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Ridge and furrow pattern classification for acral lentiginous melanoma using dermoscopic images

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Author(s)
Sejung YangByungho OhSungwon HahmKee-Yang ChungByung-Uk Lee
Keimyung Author(s)
Oh, Byung Ho
Department
Dept. of Dermatology (피부과학)
Journal Title
Biomedical Signal Processing and Control
Issued Date
2017
Volume
32
Keyword
Acral lentiginous melanomaImage analysisPattern classificationDermoscopic images
Abstract
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.
Previous article in issue
Keimyung Author(s)(Kor)
오병호
Publisher
School of Medicine
Citation
Sejung Yang et al. (2017). Ridge and furrow pattern classification for acral lentiginous melanoma using dermoscopic images. Biomedical Signal Processing and Control, 32, 90–96. doi: 10.1016/j.bspc.2016.09.019
Type
Article
ISSN
1746-8094
Source
https://www.sciencedirect.com/science/article/pii/S1746809416301458?via%3Dihub
DOI
10.1016/j.bspc.2016.09.019
URI
https://kumel.medlib.dsmc.or.kr/handle/2015.oak/32732
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Dermatology (피부과학)
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