公开(公告)号：US12156752B2

公开(公告)日：2024-12-03

申请号：US17444881

申请日：2021-08-11

Applicant: GE Precision Healthcare LLC

Inventor： Rajesh Langoju ,  Utkarsh Agrawal ,  Risa Shigemasa ,  Bipul Das ,  Yasuhiro Imai ,  Jiang Hsieh

IPC: A61B6/02 ,  G06N3/04 ,  G06N3/08 ,  G06T3/4076 ,  G06T11/00 ,  G06T15/08

Abstract: Various methods and systems are provided for computed tomography imaging. In one embodiment, a method includes acquiring, with an x-ray detector and an x-ray source coupled to a gantry, a three-dimensional image volume of a subject while the subject moves through a bore of the gantry and the gantry rotates the x-ray detector and the x-ray source around the subject, inputting the three-dimensional image volume to a trained deep neural network to generate a corrected three-dimensional image volume with a reduction in aliasing artifacts present in the three-dimensional image volume, and outputting the corrected three-dimensional image volume. In this way, aliasing artifacts caused by sub-sampling may be removed from computed tomography images while preserving details, texture, and sharpness in the computed tomography images.

公开(公告)号：US20230177747A1

公开(公告)日：2023-06-08

申请号：US17543234

申请日：2021-12-06

Applicant: GE Precision Healthcare LLC

Inventor： Rajesh Veera Venkata Lakshmi Langoju ,  Utkarsh Agrawal ,  Bipul Das ,  Risa Shigemasa ,  Yasuhiro Imai ,  Jiang Hsieh

IPC: G06T11/00 ,  G06T5/00 ,  G06T5/50 ,  G06N20/20

CPC classification number: G06T11/008 ,  G06N20/20 ,  G06T5/002 ,  G06T5/50

Abstract: Systems/techniques that facilitate machine learning generation of low-noise and high structural conspicuity images are provided. In various embodiments, a system can access an image and can apply at least one of image denoising or image resolution enhancement to the image, thereby yielding a first intermediary image. In various instances, the system can generate, via execution of a plurality of machine learning models, a plurality of second intermediary images based on the first intermediary image, wherein a given machine learning model in the plurality of machine learning models receives as input the first intermediary image, wherein the given machine learning model produces as output a given second intermediary image in the plurality of second intermediary images, and wherein the given second intermediary image represents a kernel-transformed version of the first intermediary image. In various cases, the system can generate a blended image based on the plurality of second intermediary images.

公开(公告)号：US20230290022A1

公开(公告)日：2023-09-14

申请号：US18182911

申请日：2023-03-13

Applicant: GE Precision Healthcare LLC

Inventor： Yasuhiro Imai ,  Yuri Teraoka ,  Ayako Matsumi ,  Miyo Hattori

IPC: G06T11/00

CPC classification number: G06T11/008 ,  G06T2210/41

Abstract: A computed tomography (CT) system with one or a plurality of processors to perform operations. The operations include reconstructing a series of virtual monochromatic X-ray images of the first energy and a series of virtual monochromatic X-ray images of the second energy based on data collected from an imaging subject, inputting the input image generated based on the reconstructed virtual monochromatic X-ray images of the second energy to the trained model and using the trained model to infer a series of virtual monochromatic X-ray image of the first energy, and generating a corrected series of virtual monochromatic X-ray images of the first energy based on the first reconstructed series of virtual monochromatic X-ray images of the first energy and the inferred series of virtual monochromatic X-ray images of the first energy.

公开(公告)号：US20230263485A1

公开(公告)日：2023-08-24

申请号：US18308369

申请日：2023-04-27

Applicant: GE Precision Healthcare LLC

Inventor： Yasuhiro Imai ,  Yoshihiro Oda ,  Ayako Matsumi

IPC: A61B6/04 ,  A61B6/03

CPC classification number: A61B6/0492 ,  A61B6/032 ,  A61B6/0407

Abstract: The present disclosure relates to a system and method with which an imaged range in the past can be reproduced with high precision. In accordance with certain embodiments, an X-ray CT apparatus includes a camera-image producing section for producing a first camera image of a patient, a landmark fixing section for fixing a landmark with reference to a chest of the patient, and an imaged-range defining section for defining a first imaged range in a first scan based on landmark data representing the landmark. The camera-image producing section acquires a second camera image of the patient in a follow-up examination, the landmark fixing section fixes a second landmark with reference to the chest of the patient contained in the second image, and the imaged-range defining section defines second imaged range in a second scan based on landmark data representing the landmarks, and imaged-range data representing the first imaged range.

公开(公告)号：US20230048231A1

公开(公告)日：2023-02-16

申请号：US17444881

申请日：2021-08-11

Applicant: GE Precision Healthcare LLC

Inventor： Rajesh Langoju ,  Utkarsh Agrawal ,  Risa Shigemasa ,  Bipul Das ,  Yasuhiro Imai ,  Jiang Hsieh

IPC: G06T11/00 ,  G06T15/08 ,  G06T3/40 ,  G06N3/08 ,  G06N3/04

Abstract: Various methods and systems are provided for computed tomography imaging. In one embodiment, a method includes acquiring, with an x-ray detector and an x-ray source coupled to a gantry, a three-dimensional image volume of a subject while the subject moves through a bore of the gantry and the gantry rotates the x-ray detector and the x-ray source around the subject, inputting the three-dimensional image volume to a trained deep neural network to generate a corrected three-dimensional image volume with a reduction in aliasing artifacts present in the three-dimensional image volume, and outputting the corrected three-dimensional image volume. In this way, aliasing artifacts caused by sub-sampling may be removed from computed tomography images while preserving details, texture, and sharpness in the computed tomography images.