Fast and low memory usage convolutional neural network for tomosynthesis data processing and feature detection

An X-ray imaging system comprising:

• a. an X-ray source configured to emit radiation beams towards an object;
• b. an X-ray detector movably aligned with the X-ray source to receive the radiation beams from the X-ray source and generate image data;
• c. a processing unit operably connected to the X-ray source and the X-ray detector to control the movement and operation of the X-ray source and X-ray detector, the processing unit configured to receive and process image data from the X-ray detector to form projection images;
• d. a display operably connected to the processing unit for presenting information to a user;
• e. a user interface operably connected to the processing unit to enable user input to the processing unit;
• f. an automatic anomaly detection system operably connected to the controller;
• and
• g. an electronic information storage device operably connected to the processing unit,
• wherein the automatic anomaly detection system is formed of a convolutional neural network having and operational instructions contained on the storage device to be accessed by the processing unit, the automatic anomaly detection system configured to receive a compact data representation input of the projection images and to analyze the compact data representation input to obtain an anomaly detection result, and wherein filters for the at least one layer of the convolutional neural network employed by the automatic anomaly detection system on the compact data representation are at least partially learned by the automatic anomaly detection system.