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A new method describing border irregularity of pigmented lesions
Yu Zhou1, Melvyn Smith, Lyndon Smith
1Machine Vision Laboratory, University of the West of England, Bristol, UK. yu.zhou@uwe.ac.uk
Summary
This study introduces a novel method using centroid distance diagrams (CDDs) to quantify melanoma border irregularity, improving computer-aided diagnosis. Descriptors from CDDs show strong potential for melanoma recognition.
Area of Science:
- Dermatology
- Medical Imaging
- Computer-Aided Diagnosis
Background:
- Accurate melanoma diagnosis relies on characterizing lesion border irregularity.
- Existing methods for quantitative border analysis are limited.
Purpose of the Study:
- To propose a novel approach for automatic quantitative characterization of melanoma border irregularity.
- To develop descriptors for improved melanoma recognition rates.
Main Methods:
- Introduction of a centroid distance diagram (CDD) and centroid distance curve.
- Generation of border irregularity descriptors: non-centroid-convexity index, maximum-minimum distance indicator, standard deviation of centroid distance curves, and frequency domain analysis.
- Estimation of error boundaries for the proposed descriptors.
Main Results:
- Experimental validation on 60 melanoma and 107 benign lesion images.
- Optimal sensitivity of 74.2% and specificity of 72.6% with an ROC area of 0.788.
- For the testing group, mean sensitivity reached 71.8% (SD 10.1%) and specificity was 69.8% (SD 7.2%).
Conclusions:
- Descriptors derived from centroid distance diagrams (CDDs) are highly effective for characterizing melanoma border irregularity.
- The proposed method demonstrates significant potential for enhancing computer-aided melanoma diagnosis.
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