Apparatus and method for generating a three-dimensional (3D) model of cardiac anatomy based on model uncertainty

A method of generating a three-dimensional (3D) model of cardiac anatomy, the method comprising:

• using at least a processor, receiving a first set of ultrasound images of cardiac anatomy;
• using at least a processor, generating a first 3D model of the cardiac anatomy by:
• inputting into at least a trained neural network the first set of ultrasound images of cardiac anatomy;
• receiving as an output from the at least a trained neural network a first set of shape parameters;
• and
• using a statistical shape model to determine the first 3D model of the cardiac anatomy as a function of the set of shape parameters;
• using at least a processor, calculating a level of uncertainty at a plurality of locations on the first 3D model;
• using at least a processor, receiving a second set of ultrasound images of the cardiac anatomy corresponding to a high uncertainty region of the first 3D model, wherein receiving the second set of ultrasound images comprises, by a user, positioning for capturing an image of the high uncertainty region a cardiac image capture device configured to capture ultrasound images;
• and
• using at least a processor, generating a second 3D model by:
• inputting into the at least a trained neural network the first set of ultrasound images of cardiac anatomy and the second set of ultrasound images of cardiac anatomy;
• receiving as an output from the at least a trained neural network a second set of shape parameters;
• and
• using the statistical shape model to determine the second 3D model of the cardiac anatomy as a function of the second set of shape parameters.