AIMC Topic: Breath Holding
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Breath-hold 3D magnetic resonance cholangiopancreatography at 1.5 T using a deep learning-based noise-reduction approach: Comparison with the conventional respiratory-triggered technique.
European journal of radiology
Oct 5, 2021
OBJECTIVES: To assess the image quality of conventional respiratory-triggered 3-dimentional (3D) magnetic resonance cholangiopancreatography (Resp-MRCP) and breath-hold 3D MRCP (BH-MRCP) with and without denoising procedure using deep learning-based ...
Automatic registration and precise tumour localization method for robot-assisted puncture procedure under inconsistent breath-holding conditions.
The international journal of medical robotics + computer assisted surgery : MRCAS
Aug 25, 2021
BACKGROUND: During percutaneous puncture procedure, breath holding is subjectively controlled by patients, and it is difficult to ensure consistent tumour position between the preoperative CT scanning phase and the intraoperative puncture phase. In a...
Suppression of artifact-generating echoes in cine DENSE using deep learning.
Magnetic resonance in medicine
May 22, 2021
PURPOSE: To use deep learning for suppression of the artifact-generating T -relaxation echo in cine displacement encoding with stimulated echoes (DENSE) for the purpose of reducing the scan time.
Retrospective respiratory motion correction in cardiac cine MRI reconstruction using adversarial autoencoder and unsupervised learning.
NMR in biomedicine
Nov 30, 2020
The aim of this study was to develop a deep neural network for respiratory motion compensation in free-breathing cine MRI and evaluate its performance. An adversarial autoencoder network was trained using unpaired training data from healthy volunteer...
CINENet: deep learning-based 3D cardiac CINE MRI reconstruction with multi-coil complex-valued 4D spatio-temporal convolutions.
Scientific reports
Aug 13, 2020
Cardiac CINE magnetic resonance imaging is the gold-standard for the assessment of cardiac function. Imaging accelerations have shown to enable 3D CINE with left ventricular (LV) coverage in a single breath-hold. However, 3D imaging remains limited t...
Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning-based filter using convolutional neural network.
European radiology
Jun 17, 2020
OBJECTIVES: To reveal the utility of motion artifact reduction with convolutional neural network (MARC) in gadoxetate disodium-enhanced multi-arterial phase MRI of the liver.
Estimation of cerebral blood flow velocity during breath-hold challenge using artificial neural networks.
Computers in biology and medicine
Oct 17, 2019
UNLABELLED: The effect of untreated Obstructive Sleep Apnoea (OSA) on cerebral haemodynamics and CA impairment is an active field of research interest. A breath-hold challenge is usually used in clinical and research settings to simulate cardiovascul...
Measuring Oxygen Saturation With Smartphone Cameras Using Convolutional Neural Networks.
IEEE journal of biomedical and health informatics
Dec 17, 2018
Arterial oxygen saturation ([Formula: see text]) is an indicator of how much oxygen is carried by hemoglobin in the blood. Having enough oxygen is vital for the functioning of cells in the human body. Measurement of [Formula: see text] is typically e...
Deep-learning based surface region selection for deep inspiration breath hold (DIBH) monitoring in left breast cancer radiotherapy.
Physics in medicine and biology
Dec 12, 2018
Deep inspiration breath hold (DIBH) with surface supervising is a common technique for cardiac dose reduction in left breast cancer radiotherapy. Surface supervision accuracy relies on the characteristics of surface region. In this study, a convoluti...
Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning-proof of concept in congenital heart disease.
Magnetic resonance in medicine
Sep 8, 2018
PURPOSE: Real-time assessment of ventricular volumes requires high acceleration factors. Residual convolutional neural networks (CNN) have shown potential for removing artifacts caused by data undersampling. In this study, we investigated the ability...
Magnetic Resonance Imaging, Cine
Cardiac-Gated Imaging Techniques
Heart Defects, Congenital
Fourier Analysis
Breath Holding
Heart
Image Interpretation, Computer-Assisted
Artifacts
Humans
Young Adult
Deep Learning
Respiration
Adult
Algorithms
Adolescent
Male
Retrospective Studies
Image Processing, Computer-Assisted
Middle Aged
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