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A new preprocessing approach to improve the performance of CNN-based skin lesion classification

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Abstract

Skin lesion is one of the severe diseases which in many cases endanger the lives of patients on a worldwide extent. Early detection of disease in dermoscopy images can significantly increase the survival rate. However, the accurate detection of disease is highly challenging due to the following reasons: e.g., visual similarity between different classes of disease (e.g., melanoma and non-melanoma lesions), low contrast between lesions and skin, background noise, and artifacts. Machine learning models based on convolutional neural networks (CNN) have been widely used for automatic recognition of lesion diseases with high accuracy in comparison to conventional machine learning methods. In this research, we proposed a new preprocessing technique in order to extract the region of interest (RoI) of skin lesion dataset. We compare the performance of the most state-of-the-art CNN classifiers with two datasets which contain (1) raw, and (2) RoI extracted images. Our experiment results show that training CNN models by RoI extracted dataset can improve the accuracy of the prediction (e.g., InceptionResNetV2, 2.18% improvement). Moreover, it significantly decreases the evaluation (inference) and training time of classifiers as well.

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Acknowledgements

Effort sponsored in whole or in part by United States Special Operations Command (USSOCOM), under Partnership Intermediary Agreement No. H92222-15-3-0001-01. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation thereon.

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  1. Department of Electrical Engineering, University of South Florida, Tampa, 33620, USA

    Hadi Zanddizari, Nam Nguyen, Behnam Zeinali & J. Morris Chang

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  1. Hadi Zanddizari
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  2. Nam Nguyen
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  3. Behnam Zeinali
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  4. J. Morris Chang
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Correspondence to Hadi Zanddizari.

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Zanddizari, H., Nguyen, N., Zeinali, B. et al. A new preprocessing approach to improve the performance of CNN-based skin lesion classification. Med Biol Eng Comput 59, 1123–1131 (2021). https://doi.org/10.1007/s11517-021-02355-5

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  • DOI: https://doi.org/10.1007/s11517-021-02355-5

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