[Use of artificial intelligence for image reconstruction].
[Use of artificial intelligence for image reconstruction].
Radiologe. 2020 Jan 02;:
Authors: Hoeschen C
Abstract
CLINICAL/METHODOLOGICAL PROBLEM: In the reconstruction of three-dimensional image data, artifacts that interfere with the appraisal often occur as a result of trying to minimize the dose or due to missing data. Used iterative reconstruction methods are time-consuming and have disadvantages.
STANDARD RADIOLOGICAL METHODS: These problems are known to occur in computed tomography (CT), cone beam CT, interventional imaging, magnetic resonance imaging (MRI) and nuclear medicine imaging (PET and SPECT).
METHODOLOGICAL INNOVATIONS: Using techniques based on the use of artificial intelligence (AI) in data analysis and data supplementation, a number of problems can be solved up to a certain extent.
PERFORMANCE: The performance of the methods varies greatly. Since the generated image data usually look very good using the AI-based methods presented here while their results depend strongly on the study design, reliable comparable quantitative statements on the performance are not yet available in broad terms.
EVALUATION: In principle, the methods of image reconstruction based on AI algorithms offer many possibilities for improving and optimizing three-dimensional image datasets. However, the validity strongly depends on the design of the respective study in the structure of the individual procedure. I...
Source: Der Radiologe - Category: Radiology Authors: Hoeschen C Tags: Radiologe Source Type: research
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