Towards Skin Cancer Detection Through Low Resolution Images

Currently, dermatologists need to check numerous image reports (high resolution) for diagnosing skin conditions, and Machine Learning (ML) models can help with this tedious task. However, current ML models usually work best with high-quality images in case of skin cancer, and those high-resolution images need dermoscope. In this paper, we investigated how well ML performs on low-quality ones. Our results shows though there are challenges with using lower-quality images but still models perform with >84% accuracy, and we plan to improve the models to make them more accurate and useful in real-world clinics.

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Publication Details

Journal
Studies in health technology and informatics
Published
2025-05-15
DOI
https://doi.org/10.3233/shti250642
Citations
1
Primary Topic
Cutaneous Melanoma Detection and Management
Type
article
Field-Weighted Citation Impact
10.18
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article

Towards Skin Cancer Detection Through Low Resolution Images

Asra Aslam, J. Vega
1 citations
Studies in health technology and informatics
Cutaneous Melanoma Detection and Management
10.18
article

Towards Skin Cancer Detection Through Low Resolution Images

Asra Aslam, J. Vega
article en
1 citations

Abstract

Currently, dermatologists need to check numerous image reports (high resolution) for diagnosing skin conditions, and Machine Learning (ML) models can help with this tedious task. However, current ML models usually work best with high-quality images in case of skin cancer, and those high-resolution images need dermoscope. In this paper, we investigated how well ML performs on low-quality ones. Our results shows though there are challenges with using lower-quality images but still models perform with >84% accuracy, and we plan to improve the models to make them more accurate and useful in real-world clinics.

Studies in health technology and informaticsVol. 327
University of Leeds (GB), Google (United Kingdom) (GB)
Openalex Percentile: Top 4%
Cutaneous Melanoma Detection and Management
10.18
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