Dec 1, 2023 · Deep neural networks (DNNs) have significantly improved diagnosis, treatment planning, and patient care by revolutionizing several facets of medical image processing.

Convolutional neural networks (CNNs) are effective tools for image understanding. They have outperformed human experts in many image understanding tasks. This article aims to provide a comprehensive survey of applications of CNNs in medical image understanding.

This specialized neural network class excels in tasks involving sequential medical data, such as medical image processing, analyzing MRI sequences and predicting disease progression . Like ANN, RNN also have three main layers: an input layer for receiving the data, a hidden layer for capturing the information from preceding inputs, i.e ...

Feb 16, 2021 · In the field of AI in medical imaging, image classification must be particularly precise. This article explains how convolutional neural network architecture works, particularly when used with medical images.

In the field of medical imaging, the rapid rise of convolutional neural networks (CNNs) has presented significant opportunities for conserving healthcare resources. However, with the wide spread application of CNNs, several challenges have emerged, ...

Oct 4, 2023 · Convolutional neural networks (CNNs) are the subset of AI models that are driving significant progress in the field of medical image analysis. They play a crucial role, specifically in computer vision, a field that enables machines to ‘see’ and interpret visual data.

Nov 4, 2022 · Among their many uses are recognizing objects in images, speech translation, and user profiling: these being extremely helpful utilities in the medical field. The present survey focuses on the specialized and leading edge subfield of generative models in deep neural networks (DNNs) applied in medical imaging.

This paper aims to present a review of neural networks used in medical image processing. We classify neural networks by its processing goals and the nature of medical images. Main contributions, advantages, and drawbacks of the methods are mentioned ...

Jul 15, 2021 · In this paper, we provide a survey on convolutional neural networks in medical image analysis. First, we review the commonly used CNNs in medical image processing, including AlexNet, GoogleNet, ResNet, R-CNN, and FCNN.

Jun 15, 2024 · This review addresses the importance of changing the paradigm shift from ANNs to DCNNs in the field of medical image processing. Some limitations of the ANNs and image processing challenges also are discussed. The paper is organized in 8 sections.