Near-Infrared Super Resolution Imaging with Metallic Nanoshell Particle Chain Array

We propose a near-infrared super resolution near field imaging system with an array of metallic nanoshell particle chain. The imaging array can plasmonically transfer the near field components of dipole sources and the super resolution images can be reconstructed in the output plane. By decreasing the metallic nanoshell’s thickness of the fixed size nanoparticle, the plasmon resonance wavelength of the isolate nanoshell particle is red-shifted to the near-infrared region. The operation wavelength of the imaging array is correspondingly red-shifted to the near-infrared region. In this paper, we study the incoherent and coherent super resolution imaging. The field intensity distributions at the different planes of imaging process are calculated using the finite element method. The simulation results demonstrate that the array has super resolution imaging capability at near-infrared wavelengths in the incoherent and coherent manners. The results also show that the image formation highly depends on the source coherence. In the same structural parameters, the reconstructed images under the illumination of incoherent light source reach to the higher image quality and spatial resolution than the images under the illumination of coherent light source of in phase. By reasonably designing parameters of the imaging array, the approximate spatial resolutions of λ/13 in incoherent case and λ/10 in coherent case are obtained at the near-infrared wavelength of 764 nm. Furthermore, the image–array distance and the chains’ spacing also affect the image reconstruction.     

Software for quantitation and visualization of expression array data

Software is described that facilitates the analysis of phosphoimages from large array hybridizations. The Macintosh PowerPC-compatible application and its manual are available at no charge from http:?people.bu.edu/strehlow. The software is compatible with both custom formats and array filters from three commercial manufacturers. It allows the rapid quantitation of every spot on images of hybridizations to large arrays. The user drags grids of squares over the spots on the image to define the coordinates of each spot, then aligns and edits the position of the grid. The software then corrects the positions as necessary and quantitates up to 27,000 spots per image. It stores the numerical values for each signal in a format called the fingerprint file. Fingerprint files can be directly averaged or compared, allowing the user to find mean values or differences in data from independent hybridization experiments. Data can be recalled from the fingerprint file and can be output in a variety of spreadsheet formats with several options for background correction. Finally, the software offers an output format that allows the convenient visualization of data points using animated, three-dimensional graphs.     

Use of signal quality measurements to gain efficiency in the analysis of cDNA microarray data

This research provides a new way to measure error in microarray data in order to improve gene expression analysis.Microarray data contains many sources of error.In order to glean information about mRNA expression levels,the true signal must first be segregated from noise.This research focuses on the variation that can be captured at the spot level in cDNA microarray images.Variation at other levels,due to differences at the array,dye,and block levels,can be corrected for by a variety of existing normalization procedures.Two signal quality estimates that capture the reliability of each spot printed on a microarray are described.A parametric estimate of within-spot vari ance,referred to here as σ s2pot,assumes that pixels follow a normal distribution and are spatially correlated.A non-parametric estimate of error,called the mean square prediction error(MSPE),assumes that spots of high quality possess pixels that are similar to their neighbors.This paper will provide a framework to use either spot quality measure in downstream analysis,specifically as weights in regression models.Using these spot quality estimates as weights can result in greater efficiency,in a statistical sense,when modeling microarray data.     

Use of signal quality measurements to gain efficiency in the analysis of cDNA microarray data

This research provides a new way to measure error in microarray data in order to improve gene expression analysis.Microarray data contains many sources of error.In order to glean information about mRNA expression levels,the true signal must first be segregated from noise.This research focuses on the variation that can be captured at the spot level in cDNA microarray images.Variation at other levels,due to differences at the array,dye,and block levels,can be corrected for by a variety of existing normalizati...     

Strain imaging with intravascular ultrasound array scanners: validation with phantom experiments.

Intravascular Ultrasound (IVUS) is routinely used in interventional cardiology for imaging coronary plaque morphology. However, the use of B-mode images for tissue characterization and detection of vulnerable coronary plaques is limited. Strain imaging with ultrasound is a new modality that provides additional information for tissue characterization by imaging differences in tissue stiffness. The aim is to differentiate between vulnerable (soft) plaques and less dangerous calcified (hard) plaques. In this work, the applicability of a time efficient strain imaging algorithm in conjunction with data from IVUS array transducers is evaluated. Unfocused radiofrequency (rf) data from the transducer array is acquired using custom made hardware. Rf line reconstruction is performed offline by synthetic aperture focusing techniques. Vessel mimicking phantoms of different geometries and material stiffness are made from agar and Polyvinyl Alcohol Cryogel (PVA). Experiments are conducted in a water tank and a water column is used for applying intraluminal pressure differences required for strain imaging. The results show that strain images can be calculated with A-lines reconstructed from unfocused rf raw data. Regions of different stiffness can be identified qualitatively by local strain variations. With the used algorithm strains of up to 2% can be imaged without significant decor-relation.     

Use of signal quality measurements to gain efficiency in the analysis of cDNA microarray datacDNA microarray data

This research provides a new way to measure error in microarray data in order to improve gene expression analysis. Microarray data contains many sources of error. In order to glean information about mRNA expression levels, the true signal must first be segregated from noise. This research focuses on the variation that can be captured at the spot level in cDNA microarray images. Variation at other levels, due to differences at the array, dye, and block levels, can be corrected for by a variety of existing normalization procedures. Two signal quality estimates that capture the reliability of each spot printed on a microarray are described. A parametric estimate of within-spot variance, referred to here as σ²_spot, assumes that pixels follow a normal distribution and are spatially correlated. A non-parametric estimate of error, called the mean square prediction error (MSPE), assumes that spots of high quality possess pixels that are similar to their neighbors. This paper will provide a framework to use either spot quality measure in downstream analysis, specifically as weights in regression models. Using these spot quality estimates as weights can result in greater efficiency, in a statistical sense, when modeling microarray data.     

Fluorescence data analysis on gel-based biochips

A series of biochip readers developed for gel-based biochips includes three imaging models and a novel nonimaging biochip scanner. The imaging readers, ranging from a research-grade versatile reader to a simple portable one, use wide-field objectives and 12-bit digital large-coupled device cameras for parallel addressing of multiple array elements. This feature is valuable for monitoring the kinetics of sample interaction with immobilized probes. Depending on the model and the label used, the sensitivity of these readers approaches 0.3 amol of a labeled sample per gel element. In the selective scanner, both the spot size of the excitation laser beam and the detector field of view match the size of the biochip array elements so that the whole row of the array can be read in a single scan. The portable version reads 50-mm long, 150-element, one-dimensional arrays in 5 s. With a dynamic range of 4000:1, a sensitivity of 1-5 amol of a labeled sample per gel element, and a data format facilitating online processing, the scanner is an attractive, inexpensive solution for biomedical diagnostics. Fluorophores for sample labeling were compared experimentally in terms of detection sensitivity, influence on duplex stability, and suitability for multilabel analysis and thermodynamic studies. Texas Red and tetracarboxyphenylporphyn proved to be the best choice for two-wavelength analysis using the imaging readers.     

Neural adjustments to chromatic blur

The perception of blur in images can be strongly affected by prior adaptation to blurry images or by spatial induction from blurred surrounds. These contextual effects may play a role in calibrating visual responses for the spatial structure of luminance variations in images. We asked whether similar adjustments might also calibrate the visual system for spatial variations in color. Observers adjusted the amplitude spectra of luminance or chromatic images until they appeared correctly focused, and repeated these measurements either before or after adaptation to blurred or sharpened images or in the presence of blurred or sharpened surrounds. Prior adaptation induced large and distinct changes in perceived focus for both luminance and chromatic patterns, suggesting that luminance and chromatic mechanisms are both able to adjust to changes in the level of blur. However, judgments of focus were more variable for color, and unlike luminance there was little effect of surrounding spatial context on perceived blur. In additional measurements we explored the effects of adaptation on threshold contrast sensitivity for luminance and color. Adaptation to filtered noise with a 1/f spectrum characteristic of natural images strongly and selectively elevated thresholds at low spatial frequencies for both luminance and color, thus transforming the chromatic contrast sensitivity function from lowpass to nearly bandpass. These threshold changes were found to reflect interactions between different spatial scales that bias sensitivity against the lowest spatial grain in the image, and may reflect adaptation to different stimulus attributes than the attributes underlying judgments of image focus. Our results suggest that spatial sensitivity for variations in color can be strongly shaped by adaptation to the spatial structure of the stimulus, but point to dissociations in these visual adjustments both between luminance and color and different measures of spatial sensitivity.     

Compensated Row-Column Ultrasound Imaging System Using Fisher Tippett Multilayered Conditional Random Field Model

3-D ultrasound imaging offers unique opportunities in the field of non destructive testing that cannot be easily found in A-mode and B-mode images. To acquire a 3-D ultrasound image without a mechanically moving transducer, a 2-D array can be used. The row column technique is preferred over a fully addressed 2-D array as it requires a significantly lower number of interconnections. Recent advances in 3-D row-column ultrasound imaging systems were largely focused on sensor design. However, these imaging systems face three intrinsic challenges that cannot be addressed by improving sensor design alone: speckle noise, sparsity of data in the imaged volume, and the spatially dependent point spread function of the imaging system. In this paper, we propose a compensated row-column ultrasound image reconstruction system using Fisher-Tippett multilayered conditional random field model. Tests carried out on both simulated and real row-column ultrasound images show the effectiveness of our proposed system as opposed to other published systems. Visual assessment of the results show our proposed system’s potential at preserving detail and reducing speckle. Quantitative analysis shows that our proposed system outperforms previously published systems when evaluated with metrics such as Peak Signal to Noise Ratio, Coefficient of Correlation, and Effective Number of Looks. These results show the potential of our proposed system as an effective tool for enhancing 3-D row-column imaging.     

Software package for automatic microarray image analysis (MAIA)

Although various software solutions are currently available for microarray image analysis, one would still expect to develop algorithms ensuring higher level of intelligence and robustness. We present a fully functional software package for automatic processing of the two-color microarray images including spot localization, quantification and quality control. The developed algorithms aim at making ratio estimates more resistant to array contamination and offer automatic tools to evaluate spot quality. Availability: A demo version of the software can be downloaded from http://bioinfo.curie.fr/projects/maia. A full version is freely available to non-commercial users upon request from the authors.     

Fluorescence lifetime imaging in an optically sectioning programmable array microscope (PAM).

BACKGROUND: The programmable array microscopes (PAMs) are a family of instruments incorporating arbitrary control of the patterns of illumination and/or detection. The PAM can be used in sectioning and nonsectioning modes, thereby constituting a useful platform for fluorescence lifetime imaging. METHODS AND RESULTS: We used a PAM for acquisition of optically sectioned and widefield fluorescence lifetime images, in which contrast was increased predominantly by suppressing out-of-focus light contributions. We simulate, display, and discuss the effects of blurring and fluorophore heterogeneity on lifetime imaging in widefield and confocal configurations. CONCLUSION: Sectioning improves the quality of lifetime images of samples with multiple fluorophores or spatially varying F?rster resonance energy transfer.     

Broadband Mid-Infrared Super-Resolution Imaging with Metallic Nanorod-Bridged Dimer Array

We propose a broadband mid-infrared super-resolution imaging system comprising a metallic nanorod-bridged dimer array. The imaging array enables super-resolution imaging of shaped dipole sources in the near field. A charge transfer plasmon (CTP) appears in a metallic nanorod-bridged dimer. By varying the radius of the junction, the plasmon resonance wavelength of CTP mode can be tuned into the mid-infrared region. Here, we investigate the broadband super-resolution imaging of the incoherent and coherent dipole sources at mid-infrared wavelengths. With the array pitch varying, we calculate the cross-sectional field intensity distributions at the source plane and the image plane by using the finite element method. The simulation results indicate that the broadband incoherent and coherent super-resolution imaging can be realized at mid-infrared wavelengths with the imaging array. The image quality is sensitively dependent on the source coherent, the array pitch, and the distance from the image plane to the array. In the same structural parameters, the image quality of coherent source of in-phase is lower than that of incoherent source. Increasing the array pitch improves the image quality but it also increases the size of the array. By reasonably choosing the array pitch of the array, the spatial resolution of ～λ/109 and ～λ/73 is obtained corresponding to the incoherent imaging case and coherent imaging case at the mid-infrared wavelength of 4390 nm. Moreover, the larger image-array distance results in the lower image quality.     

High-performance confocal system for microscopic or endoscopic applications

We designed a high-performance confocal system that can be easily adapted to an existing light microscope or coupled with an endoscope for remote imaging. The system employs spatially and temporally patterned illumination produced by one of several mechanisms, including a micromirror array video projection device driven by a computer video source or a microlens array scanned by a piezo actuator in the microscope illumination path. A series of subsampled "component" video images are acquired from a solid-state video camera. Confocal images are digitally reconstructed using "virtual pinhole" synthetic aperture techniques applied to the collection of component images. Unlike conventional confocal techniques that raster scan a single detector and illumination point, our system samples multiple locations in parallel, with particular advantages for monitoring fast dynamic processes. We compared methods of patterned illumination and confocal image reconstruction by characterizing the point spread function, contrast, and intensity of imaged objects. Sample 3D reconstructions include a diatom and a Golgi-stained nerve cell collected in transmission.     

Full-field OCT

Optical coherence tomography (OCT) is an emerging technique for imaging of biological media with micrometer-scale resolution, whose most significant impact concerns ophthalmology. Since its introduction in the early 1990's, OCT has known a lot of improvements and sophistications. Full-field OCT is our original approach of OCT, based on white-light interference microscopy. Tomographic images are obtained by combination of interferometric images recorded in parallel by a detector array such as a CCD camera. Whereas conventional OCT produces B-mode (axially-oriented) images like ultrasound imaging, full-field OCT acquires tomographic images in the en face (transverse) orientation. Full-field OCT is an alternative method to conventional OCT to provide ultrahigh resolution images (approximately 1 microm), using a simple halogen lamp instead of a complex laser-based source. Various studies have been carried, demonstrating the performances of this technology for three-dimensional imaging of ex vivo specimens. Full-field OCT can be used for non-invasive histological studies without sample preparation. In vivo imaging is still difficult because of the object motions. A lot of efforts are currently devoted to overcome this limitation. Ultra-fast full-field OCT was recently demonstrated with unprecedented image acquisition speed, but the detection sensitivity has still to be improved. Other research directions include the increase of the imaging penetration depth in highly scattering biological tissues such as skin, and the exploitation of new contrasts such as optical birefringence to provide additional information on the tissue morphology and composition.     

Largest contour segmentation: a tool for the localization of spots in confocal images

An accurate determination of the 3-D positions of multiple spots in images obtained by confocal microscopy is essential for the investigation of the spatial distribution of specific components or processes in biological specimens. The position of the centroid, as an estimator for the position of a spot, can be calculated on the basis of all voxels that belong to the domain of the spot. For this calculation a domain that defines which voxels belong to the spot must be delimited. To create a boundary for a domain we developed a 3-D image segmentation procedure: the largest contour segmentation (LCS). This procedure is based on an iterative region-growing procedure around each local maximum of intensity. By means of this procedure the position of each spot was determined accurately and automatically. Qualities of the procedure were evaluated by means of simulated test-images as well as 3-D images of real biological specimens.     

Light sharing in multi-flat-panel-PMT PEM detectors

Large are a detectors, such as those used in positron emission mammography (PEM) and scintimammography, utilize arrays of discrete semtillator elements mounted on arrays of position sensitive photomultiplier tubes (PSPMT). Scintillator elements can be packed very densely (minimizing area between elements), allowing good detection sensitivity and spatial resolution. And, while new flat panel PSPMTS have minimal inactive edges, when they are placed in arrays significant dead spaces where scintillation light is undetectable are created. To address this problem, a light guide is often placed between the detector and PSPMT array to spread scintillation light so that these gaps can be bridged. In this investigation we studied the effect of light guides of various thickness on system performance. A 10×10 element array of LYSO detector elements was coupled to the center of a 2×2 array of PSPMTs through varying thicknesses (1 to 4 mm) of UV glass. The spot size of the imaged elements and distortions in the regular square pattern of the imaged scintillator arrays were evaluated. Energy resolution was measured by placing single elements of LYSO at several locations of the PSPMT array. Spatial distortions in the images of the array were reduced by using thicker light guides (3–4 mm). Use of thicker light guides, however, resulted in reduced pixel resolution and slight degradation of energy resolution. Therefore, some loss of pixel and energy resolution will accompany the use of thick light guides (minimum of 3 mm) required for optimum identification of detector elements.     

Using statistical image models for objective evaluation of spot detection in two-dimensional gels

Protein spot detection is central to the analysis of two-dimensional electrophoresis gel images. There are many commercially available packages, each implementing a protein spot detection algorithm. Despite this, there have been relatively few studies comparing the performance characteristics of the different packages. This is in part due to the fact that different packages employ different sets of user-adjustable parameters. It is also partly due to the fact that the images are complex. To carry out an evaluation, "ground truth" data specifying spot position, shape and intensities needs to be defined subjectively on selected test images. We address this problem by proposing a method of evaluation using synthetic images with unambiguous interpretation. The characteristics of the spots in the synthetic images are determined from statistical models of the shape, intensity, size, spread and location of real spot data. The distribution of parameters is described using a Gaussian mixture model obtained from training images. The synthetic images allow us to investigate the effects of individual image properties, such as signal-to-noise ratios and degree of spot overlap, by measuring quantifiable outcomes, e.g. accuracy of spot position, false positive and false negative detection. We illustrate the approach by carrying out quantitative evaluations of spot detection on a number of widely used analysis packages.     

Surface plasmon resonance imaging-based protein arrays for high-throughput screening of protein-protein interaction inhibitors

The E7 protein produced by high-risk human papillomavirus (HPV) induces a degradation of the retinoblastoma tumor suppressor RB through direct interaction, which suggests that an inhibitor for the interaction can be a potential anticancer drug. A surface plasmon resonance (SPR) imaging-based protein array chip was developed for the high-throughput screening of inhibitor molecules targeting RB-E7 interaction. The glutathione S-transferase-fused E7 protein (GST-E7) was first layered onto a glutathionylated gold chip surface that had been designed to specifically bind to GST-fused proteins. Subsequently, a microarrayer was used to spot the hexa-histidine-tagged RB proteins (His(6)-RB) onto the GST-E7-layered gold chip surface, and the resulting SPR image was analyzed. Upon increased His(6)-RB concentration in the spotting solution, the SPR signal intensity increased proportionally, indicating that His(6)-RB bound to GST-E7 in a concentration-dependent manner. The His(6)-RB/GST-E7 interaction was challenged by spotting the His(6)-RB solution in the presence of a RB binding peptide (PepC) derived from a motif on E7. The SPR imaging data showed that PepC inhibited the His(6)-RB/GST-E7 interaction in a concentration-dependent manner. Our results show that the SPR imaging-based protein array chip can be applied to screen small molecule inhibitors that target protein-protein interaction.     

Plasmonic Lens with Multiple-Turn Spiral Nano-Structures

In this paper, we investigate the focusing properties of a plasmonic lens with multiple-turn spiral nano-structures, and analyze its field enhancement effect based on the phase matching theory and finite-difference time-domain simulation. The simulation result demonstrates that a left-hand spiral plasmonic lens can concentrate an incident right-hand circular polarization light into a focal spot with a high focal depth. The intensity of the focal spot could be controlled by altering the number of turns, the radius and the width of the spiral slot. And the focal spot is smaller and has a higher intensity compared to the incident linearly polarized light. This design can also eliminate the requirement of centering the incident beam to the plasmonic lens, making it possible to be used in plasmonic lens array, optical data storage, detection, and other applications.     

High Fidelity System Modeling for High Quality Image Reconstruction in Clinical CT

Today, while many researchers focus on the improvement of the regularization term in IR algorithms, they pay less concern to the improvement of the fidelity term. In this paper, we hypothesize that improving the fidelity term will further improve IR image quality in low-dose scanning, which typically causes more noise. The purpose of this paper is to systematically test and examine the role of high-fidelity system models using raw data in the performance of iterative image reconstruction approach minimizing energy functional. We first isolated the fidelity term and analyzed the importance of using focal spot area modeling, flying focal spot location modeling, and active detector area modeling as opposed to just flying focal spot motion. We then compared images using different permutations of all three factors. Next, we tested the ability of the fidelity terms to retain signals upon application of the regularization term with all three factors. We then compared the differences between images generated by the proposed method and Filtered-Back-Projection. Lastly, we compared images of low-dose in vivo data using Filtered-Back-Projection, Iterative Reconstruction in Image Space, and the proposed method using raw data. The initial comparison of difference maps of images constructed showed that the focal spot area model and the active detector area model also have significant impacts on the quality of images produced. Upon application of the regularization term, images generated using all three factors were able to substantially decrease model mismatch error, artifacts, and noise. When the images generated by the proposed method were tested, conspicuity greatly increased, noise standard deviation decreased by 90% in homogeneous regions, and resolution also greatly improved. In conclusion, the improvement of the fidelity term to model clinical scanners is essential to generating higher quality images in low-dose imaging.