Keywords: Data Analysis, Data Analysis, Neural NetworkWe describe a method, namely neural ordinary differential equations, to track the movement of the stomach based on dynamic and contrast-enhanced gastrointestinal MRI. This model uses a neural network to learn the continuous biomechanical process that drives the shape change of the stomach wall over the course of digestion. This method allows us to represent gastric motor events on a generic surface template of the stomach and to further reveal the pattern of gastric motility with higher specificity and resolution than are previously attainable in vivo. This method should be also applicable to other organs, such as the heart.
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