Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 13, 2025
BACKGROUND: Accurate segmentation of echocardiographic images is essential for assessing cardiac function, particularly in calculating key metrics such as ejection fraction. However, challenges such as domain discrepancy, noisy data, anatomical varia...
The application of machine learning in healthcare continues to gain attention as researchers attempt to prove its potential for the enhancement of diagnosis and prognosis accuracy. Although many applications of machine learning have been well studied...
Biomedical physics & engineering express
Aug 6, 2025
Due to the scarcity and high cost of pixel-level annotations for training data, semi-supervised learning has gradually become a key solution. Most existing methods rely on consistency regularization and pseudo-label generation, often adopting multi-b...
Novel insights into cardiac contractile dysfunction at the cellular level could deepen understanding of arrhythmia and heart injury, which are leading causes of morbidity and mortality worldwide. We present a comprehensive experimental and computatio...
Myocardial strain plays a crucial role in diagnosing heart failure and myocardial infarction. Its computation relies on assessing heart muscle motion throughout the cardiac cycle. This assessment can be performed by following key points on each frame...
Computer methods and programs in biomedicine
Jun 23, 2025
BACKGROUND AND OBJECTIVE: The Variational Bayesian (VB) image registration model has garnered recent attention for its ability to offer uncertainty, particularly in the context of cardiac motion estimation. Nonetheless, several challenges have plague...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jun 19, 2025
Cardiac anatomy and physiology vary considerably across the human population. Understanding and taking into account this variability is crucial for both accurate clinical decision-making and realistic in silico modeling of cardiac function. In this w...
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 ...
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...
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...
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