US 11,837,352 B2
Body representations
Birgi Tamersoy, Erlangen (DE); Ankur Kapoor, Plainsboro, NJ (US); Vivek Singh, Princeton, NJ (US); and Brian Teixeira, Lawrence Township, NJ (US)
Assigned to Siemens Healthcare GmbH, Erlangen (DE)
Filed by Siemens Healthcare GmbH, Erlangen (DE)
Filed on Apr. 15, 2021, as Appl. No. 17/231,041.
Claims priority of application No. 20174249 (EP), filed on May 12, 2020.
Prior Publication US 2021/0358595 A1, Nov. 18, 2021
Int. Cl. G16H 30/20 (2018.01); G06N 20/00 (2019.01)
CPC G16H 30/20 (2018.01) [G06N 20/00 (2019.01)] 19 Claims
OG exemplary drawing
 
1. A computer-implemented method for training a machine learning system for representing a patient body, the computer-implemented method comprising:
obtaining a plurality of stored medical imaging data sets each representing at least a part of a respective patient, wherein a first one of the plurality of stored medical imaging data sets represents a different part of the patient body than a second one of the plurality of stored medical imaging data sets;
estimating a plurality of landmarks in the stored medical imaging data sets;
aligning each of the stored medical imaging data set to a predefined pose using the plurality of landmarks, the aligning resulting in a plurality of aligned medical imaging data sets;
sampling a plurality of points in the aligned medical imaging data sets;
machine training the machine learning system based on at least the plurality of points to configure parameters of the machine learning system; and
storing at least the configured parameters of the machine learning system.