MACHINE LEARNING BASED SCATTER CORRECTION

The present approach relates to the use of machine-learning in convolution kernel design for scatter correction. In one aspect, a neural network is trained to replace or improve the convolution kernel used for scatter correction. The training data set may be generated probabilistically so that actua...

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Bibliographic Details
Main Authors Qian, Hua, De Man, Bruno Kristiaan Bernard, Rui, Xue, Lai, Hao, Tkaczyk, John Eric
Format Patent
LanguageEnglish
Published 15.11.2018
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:The present approach relates to the use of machine-learning in convolution kernel design for scatter correction. In one aspect, a neural network is trained to replace or improve the convolution kernel used for scatter correction. The training data set may be generated probabilistically so that actual measurements are not employed.
Bibliography:Application Number: US201715593157