Analysis of density based and fuzzy c-means clustering methods on lesion border extraction in dermoscopy images

BMC Bioinformatics

Volumn 11, Issue SUPPL. 6, 2010, Pages

  Kockara, Sinan ^a   Mete, Mutlu ^b   Chen, Bernard ^a   Aydin, Kemal ^c  

^a UNIVERSITY OF CENTRAL ARKANSAS   (United States)

^b TEXAS A AND M UNIVERSITY COMMERCE   (United States)

^c UNIVERSITY OF ARKANSAS AT PINE BLUFF   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED ASSESSMENT; DENSITY-BASED CLUSTERING; DERMOSCOPIC IMAGES; DIAGNOSTIC PROCEDURE; FUZZY C-MEANS CLUSTERING ALGORITHMS; FUZZY C-MEANS CLUSTERING METHOD; PRECISION AND RECALL; THERAPEUTIC INTERVENTION;

CLUSTERING ALGORITHMS; FUZZY SYSTEMS; IMAGE SEGMENTATION;

DIAGNOSIS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; EPILUMINESCENCE MICROSCOPY; FUZZY LOGIC; HUMAN; MELANOMA; METHODOLOGY; SKIN TUMOR;

ALGORITHMS; CLUSTER ANALYSIS; DERMOSCOPY; FUZZY LOGIC; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MELANOMA; PATTERN RECOGNITION, AUTOMATED; SKIN NEOPLASMS;

EID: 77957712918     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-26     Document Type: Article

References (36)

1. Jemal A, Siegel R, Ward E, Hao Y, Xu J, Murray T, Thun MJ. Cancer statistics. A Cancer Journal for Clinicians 2008, 59:225-249. CA.
2. Levy P, Berk W, Compton S, King J, Sweeny P, Kuhn G, Bock B. Effect of Rapid Patient Evaluation on the Rate and Type of Error Citation of Emergency Physicians. Annals of Emergency Medicine 2005, 46(3):108-109.
3. Pantofaru C, Hebert M. A Comparison of Image Segmentation Algorithms. Tech. report CMU-RI-TR-05-40 2005, Robotics Institute, Carnegie Mellon University.
4. Pathegama M, Göl T. Edge-end pixel extraction for edge-based image segmentation. Transactions on Engineering, Computing and Technology 2004, 2:213-216. 1305-5313.
5. Pal NR, Pal SK. A review of image segmentation techniques. Pattern Recogn 1993, 26(9):1277-1294.
6. Skarbek W, Koschan A. Colour image segmentation-a survey. Technical report. Institute for Technical Informatics 1994, Technical University of Berlin, October 1994., http://citeseer.nj.nec.com/skarbek94colour.html
7. Sezgin M, Sankur B. Image thresholding techniques: Quantitative performance evaluation. Journal of Electronic Imaging 2004, SPIE.
8. Shapiro LG, Stockman GC. Computer Vision,. 2001, 279-325. New Jersey, Prentice-Hall, 0-13-030796-3.
9. Shi J, Belongie S, Leung T, Malik J. Image and Video Segmentation: The Normalized Cut Framework. Proc. of 1998 Int'l Conf. on Image Processing (ICIP'98) 1998, 1:943-947. Chicago, IL.
10. Jianbo S, Malik J. Normalized cuts and image segmentation. IEEE Trans. on Pattern Analysis and Machine Intelligence 2000, 22(8):888-905.
11. Felzenszwalb PF, Huttenlocher DP. Efficient graph-based image segmentation. International Journal of Computer Vision 2004, 59(2):167-181.
12. Argenziano G, Soyer HP, De Giorgi V. Dermoscopy: A Tutorial. EDRA Medical Publishing & New Media 2002,
13. Steiner K, Binder M, Schemper M, Wolff K, Pehamberger H. Statistical evaluation of epiluminescence dermoscopy criteria for melanocytic pigmented lesions. Journal of the American Academy of Dermatology 1993, 29(4):581-588. 10.1016/0190-9622(93)70225-I, 8408794.
14. Binder M, Schwarz M, Winkler A, Steiner A, Kaider A, Wolff K, Pehamberger H. Epiluminescence Microscopy: a Useful Tool For The Diagnosis Of Pigmented Skin Lesions For Formally Trained Dermatologists. Archives Of Dermatology 1995, 131(3):286-291. 10.1001/archderm.131.3.286, 7887657.
15. Fleming MG, Steger C, Zhang J, Gao J, Cognetta AB, Pollak I, Dyer CR. Techniques for a structural analysis of dermatoscopic imagery. Comput Med Imaging Graph 1998, 22(5):375-389. 10.1016/S0895-6111(98)00048-2, 9890182.
16. Celebi ME, Aslandogan YA, Stoecker WV, Iyatomi H, Oka H, Chen X. Unsupervised Border Detection in Dermoscopy Images. Skin Res Technol 2007, 13(4):454-462. 10.1111/j.1600-0846.2007.00251.x, 17908199.
17. Celebi ME, Iyatomi H, Schaefer G, Stoecker WV. Lesion Border Detection in Dermoscopy Images. Comput Med Imaging Graph 2009, 33(2):148-153. 10.1016/j.compmedimag.2008.11.002, 2671195, 19121917.
18. Hance GA, Umbaugh SE, Moss RH, Stoecker WV. Unsupervised color image segmentation with application to skin tumor borders. IEEE Engineering in Medicine and Biology 1996, 15(1):104-11.
19. Pratt WK. Digital image processing: PIKS inside. 2007, Hoboken, NJ: John Wiley & Sons.
20. Carlotto MJ. Histogram Analysis Using a Scale-Space Approach. IEEE Transaction on Pattern Analysis and Machine Intelligence 1987, 1(9):121-129.
21. Delgado D, Butakoff C, Ersboll BK, Stoecker WV. Independent histogram pursuit for segmentation of skin lesions. IEEE Trans on Biomedical Engineering 2008, 55(1):157-61.
22. Celebi ME, Kingravi HA, Iyatomi H, et al. Border Detection in Dermoscopy Images Using Statistical Region Merging. Skin Res Technol 2008, 14(3):347-353. 10.1111/j.1600-0846.2008.00301.x, 19159382.
23. Schmid P. Segmentation Of Digitized Dermoscopic Images by Two-Dimensional Color Clustering. IEEE Transaction on Medical Imaging 1999, 18:164-171.
24. Geusebroek J-M, Smeulders AW, van deWeijer MJ. Fast anisotropic gauss filtering. IEEE Trans on Image Processing 2003, 12(8):938-43.
25. Perreault S, Hébert P. Median filtering in constant time. IEEE Trans on Image Processing 2007, 16(9):2389-94.
26. Lee TK, Ng V, Gallagher R. Dullrazor: A software approach to hair removal from images. Comput Biol Med 1997, 27(6):533-543. 10.1016/S0010-4825(97)00020-6, 9437554.
27. Zhou H, Chen M, Gass R, et al. Feature-preserving artifact removal from dermoscopy images. Proceedings of the SPIE medical imaging 2008 conference 2008, 6914:69141B-69141B-9.
28. Wighton P, Lee TK, Atkins MS. Dermoscopic hair disocclusion using inpainting. Proceedings of the SPIE medical imaging 2008, Conference 6914:691427-691427-8.
29. Sonka M, Hlavac V, Boyle R. Image processing, analysis, and machine vision. Cengage-Engineering 2007,
30. Melli R, Grana C, Cucchiara R. Comparison of color clustering algorithms for segmentation of dermatological images. Proceedings of the SPIE medical imaging 2006 Conference 2006, 3S1-9S39.
31. Lee I, Estivill-Castro V. Polygonization of Point Clusters Through Cluster Boundary Extraction For Geographical Data Mining. Proceedings of the 10th International Symposium on Spatial Data Handling 2002, 27-40.
32. Nosovskiy GV, Liu D, Sourina O. Automatic clustering and boundary detection algorithm based on adaptive influence function. Pattern Recognition 2008, 41(9):2757-2776.
33. Ester M, Kriegel H-P, Sander J, Xu X. A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining 1996, 226-231.
34. Dunn JC. A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters. Journal of Cybernetics 1973, 3:32-57.
35. Bezdek JC. Pattern Recognition with Fuzzy Objective Function Algoritms. 1981, Plenum Press, New York.
36. Celebi ME, Iyatomi H, Schaefer G, Stoecker WV. Approximate Lesion Localization in Dermoscopy Images. Skin Res Technol 2009, 15(3):314-322. 10.1111/j.1600-0846.2009.00357.x, 19624428.