AIMC Topic: Coronary Vessels
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Improved Centerline Extraction in Fully Automated Coronary Ostium Localization and Centerline Extraction Framework using Deep Learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
Coronary artery extraction in cardiac CT angiography (CCTA) image volume is a necessary step for any quantitative assessment of stenoses and atherosclerotic plaque. In this work, we propose a fully automated workflow that depends on convolutional net...
Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence.
Open heart
Nov 1, 2021
OBJECTIVE: The study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT).
Deep learning for prediction of fractional flow reserve from resting coronary pressure curves.
EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
May 17, 2021
BACKGROUND: It would be ideal for a non-hyperaemic index to predict fractional flow reserve (FFR) more accurately, given FFR's extensive validation in a multitude of clinical settings.
Training and validation of a deep learning architecture for the automatic analysis of coronary angiography.
EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
May 17, 2021
BACKGROUND: In recent years, the use of deep learning has become more commonplace in the biomedical field and its development will greatly assist clinical and imaging data interpretation. Most existing machine learning methods for coronary angiograph...
The role of robotic totally endoscopic coronary artery bypass in the future of coronary artery revascularization.
European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
Aug 1, 2020
Prediction of atherosclerotic disease progression combining computational modelling with machine learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Non-invasive serial computed tomography coronary angiography (CTCA) was acquired from 32 patients and 3D reconstruction of 58 coronary arteries was achieved. The arterial geometries were utilized for blood flow and LDL transport modelling. Navier-Sto...
End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Dynamic reconstructions (3D+T) of coronary arteries could give important perfusion details to clinicians. Temporal matching of the different views, which may not be acquired simultaneously, is a prerequisite for an accurate stereo-matching of the cor...
Automated interpretation of the coronary angioscopy with deep convolutional neural networks.
Open heart
May 1, 2020
BACKGROUND: Coronary angioscopy (CAS) is a useful modality to assess atherosclerotic changes, but interpretation of the images requires expert knowledge. Deep convolutional neural networks (DCNN) can be used for diagnostic prediction and image synthe...
Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography.
Journal of thoracic imaging
May 1, 2020
PURPOSE: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC...
Machine Learning and Deep Neural Networks Applications in Coronary Flow Assessment: The Case of Computed Tomography Fractional Flow Reserve.
Journal of thoracic imaging
May 1, 2020
Coronary computed tomography angiography (cCTA) is a reliable and clinically proven method for the evaluation of coronary artery disease. cCTA data sets can be used to derive fractional flow reserve (FFR) as CT-FFR. This method has respectable result...
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