Classification of dermatological images using advanced clustering techniques

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

Volumn , Issue , 2010, Pages 6721-6724

  Tasoulis, S K ^a   Doukas, C N ^b   Maglogiannis, I ^a   Plagianakos, V P ^a  

^a UNIVERSITY OF CENTRAL GREECE   (Greece)

^b UNIVERSITY OF THE AEGEAN   (Greece)

Author keywords

Classification; Cluster analysis; Feature extraction; Image analysis; Kernel density estimation; Pigmented skin lesion; Principal component analysis

Indexed keywords

BORDER DETECTION; CLASSIFICATION; CLUSTERING TECHNIQUES; DERMATOLOGICAL IMAGES; DIAGNOSIS SYSTEMS; EARLY DETECTION; HIGH DIMENSIONAL DATA; IMAGE PROCESSING TECHNIQUE; KERNEL DENSITY ESTIMATION; MALIGNANT MELANOMA; NOVEL CLUSTERING; PIGMENTED SKIN LESIONS; PRINCIPAL COMPONENTS; SKIN CANCERS; TEXTURE PROCESSING;

CLUSTER ANALYSIS; CLUSTERING ALGORITHMS; COMPUTER VISION; DERMATOLOGY; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE SEGMENTATION;

PRINCIPAL COMPONENT ANALYSIS;

ALGORITHM; ARTICLE; CLUSTER ANALYSIS; HUMAN; IMAGE PROCESSING; MELANOMA; SKIN TUMOR;

ALGORITHMS; CLUSTER ANALYSIS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MELANOMA; SKIN NEOPLASMS;

EID: 78650850938     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2010.5626242     Document Type: Conference Paper

References (17)

1. D. Boley, Principal direction divisive partitioning, Data Mining and Knowledge Discovery, 2(4), 1998, pp 325-344.
2. D.H. Chung and G. Sapiro, Segmenting skin lesions with partialdifferential-equations-based image processing algorithms, IEEE Trans. on Medical Imaging, 19(7), 2000, pp 763-767.
3. I. Dhillon, J. Kogan, and C. Nicholas, Feature selection and document clustering, A Comprehensive Survey of Text Mining, Springer-Verlag, 73-100, 2003.
4. A.K. Jain, M.N. Murty, and P.J. Flynn, Data clustering: a review, ACM Computing Surveys, 31(3), 1999, pp 264-323.
5. I. Maglogiannis, Automated segmentation and registration of dermatological images, J. Math. Model. Algorithms, 2(3), 2003, pp 277-294.
6. I. Maglogiannis, S. Pavlopoulos, and D. Koutsouris, An integrated computer supported acquisition, handling and characterization system for pigmented skin lesions in dermatological images, IEEE Trans. On Information Technology in Biomedicine, 9(1), 2005, pp 86-98.
7. I. Maglogiannis and C. Doukas, Overview of advanced computer vision systems for skin lesions characterization, IEEE Trans. on Information Technology in Biomedicine, 13(5), 2009, pp 721-33.
8. R. Marks, Epidemiology of melanoma, Clin. Exp. Dermatol., 25, 2000, pp 459-463.
9. F. Nachbar, W. Stolz, T. Merkle, A.B. Cognetta, T. Vogt, M. Landthaler, P. Bilek, O. Braun-Falco, and G. Plewig, The ABCD rule of dermatoscopy: High prospective value in the diagnosis of doubtful melanocytic skin lesions, J. Amer. Acad. Dermatol., 30(4), 1994, pp 551-559.
10. M. Nilsson, Hierarchical Clustering using non-greedy principal direction divisive partitioning, Information Retrieval 5(4), 2002, pp 311-321.
11. R. Pariser and D. Pariser, Primary care physicians errors in handling cutaneous disorders, J. Am. Acad. Dermatol., 17(3), 1987, pp 239-245.
12. J.E. Sanders, B.S. Goldstein, D.F. Leotta, and K.A. Richards, Image processing techniques for quantitative analysis of skin structures, Computer Methods and Programs in Biomedicine, 59(3), 1999, pp 167-180.
13. S.K. Tasoulis, V.P. Plagianakos, and D.K. Tasoulis, Projection based clustering at gene expression data, In: Computational Intelligence methods for Bioinformatics and Biostatistics CIBB2009), Genova, Italy, 2009.
14. S. Tasoulis and D. Tasoulis, Improving principal direction divisive clustering, In: 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2008), Las Vegas, USA, 2008.
15. S.K. Tasoulis, C.N. Doukas, I. Maglogiannis, and V.P. Plagianakos, Skin Lesions Characterisation Utilising Clustering Algorithms, In: 6th Hellenic Conference on Artificial Intelligence (SETN10), Samos, Greece, 2010.
16. C. Yang, R. Duraiswami, N.A. Gumerov, and L. Davis, Improved fast gauss transform and efficient kernel density estimation, In: Ninth IEEE International Conference on Computer Vision, Nice, France, 2003, pp 664-671.
17. Z. Zhang, W. Stoecker, and R. Moss, Border detection on digitized skin tumor image, IEEE Trans. on Medical Imaging 19(11), 2000, pp 1128-1143.