An Efficient Approach towards Skin Cancer Diagnosis with EfficientNetB3

Skin cancer has been identified as the most widespread and well-documented type of malignancy worldwide. Its origin lies in the irregular growth of melanocytic cells, often referred to as melanoma. Exposure to ultraviolet radiation and genetic factors leads to melanoma appearing on the skin. Identification at an early stage increases the chances of successful treatment. However, the conventional biopsy method used for detecting skin cancer is both invasive and painful. It involves extensive laboratory procedures that consume a considerable amount of time. Computer-aided diagnosis systems can help to address these challenges. In this work, two distinct models has been developed based on EfficientNetB3, with varying additional layers. To conduct a comparative work, various cutting-edge techniques have been evaluated. The suggested approaches surpass the majority of these techniques by achieving an overall test accuracy of 91% and 93.25% for Model 1 and Model 2 respectively.

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Publication Details

Journal
Journal of Innovative Image Processing
Published
2024-11-28
DOI
https://doi.org/10.36548/jiip.2024.4.002
Citations
1
Primary Topic
Cutaneous Melanoma Detection and Management
Type
article
Field-Weighted Citation Impact
0.28
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article

An Efficient Approach towards Skin Cancer Diagnosis with EfficientNetB3

Arijit Ghosal, Ranjit Ghoshal, Prosenjit Saha
1 citations
Journal of Innovative Image Processing
Cutaneous Melanoma Detection and Management
0.28
article

An Efficient Approach towards Skin Cancer Diagnosis with EfficientNetB3

Arijit Ghosal, Ranjit Ghoshal, Prosenjit Saha
article en
1 citations

Abstract

Skin cancer has been identified as the most widespread and well-documented type of malignancy worldwide. Its origin lies in the irregular growth of melanocytic cells, often referred to as melanoma. Exposure to ultraviolet radiation and genetic factors leads to melanoma appearing on the skin. Identification at an early stage increases the chances of successful treatment. However, the conventional biopsy method used for detecting skin cancer is both invasive and painful. It involves extensive laboratory procedures that consume a considerable amount of time. Computer-aided diagnosis systems can help to address these challenges. In this work, two distinct models has been developed based on EfficientNetB3, with varying additional layers. To conduct a comparative work, various cutting-edge techniques have been evaluated. The suggested approaches surpass the majority of these techniques by achieving an overall test accuracy of 91% and 93.25% for Model 1 and Model 2 respectively.

Journal of Innovative Image ProcessingVol. 6(4)
Velammal Medical College Hospital and Research Institute (IN), Velammal Educational Trust (IN), Maulana Abul Kalam Azad University of Technology, West Bengal (IN)
Good health and well-being
Openalex Percentile: Top 34%
Cutaneous Melanoma Detection and Management
0.28
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