HAIR ARTIFACT REMOVAL AND SKIN LESION SEGMENTATION OF DERMOSCOPY IMAGES


Julie Ann Salido, Conrado Ruiz Jr

Abstract


Objective: The objective of this research is to perform automatic hair artifact removal and skin lesion segmentation on dermoscopy images.

Methods: Dermoscopy images are images from the examination of the skin lesion using a dermatoscope. There are different types of skin lesion artifacts, structures, or objects that are present in dermoscopy images. This is a pertinent problem that can inhibit the proper examination and accurately segment the skin lesion from the surrounding skin area. Artifacts, such as hair strands, introduce additional features that can also cause problems during classification. Our process starts with hair removal using a median filter on each color space of RGB, a bottom hat filter, a binary conversion, a dilation and morphological opening, and then the removal of small connected pixels. The detected hair regions are then filled up using harmonic inpainting. Then, skin lesion segmentation is performed using a binary conversion, a dilation, a perimeter detection and morphological opening, and then the removal of small connected pixels.

Results: Experiments were carried out on the PH2 dermoscopy images. The border of the lesion was quantified for evaluation by four statistical metrics with the lesions identified by the PH2 as the reference image, resulting with a true detection rate (TDR) of 82.31 and a false detection rate of 5.69.

Conclusions: The results obtained in the research work on hair artifacts removal and skin lesion segmentation provides acceptable results in terms of TDR and low false-positive rates.


Keywords


Artifacts removal, Border detection, Dermoscopy image, Lesion segmentation.

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About this article

Title

HAIR ARTIFACT REMOVAL AND SKIN LESION SEGMENTATION OF DERMOSCOPY IMAGES

Keywords

Artifacts removal, Border detection, Dermoscopy image, Lesion segmentation.

DOI

10.22159/ajpcr.2018.v11s3.30025

Date

06-10-2018

Additional Links

Manuscript Submission

Journal

Asian Journal of Pharmaceutical and Clinical Research
Vol 11 Special issue 3 2018 Page: 36-39

Print ISSN

0974-2441

Online ISSN

2455-3891

Authors & Affiliations

Julie Ann Salido
Department of Software Technology, De La Salle University, College of Computer Studies, Manila, Philippines.
Philippines

Conrado Ruiz Jr
Department of Software Technology, De La Salle University, College of Computer Studies, Manila, Philippines.
Philippines


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