AIMC Topic: Angiography

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A multitask deep learning approach for pulmonary embolism detection and identification.

Scientific reports Jul 29, 2022
Pulmonary embolism (PE) is a blood clot traveling to the lungs and is associated with substantial morbidity and mortality. Therefore, rapid diagnoses and treatments are essential. Chest computed tomographic pulmonary angiogram (CTPA) is the gold stan...
Humans Retrospective Studies Deep Learning Pulmonary Embolism Angiography Tomography, X-Ray Computed Lung
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Editorial for "Perfusion Maps Acquired from Dynamic Angiography MRI Using Deep Learning Approaches".

Journal of magnetic resonance imaging : JMRI Jun 22, 2022
Deep Learning Magnetic Resonance Imaging Humans Perfusion Angiography
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Perfusion Maps Acquired From Dynamic Angiography MRI Using Deep Learning Approaches.

Journal of magnetic resonance imaging : JMRI Jun 21, 2022
BACKGROUND: A typical stroke MRI protocol includes perfusion-weighted imaging (PWI) and MR angiography (MRA), requiring a second dose of contrast agent. A deep learning method to acquire both PWI and MRA with single dose can resolve this issue.
Humans Retrospective Studies Female Angiography Cerebrovascular Circulation Contrast Media Magnetic Resonance Imaging Middle Aged Aged Perfusion Adult Deep Learning Magnetic Resonance Angiography
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A lightweight deep learning model for automatic segmentation and analysis of ophthalmic images.

Scientific reports May 20, 2022
Detection, diagnosis, and treatment of ophthalmic diseases depend on extraction of information (features and/or their dimensions) from the images. Deep learning (DL) model are crucial for the automation of it. Here, we report on the development of a ...
Angiography Deep Learning Image Processing, Computer-Assisted Tomography, Optical Coherence Retina Reproducibility of Results
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Rethinking the neighborhood information for deep learning-based optical coherence tomography angiography.

Medical physics Mar 28, 2022
PURPOSE: Optical coherence tomography angiography (OCTA) is a premium imaging modality for noninvasive microvasculature studies. Deep learning networks have achieved promising results in the OCTA reconstruction task, benefiting from their powerful mo...
Algorithms Fluorescein Angiography Microvessels Tomography, Optical Coherence Angiography Animals Deep Learning
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Automated detection of pulmonary embolism from CT-angiograms using deep learning.

BMC medical imaging Mar 14, 2022
BACKGROUND: The aim of this study was to develop and evaluate a deep neural network model in the automated detection of pulmonary embolism (PE) from computed tomography pulmonary angiograms (CTPAs) using only weakly labelled training data.
Angiography Deep Learning Pulmonary Embolism Retrospective Studies Humans Tomography, X-Ray Computed
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Angular super-resolution in X-ray projection radiography using deep neural network: Implementation on rotational angiography.

Biomedical journal Jan 10, 2022
BACKGROUND: Rotational angiography acquires radiographs at multiple projection angles to demonstrate superimposed vasculature. However, this comes at the expense of the inherent risk of increased ionizing radiation. In this paper, building upon a suc...
Radiography Angiography X-Rays Neural Networks, Computer Image Processing, Computer-Assisted Humans
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Performance of a 3D convolutional neural network in the detection of hypoperfusion at CT pulmonary angiography in patients with chronic pulmonary embolism: a feasibility study.

European radiology experimental Sep 24, 2021
BACKGROUND: Chronic pulmonary embolism (CPE) is a life-threatening disease easily misdiagnosed on computed tomography. We investigated a three-dimensional convolutional neural network (CNN) algorithm for detecting hypoperfusion in CPE from computed t...
Angiography Humans Feasibility Studies Neural Networks, Computer Pulmonary Embolism Tomography, X-Ray Computed
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Deep learning-based Hounsfield unit value measurement method for bolus tracking images in cerebral computed tomography angiography.

Computers in biology and medicine Sep 2, 2021
BACKGROUND: Patient movement during bolus tracking (BT) impairs the accuracy of Hounsfield unit (HU) measurements. This study assesses the accuracy of measuring HU values in the internal carotid artery (ICA) using an original deep learning (DL)-based...
Computed Tomography Angiography Humans Deep Learning Retrospective Studies Angiography Tomography, X-Ray Computed
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Improving cerebral microvascular image quality of optical coherence tomography angiography with deep learning-based segmentation.

Journal of biophotonics Aug 18, 2021
Optical coherence tomography angiography (OCTA) can map the microvascular networks of the cerebral cortices with micrometer resolution and millimeter penetration. However, the high scattering of the skull and the strong noise in the deep imaging regi...
Angiography Tomography, Optical Coherence Neural Networks, Computer Signal-To-Noise Ratio Deep Learning
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