	US 12,106,469 B2
	Image quality assessment for refinement of imaging rendering parameters for rendering medical images
Sandra Sudarsky, Bedminster, NJ (US); Kaloian Petkov, Lawrenceville, NJ (US); and Daphne Yu, Yardley, PA (US)
Assigned to Siemens Healthineers AG, Forchheim (DE)
Filed by SIEMENS HEALTHINEERS AG, Forchheim (DE)
Filed on Mar. 4, 2022, as Appl. No. 17/653,516.
Prior Publication US 2023/0281789 A1, Sep. 7, 2023
Int. Cl. G06T 7/00 (2017.01); G06F 18/214 (2023.01); G06T 1/60 (2006.01); G06T 5/50 (2006.01); G06T 7/50 (2017.01)

CPC G06T 7/001 (2013.01) [G06F 18/214 (2023.01); G06T 1/60 (2013.01); G06T 5/50 (2013.01); G06T 7/50 (2017.01); G06T 2207/20081 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30168 (2013.01)]

17 Claims

1. A computer-implemented method, comprising:

receiving a rendered medical image and an input depth map of the rendered medical image;

generating an estimated depth map from the rendered medical image;

comparing the input depth map with the estimated depth map;

extracting one or more measures of interest from the rendered medical image;

determining an image quality assessment of the rendered medical image using a machine learning based image quality assessment network based on the one or more measures of interest and results of the comparison; and

outputting the image quality assessment of the rendered medical image.