Medical image analysis using machine learning and an anatomical vector

US11847819B2 · kind B2 · utility

Assignee

• Brainlab AG · DE

Inventors

• Stefan Vilsmeier · Munich, DE
• Jens Schmaler · Mering, DE

Key dates

• Filing date: Dec 19, 2019
• Grant date: Dec 19, 2023
• Expiry date: Oct 10, 2040

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V2201/03
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Disclosed is a computer-implemented method which encompasses registering a tracked imaging device such as a microscope having a known viewing direction and an atlas to a patient space so that a transformation can be established between the atlas space and the reference system for defining positions in images of an anatomical structure of the patient. Labels are associated with certain constituents of the images and are input into a learning algorithm such as a machine learning algorithm, for example a convolutional neural network, together with the medical images and an anatomical vector and for example also the atlas to train the learning algorithm for automatic segmentation of patient images generated with the tracked imaging device. The trained learning algorithm then allows for efficient segmentation and/or labelling of patient images without having to register the patient images to the atlas each time, thereby saving on computational effort.