公开(公告)号：US12062153B2

公开(公告)日：2024-08-13

申请号：US17369596

申请日：2021-07-07

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Yujie Lu ,  Qiulin Tang ,  Zhou Yu ,  Jian Zhou

IPC: G06T5/20 ,  G06N3/08 ,  G06T5/50 ,  G16H30/40

CPC classification number: G06T5/20 ,  G06N3/08 ,  G06T5/50 ,  G16H30/40 ,  G06T2200/04 ,  G06T2207/10116 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30004

Abstract: An apparatus, method, and computer-readable medium for improving image quality of a medical volume. In an embodiment, the apparatus includes processing circuitry configured to receive a reconstructed input image volume from X-ray projection data corresponding to a three-dimensional region of an object to be examined, apply a pseudo-three-dimensional neural network (P3DNN) to the reconstructed input image volume, the application of the pseudo-three-dimensional neural network including generating, for the reconstructed input image volume, a plurality of three-dimensional image datasets representing a different anatomical plane of the reconstructed input image volume, applying at least one convolutional filter to each of a sagittal plane dataset, a transverse plane dataset, and a coronal plane dataset, and concatenating results of the applied at least one convolutional filter to generate an intermediate output image volume, and generate, based on the application of the P3DNN, an output image volume corresponding to the three-dimensional region of the object.

公开(公告)号：US10755395B2

公开(公告)日：2020-08-25

申请号：US14953221

申请日：2015-11-27

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Zhou Yu ,  Qiulin Tang ,  Satoru Nakanishi ,  Wenli Wang

IPC: G06K9/00 ,  G06T5/50 ,  G06K9/32 ,  G06K9/40 ,  G06K9/62 ,  G06T5/00 ,  G06T5/10 ,  G06K9/46

Abstract: An apparatus and method of denoising a dynamic image is provided. The dynamic image can represent a time-series of snapshot images. The dynamic image is transformed, using a sparsifying transformation, into an aggregate image and a series of transform-domain images. The transform-domain images represent kinetic information of the dynamic images (i.e., differences between the snapshots), and the aggregate image represents static information (i.e., features and structure common among the snapshots). The transform-domain images, which can be approximated using a sparse approximation method, are denoised. The denoised transform-domain images are recombined with the aggregate image using an inverse sparsifying transformation to generate a denoised dynamic image. The transform-domain images can be denoised using at least one of a principal component analysis method and a K-SVD method.

公开(公告)号：US20220323035A1

公开(公告)日：2022-10-13

申请号：US17229247

申请日：2021-04-13

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Qiulin Tang ,  Liang Cai ,  Zhou Yu ,  Jian Zhou

IPC: A61B6/00 ,  G06T11/00 ,  G06T7/11

Abstract: Devices, systems, and methods receive scan data that were generated by scanning a region of a subject with a computed tomography apparatus; generate multiple partial angle reconstruction(PAR) images based on the scan data; obtain corresponding characteristics of the multiple PAR images; perform correspondence mapping on the multiple PAR images based on the obtained corresponding characteristics and on the multiple PAR images, wherein the correspondence mapping generates correspondence-mapping data; and generate a motion-corrected reconstruction image based on the correspondence-mapping data and on one or both of the scan data and the PAR images.

公开(公告)号：US20220156919A1

公开(公告)日：2022-05-19

申请号：US16951931

申请日：2020-11-18

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Qiulin Tang ,  Jian Zhou ,  Zhou Yu

IPC: G06T7/00 ,  G16H50/50 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  G06N3/08 ,  G06T7/12 ,  G06T11/00 ,  A61B6/03 ,  A61B6/00

Abstract: Devices, systems, and methods for generating a medical image obtain scan data that were generated by scanning a scanned region, wherein the scan data include groups of scan data that were captured at respective angles; generate partial reconstructions of at least a part of the scanned region, wherein each partial reconstruction of the partial reconstructions is generated based on a respective one or more groups of the groups of scan data, and wherein a collective scanning range of the respective one or more groups is less than the angular scanning range; input the partial reconstructions into a machine-learning model, which generates one or more motion-compensated reconstructions of the at least part of the scanned region based on the partial reconstructions; calculate a respective edge entropy of each of the one or more motion-compensated reconstructions of the at least part of the scanned region; and adjust the machine-learning model based on the respective edge entropies.

公开(公告)号：US11816832B2

公开(公告)日：2023-11-14

申请号：US16951931

申请日：2020-11-18

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Qiulin Tang ,  Jian Zhou ,  Zhou Yu

IPC: G06T7/00 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  G06N3/08 ,  G06T7/12 ,  G06T11/00 ,  A61B6/03 ,  A61B6/00 ,  G16H50/50

CPC classification number: G06T7/0012 ,  A61B6/032 ,  A61B6/504 ,  A61B6/5264 ,  G06N3/08 ,  G06T7/12 ,  G06T11/005 ,  G16H30/40 ,  G16H50/20 ,  G16H50/50 ,  G16H50/70 ,  G06T2207/10081 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30101 ,  G06T2211/436

Abstract: Devices, systems, and methods obtain scan data that were generated by scanning a scanned region, wherein the scan data include groups of scan data that were captured at respective angles; generate partial reconstructions of at least a part of the scanned region, wherein each partial reconstruction of the partial reconstructions is generated based on a respective one or more groups of the groups of scan data, and wherein a collective scanning range of the respective one or more groups is less than the angular scanning range; input the partial reconstructions into a machine-learning model, which generates one or more motion-compensated reconstructions of the at least part of the scanned region based on the partial reconstructions; calculate a respective edge entropy of each of the one or more motion-compensated reconstructions of the at least part of the scanned region; and adjust the machine-learning model based on the respective edge entropies.

公开(公告)号：US20190164317A1

公开(公告)日：2019-05-30

申请号：US16206892

申请日：2018-11-30

Applicant: CANON MEDICAL SYSTEMS CORPORATION ,  THE UNIVERSITY OF CENTRAL FLORIDA RESEARCH FOUNDATION, Inc.

Inventor： Qiulin Tang ,  Alexander Katsevich ,  Zhou Yu ,  Wenli Wang

IPC: G06T11/00 ,  G06T5/00 ,  G06T5/20 ,  A61B6/03 ,  A61B6/00

Abstract: An apparatus and method are provided for computed tomography (CT) imaging to reduce truncation artifacts due to a part of an imaged object being outside the scanner field of view (FOV) for at least some views of a CT scan. After initial determining extrapolation widths to extend the projection data to fill a truncation region, the extrapolation widths are combined into a padding map and smoothed to improve uniformity and remove jagged edges. Then a hybrid material model fits the measured projection data nearest the truncation region to extrapolate projection data filling the truncation region. Smoothing the padding map is improved by the insight that in general smaller extrapolation widths are more accurate and trustworthy. Further, practical applications often include multiple inhomogeneous materials. Thus, the hybrid material model provides a better approximation than single material models, and more accurate fitting is achieved.

公开(公告)号：US12138090B2

公开(公告)日：2024-11-12

申请号：US17875051

申请日：2022-07-27

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Chih-chieh Liu ,  Jian Zhou ,  Qiulin Tang ,  Liang Cai ,  Zhou Yu

IPC: A61B6/03 ,  A61B6/00 ,  A61B6/50 ,  G01N23/046

Abstract: An information processing method controls a CT scanner such that the method includes, but is not limited to, determining an X-ray irradiation period from an electrocardiogram acquired from an electrocardiography device attached to a living object to be imaged, by processing the electrocardiogram at multiple different cardiac phases; performing, by controlling a CT gantry including and rotatably supporting an X-ray source and an X-ray detector, a diagnostic CT scan in the determined X-ray irradiation period, of at least a part of the heart region, to obtain a CT image; and causing a display unit to display the obtained CT image. The method can be performed at least by an information processing apparatus including processing circuitry and/or computer instructions stored in a non-transitory computer readable storage medium for performing the method.

公开(公告)号：US12067651B2

公开(公告)日：2024-08-20

申请号：US17462391

申请日：2021-08-31

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Qiulin Tang ,  Ruoqiao Zhang ,  Jian Zhou ,  Zhou Yu

IPC: G06T11/00 ,  G06N3/08 ,  G06T7/00

CPC classification number: G06T11/003 ,  G06N3/08 ,  G06T7/0012 ,  G06T2207/20081 ,  G06T2207/20084

Abstract: Data acquired from a scan of an object can be decomposed into frequency components. The frequency components can be input into a trained model to obtain processed frequency components. These processed frequency components can be composed and used to generate a final image. The trained model can be trained, independently or dependently, using frequency components covering the same frequencies as the to-be-processed frequency components. In addition, organ specific processing can be enabled by training the trained model using image and/or projection datasets of the specific organ.

公开(公告)号：US11026642B2

公开(公告)日：2021-06-08

申请号：US16370230

申请日：2019-03-29

Applicant: Canon Medical Systems Corporation

Inventor： Qiulin Tang ,  Jian Zhou ,  Zhou Yu

IPC: A61B6/03 ,  A61B6/00 ,  G06N3/08 ,  G16H50/50 ,  G16H50/20 ,  G06N3/04 ,  G06T11/00

Abstract: A method and apparatuses are provided that use a neural network to correct artifacts in computed tomography (CT) images, especially cone-beam CT (CBCT) artifacts. The neural network is trained using a training dataset of artifact-minimized images paired with respective artifact-exhibiting images. In some embodiments, the artifact-minimized images are acquired using a small cone angle for the X-ray beam, and the artifact-exhibiting images are acquired either by forwarding projecting the artifact-minimized images using a large-cone-angle CBCT configuration or by performing a CBCT scan. In some embodiments, the network is a 2D convolutional neural network, and an artifact-exhibiting image is applied to the neural network as 2D slices taken for the coronal and/or sagittal views. Then the 2D image results from the neural network are reassembled as a 3D imaging having reduced imaging artifacts.

公开(公告)号：US11712215B2

公开(公告)日：2023-08-01

申请号：US17229247

申请日：2021-04-13

Applicant: CANON MEDICAL SYSTEMS CORPORATION

Inventor： Qiulin Tang ,  Liang Cai ,  Zhou Yu ,  Jian Zhou

IPC: A61B6/00 ,  A61B6/03 ,  G06T11/00 ,  G06T7/11

CPC classification number: A61B6/5264 ,  A61B6/032 ,  A61B6/5205 ,  G06T7/11 ,  G06T11/005 ,  G06T11/006 ,  G06T2211/436

Abstract: Devices, systems, and methods receive scan data that were generated by scanning a region of a subject with a computed tomography apparatus; generate multiple partial angle reconstruction (PAR) images based on the scan data; obtain corresponding characteristics of the multiple PAR images; perform correspondence mapping on the multiple PAR images based on the obtained corresponding characteristics and on the multiple PAR images, wherein the correspondence mapping generates correspondence-mapping data; and generate a motion-corrected reconstruction image based on the correspondence-mapping data and on one or both of the scan data and the PAR images.