CPC G16H 30/40 (2018.01) [A61B 5/055 (2013.01); A61B 6/032 (2013.01); G06N 3/045 (2023.01); G06T 7/0014 (2013.01); G06T 11/008 (2013.01); G16H 30/20 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/10084 (2013.01); G06T 2207/10088 (2013.01)] | 13 Claims |
1. A method comprising:
receiving measurement data acquired by an imaging device;
flattening the measurement data;
selecting a decimation strategy based on a size of the measurement data;
producing a reconstructed image from the flattened measurement data using the decimation strategy and a plurality deep neural networks, where the selection is further based a size of an input layer of the plurality of deep neural networks;
decimating the measurement data according to the decimation strategy to produce at least a first decimated measurement data array and a second decimated measurement data array;
mapping the first decimated measurement data array to a first decimated image data array using a first deep neural network;
mapping the second decimated measurement data array to a second decimated image data array using a second deep neural network;
aggregating the first decimated image data array and the second decimated image data array using an aggregation network to produce an image data array;
reshaping the image data array to produce the reconstructed image; and
displaying the reconstructed image via a display device.
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