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Coronary Vessels

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Design and evaluation of vascular interventional robot system for complex coronary artery lesions.

Medical & biological engineering & computing
At present, most vascular intervention robots cannot cope with the more common coronary complex lesions in the clinic. Moreover, the lack of effective force feedback increases the risk of surgery. In this paper, a vascular interventional robot that c...

A Deep Learning Method for Motion Artifact Correction in Intravascular Photoacoustic Image Sequence.

IEEE transactions on medical imaging
In vivo application of intravascular photoacoustic (IVPA) imaging for coronary arteries is hampered by motion artifacts associated with the cardiac cycle. Gating is a common strategy to mitigate motion artifacts. However, a large amount of diagnostic...

Prediction of Coronary Artery Calcium Using Deep Learning of Echocardiograms.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
BACKGROUND: Coronary artery calcification (CAC), often assessed by computed tomography (CT), is a powerful marker of coronary artery disease that can guide preventive therapies. Computed tomographies, however, are not always accessible or serially ob...

Identification of Coronary Culprit Lesion in ST Elevation Myocardial Infarction by Using Deep Learning.

IEEE journal of translational engineering in health and medicine
OBJECTIVE: Early revascularization of the occluded coronary artery in patients with ST elevation myocardial infarction (STEMI) has been demonstrated to decrease mortality and morbidity. Currently, physicians rely on features of electrocardiograms (EC...

Opportunistic deep learning powered calcium scoring in oncologic patients with very high coronary artery calcium (≥ 1000) undergoing 18F-FDG PET/CT.

Scientific reports
Our aim was to identify and quantify high coronary artery calcium (CAC) with deep learning (DL)-powered CAC scoring (CACS) in oncological patients with known very high CAC (≥ 1000) undergoing 18F-FDG-PET/CT for re-/staging. 100 patients were enrolled...

Segmenting 3D geometry of left coronary artery from coronary CT angiography using deep learning for hemodynamic evaluation.

Biomedical physics & engineering express
While coronary CT angiography (CCTA) is crucial for detecting several coronary artery diseases, it fails to provide essential hemodynamic parameters for early detection and treatment. These parameters can be easily obtained by performing computationa...

Deep learning-based prediction of coronary artery stenosis resistance.

American journal of physiology. Heart and circulatory physiology
Coronary artery stenosis resistance (SR) is a key factor for noninvasive calculations of fractional flow reserve derived from coronary CT angiography (FFR). Existing computational fluid dynamics (CFD) methods, including three-dimensional (3-D) comput...

CAR-Net: A Deep Learning-Based Deformation Model for 3D/2D Coronary Artery Registration.

IEEE transactions on medical imaging
Percutaneous coronary intervention is widely applied for the treatment of coronary artery disease under the guidance of X-ray coronary angiography (XCA) image. However, the projective nature of XCA causes the loss of 3D structural information, which ...

Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.

Korean journal of radiology
OBJECTIVE: This study aimed to investigate whether a deep learning reconstruction (DLR) method improves the image quality, stent evaluation, and visibility of the valve apparatus in coronary computed tomography angiography (CCTA) when compared with f...