Methods and systems for providing guidance for adjusting an object based on similarity

A system for providing guidance for adjusting a target for imaging, the system comprising:

• an image acquisition apparatus configured to acquire a target image, the target image being related to a position of a target;
• an image processing apparatus configured to:
• receive, by a neural network, a reference image;
• receive, by the neural network, the target image;
• determine a similarity metric based at least in part on information associated with the reference image and information associated with the target image by the neural network;
• generate a target attention map corresponding to the target image based at least in part on the similarity metric;
• and
• output the target image and the target attention map;
• and
• a display apparatus configured to:
• receive the target image and the target attention map;
• and
• provide a guidance for adjusting the position of the target based at least in part on the target image and the target attention map;
• wherein the target attention map includes one or more high response regions that contributes substantially to the similarity metric;
• wherein the one or more high response regions correspond to one or more similar regions between the target image and the reference image when the one or more high response regions constitutes less than a coverage threshold of the target image;
• and
• wherein the one or more high response regions correspond to one or more dissimilar regions between the target image and the reference image when the one or more high response regions constitutes more than the coverage threshold of the target image.

A computer-implemented method for training a neural network, the method comprising:

• receiving, by a neural network, a first input image;
• receiving, by the neural network, a second input image;
• determining a first similarity metric based at least in part on information associated with the first input image and information associated with the second input image by the neural network;
• generating a first attention map corresponding to the first input image based at least in part on the first similarity metric;
• generating a second attention map corresponding to the second input image based at least in part on the first similarity metric;
• modifying the first input image based at least in part on the first attention map to generate a first modified image;
• modifying the second input image based at least in part on the second attention map to generate a second modified image;
• determining a second similarity metric based at least in part on information associated with the first modified image and information associated with the second modified image by the neural network;
• and
• changing one or more parameters of the neural network based at least in part on the first similarity metric and the second similarity metric;
• wherein the changing one or more parameters of the neural network includes:
• increasing the first similarity metric;
• and
• decreasing the second similarity metric;
• wherein the first attention map includes one or more high response regions that contributes substantially to the first similarity metric;
• wherein the one or more high response regions correspond to one or more similar regions between the first input image and the second input image when the one or more high response regions constitutes less than a coverage threshold of the first input image;
• and
• wherein the one or more high response regions correspond to one or more dissimilar regions between the first input image and the second input image when the one or more high response regions constitutes more than the coverage threshold of the first input image.