Semantic-based segmentation (Semseg) methods play an essential part in medical imaging
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …

Artificial intelligence algorithms based on principles of deep learning (DL) have made a
large impact on the acquisition, reconstruction, and interpretation of MRI data. Despite the …

Abstract Introduction Artificial Intelligence-based Medical Devices (AI-based MDs) are
experiencing exponential growth in healthcare. This study aimed to investigate whether …

Ultrasound imaging is a patient-friendly and robust technique for studying physiological and
pathological muscles. An automatic deep learning (DL) system for the analysis of ultrasound …

Artificial intelligence is rapidly expanding in all technological fields. The medical field, and
especially diagnostic imaging, has been showing the highest developmental potential …

Background Magnetic resonance imaging (MRI) is the dominant 3D imaging modality to
quantify muscle properties in skeletal muscle disorders, in inherited and acquired muscle …

Knee osteoarthritis (OA) is a prevalent and disabling disease that can develop over
decades. This disease is heterogeneous and involves structural changes in the whole joint …

Background Time-efficient and accurate whole volume thigh muscle segmentation is a major
challenge in moving from qualitative assessment of thigh muscle MRI to more quantitative …

By leveraging the recent development of artificial intelligence algorithms, several medical
sectors have benefited from using automatic segmentation tools from bioimaging to segment …

With the recent developments in deep learning and the rapid growth of convolutional neural
networks, artificial intelligence has shown promise as a tool that can transform several …