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公开(公告)号：US20230013209A1
公开(公告)日：2023-01-19
申请号：US17951872
申请日：2022-09-23
Inventor： Kihyun Hong , Hyun-Seok Min , YongKeun Park , Geon Kim , Youngju Jo
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying the predicted type of one or more microorganisms. In one aspect, a system comprises a phase-contrast microscope and a microorganism classification system. The phase-contrast microscope is configured to generate a three-dimensional quantitative phase image of one or more microorganisms. The microorganism classification system is configured to process the three-dimensional quantitative phase image using a neural network to generate a neural network output characterizing the microorganisms, and thereafter identify the predicted type of the microorganisms using the neural network output.
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公开(公告)号：US20220156561A1
公开(公告)日：2022-05-19
申请号：US17431871
申请日：2019-09-27
Inventor： Kihyun Hong , Hyun-Seok Min , YongKeun Park , Geon Kim , Youngju Jo
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying the predicted type of one or more microorganisms. In one aspect, a system comprises a phase-contrast microscope and a microorganism classification system. The phase-contrast microscope is configured to generate a three-dimensional quantitative phase image of one or more microorganisms. The microorganism classification system is configured to process the three-dimensional quantitative phase image using a neural network to generate a neural network output characterizing the microorganisms, and thereafter identify the predicted type of the microorganisms using the neural network output.
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公开(公告)号：US12001940B2
公开(公告)日：2024-06-04
申请号：US17951872
申请日：2022-09-23
Applicant: Tomocube, Inc.
Inventor： Kihyun Hong , Hyun-Seok Min , YongKeun Park , Geon Kim , Youngju Jo
CPC classification number: G06N3/045 , G06T7/0012 , G06T2207/10056
Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying the predicted type of one or more microorganisms. In one aspect, a system comprises a phase-contrast microscope and a microorganism classification system. The phase-contrast microscope is configured to generate a three-dimensional quantitative phase image of one or more microorganisms. The microorganism classification system is configured to process the three-dimensional quantitative phase image using a neural network to generate a neural network output characterizing the microorganisms, and thereafter identify the predicted type of the microorganisms using the neural network output.
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公开(公告)号：US11410304B2
公开(公告)日：2022-08-09
申请号：US16900364
申请日：2020-06-12
Applicant: TOMOCUBE, INC.
Inventor： YongKeun Park , Donghun Ryu , Young Seo Kim , Kihyun Hong , Hyun-Seok Min
Abstract: A non-label diagnosis apparatus for a hematologic malignancy may include a 3-D refractive index cell imaging unit configured to generate a 3-D refractive index slide image of a blood smear specimen by capturing a 3-D refractive index image in the form of the blood smear specimen in which blood (including a bone-marrow or other body fluids) of a patient has been smeared on a slide glass, an ROI detection unit configured to sample a suspected cell segment in the blood smear specimen based on the 3-D refractive index slide image and to determine, as ROI patches, cells determined as abnormal cells, and a diagnosis unit configured to determine a sub-classification of a cancer cell corresponding to each of the ROI patches using a cancer cell sub-classification determination model constructed based on a deep learning algorithm and to generate hematologic malignancy diagnosis results by gathering sub-classification results of the ROI patches.
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