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Skin Lesion Classification Using Convolutional Neural Network for Melanoma Recognition

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Proceedings of International Joint Conference on Advances in Computational Intelligence

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

Skin cancer, also known as melanoma, is generally diagnosed visually from the dermoscopic images, which is a tedious and time-consuming task for the dermatologist. Such a visual assessment, via the naked eye for skin cancers, is challenging and arduous due to different artifacts such as low contrast, various noise, presence of hair, fiber, and air bubbles. This article proposes a robust and automatic framework for the skin lesion classification (SLC), where we have integrated image augmentation, deep convolutional neural network (DCNN), and transfer learning. The proposed framework was trained and tested on publicly available IEEE International Symposium on Biomedical Imaging (ISBI)-2017 dataset. The obtained average areas under the receiver operating characteristic curve (AUC), recall, precision, and F1-score are, respectively, 0.87, 0.73, 0.76, and 0.74 for the SLC. Our experimental studies for lesion classification demonstrate that the proposed approach can successfully distinguish skin cancer with a high degree of accuracy, which has the capability of skin lesion identification for melanoma recognition.

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Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh

    Aishwariya Dutta

  2. Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology, Khulna, 9203, Bangladesh

    Md. Kamrul Hasan & Mohiuddin Ahmad

Authors
  1. Aishwariya Dutta
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  2. Md. Kamrul Hasan
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  3. Mohiuddin Ahmad
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Corresponding author

Correspondence to Md. Kamrul Hasan .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh

    Mohammad Shorif Uddin

  2. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

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Dutta, A., Kamrul Hasan, M., Ahmad, M. (2021). Skin Lesion Classification Using Convolutional Neural Network for Melanoma Recognition. In: Uddin, M.S., Bansal, J.C. (eds) Proceedings of International Joint Conference on Advances in Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-0586-4_5

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