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Detection of microscopic fission track (FT) star-shaped clusters, developed in a solid state nuclear track detector (SSNTD) by etching, created by fission fragments emitted from particles of fissile materials irradiated by neutrons, is a key technique in nuclear forensics and safeguards investigation. It involves scanning and imaging of a large area, typically 100–400 mm2, of a translucent SSNTD (e.g., polycarbonate sheet, mica, etc.) to identify the FT clusters, sparse as they may be, that must be distinguished from dirt and other artifacts present in the image. This task, if done manually, is time consuming, operator dependent, and prone to human errors. To solve this problem, an automated workflow has been developed for (a) scanning large area detectors, in order to acquire large images with adequate high resolution, and (b) processing the images with a scheme, implemented in ImageJ, to automatically detect the FT clusters. The scheme combines intensity-based segmentation approaches with a morphological algorithm capable of detecting and counting endpoints in putative FT clusters in order to reject non-FT artifacts. In this paper, the workflow is described, and very promising preliminary results are shown.

Optical sectioning microscopy can provide highly detailed three dimensional (3D) images of biological samples. However, it requires acquisition of many images per volume, and is therefore time consuming, and may not be suitable for live cell 3D imaging. We propose the use of the modified Gerchberg-Saxton phase retrieval algorithm to enable full 3D imaging of gold nanoparticles tagged sample using only two images. The reconstructed field is free space propagated to all other focus planes using post processing, and the 2D z-stack is merged to create a 3D image of the sample with high fidelity. Because we propose to apply the phase retrieving on nano particles, the regular ambiguities typical to the Gerchberg-Saxton algorithm, are eliminated. The proposed concept is then further enhanced also for tracking of single fluorescent particles within a three dimensional (3D) cellular environment based on image processing algorithms that can significantly increases localization accuracy of the 3D point spread function in respect to regular Gaussian fitting. All proposed concepts are validated both on simulated data as well as experimentally.

This work presents a technique for a full 3D imaging of biological samples tagged with gold-nanoparticles (GNPs) using only two images, rather than many images per volume as is currently needed for 3D optical sectioning microscopy. The proposed approach is based on the Gerchberg-Saxton (GS) phase retrieval algorithm. The reconstructed field is free space propagated to all other focus planes using post processing, and the 2D z-stack is merged to create a 3D image of the sample with high fidelity. Because we propose to apply the phase retrieving on nano particles, the regular ambiguities typical to the Gerchberg-Saxton algorithm, are eliminated. In addition, since the method requires the capturing of two images only, it can be suitable for 3D live cell imaging. The proposed concept is presented and validated both on simulated data as well as experimentally.

The ability to track single fluorescent particles within a three dimensional (3D) cellular environment can provide valuable insights into cellular processes. In this paper, we present a modified nonlinear image decomposition technique called K-factor that reshapes the 3D point spread function (PSF) of an XYZ image stack into a narrow Gaussian profile. The method increases localization accuracy by ~60% with compare to regular Gaussian fitting, and improves minimal resolvable distance between overlapping PSFs by ~50%. The algorithm was tested both on simulated data and experimentally. This work presets a novel use of the nonlinear image decomposition technique called K-factor that reshapes the three dimensional (3D) point spread function (PSF) of an XYZ image stack into a narrow Gaussian profile. The experimentally obtained PSF of a Z-stack raw data that is acquired by a widefield microscope has a more elaborate shape that is given by the Gibson and Lanni model. This shape increases the computational complexity associated with the localization routine, when used in localization microscopy techniques. Furthermore, due to its nature, this PSF spreads over a larger volume, making the problem of overlapping emitters detection more pronounced. The ability to use Gaussian fitting with high accuracy on 3D data can facilitate the computational complexity, hence reduce the processing time required for the generation of the 3D superresolved image. In addition it allows the detection of overlapping PSFs and reduces the effects of the penetration of out of focus PSFs into in focused PSFs, therefore enables the increase in the activated fluorophore density by ~50%. The algorithm was tested both on simulated data and experimentally, where it yielded an increase in the localization accuracy by ~60% with compare to regular Gaussian fitting, and improved the minimal resolvable distance between overlapping PSFs by ~50%, making it extremely applicable to the field of 3D biomedical imaging

A new approach aimed to achieve microscopic imaging without objective lenses and based on wavelength multiplexing of the spatial object information is presented. The proposed method is used to develop, construct and experimentally validate a new type of optical microscope having no objective lens and no numerical reconstruction algorithms to allow imaging process. In order to extract the collected spatial information we use a spectrometer as part of our microscope system. Preliminary results are presented while considering two different types of one-dimensional (1-D) objects.

Optical sectioning microscopy can provide highly detailed three dimensional (3D) images of biological samples. However, it requires acquisition of many images per volume and is therefore time consuming and may not be suitable for live cell 3D imaging. We propose the use of the modified Gerchberg-Saxton phase retrieval algorithm to enable full 3D imaging of gold-particle tagged samples using only two images. The reconstructed field is free space propagated to all other focus planes using post processing and the 2D z-stack is merged to create a 3D image of the sample with high fidelity. Because we propose to apply the phase retrieving on nano particles, the regular ambiguities typical to the Gerchberg-Saxton algorithm, are eliminated. The proposed concept is presented and validated both on simulated data as well as experimentally.

Fluorescence photobleaching was measured in dye-impregnated sol–gel/polymer composite glasses. These fluorescent glasses were used as the gain medium in a transverse-pumped solid-state dye laser. In this configuration, the fluorescent glass was excited by a pulsed Nd:YAG laser (about 6 mJ/pulse) either while placed in an optical cavity (i.e., functioning as a pulsed laser) or with the optical cavity blocked, so that lasing did not occur. The decay of the fluorescence signal versus cumulative excitation energy was recorded. We found that the rate of photobleaching decreased when the glass was lasing, as compared to the case where the optical cavity was blocked. This paper presents these results, and suggests a simple kinetic model that may explain this phenomenon.

The microwave-assisted polyol reduction method was applied to the preparation of CdSe “nanoballs”. The cubic and hexagonal forms of the CdSe nanoparticles obtained were analyzed by XRD, TEM, HRTEM, UV-VIS, photoluminescence (PL) and photoacoustic spectroscopy. Formation of the hexagonal or cubic form of CdSe depends on the glycol used for reaction. It was found that “nanoballs” are built-up of clusters of CdSe with sizes of a few nanometers. A strong blue shift is observed in the absorption spectrum, as expected for size quantization. A possible reaction mechanism is provided.

Multiplexed imaging and illumination have been used to recover enhanced arrays of intensity or spectral reflectance samples, per pixel. However, these arrays are often not the ultimate goal of a system, since the intensity is a result of underlying object characteristics, which interest the user. For example, spectral reflectance, emission or absorption distributions stem from an underlying mixture of materials. Therefore, systems try to infer concentrations of these underlying mixed components. Thus, computational analysis does not end with recovery of intensity (or equivalent) arrays. Inversion of mixtures, termed unmixing, is central to many problems. We incorporate the mixing/unmixing process explicitly into the optimization of multiplexing codes. This way, optimal recovery of the underlying components (materials) is directly sought. Without this integrated approach, multiplexing can even degrade the unmixing result. Moreover, by directly defining the goal of data acquisition to be recovery of components (materials) rather than of intensity arrays, the acquisition becomes more efficient. This yields significant generalizations of multiplexing theory. We apply this approach to fluorescence imaging.

Phase retrieval is a well-established method for the recovery of an object wave from its magnitude-only measurements, with applications in fields such as material science, biology, and astronomy. In order to guarantee a stable and global solution for phase retrieval, measurement diversity is frequently used. However, this process requires taking several measurements, which hinders some of the advantages of phase retrieval compared with interferometric techniques. Here we propose a novel diversity framework that we refer to as digital resampling diversity. The proposed resampling diversity along with sparsity-constrained object reconstruction enables improved object reconstruction from a single squared magnitude image, without using object support constraint. We demonstrate this framework with simulation and experimental results.

In this paper, we present a new approach providing super resolved images exceeding the geometrical limitation given by the detector pixel size of the imaging camera. The concept involves the projection of periodic patterns on top of the sample, which are then investigated under a microscope. Combining spatial scanning together with proper digital post-processing algorithm yields the improved geometrical resolution enhancement. This new method is especially interesting for microscopic imaging when the resolution of the detector is lower than the resolution due to diffraction.

In this manuscript we present a novel super resolving approach based upon projection of a random speckle pattern onto samples observed through a microscope. The projection of the speckle pattern is created by coherent illumination of the inspected pattern through a diffuser. Due to local interference of the coherent wave front with itself, a random speckle pattern is superimposed on the sample. This speckle pattern can be scanned over the object. A super-resolved image can be extracted from a temporal sequence of images by appropriate digital processing of the image stream. The resulting resolution is significantly higher than the diffraction limitation of the microscope objective. The new super-resolution method is demonstrated by application to fluorescence of biological samples.

Tunable solid-state dye lasers can be prepared by incorporation of the dye during sol-gel formation. The current work presents measurements of dye photostability which were taken during laser operation over an extended time.. Fluorescence decay (photobleaching) rate was compared for the case of laser operation to the case where laser operation was suppressed, using identical excitation geometries. In addition, the confocal photobleaching experiments were repeated, using sol-gel glass, composite glass/polymer, and PMMA polymer host matrices.

A photoacoustic spectrometer is described which has been constructed to measure the spectra of photovoltaic materials in the ultra violet, visible and near infra red regions. The range of this photoacoustic spectrometer is from 0.3 to 1.8 micrometers. This technique has the advantage of being non- intrusive and non-destructive. Measurements have been made of a variety of photovoltaic materials, including a CdS/CuIn 1- x Ga x Se 2 heterojunction and an InP/InGaAsP quantum well layer system. Bands arising from intrinsic impurity subgap levels were observed beyond the band edges.

A novel two dimensional optical position sensor based on confinement of luminescence within a flat panel is described. The basis of the sensor is a flat luminescent panel, such as those used in luminescent solar energy concentrators. In these concentrators, a glass or plastic plate is either coated or impregnated with a fluorescent material. The incident radiation produces luminescent emission, much of which is confined within the plate through total internal reflection, and is thus guided to solar cells which line the thin edges of the plate. In order to use such plates as a position sensor, four photodiodes are placed along two orthogonal axes at the edges of the plate, and the plate is illuminated with a spot of light. The spot of light induces luminescence, which is detected by the four photodiodes. The photodiodes' output is processed to provide position information. Large area position sensors based on the above idea were constructed, using fluorescent plexiglass which was obtained from commonly available fluorescent clipboards. The photodiode output was combined using a self-normalizing function to eliminate sensitivity to non-uniformity in the optical characteristics of the fluorescent plates. This paper presents the results obtained to date, together with suggestions for further improvement in the sensor based on these results.

Quantitative digital microscopy and analysis of fluorescence gels are examples of applications where images are acquired, usually with a video camera and frame grabber, for further processing and analysis. The use of a standard video camera and frame grabber creates problems in the subsequent data analysis, due to the nonlinear relation between the camera output and the optical input, and due to pixel jitter. In addition, the data are degraded by conversion to a standard video format followed by sampling at a rate determined by the frame grabber's image memory. In this work, an image processing workstation is described which uses a low cost ($850) 8-bit digital CCD camera in place of the video camera/frame grabber combination. The system has excellent linearity and high dynamic range. Proper setup and calibration of this system is essential, and procedures which were developed for this purpose are described. The results which were obtained are compared to those of a standard video camera. The tradeoffs involved in the use of this low cost system are discussed, and examples of data obtained with the system are presented. Although this system cannot replace a 12-bit or 16-bit digital camera in all applications, it can do so in many applications, at a price that makes widespread use of image quantitation systems practical.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

A novel two dimensional optical position sensor based on confinement of luminescence within a flat panel is described. The basis of the sensor is a flat luminescent panel, such as those used in luminescent solar energy concentrators. In these concentrators, a glass or plastic plate is either coated or impregnated with a fluorescent material. The incident radiation produces luminescent emission, much of which is confined within the plate through total internal reflection, and is thus guided to solar cells which line the thin edges of the plate. In order to use such a plate as a position sensor, four detectors are placed along two orthogonal axes at the edges of the plate, and the plate is illuminated with a spot of light. The spot of light induces luminescence, which is detected by the four detectors. The detectors' output is processed to provide position information. Position sensors based on the above idea were constructed, using both microscope slides coated with a fluorescent dye, and poly(methyl methacrylate) plates which were cast in the presence of a fluorescent dye so that they exhibited fluorescence throughout their volume. The results showed that the detector output varied monotonically with position. This paper presents the results obtained to date, together with a theory which relates the detector output to position. Suggestions for the improvement of the sensor, particularly in the areas of materials processing and sensor geometry, are provided.

A necessary part of digital image processing is segmentation of the images into a set of objects which exist on some background. We are interested in a class of objects whose distinguishing characteristic is their color. Such objects occur in many applications, such as microscopy, printing, production line monitoring, etc. In this work, a general method of rapid color-based segmentation is presented. The only hardware requirement is that look up tables (LUT) be available. Most image processing hardware contains either LUTs or processors capable of rapidly performing table lookup. The method presented allows simultaneous application of constraints on both hue and saturation. In addition, it allows for use of different color transformations. As such, it constitutes a general approach to analysis of images consisting of three spectral components. Because of the speed of LUT operations, this approach is suitable for many applications which are time sensitive. The major drawback of using LUTs is that the gray level resolution per color is limited by the size of the LUT. This method was implemented on a Matrox MVP-AT image processor, which is capable of processing 12 bit images (4 bits/color). In many cases, this resolution is adequate, as can be seen from examples which are presented.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.