Patent ID: 11887298
Assignee: RENSSELAER POLYTECHNIC INSTITUTE
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 14:
15. A fluorescence lifetime imaging (FLI) deep learning system, the system comprising:
a processor;
a memory;
input/output circuitry; and
a deep neural network (DNN), the DNN comprising:
a first convolutional layer configured to receive FLI input data;
a plurality of intermediate layers, each intermediate layer configured to receive a respective intermediate input corresponding to an output of a respective prior layer, each intermediate layer further configured to provide a respective intermediate output related to the received respective intermediate input; and
an output layer configured to provide estimated FLI output data corresponding to the received FLI input data, the output layer is a fully convolutional (FC) down-sample layer comprising:
a first two-dimensional (2D) convolutional block;
a first intermediate block coupled to an output of the first 2D convolutional block;
a second 2D convolutional block coupled to an output of the first intermediate block;
a second intermediate block coupled to an output of the second 2D convolutional block;
a third 2D convolutional block coupled to an output of the second intermediate block; and
a rectified linear unit block coupled to an output of the third 2D convolutional block;
wherein the first intermediate block and the second intermediate block each comprise a batch normalization function and a rectified linear unit;

wherein the DNN is trained using synthetic data.