AIMC Topic: Aorta

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Deep Learning-based Automated Aortic Area and Distensibility Assessment: the Multi-Ethnic Study of Atherosclerosis (MESA).

Journal of digital imaging Mar 1, 2022
This study details application of deep learning for automatic segmentation of the ascending and descending aorta from 2D phase-contrast cine magnetic resonance imaging for automatic aortic analysis on the large MESA cohort with assessment on an exter...
Magnetic Resonance Imaging Atherosclerosis Aorta Humans Algorithms Deep Learning
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Dissected aorta segmentation using convolutional neural networks.

Computer methods and programs in biomedicine Sep 15, 2021
BACKGROUND AND OBJECTIVE: Aortic dissection is a severe cardiovascular pathology in which an injury of the intimal layer of the aorta allows blood flowing into the aortic wall, forcing the wall layers apart. Such situation presents a high mortality r...
Image Processing, Computer-Assisted Aorta Computed Tomography Angiography Neural Networks, Computer Algorithms Tomography, X-Ray Computed
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Potential of high dimensional radiomic features to assess blood components in intraaortic vessels in non-contrast CT scans.

BMC medical imaging Aug 12, 2021
BACKGROUND: To assess the potential of radiomic features to quantify components of blood in intraaortic vessels to non-invasively predict moderate-to-severe anemia in non-contrast enhanced CT scans.
Tomography, X-Ray Computed Female Aged Humans Machine Learning Decision Trees Hemoglobins Hematocrit Anemia Image Interpretation, Computer-Assisted Aorta Adult Aged, 80 and over Male Young Adult Middle Aged
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Automated segmentation and quantification of the healthy and diseased aorta in CT angiographies using a dedicated deep learning approach.

European radiology Jun 25, 2021
OBJECTIVES: To develop and validate a deep learning-based algorithm for segmenting and quantifying the physiological and diseased aorta in computed tomography angiographies.
Deep Learning Aorta Computed Tomography Angiography Humans Algorithms Retrospective Studies Male
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Deep learning method for aortic root detection.

Computers in biology and medicine Jun 15, 2021
BACKGROUND: Computed tomography angiography (CTA) is a preferred imaging technique for a wide range of vascular diseases. However, extensive manual analysis is required to detect and identify several anatomical landmarks for clinical application. Thi...
Tomography, X-Ray Computed Deep Learning Aorta Computed Tomography Angiography
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Deep Learning Improves the Temporal Reproducibility of Aortic Measurement.

Journal of digital imaging May 28, 2021
Imaging-based measurements form the basis of surgical decision making in patients with aortic aneurysm. Unfortunately, manual measurement suffer from suboptimal temporal reproducibility, which can lead to delayed or unnecessary intervention. We teste...
Deep Learning Aorta Humans Reproducibility of Results
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Synthetic Database of Aortic Morphometry and Hemodynamics: Overcoming Medical Imaging Data Availability.

IEEE transactions on medical imaging Apr 30, 2021
Modeling of hemodynamics and artificial intelligence have great potential to support clinical diagnosis and decision making. While hemodynamics modeling is extremely time- and resource-consuming, machine learning (ML) typically requires large trainin...
Aortic Coarctation Aorta Models, Cardiovascular Humans Artificial Intelligence Hemodynamics Magnetic Resonance Imaging
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Prediction of Distal Aortic Enlargement after Proximal Repair of Aortic Dissection Using Machine Learning.

Annals of vascular surgery Apr 3, 2021
OBJECTIVES: This study aimed to construct a risk prediction model for distal aortic enlargement in patients with type B aortic dissection (TBAD) treated with proximal thoracic endovascular aortic repair (TEVAR).
Dilatation, Pathologic Male Middle Aged Risk Assessment Time Factors Treatment Outcome Risk Factors Aged Adult Clinical Decision-Making Female Aorta Aortic Rupture Blood Vessel Prosthesis Implantation Decision Support Techniques Endovascular Procedures Retrospective Studies Vascular Remodeling Electronic Health Records Support Vector Machine Humans Aortic Dissection Neural Networks, Computer Aortic Aneurysm, Thoracic
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CycleGAN for interpretable online EMT compensation.

International journal of computer assisted radiology and surgery Mar 14, 2021
PURPOSE: Electromagnetic tracking (EMT) can partially replace X-ray guidance in minimally invasive procedures, reducing radiation in the OR. However, in this hybrid setting, EMT is disturbed by metallic distortion caused by the X-ray device. We plan ...
Operating Rooms Electromagnetic Phenomena Phantoms, Imaging Calibration Aorta Radiation Exposure Humans Neural Networks, Computer Algorithms Reproducibility of Results Imaging, Three-Dimensional Surgery, Computer-Assisted
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A Deep Learning Pipeline to Automate High-Resolution Arterial Segmentation With or Without Intravenous Contrast.

Annals of surgery Nov 23, 2020
BACKGROUND: Existing methods to reconstruct vascular structures from a computerized tomography (CT) angiogram rely on contrast injection to enhance the radio-density within the vessel lumen. However, pathological changes in the vasculature may be pre...
Deep Learning Aorta Aortic Aneurysm Humans Tomography, X-Ray Computed
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