Method, learning apparatus, and medical imaging apparatus for registration of images

A medical imaging device comprising:

• a medical data acquisition scanner;
• a processor that receives first source image data representing a synthesized structure presented in a plurality of different views synthesized according to a model of the structure;
• said processor also receiving second source image data representing a synthesized structure presented in a plurality of different views synthesized according to a model of the structure;
• said processor also receiving third source image data representing a view of an imaged structure generated by capturing an image of the subject by operating the scanner;
• said processor being configured to perform a first training operation, as a learning agent according to a machine learning algorithm, to determine a transformation between respective coordinate frames of at least two of said plurality of different views of the synthesized structure, using the labeled first source image data and using labels associated therewith;
• wherein the learning agent includes a domain classifier comprising a feature map generated by the learning agent during said first training operation and configured to generate therefrom a classification output indicating that received image data is one of said third source image data or said second source image data;
• said processor being configured to perform a second training operation using the unlabeled second and third source image data without using labels associated therewith, as a learning agent according to a machine learning algorithm, to determine a transformation between respective coordinate frames of said view of the imaged structure and a said view of the synthesized structure, such that the ability of the domain classifier to discriminate between said synthesized structure and said imaged structure is reduced.

A non-transitory, computer-readable data storage medium encoded with programming instructions, said storage medium being loaded into a computer system and said programming instructions causing said computer system to:

• receive first source image data representing a synthesized structure presented in a plurality of different views synthesized according to a model of the structure;
• receive second source image data representing a synthesized structure presented in a plurality of different views synthesized according to a model of the structure;
• receive third source image data representing a view of an imaged structure generated by an imaging apparatus in capturing an image of the subject;
• in a first training operation, train a computer system, configured as a learning agent according to a machine learning algorithm, to determine a transformation between respective coordinate frames of at least two of said plurality of different views of the synthesized structure, using the labeled first source image data and labels associated therewith;
• wherein the learning agent includes a domain classifier comprising a feature map generated by the learning agent during said first training operation and configured to generate therefrom a classification output indicating that received image data is one of said third source image data or said second source image data;
• and
• in a second training operation, use the unlabeled second and third source image data without using labels associated therewith, training a computer system to determine a transformation between respective coordinate frames of said view of the imaged structure and said view of the synthesized structure, such that the ability of the domain classifier to discriminate between said synthesized structure and said imaged structure is reduced.