Search Results - radial+mri

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Methods and Systems for Low-Cost Medical Image Annotation Using Non-experts (Case No. 2025-108)
Summary: UCLA researchers in the Department of Electrical and Computer Engineering have developed an AI-based interface designed to enable individuals without specialized training to identify arthritis in medical imaging. Background: The use of artificial intelligence (AI) for medical imaging analysis holds great promise for the future of healthcare....
Published: 7/23/2025   |   Inventor(s): Xiang Chen, Youngseung Jeon, Christopher Hwang
Keywords(s): 3D tissue imaging, AI-guided diagnostics, AI-guided medical imaging, AI-guided medical intervention, arthritis, Artifical Intelligence (Machine Learning, Data Mining), Artificial Intelligence, artificial intelligence algorithms, artificial intelligence augmentation, artificial intelligence/machine learning models, Artificial Neural Network, bioimaging, Computer-Aided Diagnosis, computer-aided radiology, Diagnostic Markers & Platforms, Diagnostic Test, diagnostics, generative artificial intelligence, Image Analysis, Image Resolution, Imaging, infrared thermal imaging, Machine Learning, machine learning modeling, machine perception, Magnetic Resonance Imaging Medical Physics, Magnetic Resonance Imaging Pathology, Medical artificial intelligence (AI), Medical diagnostics, Medical Imaging, Microscopy And Imaging, non-invasive imaging, osteoarthritis, radial MRI, radiologic imaging, Radiology, Radiology / Radiomitigation, radiosurgery
Category(s): Software & Algorithms, Software & Algorithms > AI Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Digital Health, Software & Algorithms > Image Processing, Life Science Research Tools, Life Science Research Tools > Lab Equipment, Life Science Research Tools > Microscopy And Imaging, Medical Devices, Medical Devices > Medical Imaging, Medical Devices > Monitoring And Recording Systems, Therapeutics, Therapeutics > Musculoskeletal Disease, Therapeutics > Radiology
A Deep-Learning Framework for Quantitative Magnetic Resonance Imaging (Case No. 2021-268)
Summary: Researchers from UCLA’s Departments of Bioengineering and Radiological Sciences have developed a novel deep learning framework for accelerated quantitative magnetic resonance imaging. Background: Fatty liver disease, or hepatic steatosis, affects nearly 2 billion people globally and has pernicious implications for deadlier diseases...
Published: 7/17/2025   |   Inventor(s): Holden Wu, Shu-Fu Shih
Keywords(s): Deep Learning, fat quantification, IIM framework, Imaging, Medical Imaging, Metabolic/Endocrinology, MRI, multiparametric MRI (mpMRI), radial MRI, uncertainty estimation
Category(s): Medical Devices, Medical Devices > Medical Imaging, Medical Devices > Medical Imaging > MRI, Electrical, Electrical > Imaging, Software & Algorithms