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.

Date of Patent:
Apr. 30, 2024

Filed:

Apr. 18, 2019
Applicant:

Koninklijke Philips N.v., Eindhoven, NL;

Inventors:

Sascha Krueger, Hamburg, DE;

Julien Senegas, Hamburg, DE;

Peter Koken, Hamburg, DE;

Assignee:

Koninklijke Philips N.V., Eindhoven, NL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 30/20 (2018.01); G06T 7/00 (2017.01); G06T 7/73 (2017.01); G16H 30/40 (2018.01);
U.S. Cl.
CPC ...
G16H 30/20 (2018.01); G06T 7/0014 (2013.01); G06T 7/75 (2017.01); G16H 30/40 (2018.01);
Abstract

The invention provides for a medical instrument () that comprises a medical imaging system (′), a subject support (), and a camera system () configured for imaging the subject support in an initial position. The execution the machine executable instructions causes a processor () to: place () the subject support in the initial position (); control () the camera system to acquire a series of repeated images (); detect () the placement of one or more background objects (); detect () one or more foreground objects (); construct () a background object surface image () at least partially by stitching together the series of repeated images to replace image regions containing background objects obscured by the one or more foreground objects; determine () a three-dimensional object surface () using the background object surface image; detect () the subject in one of the series of repeated images (); calculate () a subject segmentation () of the subject in the one of the series of repeated images; determine () a visible subject surface () using the subject segmentation and the one of the series of repeated images; and calculate () a three-dimensional subject model () by estimating a volume () defined by the three-dimensional object surface and the visible subject surface.


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