The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 24, 2021
Filed:
Mar. 05, 2018
Koninklijke Philips N.v., Eindhoven, NL;
Frank Michael Weber, Hamburg, DE;
Irina Waechter-Stehle, Hamburg, DE;
Christian Buerger, Hamburg, DE;
KONINKLIJKE PHILIPS N.V., Eindhoven, NL;
Abstract
The application discloses a computer-implemented method () of providing a model for estimating an anatomical body measurement value from at least one 2-D ultrasound image including a contour of the anatomical body, the method comprising providing () a set of 3-D ultrasound images of the anatomical body; and, for each of said 3-D images, determining () a ground truth value of the anatomical body measurement; generating () a set of 2-D ultrasound image planes each including a contour of the anatomical body, and for each of the 2-D ultrasound image planes, extrapolating () a value of the anatomical body measurement from at least one of an outline contour measurement and a cross-sectional measurement of the anatomical body in the 2-D ultrasound image plane; and generating () said model by training a machine-learning algorithm to generate an estimator function of the anatomical body measurement value from at least one of a determined outline contour measurement and a determined cross-sectional measurement of a contour of the anatomical body within a 2-D ultrasound image using the obtained ground truth values, extrapolated values and at least one of the outline contour measurements and the cross-sectional measurements as inputs of said machine-learning algorithm. A computer-implemented method of deploying such a model, a computer program product, an ultrasound image processing apparatus and an ultrasound imaging system adapted to implement such methods are also disclosed.