Abstract
In a computerized image analysis environment, the irregularity of a lesion border has been used to differentiate between malignant melanoma and other pigmented skin lesions. The accuracy of the automated lesion border detection is a significant step towards accurate classification at a later stage. In this paper, we propose the use of a combined Spline and B-spline in order to enhance the quality of dermoscopic images before segmentation. In this paper, morphological operations and median filter were used first to remove noise from the original image during pre-processing. Then we proceeded to adjust image RGB values to the optimal color channel (green channel). The combined Spline and B-spline method was subsequently adopted to enhance the image before segmentation. The lesion segmentation was completed based on threshold value empirically obtained using the optimal color channel. Finally, morphological operations were utilized to merge the smaller regions with the main lesion region. Improvement on the average segmentation accuracy was observed in the experimental results conducted on 70 dermoscopic images. The average accuracy of segmentation achieved in this paper was 97.21 % (where, the average sensitivity and specificity were 94 % and 98.05 % respectively).
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Acknowledgments
The authors would like to thank Dr. Joaquim M. da Cunha Viana and Navid Razmjooy for providing the dermoscopic images to be used in this research work. We would also like to thank the specialist of skin diseases, Dr. Mohammed Ahmed for providing information for our project.
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The authors declare that there is no conflict of interests regarding the publication of this article.
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This article is part of the Topical Collection on Systems-Level Quality Improvement
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Abbas, A.A., Guo, X., Tan, W.H. et al. Combined Spline and B-spline for an Improved Automatic Skin Lesion Segmentation in Dermoscopic Images Using Optimal Color Channel. J Med Syst 38, 80 (2014). https://doi.org/10.1007/s10916-014-0080-7
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DOI: https://doi.org/10.1007/s10916-014-0080-7