US 12,266,154 B2
Medical image analysis using machine learning and an anatomical vector
Stefan Vilsmeier, Munich (DE); and Jens Schmaler, Mering (DE)
Assigned to BRAINLAB AG, Munich (DE)
Filed by Brainlab AG, Munich (DE)
Filed on Oct. 27, 2023, as Appl. No. 18/496,306.
Application 18/496,306 is a continuation of application No. 17/281,472, granted, now 11,847,819, previously published as PCT/EP2019/086352, filed on Dec. 19, 2019.
Prior Publication US 2024/0062517 A1, Feb. 22, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06V 10/764 (2022.01); G06T 7/00 (2017.01); G06T 7/136 (2017.01); G06T 7/70 (2017.01); G06V 10/26 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/69 (2022.01); G06V 20/70 (2022.01)
CPC G06V 10/764 (2022.01) [G06T 7/0014 (2013.01); G06T 7/136 (2017.01); G06T 7/70 (2017.01); G06V 10/26 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 20/695 (2022.01); G06V 20/698 (2022.01); G06V 20/70 (2022.01); G06T 2207/10056 (2013.01); G06T 2207/10061 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01); G06V 2201/03 (2022.01)] 10 Claims
OG exemplary drawing
 
1. A computer-implemented method of training a learning algorithm for determining a relation between a label for indicating a position or type of an anatomical structure in a medical image and the position or type of the anatomical structure in the medical image, the method comprising the following steps:
patient training image data is acquired which describes digital medical images of the anatomical structure of a plurality of patients;
atlas data is acquired which describes a model of an anatomical body part including the anatomical structure;
viewing direction data is acquired which describes a viewing direction of an imaging device towards the anatomical structure at a point in time when the imaging device was used to generate the medical image;
anatomical vector data is determined based on the viewing direction data and the atlas data, wherein the anatomical vector data describes an anatomical vector which is a result of transforming the viewing direction into a reference system in which positions in an image-based model are defined;
label data is acquired which describes a label describing the position or type of the anatomical structure in the image-based model; and
anatomical indicator data is determined based on the patient training image data and the anatomical vector data and the label data, wherein the anatomical indicator data describes model parameters of the learning algorithm for establishing the relation between the position or type of the anatomical structure described by the medical image and the label, wherein the anatomical indicator data is determined by inputting the patient training image data and the label data into a function which establishes the relation.