The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Unsupervised border detection in dermoscopy images
Open accessAbstract
Background: As a result of the advances in skin imaging technology and the development of suitable image processing techniques, during the last decade, there has been a significant increase of interest in the computer‐aided diagnosis of skin cancer. Automated border detection is one of the most important steps in this procedure as the accuracy of the subsequent steps crucially depends on the accuracy of this step. Methods: In this article, we present an unsupervised approach to border detection in dermoscopy skin lesion images based on a modified version of the JSEG algorithm. Results: The method is tested on a set of 100 dermoscopy images. The border detection error is quantified by a metric that uses manually determined borders from a dermatologist as the ground truth. The results are compared with three other automated methods and manually determined borders by a second dermatologist. Conclusion: The results demonstrate that the presented method achieves both fast and accurate border detection in dermoscopy images.
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Citations
Cites
Diagnostic accuracy of dermoscopy
Kittler, H., Pehamberger, H., Wolff, K., & Binder, M. (2002) · The Lancet Oncology · doi:10.1016/s1470-2045(02)00679-4 · Cited by 1,349
Cited by
Lesion border detection in dermoscopy images
Celebi, M. E., Iyatomi, H., Schaefer, G., & Stoecker, W. V. (2009) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2008.11.002 · Cited by 422
Self-citationBorder detection in dermoscopy images using statistical region merging
Emre Celebi, M., Kingravi, H. A., Iyatomi, H., Alp Aslandogan, Y., Stoecker, W. V., Moss, R. H., Malters, J. M., Grichnik, J. M., Marghoob, A. A., Rabinovitz, H. S., et al. (2008) · Skin Research and Technology · doi:10.1111/j.1600-0846.2008.00301.x · Cited by 366
Self-citationMachine learning applications in the evaluation and management of psoriasis: a systematic review
Yu, K., Syed, M. N., Bernardis, E., & Gelfand, J. M. (2020) · Journal of Psoriasis and Psoriatic Arthritis · doi:10.1177/2475530320950267 · Cited by 65
Metadata
- Authors
- Emre Celebi, M., Alp Aslandogan, Y., Stoecker, W. V., Iyatomi, H., Oka, H., & Chen, X.
- Venue
- Skin Research and Technology
- Publisher
- Wiley
- Published
- 2007-03-09
- Volume
- 13
- Issue
- 4
- Pages
- 454-462
- ISSN
- 0909-752X (ISSN-L)
- 1600-0846
- OpenAlex
- W2069493544
- Cited by
- 187
- References
- 1
- FWCI
- 4.83
- Type
- journal article
- Language
- en
- Open access
- green
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- Emre Celebi, M., Alp Aslandogan, Y., Stoecker, W. V., Iyatomi, H., Oka, H., & Chen, X. (2007). Unsupervised border detection in dermoscopy images. Skin Research and Technology. https://doi.org/10.1111/j.1600-0846.2007.00251.x
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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