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Skin Cancer

Skin Cancer

Skin cancer is a type of cancer that occurs when there is an abnormal growth of skin cells, usually triggered by damage to the DNA within the skin cells. It is primarily caused by exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds. Skin cancer is the most common type of cancer worldwide, and its incidence continues to rise.
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Updated: May 26, 2026

SCAnED - An Open-source Skin Segmentation Macro for Semi-automated Cell and Nuclei Detection in Epidermal and Dermal Skin Compartments

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Computerised image analysis of vitiligo lesion: evaluation using manually defined lesion areas.

Hermawan Nugroho¹, M Hani Ahmad Fadzil, Norashikin Shamsudin

¹Intelligent Signal and Imaging Research Centre, Department of Electrical & Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Malaysia. dewa00@gmail.com

Skin Research and Technology : Official Journal of International Society for Bioengineering and the Skin (ISBS) [And] International Society for Digital Imaging of Skin (ISDIS) [And] International Society for Skin Imaging (ISSI)

|January 12, 2012

Summary

This study introduces a novel digital image processing technique for objectively measuring vitiligo lesion area. This method enhances the assessment of vitiligo treatment efficacy, moving beyond subjective physician evaluations.

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Area of Science:

Dermatology
Medical Imaging
Computational Biology

Background:

Vitiligo is a skin disorder causing depigmented patches due to melanocyte loss.
Current treatment efficacy assessment relies on subjective Physician's Global Assessment (PGA).
Objective measurement of vitiligo lesion area is needed.

Purpose of the Study:

To present an innovative digital image processing method for objective vitiligo lesion area determination.
To provide an objective alternative to the subjective Physician's Global Assessment (PGA).

Main Methods:

Utilized Independent Component Analysis (ICA) to create melanin-specific images.
Employed Region Growing algorithms for segmenting vitiligo lesions from normal skin.
Validated the method using 41 digital images from 18 vitiligo patients.

Main Results:

Achieved high sensitivity (0.9105 ± 0.0161).
Demonstrated excellent specificity (0.9973 ± 0.0009).
Reported high accuracy (0.9901 ± 0.0028) at a 95% confidence level.

Conclusions:

The proposed digital method enables objective assessment of vitiligo treatment efficacy.
This innovation supports more reliable and reproducible clinical evaluations of vitiligo therapies.