公开(公告)号：US20240062047A1

公开(公告)日：2024-02-22

申请号：US17891702

申请日：2022-08-19

Applicant: Shanghai United Imaging Intelligence Co., Ltd.

Inventor： Zhang Chen ,  Siyuan Dong ,  Shanhui Sun ,  Xiao Chen ,  Yikang Liu ,  Terrence Chen

IPC: G06N3/04

CPC classification number: G06N3/0472 ,  G06N3/0454 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Deep learning-based systems, methods, and instrumentalities are described herein for MRI reconstruction and/or refinement. An MRI image may be reconstructed based on under-sampled MRI information and a generative model may be trained to refine the reconstructed image, for example, by increasing the sharpness of the MRI image without introducing artifacts into the image. The generative model may be implemented using various types of artificial neural networks including a generative adversarial network. The model may be trained based on an adversarial loss and a pixel-wise image loss, and once trained, the model may be used to improve the quality of a wide range of 2D or 3D MRI images including those of a knee, brain, or heart.

公开(公告)号：US20240062438A1

公开(公告)日：2024-02-22

申请号：US17891668

申请日：2022-08-19

Applicant: Shanghai United Imaging Intelligence Co., Ltd.

Inventor： Zhang Chen ,  Siyuan Dong ,  Shanhui Sun ,  Xiao Chen ,  Yikang Liu ,  Terrence Chen

IPC: G06T11/00 ,  G06T5/20 ,  G06T5/00 ,  G06T5/10 ,  G06T7/00

CPC classification number: G06T11/008 ,  G06T5/20 ,  G06T5/003 ,  G06T5/002 ,  G06T5/10 ,  G06T7/0014 ,  G06T2207/20084 ,  G06T2207/10088 ,  G06T2207/20081 ,  G06T2207/30008

Abstract: Described herein are systems, methods, and instrumentalities associated with using an invertible neural network to complete various medical imaging tasks. Unlike traditional neural networks that may learn to map input data (e.g., a blurry reconstructed MRI image) to ground truth (e.g., a fully-sampled MRI image), the invertible neural network may be trained to learn a mapping from the ground truth to the input data, and may subsequently apply an inverse of the mapping (e.g., at an inference time) to complete a medical imaging task. The medical imaging task may include, for example, MRI image reconstruction (e.g., to increase the sharpness of a reconstructed MRI image), image denoising, image super-resolution, and/or the like.