Patent ID: 11861846
Assignee: BRAINLAB AG
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A computer-implemented method of training a learning algorithm for determining a connection of a segmentation of a digital medical image, the method comprising:
executing a computer-implemented method of determining distributions of corrections for correcting a segmentation of medical image data which includes:
acquiring initial segmented patient image data which describes an initial segmentation of digital medical images of an anatomical body part of a first plurality of patients;
acquiring segmentation correction data which describes a correction of the initial segmentation for each patient of the first plurality of patients;
acquiring atlas data which describes an image-based model of the anatomical body part;
determining correction transformation data based on the segmentation correction data and the atlas data, wherein the correction transformation data describes a transformation for transforming the corrections into a reference system used for describing positions in the image-based model;
determining transformed correction data based on the segmentation correction data and the correction transformation data by applying the transformation to the corrections to determine transformed corrections;
determining combined correction data based on the transformed co2rection data, wherein the combined correction data describes the results of a statistical analysis of the corrections;
wherein the computer-implemented method of determining corrections for correcting the segmentation of medical image data further comprises:
acquiring training patient image data which describes digital medical images of an anatomical structure of a second plurality of patients;

acquiring label data which describes positions of labels assigned to the training patient image data, wherein the positions of the labels are defined in the reference system in which positions in the training patient image data are defined;
determining transformed statistical distribution data based on the training patient image data and the combined correction data, wherein the transformed statistical distribution data describes a result of transforming the statistical distributions into the reference system in which positions in the training patient image data are defined;
determining statistics assignment data based on the transformed statistical distribution data and the label data, wherein the statistics assignment data describes an assignment of the results of the statistical analysis to the labels; and
determining label relation data which describes model parameters of the learning algorithm for establishing a relation between the position of the anatomical structure in each medical image of the second plurality of patients and the position of its associated label, wherein the label relation data is determined by inputting the training patient image data and the label data and the transformed statistical distribution data into a function which establishes the relation.