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Deep-Learning Image Reconstruction in CCTA

2019-06-14 01:54:39 | BioPortfolio

Summary

Cardiac CT allows the assessment of the heart and of the coronary arteries by use of ionising radiation. Although radiation exposure was significantly reduced in recent years, further decrease in radiation exposure is limited by increased image noise and deterioration in image quality. Recent evidence suggests that further technological refinements with artificial intelligence allows improved post-processing of images with reduction of image noise.

The present study aims at assessing the potential of a deep-learning image reconstruction algorithm in a clinical setting. Specifically, after a standard clinical scan, patients are scanned with lower radiation exposure and reconstructed with the DLIR algorithm. This interventional scan is then compared to the standard clinical scan.

Study Design

Conditions

Coronary Artery Disease

Intervention

TrueFidelity

Location

University Hospital
Zurich
Switzerland
8091

Status

Recruiting

Source

University of Zurich

Results (where available)

View Results

Links

Published on BioPortfolio: 2019-06-14T01:54:39-0400

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