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公开(公告)号:US12210167B2
公开(公告)日:2025-01-28
申请号:US18636195
申请日:2024-04-15
Applicant: Purdue Research Foundation
Inventor: Fan Xu , Fang Huang , Donghan Ma
Abstract: A method of in situ point spread function (PSF) retrieval is disclosed which includes encoding 3D location of molecules into PSFs, receiving molecule-generated images containing PSFs, segmenting the images into sub-PSF, initializing template PSFs from a pupil function, determining a statistical measure of a predetermined function between the sub- and template PSFs, associating each of the sub-PSFs with a template PSF, aligning and averaging the sub-PSF, applying a phase retrieval algorithm to the averaged sub-PSFs to update the pupil function, regenerating the template PSFs, repeating until a difference between a new and a prior generation pupil function is below a predetermined threshold, generating in situ PSFs from the last pupil function, and applying a maximum likelihood estimation algorithm based on the in situ PSFs and the sub-PSF to thereby generate lateral and axial locations of molecules.
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公开(公告)号:US11960102B2
公开(公告)日:2024-04-16
申请号:US17628140
申请日:2020-08-06
Applicant: Purdue Research Foundation
Inventor: Fan Xu , Fang Huang , Donghan Ma
CPC classification number: G02B27/58 , G01N21/6458 , G02B21/367 , G02B26/0825 , G02B27/0068 , G06T2207/10056
Abstract: A method of in situ point spread function (PSF) retrieval is disclosed which includes encoding 3D location of molecules into PSFs, receiving molecule-generated images containing PSFs, segmenting the images into sub-PSFs, initializing template PSFs from a pupil function, determining a maximum normalized cross correlation (NCC) coefficient (NCCmax) between the sub- and template PSFs, associating each of the sub-PSFs with a template PSF based on the NCCmax and storing the sub-PSFs in associated bins, aligning and averaging the binned sub-PSFs, applying a phase retrieval algorithm to the averaged sub-PSFs to update the pupil function, regenerating the template PSFs, repeating until a difference between a new and a prior generation pupil function is below a predetermined threshold, generating in situ PSFs from the last pupil function, and applying a maximum likelihood estimation algorithm based on the in situ PSFs and the sub-PSFs to thereby generate lateral and axial locations of molecules.
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公开(公告)号:US20240272449A1
公开(公告)日:2024-08-15
申请号:US18636195
申请日:2024-04-15
Applicant: Purdue Research Foundation
Inventor: Fan Xu , Fang Huang , Donghan Ma
CPC classification number: G02B27/58 , G01N21/6458 , G02B21/367 , G02B26/0825 , G02B27/0068 , G06T2207/10056
Abstract: A method of in situ point spread function (PSF) retrieval is disclosed which includes encoding 3D location of molecules into PSFs, receiving molecule-generated images containing PSFs, segmenting the images into sub-PSF, initializing template PSFs from a pupil function, determining a statistical measure of a predetermined function between the sub- and template PSFs, associating each of the sub-PSFs with a template PSF, aligning and averaging the sub-PSF, applying a phase retrieval algorithm to the averaged sub-PSFs to update the pupil function, regenerating the template PSFs, repeating until a difference between a new and a prior generation pupil function is below a predetermined threshold, generating in situ PSFs from the last pupil function, and applying a maximum likelihood estimation algorithm based on the in situ PSFs and the sub-PSF to thereby generate lateral and axial locations of molecules.
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公开(公告)号:US20220283443A1
公开(公告)日:2022-09-08
申请号:US17628140
申请日:2020-08-06
Applicant: Purdue Research Foundation
Inventor: Fan Xu , Fang Huang , Donghan Ma
Abstract: A method of in situ point spread function (PSF) retrieval is disclosed which includes encoding 3D location of molecules into PSFs, receiving molecule-generated images containing PSFs, segmenting the images into sub-PSFs, initializing template PSFs from a pupil function, determining a maximum normalized cross correlation (NCC) coefficient (NCCmax) between the sub- and template PSFs, associating each of the sub-PSFs with a template PSF based on the NCCmax and storing the sub-PSFs in associated bins, aligning and averaging the binned sub-PSFs, applying a phase retrieval algorithm to the averaged sub-PSFs to update the pupil function, regenerating the template PSFs, repeating until a difference between a new and a prior generation pupil function is below a predetermined threshold, generating in situ PSFs from the last pupil function, and applying a maximum likelihood estimation algorithm based on the in situ PSFs and the sub-PSFs to thereby generate lateral and axial locations of molecules.
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