AIMC Topic: Heart

Clear Filters Showing 1 to 10 of 499 articles

SSMCE: A semi-supervised learning framework for myocardial segmentation in myocardial contrast echocardiography.

Biomedical physics & engineering express
Accurate myocardial segmentation in myocardial contrast echocardiography (MCE) images remains challenging due to the scarcity of publicly available labeled datasets and the pervasive presence of speckle noise.Currently, echocardiographers must manual...

Exercise mitigates high-fat diet-induced cardiac dysfunction via APOE genotype- and immune-dependent mechanisms: A photon-counting CT study in adult mice.

PloS one
BACKGROUND: Cardiovascular dysfunction frequently accompanies aging and is often worsened by adverse lifestyle factors and genetic susceptibility. The apolipoprotein E (APOE) gene modulates susceptibility to cardiovascular disease, but how exercise a...

Adaptive composite loss for volumetric whole heart segmentation.

Scientific reports
Accurate segmentation in medical imaging requires loss functions that capture both regional overlap and boundary alignment. This study evaluates composite losses combining binary cross-entropy (BCE) and a boundary-based term under fixed and adaptive ...

A novel deep learning system for STEMI prognostic prediction from multi-sequence cardiac magnetic resonance.

Science bulletin
ST-elevation myocardial infarction (STEMI) remains a leading cause of cardiovascular morbidity and mortality worldwide, and accurate early risk stratification is critical for implementing precision therapies in clinical practice. However, existing cl...

Classification of cardiac electrical signals between patients with myocardial infarction and healthy controls by using time-frequency features and 3D convolutional neural networks.

Biomedical physics & engineering express
Electrocardiogram (ECG) signal classification plays an important role in myocardial infarction (MI) detection and screening. Despite that much progress has been made, the interpretation of ECG signals is still extremely time-consuming, and heavily re...

Federated nnU-Net for privacy-preserving medical image segmentation.

Scientific reports
The nnU-Net framework has played a crucial role in medical image segmentation and has become the gold standard in multitudes of applications targeting different diseases, organs, and modalities. However, so far it has been used primarily in a central...

Generative augmentations for improved cardiac ultrasound segmentation using diffusion models.

Scientific reports
One of the main challenges in current research on segmentation in cardiac ultrasound is the lack of large and varied labeled datasets and the differences in annotation conventions between datasets. This makes it difficult to design robust segmentatio...

Intra- and inter-field strength reproducibility of deep-learning based real-time cardiac MRI cine sequences with breath hold and in free breathing.

Scientific reports
To assess intra- and inter-field strength reproducibility of volumetric parameters using deep-learning-based real-time cardiac cine MRI during breath-hold (BH) and free-breathing (FB). In this prospective single-center study, 56 healthy adults underw...

Fast and Robust Single-Shot Cine Cardiac MRI Using Deep Learning Super-Resolution Reconstruction.

Investigative radiology
OBJECTIVE: The aim of the study was to compare the diagnostic quality of deep learning (DL) reconstructed balanced steady-state free precession (bSSFP) single-shot (SSH) cine images with standard, multishot (also: segmented) bSSFP cine (standard cine...

The pericardium forms as a distinct structure during heart formation.

Nature communications
The heart is formed from diverse cell lineages that assemble into a functional unit, including the pericardium, a mesothelial sac that supports movement, homeostasis, and immune responses. However, its developmental origins remain unresolved. Here, w...