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A single-pixel approach to recover the transmission matrix. A Simplified schematic view of a general fluorescence microscope with a single-pixel detector. Random wavefront generated by a SLM a Nm impinges on a scattering medium with a transmission matrix T and excites 2-photon fluorescence (2PF) of an extended object o . The fluorescence signal y is collected by a single-pixel detector (e.g. photo-multiplier tube (PMT)). A matrix A is made from the known wavefronts a Nm . A gradient-descent-based algorithm is used to solve the forward problem min t i || y− ∑| At i | 4 || 2 , where t i are filtered columns of T by the positions of o . B Selected experimental realization. (Upper panel) 2PF signal detected vs. number of random wavefronts. Representative wavefronts used are shown in the insets. (Bottom panels) Inspected foci for two selected column after retrieval of z z , a sum of all images for each focus demonstrating unique single focus for each column retrieved, and comparison with brightfield image confirming the number of sources . The <t>MATLAB</t> codes for speckle analysis and control are given in
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A single-pixel approach to recover the transmission matrix. A Simplified schematic view of a general fluorescence microscope with a single-pixel detector. Random wavefront generated by a SLM a Nm impinges on a scattering medium with a transmission matrix T and excites 2-photon fluorescence (2PF) of an extended object o . The fluorescence signal y is collected by a single-pixel detector (e.g. photo-multiplier tube (PMT)). A matrix A is made from the known wavefronts a Nm . A gradient-descent-based algorithm is used to solve the forward problem min t i || y− ∑| At i | 4 || 2 , where t i are filtered columns of T by the positions of o . B Selected experimental realization. (Upper panel) 2PF signal detected vs. number of random wavefronts. Representative wavefronts used are shown in the insets. (Bottom panels) Inspected foci for two selected column after retrieval of z z , a sum of all images for each focus demonstrating unique single focus for each column retrieved, and comparison with brightfield image confirming the number of sources . The <t>MATLAB</t> codes for speckle analysis and control are given in
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A single-pixel approach to recover the transmission matrix. A Simplified schematic view of a general fluorescence microscope with a single-pixel detector. Random wavefront generated by a SLM a Nm impinges on a scattering medium with a transmission matrix T and excites 2-photon fluorescence (2PF) of an extended object o . The fluorescence signal y is collected by a single-pixel detector (e.g. photo-multiplier tube (PMT)). A matrix A is made from the known wavefronts a Nm . A gradient-descent-based algorithm is used to solve the forward problem min t i || y− ∑| At i | 4 || 2 , where t i are filtered columns of T by the positions of o . B Selected experimental realization. (Upper panel) 2PF signal detected vs. number of random wavefronts. Representative wavefronts used are shown in the insets. (Bottom panels) Inspected foci for two selected column after retrieval of z z , a sum of all images for each focus demonstrating unique single focus for each column retrieved, and comparison with brightfield image confirming the number of sources . The MATLAB codes for speckle analysis and control are given in

Journal: Applied Physics. B, Lasers and Optics

Article Title: Roadmap on computational methods in optical imaging and holography [invited]

doi: 10.1007/s00340-024-08280-3

Figure Lengend Snippet: A single-pixel approach to recover the transmission matrix. A Simplified schematic view of a general fluorescence microscope with a single-pixel detector. Random wavefront generated by a SLM a Nm impinges on a scattering medium with a transmission matrix T and excites 2-photon fluorescence (2PF) of an extended object o . The fluorescence signal y is collected by a single-pixel detector (e.g. photo-multiplier tube (PMT)). A matrix A is made from the known wavefronts a Nm . A gradient-descent-based algorithm is used to solve the forward problem min t i || y− ∑| At i | 4 || 2 , where t i are filtered columns of T by the positions of o . B Selected experimental realization. (Upper panel) 2PF signal detected vs. number of random wavefronts. Representative wavefronts used are shown in the insets. (Bottom panels) Inspected foci for two selected column after retrieval of z z , a sum of all images for each focus demonstrating unique single focus for each column retrieved, and comparison with brightfield image confirming the number of sources . The MATLAB codes for speckle analysis and control are given in

Article Snippet: As an example of the methods explained, we present MATLAB pseudocodes for making diffractive lenses and for the 3D volume reconstruction from phase-shift holographic images.

Techniques: Transmission Assay, Fluorescence, Microscopy, Generated, Comparison, Control

List of acronyms

Journal: Applied Physics. B, Lasers and Optics

Article Title: Roadmap on computational methods in optical imaging and holography [invited]

doi: 10.1007/s00340-024-08280-3

Figure Lengend Snippet: List of acronyms

Article Snippet: As an example of the methods explained, we present MATLAB pseudocodes for making diffractive lenses and for the 3D volume reconstruction from phase-shift holographic images.

Techniques: Multiplexing, Imaging, Microscopy, Fluorescence, Computed Tomography, Virus, Tomography, Refractive Index, Digital Holographic Microscopy, Blocking Assay, Optical Imaging