computed tomography angiography

Welcome to the blog on Artificial Intelligence of
the European Society of Radiology

This blog aims at bringing educational and critical perspectives on AI to readers. It should help imaging professionals to learn and keep up to date with the technologies being developed in this rapidly evolving field.

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Latest posts

How well does a 3D convolutional neural network perform in detecting hypoperfusion?

Due to the life-threatening nature of chronic pulmonary embolism (CPE) and how easily it can be misdiagnosed on computed tomography, the authors of this study investigated a three-dimensional convolutional neural network (CNN) algorithm for detecting hypoperfusion in CPE from computed tomography pulmonary angiography (CTPA). This study demonstrated the feasibility of a deep learning algorithm for detecting hypoperfusion in CPE from

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Do plaque-related factors affect the diagnostic performance of an AI-CADS?

In this study, the authors aimed to investigate the effects of plaque-related factors, if any, on the diagnostic performance of an artificial intelligence coronary-assisted diagnosis system (AI-CADS). This was undertaken by analyzing 1,224 vessels in 306 patients. The authors were able to determine that AI-CADS has the ability to distinguish ≥50% coronary stenosis, but found that an additional manual interpretation

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Evaluation of a CTA-based convolutional neural network for infarct volume prediction in anterior cerebral circulation ischaemic stroke

The authors of this study aimed to determine the efficacy of a convolutional neural network (CNN) in final infarct volume prediction from computed tomography angiography (CTA), subsequently comparing the results to a CT perfusion (CTP)-based commercially available software. The stroke cases treated with thrombolytic therapy or receiving supportive care were retrospectively selected by the authors. The study found that a

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How well does a 3D convolutional neural network perform in detecting hypoperfusion?

Due to the life-threatening nature of chronic pulmonary embolism (CPE) and how easily it can be misdiagnosed on computed tomography, the authors of this study investigated a three-dimensional convolutional neural network (CNN) algorithm for detecting hypoperfusion in CPE from computed tomography pulmonary angiography (CTPA). This study demonstrated the feasibility of a deep learning algorithm for detecting hypoperfusion in CPE from

Read More →

Do plaque-related factors affect the diagnostic performance of an AI-CADS?

In this study, the authors aimed to investigate the effects of plaque-related factors, if any, on the diagnostic performance of an artificial intelligence coronary-assisted diagnosis system (AI-CADS). This was undertaken by analyzing 1,224 vessels in 306 patients. The authors were able to determine that AI-CADS has the ability to distinguish ≥50% coronary stenosis, but found that an additional manual interpretation

Read More →

Evaluation of a CTA-based convolutional neural network for infarct volume prediction in anterior cerebral circulation ischaemic stroke

The authors of this study aimed to determine the efficacy of a convolutional neural network (CNN) in final infarct volume prediction from computed tomography angiography (CTA), subsequently comparing the results to a CT perfusion (CTP)-based commercially available software. The stroke cases treated with thrombolytic therapy or receiving supportive care were retrospectively selected by the authors. The study found that a

Read More →

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Footnotes:

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Reduced registration fees for ECR 2024:
Provided that ESR 2023 membership is activated and approved by August 31, 2023 (excl. "Members in Training Offer").

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