System and method for medical imaging

A method, comprising:

• a) receiving, by a controller unit, from a C-arm device, a plurality of fluoroscopic images of at least one portion of a lung of a patient,
• wherein each image of the plurality of fluoroscopic images is obtained with the C-arm device positioned at a particular pose of a plurality of poses traversed by the C-arm device while the C-arm device is moved through a range of motion,
• wherein the range of motion comprises at least a range of rotation, and
• wherein the range of rotation encompasses a sweep angle that is between 45 degrees and 75 degrees;
• b) generating, by the controller unit, an enhanced tomographic image of the at least a portion of the lung, by utilizing at least:
• a trained machine learning model and
• the plurality of fluoroscopic images;
• and
• c) outputting, by the controller unit, a representation of the enhanced tomographic image,
• wherein, when tested by a test method in which:
• (a) the at least one portion of the lung of the patient includes at least one lesion having a size of less than 30 millimeters, and
• (b) the representation of the enhanced tomographic image is an axial slice showing a defined boundary of the at least one lesion,
• the at least one lesion has a contrast-to-noise value of at least 5 as compared to a background of the representation.