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1.发明公开公开(公告)号：US20230404514A1
公开(公告)日：2023-12-21
申请号：US18332006
申请日：2023-06-09
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Masakazu MATSUURA , Takuya NEMOTO , Hiroki TAGUCHI , Yuto HAMADA , Yohei MINATOYA
IPC: A61B6/00 , G16H30/40 , G06N3/0464 , G06N3/08
CPC classification number: A61B6/5258 , A61B6/405 , A61B6/482 , A61B6/5205 , G16H30/40 , G06N3/0464 , G06N3/08
Abstract: A medical data processing method according to an embodiment includes: outputting second spectral data by inputting first spectral data related to an examined subject imaged by a spectral medical imaging apparatus to a trained model configured to generate, on the basis of the first spectral data, the second spectral data having less noise than the first spectral data and a higher resolution than the first spectral data. The first spectral data in the medical data processing method according to the embodiment corresponds to medical data obtained by performing a spectral scan on the examined subject. The trained model in the medical data processing method according to the embodiment is configured to perform a noise reducing process and a super-resolution process on the first spectral data.
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2.发明申请公开(公告)号：US20220139006A1
公开(公告)日：2022-05-05
申请号：US17577689
申请日：2022-01-18
Applicant: CANON MEDICAL SYSTEMS CORPORATION
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: acquiring noise data by imaging a phantom using a medical imaging apparatus; based on first subject projection data acquired by the imaging performed by a medical image diagnostic modality of a same kind as the medical image diagnostic apparatus and the noise data, acquiring synthesized subject data in which noise based on the noise data is added to the first subject projection data; and acquiring a noise reduction processing model by machine learning using the synthesized subject data and second subject projection data acquired by the imaging performed by the medical image diagnostic modality.
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公开(公告)号：US20230145523A1
公开(公告)日：2023-05-11
申请号：US17680048
申请日：2022-02-24
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Masakazu MATSUURA , Jian ZHOU , Zhou YU
CPC classification number: G06T11/008 , G06T7/30 , A61B6/5258 , A61B6/032 , G06T2207/10081 , G06T2207/20081 , G06T2207/10116 , A61B6/563
Abstract: A medical image processing apparatus according to an embodiment includes processing circuitry configured to acquire a radiographic image of a subject and acquire a post-processing image with reduced steak artifacts by applying a model that reduces streak artifacts to the radiographic image, wherein the model is generated by machine learning that uses, as a training data pair, a first radiographic image and a second radiographic image based on artifact generation processing for generating streak artifacts.
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Patent Agency Ranking
公开(公告)号：US20200311878A1
公开(公告)日：2020-10-01
申请号：US16372174
申请日：2019-04-01
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Masakazu MATSUURA , Jian Zhou , Zhou Yu
Abstract: A method and apparatus is provided to perform medical imaging in which feature-aware reconstruction is performed using a neural network. The neural network is trained to perform feature-aware reconstruction by using a training dataset in which the target data has a spatially-dependent degree of denoising and artifact reduction based on the features represented in the image. For example, a target image can be generated by reconstructing multiple images, each using a respective regularization parameter that is optimized for a different anatomy/organ (e.g., abdomen, lung, bone, etc.). And a target image can be generated using artifact reduction method (e.g. metal artifact reduction, aliasing artifact reduction, etc.). Then respective regions/features (e.g., abdomen, lung, and bone, artifact free, regions/features) can be extracted from the corresponding images and combined into a single combined image, which is used as the target data to train the neural network.
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公开(公告)号：US20240423560A1
公开(公告)日：2024-12-26
申请号：US18748716
申请日：2024-06-20
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Hiroaki KIJI , Hiroki TAGUCHI , Yohei MINATOYA , Masakazu MATSUURA
Abstract: A photon counting CT apparatus of an embodiment includes processing circuitry. The processing circuitry is configured to perform first determination processing of determining spike components in a counting image generated on the basis of sum data of photon detection results for a plurality of different X-ray energy bands and second determination processing of determining ring artifacts on the basis of a plurality of energy images generated on the basis of a photon detection result for each of the plurality of different X-ray energy bands, and remove or reduce ring artifacts in the counting image on the basis of both a result of the first determination processing and a result of the second determination processing.
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6.发明公开公开(公告)号：US20240169531A1
公开(公告)日：2024-05-23
申请号：US18507148
申请日：2023-11-13
Applicant: CANON MEDICAL SYSTEMS CORPORATION
Inventor： Masakazu MATSUURA
CPC classification number: G06T7/0012 , G06T5/002 , G06T11/008 , G06T2207/10081
Abstract: A medical image processing apparatus according to one embodiment includes processing circuitry. The processing circuitry acquires second image data in which a low count artifact is reduced, by applying a trained machine learning model to first image data that is obtained by X-ray CT scan. The processing circuitry outputs image data based on the second image data. The machine learning model is trained by using training data that includes third image data and fourth image data, where the third image data is reconstructed based on projection data that is obtained by X-ray CT scan and the fourth image data is based on the projection data and includes a generated low count artifact.
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公开(公告)号：US20220327662A1
公开(公告)日：2022-10-13
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
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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8.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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