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

US10832392B2 · kind B2 · utility

Assignee

• Siemens Healthcare Limited · DE

Inventors

• Pascal Ceccaldi · New York, US
• Tanja Kurzendorfer · Trautmannshofen, DE
• Tommaso Mansi · Plainsboro, US
• Peter Mountney · London, GB
• Sebastien Piat · Lawrence, US
• Daniel Toth · Teddington, GB

Key dates

• Filing date: Dec 19, 2018
• Grant date: Nov 10, 2020
• Expiry date: Apr 21, 2039

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2210/41
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method of training a computer system for use in determining a transformation between coordinate frames of image data representing an imaged subject. The method trains a learning agent according to a machine learning algorithm, to determine a transformation between respective coordinate frames of a number of different views of an anatomical structure simulated using a 3D model. The views are images containing labels. The learning agent includes a domain classifier comprising a feature map generated by the learning agent during the training operation. The classifier is configured to generate a classification output indicating whether image data is synthesized or real images data. Training includes using unlabeled real image data to training the computer system to determine a transformation between a coordinate frame of a synthesized view of the imaged structure and a view of the structure within a real image. This is done whilst deliberately reducing the ability of the domain classifier to discriminate between a synthesized image and a real image of the structure.