公开(公告)号：US10949951B2

公开(公告)日：2021-03-16

申请号：US16110764

申请日：2018-08-23

Applicant: General Electric Company

Inventor： Jie Tang ,  Eric Gros ,  Jiang Hsieh ,  Roy Nilsen

IPC: G06T5/00 ,  G16H30/20 ,  G06N20/00 ,  G06K9/62 ,  G06T3/40

Abstract: Systems and methods for improved image denoising using a deep learning network model are disclosed. An example system includes an input data processor to process a first patient image of a first patient to add a first noise to the first patient image to form a noisy image input. The example system includes an image data denoiser to process the noisy image input using a first deep learning network to identify the first noise. The image data denoiser is to train the first deep learning network using the noisy image input. When the first deep learning network is trained to identify the first noise, the image data denoiser is to deploy the first deep learning network as a second deep learning network model to be applied to a second patient image of the first patient to identify a second noise in the second patient image.

公开(公告)号：US20200065940A1

公开(公告)日：2020-02-27

申请号：US16110764

申请日：2018-08-23

Applicant: General Electric Company

Inventor： Jie Tang ,  Eric Gros ,  Jiang Hsieh ,  Roy Nilsen

IPC: G06T5/00 ,  G06N99/00 ,  G16H30/20 ,  G06T3/40 ,  G06K9/62

Abstract: Systems and methods for improved image denoising using a deep learning network model are disclosed. An example system includes an input data processor to process a first patient image of a first patient to add a first noise to the first patient image to form a noisy image input. The example system includes an image data denoiser to process the noisy image input using a first deep learning network to identify the first noise. The image data denoiser is to train the first deep learning network using the noisy image input. When the first deep learning network is trained to identify the first noise, the image data denoiser is to deploy the first deep learning network as a second deep learning network model to be applied to a second patient image of the first patient to identify a second noise in the second patient image.