Abstract: Enhancing the resolution of Magnetic Resonance Imaging (MRI) through super-resolution (SR) reconstruction is crucial for boosting diagnostic precision. However, current SR methods primarily ...

Radiology capacity is a bottleneck in hospitals, while imaging exams can be a major pain point for patients as well. Health systems and imaging centers are facing increasing volumes of medical imaging ...

Abstract: Central lumbar spinal stenosis, a prevalent degenerative spinal disorder, severely impacts the quality of life for those affected. Axial and sagittal MRI images offer diverse information on ...

The novel system, called CMR-CLIP, is designed to interpret cardiac MRI scans by connecting moving images of the heart with corresponding clinical radiology reports. In testing, it significantly ...

Researchers at Cleveland Clinic and Pittsburgh-based Carnegie Mellon University have developed an AI system designed to interpret cardiac MRI scans without manually labeled training data. The system ...

PITTSBURGH and CLEVELAND: A team of researchers from Carnegie Mellon University, in collaboration with Cleveland Clinic’s Cardiovascular Innovation Research Center, has developed an artificial ...

The collaboration between Institute of Instrumentation for Molecular Imaging (I3M) in Spain and Mbarara University of Science and Technology in Uganda began with shared ambition and a shared ...

High-resolution 7.0 T MRI of the eye and orbit of a volunteer that shows in great detail the anterior cranial structures, including the extraocular muscles, optic nerve, and a cyst adjacent (yellow ...

Performance of a blood-biomarker test for early detection of pancreatic ductal adenocarcinoma (PDAC) across all stages of disease versus a mixed control population. This is an ASCO Meeting Abstract ...

This repository explores multiple deep learning pipelines (Pix2Pix, improved GAN variants) to synthesize CT images from MRI scans, with a focus on clinical-quality reconstruction and robust evaluation ...