US 12,482,074 B2
Systems and methods for training a machine-learning algorithm and application of a machine-learning model for denoising images
Hideki Sasaki, Wetzlar (DE); Chi-Chou Huang, Wetzlar (DE); and Shih-Jong James Lee, Wetzlar (DE)
Assigned to LEICA MICROSYSTEMS CMS GMBH, Wetzlar (DE)
Filed by LEICA MICROSYSTEMS CMS GMBH, Wetzlar (DE)
Filed on Dec. 21, 2023, as Appl. No. 18/391,713.
Claims priority of application No. 102022134730.3 (DE), filed on Dec. 23, 2022.
Prior Publication US 2024/0212109 A1, Jun. 27, 2024
Int. Cl. G06T 5/70 (2024.01)
CPC G06T 5/70 (2024.01) [G06T 2207/20081 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A system comprising one or more processors and one or more storage devices for training a machine-learning algorithm for denoising images, the system configured to:
receive training data, the training data comprising multiple image sets obtained from one or more series of consecutive images, wherein each image set comprises a plurality of images obtained from a same series of the one or more series of consecutive images, wherein the plurality of images of each image set comprise an initial image, a middle image and a last image;
adjust weights of the machine-learning algorithm to obtain a trained machine-learning model, based on an output image of the machine-learning algorithm and a target image, wherein the output image of the machine-learning algorithm is obtained by using the initial image and the last image as input images, and wherein the target image is obtained from the middle image by applying a random shift to the middle image; and
provide the trained machine-learning model.