Zero-crossing approach to high-resolution reconstruction in frequency-domain optical-coherence tomography

We address the problem of high-resolution reconstruction in frequency-domain optical-coherence tomography (FDOCT). The traditional method employed uses the inverse discrete Fourier transform, which is limited in resolution due to the Heisenberg uncertainty principle. We propose a reconstruction technique based on zero-crossing (ZC) interval analysis. The motivation for our approach lies in the observation that, for a multilayered specimen, the backscattered signal may be expressed as a sum of sinusoids, and each sinusoid manifests as a peak in the FDOCT reconstruction. The successive ZC intervals of a sinusoid exhibit high consistency, with the intervals being inversely related to the frequency of the sinusoid. The statistics of the ZC intervals are used for detecting the frequencies present in the input signal. The noise robustness of the proposed technique is improved by using a cosine-modulated filter bank for separating the input into different frequency bands, and the ZC analysis is carried out on each band separately. The design of the filter bank requires the design of a prototype, which we accomplish using a Kaiser window approach. We show that the proposed method gives good results on synthesized and experimental data. The resolution is enhanced, and noise robustness is higher compared with the standard Fourier reconstruction. (c) 2012 Optical Society of America

Fast image reconstruction for fluorescence microscopy

Real-time image reconstruction is essential for improving the temporal resolution of fluorescence microscopy. A number of unavoidable processes such as, optical aberration, noise and scattering degrade image quality, thereby making image reconstruction an ill-posed problem. Maximum likelihood is an attractive technique for data reconstruction especially when the problem is ill-posed. Iterative nature of the maximum likelihood technique eludes real-time imaging. Here we propose and demonstrate a compute unified device architecture (CUDA) based fast computing engine for real-time 3D fluorescence imaging. A maximum performance boost of 210x is reported. Easy availability of powerful computing engines is a boon and may accelerate to realize real-time 3D fluorescence imaging. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.4754604]

Prior image-constrained l(1)-norm-based reconstruction method for effective usage of structural information in diffuse optical tomography

A novel approach that can more effectively use the structural information provided by the traditional imaging modalities in multimodal diffuse optical tomographic imaging is introduced. This approach is based on a prior image-constrained-l(1) minimization scheme and has been motivated by the recent progress in the sparse image reconstruction techniques. It is shown that the proposed framework is more effective in terms of localizing the tumor region and recovering the optical property values both in numerical and gelatin phantom cases compared to the traditional methods that use structural information. (C) 2012 Optical Society of America

Effective contrast recovery in rapid dynamic near-infrared diffuse optical tomography using l(1)-norm-based linear image reconstruction method

Traditional image reconstruction methods in rapid dynamic diffuse optical tomography employ l(2)-norm-based regularization, which is known to remove the high-frequency components in the reconstructed images and make them appear smooth. The contrast recovery in these type of methods is typically dependent on the iterative nature of method employed, where the nonlinear iterative technique is known to perform better in comparison to linear techniques (noniterative) with a caveat that nonlinear techniques are computationally complex. Assuming that there is a linear dependency of solution between successive frames resulted in a linear inverse problem. This new framework with the combination of l(1)-norm based regularization can provide better robustness to noise and provide better contrast recovery compared to conventional l(2)-based techniques. Moreover, it is shown that the proposed l(1)-based technique is computationally efficient compared to its counterpart (l(2)-based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame, and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames.

Demonstrating the Usefulness of CAELinux for Computer Aided Engineering using an Example of the Three Dimensional Reconstruction of a Pig Liver

CAELinux is a Linux distribution which is bundled with free software packages related to Computer Aided Engineering (CAE). The free software packages include software that can build a three dimensional solid model, programs that can mesh a geometry, software for carrying out Finite Element Analysis (FEA), programs that can carry out image processing etc. Present work has two goals: 1) To give a brief description of CAELinux 2) To demonstrate that CAELinux could be useful for Computer Aided Engineering, using an example of the three dimensional reconstruction of a pig liver from a stack of CT-scan images. One can note that instead of using CAELinux, using commercial software for reconstructing the liver would cost a lot of money. One can also note that CAELinux is a free and open source operating system and all software packages that are included in the operating system are also free. Hence one can conclude that CAELinux could be a very useful tool in application areas like surgical simulation which require three dimensional reconstructions of biological organs. Also, one can see that CAELinux could be a very useful tool for Computer Aided Engineering, in general.

Extracts of Strawberry Fruits Induce Intrinsic Pathway of Apoptosis in Breast Cancer Cells and Inhibits Tumor Progression in Mice

Background: The consumption of berry fruits, including strawberries, has been suggested to have beneficial effects against oxidative stress mediated diseases. Berries contain multiple phenolic compounds and secondary metabolites that contribute to their biological properties. Methodology/Principal Findings: Current study investigates the anticancer activity of the methanolic extract of strawberry (MESB) fruits in leukaemia (CEM) and breast cancer (T47D) cell lines ex vivo, and its cancer therapeutic and chemopreventive potential in mice models. Results of MTT, trypan blue and LDH assays suggested that MESB can induce cytotoxicity in cancer cells, irrespective of origin, in a concentration-and time-dependent manner. Treatment of mice bearing breast adenocarcinoma with MESB blocked the proliferation of tumor cells in a time-dependent manner and resulted in extended life span. Histological and immunohistochemical studies suggest that MESB treatment affected tumor cell proliferation by activating apoptosis and did not result in any side effects. Finally, we show that MESB can induce intrinsic pathway of apoptosis by activating p73 in breast cancer cells, when tumor suppressor gene p53 is mutated. Conclusions/Significance: The present study reveals that strawberry fruits possess both cancer preventive and therapeutic values and we discuss the mechanism by which it is achieved.

Multidimensional data reconstruction for two color fluorescence microscopy

We propose an iterative data reconstruction technique specifically designed for multi-dimensional multi-color fluorescence imaging. Markov random field is employed (for modeling the multi-color image field) in conjunction with the classical maximum likelihood method. It is noted that, ill-posed nature of the inverse problem associated with multi-color fluorescence imaging forces iterative data reconstruction. Reconstruction of three-dimensional (3D) two-color images (obtained from nanobeads and cultured cell samples) show significant reduction in the background noise (improved signal-to-noise ratio) with an impressive overall improvement in the spatial resolution (approximate to 250 nm) of the imaging system. Proposed data reconstruction technique may find immediate application in 3D in vivo and in vitro multi-color fluorescence imaging of biological specimens. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4769058]

SPARSE SIGNAL RECONSTRUCTION BASED ON SIGNAL DEPENDENT NON-UNIFORM SAMPLES

The classical approach to A/D conversion has been uniform sampling and we get perfect reconstruction for bandlimited signals by satisfying the Nyquist Sampling Theorem. We propose a non-uniform sampling scheme based on level crossing (LC) time information. We show stable reconstruction of bandpass signals with correct scale factor and hence a unique reconstruction from only the non-uniform time information. For reconstruction from the level crossings we make use of the sparse reconstruction based optimization by constraining the bandpass signal to be sparse in its frequency content. While overdetermined system of equations is resorted to in the literature we use an undetermined approach along with sparse reconstruction formulation. We could get a reconstruction SNR > 20dB and perfect support recovery with probability close to 1, in noise-less case and with lower probability in the noisy case. Random picking of LC from different levels over the same limited signal duration and for the same length of information, is seen to be advantageous for reconstruction.

Multiple transmitter localization and communication footprint identification using sparse reconstruction techniques

This paper considers the problem of identifying the footprints of communication of multiple transmitters in a given geographical area. To do this, a number of sensors are deployed at arbitrary but known locations in the area, and their individual decisions regarding the presence or absence of the transmitters' signal are combined at a fusion center to reconstruct the spatial spectral usage map. One straightforward scheme to construct this map is to query each of the sensors and cluster the sensors that detect the primary's signal. However, using the fact that a typical transmitter footprint map is a sparse image, two novel compressive sensing based schemes are proposed, which require significantly fewer number of transmissions compared to the querying scheme. A key feature of the proposed schemes is that the measurement matrix is constructed from a pseudo-random binary phase shift applied to the decision of each sensor prior to transmission. The measurement matrix is thus a binary ensemble which satisfies the restricted isometry property. The number of measurements needed for accurate footprint reconstruction is determined using compressive sampling theory. The three schemes are compared through simulations in terms of a performance measure that quantifies the accuracy of the reconstructed spatial spectral usage map. It is found that the proposed sparse reconstruction technique-based schemes significantly outperform the round-robin scheme.

Cytotoxic and pro-apoptotic effects of Abrus precatorius L. on human metastatic breast cancer cell line, MDA-MB-231

Abrus precatorius is highly regarded as a universal panacea in the herbal medicine with diverse pharmacological activity spectra. This experimental study on the mechanism of the anticancer activity of A. precatorius leaf extracts, may offer new evidence for A. precatorius in the treatment of breast cancer in clinical practice. Cell death was determined by using MTT assay. Further analyses were carried out by doing DNA laddering, PARP cleavage, FACS, semi-quantitative RT-PCR and detection of cellular reactive oxygen species (ROS) by DCFDA assay. A. precatorius showed very striking inhibition on MDA-MB-231 cells. MTT assay showed more than 75 % inhibition of the cells and treated cells indicated visible laddering pattern with thick compact band. PARP cleavage produced 89 kDa cleavage product which was associated with apoptosis. Flow cytometer exhibited a sub-G0/G1 peak as an indicative of apoptosis. mRNA expression level of apoptosis-related genes p21 and p53 was markedly increased in cells treated with the extract as compared to control. The up-regulation of p21 and p53 may be the molecular mechanisms by which A. precatorius extract which induces apoptosis. An increase in the concentration of A. precatorius extract does not generate ROS, instead it reduces ROS formation in MDA-MB-231 cells, as evident from the shift in fluorescence below untreated control. This is the first report showing that A. precatorius leaf extract exhibits a growth inhibitory effect by induction of apoptosis in MDA-MB-231 cells. Our results contribute towards validation of the A. precatorius extract as a potentially effective chemopreventive or therapeutic agent against breast cancer.

Some new results on signal reconstruction from Fourier transform magnitude spectrum

We address the problem of signal reconstruction from Fourier transform magnitude spectrum. The problem arises in many real-world scenarios where magnitude-only measurements are possible, but it is required to construct a complex-valued signal starting from those measurements. We present some new general results in this context and show that the previously known results on minimum-phase rational transfer functions, and recoverability of minimum-phase functions from magnitude spectrum, form special cases of the results reported in this paper. Some simulation results are also provided to demonstrate the practical feasibility of the reconstruction methodology.

Regulation of protumorigenic pathways by Insulin like growth factor binding protein2 and its association along with beta-catenin in breast cancer lymph node metastasis

Background: Insulin like growth factor binding proteins modulate the mitogenic and pro survival effects of IGF. Elevated expression of IGFBP2 is associated with progression of tumors that include prostate, ovarian, glioma among others. Though implicated in the progression of breast cancer, the molecular mechanisms involved in IGFBP2 actions are not well defined. This study investigates the molecular targets and biological pathways targeted by IGFBP2 in breast cancer. Methods: Transcriptome analysis of breast tumor cells (BT474) with stable knockdown of IGFBP2 and breast tumors having differential expression of IGFBP2 by immunohistochemistry was performed using microarray. Differential gene expression was established using R-Bioconductor package. For validation, gene expression was determined by qPCR. Inhibitors of IGF1R and integrin pathway were utilized to study the mechanism of regulation of beta-catenin. Immunohistochemical and immunocytochemical staining was performed on breast tumors and experimental cells, respectively for beta-catenin and IGFBP2 expression. Results: Knockdown of IGFBP2 resulted in differential expression of 2067 up regulated and 2002 down regulated genes in breast cancer cells. Down regulated genes principally belong to cell cycle, DNA replication, repair, p53 signaling, oxidative phosphorylation, Wnt signaling. Whole genome expression analysis of breast tumors with or without IGFBP2 expression indicated changes in genes belonging to Focal adhesion, Map kinase and Wnt signaling pathways. Interestingly, IGFBP2 knockdown clones showed reduced expression of beta-catenin compared to control cells which was restored upon IGFBP2 re-expression. The regulation of beta-catenin by IGFBP2 was found to be IGF1R and integrin pathway dependent. Furthermore, IGFBP2 and beta-catenin are co-ordinately overexpressed in breast tumors and correlate with lymph node metastasis. Conclusion: This study highlights regulation of beta-catenin by IGFBP2 in breast cancer cells and most importantly, combined expression of IGFBP2 and beta-catenin is associated with lymph node metastasis of breast tumors.

Taylor series expansion based multidimensional image reconstruction for confocal and 4pi microscopy

We propose and experimentally demonstrate a three-dimensional (3D) image reconstruction methodology based on Taylor series approximation (TSA) in a Bayesian image reconstruction formulation. TSA incorporates the requirement of analyticity in the image domain, and acts as a finite impulse response filter. This technique is validated on images obtained from widefield, confocal laser scanning fluorescence microscopy and two-photon excited 4pi (2PE-4pi) fluorescence microscopy. Studies on simulated 3D objects, mitochondria-tagged yeast cells (labeled with Mitotracker Orange) and mitochondrial networks (tagged with Green fluorescent protein) show a signal-to-background improvement of 40% and resolution enhancement from 360 to 240 nm. This technique can easily be extended to other imaging modalities (single plane illumination microscopy (SPIM), individual molecule localization SPIM, stimulated emission depletion microscopy and its variants).

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.

Sparse Recovery Methods Hold Promise for Diffuse Optical Tomographic Image Reconstruction

The sparse recovery methods utilize the l(p)-normbased regularization in the estimation problem with 0 <= p <= 1. These methods have a better utility when the number of independent measurements are limited in nature, which is a typical case for diffuse optical tomographic image reconstruction problem. These sparse recovery methods, along with an approximation to utilize the l(0)-norm, have been deployed for the reconstruction of diffuse optical images. Their performancewas compared systematically using both numerical and gelatin phantom cases to show that these methods hold promise in improving the reconstructed image quality.