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Search Results - cardiac+cycle
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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
Synchronized Biventricular Heart Pacing Using Wirelessly Powered Leadless Pacemakers (Cases 2019-237 & 2020-401)
Summary: UCLA researchers in the department of electrical and computer engineering have developed a device for synchronized biventricular pacing. Background: Many patients with impaired cardiac function suffer from ventricular desynchrony, a condition that involves a lack of synchronization between the contractions of the left and right ventricles...
Published: 7/17/2025
|
Inventor(s):
Aydin Babakhani
,
Hongming Lyu
,
Medhi Razavi
,
Mathews John
,
Allison Post
Keywords(s):
acute myocardial infarction
,
cardiac cycle
,
Cardiac failure
,
cardiometabolic disease
,
cardiopulmonary illness
,
Cardiovascular
,
Cardiovascular Disease
,
cardiovascular diseases
,
cardiovascular modeling
,
cardiovascular monitoring
,
cardiovascular prediction
,
cardiovascular therapeutic solution
,
medical device cardiac monitoring
,
non-invasive cardiac monitoring
,
tachycardia
Category(s):
Medical Devices
,
Medical Devices > Cardiac
,
Medical Devices > Monitoring And Recording Systems
Detection of Dicrotic Notch in Arterial Pressure and Photoplethysmography Signals Using Iterative Envelope Mean Filter (Case No. 2024-034)
Summary: UCLA Researchers in the Department of Anesthesiology have developed an iterative envelope mean (IEM) method for the detection of specific features in arterial pressure monitoring applications. Background: The
cardiac cycle
consists of the distinct systolic and diastolic phases. The transition from the contracted, systolic phase to the...
Published: 3/26/2025
|
Inventor(s):
Maxime Cannesson
,
Ravi Pal
,
Akos Rudas
,
Jeffrey Chiang
,
Sungsoo Kim
Keywords(s):
arrhythmia
,
arterial blood pressure (ABP)
,
cardiac cycle
,
Cardiac Electrophysiology
,
Cardiac failure
,
Cardiac Magnetic Resonance Imaging
,
cardiometabolic disease
,
cardiopulmonary illness
,
Cardiovascular
,
Cardiovascular Disease
,
Cardiovascular Disease Nephropathy
,
cardiovascular modeling
,
cardiovascular prediction
,
cardiovascular therapeutic solution
,
diastolic
,
diastolic phase peak
,
dicrotic notch
,
feature extraction tool
,
iterative envelope method (IEM)
,
Medical Device
,
medical device cardiac monitoring
,
Medical Device Poly(Methyl Methacrylate)
,
Medical Devices and Materials
,
non-invasive cardiac monitoring
,
photoplethysmography (PPG)
,
Smart medical device
,
systolic
,
tachycardia
,
wearable medical device
,
wearable medical devices
Category(s):
Medical Devices
,
Medical Devices > Monitoring And Recording Systems
,
Platforms
,
Platforms > Diagnostic Platform Technologies
,
Software & Algorithms
,
Diagnostic Markers > Targets And Assays
,
Diagnostic Markers