AIMC Topic: Microbubbles

Clear Filters Showing 21 to 30 of 33 articles

Faster super-resolution ultrasound imaging with a deep learning model for tissue decluttering and contrast agent localization.

Biomedical physics & engineering express Oct 25, 2021
Super-resolution ultrasound (SR-US) imaging allows visualization of microvascular structures as small as tens of micrometers in diameter. However, use in the clinical setting has been impeded in part by ultrasound (US) acquisition times exceeding a b...
Animals Deep Learning Contrast Media Microbubbles Phantoms, Imaging Ultrasonography Rats
View on PubMed DOI

A Deep Learning Framework for Spatiotemporal Ultrasound Localization Microscopy.

IEEE transactions on medical imaging Apr 30, 2021
Ultrasound Localization Microscopy (ULM) can resolve the microvascular bed down to a few micrometers. To achieve such performance, microbubble contrast agents must perfuse the entire microvascular network. Microbubbles are then located individually a...
Microbubbles Mice Microscopy Neural Networks, Computer Ultrasonography Animals Deep Learning Image Processing, Computer-Assisted
View on PubMed DOI

Super-Resolution Ultrasound Localization Microscopy Through Deep Learning.

IEEE transactions on medical imaging Mar 2, 2021
Ultrasound localization microscopy has enabled super-resolution vascular imaging through precise localization of individual ultrasound contrast agents (microbubbles) across numerous imaging frames. However, analysis of high-density regions with signi...
Contrast Media Microscopy Deep Learning Microbubbles Ultrasonography
View on PubMed DOI

Neural network-based modeling of the number of microbubbles generated with four circulation factors in cardiopulmonary bypass.

Scientific reports Jan 12, 2021
The need for the estimation of the number of microbubbles (MBs) in cardiopulmonary bypass surgery has been recognized among surgeons to avoid postoperative neurological complications. MBs that exceed the diameter of human capillaries may cause endoth...
Hemodynamics Cardiopulmonary Bypass Nervous System Diseases Neural Networks, Computer Postoperative Complications Cardiovascular Surgical Procedures Blood Viscosity Capillaries Microbubbles Embolism, Air Humans
View on PubMed DOI

Detection and Localization of Ultrasound Scatterers Using Convolutional Neural Networks.

IEEE transactions on medical imaging Nov 30, 2020
Delay-and-sum (DAS) beamforming is unable to identify individual scatterers when their density is so high that their point spread functions overlap. This paper proposes a convolutional neural network (CNN)-based method to detect and localize high-den...
Neural Networks, Computer Ultrasonography Phantoms, Imaging Microbubbles
View on PubMed DOI

Deep Learning of Spatiotemporal Filtering for Fast Super-Resolution Ultrasound Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Apr 15, 2020
Super-resolution ultrasound (SR-US) imaging is a new technique that breaks the diffraction limit and allows visualization of microvascular structures down to tens of micrometers. The image processing methods for the spatiotemporal filtering needed in...
Mammary Neoplasms, Experimental Signal Processing, Computer-Assisted Microbubbles Contrast Media Mice, Nude Deep Learning Ultrasonography Image Processing, Computer-Assisted Mice Cell Line, Tumor Female Animals Neural Networks, Computer
View on PubMed DOI

Deep Learning for Ultrasound Localization Microscopy.

IEEE transactions on medical imaging Apr 9, 2020
By localizing microbubbles (MBs) in the vasculature, ultrasound localization microscopy (ULM) has recently been proposed, which greatly improves the spatial resolution of ultrasound (US) imaging and will be helpful for clinical diagnosis. Nevertheles...
Microscopy Microbubbles Reproducibility of Results Deep Learning Ultrasonography
View on PubMed DOI

Nondestructive Detection of Targeted Microbubbles Using Dual-Mode Data and Deep Learning for Real-Time Ultrasound Molecular Imaging.

IEEE transactions on medical imaging Apr 9, 2020
Ultrasound molecular imaging (UMI) is enabled by targeted microbubbles (MBs), which are highly reflective ultrasound contrast agents that bind to specific biomarkers. Distinguishing between adherent MBs and background signals can be challenging in vi...
Animals Deep Learning Mice Contrast Media Ultrasonography Humans Molecular Imaging Microbubbles
View on PubMed DOI

Contrast-Enhanced Ultrasound Quantification: From Kinetic Modeling to Machine Learning.

Ultrasound in medicine & biology Jan 8, 2020
Ultrasound contrast agents (UCAs) have opened up immense diagnostic possibilities by combined use of indicator dilution principles and dynamic contrast-enhanced ultrasound (DCE-US) imaging. UCAs are microbubbles encapsulated in a biocompatible shell....
Machine Learning Animals Ultrasonography Humans Kinetics Microbubbles Models, Theoretical Contrast Media
View on PubMed DOI

Post-processing radio-frequency signal based on deep learning method for ultrasonic microbubble imaging.

Biomedical engineering online Sep 11, 2019
BACKGROUND: Improving imaging quality is a fundamental problem in ultrasound contrast agent imaging (UCAI) research. Plane wave imaging (PWI) has been deemed as a potential method for UCAI due to its' high frame rate and low mechanical index. High fr...
Abdomen Radio Waves Contrast Media Ultrasonography Animals Image Processing, Computer-Assisted Microbubbles Deep Learning Rabbits Arteries
View on PubMed DOI
Popular Topics
Recent Journals