Computational imaging through diffusing or scattering media has attracted attention in many fields. Deep learning has been used in recent years to reconstruct images behind scattering media. As described in this paper, we investigate image reconstruction through a diffuser by changing the distance separating the diffuser and the lens. We also investigate aperture diameter effects on scattered light removal by spatial filtering.
Lensless digital holography can reconstruct the intensity and phase of an object located behind a diffuser. However, the image quality of reconstructed images is dependent on the distance between the diffuser and the image sensor or between the diffuser and the sample. For this study, we reconstruct the object intensity by changing the distance between the sample and the diffuser. Then we investigate the image quality of reconstructed images.
Mobile phone technology has led to implementation of portable and inexpensive microscopes. Light-emitting diode (LED) array microscopes support various multicontrast imaging by flexible illumination patterns of the LED array that can be achieved without changing the optical components of the microscope. Here, we demonstrate a mobile-phone-based LED array microscope to realize multimodal imaging with bright-field, dark-field, differential phase-contrast, and Rheinberg illuminations using as few as 37 LED bulbs. Using this microscope, we obtained high-contrast images of living cells. Furthermore, by changing the color combinations of Rheinberg illumination, we were able to obtain images of living chromatic structures with enhanced or diminished contrast. This technique is expected to be a foundation for high-contrast microscopy used in modern field studies.
The light emitting diode (LED) array microscope enables various multi-contrast imaging such as bright-field, dark- field and differential phase-contrast (DPC) by various illumination patterns without any expensive optical components. We built LED array microscopic system that enables us to obtain multi-contrast images with a smartphone camera. We demonstrate that a smartphone-based LED array microscope can acquire bright field, dark field, and DPC of cell by changing the numerical apertures of objective lenses.
Optical imaging through diffusive or scattering media has attracted much attention. Digital holographic microscopy provides quantitative phase imaging thorough diffusive media. We experimentally reconstruct intensity and phase images of an object through an opaque ground glass screen by means of digital holography. A clear image of the object is acquired by wavefield back propagation algorithm for the object with an information of a quantitative phase distribution of the diffusive screen measured in advance with the principle of the lensless digital holography.
The light emitting diode (LED) array microscope enables various multi-contrast imaging such as bright-field, darkfield and differential phase-contrast by various illumination patterns without any expensive optical components. We build an LED array microscopic system operated with Raspberry Pi. Illumination patterns are controlled with Raspberry Pi and images are obtained with a Raspberry Pi camera module. We demonstrate acquisition of bright-field, dark-field, and differential phase-contrast of cells.
When ultrashort laser pulses are focused inside a glass at a high repetition rate, structural changes occur because of the heat accumulation from the train of laser pulses. This report describes phase measurement of the structural changes induced inside glass by phase-shifting digital holographic microscopy. Two-dimensional phase distribution across the structural change for static exposure is retrieved. By focusing femtosecond laser pulses at the interface between two glass substrates, melted materials can directly weld glass plates. Quantitative phase measurement of welded glass substrates revealed that the refractive index decreased in the laser-irradiated zone.
Auto fluorescence distribution of coenzymes NADH and FAD is investigated for the unstained tumor detection using an [?] originally designed confocal spectroscope. The tumor region in digestive organ can be determined by evaluating the redox index which is defined as the raio of NADH and FAD concentration. However, the redox index is largely influenced by the presence of collagen in the submucosal layer because its auto fluorescence spectrum overlaps considerably with that of NADH. Therefore, it is necessary to know in advance the distribution of NADH, FAD, and collagen in the mucosal layer. The purpose of our study is to investigate the vertical distribution of the redox index in tissue using depth-sensitive auto fluorescence spectroscopy. The experimental procedure and the results are presented.
We present new near-infrared (NIR) imaging technique for analyzing the moisturizer drop dynamics on the human skin surface. From the measurement experiment for the vertical water content in the skin tissue and light transport simulation, it was clarified that imaging the skin tissue using 1950 nm band effectively visualizes the water distribution. We demonstrate the NIR imaging experiment using originally developed NIR microscopic water imaging system. The relationship between the moisturizer drop dynamics and the water condition of the skin tissue is also discussed.
Wavelength-dependent light penetration depth in the measurement of water distribution of the skin tissue is analyzed. Near-infrared (NIR) imaging enables 2-D water content map on the skin tissue because water absorbs light strongly in the NIR region particularly around the wavelengths of 1450 and 1920 nm. However, the depth of the light penetration depends largely on wavelength as the absorption coefficient of water changes considerably in the NIR range. We investigate the measurement depth of the water content mapping with a NIR camera and bandpass filters at the wavelengths of 1300, 1450 and 1920 nm. Analysis is performed with Monte Carlo light scattering simulation adopting the optical parameters which is derived from the depth profile of the water contents measured by the confocal Raman spectroscopy. It is found that the NIR image in 1920 nm gives the highest sensitivity to the water content in the surface layer of the skin tissue.
Two-dimensional distribution of oxygen saturation levels across the human retina is predicted by measuring the multispectral images. A liquid crystal tunable filter is used to scan wavelength ranging from 500 to 700 nm to acquire the multispectral images with the spectral resolution of 20 nm. After preprocessing reflected spectra at every pixel to cancel common offsets and amplifications, the partial least squares regression is adopted to estimate the oxygen saturation levels at each pixel point. All the resulted response values compose the oxygen saturation level map. The effects of preprocessing types on the predicted oxygen saturation levels are also discussed.
Predicting concentrations of aqueous glucose solutions using reduced wavelength components is presented. The wavelengths are selected based on the second derivative of the near-infrared absorbance spectra. In the demonstration of the temperature-insensitive partial least squares analysis, good agreement between actual glucose concentrations and predicted values is verified.
The study on the magnitude of spectral change in blood glucose measurements with diffuse reflectance NIR spectroscopy is presented. Spectral change is estimated by a Monte Carlo simulation and measurements of absorbance spectra of aqueous glucose solution. Required sensitivity of spectrophotometers for monitoring the changein the blood glucose concentration as small as 10mg/dL has been obtained using the estimated change in the absorbance spectrum and mean pathlength of light in tissue.
A computed three-dimensional (3-D) displaying system based on integral imaging is presented. The 3-D image is reconstructed by numerical processing of an optically observed image array formed by a micro-lens array. The algorithm to reconstruct 3-D images is simple, and it enables us to obtain the images viewed from arbitrary directions. The computer-based image retrieval makes it possible to improve quality of the image such as contrast, brightness, and resolution. In this presentation, we show the experimental results of the 3-D image reconstruction to test and verify the performance of the algorithms.
Interferometric 3D imaging based on measuring the space- variant cross-spectral density propagated in free space is reviewed. The spatial coherence function such as the cross- spectral density or the mutual intensity conserves the total 3D information as propagating in free space. The present method is on the basis of the propagation law of the cross- spectral density described in the Fourier domain. By using this law, the cross-spectral density across an arbitrary transverse plane is retrieved from the cross-spectral density measured on the observation plane. A series of retrieved cross-spectral densities composes the 3D intensity distribution. An experimental retrieval of the intensity distribution is demonstrated by using uncorrelated two point sources. A similarity of a point spread function of the present interferometric imaging system to an ordinary image forming system is also discussed.
New imaging method based on measuring the spatial coherence function across an observation area is presented. The propagation law of the cross-spectral density described in the Fourier domain allows us to retrieve the cross-spectral density at arbitrary reference planes. The method can be applied to a source of any state of coherence. Results of the experimental demonstration are also shown.
A new method for retrieving the three-dimensional image is proposed. The method is on the basis of the propagation law of the cross-spectral density and the relationship between the cross-spectral density and the generalized radiance. The image is obtained in terms of the spatial distribution of the generalized radiance. Results of numerically calculated examples are also shown.
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