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公开(公告)号：US12243127B2
公开(公告)日：2025-03-04
申请号：US17699008
申请日：2022-03-18
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Tzu-Cheng Lee , Jian Zhou , Liang Cai , Zhou Yu , Masakazu Matsuura , Takuya Nemoto , Hiroki Taguchi
Abstract: A medical image processing method includes obtaining a first set of projection data by performing, with a first CT apparatus including a first detector with a first pixel size, a first CT scan of an object in a first imaging region of the first detector; obtaining a first CT image with a first resolution by reconstructing the first set of projection data; obtaining a processed CT image with a resolution higher than the first resolution by applying a machine-learning model for resolution enhancement to the first CT image; and displaying the processed CT image or outputting the processed CT image for analysis. The machine-learning model is obtained by training using a second CT image based on a second set of projection data acquired by a second CT scan of the object in a second imaging region with a second CT apparatus including a second detector with a second pixel size.
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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
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.
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公开(公告)号：US11547378B2
公开(公告)日：2023-01-10
申请号：US16509369
申请日：2019-07-11
Applicant: Canon Medical Systems Corporation
Inventor： Ilmar Hein , Zhou Yu , Tzu-Cheng Lee
Abstract: A method and apparatus is provided that uses a deep learning (DL) network together with a multi-resolution detector to perform X-ray projection imaging to provide improved resolution similar to a single-resolution detector but at lower cost and less demand on the communication bandwidth between the rotating and stationary parts of an X-ray gantry. The DL network is trained using a training dataset that includes input data and target data. The input data includes projection data acquired using a multi-resolution detector, and the target data includes projection data acquired using a single-resolution, high-resolution detector. Thus, the DL network is trained to improve the resolution of projection data acquired using a multi-resolution detector. Further, the DL network is can be trained to additional correct other aspects of the projection data (e.g., noise and artifacts).
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公开(公告)号：US20220327750A1
公开(公告)日：2022-10-13
申请号：US17699008
申请日：2022-03-18
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Tzu-Cheng Lee , Jian Zhou , Liang Cai , Zhou Yu , Masakazu Matsuura , Takuya Nemoto , Hiroki Taguchi
Abstract: A medical image processing method includes obtaining a first set of projection data by performing, with a first CT apparatus including a first detector with a first pixel size, a first CT scan of an object in a first imaging region of the first detector; obtaining a first CT image with a first resolution by reconstructing the first set of projection data; obtaining a processed CT image with a resolution higher than the first resolution by applying a machine-learning model for resolution enhancement to the first CT image; and displaying the processed CT image or outputting the processed CT image for analysis. The machine-learning model is obtained by training using a second CT image based on a second set of projection data acquired by a second CT scan of the object in a second imaging region with a second CT apparatus including a second detector with a second pixel size.
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5.发明申请公开(公告)号：US20220031274A1
公开(公告)日：2022-02-03
申请号：US16941760
申请日：2020-07-29
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Masakazu MATSUURA , Jian Zhou , Zhou Yu
Abstract: An information processing method of an embodiment is a processing method of information acquired by imaging performed by a medical image diagnostic apparatus, the information processing method includes the steps of: on the basis of first subject data acquired by the imaging performed by the medical image diagnostic apparatus, acquiring noise data in the first subject data; on the basis of second subject data acquired by the imaging performed by a medical image diagnostic modality same kind as the medical image diagnostic apparatus and the noise data, acquiring synthesized subject data in which noises based on the noise data are added to the second subject data; and acquiring a noise reduction processing model by machine learning using the synthesized subject data and third subject data acquired by the imaging performed by the medical image diagnostic modality.
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Patent Agency Ranking
公开(公告)号：US20210312612A1
公开(公告)日：2021-10-07
申请号：US16839733
申请日：2020-04-03
Inventor： Dimple MODGIL , Patrick La Riviere , Yan Liu , Zhou Yu
Abstract: A method and apparatus uses multi-material decomposition of three or more material components to generate material-component images from spectral images reconstructed from spectral computed tomography data. In three-component material decomposition e.g., the Mendonça method is used for multi-material decomposition when the attenuation values satisfy an assumed volume fraction condition (i.e., for a given voxel, the attenuation values are within a triangle having vertices given by unit volume fractions of three respective material components). However, when the volume fraction condition fails (e.g., the attenuation values are outside the triangle), either a shortest-Hausdorff-distance method or a closest-edge method is used for multi-material decomposition. For example, the attenuation values of the voxel are projected onto a lower-dimensional space (e.g., the space of a closest edge) and decomposed into a pair/single material component(s) of the lower-dimensional space.
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公开(公告)号：US10945695B2
公开(公告)日：2021-03-16
申请号：US16231189
申请日：2018-12-21
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Abstract: A deep learning (DL) network reduces artifacts in computed tomography (CT) images based on complementary sparse-view projection data generated from a sparse kilo-voltage peak (kVp)-switching CT scan. The DL network is trained using input images exhibiting artifacts and target images exhibiting little to no artifacts. Another DL network can be trained to perform image-domain material decomposition of the artifact-mitigated images by being trained using target images in which beam hardening is corrected and spatial variations in the X-ray beam are accounted for. Further, material decomposition and artifact mitigation can be integrated in a single DL network that is trained using as inputs reconstructed images having artifacts and as targets material images without artifacts with beam-hardening corrections, etc. Further, the target material images can be transformed using a whitening transform to decorrelate noise.
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8.发明授权公开(公告)号：US10825210B2
公开(公告)日：2020-11-03
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
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.
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9.发明申请公开(公告)号：US20190328341A1
公开(公告)日：2019-10-31
申请号：US16412290
申请日：2019-05-14
Applicant: University of Central Florida Research Foundation, Inc. , iTomography Corporation , Canon Medical Systems Corporation
Inventor： Alexander Katsevich , Michael Frenkel , Victor Prieto , Zhou Yu
Abstract: An improved system and method for estimating and compensating for motion by reducing motion artifacts produced during image reconstruction from helical computed tomography (CT) scan data. In a particular embodiment, the reconstruction may be based on helical partial angle reconstruction (PAR) and the registration may be performed utilizing one or more artificial intelligence (AI) based methods.
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公开(公告)号：US12299841B2
公开(公告)日：2025-05-13
申请号：US17705030
申请日：2022-03-25
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Masakazu Matsuura , Takuya Nemoto , Hiroki Taguchi , Tzu-Cheng Lee , Jian Zhou , Liang Cai , Zhou Yu
IPC: G06T3/4053 , G06T3/4046 , G06T5/50 , G06T5/70
Abstract: A medical data processing method according to an embodiment includes inputting first medical data relating to a subject imaged with a medical image capture apparatus to a learned model to configured to generate second medical data having lower noise than that of the first medical data and having a super resolution compared with the first medical data based on the first medical data to output the second medical data.
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