AIMC Topic: Heart

Clear Filters Showing 1 to 10 of 470 articles

Investigating methods to enhance interpretability and performance in cardiac MRI for myocardial scarring diagnosis using convolutional neural network classification and One Match.

PloS one Jun 9, 2025
Machine learning (ML) classification of myocardial scarring in cardiac MRI is often hindered by limited explainability, particularly with convolutional neural networks (CNNs). To address this, we developed One Match (OM), an algorithm that builds on ...
Heart Image Interpretation, Computer-Assisted Cicatrix Myocardium Female Aged Male Middle Aged Convolutional Neural Networks Magnetic Resonance Imaging Neural Networks, Computer Machine Learning Algorithms Humans
View on PubMed DOI

Aging at the Crossroads of Organ Interactions: Implications for the Heart.

Circulation research May 22, 2025
Aging processes underlie common chronic cardiometabolic diseases such as heart failure and diabetes. Cross-organ/tissue interactions can accelerate aging through cellular senescence, tissue wasting, accelerated atherosclerosis, increased vascular sti...
Cellular Senescence Aging Humans Animals Oxidative Stress Heart
View on PubMed DOI

Multi-view hybrid graph convolutional network for volume-to-mesh reconstruction in cardiovascular MRI.

Medical image analysis May 17, 2025
Cardiovascular magnetic resonance imaging is emerging as a crucial tool to examine cardiac morphology and function. Essential to this endeavour are anatomical 3D surface and volumetric meshes derived from CMR images, which facilitate computational an...
Humans Magnetic Resonance Imaging Heart Image Interpretation, Computer-Assisted Neural Networks, Computer Imaging, Three-Dimensional Image Processing, Computer-Assisted
View on PubMed DOI

Integrating anatomy and electrophysiology in the healthy human heart: Insights from biventricular statistical shape analysis using universal coordinates.

Computers in biology and medicine May 4, 2025
A cardiac digital twin is a virtual replica of a patient-specific heart, mimicking its anatomy and physiology. A crucial step of building a cardiac digital twin is anatomical twinning, where the computational mesh of the digital twin is tailored to t...
Heart Ventricles Models, Cardiovascular Middle Aged Electrocardiography Heart Humans Tomography, X-Ray Computed Female Adult Male
View on PubMed DOI

Semi-Supervised Echocardiography Video Segmentation via Adaptive Spatio-Temporal Tensor Semantic Awareness and Memory Flow.

IEEE transactions on medical imaging May 2, 2025
Accurate segmentation of cardiac structures in echocardiography videos is vital for diagnosing heart disease. However, challenges such as speckle noise, low spatial resolution, and incomplete video annotations hinder the accuracy and efficiency of se...
Image Interpretation, Computer-Assisted Semantics Image Processing, Computer-Assisted Heart Supervised Machine Learning Algorithms Echocardiography Humans
View on PubMed DOI

Feedback Attention to Enhance Unsupervised Deep Learning Image Registration in 3D Echocardiography.

IEEE transactions on medical imaging May 2, 2025
Cardiac motion estimation is important for assessing the contractile health of the heart, and performing this in 3D can provide advantages due to the complex 3D geometry and motions of the heart. Deep learning image registration (DLIR) is a robust wa...
Humans Algorithms Female Adult Heart Echocardiography, Three-Dimensional Deep Learning Unsupervised Machine Learning
View on PubMed DOI

Spatiotemporal Implicit Neural Representation for Unsupervised Dynamic MRI Reconstruction.

IEEE transactions on medical imaging May 2, 2025
Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results for highly-undersampled dynamic Magnetic Resonance Imaging (MRI) reconstruction. However, the requirement of excessive high-quality ground-truth data hi...
Heart Neural Networks, Computer Humans Image Processing, Computer-Assisted Algorithms Magnetic Resonance Imaging Brain Unsupervised Machine Learning
View on PubMed DOI

Self-supervised learning for label-free segmentation in cardiac ultrasound.

Nature communications Apr 30, 2025
Segmentation and measurement of cardiac chambers from ultrasound is critical, but laborious and poorly reproducible. Neural networks can assist, but supervised approaches require the same problematic manual annotations. We build a pipeline for self-s...
Supervised Machine Learning Echocardiography Deep Learning Magnetic Resonance Imaging Image Processing, Computer-Assisted Female Humans Heart Reproducibility of Results Neural Networks, Computer Heart Ventricles Male
View on PubMed DOI

An end-to-end neural network for 4D cardiac CT reconstruction using single-beat scans.

Physics in medicine and biology Apr 22, 2025
Motion artifacts remain a significant challenge in cardiac CT imaging, often impairing the accurate detection and diagnosis of cardiac diseases. These artifacts result from involuntary cardiac motion, and traditional mitigation methods typically rely...
Neural Networks, Computer Humans Deep Learning Heart Phantoms, Imaging Image Processing, Computer-Assisted Artifacts Four-Dimensional Computed Tomography Signal-To-Noise Ratio
View on PubMed DOI

Causal recurrent intervention for cross-modal cardiac image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Apr 21, 2025
Cross-modal cardiac image segmentation is essential for cardiac disease analysis. In diagnosis, it enables clinicians to obtain more precise information about cardiac structure or function for potential signs by leveraging specific imaging modalities...
Humans Multimodal Imaging Heart Image Interpretation, Computer-Assisted Algorithms Deep Learning Image Processing, Computer-Assisted
View on PubMed DOI
Popular Topics
Recent Journals