An integrated and interactive decision support system for automated melanoma recognition of dermoscopic images

Computerized Medical Imaging and Graphics

Volumn 34, Issue 6, 2010, Pages 479-486

  Rahman, M M ^a   Bhattacharya, P ^a  

^a Concordia University ^*  (Canada)

Author keywords

Classification; Content based image retrieval; Decision support system; Dermoscopy; Fusion; Melanoma; Skin cancer

Indexed keywords

CLASSIFICATION; CLASSIFICATION ACCURACY; CLINICAL APPLICATION; COLOR CHANNELS; COMBINED FEATURES; CONTENT BASED IMAGE RETRIEVAL; DERMOSCOPY; DYSPLASTIC NEVI; IMAGE COLLECTIONS; IMAGE FEATURES; INTENSITY IMAGES; INTERACTIVE DECISION SUPPORT SYSTEM; LOCAL COLOR; SEGMENTATION METHODS; SKIN CANCERS; THRESHOLDING; VARIANCE-COVARIANCE;

ARTIFICIAL INTELLIGENCE; CONTENT BASED RETRIEVAL; DECISION MAKING; DECISION SUPPORT SYSTEMS; DECISION THEORY; DERMATOLOGY; FEATURE EXTRACTION; IMAGE SEGMENTATION; INFORMATION RETRIEVAL; ONCOLOGY;

IMAGE FUSION;

ARTICLE; CANCER DIAGNOSIS; COLOR VISION; DECISION SUPPORT SYSTEM; EPILUMINESCENCE MICROSCOPY; HUMAN; IMAGE PROCESSING; MEDICAL DECISION MAKING; MELANOMA; NONHUMAN; PRIORITY JOURNAL; TASK PERFORMANCE;

ALGORITHMS; DECISION MAKING, COMPUTER-ASSISTED; DERMOSCOPY; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MELANOMA; PATTERN RECOGNITION, AUTOMATED;

EID: 77954385516     PISSN: 08956111     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compmedimag.2009.10.003     Document Type: Article

References (28)

1. Rigel D.S., Carucci J.A. Malignant melanoma: prevention, early detection, and treatment in the 21st century. CA: Cancer J Clin 2000, 50:215-236.
2. Binder M., Schwarz M., Winkler A., Steiner A., Kaider A., Wolff K., et al. Epiluminescence microscopy. A useful tool for the diagnosis of pigmented skin lesions for formally trained dermatologists. Arch Dermatol 1995, 131(3):286-291.
3. Johr R.H. Dermoscopy: alternative melanocytic algorithms-the ABCD rule of dermatoscopy, Menzies scoring method, and 7-point checklist. Clin Dermatol 2002, 20(3):240-247.
4. Saugeon P.S., Guillod J., Thiran J. Towards a computer-aided diagnosis system for pigmented skin lesions. Comput Med Imaging Graph 2003, 27:65-78.
5. Maglogiannis I., Pavlopoulos S., Koutsouris D. An integrated computer supported acquisition, handling, and characterization system for pigmented skin lesions in dermatological images. IEEE Trans Inf Technol Biomed 2005, 9(1):86-98.
6. Ganster H., Pinz A., Röhrer R., Wildling E., Binder M., Kittler H. Automated melanoma recognition. IEEE Trans Med Imaging 2001, 20(3):233-239.
7. Maglogiannis I.G., Zafiropoulos E.P. Characterization of digital medical images utilizing support vector machines. BMC Med Inform Decis Making 2004, 4(4).
8. Dreiseitl S., Ohno-Machado L., Kittler H., Vinterbo S., Billhardt H., Binder M. A comparison of machine learning methods for the diagnosis of pigmented skin lesions. J Biomed Inform 2001, 34(1):28-36.
9. Smeulders A., Worring M., Santini S., Gupta A., Jain R. Content-based image retrieval at the end of the early years. IEEE Trans Pattern Anal Mach Intell 2000, 22(12):1349-1380.
10. Kittler J., Hatef M., Duin R.P.W., Matas J. On combining classifiers. IEEE Trans Pattern Anal Mach Intell 1998, 20(3):226-239.
11. Xu L., Jackowski M., Goshtasby A., Roseman D., Bines S., Yu C., et al. Segmentation of skin cancer images. Image Vis Comput 1999, 17:65-74.
12. Umbaugh S.E., Moss R.H., Stoecker W.V., Hance G.A. Automatic color segmentation algorithms: with application to skin tumor feature identification. IEEE Eng Med Biol Mag 1993, 12(3):75-82.
13. Rahman M.M., Desai B.C., Bhattacharya P. Image retrieval-based decision support system for dermatoscopic image. Proceedings of the IEEE symposium on computer-based medical systems 2006, 285-290.
14. Rahman M.M., Bhattacharya P., Desai B.C. A multiple expert-based melanoma recognition system for dermoscopic images of pigmented skin lesions. Proceedings of 8th IEEE international conference on bioinformatics and bioengineering (BIBE 2008) 2008.
15. Miyahara M., Yoshida Y. Mathematical transform of (r,g,b) color data to Munsell (h,v,c) color data. SPIE Proc Vis Commun Image Process 1988, 1001:650-657.
16. Gong Y., Proietti G., Faloutsos C. Proc Int Conf Comput Vis Pattern Recognit 1998, 578.
17. Bezdek J.C., Pal M.R., Keller J., Krisnapuram R. Fuzzy models and algorithms for pattern recognition and image processing 1999, Kluwer Academic Publishers, Boston.
18. Ridler T.W., Calvard S. Picture thresholding using an iterative selection method. IEEE Trans Syst Man Cybernet 1978, SMC-8:630-632.
19. Kohonen T. Self-organizing formation of topologically correct feature maps. Biol Cybernet 1982, 43(1):59-69.
20. Haralick R.M., Shanmugam K., Dinstein I. Textural features for image classification. IEEE Trans Syst Man Cybernet 1973, 3:610-621.
21. Fukunaga K. Introduction to statistical pattern recognition 1990, Academic Press, Boston. 2nd ed.
22. Xu L., Krzyzak A., Suen C.Y. Methods of combining multiple classifiers and their applications to handwriting recognition. IEEE Trans Syst Man Cybernet 1992, 23(3):418-435.
23. Burges J.C. A tutorial on support vector machines for pattern recognition. Data Min Knowledge Discov 1998, 2:121-167.
24. Wu T.F., Lin C.J., Weng R.C. Probability estimates for multi-class classification by pairwise coupling. J Mach Learn Res 2004, 5:975-1005.
25. Dermatology Image Atlas, Dermnet: the dermtologist's image resource; 2006. Available at: http://www.dermnet.com/.
26. Menzies S.W., Crotty K., Ingvar C., McCarthy W. An atlas of surface microscopy of pigmented skin lesions-dermoscopy 2003, McGraw-Hill Book Co., Sydney. 2nd ed. & CDROM quiz.
27. Baeza-Yates R., Ribeiro-Neto B. Modern information retrieval 1999, Addison-Wesley, Reading, MA.
28. Chang CC, Lin CJ. LIBSVM: a library for support vector machines; 2001. Available at: http://www.csie.ntu.edu.tw/cjlin/libsvm.