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.

Abstract: A lens-free microscope system for automatically analyzing yeast cell viability in a stained sample includes a portable, lens-free microscopy device that includes a housing containing a light source coupled to an optical fiber, the optical fiber spaced away several centimeters from an image sensor disposed at one end of the housing, wherein the stained sample is disposed on the image sensor or a sample holder adjacent to the image sensor. Hologram images are transferred to a computing device having image processing software contained therein, the image processing software identifying yeast cell candidates of interest from back-propagated images of the stained sample, whereby a plurality of spatial features are extracted from the yeast cell candidates of interest and subject to a trained machine learning model to classify the yeast cell candidates of interest as live or dead.

Abstract: A lens-free microscope system for automatically analyzing yeast cell viability in a stained sample includes a portable, lens-free microscopy device that includes a housing containing a light source coupled to an optical fiber, the optical fiber spaced away several centimeters from an image sensor disposed at one end of the housing, wherein the stained sample is disposed on the image sensor or a sample holder adjacent to the image sensor. Hologram images are transferred to a computing device having image processing software contained therein, the image processing software identifying yeast cell candidates of interest from back-propagated images of the stained sample, whereby a plurality of spatial features are extracted from the yeast cell candidates of interest and subject to a trained machine learning model to classify the yeast cell candidates of interest as live or dead.

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.

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.

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.