High-resolution restoration of 3D structures from widefield images with extreme low signal-to-noise-ratio

Four-dimensional fluorescence microscopy-which records 3D image information as a function of time-provides an unbiased way of tracking dynamic behavior of subcellular components in living samples and capturing key events in complex macromolecular processes. Unfortunately, the combination of phototoxicity and photobleaching can severely limit the density or duration of sampling, thereby limiting the biological information that can be obtained. Although widefield microscopy provides a very light-efficient way of imaging, obtaining high-quality reconstructions requires deconvolution to remove optical aberrations. Unfortunately, most deconvolution methods perform very poorly at low signal-to-noise ratios, thereby requiring moderate photon doses to obtain acceptable resolution. We present a unique deconvolution method that combines an entropy-based regularization function with kernels that can exploit general spatial characteristics of the fluorescence image to push the required dose to extreme low levels, resulting in an enabling technology for high-resolution in vivo biological imaging.

Image reconstruction enables high resolution imaging at large penetration depths in fluorescence microscopy

Imaging thick specimen at a large penetration depth is a challenge in biophysics and material science. Refractive index mismatch results in spherical aberration that is responsible for streaking artifacts, while Poissonian nature of photon emission and scattering introduces noise in the acquired three-dimensional image. To overcome these unwanted artifacts, we introduced a two-fold approach: first, point-spread function modeling with correction for spherical aberration and second, employing maximum-likelihood reconstruction technique to eliminate noise. Experimental results on fluorescent nano-beads and fluorescently coated yeast cells (encaged in Agarose gel) shows substantial minimization of artifacts. The noise is substantially suppressed, whereas the side-lobes (generated by streaking effect) drops by 48.6% as compared to raw data at a depth of 150 mu m. Proposed imaging technique can be integrated to sophisticated fluorescence imaging techniques for rendering high resolution beyond 150 mu m mark. (C) 2013 AIP Publishing LLC.

The upper Bay of Bengal salinity structure in a high-resolution model

Salinity in the Bay of Bengal is highly heterogeneous, with extremely fresh waters found at the surface in the Northern part of the basin, and saltier waters at subsurface as well as to the south. This paper investigates the seasonal structure of sea surface salinity of the Bay in a regional high-resolution model forced by ERA-Interim reanalysis and various precipitation products. Surface circulation is believed to drive the spreading of northern Bay of Bengal fresh waters to the rest of the Indian Ocean. We first present a series of experiments to infer the sensitivity of modeled circulation to various numerical choices. Surface circulation is found to be sensitive to the horizontal resolution of the model, with the 1/12 degrees version appearing much more realistic than the 1/4 degrees version. The sidewall boundary condition is also drastically influencing the characteristics of the western boundary current simulated. We then investigate the sensitivity of the salinity response to the various precipitation products. We observe that ERA-Interim excess precipitation induces a fresh bias in the surface salinity response. Spaceborne precipitation products are more satisfactory. We then identify the pathways of the northern Bay freshwater mass, based on passive tracers experiments. Our model suggests that over timescales of a few months, vertical exchanges between the upper fresh layer and the underlying saltier layer appear to be the main export pathway for the freshwater. The horizontal circulation within the mixed layer also acts to convey fresh waters out of the Bay at these timescales, but in a lesser quantity compared to the vertical export. Beyond its intrinsic interest for the understanding of Bay of Bengal physics, this study highlights the need for a careful design of any realistic numerical model, in three key aspects: the choice of the resolution of the model, the choice of the sub-grid scale parameterizations, and the choice of the forcing fluxes. (C) 2013 Elsevier Ltd. All rights reserved.

Improving tangential resolution with a modified delay-and-sum reconstruction algorithm in photoacoustic and thermoacoustic tomography

Spatial resolution in photoacoustic and thermoacoustic tomography is ultrasound transducer (detector) bandwidth limited. For a circular scanning geometry the axial (radial) resolution is not affected by the detector aperture, but the tangential (lateral) resolution is highly dependent on the aperture size, and it is also spatially varying (depending on the location relative to the scanning center). Several approaches have been reported to counter this problem by physically attaching a negative acoustic lens in front of the nonfocused transducer or by using virtual point detectors. Here, we have implemented a modified delay-and-sum reconstruction method, which takes into account the large aperture of the detector, leading to more than fivefold improvement in the tangential resolution in photoacoustic (and thermoacoustic) tomography. Three different types of numerical phantoms were used to validate our reconstruction method. It is also shown that we were able to preserve the shape of the reconstructed objects with the modified algorithm. (C) 2014 Optical Society of America

Model-Resolution-Based Basis Pursuit Deconvolution Improves Diffuse Optical Tomographic Imaging

The image reconstruction problem encountered in diffuse optical tomographic imaging is ill-posed in nature, necessitating the usage of regularization to result in stable solutions. This regularization also results in loss of resolution in the reconstructed images. A frame work, that is attributed by model-resolution, to improve the reconstructed image characteristics using the basis pursuit deconvolution method is proposed here. The proposed method performs this deconvolution as an additional step in the image reconstruction scheme. It is shown, both in numerical and experimental gelatin phantom cases, that the proposed method yields better recovery of the target shapes compared to traditional method, without the loss of quantitativeness of the results.

High-Resolution Solid State C-13 NMR Studies of Bent-Core Mesogens of Benzene and Thiophene

Bent-core mesogens are an important class of thermotropic liquid crystals as they exhibit unusual properties as well as morphologies distinctly different from rodlike mesogens. Two bent-core mesogens with differing center rings namely benzene and thiophene are considered and investigated using high-resolution oriented solid state C-13 NMR method in their liquid crystalline phases. The mesogens exhibit different phase sequences with the benzene-based mesogen showing a B-1 phase, while the one based on thiophene showing nematic and smectic C phases. The 2-dimensional separated local field (2D-SLF) NMR method was used to obtain the C-13-H-1 dipolar couplings of carbons in the center ring as well as in the side-wing phenyl rings. Couplings, characteristic of the type of the center ring, that also provide orientational information on the molecule in the magnetic field were observed. Together with the dipolar couplings of the side-wing phenyl ring carbons from which the local order parameters of the different subunits of the core could be extracted, the bent angle of the mesogenic molecule could be obtained. Accordingly, for the benzene mesogen in its B-1 phase at 145 degrees C, the center ring methine C-13-H-1 dipolar couplings were found to be significantly larger (9.5-10.2 kHz) compared to those of the side-wing rings (1.6-2.1 kHz). From the local order parameter values of the center (0.68) as well as the side-wing rings (0.50), a bent-angle of 130.3 degrees for this mesogen was obtained. Interestingly, for the thiophene mesogen in its smectic C phase at 210 degrees C, the C-13-H-1 dipolar coupling of the center ring methine carbon (2.11 kHz) is smaller than those of the side-wing phenyl ring carbons (2.75-3.00 kHz) which is a consequence of the different structures of the thiophene and the benzene rings. These values correspond to local order parameters of 0.85 for the center thiophene ring and 0.76 for the first side-wing phenyl ring and a bent-angle of 149.2 degrees. Thus, the significant differences in the dipolar couplings and the order parameter values between different parts in the rigid core of the mesogens are a direct consequence of the nature of the center ring and the bent structure of the molecule. The present investigation thus highlights the ability of the C-13 2D-SLF technique to provide the geometry of the bent-core mesogens in a straightforward manner through the measurement of the C-13-H-1 dipolar couplings.

Super-Resolution Reconstruction in Frequency-Domain Optical-Coherence Tomography Using the Finite-Rate-of-Innovation Principle

The standard approach to signal reconstruction in frequency-domain optical-coherence tomography (FDOCT) is to apply the inverse Fourier transform to the measurements. This technique offers limited resolution (due to Heisenberg's uncertainty principle). We propose a new super-resolution reconstruction method based on a parametric representation. We consider multilayer specimens, wherein each layer has a constant refractive index and show that the backscattered signal from such a specimen fits accurately in to the framework of finite-rate-of-innovation (FRI) signal model and is represented by a finite number of free parameters. We deploy the high-resolution Prony method and show that high-quality, super-resolved reconstruction is possible with fewer measurements (about one-fourth of the number required for the standard Fourier technique). To further improve robustness to noise in practical scenarios, we take advantage of an iterated singular-value decomposition algorithm (Cadzow denoiser). We present results of Monte Carlo analyses, and assess statistical efficiency of the reconstruction techniques by comparing their performance against the Cramer-Rao bound. Reconstruction results on experimental data obtained from technical as well as biological specimens show a distinct improvement in resolution and signal-to-reconstruction noise offered by the proposed method in comparison with the standard approach.

High resolution light-sheet based high-throughput imaging cytometry system enables visualization of intra-cellular organelles

Visualization of intracellular organelles is achieved using a newly developed high throughput imaging cytometry system. This system interrogates the microfluidic channel using a sheet of light rather than the existing point-based scanning techniques. The advantages of the developed system are many, including, single-shot scanning of specimens flowing through the microfluidic channel at flow rate ranging from micro-to nano- lit./min. Moreover, this opens-up in-vivo imaging of sub-cellular structures and simultaneous cell counting in an imaging cytometry system. We recorded a maximum count of 2400 cells/min at a flow-rate of 700 nl/min, and simultaneous visualization of fluorescently-labeled mitochondrial network in HeLa cells during flow. The developed imaging cytometry system may find immediate application in biotechnology, fluorescence microscopy and nano-medicine. (C) 2014 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.

Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data

Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged derision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 x 10(6) km(2)), mean annual maximum (12.1 x 10(6) km(2)), and long-term maximum (173 x 10(6) km(2)); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations. (C) 2014 Elsevier Inc All rights reserved.

The Relationship Between Solar Coronal X-Ray Brightness and Active Region Magnetic Fields: A Study Using High-Resolution Hinode Observations

By using high-resolution observations of nearly co-temporal and co-spatial Solar Optical Telescope spectropolarimeter and X-Ray Telescope coronal X-ray data onboard Hinode, we revisit the problematic relationship between global magnetic quantities and coronal X-ray brightness. Co-aligned vector magnetogram and X-ray data were used for this study. The total X-ray brightness over active regions is well correlated with integrated magnetic quantities such as the total unsigned magnetic flux, the total unsigned vertical current, and the area-integrated square of the vertical and horizontal magnetic fields. On accounting for the inter-dependence of the magnetic quantities, we inferred that the total magnetic flux is the primary determinant of the observed integrated X-ray brightness. Our observations indicate that a stronger coronal X-ray flux is not related to a higher non-potentiality of active-region magnetic fields. The data even suggest a slightly negative correlation between X-ray brightness and a proxy of active-region non-potentiality. Although there are small numerical differences in the established correlations, the main conclusions are qualitatively consistent over two different X-ray filters, the Al-poly and Ti-poly filters, which confirms the strength of our conclusions and validate and extend earlier studies that used low-resolution data. We discuss the implications of our results and the constraints they set on theories of solar coronal heating.

Super Resolution Using a Single Image Dictionary

To perform super resolution of low resolution images, state-of-the-art methods are based on learning a pair of lowresolution and high-resolution dictionaries from multiple images. These trained dictionaries are used to replace patches in lowresolution image with appropriate matching patches from the high-resolution dictionary. In this paper we propose using a single common image as dictionary, in conjunction with approximate nearest neighbour fields (ANNF) to perform super resolution (SR). By using a common source image, we are able to bypass the learning phase and also able to reduce the dictionary from a collection of hundreds of images to a single image. By adapting recent developments in ANNF computation, to suit super-resolution, we are able to perform much faster and accurate SR than existing techniques. To establish this claim, we compare the proposed algorithm against various state-of-the-art algorithms, and show that we are able to achieve b etter and faster reconstruction without any training.

CH-RES-TOCSY: Enantiomers spectral resolution and measurement of heteronuclear residual dipolar couplings

A new 2D NMR technique cited as CH-RES-TOCSY, for complete unraveling the spectra of enantiomers and for the measurement of structurally important C-HRDC sis reported. The spectral overlap and complexity of peaks were reduced by the blend of selective excitation and homo-decoupling. Differential values of C-H RDCs of enantiomers (R and S) are exploited to separate the enantiomeric peaks. The complete unraveling of the spectra of both the enantiomers is achieved by incorporating a TOCSY mixing blockprior to signal acquisition. The additional application of the method is demonstrated for the assignment of symmetric isomers. (C) 2015 Elsevier B.V. All rights reserved.

MRT Letter: A Unified Accelerated Maximum Likelihood Technique for Widefield, Confocal, and Super-Resolution 4Pi Microscopy

We propose an algorithmic technique for accelerating maximum likelihood (ML) algorithm for image reconstruction in fluorescence microscopy. This is made possible by integrating Biggs-Andrews (BA) method with ML approach. The results on widefield, confocal, and super-resolution 4Pi microscopy reveal substantial improvement in the speed of 3D image reconstruction (the number of iterations has reduced by approximately one-half). Moreover, the quality of reconstruction obtained using accelerated ML closely resembles with nonaccelerated ML method. The proposed technique is a step closer to realize real-time reconstruction in 3D fluorescence microscopy. Microsc. Res. Tech. 78:331-335, 2015. (c) 2015 Wiley Periodicals, Inc.

Estimation of Aboveground Phytomass of Plantations Using Digital Photogrammetry and High Resolution Remote Sensing Data

The study follows an approach to estimate phytomass using recent techniques of remote sensing and digital photogrammetry. It involved tree inventory of forest plantations in Bhakra forest range of Nainital district. Panchromatic stereo dataset of Cartosat-1 was evaluated for mean stand height retrieval. Texture analysis and tree-tops detection analyses were done on Quick-Bird PAN data. The composite texture image of mean, variance and contrast with a 5x5 pixel window was found best to separate tree crowns for assessment of crown areas. Tree tops count obtained by local maxima filtering was found to be 83.4 % efficient with an RMSE+/-13 for 35 sample plots. The predicted phytomass ranged from 27.01 to 35.08 t/ha in the case of Eucalyptus sp. while in the case of Tectona grandis from 26.52 to 156 t/ha. The correlation between observed and predicted phytomass in Eucalyptus sp. was 0.468 with an RMSE of 5.12. However, the phytomass predicted in Tectona grandis was fairly strong with R-2=0.65 and RMSE of 9.89 as there was no undergrowth and the crowns were clearly visible. Results of the study show the potential of Cartosat-1 derived DSM and Quick-Bird texture image for the estimation of stand height, stem diameter, tree count and phytomass of important timber species.

Synthetic image super resolution using FeatureMatch

In this paper, we propose a super resolution (SR) method for synthetic images using FeatureMatch. Existing state-of-the-art super resolution methods are learning based methods, where a pair of low-resolution and high-resolution dictionary pair are trained, and this trained pair is used to replace patches in low-resolution image with appropriate matching patches from the high-resolution dictionary. In this paper, we show that by using Approximate Nearest Neighbour Fields (ANNF), and a common source image, we can by-pass the learning phase, and use a single image for dictionary. Thus, reducing the dictionary from a collection obtained from hundreds of training images, to a single image. We show that by modifying the latest developments in ANNF computation, to suit super resolution, we can perform much faster and more accurate SR than existing techniques. To establish this claim we will compare our algorithm against various state-of-the-art algorithms, and show that we are able to achieve better and faster reconstruction without any training phase.