Search Results - multiparametric+mri+(mpmri)

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Method and Apparatus for Segmentation of Dense MR Images Using Deep Learning with Domain Adaptation (Case No. 2025-208)

Summary: UCLA researchers from the Department of Radiological Sciences have developed a deep learning-based segmentation framework that enables fully automated and reproducible analysis of left ventricular (LV) function in Displacement Encoding with Stimulated Echoes (DENSE) MRI. Background: Myocardial strain is a key metric for analyzing how much...

Published: 8/18/2025 | Inventor(s): Xiaodong Zhong, Siyue Li, Kim-Lien Nguyen

Keywords(s): acute myocardial infarction, adjustable mount, aneurysm drainage, automatic leveling, bedside decisions, blood pressure monitoring, cardiac cycle, Cardiac Electrophysiology, Cardiac failure, Cardiac Magnetic Resonance Imaging, Cardiac MRI, Cardiovascular, Cardiovascular Disease, Cardiovascular Disease Nephropathy, cardiovascular diseases, cardiovascular monitoring, cerebrospinal fluid (CSF) drainage, Cine MRI, clamp, critical-care, CSF drainage, Deep learning MRI, DENSE MRI, laser alignment, Left ventricular segmentation, lumbar drains, Motion analysis, MRI, multiparametric MRI (mpMRI), Myocardial strain, non-invasive cardiac monitoring, operator variability, passive reflective target, phlebostatic axis measurement, Pseudo-labeling, radial MRI, Segment Anything Model (SAM), self-leveling system, transducer alignment, Unsupervised domain adaptation (UDA)

Category(s): Medical Devices > Cardiac, Electrical > Imaging, Software & Algorithms > AI Algorithms, Software & Algorithms > Artificial Intelligence & Machine Learning, Software & Algorithms > Image Processing, Therapeutics > Cardiovascular, Therapeutics > Radiology, Medical Devices > Medical Imaging > MRI, Medical Devices > Medical Imaging

Interleaved Radial Amine CEST and Sodium (INTERLACED) NMR Pulse Sequence (Case No. 2024-069)

Summary: UCLA researchers in the Department of Radiological Sciences have developed a novel MRI modality that simultaneously utilizes multiple nuclei to enhance scanning capabilities while reducing scanning times. Background: Magnetic Resonance Imaging (MRI) is a major tool in medical diagnostics and monitoring, as well as the primary clinical research...

Published: 2/25/2025 | Inventor(s): Benjamin Ellingson, Alfredo Lopez Kolkovsky

Keywords(s): diagnostic radionuclides, Functional Magnetic Resonance Imaging, Magnetic Resonance Imaging, MRI, multiparametric MRI (mpMRI)

Category(s): Medical Devices, Medical Devices > Medical Imaging

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

Novel Method to Group Pixels for Medical Imaging (UCLA Case No. 2022-290)

Summary: UCLA researchers in the Department of Radiological Sciences have developed a new computational pipeline for identifying lesions in MRI data. Background: Prostate cancer is one of the most common cancer types with 12.6% of men diagnosed within their lifetime. Prostate cancer ranks as the 2nd leading cause of cancer-related deaths in the...

Published: 2/14/2025 | Inventor(s): Ashley Yeager

Keywords(s): AI algorithms, Algorithm, algorithmic cancer detection, Cancer, cancer detection, DICOM, multiparametric MRI (mpMRI), prostate cancer, Radiology, Software & Algorithms, Tumor, Tumor Marker

Category(s): Software & Algorithms, Software & Algorithms > Image Processing, Software & Algorithms > Digital Health

Deep Learning Super-Resolution Magnetic Resonance Imaging via Slice-Profile-Transformation Based Downsampling (UCLA Case No. 2022-062)

Summary: UCLA Researchers in the Department of Radiological Sciences have developed a deep learning-based approach for super-resolution magnetic resonance imaging. This method incorporates a novel slice-profile transformation super-resolution framework for through-plane super-resolution of multi-slice 2D MRI. This approach results in higher accuracy...

Published: 7/17/2025 | Inventor(s): Kyung Sung, Jiahao Lin

Keywords(s): Deep Learning, down sampling, High-resolution, Image Resolution, isotropic super-resolution, MRI, multiparametric MRI (mpMRI), slice-profile, Super Resolution Microscopy

Category(s): Medical Devices > Medical Imaging, Medical Devices > Medical Imaging > MRI