Systems and methods for image cropping and anatomical structure segmentation in medical imaging

A system comprising:

• one or more data storage devices storing at least one first neural network model and at least one second neural network model, each first neural network model having been trained to approximate a region-of-interest (ROI) around an anatomical structure or a cut-off plane with respect to the anatomical structure, each second neural network model having been trained to approximate a contour of the anatomical structure;
• and
• one or more processors operatively coupled to the one or more data storage devices and configured to:
• employ the at least one first neural network model to process one or more medical images of a patient to generate cropping data;
• based at least one the cropping data from the at least one first neural network model, crop the one or more medical images of the patient;
• and
• employ the at least one second neural network model to process the one or more cropped medical images of the patient to generate one or more contours of anatomical structures in the medical images of the patient.

A non-transitory computer-readable storage medium upon which is embodied a sequence of programmed instructions, and a computer processing system that executes the sequence of programmed instructions embodied on the computer-readable storage medium to cause the computer processing system to:

• process one or more medical images of a patient using at least one first neural network model to generate cropping data, each first neural network model having been trained to approximate a region-of-interest (ROI) around an anatomical structure or a cut-off plane with respect to the anatomical structure;
• crop the one or more medical images of the patient based at least on the cropping data from the at least one first neural network model;
• and
• process the one or more cropped medical images of the patient using at least one second neural network model to generate one or more contours of anatomical structures in the one or more medical images of the patient, each second neural network model having been trained to approximate contours of anatomical structures.