Artificial intelligence training with multiple pulsed x-ray source-in-motion tomosynthesis imaging system

Disclosed are image recognition Artificial Intelligence (AI) training methods for multiple pulsed X-ray source-in-motion tomosynthesis imaging system. Image recognition AI training can be performed three ways: first, using existing acquired chest CT data set with known nodules to generate synthetic...

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Bibliographische Detailangaben
Hauptverfasser:	Ku, Chwen-yuan, Liu, Jianqiang, Yang, Linbo, Maolinbay, Manat
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING 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:	Disclosed are image recognition Artificial Intelligence (AI) training methods for multiple pulsed X-ray source-in-motion tomosynthesis imaging system. Image recognition AI training can be performed three ways: first, using existing acquired chest CT data set with known nodules to generate synthetic tomosynthesis Images, no X-ray radiation applied; second, taking X-ray raw images with anthropomorphic chest phantoms with simulated lung nodules, applying X-ray beam on phantom only; third, acquiring X-ray images using multiple pulsed source-in-motion tomosynthesis images from real patients with real known nodules and without nodules. An X-ray image recognition training network that is configured to receive X-ray training images, automatically determine whether the received images indicate a nodule or lesion condition. After training, image knowledge is updated and stored at knowledge database.