US 11,941,786 B2
Image noise reduction method and device
Jialiang Ren, Beijing (CN); Zhoushe Zhao, Beijing (CN); and Chen Zhang, Guangzhou (CN)
Assigned to GE Precision Healthcare LLC, Wauwatosa, WI (US)
Filed by GE Precision Healthcare LLC, Wauwatosa, WI (US)
Filed on Jun. 9, 2021, as Appl. No. 17/343,585.
Claims priority of application No. 202010531261.1 (CN), filed on Jun. 11, 2020.
Prior Publication US 2021/0390668 A1, Dec. 16, 2021
Int. Cl. G06K 9/00 (2022.01); G06T 5/00 (2006.01); G06T 5/50 (2006.01)
CPC G06T 5/002 (2013.01) [G06T 5/50 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/20221 (2013.01)] 18 Claims
OG exemplary drawing
 
1. An image noise reduction method, comprising:
processing, based on a first deep learning network, an original scanned object image to acquire a noise image corresponding to the original scanned object image; and
acquiring a denoised image based on the original scanned object image and the noise image;
wherein the first deep learning network is obtained by training based on low signal-to-noise ratio images and high signal-to-noise ratio images, wherein the low signal-to-noise ration images are an original sample image set;
wherein the original sample image set comprises a plurality of blocks in the low signal-to-noise ratio images and at least one transformed block obtained after transformation processing is performed on the respective block, wherein the transformation processing comprises at least one of rotation of at least one angle and mirror flip.