AIMC Topic: Heart
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Synergistic biophysics and machine learning modeling to rapidly predict cardiac growth probability.
Computers in biology and medicine
Nov 7, 2024
Computational models that can predict growth and remodeling of the heart could have important clinical applications. However, the time it takes to calibrate and run current models while considering data uncertainty and variability makes them impracti...
Cardiac motion correction with a deep learning network for perfusion defect assessment in single-photon emission computed tomography myocardial perfusion imaging.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Nov 2, 2024
BACKGROUND: In myocardial perfusion imaging (MPI) with single-photon emission computed tomography (SPECT), ungated studies are used for evaluation of perfusion defects despite motion blur. We investigate the potential benefit of motion correction usi...
Accelerated cardiac cine with spatio-coil regularized deep learning reconstruction.
Magnetic resonance in medicine
Oct 21, 2024
PURPOSE: To develop an iterative deep learning (DL) reconstruction with spatio-coil regularization and multichannel k-space data consistency for accelerated cine imaging.
Deep learning assists early-detection of hypertension-mediated heart change on ECG signals.
Hypertension research : official journal of the Japanese Society of Hypertension
Oct 12, 2024
Arterial hypertension is a major risk factor for cardiovascular diseases. While cardiac ultrasound is a typical way to diagnose hypertension-mediated heart change, it often fails to detect early subtle structural changes. Electrocardiogram(ECG) repre...
A machine learning algorithm for creating isotropic 3D aortic segmentations from routine cardiac MR localizers.
Magnetic resonance imaging
Oct 12, 2024
BACKGROUND: The identification and measurement of aortic aneurysms is an important clinical problem. While specialized high-resolution 3D CMR sequences allow detailed aortic assessment, they are time-consuming which limits their use in screening rout...
Deep-Learning-Based Disease Classification in Patients Undergoing Cine Cardiac MRI.
Journal of magnetic resonance imaging : JMRI
Oct 1, 2024
BACKGROUND: Automated approaches may allow for fast, reproducible clinical assessment of cardiovascular diseases from MRI.
Male
Middle Aged
Deep Learning
Image Processing, Computer-Assisted
Aged
Cardiomyopathy, Hypertrophic
Humans
Adult
Algorithms
Myocardial Ischemia
Sensitivity and Specificity
Retrospective Studies
Heart
Magnetic Resonance Imaging, Cine
Female
Cardiomyopathy, Dilated
Heart Ventricles
Reproducibility of Results
Image Interpretation, Computer-Assisted
Wirelessly steerable bioelectronic neuromuscular robots adapting neurocardiac junctions.
Science robotics
Sep 25, 2024
Biological motions of native muscle tissues rely on the nervous system to interface movement with the surrounding environment. The neural innervation of muscles, crucial for regulating movement, is the fundamental infrastructure for swiftly respondin...
Dynamic MRI interpolation in temporal direction using an unsupervised generative model.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 22, 2024
PURPOSE: Cardiac cine magnetic resonance imaging (MRI) is an important tool in assessing dynamic heart function. However, this technique requires long acquisition time and long breath holds, which presents difficulties. The aim of this study is to pr...
Automatic segmentation of echocardiographic images using a shifted windows vision transformer architecture.
Biomedical physics & engineering express
Sep 13, 2024
Echocardiography is one the most commonly used imaging modalities for the diagnosis of congenital heart disease. Echocardiographic image analysis is crucial to obtaining accurate cardiac anatomy information. Semantic segmentation models can be used t...
Deep learning method with integrated invertible wavelet scattering for improving the quality ofcardiac DTI.
Physics in medicine and biology
Sep 5, 2024
Respiratory motion, cardiac motion and inherently low signal-to-noise ratio (SNR) are major limitations ofcardiac diffusion tensor imaging (DTI). We propose a novel enhancement method that uses unsupervised learning based invertible wavelet scatterin...
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