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公开(公告)号：US11842556B2
公开(公告)日：2023-12-12
申请号：US17352488
申请日：2021-06-21
Applicant: SYSMEX CORPORATION
Inventor： Yosuke Sekiguchi , Kazumi Hakamada , Yuki Aihara , Kohei Yamada , Kanako Masumoto , Krupali Jain
CPC classification number: G06V20/698 , G06T7/0014 , G06T7/74 , G06T7/90 , G06V10/44 , G06V10/56 , G06T2207/20084 , G06T2207/30024
Abstract: The present invention provides an image analysis method for generating data indicating a region of a cell nucleus in an image of a tissue or a cell. The image analysis method is a method for analyzing an image of a tissue or a cell using a deep learning algorithm of a neural network structure, and generates data indicating a region of a cell nucleus in an analysis target image by the deep learning algorithm by generating analysis data from the analysis target image including an analysis target tissue or cell, and inputting the analysis data in the deep learning algorithm.
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2.发明申请公开(公告)号：US20190266486A1
公开(公告)日：2019-08-29
申请号：US16284451
申请日：2019-02-25
Applicant: Sysmex Corporation
Inventor： Kohei Yamada , Kazumi Hakamada , Yuki Aihara , Kanako Masumoto , Yosuke Sekiguchi , Krupali Jain
Abstract: An image analysis method for analyzing an image of a tissue collected from a subject using a deep learning algorithm of a neural network structure. The image analysis method includes generating analysis data from the analysis target image that includes the tissue to be analyzed, inputting the analysis data to a deep learning algorithm, and generating data indicating a layer structure configuring a tissue in the analysis target image by the deep learning algorithm.
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公开(公告)号：US11436718B2
公开(公告)日：2022-09-06
申请号：US16192850
申请日：2018-11-16
Applicant: National Cancer Center , SYSMEX CORPORATION
Inventor： Hiroshi Yoshida , Yosuke Sekiguchi , Kazumi Hakamada , Yuki Aihara , Kohei Yamada , Kanako Masumoto , Krupali Jain
Abstract: An image analysis method for generating data indicating a tumorigenic state of an image of a tissue or a cell. The image analysis method is an image analysis method for analyzing an image of a tissue or a cell using a deep learning algorithm of a neural network structure, analysis data are generated from the analysis target image including a tissue or cell to be analyzed, the analysis data are input to the deep learning algorithm, and data indicating the tumorigenic state of tissues or cells in the analysis target image are generated by the depth learning algorithm.
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公开(公告)号：US20190156481A1
公开(公告)日：2019-05-23
申请号：US16193422
申请日：2018-11-16
Applicant: Sysmex Corporation
Inventor： Yosuke Sekiguchi , Kazumi Hakamada , Yuki Aihara , Kohei Yamada , Kanako Masumoto , Krupali Jain
Abstract: The present invention provides an image analysis method for generating data indicating a region of a cell nucleus in an image of a tissue or a cell. The image analysis method is a method for analyzing an image of a tissue or a cell using a deep learning algorithm of a neural network structure, and generates data indicating a region of a cell nucleus in an analysis target image by the deep learning algorithm by generating analysis data from the analysis target image including an analysis target tissue or cell, and inputting the analysis data in the deep learning algorithm.
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公开(公告)号：US10184109B2
公开(公告)日：2019-01-22
申请号：US14673199
申请日：2015-03-30
Applicant: SYSMEX CORPORATION
Inventor： Eiji Kobayashi , Toshiyuki Sato , Kenji Akama , Nobuyasu Hori , Masaki Shibayama , Yuki Aihara , Masakazu Kadowaki
Abstract: Disclosed is a method for obtaining differentiated cells and/or differentiated cell products, including the steps of: introducing undifferentiated cells into a perfused organ or living tissue; subjecting the undifferentiated cells introduced to perfusion culture together with the organ or living tissue so as to allow the undifferentiated cells to differentiate, thereby obtaining differentiated cells and/or differentiated cell products; collecting a perfusion culture solution that contains the resulting differentiated cells and/or differentiated cell products; and obtaining the differentiated cells and/or differentiated cell products contained in the collected perfusion culture solution.
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Patent Agency Ranking
公开(公告)号：US11276000B2
公开(公告)日：2022-03-15
申请号：US16284451
申请日：2019-02-25
Applicant: Sysmex Corporation
Inventor： Kohei Yamada , Kazumi Hakamada , Yuki Aihara , Kanako Masumoto , Yosuke Sekiguchi , Krupali Jain
Abstract: An image analysis method for analyzing an image of a tissue collected from a subject using a deep learning algorithm of a neural network structure. The image analysis method includes generating analysis data from the analysis target image that includes the tissue to be analyzed, inputting the analysis data to a deep learning algorithm, and generating data indicating a layer structure configuring a tissue in the analysis target image by the deep learning algorithm.
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公开(公告)号：US10482605B2
公开(公告)日：2019-11-19
申请号：US15391311
申请日：2016-12-27
Inventor： Kazumi Hakamada , Yuki Aihara , Masaya Okada , Toshiyuki Sato , Ichiro Sekiya , Eiji Kobayashi
Abstract: A method comprises obtaining a first cell image of a cell by a first observation method, obtaining a second cell image of the cell by a second observation method that is different from the first observation method, and determining the region of the cell based on the first cell image and the second cell image.
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公开(公告)号：US20190156476A1
公开(公告)日：2019-05-23
申请号：US16192850
申请日：2018-11-16
Applicant: National Cancer Center , SYSMEX CORPORATION
Inventor： Hiroshi Yoshida , Yosuke Sekiguchi , Kazumi Hakamada , Yuki Aihara , Kohei Yamada , Kanako Masumoto , Krupali Jain
Abstract: An image analysis method for generating data indicating a tumorigenic state of an image of a tissue or a cell. The image analysis method is an image analysis method for analyzing an image of a tissue or a cell using a deep learning algorithm of a neural network structure, analysis data are generated from the analysis target image including a tissue or cell to be analyzed, the analysis data are input to the deep learning algorithm, and data indicating the tumorigenic state of tissues or cells in the analysis target image are generated by the depth learning algorithm.
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公开(公告)号：US20230419696A1
公开(公告)日：2023-12-28
申请号：US18462530
申请日：2023-09-07
Applicant: SYSMEX CORPORATION
Inventor： Yosuke Sekiguchi , Kazumi Hakamada , Yuki Aihara , Kohei Yamada , Kanako Masumoto , Krupali Jain
CPC classification number: G06V20/698 , G06V10/44 , G06V10/56 , G06T2207/30024 , G06T7/90 , G06T7/0014 , G06T2207/20084 , G06T7/74
Abstract: The present invention provides an image analysis method for generating data indicating a region of a cell nucleus in an image of a tissue or a cell. The image analysis method is a method for analyzing an image of a tissue or a cell using a deep learning algorithm of a neural network structure, and generates data indicating a region of a cell nucleus in an analysis target image by the deep learning algorithm by generating analysis data from the analysis target image including an analysis target tissue or cell, and inputting the analysis data in the deep learning algorithm.
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公开(公告)号：US11467073B2
公开(公告)日：2022-10-11
申请号：US15935445
申请日：2018-03-26
Applicant: SYSMEX CORPORATION
Inventor： Koya Yamawaki , Yuki Aihara
Abstract: Disclosed is a method for concentrating extracellular vesicles, comprising preparing a mixture comprising a first fraction and a second fraction by mixing a liquid sample comprising extracellular vesicles, a polysaccharide, and a polyether having an average molecular weight of 20,000 or less, wherein the first fraction comprises a higher concentration of extracellular vesicles than the second fraction, and the first fraction comprises a higher concentration of extracellular vesicles than the liquid sample.
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