A machine learning based system for multichannel fluorescence analysis in pancreatic tissue bioimages

8th IEEE International Conference on BioInformatics and BioEngineering, BIBE 2008

Volumn , Issue , 2008, Pages

  Herold, Julia ^a   Abouna, Sylvie ^b   Zhou, Luxian ^b   Pelengaris, Stella ^b   Epstein, David B A ^c   Khan, Michael ^b   Nattkemper, Tim W ^a  

^a BIELEFELD UNIVERSITY   (Germany)

^b UNIVERSITY OF WARWICK   (United Kingdom)

^c UNIVERSITY OF WARWICK   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL TECHNIQUES; BIOLOGICAL OBJECTS; CELL NUMBER; CELL TYPES; FLUORESCENCE ANALYSIS; FLUORESCENCE IMAGE; HIGH-CONTENT; HIGH-THROUGHPUT; ISLETS OF LANGERHANS; MACHINE-LEARNING; MULTI-CHANNEL; PANCREATIC TISSUE; RAPID DETERMINATION; SEMANTIC ANNOTATIONS; SEMANTIC IMAGES; SYSTEMS BIOLOGY;

BIOINFORMATICS; FLUORESCENCE MICROSCOPY; IMAGE ANALYSIS; ROBOT LEARNING; SEMANTICS;

FLUORESCENCE;

EID: 67549097164     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/BIBE.2008.4696798     Document Type: Conference Paper

References (20)

1. D.S. Rigel, and J.A. Carucci, "Malignant melanoma: prevention, early detection, and treatment in the 21st century," CA: Cancer J Clin., vol. 50, pp. 215-36, 2000.
2. M. Binder, M. Schwarz, A. Winkler, A. Steiner, A. Kaider, K. Wolff, and H. Pehamberger, "Epiluminescence microscopy. A useful tool for the diagnosis of pigmented skin lesions for formally trained dermatologists," Arch Dermatol., vol. 131(3), pp. 286-291, 1995.
3. R.H. Johr, "Dermoscopy: alternative melanocytic algorithms-the ABCD rule of dermatoscopy, Menzies scoring method, and 7-point checklist," Clin Dermatol., vol. 20(3), pp. 240-247, 2002.
4. H. Ganster, A. Pinz, R. Rohrer, E. Wildling, M. Binder, and H. Kittler, "Automated Melanoma Recognition," IEEE Trans Med Imaging, vol. 20, No. 3, pp. 233-239, 2001.
5. M. Binder, H. Kittler, A. Seeber, and A. Steiner, "Epiluminescence microscopy-based classification of pigmented skin lesions using computerized image analysis and an artificial neural network," Melanoma Res., vol. 8, pp. 261-266, 1998.
6. S. Dreiseitl, L. Ohno-Machado, H. Kittler, S. Vinterbo, H. Billhardt, and M. Binder, "A comparison of machine learning methods for the diagnosis of pigmented skin lesions," J Biomed Inform., vol. 34(1), pp. 28-36, 2001.
7. J. Kittler, M. Hatef, R.P.W. Duin, and J. Matas, "On combining classifiers," IEEE Trans Pattern Anal Machine Intell, vol. 20 (3), pp. 226-239, 1998.
8. L. Xu, M. Jackowski, A. Goshtasby, D. Roseman, S. Bines, C. Yu, A. Dhawan, and A. Huntley, "Segmentation of skin cancer images," Image Vis. Computing, vol. 17, pp. 65-74, 1999.
9. S.E. Umbaugh, R.H. Moss, W.V. Stoecker, and G. A. Hance, "Automatic color segmentation algorithms: With application to skin tumor feature identification," IEEE Eng. Med. Biol. Mag., vol. 12(3), pp. 75-82, 1993.
10. M. Miyahara, and Y. Yoshida, "Mathematical transform of (r,g,b) color data to Munsell (h,v,c) color data," SPIE Proc. in Vis Comm and Image Process., vol. 1001, pp. 650-657, 1988.
11. J.C. Bezdek, M. R. Pal, J. Keller, and R. Krisnapuram, Fuzzy Models and Algorithms for Pattern Recognition and Image Processing., Kluwer Academic Publishers, Boston, 1999.
12. T.W. Ridler and S. Calvard, "Picture thresholding using an iterative selection method," IEEE Transactions on Systems, Man and Cybernetics, vol. SMC-8, pp. 630-632, 1978.
13. R.M. Haralick, Shanmugam, and I. Dinstein, "Textural features for image classification," IEEE Trans Syst Man Cybernetics, vol. 3, pp. 610-621, 1973.
14. K. Fukunaga, Introduction to Statistical Pattern Recognition, Boston, 2nd edition: Academic Press; 1990.
15. L. Xu, A. Krzyzak, and C. Y. Suen, "Methods of combining multiple classifiers and their applications to handwriting recognition," IEEE Trans. Sys. Man. Cybern., vol. 23(3), pp. 418-435, 1992.
16. J.C. Burges, "A Tutorial on Support Vector Machines for Pattern Recognition," Data Mining and Knowledge Discovery, vol. 2, pp. 121167, 1998.
17. T.F. Wu, C.J. Lin, and R.C. Weng, "Probability Estimates for Multi-c lass Classification by Pairwise Coupling," J Machine Learning Research, vol. 5, pp. 975-1005, 2004.
18. Dermatology Image Atlas, "Dermnet: the dermtologist's image resource", 2006, available at: http://www.dermnet.com/
19. S.W. Menzies, K. Crotty, C. Ingvar, and W. McCarthy, An atlas of surface microscopy of pigmented skin lesions dermoscopy, 2nd Edition &CDROM quiz, Sydney, McGraw-Hill Book Co., 2003.
20. C.C. Chang, and C.J. Lin, "LIBSVM: a library for support vector machines.", 2001, Available: http://www.csie.ntu.edu.tw/cjlin/libsvm