Real time medical image processing using deep learning accelerator with integrated random access memory

A method, comprising:

• writing, to random access memory of a device, first data representative of parameters of an artificial neural network;
• writing, to the random access memory of the device, second data representative of instructions executable to implement matrix computations of the artificial neural network using at least the first data stored in the random access memory;
• receiving, via at least one interface of the device, third data representative of an image generated in an imaging apparatus, the imaging apparatus configured to image a portion of a person;
• writing, to the random access memory of the device, the third data representative of the image received via the at least one interface;
• executing the instructions represented by the second data to implement the matrix computations of the artificial neural network;
• and
• outputting an indication configured to guide or assist imaging of the portion of the person according to the artificial neural network.

An apparatus, comprising:

• memory configured to store first data representative of parameters of an artificial neural network, second data representative of instructions executable to implement matrix computations of the artificial neural network using at least the first data stored in the memory, and third data representative of an image generated in an imaging device, the imaging device configured to image a portion of a person;
• at least one interface configured to receive the third data representative of the image and store the third data into the memory;
• a connection to the memory;
• and
• a Field-Programmable Gate Array (FPGA) or Application Specific Integrated circuit (ASIC) having:
• a memory interface configure to access the memory via the connection;
• and
• at least one processing unit configured to execute the instructions having matrix operands to implement the matrix computations of the artificial neural network, the artificial neural network configured to generate, using the image as an input, an output configured to guide or assist imaging of the portion of the person.