Ridge and furrow pattern classification for acral lentiginous melanoma using dermoscopic images
- 주제(키워드) Acral lentiginous melanoma , Dermoscopic images , Image analysis , Pattern classification
- 등재 SCIE, SCOPUS
- 발행기관 Elsevier Ltd
- 발행년도 2017
- 총서유형 Journal
- URI http://www.dcollection.net/handler/ewha/000000139413
- 본문언어 영어
- Published As http://dx.doi.org/10.1016/j.bspc.2016.09.019
- 저작권 이화여자대학교 논문은 저작권에 의해 보호받습니다.
초록/요약
Background/purpose The development of an automatic diagnostic algorithm using characteristics of dermoscopic findings in acral lentiginous melanoma (ALM) has been slow due to the rarity of melanoma in non-Caucasian populations. In this study, we present an automatic algorithm that can distinguish the “furrow” and “ridge” patterns of pigmentation on the palm and foot, and report its usefulness for the detection of ALM. Methods To distinguish between ALM and nevus, the proposed image analysis is applied. From a dermoscopic image, edges having the steepest ascent or descent are detected through Gaussian derivative filtering. The widths between edges are then measured and the brightness of each stripe is tagged. The dark area is tagged as black and the bright area is tagged as white. The ratio of widths of dark to bright is calculated at each stripe pair and the histogram of the width ratio in the dermoscopic image is generated. Results A total of 297 dermoscopic images confirmed by histopathologic diagnoses are classified. All of the melanoma dermoscopic images were classified correctly using the proposed algorithm, while only one nevus image was misclassified. The proposed method achieved a sensitivity of 100%, a specificity of 99.1%, an accuracy of 99.7%, and a similarity of 99.7%. Conclusion In this study, we propose a novel automatic algorithm that can precisely distinguish the “furrow” and “ridge” patterns of pigmentation on dermoscopic images using the width ratio of dark and bright patterns. It is expected that the proposed algorithm will contribute to the early diagnosis of ALM. © 2016 Elsevier Ltd
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