Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging
Single-molecule localization microscopy in a typical wide-field setup has been widely used
for investigating subcellular structures with super resolution; however, field-dependent …
for investigating subcellular structures with super resolution; however, field-dependent …
DeepSTORM3D: dense 3D localization microscopy and PSF design by deep learning
An outstanding challenge in single-molecule localization microscopy is the accurate and
precise localization of individual point emitters in three dimensions in densely labeled …
precise localization of individual point emitters in three dimensions in densely labeled …
Fluorescence Microscopy: a statistics-optics perspective
Fundamental properties of light unavoidably impose features on images collected using
fluorescence microscopes. Accounting for these features is often critical in quantitatively …
fluorescence microscopes. Accounting for these features is often critical in quantitatively …
Dipole-spread-function engineering for simultaneously measuring the 3D orientations and 3D positions of fluorescent molecules
Interactions between biomolecules are characterized by where they occur and how they are
organized, eg, the alignment of lipid molecules to form a membrane. However, spatial and …
organized, eg, the alignment of lipid molecules to form a membrane. However, spatial and …
Learning optimal wavefront shaping for multi-channel imaging
Fast acquisition of depth information is crucial for accurate 3D tracking of moving objects.
Snapshot depth sensing can be achieved by wavefront coding, in which the point-spread …
Snapshot depth sensing can be achieved by wavefront coding, in which the point-spread …
Practical sensorless aberration estimation for 3D microscopy with deep learning
Estimation of optical aberrations from volumetric intensity images is a key step in sensorless
adaptive optics for 3D microscopy. Recent approaches based on deep learning promise …
adaptive optics for 3D microscopy. Recent approaches based on deep learning promise …
3D printable diffractive optical elements by liquid immersion
Diffractive optical elements (DOEs) are used to shape the wavefront of incident light. This
can be used to generate practically any pattern of interest, albeit with varying efficiency. A …
can be used to generate practically any pattern of interest, albeit with varying efficiency. A …
Combining deep learning approaches and point spread function engineering for simultaneous 3D position and 3D orientation measurements of fluorescent single …
Abstract Point Spread Function (PSF) engineering is an effective method to increase the
sensitivity of single-molecule fluorescence images to specific parameters. Classical phase …
sensitivity of single-molecule fluorescence images to specific parameters. Classical phase …
Recent advances in point spread function engineering and related computational microscopy approaches: from one viewpoint
Y Shechtman - Biophysical reviews, 2020 - Springer
This personal hybrid review piece, written in light of my recipience of the UIPAB 2020 young
investigator award, contains a mixture of my scientific biography and work so far. This paper …
investigator award, contains a mixture of my scientific biography and work so far. This paper …
Deep learning-based adaptive optics for light sheet fluorescence microscopy
Light sheet fluorescence microscopy (LSFM) is a high-speed imaging technique that is often
used to image intact tissue-cleared specimens with cellular or subcellular resolution. Like …
used to image intact tissue-cleared specimens with cellular or subcellular resolution. Like …