadoran, P.F. Penas, U. Zoras and P. Altmeyer, Diagnostic and neural analysis of skin cancer (DANAOS). A multicentre study for collection and computer-aided analysis of data from pigmented skin lesions using digital dermoscopy, British Journal of Dermatology, 149(4), 2003, 801–809.
  3. [3] J.C. Bystryn, Epiluminescence microscopy: A re-evaluation of its purpose, Archives of Dermatology, 137(3), 2001, 377–378.
  4. [4] P. Vadakkepat, P. Lim, L. De Silva, L. Jing, and L.L. Ling, Multimodal approach to human-face detection and tracking, IEEE Transactions on Industrial Electronics, 55(3), 2008, 1385–1393.
  5. [5] C.S. Chan, H. Liu, and D.J. Brown, Recognition of human motion from qualitative normalised templates, Journal of Intelligent and Robotic Systems, 48(1), 2007, 79–95.
  6. [6] N. Kubota and K. Nishida, Perceptual control based on prediction for natural communication of a partner robot, IEEE Transactions on Industrial Electronics, 54(2), 2007, 866–877.
  7. [7] O. Linda and M. Manic, Fuzzy force-feedback augmentation for manual control of multi-robot system, IEEE Transactions on Industrial Electronics, 58(8), 2010, 3213–3220.
  8. [8] G. Pratl, D. Dietrich, G.P. Hancke, and W.T. Penzhorn, A new model for autonomous, networked control systems, IEEE Transactions on Industrial Informatics, 3(1), 2007, 21–32.
  9. [9] R.M. Haralick, K. Shanmugam, and I. Dinstein, Textural features for image classification, IEEE Transactions on Systems, Man and Cybernetics, 3, 1973, 610–621.
  10. [10] B. Julesz, Textons, The elements of texture perception, and their interactions, Nature, 290, 1981, 91–97.
  11. [11] J.G. Daugman, Uncertainty relation for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters, Journal of Optical Society of America, A2, 1985, 1160–1169.
  12. [12] A. Drimbarean and P.F. Whelan, Experiments in color texture analysis, Pattern Recognition Letter, 22, 2001, 1161–1167.
  13. [13] T. M¨aenp¨a¨a and M. Pietik¨ainen, Classification with color and texture: Jointly or separately? Pattern Recognition, 37, 2004, 1629–1640.
  14. [14] H.H.W.J. Bosman, N. Petkov, and M.F. Jonkman, Comparison of color representations for content based image retrieval in dermatology, Skin Research and Technology, 16, 2010, 109–113.
  15. [15] C. Li, C. Xu, C. Gui, and M.D. Fox, Level set evolution without re-initialization: A new variational formulation, Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), San Diego, CA, Vol. 1, 2005, 430–436.
  16. [16] J.A. Schnabel, Multi-scale active shape description in medical imaging, Doctoral Dissertation, University of London, 1997.
  17. [17] R.L. Graham, An efficient algorithm for determining the convex hull of a finite planar set, Information Processing Letters, 1, 1972, 132–133.
  18. [18] M. Yang, K. Kpalma, and J. Ronsin, A survey of shape feature extraction techniques, pattern recognition techniques, technology and applications, in Y. Peng-Yeng (ed.), (I-Tech, Vienna, Austria, 2008), pp. 626, ISBN 978-953-7619-24-4.
  19. [19] M. Amadasum and R. King, Texture feature corresponding to textural properties, IEEE Transactions on Systems, Man and Cybernetics, 19(5), 1989, 1264–1274.
  20. [20] G.W. Jiji, Colour texture classification for human tissue images, Elsevier Editorial SystemTM for Applied Soft Computing, 11, 2011, 1623–1630.
  21. [21] F. Lopez, J.M. Valiente, R. Baldrich, and M. Vanrell, Fast surface grading using color statistics in the CIE lab space, Pattern Recognition and Image Analysis, Springer, Berlin, Heidelberg, 2005, 666–673.
  22. [22] F. Bianconi, R.H. P.Southam, and A. Fernandez, Theoretical and experimental comparison of different approached for color texture classification, Journal of Electronic Imaging 043006, 20(4), 2011, 1–17.
  23. [23] H. Hsin, C. Li, M. Sun, and R.J. Sclabassi, An adaptive training algorithm for back-propagation neural networks, IEEE Transactions on SMC, 25, 1995, 512–514.
  24. [24] S. Dasgupta, The evolution of the D2-statistic of Mahalanobis, Indian Journal of Pure Applied Mathematics, 26(6), 1995, 485–501.
  25. [25] R. Fabbri, L.D.F. Costa, J.C. Torelli, and O.M. Bruno, 2D Euclidean distance transform algorithm: A comparative survey, ACM Computing Surveys, 40(1), 2008, p. 2.
  26. [26] T.W. Schoenharl and G. Madey, Evaluation of measurement techniques for the validation of agent-based simulations against streaming data, Computational Science – ICCS, Springer, Berlin, Heidelberg, 2008, 6–15.
  27. [27] S.B. Park, J.W. Lee, and S.K. Kim, Content-based image classification using a neural network, Pattern Recognition Letters, 25, 2004, 287–300.

Important Links:

Go Back