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1.发明授权公开(公告)号：US11893779B2
公开(公告)日：2024-02-06
申请号：US17285898
申请日：2019-10-18
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Yibo Zhang , Hatice Ceylan Koydemir
CPC classification number: G06V10/82 , G01N15/14 , G01N33/49 , G03H1/0005 , G03H1/08 , G06T7/20 , G06V20/69 , G06V20/698 , G06V30/19173 , G01N2015/1486 , G03H2001/0033 , G03H2210/42 , G03H2210/46 , G06T2207/20081 , G06T2207/30024 , G06T2207/30242
Abstract: Systems and methods for detecting motile objects (e.g., parasites) in a fluid sample by utilizing the locomotion of the parasites as a specific biomarker and endogenous contrast mechanism. The imaging platform includes one or more substantially optically transparent sample holders. The imaging platform has a moveable scanning head containing light sources and corresponding image sensor(s) associated with the light source(s). The light source(s) are directed at a respective sample holder containing a sample and the respective image sensor(s) are positioned below a respective sample holder to capture time-varying holographic speckle patterns of the sample contained in the sample holder. The image sensor(s). A computing device is configured to receive time-varying holographic speckle pattern image sequences obtained by the image sensor(s). The computing device generates a 3D contrast map of motile objects within the sample use deep learning-based classifier software to identify the motile objects.
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公开(公告)号：US20190286053A1
公开(公告)日：2019-09-19
申请号：US16300546
申请日：2017-05-10
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Yichen Wu , Yibo Zhang , Wei Luo
Abstract: A method of generating a color image of a sample includes obtaining a plurality of low resolution holographic images of the sample using a color image sensor, the sample illuminated simultaneously by light from three or more distinct colors, wherein the illuminated sample casts sample holograms on the image sensor and wherein the plurality of low resolution holographic images are obtained by relative x, y, and z directional shifts between sample holograms and the image sensor. Pixel super-resolved holograms of the sample are generated at each of the three or more distinct colors. De-multiplexed holograms are generated from the pixel super-resolved holograms. Phase information is retrieved from the de-multiplexed holograms using a phase retrieval algorithm to obtain complex holograms. The complex hologram for the three or more distinct colors is digitally combined and back-propagated to a sample plane to generate the color image.
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公开(公告)号：US12038370B2
公开(公告)日：2024-07-16
申请号：US17621979
申请日：2020-07-02
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Aniruddha Ray , Yibo Zhang , Dino Di Carlo
IPC: G01N15/1433 , B03C1/01 , B03C1/02 , G01N15/1434 , G03H1/00 , G06V10/147 , G06V10/82 , G06V20/69 , G01N15/01 , G01N15/10
CPC classification number: G01N15/1433 , B03C1/01 , B03C1/02 , G01N15/1434 , G03H1/0005 , G06V10/147 , G06V10/82 , G06V20/693 , G06V20/698 , B03C2201/18 , B03C2201/26 , G01N15/01 , G01N2015/1006 , G03H2001/005 , G03H2222/12
Abstract: A computational cytometer operates using magnetically modulated lensless speckle imaging, which introduces oscillatory motion to magnetic bead-conjugated rare cells of interest through a periodic magnetic force and uses lensless time-resolved holographic speckle imaging to rapidly detect the target cells in three-dimensions (3D). Detection specificity is further enhanced through a deep learning-based classifier that is based on a densely connected pseudo-3D convolutional neural network (P3D CNN), which automatically detects rare cells of interest based on their spatio-temporal features under a controlled magnetic force. This compact, cost-effective and high-throughput computational cytometer can be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.
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公开(公告)号：US10795315B2
公开(公告)日：2020-10-06
申请号：US16300546
申请日：2017-05-10
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Yichen Wu , Yibo Zhang , Wei Luo
IPC: G06K9/76 , G03H1/04 , H04N9/04 , G03H1/00 , G03H1/22 , G06T3/40 , H04N5/232 , H04N9/68 , H04N9/73
Abstract: A method of generating a color image of a sample includes obtaining a plurality of low resolution holographic images of the sample using a color image sensor, the sample illuminated simultaneously by light from three or more distinct colors, wherein the illuminated sample casts sample holograms on the image sensor and wherein the plurality of low resolution holographic images are obtained by relative x, y, and z directional shifts between sample holograms and the image sensor. Pixel super-resolved holograms of the sample are generated at each of the three or more distinct colors. De-multiplexed holograms are generated from the pixel super-resolved holograms. Phase information is retrieved from the de-multiplexed holograms using a phase retrieval algorithm to obtain complex holograms. The complex hologram for the three or more distinct colors is digitally combined and back-propagated to a sample plane to generate the color image.
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5.发明授权公开(公告)号：US11422503B2
公开(公告)日：2022-08-23
申请号：US16952492
申请日：2020-11-19
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Alon Grinbaum , Yibo Zhang , Alborz Feizi , Wei Luo
Abstract: A method for lens-free imaging of a sample or objects within the sample uses multi-height iterative phase retrieval and rotational field transformations to perform wide FOV imaging of pathology samples with clinically comparable image quality to a benchtop lens-based microscope. The solution of the transport-of-intensity (TIE) equation is used as an initial guess in the phase recovery process to speed the image recovery process. The holographically reconstructed image can be digitally focused at any depth within the object FOV (after image capture) without the need for any focus adjustment, and is also digitally corrected for artifacts arising from uncontrolled tilting and height variations between the sample and sensor planes. In an alternative embodiment, a synthetic aperture approach is used with multi-angle iterative phase retrieval to perform wide FOV imaging of pathology samples and increase the effective numerical aperture of the image.
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Patent Agency Ranking
6.发明申请公开(公告)号：US20210374381A1
公开(公告)日：2021-12-02
申请号：US17285898
申请日：2019-10-18
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Yibo Zhang , Hatice Ceylan Koydemir
Abstract: Systems and methods for detecting motile objects (e.g., parasites) in a fluid sample by utilizing the locomotion of the parasites as a specific biomarker and endogenous contrast mechanism. The imaging platform includes one or more substantially optically transparent sample holders. The imaging platform has a moveable scanning head containing light sources and corresponding image sensor(s) associated with the light source(s). The light source(s) are directed at a respective sample holder containing a sample and the respective image sensor(s) are positioned below a respective sample holder to capture time-varying holographic speckle patterns of the sample contained in the sample holder. The image sensor(s). A computing device is configured to receive time-varying holographic speckle pattern image sequences obtained by the image sensor(s). The computing device generates a 3D contrast map of motile objects within the sample use deep learning-based classifier software to identify the motile objects.
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7.发明授权公开(公告)号：US11514325B2
公开(公告)日：2022-11-29
申请号：US16359609
申请日：2019-03-20
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Yair Rivenson , Yichen Wu , Yibo Zhang , Harun Gunaydin
Abstract: A method of performing phase retrieval and holographic image reconstruction of an imaged sample includes obtaining a single hologram intensity image of the sample using an imaging device. The single hologram intensity image is back-propagated to generate a real input image and an imaginary input image of the sample with image processing software, wherein the real input image and the imaginary input image contain twin-image and/or interference-related artifacts. A trained deep neural network is provided that is executed by the image processing software using one or more processors and configured to receive the real input image and the imaginary input image of the sample and generate an output real image and an output imaginary image in which the twin-image and/or interference-related artifacts are substantially suppressed or eliminated. In some embodiments, the trained deep neural network simultaneously achieves phase-recovery and auto-focusing significantly extending the DOF of holographic image reconstruction.
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8.发明申请公开(公告)号：US20210181673A1
公开(公告)日：2021-06-17
申请号：US16952492
申请日：2020-11-19
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Alon Grinbaum , Yibo Zhang , Alborz Feizi , Wei Luo
Abstract: A method for lens-free imaging of a sample or objects within the sample uses multi-height iterative phase retrieval and rotational field transformations to perform wide FOV imaging of pathology samples with clinically comparable image quality to a benchtop lens-based microscope. The solution of the transport-of-intensity (TIE) equation is used as an initial guess in the phase recovery process to speed the image recovery process. The holographically reconstructed image can be digitally focused at any depth within the object FOV (after image capture) without the need for any focus adjustment, and is also digitally corrected for artifacts arising from uncontrolled tilting and height variations between the sample and sensor planes. In an alternative embodiment, a synthetic aperture approach is used with multi-angle iterative phase retrieval to perform wide FOV imaging of pathology samples and increase the effective numerical aperture of the image.
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9.发明申请公开(公告)号：US20200310100A1
公开(公告)日：2020-10-01
申请号：US16300539
申请日：2017-05-09
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Yibo Zhang , Yichen Wu
Abstract: Methods and systems for generating a high-color-fidelity and high-resolution color image of a sample are disclosed; which fuses or merges a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform based colorization method. A holographic microscope is used to obtain holographic images which are used to computationally reconstruct a high-resolution mono-color holographic image of the sample. A lens-based microscope is used to obtain low resolution color images. A discrete wavelet transform (DWT) is used to generate a final image that merges the low-resolution components from the lens-based color image and the high-resolution components from the high-resolution mono-color holographic image.
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公开(公告)号：US20220260481A1
公开(公告)日：2022-08-18
申请号：US17621979
申请日：2020-07-02
Applicant: THE REGENTS OF THE UNIVERSITY OF CALIFORNIA
Inventor： Aydogan Ozcan , Aniruddha Ray , Yibo Zhang , Dino Di Carlo
Abstract: A computational cytometer operates using magnetically modulated lensless speckle imaging, which introduces oscillatory motion to magnetic bead-conjugated rare cells of interest through a periodic magnetic force and uses lensless time-resolved holographic speckle imaging to rapidly detect the target cells in three-dimensions (3D). Detection specificity is further enhanced through a deep learning-based classifier that is based on a densely connected pseudo-3D convolutional neural network (P3D CNN), which automatically detects rare cells of interest based on their spatio-temporal features under a controlled magnetic force. This compact, cost-effective and high-throughput computational cytometer can be used for rare cell detection and quantification in bodily fluids for a variety of biomedical applications.
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