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公开(公告)号:US20250157232A1
公开(公告)日:2025-05-15
申请号:US18508896
申请日:2023-11-14
Applicant: Leica Microsystems CMS GmbH
Inventor: Won Yung CHOI , Hung-Yu CHANG , Chi-Chou HUANG , Hoyin LAI , Sean McELROY , Luciano Andre GUERREIRO LUCAS
Abstract: A first aspect of this disclosure is related to a computer-implemented method for identifying neuronal patterns in an image, comprising the steps: obtaining a first data set with Golgi-stained neuronal structures; based on the first data set, determining a first auxiliary data set, AR1, based on a first type of neuronal structure and a second auxiliary data set, AR2, based on a second type of neuronal structure; analyzing AR1 with a first method to identify information related to the first type of neuronal structure in AR1; analyzing AR2 with a second method to identify information related to the second type of neuronal structure in AR2; generating a second data set with the identified information related to the first and second type of neuronal structures.
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公开(公告)号:US20250037485A1
公开(公告)日:2025-01-30
申请号:US18782178
申请日:2024-07-24
Applicant: Leica Microsystems CMS GmbH
Inventor: Constantin KAPPEL , José Miguel SERRA LLETI , Volker SCHWEIKHARD , Hoyin LAI
Abstract: An image processing system is configured to receive at least one reference image, wherein each reference image is a microscopy image capturing cells of a biological sample, wherein the at least one reference image includes at least one reference labeling directed to a reference cellular compartment of the captured cells. The image processing system is configured to employ a trained deep neural network for processing the at least one reference image to generate a target image, wherein the target image includes a target labeling directed to a target cellular compartment of the captured cells, wherein the at least one reference labeling comprises a fluorescence labeling, wherein the reference cellular compartment is a distributed structure within cells, and wherein the target cellular compartment is the cell nucleus.
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