International Journal of Computer Science & Network Security

International Journal of Computer Science & Network Security (국제컴퓨터통신보호논문지학회)
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Medical Image Classification using Pre-trained Convolutional Neural Networks and Support Vector Machine

  • Received : 2021.06.05
  • Published : 2021.06.30
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Abstract

Recently, pre-trained convolutional neural network CNNs have been widely used and applied for medical image classification. These models can utilised in three different ways, for feature extraction, to use the architecture of the pre-trained model and to train some layers while freezing others. In this study, the ResNet18 pre-trained CNNs model is used for feature extraction, followed by the support vector machine for multiple classes to classify medical images from multi-classes, which is used as the main classifier. Our proposed classification method was implemented on Kvasir and PH2 medical image datasets. The overall accuracy was 93.38% and 91.67% for Kvasir and PH2 datasets, respectively. The classification results and performance of our proposed method outperformed some of the related similar methods in this area of study.

Keywords

Acknowledgement

This research was funded by the Deanship of Scientific Research (DSR) at King Ab-dulaziz University, Jeddah, Saudi Arabia. The authors, therefore, gratefully acknowledge the DSR for their technical and financial support.

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