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Heart Atria

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Machine learning based deconvolution of microarray atrial samples from atrial fibrillation patients reveals increased fractions of follicular CD4+ T lymphocytes and gamma-delta T cells.

Journal of physiology and pharmacology : an official journal of the Polish Physiological Society
A potential relationship between T cell immunity and development of atrial fibrillation (AF) has been proposed. Historically in AF patients it has been reported that peripheral blood had elevated CD4+ T cells. However few studies have explored whethe...

Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes.

Journal of cardiovascular computed tomography
BACKGROUND: Low-dose computed tomography (LDCT) are performed routinely for lung cancer screening. However, a large amount of nonpulmonary data from these scans remains unassessed. We aimed to validate a deep learning model to automatically segment a...

Generalizability and quality control of deep learning-based 2D echocardiography segmentation models in a large clinical dataset.

The international journal of cardiovascular imaging
Use of machine learning (ML) for automated annotation of heart structures from echocardiographic videos is an active research area, but understanding of comparative, generalizable performance among models is lacking. This study aimed to (1) assess th...

Segmentation of left atrium using CT images and a deep learning model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The left atrium (LA) is one of the cardiac cavities with the most complex anatomical structures. Its role in the clinical diagnosis and patient's management is critical, as it is responsible for the atrial fibrillation, a condition that promotes the ...

Robotic excision of gigantic left atrial myxoma.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery

Cardiac CTA image quality of adaptive statistical iterative reconstruction-V versus deep learning reconstruction "TrueFidelity" in children with congenital heart disease.

Medicine
BACKGROUND: Several recent studies have reported that deep learning reconstruction "TrueFidelity" (TF) improves computed tomography (CT) image quality. However, no study has compared adaptive statistical repeated reconstruction (ASIR-V) using TF in p...

Transformer-based multilevel region and edge aggregation network for magnetic resonance image segmentation.

Computers in biology and medicine
To improve the quality of magnetic resonance (MR) image edge segmentation, some researchers applied additional edge labels to train the network to extract edge information and aggregate it with region information. They have made significant progress....

Deep learning estimation of three-dimensional left atrial shape from two-chamber and four-chamber cardiac long axis views.

European heart journal. Cardiovascular Imaging
AIMS: Left atrial volume is commonly estimated using the bi-plane area-length method from two-chamber (2CH) and four-chamber (4CH) long axes views. However, this can be inaccurate due to a violation of geometric assumptions. We aimed to develop a dee...

Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

IEEE journal of biomedical and health informatics
In recent years, several deep learning models have been proposed to accurately quantify and diagnose cardiac pathologies. These automated tools heavily rely on the accurate segmentation of cardiac structures in MRI images. However, segmentation of th...

Design and Validation of a Soft Robotic Simulator for Transseptal Puncture Training.

IEEE transactions on bio-medical engineering
OBJECTIVE: Transseptal puncture (TP) is the technique used to access the left atrium of the heart from the right atrium during cardiac catheterization procedures. Through repetition, electrophysiologists and interventional cardiologists experienced i...