System and methods for a measurement tool for medical imaging

A system, comprising:

• a display device;
• and
• an image processing system configured with instructions in non-transitory memory that when executed cause the image processing system to:
• determine, based on a first output of a measurement model and a second output of the measurement model, if an ultrasound image frame of a subject includes a target anatomical view and if an image quality of the ultrasound image frame is above a threshold image quality;
• if the ultrasound image frame includes the target anatomical view and has an image quality that is above the threshold image quality, obtain, from the measurement model, a measurement of a thickness of visceral fat present in the ultrasound image frame;
• and
• output, for display on the display device, the measurement of the thickness of the visceral fat and an assessment of a liver disease of the subject that is determined based on the measurement of the visceral fat, wherein the measurement model includes one or more deep learning networks that are configured to take the ultrasound image frame as input and produce multiple outputs, including the first output indicating if the ultrasound image frame includes the target anatomical view, the second output indicating the image quality of the ultrasound image frame, and a third output including the measurement of the thickness of the visceral fat, wherein the measurement model is trained to generate the second output after the measurement model is trained to generate the third output, and wherein training the measurement model to generate the second output includes entering a plurality of training ultrasound images of varying quality to the measurement model, determining an accuracy of measured visceral fat of each training ultrasound image, and updating the measurement model based on the accuracy.