Abrupt skin lesion border cutoff measurement for malignancy detection in dermoscopy images

BMC Bioinformatics

Volumn 17, Issue , 2016, Pages

  Kaya, Sertan ^a   Bayraktar, Mustafa ^b   Kockara, Sinan ^a   Mete, Mutlu ^c   Halic, Tansel ^a   Field, Halle E ^d   Wong, Henry K ^d  

^a UNIVERSITY OF CENTRAL ARKANSAS   (United States)

^b UNIVERSITY OF ARKANSAS AT LITTLE ROCK   (United States)

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

^d UNIVERSITY OF ARKANSAS FOR MEDICAL SCIENCES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COLOR; DERMATOLOGY;

ANALYSIS TECHNIQUES; CLINICAL SETTINGS; DERMOSCOPY IMAGES; PIGMENTED LESIONS; RECALL AND PRECISION; STATISTICAL TEXTURE FEATURES; VECTOR OPERATIONS; YCBCR COLOR SPACES;

DIAGNOSIS;

ALGORITHM; AUTOMATED PATTERN RECOGNITION; COLOR; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC IMAGING; EPILUMINESCENCE MICROSCOPY; HUMAN; MEASUREMENT ACCURACY; MELANOMA; PATHOLOGY; PROCEDURES; SENSITIVITY AND SPECIFICITY; SKIN TUMOR;

ALGORITHMS; COLOR; DATA ACCURACY; DERMOSCOPY; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MELANOMA; PATTERN RECOGNITION, AUTOMATED; SENSITIVITY AND SPECIFICITY; SKIN NEOPLASMS;

EID: 84990856324     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/s12859-016-1221-4     Document Type: Article

References (35)

1. Cancer Facts and Statistics 2015 | Research | American Cancer Society. [Online]. Available: http://www.cancer.org/research/cancerfactsstatistics/cancerfactsfigures2015/. [Accessed: 23 Mar 2016].
2. 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. Arch Dermatol. 1995;131(3):286-91.
3. Stanganelli I, Pizzichetta M-A, [Online]. Available: http://emedicine.medscape.com/article/1130783-overview. Accessed 5 Sept 2016.
4. Vestergaard ME, Macaskill P, Holt PE, Menzies SW. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting. Br J Dermatol. 2008;159(3):669-76.
5. Nachbar F, Stolz W, Merkle T, Cognetta AB, Vogt T, Landthaler M, Bilek P, Braun-Falco O, Plewig G. The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. J Am Acad Dermatol. 1994;30(4):551-9.
6. Dermoscopy_tutorial. [Online]. Available: http://www.dermoscopy.org/atlas/base.htm. [Accessed: 23-Mar-2016].
7. Stolz: Abcd rule of dermatoscopy-a new practical. - Google Scholar. [Online]. Available: https://scholar.google.com/scholar_lookup?title=ABCD+rule+of+dermatoscopy%3A+a+new+practical+method+for+early+recognition+of+malignant+melanoma&author=W.+Stolz&author=A.+Riemann&author=A.+B.+Cognetta+et+al.&publication_year=1994. [Accessed: 23-Mar-2016].
8. Wolf IH, Smolle J, Soyer HP, Kerl H. Sensitivity in the clinical diagnosis of malignant melanoma. Melanoma Res. 1998;8(5):425-9.
9. Lin MJ, Victoria M, Catriona ML, Rory W, Kelly JW. Diagnostic accuracy of malignant melanoma according to subtype. Australas J Dermatol. 2014;55(1):35-42.
10. Tan E, Oakley A, Soyer HP, Haskett M, Marghoob A, Jameson M, Rademaker M. Interobserver variability of teledermoscopy: an international study. Br J Dermatol. 2010;163(6):1276-81.
11. Norton K-A, Iyatomi H, Celebi ME, Ishizaki S, Sawada M, Suzaki R, Kobayashi K, Tanaka M, Ogawa K. Three-phase general border detection method for dermoscopy images using non-uniform illumination correction. Skin Res Technol. 2012;18(3):290-300.
12. Mete M, Kockara S, Aydin K. Fast density-based lesion detection in dermoscopy images. Comput Med Imaging Graph. 2011;35(2):128-36.
13. Suer S, Kockara S, Mete M. An improved border detection in dermoscopy images for density based clustering. BMC Bioinformatics. 2011;12(10):1-10.
14. Freeman H. On the encoding of arbitrary geometric configurations. IRE Trans Electron Comput. 1961;EC-10(2):260-8.
15. Celebi ME, Kingravi HA, Celiker F. Fast colour space transformations using minimax approximations. IET Image Process. 2010;4(2):70-80.
16. Materka A, Strzelecky M. Texture analysis methods-a review. Technical University of Lodz 1998, COST B11-technical report. 1998;11: 873-887.
17. Geman S, Geman D. Stochastic relaxation, Gibbs distribution and the Bayesian restoration of images. IEEE Trans Pattern Anal Mach Intell. 1984;6(11):721-41.
18. Hassner M, Sklansky J. The Use of Markov Random Fields as Model s of Texture. In: Rosenfeld A, Editor. Image Modelling. New York: Academic Press; 1981. pp. 185-98.
19. Udrea A, Popescu D, Miron C. An analysis on the realiability of a series of texture and shape descriptors for melanoma diagnosis. UPB Sci Bull Series C. 2016;78(2):23-134.
20. Digital Image Processing 3rd ed. - R. Gonzalez, R. Woods. [Online]. Available: http://www.academia.edu/7310640/Digital_Image_Processing_3rd_ed._-_R._Gonzalez_R._Woods. [Accessed: 23-Mar-2016].
21. Young IT, Gerbrands JJ, Van Vliet LJ. Fundamentals of image processing. The Netherlands: Delft University of Technology Delft; 1998.
22. Properties of gray-level co-occurrence matrix - MATLAB graycoprops. [Online]. Available: http://www.mathworks.com/help/images/ref/graycoprops.html. [Accessed: 24-Mar-2016].
23. Jähne B. Digital Image Processing. Berlin/Heidelberg: Springer-Verlag; 2005.
24. Argenziano G, Soyer HP, De Giorgi V. Dermoscopy: A Tutorial. Milan: Edra Medical Publishing & New Media; 2002.
25. Cortes C, Vapnik V. Support vector networks. Machine Learn. 1995;20:273-97.
26. Guyon I, Weston J, Barnhill S, Vapnik V. Gene selection for cancer classification using support vector machines. Mach Learn. 2002;46(1-3):389-422.
27. Kockara S, Mete M, Halic T, Yuruk N, Ercan M, Lawrence A. Fractals for Malignancy Detection in Dermoscopy Images. In: Healthcare Informatics (ICHI). International Conference; 2015. pp. 115-121
28. Cunliffe WJ, Goulden V. Phototherapy and acne vulgaris. Br J Dermatol. 2000;142(5):855-6.
29. Avci P, Gupta A, Sadasivam M, Vecchio D, Pam Z, Pam N, Hamblin MR. Low-level laser (light) therapy (LLLT) in skin: stimulating, healing, restoring. Semin Cutan Med Surg. 2013;32(1):41-52.
30. Aziz-Jalali MH, Tabaie SM, Djavid GE. Comparison of Red and infrared Low-level laser therapy in the treatment of acne vulgaris. Indian J Dermatol. 2012;57(2):128-30.
31. Lee SY, You CE, Park MY. Blue and red light combination LED phototherapy for acne vulgaris in patients with skin phototype IV. Lasers Surg Med. 2007;39(2):180-8.
32. Yu H-S, Wu C-S, Yu C-L, Kao Y-H, Chiou M-H. Helium-neon laser irradiation stimulates migration and proliferation in melanocytes and induces repigmentation in segmental-type vitiligo. J Invest Dermatol. 2003;120(1):56-64.
33. Lan C-CE, Wu C-S, Chiou M-H, Chiang T-Y, Yu H-S. Low-energy helium-neon laser induces melanocyte proliferation via interaction with type IV collagen: visible light as a therapeutic option for vitiligo. Br J Dermatol. 2009;161(2):273-80.
34. Low Level Laser (Light) Therapy (LLLT) for Cosmetic Medicine and Dermatology. [Online]. Available: http://photobiology.info/Sawhney.html. Accessed 06 May 2016.
35. Scheinfeld N-S, Goldberg D-J, Laser Treatment of Benign Pigmented Lesions, [Online]. Available: http://emedicine.medscape.com/article/1120359-overview. Accessed 5 Sept 2016.