LEARNING-BASED CORRECTION OF GRID ARTIFACTS IN X-RAY IMAGING

A method for training a function of an X-ray system that has a positioning mechanism such as a C-arm, a detector, and, in a beam path in front of the detector, an anti-scatter grid. Positioning of the detector at a large number of different positions occurs. The positioning mechanism is deflected an...

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Bibliographische Detailangaben
Hauptverfasser:	Bernhardt, Philipp, Stowasser, Boris
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DIAGNOSIS HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA HUMAN NECESSITIES HYGIENE IDENTIFICATION IMAGE DATA PROCESSING OR GENERATION, IN GENERAL INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES MEASURING MEDICAL OR VETERINARY SCIENCE PHYSICS SURGERY TESTING
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Beschreibung
Zusammenfassung:	A method for training a function of an X-ray system that has a positioning mechanism such as a C-arm, a detector, and, in a beam path in front of the detector, an anti-scatter grid. Positioning of the detector at a large number of different positions occurs. The positioning mechanism is deflected and/or distorted. Recording of at least one X-ray photograph in each of the positions then takes place, and the method further includes machine learning of artifacts generated by the anti-scatter grid from all X-ray photographs for the function.