Medical image analysis has witnessed significant advancements with the introduction of Convolutional Neural Networks (CNNs). This paper explores the application of CNNs in the field of medical image analysis, highlighting their potential, challenges, and key contributions. CNNs have shown remarkable results in tasks such as image classification, segmentation, and disease detection, making them a powerful tool for healthcare professionals and researchers. In this article, we delve into the architecture of CNNs, discuss their training and fine-tuning techniques, and provide insights into their use in various medical imaging modalities. Furthermore, we address the ethical and privacy concerns associated with the use of CNNs in medical image analysis.
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Journal of Global Economics received 1931 citations as per Google Scholar report