Weighted performance index for objective evaluation of border detection methods in dermoscopy images

Skin Research and Technology

Volumn 17, Issue 1, 2011, Pages 35-44

  Garnavi, Rahil ^a   Aldeen, Mohammad ^a   Celebi, M E ^b  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b Louisiana State University   (United States)

Author keywords

Border detection; Computer aided diagnosis; Dermoscopy; Evaluation metric; Melanoma; Weighted performance index

Indexed keywords

BORDER DETECTION; DERMOSCOPY; EVALUATION METRICS; MELANOMA; PERFORMANCE INDICES;

DERMATOLOGY; ONCOLOGY; OPTIMIZATION;

COMPUTER AIDED DIAGNOSIS;

ARTICLE; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC ACCURACY; EPILUMINESCENCE MICROSCOPY; EVALUATION; MELANOMA; SENSITIVITY AND SPECIFICITY;

DERMOSCOPY; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; MELANOMA; MODELS, STATISTICAL; REFERENCE STANDARDS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SKIN NEOPLASMS;

EID: 78651452606     PISSN: 0909752X     EISSN: 16000846     Source Type: Journal    
DOI: 10.1111/j.1600-0846.2010.00460.x     Document Type: Article

References (18)

1. "Australia skin cancer facts and figures, " Available at (accessed 1 September 2009).
2. Argenziano G, Soyer HP, Chimenti S et al. Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet. J Am Acad Dermatol 2003; 48: 679-693.
3. Henning JS, Dusza SW, Wang SQ, Marghoob AA, Rabinovitz HS, Polsky D, Kopf AW. The CASH (color, architecture, symmetry, and homogeneity) algorithm for dermoscopy. J Am Acad Dermatol 2007; 56: 45-52.
4. Braun RP, Rabinovitz HS, Oliviero M, Kopf AW, Saurat JH. Dermoscopy of pigmented lesions. J Am Acad Dermatol 2005; 52: 109-121.
5. Celebi ME, Iyatomi H, Schaefer G, Stoecker WV. Lesion border detection in dermoscopy images. Comput Med Imaging Graphics 2009; 33: 148-153.
6. Hintz-Madsen M, Hansen LK, Larsen J, Drzewiecki KT. A probabilistic neural network framework for the detection of malignant melanoma. Artificial Neural Networks In Cancer Diagnosis. R.N.G. Naguib and G.V. Sherbet, CRC Press 2001: 141-183.
7. Iyatomi H, Oka H, Saito M et al. Quantitative assessment of tumour extraction from dermoscopy images and evaluation of computer-based extraction methods for an automatic melanoma diagnostic system. Melanoma Res 2006; 16: 183-190.
8. Melli R, Grana C, Cucchiara R. Comparison of color clustering algorithms for segmentation of dermatological images. SPIE Med Imaging 2006; 6144: 3S1-3S9.
9. Schmid P. Segmentation of digitized dermatoscopic images by two-dimensional color clustering. IEEE Trans Med Imaging 1999; 18: 164-171.
10. Celebi ME, Kingravi HA, Iyatomi H et al. Border detection in dermoscopy images using statistical region merging. Skin Res Technol 2008; 14: 347-353.
11. Celebi ME, Aslandogan YA, Stoecker WV, Iyatomi H, Oka H, Chen X. Unsupervised border detection in dermoscopy images. Skin Res Technol 2007; 13: 454-462.
12. Zhou H, Chen M, Zou L, Gass R, Ferris L, Drogowski L, Rehg JM. "Spatially constrained segmentation of dermoscopy images."5th IEEE International Symposium on Biomedical Imaging, Paris, France, 2008, pp. 800-803.
13. Garnavi R, Aldeen M, Celebi ME, Bhuiyan A, Dolianitis C, Varigos G. "Skin lesion segmentation using color channel optimization and clustering-based histogram thresholding."International Conference on Machine Vision, Image Processing, and Pattern Analysis (MVIPPA09), World Academy of Science, Engineering and Technology, Bangkok, Thailand, vol. 60, 2009, pp. 549-557.
14. Garnavi R, Aldeen M, Celebis ME, Finch S, Varigos G. "Border detection in dermoscopy images using hybrid thresholding on optimized color channels, "Computerized Medical Imaging and Graphics, Special Issue: Skin Cancer Imaging, in press.
15. Guillod J, Schmid-Saugeon P, Guggisberg D, Cerottini JP, Braun R, Krischer J, Saurat JH, Kunt M. Validation of segmentation techniques for digital dermoscopy. Skin Res Technol 2002; 8: 240-249.
16. Celebi ME, Schaefer G, Iyatomi H, Stoecker WV, Malters JM, Grichnik JM. An improved objective evaluation measure for border detection in dermoscopy images. Skin Res Technol 2009; 15: 444-450.
17. Lee T, Ng V, Gallagher R, Coldman A, McLean D. Dullrazor: a software approach to hair removal from images. Comput Biol Med 1997; 27: 533-543.
18. Otsu N. A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybernet 1979; 9: 62-66.