In the field of Medical Image Segmentation, deep learning models, especially Convolutional Neural Networks (CNN) and Vision Transformer (ViT) models, have been widely researched and applied in recent ...

This paper proposes a novel data model for the recognition of medical images in breast cancer ultrasound examinations, based on convolutional neural networks (CNN). To validate the effectiveness of ...

You’re feeling unusually tired and sad, and your interest in sex has dropped off. That’s no fun. If you’re a guy, you may be thinking you have low testosterone. Wait a minute. Don’t we all experience ...

This article reviews the deep learning methods for computed tomography image denoising and deblurring separately and simultaneously. Then, we discuss promising directions in this field, such as a ...

The security of private medical data is crucial in the age of digital healthcare, especially when it comes to imaging tests like X-rays and ECGs. In addition to jeopardizing patient privacy, ...

Medical images are the standard approach for the analysis and diagnosis of critical issues of diseases. To minimize the time-consuming inspection and evaluation process of the medical images from ...

This paper suggests a novel diversion in color medical image encryption using a chaotic framework and Advanced Encryption Standard AES with Poisson regression model. Nowa-days, the remote healthcare ...

This research presents a comprehensive comparative analysis of various pre-trained backbone models and machine learning techniques for output layers in convolutional neural networks (CNNs) applied to ...

Speckle Noise Reduction for Medical Ultrasound Images Using Hybrid CNN-Transformer Network Abstract: Ultrasound images are often affected by limited resolution, artifacts, and inherent speckle noise.

The precision and efficacy of automated image analysis have been improved by integrating these models into medical diagnostics. Furthermore, we investigate the challenges that arise when applying deep ...

In order to solve the problems of limited ability of extracting local information and excessive parameters in the diagnosis model of major depression (MDD), an image depression recognition algorithm ...

In these days, research on the medical healthcare system is an emerging area and mainly focused on the designing of an efficient segmentation approach with the concept of Artificial Intelligence (AI) ...