Classification of Images of Skin Lesion Using Deep Learning

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Author(s)

Momina Shaheen 1,* Usman Saif 2 Shahid M. Awan 3 Faizan Ahmad 4 Aimen Anum 5

1. School of Arts and Digital Industries, University of Roehampton, London, United Kingdom, SW15 2YB

2. School of System and Technology, University of Management and Technology Lahore, Pakistan

3. University of West Scotland, Paisley, Glasgow United Kingdom PA1 2BE

4. Cardiff Metropolitan University, Llandaff Campus, United Kingdom CF5 2YB

5. Islamia University Bahawalpur, Bahawal Nagar Campus 063200

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2023.02.03

Received: 17 Aug. 2022 / Revised: 9 Nov. 2022 / Accepted: 4 Jan. 2023 / Published: 8 Apr. 2023

Index Terms

Biomedical, Convolutional Neural Network, Deep Learning, Skin Cancer Diagnosis

Abstract

Skin cancer is among common and rapidly increasing human malignancies, which can be diagnosed visually. The diagnosis begins with preliminary medical screening and by dermoscopic examination, histopathological examination, and proceeding to the biopsy. This screening and diagnosis can be automated using machine learning tools and techniques. Artificial neural networks are helping a lot in medical diagnosis applications. In this research, skin images are classified into 7 different classes of skin cancer using deep learning methodology, then analyzed the results w.r.t to their respective precision, recall, support, and accuracy to find its practical applicability. This model is efficient in comparison to the detection of skin cancer with human eyes. Human eyes detection can be 79% accurate at most. Thus, having a scientific method of diagnosis can help the doctors and practitioners to accurately identify the cancer and its type. The model provides 80% accuracy on average for all 7 types of skin diseases, thus being more reliable than human eye examination. It will help the doctors to diagnose the skin diseases more confidently. The model has only 2 misclassified predictions for Basal cell carcinoma and Vascular lesions. However, Actinic keratosis diagnosis is most accurately predicted.

Cite This Paper

Momina Shaheen, Usman Saif, Shahid M. Awan, Faizan Ahmad, Aimen Anum, "Classification of Images of Skin Lesion Using Deep Learning", International Journal of Intelligent Systems and Applications(IJISA), Vol.15, No.2, pp.23-36, 2023. DOI:10.5815/ijisa.2023.02.03

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