Optical Reconstruction
Optical Reconstruction - Related Videos
09:36
Direct Stochastic Optical Reconstruction Microscopy of Extracellular Vesicles in Three Dimensions
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Cited by 8 •
2021
Direct stochastic optical reconstruction microscopy (dSTORM) is used to bypass the typical diffraction limit of light microscopy and to view exosomes at the nanometer scale. It can be employed in both two and three dimensions to characterize exosomes.
08:31
Three-dimensional Optical-resolution Photoacoustic Microscopy
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Cited by 27 •
2011
Optical-resolution photoacoustic microscopy (OR-PAM) is an emerging technology capable of imaging optical absorption contrasts in vivo with cellular resolution and sensitivity. Here, we provide a visualized instruction on the experimental protocols of OR-PAM, including system configuration, system alignment, typical in vivo experimental procedures, and functional imaging schemes.
14:09
Quantitative Optical Microscopy: Measurement of Cellular Biophysical Features with a Standard Optical Microscope
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Cited by 11 •
2014
We describe the use of a standard optical microscope to perform quantitative measurements of cellular mass, volume, and density through a combination of bright field and differential interference contrast imagery.
14:23
Imaging Intermediate Filaments and Microtubules with 2-dimensional Direct Stochastic Optical Reconstruction Microscopy
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Cited by 6 •
2018
The overall goal of this methodology is to give the optimal experimental conditions from sample preparation to image acquisition and reconstruction in order to perform 2D dual color dSTORM images of microtubules and intermediate filaments in fixed cells...
14:09
High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip
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Cited by 7 •
2019
Chip-based super-resolution optical microscopy is a novel approach to fluorescence microscopy and offers advantages in cost effectiveness and throughput. Here, the protocols for chip preparation and imaging are shown for TIRF microscopy and localization-based super-resolution microscopy.
FAQs
Its central challenge is that recorded optical signals do not directly display the target anatomy. Models connect those measurements to light propagation through tissue, including scattering and absorption, while computational algorithms estimate the underlying structure. This inverse-problem framing matters because the quality of the reconstructed image depends on how well the model represents image formation.
Scattering and absorption are essential parts of the light-propagation model used in reconstruction. Rather than treating them as background details, the method incorporates both when interpreting camera or detector measurements. This allows the computational analysis to relate recorded optical signals to the tissue structures that produced them.
The reconstruction target shapes the output: an algorithm may estimate an image, surface, or three-dimensional structure. That distinction is important in medicine because the resulting spatial representation must match the biological feature being visualized. The same measurement concept can therefore support different forms of anatomical visualization.
An optical reconstruction workflow begins by collecting light measurements with a camera or detector. Those signals are then analyzed using models of light propagation, scattering, and absorption, followed by computational estimation of the structure that produced them. The resulting spatial information can be organized as an image, surface, or three-dimensional representation, depending on the reconstruction goal.
In medicine, optical reconstruction supports microscopy, tissue imaging, anatomical visualization, and image-guided procedures. These applications use reconstructed spatial information to examine biological tissues that cannot be assessed directly and to support noninvasive assessment. The technique also enables quantitative analysis and contributes to development of diagnostic technologies, extending optical measurements beyond simple visual recording.
The value of a medical reconstruction is not limited to producing a visually interpretable result. By converting indirect optical measurements into spatial information, it can support quantitative analysis alongside visualization. This is relevant to image-guided procedures and diagnostic technology development, where noninvasive assessment and clearer anatomical context are important.