CONTINUOUS AND DYNAMIC EJECTION FRACTION DETERMINATION
Abstract:
The continuous and dynamic computation of ejection fraction (EF) includes training a neural network with different sets of cardiac imaging data acquired of a ventricle for different hearts and a known EF for each of the sets and then loading the trained neural network into memory of a computer. Afterwards, contemporaneous sets of imaging data of a ventricle of a heart are continuously acquired according to a specified view. For each corresponding set of imaging data, an image quality value may then be computed, and the corresponding set of imaging data may be provided to the neural network. The neural network, in response, provides, as output, an EF determination output without tracing a ventricle boundary of the heart. Thereafter, both the computed image quality value and the EF determination output may be displayed in a display of the computer.
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