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Synthetic aperture microscopy(SAM) is an imaging technique used to improve the resolution of optical microscopes by combining multiple images obtained at different angles or positions. It is a non-invasive method that can be used to study the morphology, structure, and dynamics of biological and non-biological samples.
Introduction
[edit]The synthetic aperture microscope (SAM) is a patented optical imaging system that is based on the concepts that originated with synthetic aperture radar (SAR) which was invented in 1951.[1]
Optical microscopy is an essential tool for studying the micro- and nano-scale features of materials and biological samples. However, its resolution is limited by the diffraction of light, which prevents the microscope from distinguishing two objects that are closer than half the wavelength of the light used. This limit is known as the Abbe limit, and it restricts the resolution of conventional optical microscopes to approximately 200-300 nm.[2]
SAM overcomes this limit by combining the information from multiple images of the same sample, taken at different angles or positions. It achieves this by using computer algorithms to synthesize a high-resolution image from the low-resolution images obtained by the microscope.
Working Principle
[edit]A plane wave is often used for illumination and only the spatial frequencies diffracted by the sample up to ~ NA/λ can be transmitted through the limited aperture of the microscope lens, resulting in an upper limit for the spatial resolution in terms of 0.82λ/NA. With oblique beam illumination, an enhanced spatial resolution can be achieved. When a sample is illuminated by an oblique wave, the high spatial frequency of the object wave in the opposite direction of the oblique illumination will be downshifted and, thus, will pass through the limited aperture of the imaging system. The downshifted frequencies are back-assembled to their original positions in the spectrum of the object, thus, synthesizing a wider spectrum than that of the NA-defined aperture. The final resolution-enhanced image is obtained by an inverse Fourier transform (FT) of the synthesized spectrum.[3]
Algorithm
[edit]Iterative synthetic aperture reconstruction algorithm (ISARA)
The ISARA algorithm begins by acquiring multiple low-resolution images of the sample from different angles or positions. These images are combined to create a low-resolution synthetic aperture image. The synthetic aperture image is then used as an initial estimate for the high-resolution image. The algorithm iteratively refines this estimate by comparing it with the low-resolution images and adjusting it to better match the data.
The iteration process involves the following steps:[4]
1. Forward model: The low-resolution images are simulated from the current estimate of the high-resolution image using a forward model that accounts for the optical properties of the microscope and the sample.
2. Data fidelity: The simulated low-resolution images are compared with the measured low-resolution images, and the difference is quantified as a measure of data fidelity.
3. Regularization: To prevent overfitting and improve the stability of the algorithm, a regularization term is added to the data fidelity term. The regularization term imposes a constraint on the high-resolution image that promotes smoothness and sparsity.
4. Optimization: The data fidelity and regularization terms are combined into an objective function that is optimized to update the high-resolution image estimate. This process is repeated iteratively until the objective function converges to a minimum.
Applications
[edit]SAM has a wide range of applications in materials science, biology, and medicine. In materials science, it is used to study the microstructure of materials, such as metals, ceramics, and polymers, with high resolution. It can also be used to analyze the composition of samples and to study their surface properties.
In biology, SAM is used to study the structure and dynamics of cells and tissues. It can be used to study the morphology of cells, the distribution of proteins, and the organization of organelles. SAM can also be used to study the structure and function of tissues, such as blood vessels, nerves, and muscles.
In medicine, SAM is used in the diagnosis and treatment of diseases. It can be used to study the structure of tissues, such as tumors, and to monitor the response of tissues to treatment. SAM can also be used to study the distribution of drugs and to optimize drug delivery.
Conclusion
[edit]Synthetic Aperture Microscopy is a powerful imaging technique that overcomes the diffraction limit of conventional optical microscopes. It has applications in materials science, biology, and medicine and can be used to study the microstructure, morphology, and dynamics of samples with high resolution. With the advancement of technology, SAM is expected to become more widely used in research and industry, leading to new discoveries and applications in various fields.
References
[edit]- ^ Turpin, Terry M., et al. "Theory of the synthetic aperture microscope." Advanced Imaging Technologies and Commercial Applications. Vol. 2566. SPIE, 1995.
- ^ Wilson, M. "Microscope Resolution: Concepts, Factors and Calculation." Leica Microsystems Science Lab (2016).
- ^ Luo, Wei, et al. "Synthetic aperture-based on-chip microscopy." Light: Science & Applications 4.3 (2015): e261-e261.
- ^ Zhou, Xi, et al. "NUFFT-based iterative reconstruction algorithm for synthetic aperture imaging radiometers." IEEE Geoscience and Remote Sensing Letters 6.2 (2009): 273-276.