• Present Invention explains about a system & method for image reconstruction using fully unsupervised deep learning techniques.
• Further it explains that a system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions.. like a method for training a neural network for image reconstruction.

• The method includes the following steps depicted in the smart chart hereinbelow:

STEP 1

• Calculating loss function (L(X,X′)) & projection data error (X-X′) based on actual projection data (X) & reference reconstructed projection data (X′);

STEP 2

• Updating one or more parameters of the neural network based on the calculated loss function (L(X,X′));

STEP 3

• Reconstructing an image (Y′) by processing the actual projection data error (X-X′) using the one or more updated neural network parameters;

STEP 4

• Transforming the reconstructed image (Y′) into new reference reconstructed projection data (X′);

STEP 5

• Iteratively performing steps S1-S4 for a predefined number of cycle for calculating an optimum loss function (L(X,X′));

STEP 6

• Generating one or more optimum parameters of the neural network using the optimum loss function (L(X,X′));

STEP 7

• Updating the neural network with the one or more optimum parameters, & Transforming the reconstructed image (Y′) by processing the projection data (X) using a trained neural network.