Nonlinear Optical Image Processing with Bacteriorhodopsin Films

NASA Technical Reports Server (NTRS)

Downie, John D.; Deiss, Ron (Technical Monitor)

1994-01-01

The transmission properties of some bacteriorhodopsin film spatial light modulators are uniquely suited to allow nonlinear optical image processing operations to be applied to images with multiplicative noise characteristics. A logarithmic amplitude transmission feature of the film permits the conversion of multiplicative noise to additive noise, which may then be linearly filtered out in the Fourier plane of the transformed image. The bacteriorhodopsin film displays the logarithmic amplitude response for write beam intensities spanning a dynamic range greater than 2.0 orders of magnitude. We present experimental results demonstrating the principle and capability for several different image and noise situations, including deterministic noise and speckle. Using the bacteriorhodopsin film, we successfully filter out image noise from the transformed image that cannot be removed from the original image.

Sparsity Aware Adaptive Radar Sensor Imaging in Complex Scattering Environments

DTIC Science & Technology

2015-06-15

while meeting the requirement on the peak to average power ratio. Third, we study impact of waveform encoding on nonlinear electromagnetic tomographic...Enyue Lu. Time Domain Electromagnetic Tomography Using Propagation and Backpropagation Method, IEEE International Conference on Image Processing...Received Paper 3.00 4.00 Yuanwei Jin, Chengdon Dong, Enyue Lu. Waveform Encoding for Nonlinear Electromagnetic Tomographic Imaging, IEEE Global

Real-Time Implementation of Nonlinear Processing Functions.

DTIC Science & Technology

1981-08-01

crystal devices and then to use them in a coherent optical data- processing apparatus using halftone masks custom designed at the University oi Southern...California. With the halftone mask technique, we have demonstrated logarithmic nonlinear transformation, allowing us to separate multiplicative images...improved.,_ This device allowed nonlinear functions to be implemented directly wit - out the need for specially made halftone masks. Besides

Hazardous Continuation Backward in Time in Nonlinear Parabolic Equations, and an Experiment in Deblurring Nonlinearly Blurred Imagery

PubMed Central

Carasso, Alfred S

2013-01-01

Identifying sources of ground water pollution, and deblurring nanoscale imagery as well as astronomical galaxy images, are two important applications involving numerical computation of parabolic equations backward in time. Surprisingly, very little is known about backward continuation in nonlinear parabolic equations. In this paper, an iterative procedure originating in spectroscopy in the 1930’s, is adapted into a useful tool for solving a wide class of 2D nonlinear backward parabolic equations. In addition, previously unsuspected difficulties are uncovered that may preclude useful backward continuation in parabolic equations deviating too strongly from the linear, autonomous, self adjoint, canonical model. This paper explores backward continuation in selected 2D nonlinear equations, by creating fictitious blurred images obtained by using several sharp images as initial data in these equations, and capturing the corresponding solutions at some positive time T. Successful backward continuation from t=T to t = 0, would recover the original sharp image. Visual recognition provides meaningful evaluation of the degree of success or failure in the reconstructed solutions. Instructive examples are developed, illustrating the unexpected influence of certain types of nonlinearities. Visually and statistically indistinguishable blurred images are presented, with vastly different deblurring results. These examples indicate that how an image is nonlinearly blurred is critical, in addition to the amount of blur. The equations studied represent nonlinear generalizations of Brownian motion, and the blurred images may be interpreted as visually expressing the results of novel stochastic processes. PMID:26401430

Hazardous Continuation Backward in Time in Nonlinear Parabolic Equations, and an Experiment in Deblurring Nonlinearly Blurred Imagery.

PubMed

Carasso, Alfred S

2013-01-01

Identifying sources of ground water pollution, and deblurring nanoscale imagery as well as astronomical galaxy images, are two important applications involving numerical computation of parabolic equations backward in time. Surprisingly, very little is known about backward continuation in nonlinear parabolic equations. In this paper, an iterative procedure originating in spectroscopy in the 1930's, is adapted into a useful tool for solving a wide class of 2D nonlinear backward parabolic equations. In addition, previously unsuspected difficulties are uncovered that may preclude useful backward continuation in parabolic equations deviating too strongly from the linear, autonomous, self adjoint, canonical model. This paper explores backward continuation in selected 2D nonlinear equations, by creating fictitious blurred images obtained by using several sharp images as initial data in these equations, and capturing the corresponding solutions at some positive time T. Successful backward continuation from t=T to t = 0, would recover the original sharp image. Visual recognition provides meaningful evaluation of the degree of success or failure in the reconstructed solutions. Instructive examples are developed, illustrating the unexpected influence of certain types of nonlinearities. Visually and statistically indistinguishable blurred images are presented, with vastly different deblurring results. These examples indicate that how an image is nonlinearly blurred is critical, in addition to the amount of blur. The equations studied represent nonlinear generalizations of Brownian motion, and the blurred images may be interpreted as visually expressing the results of novel stochastic processes.

Real-Time Nonlinear Optical Information Processing.

DTIC Science & Technology

1979-06-01

operations aree presented. One approach realizes the halftone method of nonlinear optical processing in real time by replacing the conventional...photographic recording medium with a real-time image transducer. In the second approach halftoning is eliminated and the real-time device is used directly

New scheme for image edge detection using the switching mechanism of nonlinear optical material

NASA Astrophysics Data System (ADS)

Pahari, Nirmalya; Mukhopadhyay, Sourangshu

2006-03-01

The limitations of electronics in conducting parallel arithmetic, algebraic, and logic processing are well known. Very high-speed (terahertz) performance cannot be expected in conventional electronic mechanisms. To achieve such performance we can introduce optics instead of electronics for information processing, computing, and data handling. Nonlinear optical material (NOM) is a successful candidate in this regard to play a major role in the domain of optically controlled switching systems. The character of some NOMs is such as to reflect the probe beam in the presence of two read beams (or pump beams) exciting the material from opposite directions, using the principle of four-wave mixing. In image processing, edge extraction from an image is an important and essential task. Several optical methods of digital image processing are used for properly evaluating the image edges. We propose here a new method of image edge detection, extraction, and enhancement by use of AND-based switching operations with NOM. In this process we have used the optically inverted image of a supplied image. This can be obtained by the EXOR switching operation of the NOM.

Imaging of matrix-disorder in normal and pathological human dermis using nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Zhuo, Shuangmu; Chen, Jianxin; Xie, Shusen; Zheng, Liqin; Jiang, Xingshan

2009-11-01

In dermis, collagen and elastin are important structural proteins of extracellular maxtrix. The matrix-disorder is associated with various physiologic processes, such as localized scleroderma, anetoderma, photoaging. In this work, we demonstrate the capability of nonlinear optical microscopy in imaging structural proteins in normal and pathological human dermis.

Position Estimation Using Image Derivative

NASA Technical Reports Server (NTRS)

Mortari, Daniele; deDilectis, Francesco; Zanetti, Renato

2015-01-01

This paper describes an image processing algorithm to process Moon and/or Earth images. The theory presented is based on the fact that Moon hard edge points are characterized by the highest values of the image derivative. Outliers are eliminated by two sequential filters. Moon center and radius are then estimated by nonlinear least-squares using circular sigmoid functions. The proposed image processing has been applied and validated using real and synthetic Moon images.

1984 European Conference on Optics, Optical Systems and Applications, Amsterdam, Netherlands, October 9-12, 1984, Proceedings

NASA Astrophysics Data System (ADS)

Boelger, B.; Ferwerda, H. A.

Various papers on optics, optical systems, and their applications are presented. The general topics addressed include: laser systems, optical and electrooptical materials and devices; novel spectroscopic techniques and applications; inspection, remote sensing, velocimetry, and gauging; optical design and image formation; holography, image processing, and storage; and integrated and fiber optics. Also discussed are: nonlinear optics; nonlinear photorefractive materials; scattering and diffractions applications in materials processing, deposition, and machining; medical and biological applications; and focus on industry.

Nonlinear features for classification and pose estimation of machined parts from single views

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1998-10-01

A new nonlinear feature extraction method is presented for classification and pose estimation of objects from single views. The feature extraction method is called the maximum representation and discrimination feature (MRDF) method. The nonlinear MRDF transformations to use are obtained in closed form, and offer significant advantages compared to nonlinear neural network implementations. The features extracted are useful for both object discrimination (classification) and object representation (pose estimation). We consider MRDFs on image data, provide a new 2-stage nonlinear MRDF solution, and show it specializes to well-known linear and nonlinear image processing transforms under certain conditions. We show the use of MRDF in estimating the class and pose of images of rendered solid CAD models of machine parts from single views using a feature-space trajectory neural network classifier. We show new results with better classification and pose estimation accuracy than are achieved by standard principal component analysis and Fukunaga-Koontz feature extraction methods.

Image storage in coumarin-based copolymer thin films by photoinduced dimerization.

PubMed

Gindre, Denis; Iliopoulos, Konstantinos; Krupka, Oksana; Champigny, Emilie; Morille, Yohann; Sallé, Marc

2013-11-15

We report a technique to encode grayscale digital images in thin films composed of copolymers containing coumarins. A nonlinear microscopy setup was implemented and two nonlinear optical processes were used to store and read information. A third-order process (two-photon absorption) was used to photoinduce a controlled dimer-to-monomer ratio within a defined tiny volume in the material, which corresponds to each recorded bit of data. Moreover, a second-order process (second-harmonic generation) was used to read the stored information, which has been found to be highly dependent upon the monomer-to-dimer ratio.

The parallel-sequential field subtraction technique for coherent nonlinear ultrasonic imaging

NASA Astrophysics Data System (ADS)

Cheng, Jingwei; Potter, Jack N.; Drinkwater, Bruce W.

2018-06-01

Nonlinear imaging techniques have recently emerged which have the potential to detect cracks at a much earlier stage than was previously possible and have sensitivity to partially closed defects. This study explores a coherent imaging technique based on the subtraction of two modes of focusing: parallel, in which the elements are fired together with a delay law and sequential, in which elements are fired independently. In the parallel focusing a high intensity ultrasonic beam is formed in the specimen at the focal point. However, in sequential focusing only low intensity signals from individual elements enter the sample and the full matrix of transmit-receive signals is recorded and post-processed to form an image. Under linear elastic assumptions, both parallel and sequential images are expected to be identical. Here we measure the difference between these images and use this to characterise the nonlinearity of small closed fatigue cracks. In particular we monitor the change in relative phase and amplitude at the fundamental frequencies for each focal point and use this nonlinear coherent imaging metric to form images of the spatial distribution of nonlinearity. The results suggest the subtracted image can suppress linear features (e.g. back wall or large scatters) effectively when instrumentation noise compensation in applied, thereby allowing damage to be detected at an early stage (c. 15% of fatigue life) and reliably quantified in later fatigue life.

Dynamic updating atlas for heart segmentation with a nonlinear field-based model.

PubMed

Cai, Ken; Yang, Rongqian; Yue, Hongwei; Li, Lihua; Ou, Shanxing; Liu, Feng

2017-09-01

Segmentation of cardiac computed tomography (CT) images is an effective method for assessing the dynamic function of the heart and lungs. In the atlas-based heart segmentation approach, the quality of segmentation usually relies upon atlas images, and the selection of those reference images is a key step. The optimal goal in this selection process is to have the reference images as close to the target image as possible. This study proposes an atlas dynamic update algorithm using a scheme of nonlinear deformation field. The proposed method is based on the features among double-source CT (DSCT) slices. The extraction of these features will form a base to construct an average model and the created reference atlas image is updated during the registration process. A nonlinear field-based model was used to effectively implement a 4D cardiac segmentation. The proposed segmentation framework was validated with 14 4D cardiac CT sequences. The algorithm achieved an acceptable accuracy (1.0-2.8 mm). Our proposed method that combines a nonlinear field-based model and dynamic updating atlas strategies can provide an effective and accurate way for whole heart segmentation. The success of the proposed method largely relies on the effective use of the prior knowledge of the atlas and the similarity explored among the to-be-segmented DSCT sequences. Copyright © 2016 John Wiley & Sons, Ltd.

Nonlinear spike-and-slab sparse coding for interpretable image encoding.

PubMed

Shelton, Jacquelyn A; Sheikh, Abdul-Saboor; Bornschein, Jörg; Sterne, Philip; Lücke, Jörg

2015-01-01

Sparse coding is a popular approach to model natural images but has faced two main challenges: modelling low-level image components (such as edge-like structures and their occlusions) and modelling varying pixel intensities. Traditionally, images are modelled as a sparse linear superposition of dictionary elements, where the probabilistic view of this problem is that the coefficients follow a Laplace or Cauchy prior distribution. We propose a novel model that instead uses a spike-and-slab prior and nonlinear combination of components. With the prior, our model can easily represent exact zeros for e.g. the absence of an image component, such as an edge, and a distribution over non-zero pixel intensities. With the nonlinearity (the nonlinear max combination rule), the idea is to target occlusions; dictionary elements correspond to image components that can occlude each other. There are major consequences of the model assumptions made by both (non)linear approaches, thus the main goal of this paper is to isolate and highlight differences between them. Parameter optimization is analytically and computationally intractable in our model, thus as a main contribution we design an exact Gibbs sampler for efficient inference which we can apply to higher dimensional data using latent variable preselection. Results on natural and artificial occlusion-rich data with controlled forms of sparse structure show that our model can extract a sparse set of edge-like components that closely match the generating process, which we refer to as interpretable components. Furthermore, the sparseness of the solution closely follows the ground-truth number of components/edges in the images. The linear model did not learn such edge-like components with any level of sparsity. This suggests that our model can adaptively well-approximate and characterize the meaningful generation process.

Nonlinear Spike-And-Slab Sparse Coding for Interpretable Image Encoding

PubMed Central

Shelton, Jacquelyn A.; Sheikh, Abdul-Saboor; Bornschein, Jörg; Sterne, Philip; Lücke, Jörg

2015-01-01

Sparse coding is a popular approach to model natural images but has faced two main challenges: modelling low-level image components (such as edge-like structures and their occlusions) and modelling varying pixel intensities. Traditionally, images are modelled as a sparse linear superposition of dictionary elements, where the probabilistic view of this problem is that the coefficients follow a Laplace or Cauchy prior distribution. We propose a novel model that instead uses a spike-and-slab prior and nonlinear combination of components. With the prior, our model can easily represent exact zeros for e.g. the absence of an image component, such as an edge, and a distribution over non-zero pixel intensities. With the nonlinearity (the nonlinear max combination rule), the idea is to target occlusions; dictionary elements correspond to image components that can occlude each other. There are major consequences of the model assumptions made by both (non)linear approaches, thus the main goal of this paper is to isolate and highlight differences between them. Parameter optimization is analytically and computationally intractable in our model, thus as a main contribution we design an exact Gibbs sampler for efficient inference which we can apply to higher dimensional data using latent variable preselection. Results on natural and artificial occlusion-rich data with controlled forms of sparse structure show that our model can extract a sparse set of edge-like components that closely match the generating process, which we refer to as interpretable components. Furthermore, the sparseness of the solution closely follows the ground-truth number of components/edges in the images. The linear model did not learn such edge-like components with any level of sparsity. This suggests that our model can adaptively well-approximate and characterize the meaningful generation process. PMID:25954947

System and method for investigating sub-surface features and 3D imaging of non-linear property, compressional velocity VP, shear velocity VS and velocity ratio VP/VS of a rock formation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vu, Cung Khac; Skelt, Christopher; Nihei, Kurt

A system and a method for generating a three-dimensional image of a rock formation, compressional velocity VP, shear velocity VS and velocity ratio VP/VS of a rock formation are provided. A first acoustic signal includes a first plurality of pulses. A second acoustic signal from a second source includes a second plurality of pulses. A detected signal returning to the borehole includes a signal generated by a non-linear mixing process from the first and second acoustic signals in a non-linear mixing zone within an intersection volume. The received signal is processed to extract the signal over noise and/or signals resultingmore » from linear interaction and the three dimensional image of is generated.« less

Comparisons of linear and nonlinear pyramid schemes for signal and image processing

NASA Astrophysics Data System (ADS)

Morales, Aldo W.; Ko, Sung-Jea

1997-04-01

Linear filters banks are being used extensively in image and video applications. New research results in wavelet applications for compression and de-noising are constantly appearing in the technical literature. On the other hand, non-linear filter banks are also being used regularly in image pyramid algorithms. There are some inherent advantages in using non-linear filters instead of linear filters when non-Gaussian processes are present in images. However, a consistent way of comparing performance criteria between these two schemes has not been fully developed yet. In this paper a recently discovered tool, sample selection probabilities, is used to compare the behavior of linear and non-linear filters. In the conversion from weights of order statistics (OS) filters to coefficients of the impulse response is obtained through these probabilities. However, the reverse problem: the conversion from coefficients of the impulse response to the weights of OS filters is not yet fully understood. One of the reasons for this difficulty is the highly non-linear nature of the partitions and generating function used. In the present paper the problem is posed as an optimization of integer linear programming subject to constraints directly obtained from the coefficients of the impulse response. Although the technique to be presented in not completely refined, it certainly appears to be promising. Some results will be shown.

Adaptive nonlinear L2 and L3 filters for speckled image processing

NASA Astrophysics Data System (ADS)

Lukin, Vladimir V.; Melnik, Vladimir P.; Chemerovsky, Victor I.; Astola, Jaakko T.

1997-04-01

Here we propose adaptive nonlinear filters based on calculation and analysis of two or three order statistics in a scanning window. They are designed for processing images corrupted by severe speckle noise with non-symmetrical. (Rayleigh or one-side exponential) distribution laws; impulsive noise can be also present. The proposed filtering algorithms provide trade-off between impulsive noise can be also present. The proposed filtering algorithms provide trade-off between efficient speckle noise suppression, robustness, good edge/detail preservation, low computational complexity, preservation of average level for homogeneous regions of images. Quantitative evaluations of the characteristics of the proposed filter are presented as well as the results of the application to real synthetic aperture radar and ultrasound medical images.

Corner-point criterion for assessing nonlinear image processing imagers

NASA Astrophysics Data System (ADS)

Landeau, Stéphane; Pigois, Laurent; Foing, Jean-Paul; Deshors, Gilles; Swiathy, Greggory

2017-10-01

Range performance modeling of optronics imagers attempts to characterize the ability to resolve details in the image. Today, digital image processing is systematically used in conjunction with the optoelectronic system to correct its defects or to exploit tiny detection signals to increase performance. In order to characterize these processing having adaptive and non-linear properties, it becomes necessary to stimulate the imagers with test patterns whose properties are similar to the actual scene image ones, in terms of dynamic range, contours, texture and singular points. This paper presents an approach based on a Corner-Point (CP) resolution criterion, derived from the Probability of Correct Resolution (PCR) of binary fractal patterns. The fundamental principle lies in the respectful perception of the CP direction of one pixel minority value among the majority value of a 2×2 pixels block. The evaluation procedure considers the actual image as its multi-resolution CP transformation, taking the role of Ground Truth (GT). After a spatial registration between the degraded image and the original one, the degradation is statistically measured by comparing the GT with the degraded image CP transformation, in terms of localized PCR at the region of interest. The paper defines this CP criterion and presents the developed evaluation techniques, such as the measurement of the number of CP resolved on the target, the transformation CP and its inverse transform that make it possible to reconstruct an image of the perceived CPs. Then, this criterion is compared with the standard Johnson criterion, in the case of a linear blur and noise degradation. The evaluation of an imaging system integrating an image display and a visual perception is considered, by proposing an analysis scheme combining two methods: a CP measurement for the highly non-linear part (imaging) with real signature test target and conventional methods for the more linear part (displaying). The application to color imaging is proposed, with a discussion about the choice of the working color space depending on the type of image enhancement processing used.

Sparse 4D TomoSAR imaging in the presence of non-linear deformation

NASA Astrophysics Data System (ADS)

Khwaja, Ahmed Shaharyar; ćetin, Müjdat

2018-04-01

In this paper, we present a sparse four-dimensional tomographic synthetic aperture radar (4D TomoSAR) imaging scheme that can estimate elevation and linear as well as non-linear seasonal deformation rates of scatterers using the interferometric phase. Unlike existing sparse processing techniques that use fixed dictionaries based on a linear deformation model, we use a variable dictionary for the non-linear deformation in the form of seasonal sinusoidal deformation, in addition to the fixed dictionary for the linear deformation. We estimate the amplitude of the sinusoidal deformation using an optimization method and create the variable dictionary using the estimated amplitude. We show preliminary results using simulated data that demonstrate the soundness of our proposed technique for sparse 4D TomoSAR imaging in the presence of non-linear deformation.

Direction selectivity of blowfly motion-sensitive neurons is computed in a two-stage process.

PubMed Central

Borst, A; Egelhaaf, M

1990-01-01

Direction selectivity of motion-sensitive neurons is generally thought to result from the nonlinear interaction between the signals derived from adjacent image points. Modeling of motion-sensitive networks, however, reveals that such elements may still respond to motion in a rather poor directionally selective way. Direction selectivity can be significantly enhanced if the nonlinear interaction is followed by another processing stage in which the signals of elements with opposite preferred directions are subtracted from each other. Our electrophysiological experiments in the fly visual system suggest that here direction selectivity is acquired in such a two-stage process. Images PMID:2251278

Nonlinear dynamic range transformation in visual communication channels.

PubMed

Alter-Gartenberg, R

1996-01-01

The article evaluates nonlinear dynamic range transformation in the context of the end-to-end continuous-input/discrete processing/continuous-display imaging process. Dynamic range transformation is required when we have the following: (i) the wide dynamic range encountered in nature is compressed into the relatively narrow dynamic range of the display, particularly for spatially varying irradiance (e.g., shadow); (ii) coarse quantization is expanded to the wider dynamic range of the display; and (iii) nonlinear tone scale transformation compensates for the correction in the camera amplifier.

Applied Nonlinear Dynamics and Stochastic Systems Near The Millenium. Proceedings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kadtke, J.B.; Bulsara, A.

These proceedings represent papers presented at the Applied Nonlinear Dynamics and Stochastic Systems conference held in San Diego, California in July 1997. The conference emphasized the applications of nonlinear dynamical systems theory in fields as diverse as neuroscience and biomedical engineering, fluid dynamics, chaos control, nonlinear signal/image processing, stochastic resonance, devices and nonlinear dynamics in socio{minus}economic systems. There were 56 papers presented at the conference and 5 have been abstracted for the Energy Science and Technology database.(AIP)

Optoelectronic associative memory

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin (Inventor)

1993-01-01

An associative optical memory including an input spatial light modulator (SLM) in the form of an edge enhanced liquid crystal light valve (LCLV) and a pair of memory SLM's in the form of liquid crystal televisions (LCTV's) forms a matrix array of an input image which is cross correlated with a matrix array of stored images. The correlation product is detected and nonlinearly amplified to illuminate a replica of the stored image array to select the stored image correlating with the input image. The LCLV is edge enhanced by reducing the bias frequency and voltage and rotating its orientation. The edge enhancement and nonlinearity of the photodetection improves the orthogonality of the stored image. The illumination of the replicate stored image provides a clean stored image, uncontaminated by the image comparison process.

Visual communications and image processing '92; Proceedings of the Meeting, Boston, MA, Nov. 18-20, 1992

NASA Astrophysics Data System (ADS)

Maragos, Petros

The topics discussed at the conference include hierarchical image coding, motion analysis, feature extraction and image restoration, video coding, and morphological and related nonlinear filtering. Attention is also given to vector quantization, morphological image processing, fractals and wavelets, architectures for image and video processing, image segmentation, biomedical image processing, and model-based analysis. Papers are presented on affine models for motion and shape recovery, filters for directly detecting surface orientation in an image, tracking of unresolved targets in infrared imagery using a projection-based method, adaptive-neighborhood image processing, and regularized multichannel restoration of color images using cross-validation. (For individual items see A93-20945 to A93-20951)

Correction of Non-Linear Propagation Artifact in Contrast-Enhanced Ultrasound Imaging of Carotid Arteries: Methods and in Vitro Evaluation.

PubMed

Yildiz, Yesna O; Eckersley, Robert J; Senior, Roxy; Lim, Adrian K P; Cosgrove, David; Tang, Meng-Xing

2015-07-01

Non-linear propagation of ultrasound creates artifacts in contrast-enhanced ultrasound images that significantly affect both qualitative and quantitative assessments of tissue perfusion. This article describes the development and evaluation of a new algorithm to correct for this artifact. The correction is a post-processing method that estimates and removes non-linear artifact in the contrast-specific image using the simultaneously acquired B-mode image data. The method is evaluated on carotid artery flow phantoms with large and small vessels containing microbubbles of various concentrations at different acoustic pressures. The algorithm significantly reduces non-linear artifacts while maintaining the contrast signal from bubbles to increase the contrast-to-tissue ratio by up to 11 dB. Contrast signal from a small vessel 600 μm in diameter buried in tissue artifacts before correction was recovered after the correction. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Effects of EPI distortion correction pipelines on the connectome in Parkinson's Disease

NASA Astrophysics Data System (ADS)

Galvis, Justin; Mezher, Adam F.; Ragothaman, Anjanibhargavi; Villalon-Reina, Julio E.; Fletcher, P. Thomas; Thompson, Paul M.; Prasad, Gautam

2016-03-01

Echo-planar imaging (EPI) is commonly used for diffusion-weighted imaging (DWI) but is susceptible to nonlinear geometric distortions arising from inhomogeneities in the static magnetic field. These inhomogeneities can be measured and corrected using a fieldmap image acquired during the scanning process. In studies where the fieldmap image is not collected, these distortions can be corrected, to some extent, by nonlinearly registering the diffusion image to a corresponding anatomical image, either a T1- or T2-weighted image. Here we compared two EPI distortion correction pipelines, both based on nonlinear registration, which were optimized for the particular weighting of the structural image registration target. The first pipeline used a 3D nonlinear registration to a T1-weighted target, while the second pipeline used a 1D nonlinear registration to a T2-weighted target. We assessed each pipeline in its ability to characterize high-level measures of brain connectivity in Parkinson's disease (PD) in 189 individuals (58 healthy controls, 131 people with PD) from the Parkinson's Progression Markers Initiative (PPMI) dataset. We computed a structural connectome (connectivity map) for each participant using regions of interest from a cortical parcellation combined with DWI-based whole-brain tractography. We evaluated test-retest reliability of the connectome for each EPI distortion correction pipeline using a second diffusion scan acquired directly after the participants' first. Finally, we used support vector machine (SVM) classification to assess how accurately each pipeline classified PD versus healthy controls using each participants' structural connectome.

Real-Time Optical Image Processing Techniques

DTIC Science & Technology

1988-10-31

pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the modification of micro-chan- nel spatial...required for non-linear operation. Real-time nonlinear processing was performed using the halftone screen and MSLM. The experiments showed the effectiveness...pulse frequency modulation has been pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the

Automated aerial image based CD metrology initiated by pattern marking with photomask layout data

NASA Astrophysics Data System (ADS)

Davis, Grant; Choi, Sun Young; Jung, Eui Hee; Seyfarth, Arne; van Doornmalen, Hans; Poortinga, Eric

2007-05-01

The photomask is a critical element in the lithographic image transfer process from the drawn layout to the final structures on the wafer. The non-linearity of the imaging process and the related MEEF impose a tight control requirement on the photomask critical dimensions. Critical dimensions can be measured in aerial images with hardware emulation. This is a more recent complement to the standard scanning electron microscope measurement of wafers and photomasks. Aerial image measurement includes non-linear, 3-dimensional, and materials effects on imaging that cannot be observed directly by SEM measurement of the mask. Aerial image measurement excludes the processing effects of printing and etching on the wafer. This presents a unique contribution to the difficult process control and modeling tasks in mask making. In the past, aerial image measurements have been used mainly to characterize the printability of mask repair sites. Development of photomask CD characterization with the AIMS TM tool was motivated by the benefit of MEEF sensitivity and the shorter feedback loop compared to wafer exposures. This paper describes a new application that includes: an improved interface for the selection of meaningful locations using the photomask and design layout data with the Calibre TM Metrology Interface, an automated recipe generation process, an automated measurement process, and automated analysis and result reporting on a Carl Zeiss AIMS TM system.

Iterative Nonlinear Tikhonov Algorithm with Constraints for Electromagnetic Tomography

NASA Technical Reports Server (NTRS)

Xu, Feng; Deshpande, Manohar

2012-01-01

Low frequency electromagnetic tomography such as the capacitance tomography (ECT) has been proposed for monitoring and mass-gauging of gas-liquid two-phase system under microgravity condition in NASA's future long-term space missions. Due to the ill-posed inverse problem of ECT, images reconstructed using conventional linear algorithms often suffer from limitations such as low resolution and blurred edges. Hence, new efficient high resolution nonlinear imaging algorithms are needed for accurate two-phase imaging. The proposed Iterative Nonlinear Tikhonov Regularized Algorithm with Constraints (INTAC) is based on an efficient finite element method (FEM) forward model of quasi-static electromagnetic problem. It iteratively minimizes the discrepancy between FEM simulated and actual measured capacitances by adjusting the reconstructed image using the Tikhonov regularized method. More importantly, it enforces the known permittivity of two phases to the unknown pixels which exceed the reasonable range of permittivity in each iteration. This strategy does not only stabilize the converging process, but also produces sharper images. Simulations show that resolution improvement of over 2 times can be achieved by INTAC with respect to conventional approaches. Strategies to further improve spatial imaging resolution are suggested, as well as techniques to accelerate nonlinear forward model and thus increase the temporal resolution.

Validation of nonlinear interferometric vibrational imaging as a molecular OCT technique by the use of Raman microscopy

NASA Astrophysics Data System (ADS)

Benalcazar, Wladimir A.; Jiang, Zhi; Marks, Daniel L.; Geddes, Joseph B.; Boppart, Stephen A.

2009-02-01

We validate a molecular imaging technique called Nonlinear Interferometric Vibrational Imaging (NIVI) by comparing vibrational spectra with those acquired from Raman microscopy. This broadband coherent anti-Stokes Raman scattering (CARS) technique uses heterodyne detection and OCT acquisition and design principles to interfere a CARS signal generated by a sample with a local oscillator signal generated separately by a four-wave mixing process. These are mixed and demodulated by spectral interferometry. Its confocal configuration allows the acquisition of 3D images based on endogenous molecular signatures. Images from both phantom and mammary tissues have been acquired by this instrument and its spectrum is compared with its spontaneous Raman signatures.

Imaging of human tooth using ultrasound based chirp-coded nonlinear time reversal acoustics.

PubMed

Dos Santos, Serge; Prevorovsky, Zdenek

2011-08-01

Human tooth imaging sonography is investigated experimentally with an acousto-optic noncoupling set-up based on the chirp-coded nonlinear time reversal acoustic concept. The complexity of the tooth internal structure (enamel-dentine interface, cracks between internal tubules) is analyzed by adapting the nonlinear elastic wave spectroscopy (NEWS) with the objective of the tomography of damage. Optimization of excitations using intrinsic symmetries, such as time reversal (TR) invariance, reciprocity, correlation properties are then proposed and implemented experimentally. The proposed medical application of this TR-NEWS approach is implemented on a third molar human tooth and constitutes an alternative of noncoupling echodentography techniques. A 10 MHz bandwidth ultrasonic instrumentation has been developed including a laser vibrometer and a 20 MHz contact piezoelectric transducer. The calibrated chirp-coded TR-NEWS imaging of the tooth is obtained using symmetrized excitations, pre- and post-signal processing, and the highly sensitive 14 bit resolution TR-NEWS instrumentation previously calibrated. Nonlinear signature coming from the symmetry properties is observed experimentally in the tooth using this bi-modal TR-NEWS imaging after and before the focusing induced by the time-compression process. The TR-NEWS polar B-scan of the tooth is described and suggested as a potential application for modern echodentography. It constitutes the basis of the self-consistent harmonic imaging sonography for monitoring cracks propagation in the dentine, responsible of human tooth structural health. Copyright © 2011 Elsevier B.V. All rights reserved.

Nonlinear adaptive optics: aberration correction in three photon fluorescence microscopy for mouse brain imaging

NASA Astrophysics Data System (ADS)

Sinefeld, David; Paudel, Hari P.; Wang, Tianyu; Wang, Mengran; Ouzounov, Dimitre G.; Bifano, Thomas G.; Xu, Chris

2017-02-01

Multiphoton fluorescence microscopy is a well-established technique for deep-tissue imaging with subcellular resolution. Three-photon microscopy (3PM) when combined with long wavelength excitation was shown to allow deeper imaging than two-photon microscopy (2PM) in biological tissues, such as mouse brain, because out-of-focus background light can be further reduced due to the higher order nonlinear excitation. As was demonstrated in 2PM systems, imaging depth and resolution can be improved by aberration correction using adaptive optics (AO) techniques which are based on shaping the scanning beam using a spatial light modulator (SLM). In this way, it is possible to compensate for tissue low order aberration and to some extent, to compensate for tissue scattering. Here, we present a 3PM AO microscopy system for brain imaging. Soliton self-frequency shift is used to create a femtosecond source at 1675 nm and a microelectromechanical (MEMS) SLM serves as the wavefront shaping device. We perturb the 1020 segment SLM using a modified nonlinear version of three-point phase shifting interferometry. The nonlinearity of the fluorescence signal used for feedback ensures that the signal is increasing when the spot size decreases, allowing compensation of phase errors in an iterative optimization process without direct phase measurement. We compare the performance for different orders of nonlinear feedback, showing an exponential growth in signal improvement as the nonlinear order increases. We demonstrate the impact of the method by applying the 3PM AO system for in-vivo mouse brain imaging, showing improvement in signal at 1-mm depth inside the brain.

Bi-dimensional empirical mode decomposition based fringe-like pattern suppression in polarization interference imaging spectrometer

NASA Astrophysics Data System (ADS)

Ren, Wenyi; Cao, Qizhi; Wu, Dan; Jiang, Jiangang; Yang, Guoan; Xie, Yingge; Wang, Guodong; Zhang, Sheqi

2018-01-01

Many observers using interference imaging spectrometer were plagued by the fringe-like pattern(FP) that occurs for optical wavelengths in red and near-infrared region. It brings us more difficulties in the data processing such as the spectrum calibration, information retrieval, and so on. An adaptive method based on the bi-dimensional empirical mode decomposition was developed to suppress the nonlinear FP in polarization interference imaging spectrometer. The FP and corrected interferogram were separated effectively. Meanwhile, the stripes introduced by CCD mosaic was suppressed. The nonlinear interferogram background removal and the spectrum distortion correction were implemented as well. It provides us an alternative method to adaptively suppress the nonlinear FP without prior experimental data and knowledge. This approach potentially is a powerful tool in the fields of Fourier transform spectroscopy, holographic imaging, optical measurement based on moire fringe, etc.

Functional Nonlinear Mixed Effects Models For Longitudinal Image Data

PubMed Central

Luo, Xinchao; Zhu, Lixing; Kong, Linglong; Zhu, Hongtu

2015-01-01

Motivated by studying large-scale longitudinal image data, we propose a novel functional nonlinear mixed effects modeling (FN-MEM) framework to model the nonlinear spatial-temporal growth patterns of brain structure and function and their association with covariates of interest (e.g., time or diagnostic status). Our FNMEM explicitly quantifies a random nonlinear association map of individual trajectories. We develop an efficient estimation method to estimate the nonlinear growth function and the covariance operator of the spatial-temporal process. We propose a global test and a simultaneous confidence band for some specific growth patterns. We conduct Monte Carlo simulation to examine the finite-sample performance of the proposed procedures. We apply FNMEM to investigate the spatial-temporal dynamics of white-matter fiber skeletons in a national database for autism research. Our FNMEM may provide a valuable tool for charting the developmental trajectories of various neuropsychiatric and neurodegenerative disorders. PMID:26213453

Forty-five degree backscattering-mode nonlinear absorption imaging in turbid media.

PubMed

Cui, Liping; Knox, Wayne H

2010-01-01

Two-color nonlinear absorption imaging has been previously demonstrated with endogenous contrast of hemoglobin and melanin in turbid media using transmission-mode detection and a dual-laser technology approach. For clinical applications, it would be generally preferable to use backscattering mode detection and a simpler single-laser technology. We demonstrate that imaging in backscattering mode in turbid media using nonlinear absorption can be obtained with as little as 1-mW average power per beam with a single laser source. Images have been achieved with a detector receiving backscattered light at a 45-deg angle relative to the incoming beams' direction. We obtain images of capillary tube phantoms with resolution as high as 20 microm and penetration depth up to 0.9 mm for a 300-microm tube at SNR approximately 1 in calibrated scattering solutions. Simulation results of the backscattering and detection process using nonimaging optics are demonstrated. A Monte Carlo-based method shows that the nonlinear signal drops exponentially as the depth increases, which agrees well with our experimental results. Simulation also shows that with our current detection method, only 2% of the signal is typically collected with a 5-mm-radius detector.

Performance assessment of a compressive sensing single-pixel imaging system

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Preece, Bradley L.

2017-04-01

Conventional sensors measure the light incident at each pixel in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process to recover the image. CS has the potential to acquire imagery with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations, reconstruction accuracy, and reconstruction speed to meet operational requirements. Performance modeling of CS imagers is challenging due to the complexity and nonlinearity of the system and reconstruction algorithm. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of a two-handheld object target set was collected using an shortwave infrared single-pixel CS camera for various ranges and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques are discussed.

Chirp Scaling Algorithms for SAR Processing

NASA Technical Reports Server (NTRS)

Jin, M.; Cheng, T.; Chen, M.

1993-01-01

The chirp scaling SAR processing algorithm is both accurate and efficient. Successful implementation requires proper selection of the interval of output samples, which is a function of the chirp interval, signal sampling rate, and signal bandwidth. Analysis indicates that for both airborne and spaceborne SAR applications in the slant range domain a linear chirp scaling is sufficient. To perform nonlinear interpolation process such as to output ground range SAR images, one can use a nonlinear chirp scaling interpolator presented in this paper.

Robust Models for Optic Flow Coding in Natural Scenes Inspired by Insect Biology

PubMed Central

Brinkworth, Russell S. A.; O'Carroll, David C.

2009-01-01

The extraction of accurate self-motion information from the visual world is a difficult problem that has been solved very efficiently by biological organisms utilizing non-linear processing. Previous bio-inspired models for motion detection based on a correlation mechanism have been dogged by issues that arise from their sensitivity to undesired properties of the image, such as contrast, which vary widely between images. Here we present a model with multiple levels of non-linear dynamic adaptive components based directly on the known or suspected responses of neurons within the visual motion pathway of the fly brain. By testing the model under realistic high-dynamic range conditions we show that the addition of these elements makes the motion detection model robust across a large variety of images, velocities and accelerations. Furthermore the performance of the entire system is more than the incremental improvements offered by the individual components, indicating beneficial non-linear interactions between processing stages. The algorithms underlying the model can be implemented in either digital or analog hardware, including neuromorphic analog VLSI, but defy an analytical solution due to their dynamic non-linear operation. The successful application of this algorithm has applications in the development of miniature autonomous systems in defense and civilian roles, including robotics, miniature unmanned aerial vehicles and collision avoidance sensors. PMID:19893631

In-vivo monitoring rat skin wound healing using nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Chen, Jing; Guo, Chungen; Zhang, Fan; Xu, Yahao; Zhu, Xiaoqin; Xiong, Shuyuan; Chen, Jianxin

2014-11-01

Nonlinear optical microscopy (NLOM) was employed for imaging and evaluating the wound healing process on rat skin in vivo. From the high-resolution nonlinear optical images, the morphology and distribution of specific biological markers in cutaneous wound healing such as fibrin clot, collagens, blood capillaries, and hairs were clearly observed at 1, 5 and 14 days post injury. We found that the disordered collagen in the fibrin clot at day 1 was replaced by regenerative collagen at day 5. By day 14, the thick collagen with well-network appeared at the original margin of the wound. These findings suggested that NLOM is ideal for noninvasively monitoring the progress of wound healing in vivo.

A novel image enhancement algorithm based on stationary wavelet transform for infrared thermography to the de-bonding defect in solid rocket motors

NASA Astrophysics Data System (ADS)

Liu, Tao; Zhang, Wei; Yan, Shaoze

2015-10-01

In this paper, a multi-scale image enhancement algorithm based on low-passing filtering and nonlinear transformation is proposed for infrared testing image of the de-bonding defect in solid propellant rocket motors. Infrared testing images with high-level noise and low contrast are foundations for identifying defects and calculating the defects size. In order to improve quality of the infrared image, according to distribution properties of the detection image, within framework of stationary wavelet transform, the approximation coefficients at suitable decomposition level is processed by index low-passing filtering by using Fourier transform, after that, the nonlinear transformation is applied to further process the figure to improve the picture contrast. To verify validity of the algorithm, the image enhancement algorithm is applied to infrared testing pictures of two specimens with de-bonding defect. Therein, one specimen is made of a type of high-strength steel, and the other is a type of carbon fiber composite. As the result shown, in the images processed by the image enhancement algorithm presented in the paper, most of noises are eliminated, and contrast between defect areas and normal area is improved greatly; in addition, by using the binary picture of the processed figure, the continuous defect edges can be extracted, all of which show the validity of the algorithm. The paper provides a well-performing image enhancement algorithm for the infrared thermography.

Nonlinear microscopy of collagen fibers

NASA Astrophysics Data System (ADS)

Strupler, M.; Pena, A.-M.; Hernest, M.; Tharaux, P.-L.; Fabre, A.; Marchal-Somme, J.; Crestani, B.; Débarre, D.; Martin, J.-L.; Beaurepaire, E.; Schanne-Klein, M.-C.

2007-02-01

We used intrinsic Second Harmonic Generation (SHG) by fibrillar collagen to visualize the three-dimensional architecture of collagen fibrosis at the micrometer scale using laser scanning nonlinear microscopy. We showed that SHG signals are highly specific to fibrillar collagen and provide a sensitive probe of the micrometer-scale structural organization of collagen in tissues. Moreover, recording simultaneously other nonlinear optical signals in a multimodal setup, we visualized the tissue morphology using Two-Photon Excited Fluorescence (2PEF) signals from endogenous chromophores such as NADH or elastin. We then compared different methods to determine accurate indexes of collagen fibrosis using nonlinear microscopy, given that most collagen fibrils are smaller than the microscope resolution and that second harmonic generation is a coherent process. In order to define a robust method to process our three-dimensional images, we either calculated the fraction of the images occupied by a significant SHG signal, or averaged SHG signal intensities. We showed that these scores provide an estimation of the extension of renal and pulmonary fibrosis in murine models, and that they clearly sort out the fibrotic mice.

Nonlinear propagation in ultrasonic fields: measurements, modelling and harmonic imaging.

PubMed

Humphrey, V F

2000-03-01

In high amplitude ultrasonic fields, such as those used in medical ultrasound, nonlinear propagation can result in waveform distortion and the generation of harmonics of the initial frequency. In the nearfield of a transducer this process is complicated by diffraction effects associated with the source. The results of a programme to study the nonlinear propagation in the fields of circular, focused and rectangular transducers are described, and comparisons made with numerical predictions obtained using a finite difference solution to the Khokhlov-Zabolotskaya-Kuznetsov (or KZK) equation. These results are extended to consider nonlinear propagation in tissue-like media and the implications for ultrasonic measurements and ultrasonic heating are discussed. The narrower beamwidths and reduced side-lobe levels of the harmonic beams are illustrated and the use of harmonics to form diagnostic images with improved resolution is described.

A cost-effective line-based light-balancing technique using adaptive processing.

PubMed

Hsia, Shih-Chang; Chen, Ming-Huei; Chen, Yu-Min

2006-09-01

The camera imaging system has been widely used; however, the displaying image appears to have an unequal light distribution. This paper presents novel light-balancing techniques to compensate uneven illumination based on adaptive signal processing. For text image processing, first, we estimate the background level and then process each pixel with nonuniform gain. This algorithm can balance the light distribution while keeping a high contrast in the image. For graph image processing, the adaptive section control using piecewise nonlinear gain is proposed to equalize the histogram. Simulations show that the performance of light balance is better than the other methods. Moreover, we employ line-based processing to efficiently reduce the memory requirement and the computational cost to make it applicable in real-time systems.

Modeling of biologically motivated self-learning equivalent-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for image fragments clustering and recognition

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2018-03-01

The biologically-motivated self-learning equivalence-convolutional recurrent-multilayer neural structures (BLM_SL_EC_RMNS) for fragments images clustering and recognition will be discussed. We shall consider these neural structures and their spatial-invariant equivalental models (SIEMs) based on proposed equivalent two-dimensional functions of image similarity and the corresponding matrix-matrix (or tensor) procedures using as basic operations of continuous logic and nonlinear processing. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalent weighing of input patterns. We show that these SL_EC_RMNSs have several advantages, such as the self-study and self-identification of features and signs of the similarity of fragments, ability to clustering and recognize of image fragments with best efficiency and strong mutual correlation. The proposed combined with learning-recognition clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively continuous logic and nonlinear processing algorithms and to k-average method or method the winner takes all (WTA). The experimental results confirmed that fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an images of different dimensions (a reference array) and fragments with diferent dimensions for clustering is carried out. The experiments, using the software environment Mathcad showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. The experimental results show that such models can be successfully used for auto- and hetero-associative recognition. Also they can be used to explain some mechanisms, known as "the reinforcementinhibition concept". Also we demonstrate a real model experiments, which confirm that the nonlinear processing by equivalent function allow to determine the neuron-winners and customize the weight matrix. At the end of the report, we will show how to use the obtained results and to propose new more efficient hardware architecture of SL_EC_RMNS based on matrix-tensor multipliers. Also we estimate the parameters and performance of such architectures.

Knowledge Driven Image Mining with Mixture Density Mercer Kernels

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Oza, Nikunj

2004-01-01

This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels; which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper, we present the theory of Mercer Kernels, describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

Knowledge Driven Image Mining with Mixture Density Mercer Kernals

NASA Technical Reports Server (NTRS)

Srivastava, Ashok N.; Oza, Nikunj

2004-01-01

This paper presents a new methodology for automatic knowledge driven image mining based on the theory of Mercer Kernels, which are highly nonlinear symmetric positive definite mappings from the original image space to a very high, possibly infinite dimensional feature space. In that high dimensional feature space, linear clustering, prediction, and classification algorithms can be applied and the results can be mapped back down to the original image space. Thus, highly nonlinear structure in the image can be recovered through the use of well-known linear mathematics in the feature space. This process has a number of advantages over traditional methods in that it allows for nonlinear interactions to be modelled with only a marginal increase in computational costs. In this paper we present the theory of Mercer Kernels; describe its use in image mining, discuss a new method to generate Mercer Kernels directly from data, and compare the results with existing algorithms on data from the MODIS (Moderate Resolution Spectral Radiometer) instrument taken over the Arctic region. We also discuss the potential application of these methods on the Intelligent Archive, a NASA initiative for developing a tagged image data warehouse for the Earth Sciences.

The Statistics of Visual Representation

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.; Rahman, Zia-Ur; Woodell, Glenn A.

2002-01-01

The experience of retinex image processing has prompted us to reconsider fundamental aspects of imaging and image processing. Foremost is the idea that a good visual representation requires a non-linear transformation of the recorded (approximately linear) image data. Further, this transformation appears to converge on a specific distribution. Here we investigate the connection between numerical and visual phenomena. Specifically the questions explored are: (1) Is there a well-defined consistent statistical character associated with good visual representations? (2) Does there exist an ideal visual image? And (3) what are its statistical properties?

Air-Coupled Vibrometry

NASA Astrophysics Data System (ADS)

Döring, D.; Solodov, I.; Busse, G.

Sound and ultrasound in air are the products of a multitude of different processes and thus can be favorable or undesirable phenomena. Development of experimental tools for non-invasive measurements and imaging of airborne sound fields is of importance for linear and nonlinear nondestructive material testing as well as noise control in industrial or civil engineering applications. One possible solution is based on acousto-optic interaction, like light diffraction imaging. The diffraction approach usually requires a sophisticated setup with fine optical alignment barely applicable in industrial environment. This paper focuses on the application of the robust experimental tool of scanning laser vibrometry, which utilizes commercial off-the-shelf equipment. The imaging technique of air-coupled vibrometry (ACV) is based on the modulation of the optical path length by the acoustic pressure of the sound wave. The theoretical considerations focus on the analysis of acousto-optical phase modulation. The sensitivity of the ACV in detecting vibration velocity was estimated as ~1 mm/s. The ACV applications to imaging of linear airborne fields are demonstrated for leaky wave propagation and measurements of ultrasonic air-coupled transducers. For higher-intensity ultrasound, the classical nonlinear effect of the second harmonic generation was measured in air. Another nonlinear application includes a direct observation of the nonlinear air-coupled emission (NACE) from the damaged areas in solid materials. The source of the NACE is shown to be strongly localized around the damage and proposed as a nonlinear "tag" to discern and image the defects.

BP fusion model for the detection of oil spills on the sea by remote sensing

NASA Astrophysics Data System (ADS)

Chen, Weiwei; An, Jubai; Zhang, Hande; Lin, Bin

2003-06-01

Oil spills are very serious marine pollution in many countries. In order to detect and identify the oil-spilled on the sea by remote sensor, scientists have to conduct a research work on the remote sensing image. As to the detection of oil spills on the sea, edge detection is an important technology in image processing. There are many algorithms of edge detection developed for image processing. These edge detection algorithms always have their own advantages and disadvantages in the image processing. Based on the primary requirements of edge detection of the oil spills" image on the sea, computation time and detection accuracy, we developed a fusion model. The model employed a BP neural net to fuse the detection results of simple operators. The reason we selected BP neural net as the fusion technology is that the relation between simple operators" result of edge gray level and the image"s true edge gray level is nonlinear, while BP neural net is good at solving the nonlinear identification problem. Therefore in this paper we trained a BP neural net by some oil spill images, then applied the BP fusion model on the edge detection of other oil spill images and obtained a good result. In this paper the detection result of some gradient operators and Laplacian operator are also compared with the result of BP fusion model to analysis the fusion effect. At last the paper pointed out that the fusion model has higher accuracy and higher speed in the processing oil spill image"s edge detection.

Iterative nonlinear joint transform correlation for the detection of objects in cluttered scenes

NASA Astrophysics Data System (ADS)

Haist, Tobias; Tiziani, Hans J.

1999-03-01

An iterative correlation technique with digital image processing in the feedback loop for the detection of small objects in cluttered scenes is proposed. A scanning aperture is combined with the method in order to improve the immunity against noise and clutter. Multiple reference objects or different views of one object are processed in parallel. We demonstrate the method by detecting a noisy and distorted face in a crowd with a nonlinear joint transform correlator.

Optical image encryption system using nonlinear approach based on biometric authentication

NASA Astrophysics Data System (ADS)

Verma, Gaurav; Sinha, Aloka

2017-07-01

A nonlinear image encryption scheme using phase-truncated Fourier transform (PTFT) and natural logarithms is proposed in this paper. With the help of the PTFT, the input image is truncated into phase and amplitude parts at the Fourier plane. The phase-only information is kept as the secret key for the decryption, and the amplitude distribution is modulated by adding an undercover amplitude random mask in the encryption process. Furthermore, the encrypted data is kept hidden inside the face biometric-based phase mask key using the base changing rule of logarithms for secure transmission. This phase mask is generated through principal component analysis. Numerical experiments show the feasibility and the validity of the proposed nonlinear scheme. The performance of the proposed scheme has been studied against the brute force attacks and the amplitude-phase retrieval attack. Simulation results are presented to illustrate the enhanced system performance with desired advantages in comparison to the linear cryptosystem.

Analyses of requirements for computer control and data processing experiment subsystems. Volume 1: ATM experiment S-056 image data processing system techniques development

NASA Technical Reports Server (NTRS)

1972-01-01

The solar imaging X-ray telescope experiment (designated the S-056 experiment) is described. It will photograph the sun in the far ultraviolet or soft X-ray region. Because of the imaging characteristics of this telescope and the necessity of using special techniques for capturing images on film at these wave lengths, methods were developed for computer processing of the photographs. The problems of image restoration were addressed to develop and test digital computer techniques for applying a deconvolution process to restore overall S-056 image quality. Additional techniques for reducing or eliminating the effects of noise and nonlinearity in S-056 photographs were developed.

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging.

PubMed

Yi, Tianzhu; He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-11-07

This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data.

Brain shift computation using a fully nonlinear biomechanical model.

PubMed

Wittek, Adam; Kikinis, Ron; Warfield, Simon K; Miller, Karol

2005-01-01

In the present study, fully nonlinear (i.e. accounting for both geometric and material nonlinearities) patient specific finite element brain model was applied to predict deformation field within the brain during the craniotomy-induced brain shift. Deformation of brain surface was used as displacement boundary conditions. Application of the computed deformation field to align (i.e. register) the preoperative images with the intraoperative ones indicated that the model very accurately predicts the displacements of gravity centers of the lateral ventricles and tumor even for very limited information about the brain surface deformation. These results are sufficient to suggest that nonlinear biomechanical models can be regarded as one possible way of complementing medical image processing techniques when conducting nonrigid registration. Important advantage of such models over the linear ones is that they do not require unrealistic assumptions that brain deformations are infinitesimally small and brain tissue stress-strain relationship is linear.

Modeling and possible implementation of self-learning equivalence-convolutional neural structures for auto-encoding-decoding and clusterization of images

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Lazarev, Alexander A.; Nikitovich, Diana V.

2017-08-01

Self-learning equivalent-convolutional neural structures (SLECNS) for auto-coding-decoding and image clustering are discussed. The SLECNS architectures and their spatially invariant equivalent models (SI EMs) using the corresponding matrix-matrix procedures with basic operations of continuous logic and non-linear processing are proposed. These SI EMs have several advantages, such as the ability to recognize image fragments with better efficiency and strong cross correlation. The proposed clustering method of fragments with regard to their structural features is suitable not only for binary, but also color images and combines self-learning and the formation of weight clustered matrix-patterns. Its model is constructed and designed on the basis of recursively processing algorithms and to k-average method. The experimental results confirmed that larger images and 2D binary fragments with a large numbers of elements may be clustered. For the first time the possibility of generalization of these models for space invariant case is shown. The experiment for an image with dimension of 256x256 (a reference array) and fragments with dimensions of 7x7 and 21x21 for clustering is carried out. The experiments, using the software environment Mathcad, showed that the proposed method is universal, has a significant convergence, the small number of iterations is easily, displayed on the matrix structure, and confirmed its prospects. Thus, to understand the mechanisms of self-learning equivalence-convolutional clustering, accompanying her to the competitive processes in neurons, and the neural auto-encoding-decoding and recognition principles with the use of self-learning cluster patterns is very important which used the algorithm and the principles of non-linear processing of two-dimensional spatial functions of images comparison. These SIEMs can simply describe the signals processing during the all training and recognition stages and they are suitable for unipolar-coding multilevel signals. We show that the implementation of SLECNS based on known equivalentors or traditional correlators is possible if they are based on proposed equivalental two-dimensional functions of image similarity. The clustering efficiency in such models and their implementation depends on the discriminant properties of neural elements of hidden layers. Therefore, the main models and architecture parameters and characteristics depends on the applied types of non-linear processing and function used for image comparison or for adaptive-equivalental weighing of input patterns. Real model experiments in Mathcad are demonstrated, which confirm that non-linear processing on equivalent functions allows you to determine the neuron winners and adjust the weight matrix. Experimental results have shown that such models can be successfully used for auto- and hetero-associative recognition. They can also be used to explain some mechanisms known as "focus" and "competing gain-inhibition concept". The SLECNS architecture and hardware implementations of its basic nodes based on multi-channel convolvers and correlators with time integration are proposed. The parameters and performance of such architectures are estimated.

Towards automated segmentation of cells and cell nuclei in nonlinear optical microscopy.

PubMed

Medyukhina, Anna; Meyer, Tobias; Schmitt, Michael; Romeike, Bernd F M; Dietzek, Benjamin; Popp, Jürgen

2012-11-01

Nonlinear optical (NLO) imaging techniques based e.g. on coherent anti-Stokes Raman scattering (CARS) or two photon excited fluorescence (TPEF) show great potential for biomedical imaging. In order to facilitate the diagnostic process based on NLO imaging, there is need for an automated calculation of quantitative values such as cell density, nucleus-to-cytoplasm ratio, average nuclear size. Extraction of these parameters is helpful for the histological assessment in general and specifically e.g. for the determination of tumor grades. This requires an accurate image segmentation and detection of locations and boundaries of cells and nuclei. Here we present an image processing approach for the detection of nuclei and cells in co-registered TPEF and CARS images. The algorithm developed utilizes the gray-scale information for the detection of the nuclei locations and the gradient information for the delineation of the nuclear and cellular boundaries. The approach reported is capable for an automated segmentation of cells and nuclei in multimodal TPEF-CARS images of human brain tumor samples. The results are important for the development of NLO microscopy into a clinically relevant diagnostic tool. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Grid Computing Application for Brain Magnetic Resonance Image Processing

NASA Astrophysics Data System (ADS)

Valdivia, F.; Crépeault, B.; Duchesne, S.

2012-02-01

This work emphasizes the use of grid computing and web technology for automatic post-processing of brain magnetic resonance images (MRI) in the context of neuropsychiatric (Alzheimer's disease) research. Post-acquisition image processing is achieved through the interconnection of several individual processes into pipelines. Each process has input and output data ports, options and execution parameters, and performs single tasks such as: a) extracting individual image attributes (e.g. dimensions, orientation, center of mass), b) performing image transformations (e.g. scaling, rotation, skewing, intensity standardization, linear and non-linear registration), c) performing image statistical analyses, and d) producing the necessary quality control images and/or files for user review. The pipelines are built to perform specific sequences of tasks on the alphanumeric data and MRIs contained in our database. The web application is coded in PHP and allows the creation of scripts to create, store and execute pipelines and their instances either on our local cluster or on high-performance computing platforms. To run an instance on an external cluster, the web application opens a communication tunnel through which it copies the necessary files, submits the execution commands and collects the results. We present result on system tests for the processing of a set of 821 brain MRIs from the Alzheimer's Disease Neuroimaging Initiative study via a nonlinear registration pipeline composed of 10 processes. Our results show successful execution on both local and external clusters, and a 4-fold increase in performance if using the external cluster. However, the latter's performance does not scale linearly as queue waiting times and execution overhead increase with the number of tasks to be executed.

A biological phantom for evaluation of CT image reconstruction algorithms

NASA Astrophysics Data System (ADS)

Cammin, J.; Fung, G. S. K.; Fishman, E. K.; Siewerdsen, J. H.; Stayman, J. W.; Taguchi, K.

2014-03-01

In recent years, iterative algorithms have become popular in diagnostic CT imaging to reduce noise or radiation dose to the patient. The non-linear nature of these algorithms leads to non-linearities in the imaging chain. However, the methods to assess the performance of CT imaging systems were developed assuming the linear process of filtered backprojection (FBP). Those methods may not be suitable any longer when applied to non-linear systems. In order to evaluate the imaging performance, a phantom is typically scanned and the image quality is measured using various indices. For reasons of practicality, cost, and durability, those phantoms often consist of simple water containers with uniform cylinder inserts. However, these phantoms do not represent the rich structure and patterns of real tissue accurately. As a result, the measured image quality or detectability performance for lesions may not reflect the performance on clinical images. The discrepancy between estimated and real performance may be even larger for iterative methods which sometimes produce "plastic-like", patchy images with homogeneous patterns. Consequently, more realistic phantoms should be used to assess the performance of iterative algorithms. We designed and constructed a biological phantom consisting of porcine organs and tissue that models a human abdomen, including liver lesions. We scanned the phantom on a clinical CT scanner and compared basic image quality indices between filtered backprojection and an iterative reconstruction algorithm.

Harmonic vibro-acoustography.

PubMed

Chen, Shigao; Kinnick, Randall R; Greenleaf, James F; Fatemi, Mostafa

2007-07-01

Vibro-acoustography is an imaging method that uses the radiation force of two interfering ultrasound beams of slightly different frequency to probe an object. An image is made using the acoustic emission resulted from the object vibration at the difference frequency. In this paper, the feasibility of imaging objects at twice the difference frequency (harmonic acoustic emission) is studied. Several possible origins of harmonic acoustic emission are explored. As an example, it is shown that microbubbles close to resonance can produce significant harmonic acoustic emission due to its high nonlinearity. Experiments demonstrate that, compared to the fundamental acoustic emission, harmonic acoustic emission greatly improves the contrast between microbubbles and other objects in vibro-acoustography (an improvement of 17-23 dB in these experiments). Applications of this technique include imaging the nonlinearity of the object and selective detection of microbubbles for perfusion imaging. The impact of microbubble destruction during the imaging process also is discussed.

Image classification using multiscale information fusion based on saliency driven nonlinear diffusion filtering.

PubMed

Hu, Weiming; Hu, Ruiguang; Xie, Nianhua; Ling, Haibin; Maybank, Stephen

2014-04-01

In this paper, we propose saliency driven image multiscale nonlinear diffusion filtering. The resulting scale space in general preserves or even enhances semantically important structures such as edges, lines, or flow-like structures in the foreground, and inhibits and smoothes clutter in the background. The image is classified using multiscale information fusion based on the original image, the image at the final scale at which the diffusion process converges, and the image at a midscale. Our algorithm emphasizes the foreground features, which are important for image classification. The background image regions, whether considered as contexts of the foreground or noise to the foreground, can be globally handled by fusing information from different scales. Experimental tests of the effectiveness of the multiscale space for the image classification are conducted on the following publicly available datasets: 1) the PASCAL 2005 dataset; 2) the Oxford 102 flowers dataset; and 3) the Oxford 17 flowers dataset, with high classification rates.

k-t Acceleration in pure phase encode MRI to monitor dynamic flooding processes in rock core plugs

NASA Astrophysics Data System (ADS)

Xiao, Dan; Balcom, Bruce J.

2014-06-01

Monitoring the pore system in sedimentary rocks with MRI when fluids are introduced is very important in the study of petroleum reservoirs and enhanced oil recovery. However, the lengthy acquisition time of each image, with pure phase encode MRI, limits the temporal resolution. Spatiotemporal correlations can be exploited to undersample the k-t space data. The stacked frames/profiles can be well approximated by an image matrix with rank deficiency, which can be recovered by nonlinear nuclear norm minimization. Sparsity of the x-t image can also be exploited for nonlinear reconstruction. In this work the results of a low rank matrix completion technique were compared with k-t sparse compressed sensing. These methods are demonstrated with one dimensional SPRITE imaging of a Bentheimer rock core plug and SESPI imaging of a Berea rock core plug, but can be easily extended to higher dimensionality and/or other pure phase encode measurements. These ideas will enable higher dimensionality pure phase encode MRI studies of dynamic flooding processes in low magnetic field systems.

Multiphoton microscopy for the in-situ investigation of cellular processes and integrity in cryopreservation.

PubMed

Doerr, Daniel; Stark, Martin; Ehrhart, Friederike; Zimmermann, Heiko; Stracke, Frank

2009-08-01

In this study we demonstrate a new noninvasive imaging method to monitor freezing processes in biological samples and to investigate life in the frozen state. It combines a laser scanning microscope with a computer-controlled cryostage. Nearinfrared (NIR) femtosecond laser pulses evoke the fluorescence of endogenous fluorophores and fluorescent labels due to multiphoton absorption.The inherent optical nonlinearity of multiphoton absorption allows 3D fluorescence imaging for optical tomography of frozen biological material in-situ. As an example for functional imaging we use fluorescence lifetime imaging (FLIM) to create images with chemical and physical contrast.

STAMPS: Software Tool for Automated MRI Post-processing on a supercomputer.

PubMed

Bigler, Don C; Aksu, Yaman; Miller, David J; Yang, Qing X

2009-08-01

This paper describes a Software Tool for Automated MRI Post-processing (STAMP) of multiple types of brain MRIs on a workstation and for parallel processing on a supercomputer (STAMPS). This software tool enables the automation of nonlinear registration for a large image set and for multiple MR image types. The tool uses standard brain MRI post-processing tools (such as SPM, FSL, and HAMMER) for multiple MR image types in a pipeline fashion. It also contains novel MRI post-processing features. The STAMP image outputs can be used to perform brain analysis using Statistical Parametric Mapping (SPM) or single-/multi-image modality brain analysis using Support Vector Machines (SVMs). Since STAMPS is PBS-based, the supercomputer may be a multi-node computer cluster or one of the latest multi-core computers.

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

PubMed Central

He, Zhihua; He, Feng; Dong, Zhen; Wu, Manqing

2017-01-01

This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data. PMID:29112151

Beyond endoscopic assessment in inflammatory bowel disease: real-time histology of disease activity by non-linear multimodal imaging

NASA Astrophysics Data System (ADS)

Chernavskaia, Olga; Heuke, Sandro; Vieth, Michael; Friedrich, Oliver; Schürmann, Sebastian; Atreya, Raja; Stallmach, Andreas; Neurath, Markus F.; Waldner, Maximilian; Petersen, Iver; Schmitt, Michael; Bocklitz, Thomas; Popp, Jürgen

2016-07-01

Assessing disease activity is a prerequisite for an adequate treatment of inflammatory bowel diseases (IBD) such as Crohn’s disease and ulcerative colitis. In addition to endoscopic mucosal healing, histologic remission poses a promising end-point of IBD therapy. However, evaluating histological remission harbors the risk for complications due to the acquisition of biopsies and results in a delay of diagnosis because of tissue processing procedures. In this regard, non-linear multimodal imaging techniques might serve as an unparalleled technique that allows the real-time evaluation of microscopic IBD activity in the endoscopy unit. In this study, tissue sections were investigated using the non-linear multimodal microscopy combination of coherent anti-Stokes Raman scattering (CARS), two-photon excited auto fluorescence (TPEF) and second-harmonic generation (SHG). After the measurement a gold-standard assessment of histological indexes was carried out based on a conventional H&E stain. Subsequently, various geometry and intensity related features were extracted from the multimodal images. An optimized feature set was utilized to predict histological index levels based on a linear classifier. Based on the automated prediction, the diagnosis time interval is decreased. Therefore, non-linear multimodal imaging may provide a real-time diagnosis of IBD activity suited to assist clinical decision making within the endoscopy unit.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Jianjun; Shen, Dongyi; Feng, Yaming

Negative refraction has attracted much interest for its promising capability in imaging applications. Such an effect can be implemented by negative index meta-materials, however, which are usually accompanied by high loss and demanding fabrication processes. Recently, alternative nonlinear approaches like phase conjugation and four wave mixing have shown advantages of low-loss and easy-to-implement, but associated problems like narrow accepting angles can still halt their practical applications. Here, we demonstrate theoretically and experimentally a scheme to realize negative refraction by nonlinear difference frequency generation with wide tunability, where a thin Beta barium borate slice serves as a negative refraction layer bendingmore » the input signal beam to the idler beam at a negative angle. Furthermore, we realize optical focusing effect using such nonlinear negative refraction, which may enable many potential applications in imaging science.« less

Sources of image degradation in fundamental and harmonic ultrasound imaging using nonlinear, full-wave simulations.

PubMed

Pinton, Gianmarco F; Trahey, Gregg E; Dahl, Jeremy J

2011-04-01

A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain (FDTD). This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-andsum beamforming is used to generate point spread functions (PSF) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is reverberation from near-field structures. Reverberation clutter in the harmonic PSF is 26 dB higher than the fundamental PSF. An artificial medium with uniform velocity but unchanged impedance characteristics indicates that for the fundamental PSF, the primary source of degradation is phase aberration. An ultrasound image is created in silico using the same physical and algorithmic process used in an ultrasound scanner: a series of pulses are transmitted through heterogeneous scattering tissue and the received echoes are used in a delay-and-sum beamforming algorithm to generate images. These beamformed images are compared with images obtained from convolution of the PSF with a scatterer field to demonstrate that a very large portion of the PSF must be used to accurately represent the clutter observed in conventional imaging. © 2011 IEEE

Live animal myelin histomorphometry of the spinal cord with video-rate multimodal nonlinear microendoscopy

NASA Astrophysics Data System (ADS)

Bélanger, Erik; Crépeau, Joël; Laffray, Sophie; Vallée, Réal; De Koninck, Yves; Côté, Daniel

2012-02-01

In vivo imaging of cellular dynamics can be dramatically enabling to understand the pathophysiology of nervous system diseases. To fully exploit the power of this approach, the main challenges have been to minimize invasiveness and maximize the number of concurrent optical signals that can be combined to probe the interplay between multiple cellular processes. Label-free coherent anti-Stokes Raman scattering (CARS) microscopy, for example, can be used to follow demyelination in neurodegenerative diseases or after trauma, but myelin imaging alone is not sufficient to understand the complex sequence of events that leads to the appearance of lesions in the white matter. A commercially available microendoscope is used here to achieve minimally invasive, video-rate multimodal nonlinear imaging of cellular processes in live mouse spinal cord. The system allows for simultaneous CARS imaging of myelin sheaths and two-photon excitation fluorescence microendoscopy of microglial cells and axons. Morphometric data extraction at high spatial resolution is also described, with a technique for reducing motion-related imaging artifacts. Despite its small diameter, the microendoscope enables high speed multimodal imaging over wide areas of tissue, yet at resolution sufficient to quantify subtle differences in myelin thickness and microglial motility.

An extended algebraic reconstruction technique (E-ART) for dual spectral CT.

PubMed

Zhao, Yunsong; Zhao, Xing; Zhang, Peng

2015-03-01

Compared with standard computed tomography (CT), dual spectral CT (DSCT) has many advantages for object separation, contrast enhancement, artifact reduction, and material composition assessment. But it is generally difficult to reconstruct images from polychromatic projections acquired by DSCT, because of the nonlinear relation between the polychromatic projections and the images to be reconstructed. This paper first models the DSCT reconstruction problem as a nonlinear system problem; and then extend the classic ART method to solve the nonlinear system. One feature of the proposed method is its flexibility. It fits for any scanning configurations commonly used and does not require consistent rays for different X-ray spectra. Another feature of the proposed method is its high degree of parallelism, which means that the method is suitable for acceleration on GPUs (graphic processing units) or other parallel systems. The method is validated with numerical experiments from simulated noise free and noisy data. High quality images are reconstructed with the proposed method from the polychromatic projections of DSCT. The reconstructed images are still satisfactory even if there are certain errors in the estimated X-ray spectra.

A digital ISO expansion technique for digital cameras

NASA Astrophysics Data System (ADS)

Yoo, Youngjin; Lee, Kangeui; Choe, Wonhee; Park, SungChan; Lee, Seong-Deok; Kim, Chang-Yong

2010-01-01

Market's demands of digital cameras for higher sensitivity capability under low-light conditions are remarkably increasing nowadays. The digital camera market is now a tough race for providing higher ISO capability. In this paper, we explore an approach for increasing maximum ISO capability of digital cameras without changing any structure of an image sensor or CFA. Our method is directly applied to the raw Bayer pattern CFA image to avoid non-linearity characteristics and noise amplification which are usually deteriorated after ISP (Image Signal Processor) of digital cameras. The proposed method fuses multiple short exposed images which are noisy, but less blurred. Our approach is designed to avoid the ghost artifact caused by hand-shaking and object motion. In order to achieve a desired ISO image quality, both low frequency chromatic noise and fine-grain noise that usually appear in high ISO images are removed and then we modify the different layers which are created by a two-scale non-linear decomposition of an image. Once our approach is performed on an input Bayer pattern CFA image, the resultant Bayer image is further processed by ISP to obtain a fully processed RGB image. The performance of our proposed approach is evaluated by comparing SNR (Signal to Noise Ratio), MTF50 (Modulation Transfer Function), color error ~E*ab and visual quality with reference images whose exposure times are properly extended into a variety of target sensitivity.

Nonlinear optical response of the collagen triple helix and second harmonic microscopy of collagen liquid crystals

NASA Astrophysics Data System (ADS)

Deniset-Besseau, A.; De Sa Peixoto, P.; Duboisset, J.; Loison, C.; Hache, F.; Benichou, E.; Brevet, P.-F.; Mosser, G.; Schanne-Klein, M.-C.

2010-02-01

Collagen is characterized by triple helical domains and plays a central role in the formation of fibrillar and microfibrillar networks, basement membranes, as well as other structures of the connective tissue. Remarkably, fibrillar collagen exhibits efficient Second Harmonic Generation (SHG) and SHG microscopy proved to be a sensitive tool to score fibrotic pathologies. However, the nonlinear optical response of fibrillar collagen is not fully characterized yet and quantitative data are required to further process SHG images. We therefore performed Hyper-Rayleigh Scattering (HRS) experiments and measured a second order hyperpolarisability of 1.25 10-27 esu for rat-tail type I collagen. This value is surprisingly large considering that collagen presents no strong harmonophore in its amino-acid sequence. In order to get insight into the physical origin of this nonlinear process, we performed HRS measurements after denaturation of the collagen triple helix and for a collagen-like short model peptide [(Pro-Pro-Gly)10]3. It showed that the collagen large nonlinear response originates in the tight alignment of a large number of weakly efficient harmonophores, presumably the peptide bonds, resulting in a coherent amplification of the nonlinear signal along the triple helix. To illustrate this mechanism, we successfully recorded SHG images in collagen liquid solutions by achieving liquid crystalline ordering of the collagen triple helices.

Fast and Accurate Poisson Denoising With Trainable Nonlinear Diffusion.

PubMed

Feng, Wensen; Qiao, Peng; Chen, Yunjin; Wensen Feng; Peng Qiao; Yunjin Chen; Feng, Wensen; Chen, Yunjin; Qiao, Peng

2018-06-01

The degradation of the acquired signal by Poisson noise is a common problem for various imaging applications, such as medical imaging, night vision, and microscopy. Up to now, many state-of-the-art Poisson denoising techniques mainly concentrate on achieving utmost performance, with little consideration for the computation efficiency. Therefore, in this paper we aim to propose an efficient Poisson denoising model with both high computational efficiency and recovery quality. To this end, we exploit the newly developed trainable nonlinear reaction diffusion (TNRD) model which has proven an extremely fast image restoration approach with performance surpassing recent state-of-the-arts. However, the straightforward direct gradient descent employed in the original TNRD-based denoising task is not applicable in this paper. To solve this problem, we resort to the proximal gradient descent method. We retrain the model parameters, including the linear filters and influence functions by taking into account the Poisson noise statistics, and end up with a well-trained nonlinear diffusion model specialized for Poisson denoising. The trained model provides strongly competitive results against state-of-the-art approaches, meanwhile bearing the properties of simple structure and high efficiency. Furthermore, our proposed model comes along with an additional advantage, that the diffusion process is well-suited for parallel computation on graphics processing units (GPUs). For images of size , our GPU implementation takes less than 0.1 s to produce state-of-the-art Poisson denoising performance.

Rank-based decompositions of morphological templates.

PubMed

Sussner, P; Ritter, G X

2000-01-01

Methods for matrix decomposition have found numerous applications in image processing, in particular for the problem of template decomposition. Since existing matrix decomposition techniques are mainly concerned with the linear domain, we consider it timely to investigate matrix decomposition techniques in the nonlinear domain with applications in image processing. The mathematical basis for these investigations is the new theory of rank within minimax algebra. Thus far, only minimax decompositions of rank 1 and rank 2 matrices into outer product expansions are known to the image processing community. We derive a heuristic algorithm for the decomposition of matrices having arbitrary rank.

Multimodal Deep Autoencoder for Human Pose Recovery.

PubMed

Hong, Chaoqun; Yu, Jun; Wan, Jian; Tao, Dacheng; Wang, Meng

2015-12-01

Video-based human pose recovery is usually conducted by retrieving relevant poses using image features. In the retrieving process, the mapping between 2D images and 3D poses is assumed to be linear in most of the traditional methods. However, their relationships are inherently non-linear, which limits recovery performance of these methods. In this paper, we propose a novel pose recovery method using non-linear mapping with multi-layered deep neural network. It is based on feature extraction with multimodal fusion and back-propagation deep learning. In multimodal fusion, we construct hypergraph Laplacian with low-rank representation. In this way, we obtain a unified feature description by standard eigen-decomposition of the hypergraph Laplacian matrix. In back-propagation deep learning, we learn a non-linear mapping from 2D images to 3D poses with parameter fine-tuning. The experimental results on three data sets show that the recovery error has been reduced by 20%-25%, which demonstrates the effectiveness of the proposed method.

A novel encryption scheme for high-contrast image data in the Fresnelet domain

PubMed Central

Bibi, Nargis; Farwa, Shabieh; Jahngir, Adnan; Usman, Muhammad

2018-01-01

In this paper, a unique and more distinctive encryption algorithm is proposed. This is based on the complexity of highly nonlinear S box in Flesnelet domain. The nonlinear pattern is transformed further to enhance the confusion in the dummy data using Fresnelet technique. The security level of the encrypted image boosts using the algebra of Galois field in Fresnelet domain. At first level, the Fresnelet transform is used to propagate the given information with desired wavelength at specified distance. It decomposes given secret data into four complex subbands. These complex sub-bands are separated into two components of real subband data and imaginary subband data. At second level, the net subband data, produced at the first level, is deteriorated to non-linear diffused pattern using the unique S-box defined on the Galois field F28. In the diffusion process, the permuted image is substituted via dynamic algebraic S-box substitution. We prove through various analysis techniques that the proposed scheme enhances the cipher security level, extensively. PMID:29608609

Reconstruction of nonlinear wave propagation

DOEpatents

Fleischer, Jason W; Barsi, Christopher; Wan, Wenjie

2013-04-23

Disclosed are systems and methods for characterizing a nonlinear propagation environment by numerically propagating a measured output waveform resulting from a known input waveform. The numerical propagation reconstructs the input waveform, and in the process, the nonlinear environment is characterized. In certain embodiments, knowledge of the characterized nonlinear environment facilitates determination of an unknown input based on a measured output. Similarly, knowledge of the characterized nonlinear environment also facilitates formation of a desired output based on a configurable input. In both situations, the input thus characterized and the output thus obtained include features that would normally be lost in linear propagations. Such features can include evanescent waves and peripheral waves, such that an image thus obtained are inherently wide-angle, farfield form of microscopy.

Solution for the nonuniformity correction of infrared focal plane arrays.

PubMed

Zhou, Huixin; Liu, Shangqian; Lai, Rui; Wang, Dabao; Cheng, Yubao

2005-05-20

Based on the S-curve model of the detector response of infrared focal plan arrays (IRFPAs), an improved two-point correction algorithm is presented. The algorithm first transforms the nonlinear image data into linear data and then uses the normal two-point algorithm to correct the linear data. The algorithm can effectively overcome the influence of nonlinearity of the detector's response, and it enlarges the correction precision and the dynamic range of the response. A real-time imaging-signal-processing system for IRFPAs that is based on a digital signal processor and field-programmable gate arrays is also presented. The nonuniformity correction capability of the presented solution is validated by experimental imaging procedures of a 128 x 128 pixel IRFPA camera prototype.

Fibre-optic nonlinear optical microscopy and endoscopy.

PubMed

Fu, L; Gu, M

2007-06-01

Nonlinear optical microscopy has been an indispensable laboratory tool of high-resolution imaging in thick tissue and live animals. Rapid developments of fibre-optic components in terms of growing functionality and decreasing size provide enormous opportunities for innovations in nonlinear optical microscopy. Fibre-based nonlinear optical endoscopy is the sole instrumentation to permit the cellular imaging within hollow tissue tracts or solid organs that are inaccessible to a conventional optical microscope. This article reviews the current development of fibre-optic nonlinear optical microscopy and endoscopy, which includes crucial technologies for miniaturized nonlinear optical microscopy and their embodiments of endoscopic systems. A particular attention is given to several classes of photonic crystal fibres that have been applied to nonlinear optical microscopy due to their unique properties for ultrashort pulse delivery and signal collection. Furthermore, fibre-optic nonlinear optical imaging systems can be classified into portable microscopes suitable for imaging behaving animals, rigid endoscopes that allow for deep tissue imaging with minimally invasive manners, and flexible endoscopes enabling imaging of internal organs. Fibre-optic nonlinear optical endoscopy is coming of age and a paradigm shift leading to optical microscope tools for early cancer detection and minimally invasive surgery.

Removing the depth-degeneracy in optical frequency domain imaging with frequency shifting

PubMed Central

Yun, S. H.; Tearney, G. J.; de Boer, J. F.; Bouma, B. E.

2009-01-01

A novel technique using an acousto-optic frequency shifter in optical frequency domain imaging (OFDI) is presented. The frequency shift eliminates the ambiguity between positive and negative differential delays, effectively doubling the interferometric ranging depth while avoiding image cross-talk. A signal processing algorithm is demonstrated to accommodate nonlinearity in the tuning slope of the wavelength-swept OFDI laser source. PMID:19484034

PREFACE: Ultrafast biophotonics Ultrafast biophotonics

NASA Astrophysics Data System (ADS)

Gu, Min; Reid, Derryck; Ben-Yakar, Adela

2010-08-01

The use of light to explore biology can be traced to the first observations of tissue made with early microscopes in the mid-seventeenth century, and has today evolved into the discipline which we now know as biophotonics. This field encompasses a diverse range of activities, each of which shares the common theme of exploiting the interaction of light with biological material. With the rapid advancement of ultrafast optical technologies over the last few decades, ultrafast lasers have increasingly found applications in biophotonics, to the extent that the distinctive new field of ultrafast biophotonics has now emerged, where robust turnkey ultrafast laser systems are facilitating cutting-edge studies in the life sciences to take place in everyday laboratories. The broad spectral bandwidths, precision timing resolution, low coherence and high peak powers of ultrafast optical pulses provide unique opportunities for imaging and manipulating biological systems. Time-resolved studies of bio-molecular dynamics exploit the short pulse durations from such lasers, while other applications such as optical coherence tomography benefit from the broad optical bandwidths possible by using super-continuum generation and additionally allowing for high speed imaging with speeds as high as 47 000 scans per second. Continuing progress in laser-system technology is accelerating the adoption of ultrafast techniques across the life sciences, both in research laboratories and in clinical applications, such as laser-assisted in situ keratomileusis (LASIK) eye surgery. Revolutionizing the field of optical microscopy, two-photon excitation fluorescence (TPEF) microscopy has enabled higher spatial resolution with improved depth penetration into biological specimens. Advantages of this nonlinear optical process include: reduced photo-interactions, allowing for extensive imaging time periods; simultaneously exciting multiple fluorescent molecules with only one excitation wavelength; and reduced chromatic aberration effects. These extensive advantages have led to further exploration of nonlinear processes including second-harmonic generation (SHG) microscopy and third-harmonic generation (THG) microscopy. Second-harmonic generation has provided biologists with an extremely powerful tool for generating contrast in biological imaging, with the additional benefit of non-invasive three-dimensional imaging. The recent popularity of THG microscopy is largely due to the fact that three-dimensional imaging is achievable without the need for any labels, but rather relying on the intrinsic properties of the biological specimen itself. This optical nonlinear technique has attracted much attention recently from the biological community due to its non-invasive capabilities. Users of ultrafast lasers in the biological and medical fields are becoming a fast-growing community, employing pulse-shaping microscopy, resolution-enhancing microscopy techniques, linear and nonlinear micro-spectroscopy, functional deep-tissue imaging, optical coherence tomography, nonlinear fluorescence microscopy, molecular imaging and control, harmonic microscopy and femtosecond lifetime imaging, for cutting-edge research concerning the interaction of light with biological dynamics. The adaptability of ultrafast lasers to interact with a large array of materials through nonlinear excitation has enabled precise control of laser fluence allowing for highly localized material interactions, permitting micro-structured fabricated surfaces. The resultant multi-dimensional fabricated micro-structures are capable of replicating and/or manipulating microenvironments for controlled cell biology. In this special issue of Journal of Optics readers have a chance to view a collection of new contributions to the growing research field of ultrafast biophotonics. They are presented with recent advances in ultrafast technology applied to biological and medical investigations, where topics include advances in the visualization and identification of photo-reaction dynamics of biological functions under relevant physiological conditions, theoretically proposed imaging designs for obtaining super-resolved optical sectioned images in single exposures and fabricated micro-structured surfaces for biological micro-environments. We hope the collection will stimulate innovative new research in this growing field by showcasing new techniques for the visualization and manipulation of complex biological systems using linear and and nonlinear optical processes. Professor Min Gu would like to acknowledge Dr Betty Kouskousis for her contribution and support towards this editorial.

Continuous functional magnetic resonance imaging reveals dynamic nonlinearities of "dose-response" curves for finger opposition.

PubMed

Berns, G S; Song, A W; Mao, H

1999-07-15

Linear experimental designs have dominated the field of functional neuroimaging, but although successful at mapping regions of relative brain activation, the technique assumes that both cognition and brain activation are linear processes. To test these assumptions, we performed a continuous functional magnetic resonance imaging (MRI) experiment of finger opposition. Subjects performed a visually paced bimanual finger-tapping task. The frequency of finger tapping was continuously varied between 1 and 5 Hz, without any rest blocks. After continuous acquisition of fMRI images, the task-related brain regions were identified with independent components analysis (ICA). When the time courses of the task-related components were plotted against tapping frequency, nonlinear "dose- response" curves were obtained for most subjects. Nonlinearities appeared in both the static and dynamic sense, with hysteresis being prominent in several subjects. The ICA decomposition also demonstrated the spatial dynamics with different components active at different times. These results suggest that the brain response to tapping frequency does not scale linearly, and that it is history-dependent even after accounting for the hemodynamic response function. This implies that finger tapping, as measured with fMRI, is a nonstationary process. When analyzed with a conventional general linear model, a strong correlation to tapping frequency was identified, but the spatiotemporal dynamics were not apparent.

The Radon cumulative distribution transform and its application to image classification

PubMed Central

Kolouri, Soheil; Park, Se Rim; Rohde, Gustavo K.

2016-01-01

Invertible image representation methods (transforms) are routinely employed as low-level image processing operations based on which feature extraction and recognition algorithms are developed. Most transforms in current use (e.g. Fourier, Wavelet, etc.) are linear transforms, and, by themselves, are unable to substantially simplify the representation of image classes for classification. Here we describe a nonlinear, invertible, low-level image processing transform based on combining the well known Radon transform for image data, and the 1D Cumulative Distribution Transform proposed earlier. We describe a few of the properties of this new transform, and with both theoretical and experimental results show that it can often render certain problems linearly separable in transform space. PMID:26685245

Separating higher-order nonlinearities in transient absorption microscopy

NASA Astrophysics Data System (ADS)

Wilson, Jesse W.; Anderson, Miguel; Park, Jong Kang; Fischer, Martin C.; Warren, Warren S.

2015-08-01

The transient absorption response of melanin is a promising optically-accessible biomarker for distinguishing malignant melanoma from benign pigmented lesions, as demonstrated by earlier experiments on thin sections from biopsied tissue. The technique has also been demonstrated in vivo, but the higher optical intensity required for detecting these signals from backscattered light introduces higher-order nonlinearities in the transient response of melanin. These components that are higher than linear with respect to the pump or the probe introduce intensity-dependent changes to the overall response that complicate data analysis. However, our data also suggest these nonlinearities might be advantageous to in vivo imaging, in that different types of melanins have different nonlinear responses. Therefore, methods to separate linear from nonlinear components in transient absorption measurements might provide additional information to aid in the diagnosis of melanoma. We will discuss numerical methods for analyzing the various nonlinear contributions to pump-probe signals, with the ultimate objective of real time analysis using digital signal processing techniques. To that end, we have replaced the lock-in amplifier in our pump-probe microscope with a high-speed data acquisition board, and reprogrammed the coprocessor field-programmable gate array (FPGA) to perform lock-in detection. The FPGA lock-in offers better performance than the commercial instrument, in terms of both signal to noise ratio and speed. In addition, the flexibility of the digital signal processing approach enables demodulation of more complicated waveforms, such as spread-spectrum sequences, which has the potential to accelerate microscopy methods that rely on slow relaxation phenomena, such as photo-thermal and phosphorescence lifetime imaging.

A robust nonlinear filter for image restoration.

PubMed

Koivunen, V

1995-01-01

A class of nonlinear regression filters based on robust estimation theory is introduced. The goal of the filtering is to recover a high-quality image from degraded observations. Models for desired image structures and contaminating processes are employed, but deviations from strict assumptions are allowed since the assumptions on signal and noise are typically only approximately true. The robustness of filters is usually addressed only in a distributional sense, i.e., the actual error distribution deviates from the nominal one. In this paper, the robustness is considered in a broad sense since the outliers may also be due to inappropriate signal model, or there may be more than one statistical population present in the processing window, causing biased estimates. Two filtering algorithms minimizing a least trimmed squares criterion are provided. The design of the filters is simple since no scale parameters or context-dependent threshold values are required. Experimental results using both real and simulated data are presented. The filters effectively attenuate both impulsive and nonimpulsive noise while recovering the signal structure and preserving interesting details.

Stability of Gradient Field Corrections for Quantitative Diffusion MRI.

PubMed

Rogers, Baxter P; Blaber, Justin; Welch, E Brian; Ding, Zhaohua; Anderson, Adam W; Landman, Bennett A

2017-02-11

In magnetic resonance diffusion imaging, gradient nonlinearity causes significant bias in the estimation of quantitative diffusion parameters such as diffusivity, anisotropy, and diffusion direction in areas away from the magnet isocenter. This bias can be substantially reduced if the scanner- and coil-specific gradient field nonlinearities are known. Using a set of field map calibration scans on a large (29 cm diameter) phantom combined with a solid harmonic approximation of the gradient fields, we predicted the obtained b-values and applied gradient directions throughout a typical field of view for brain imaging for a typical 32-direction diffusion imaging sequence. We measured the stability of these predictions over time. At 80 mm from scanner isocenter, predicted b-value was 1-6% different than intended due to gradient nonlinearity, and predicted gradient directions were in error by up to 1 degree. Over the course of one month the change in these quantities due to calibration-related factors such as scanner drift and variation in phantom placement was <0.5% for b-values, and <0.5 degrees for angular deviation. The proposed calibration procedure allows the estimation of gradient nonlinearity to correct b-values and gradient directions ahead of advanced diffusion image processing for high angular resolution data, and requires only a five-minute phantom scan that can be included in a weekly or monthly quality assurance protocol.

Removal of intensity bias in magnitude spin-echo MRI images by nonlinear diffusion filtering

NASA Astrophysics Data System (ADS)

Samsonov, Alexei A.; Johnson, Chris R.

2004-05-01

MRI data analysis is routinely done on the magnitude part of complex images. While both real and imaginary image channels contain Gaussian noise, magnitude MRI data are characterized by Rice distribution. However, conventional filtering methods often assume image noise to be zero mean and Gaussian distributed. Estimation of an underlying image using magnitude data produces biased result. The bias may lead to significant image errors, especially in areas of low signal-to-noise ratio (SNR). The incorporation of the Rice PDF into a noise filtering procedure can significantly complicate the method both algorithmically and computationally. In this paper, we demonstrate that inherent image phase smoothness of spin-echo MRI images could be utilized for separate filtering of real and imaginary complex image channels to achieve unbiased image denoising. The concept is demonstrated with a novel nonlinear diffusion filtering scheme developed for complex image filtering. In our proposed method, the separate diffusion processes are coupled through combined diffusion coefficients determined from the image magnitude. The new method has been validated with simulated and real MRI data. The new method has provided efficient denoising and bias removal in conventional and black-blood angiography MRI images obtained using fast spin echo acquisition protocols.

Observation of wave celerity evolution in the nearshore using digital video imagery

NASA Astrophysics Data System (ADS)

Yoo, J.; Fritz, H. M.; Haas, K. A.; Work, P. A.; Barnes, C. F.; Cho, Y.

2008-12-01

Celerity of incident waves in the nearshore is observed from oblique video imagery collected at Myrtle Beach, S.C.. The video camera covers the field view of length scales O(100) m. Celerity of waves propagating in shallow water including the surf zone is estimated by applying advanced image processing and analysis methods to the individual video images sampled at 3 Hz. Original image sequences are processed through video image frame differencing, directional low-pass image filtering to reduce the noise arising from foam in the surf zone. The breaking wave celerity is computed along a cross-shore transect from the wave crest tracks extracted by a Radon transform-based line detection method. The observed celerity from the nearshore video imagery is larger than the linear wave celerity computed from the measured water depths over the entire surf zone. Compared to the nonlinear shallow water wave equation (NSWE)-based celerity computed using the measured depths and wave heights, in general, the video-based celerity shows good agreements over the surf zone except the regions across the incipient wave breaking locations. In the regions across the breaker points, the observed wave celerity is even larger than the NSWE-based celerity due to the transition of wave crest shapes. The observed celerity using the video imagery can be used to monitor the nearshore geometry through depth inversion based on the nonlinear wave celerity theories. For this purpose, the exceeding celerity across the breaker points needs to be corrected accordingly compared to a nonlinear wave celerity theory applied.

Effect of nonlinearity saturation on hot-image formation in cascaded saturable nonlinear medium slabs

NASA Astrophysics Data System (ADS)

Wang, Youwen; Dai, Zhiping; Ling, Xiaohui; Chen, Liezun; Lu, Shizhuan; You, Kaiming

2016-11-01

In high-power laser system such as Petawatt lasers, the laser beam can be intense enough to result in saturation of nonlinear refraction index of medium. Based on the standard linearization method of small-scale self-focusing and the split-step Fourier numerical calculation method, we present analytical and simulative investigations on the hot-image formation in cascaded saturable nonlinear medium slabs, to disclose the effect of nonlinearity saturation on the distribution and intensity of hot images. The analytical and simulative results are found in good agreement. It is shown that, saturable nonlinearity does not change the distribution of hot images, while may greatly affect the intensity of hot images, i.e., for a given saturation light intensity, with the intensity of the incident laser beam, the intensity of hot images firstly increases monotonously and eventually reaches a saturation; for the incident laser beam of a given intensity, with the saturation light intensity lowering, the intensity of hot images decreases rapidly, even resulting in a few hot images too weak to be visible.

In-TFT-array-process micro defect inspection using nonlinear principal component analysis.

PubMed

Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang

2009-11-20

Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image.

Some New Results in Astrophysical Problems of Nonlinear Theory of Radiative Transfer

NASA Astrophysics Data System (ADS)

Pikichyan, H. V.

2017-07-01

In the interpretation of the observed astrophysical spectra, a decisive role is related to nonlinear problems of radiative transfer, because the processes of multiple interactions of matter of cosmic medium with the exciting intense radiation ubiquitously occur in astrophysical objects, and in their vicinities. Whereas, the intensity of the exciting radiation changes the physical properties of the original medium, and itself was modified, simultaneously, in a self-consistent manner under its influence. In the present report, we show that the consistent application of the principle of invariance in the nonlinear problem of bilateral external illumination of a scattering/absorbing one-dimensional anisotropic medium of finite geometrical thickness allows for simplifications that were previously considered as a prerogative only of linear problems. The nonlinear problem is analyzed through the three methods of the principle of invariance: (i) an adding of layers, (ii) its limiting form, described by differential equations of invariant imbedding, and (iii) a transition to the, so-called, functional equations of the "Ambartsumyan's complete invariance". Thereby, as an alternative to the Boltzmann equation, a new type of equations, so-called "kinetic equations of equivalence", are obtained. By the introduction of new functions - the so-called "linear images" of solution of nonlinear problem of radiative transfer, the linear structure of the solution of the nonlinear problem under study is further revealed. Linear images allow to convert naturally the statistical characteristics of random walk of a "single quantum" or their "beam of unit intensity", as well as widely known "probabilistic interpretation of phenomena of transfer", to the field of nonlinear problems. The structure of the equations obtained for determination of linear images is typical of linear problems.

Photogrammetric Modeling and Image-Based Rendering for Rapid Virtual Environment Creation

DTIC Science & Technology

2004-12-01

area and different methods have been proposed. Pertinent methods include: Camera Calibration , Structure from Motion, Stereo Correspondence, and Image...Based Rendering 1.1.1 Camera Calibration Determining the 3D structure of a model from multiple views becomes simpler if the intrinsic (or internal...can introduce significant nonlinearities into the image. We have found that camera calibration is a straightforward process which can simplify the

Compact ultrafast semiconductor disk laser: targeting GFP based nonlinear applications in living organisms

PubMed Central

Aviles-Espinosa, Rodrigo; Filippidis, George; Hamilton, Craig; Malcolm, Graeme; Weingarten, Kurt J.; Südmeyer, Thomas; Barbarin, Yohan; Keller, Ursula; Santos, Susana I.C.O; Artigas, David; Loza-Alvarez, Pablo

2011-01-01

We present a portable ultrafast Semiconductor Disk Laser (SDL) (or vertical extended cavity surface emitting laser—VECSELs), to be used for nonlinear microscopy. The SDL is modelocked using a quantum-dot semiconductor saturable absorber mirror (SESAM), delivering an average output power of 287 mW, with 1.5 ps pulses at 500 MHz and a central wavelength of 965 nm. Specifically, despite the fact of having long pulses and high repetition rates, we demonstrate the potential of this laser for Two-Photon Excited Fluorescence (TPEF) imaging of in vivo Caenorhabditis elegans (C. elegans) expressing Green Fluorescent Protein (GFP) in a set of neuronal processes and cell bodies. Efficient TPEF imaging is achieved due to the fact that this wavelength matches the peak of the two-photon action cross section of this widely used fluorescent marker. The SDL extended versatility is shown by presenting Second Harmonic Generation images of pharynx, uterus, body wall muscles and its potential to be used to excite other different commercial dyes. Importantly this non-expensive, turn-key, compact laser system could be used as a platform to develop portable nonlinear bio-imaging devices. PMID:21483599

Separation of irradiance and reflectance from observed color images by logarithmical nonlinear diffusion process

NASA Astrophysics Data System (ADS)

Saito, Takahiro; Takahashi, Hiromi; Komatsu, Takashi

2006-02-01

The Retinex theory was first proposed by Land, and deals with separation of irradiance from reflectance in an observed image. The separation problem is an ill-posed problem. Land and others proposed various Retinex separation algorithms. Recently, Kimmel and others proposed a variational framework that unifies the previous Retinex algorithms such as the Poisson-equation-type Retinex algorithms developed by Horn and others, and presented a Retinex separation algorithm with the time-evolution of a linear diffusion process. However, the Kimmel's separation algorithm cannot achieve physically rational separation, if true irradiance varies among color channels. To cope with this problem, we introduce a nonlinear diffusion process into the time-evolution. Moreover, as to its extension to color images, we present two approaches to treat color channels: the independent approach to treat each color channel separately and the collective approach to treat all color channels collectively. The latter approach outperforms the former. Furthermore, we apply our separation algorithm to a high quality chroma key in which before combining a foreground frame and a background frame into an output image a color of each pixel in the foreground frame are spatially adaptively corrected through transformation of the separated irradiance. Experiments demonstrate superiority of our separation algorithm over the Kimmel's separation algorithm.

Time domain simulation of nonlinear acoustic beams generated by rectangular pistons with application to harmonic imaging

NASA Astrophysics Data System (ADS)

Yang, Xinmai; Cleveland, Robin O.

2005-01-01

A time-domain numerical code (the so-called Texas code) that solves the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation has been extended from an axis-symmetric coordinate system to a three-dimensional (3D) Cartesian coordinate system. The code accounts for diffraction (in the parabolic approximation), nonlinearity and absorption and dispersion associated with thermoviscous and relaxation processes. The 3D time domain code was shown to be in agreement with benchmark solutions for circular and rectangular sources, focused and unfocused beams, and linear and nonlinear propagation. The 3D code was used to model the nonlinear propagation of diagnostic ultrasound pulses through tissue. The prediction of the second-harmonic field was sensitive to the choice of frequency-dependent absorption: a frequency squared f2 dependence produced a second-harmonic field which peaked closer to the transducer and had a lower amplitude than that computed for an f1.1 dependence. In comparing spatial maps of the harmonics we found that the second harmonic had dramatically reduced amplitude in the near field and also lower amplitude side lobes in the focal region than the fundamental. These findings were consistent for both uniform and apodized sources and could be contributing factors in the improved imaging reported with clinical scanners using tissue harmonic imaging. .

Time domain simulation of nonlinear acoustic beams generated by rectangular pistons with application to harmonic imaging.

PubMed

Yang, Xinmai; Cleveland, Robin O

2005-01-01

A time-domain numerical code (the so-called Texas code) that solves the Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation has been extended from an axis-symmetric coordinate system to a three-dimensional (3D) Cartesian coordinate system. The code accounts for diffraction (in the parabolic approximation), nonlinearity and absorption and dispersion associated with thermoviscous and relaxation processes. The 3D time domain code was shown to be in agreement with benchmark solutions for circular and rectangular sources, focused and unfocused beams, and linear and nonlinear propagation. The 3D code was used to model the nonlinear propagation of diagnostic ultrasound pulses through tissue. The prediction of the second-harmonic field was sensitive to the choice of frequency-dependent absorption: a frequency squared f2 dependence produced a second-harmonic field which peaked closer to the transducer and had a lower amplitude than that computed for an f1.1 dependence. In comparing spatial maps of the harmonics we found that the second harmonic had dramatically reduced amplitude in the near field and also lower amplitude side lobes in the focal region than the fundamental. These findings were consistent for both uniform and apodized sources and could be contributing factors in the improved imaging reported with clinical scanners using tissue harmonic imaging.

A robust approach to measuring the detective quantum efficiency of radiographic detectors in a clinical setting

NASA Astrophysics Data System (ADS)

McDonald, Michael C.; Kim, H. K.; Henry, J. R.; Cunningham, I. A.

2012-03-01

The detective quantum efficiency (DQE) is widely accepted as a primary measure of x-ray detector performance in the scientific community. A standard method for measuring the DQE, based on IEC 62220-1, requires the system to have a linear response meaning that the detector output signals are proportional to the incident x-ray exposure. However, many systems have a non-linear response due to characteristics of the detector, or post processing of the detector signals, that cannot be disabled and may involve unknown algorithms considered proprietary by the manufacturer. For these reasons, the DQE has not been considered as a practical candidate for routine quality assurance testing in a clinical setting. In this article we described a method that can be used to measure the DQE of both linear and non-linear systems that employ only linear image processing algorithms. The method was validated on a Cesium Iodide based flat panel system that simultaneously stores a raw (linear) and processed (non-linear) image for each exposure. It was found that the resulting DQE was equivalent to a conventional standards-compliant DQE with measurement precision, and the gray-scale inversion and linear edge enhancement did not affect the DQE result. While not IEC 62220-1 compliant, it may be adequate for QA programs.

Nonlinear optical polymers for electro-optic signal processing

NASA Technical Reports Server (NTRS)

Lindsay, Geoffrey A.

1991-01-01

Photonics is an emerging technology, slated for rapid growth in communications systems, sensors, imagers, and computers. Its growth is driven by the need for speed, reliability, and low cost. New nonlinear polymeric materials will be a key technology in the new wave of photonics devices. Electron-conjubated polymeric materials offer large electro-optic figures of merit, ease of processing into films and fibers, ruggedness, low cost, and a plethora of design options. Several new broad classes of second-order nonlinear optical polymers were developed at the Navy's Michelson Laboratory at China Lake, California. Polar alignment in thin film waveguides was achieved by electric-field poling and Langmuir-Blodgett processing. Our polymers have high softening temperatures and good aging properties. While most of the films can be photobleached with ultraviolet (UV) light, some have excellent stability in the 500-1600 nm range, and UV stability in the 290-310 nm range. The optical nonlinear response of these polymers is subpicosecond. Electro-optic switches, frequency doublers, light modulators, and optical data storage media are some of the device applications anticipated for these polymers.

Image gathering and digital restoration for fidelity and visual quality

NASA Technical Reports Server (NTRS)

Huck, Friedrich O.; Alter-Gartenberg, Rachel; Rahman, Zia-Ur

1991-01-01

The fidelity and resolution of the traditional Wiener restorations given in the prevalent digital processing literature can be significantly improved when the transformations between the continuous and discrete representations in image gathering and display are accounted for. However, the visual quality of these improved restorations also is more sensitive to the defects caused by aliasing artifacts, colored noise, and ringing near sharp edges. In this paper, these visual defects are characterized, and methods for suppressing them are presented. It is demonstrated how the visual quality of fidelity-maximized images can be improved when (1) the image-gathering system is specifically designed to enhance the performance of the image-restoration algorithm, and (2) the Wiener filter is combined with interactive Gaussian smoothing, synthetic high edge enhancement, and nonlinear tone-scale transformation. The nonlinear transformation is used primarily to enhance the spatial details that are often obscurred when the normally wide dynamic range of natural radiance fields is compressed into the relatively narrow dynamic range of film and other displays.

Monitoring the effect of low-level laser therapy in healing process of skin with second harmonic generation imaging techniques

NASA Astrophysics Data System (ADS)

Zhang, Xiaoman; Yu, Biying; Weng, Cuncheng; Li, Hui

2014-11-01

The 632nm wavelength low intensity He-Ne laser was used to irradiated on 15 mice which had skin wound. The dynamic changes and wound healing processes were observed with nonlinear spectral imaging technology. We observed that:(1)The wound healing process was accelerated by the low-level laser therapy(LLLT);(2)The new tissues produced second harmonic generation (SHG) signals. Collagen content and microstructure differed dramatically at different time pointed along the wound healing. Our observation shows that the low intensity He-Ne laser irradiation can accelerate the healing process of skin wound in mice, and SHG imaging technique can be used to observe wound healing process, which is useful for quantitative characterization of wound status during wound healing process.

Acoustical holographic recording with coherent optical read-out and image processing

NASA Astrophysics Data System (ADS)

Liu, H. K.

1980-10-01

New acoustic holographic wave memory devices have been designed for real-time in-situ recording applications. The basic operating principles of these devices and experimental results through the use of some of the prototypes of the devices are presented. Recording media used in the device include thermoplastic resin, Crisco vegetable oil, and Wilson corn oil. In addition, nonlinear coherent optical image processing techniques including equidensitometry, A-D conversion, and pseudo-color, all based on the new contact screen technique, are discussed with regard to the enhancement of the normally poor-resolved acoustical holographic images.

Measuring upconversion nanoparticles photoluminescence lifetime with FastFLIM and phasor plots

NASA Astrophysics Data System (ADS)

Sun, Yuansheng; Lee, Hsien-Ming; Qiu, Hailin; Liao, Shih-Chu Jeff; Coskun, Ulas; Barbieri, Beniamino

2018-02-01

Photon upconversion is a nonlinear process in which the sequential of absorption of two or more photons leads to the anti-stoke emission. Different than the conventional multiphoton excitation process, upconversion can be efficiently performed at low excitation densities. Recent developments in lanthanide-doped upconversion nanoparticles (UCNPs) have led to a diversity of applications, including detecting and sensing of biomolecules, imaging of live cells, tissues and animals, cancer diagnostic and therapy, etc. Measuring the upconversion lifetime provides a new dimension of its imaging and opens a new window for its applications. Due to the long metastable intermediate excited state, UCNP typically has a long excited state lifetime ranging from sub-microseconds to milliseconds. Here, we present a novel development using the FastFLIM technique to measure UCNP lifetime by laser scanning confocal microscopy. FastFLIM is capable of measuring lifetime from 100 ps to 100 ms and features the high data collection efficiency (up to 140-million counts per second). Other than the traditional nonlinear least-square fitting analysis, the raw data acquired by FastFLIM can be directly processed by the model-free phasor plots approach for instant and unbiased lifetime results, providing the ideal routine for the UCNP photoluminescence lifetime microscopy imaging.

System and method for generating 3D images of non-linear properties of rock formation using surface seismic or surface to borehole seismic or both

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vu, Cung Khac; Nihei, Kurt Toshimi; Johnson, Paul A.

A system and method of characterizing properties of a medium from a non-linear interaction are include generating, by first and second acoustic sources disposed on a surface of the medium on a first line, first and second acoustic waves. The first and second acoustic sources are controllable such that trajectories of the first and second acoustic waves intersect in a mixing zone within the medium. The method further includes receiving, by a receiver positioned in a plane containing the first and second acoustic sources, a third acoustic wave generated by a non-linear mixing process from the first and second acousticmore » waves in the mixing zone; and creating a first two-dimensional image of non-linear properties or a first ratio of compressional velocity and shear velocity, or both, of the medium in a first plane generally perpendicular to the surface and containing the first line, based on the received third acoustic wave.« less

A novel Kalman filter based video image processing scheme for two-photon fluorescence microscopy

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Li, Chunqiang; Xiao, Chuan; Qian, Wei

2016-03-01

Two-photon fluorescence microscopy (TPFM) is a perfect optical imaging equipment to monitor the interaction between fast moving viruses and hosts. However, due to strong unavoidable background noises from the culture, videos obtained by this technique are too noisy to elaborate this fast infection process without video image processing. In this study, we developed a novel scheme to eliminate background noises, recover background bacteria images and improve video qualities. In our scheme, we modified and implemented the following methods for both host and virus videos: correlation method, round identification method, tree-structured nonlinear filters, Kalman filters, and cell tracking method. After these procedures, most of noises were eliminated and host images were recovered with their moving directions and speed highlighted in the videos. From the analysis of the processed videos, 93% bacteria and 98% viruses were correctly detected in each frame on average.

Ultrathin Nonlinear Metasurface for Optical Image Encoding.

PubMed

Walter, Felicitas; Li, Guixin; Meier, Cedrik; Zhang, Shuang; Zentgraf, Thomas

2017-05-10

Security of optical information is of great importance in modern society. Many cryptography techniques based on classical and quantum optics have been widely explored in the linear optical regime. Nonlinear optical encryption in which encoding and decoding involve nonlinear frequency conversions represents a new strategy for securing optical information. Here, we demonstrate that an ultrathin nonlinear photonic metasurface, consisting of meta-atoms with 3-fold rotational symmetry, can be used to hide optical images under illumination with a fundamental wave. However, the hidden image can be read out from second harmonic generation (SHG) waves. This is achieved by controlling the destructive and constructive interferences of SHG waves from two neighboring meta-atoms. In addition, we apply this concept to obtain gray scale SHG imaging. Nonlinear metasurfaces based on space variant optical interference open new avenues for multilevel image encryption, anticounterfeiting, and background free image reconstruction.

Possible functions of contextual modulations and receptive field nonlinearities: pop-out and texture segmentation

PubMed Central

Schmid, Anita M.; Victor, Jonathan D.

2014-01-01

When analyzing a visual image, the brain has to achieve several goals quickly. One crucial goal is to rapidly detect parts of the visual scene that might be behaviorally relevant, while another one is to segment the image into objects, to enable an internal representation of the world. Both of these processes can be driven by local variations in any of several image attributes such as luminance, color, and texture. Here, focusing on texture defined by local orientation, we propose that the two processes are mediated by separate mechanisms that function in parallel. More specifically, differences in orientation can cause an object to “pop out” and attract visual attention, if its orientation differs from that of the surrounding objects. Differences in orientation can also signal a boundary between objects and therefore provide useful information for image segmentation. We propose that contextual response modulations in primary visual cortex (V1) are responsible for orientation pop-out, while a different kind of receptive field nonlinearity in secondary visual cortex (V2) is responsible for orientation-based texture segmentation. We review a recent experiment that led us to put forward this hypothesis along with other research literature relevant to this notion. PMID:25064441

Nonlinear ultrasonic imaging with X wave

NASA Astrophysics Data System (ADS)

Du, Hongwei; Lu, Wei; Feng, Huanqing

2009-10-01

X wave has a large depth of field and may have important application in ultrasonic imaging to provide high frame rate (HFR). However, the HFR system suffers from lower spatial resolution. In this paper, a study of nonlinear imaging with X wave is presented to improve the resolution. A theoretical description of realizable nonlinear X wave is reported. The nonlinear field is simulated by solving the KZK nonlinear wave equation with a time-domain difference method. The results show that the second harmonic field of X wave has narrower mainlobe and lower sidelobes than the fundamental field. In order to evaluate the imaging effect with X wave, an imaging model involving numerical calculation of the KZK equation, Rayleigh-Sommerfeld integral, band-pass filtering and envelope detection is constructed to obtain 2D fundamental and second harmonic images of scatters in tissue-like medium. The results indicate that if X wave is used, the harmonic image has higher spatial resolution throughout the entire imaging region than the fundamental image, but higher sidelobes occur as compared to conventional focus imaging. A HFR imaging method with higher spatial resolution is thus feasible provided an apodization method is used to suppress sidelobes.

Improved decryption quality and security of a joint transform correlator-based encryption system

NASA Astrophysics Data System (ADS)

Vilardy, Juan M.; Millán, María S.; Pérez-Cabré, Elisabet

2013-02-01

Some image encryption systems based on modified double random phase encoding and joint transform correlator architecture produce low quality decrypted images and are vulnerable to a variety of attacks. In this work, we analyse the algorithm of some reported methods that optically implement the double random phase encryption in a joint transform correlator. We show that it is possible to significantly improve the quality of the decrypted image by introducing a simple nonlinear operation in the encrypted function that contains the joint power spectrum. This nonlinearity also makes the system more resistant to chosen-plaintext attacks. We additionally explore the system resistance against this type of attack when a variety of probability density functions are used to generate the two random phase masks of the encryption-decryption process. Numerical results are presented and discussed.

Development of a piecewise linear omnidirectional 3D image registration method

NASA Astrophysics Data System (ADS)

Bae, Hyunsoo; Kang, Wonjin; Lee, SukGyu; Kim, Youngwoo

2016-12-01

This paper proposes a new piecewise linear omnidirectional image registration method. The proposed method segments an image captured by multiple cameras into 2D segments defined by feature points of the image and then stitches each segment geometrically by considering the inclination of the segment in the 3D space. Depending on the intended use of image registration, the proposed method can be used to improve image registration accuracy or reduce the computation time in image registration because the trade-off between the computation time and image registration accuracy can be controlled for. In general, nonlinear image registration methods have been used in 3D omnidirectional image registration processes to reduce image distortion by camera lenses. The proposed method depends on a linear transformation process for omnidirectional image registration, and therefore it can enhance the effectiveness of the geometry recognition process, increase image registration accuracy by increasing the number of cameras or feature points of each image, increase the image registration speed by reducing the number of cameras or feature points of each image, and provide simultaneous information on shapes and colors of captured objects.

Cellular Neural Network for Real Time Image Processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vagliasindi, G.; Arena, P.; Fortuna, L.

2008-03-12

Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information formore » plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)« less

Nonlinear optical and multiphoton processes for in situ manipulation and conversion of photons: applications to energy and healthcare (Conference Presentation)

NASA Astrophysics Data System (ADS)

Prasad, Paras N.

2017-02-01

Chiral control of nonlinear optical functions holds a great promise for a wide range of applications including optical signal processing, bio-sensing and chiral bio-imaging. In chiral polyfluorene thin films, we demonstrated extremely large chiral nonlinearity. The physics of manipulating excitation dynamics for photon transformation will be discussed, along with nanochemistry control of upconversion in hierarchically built organic chromophore coupled-core-multiple shell nanostructures which enable introduce new, organic-inorganic energy transfer routes for broadband light harvesting and increased upconversion efficiency via multistep cascaded energy transfer. We are pursuing the applications of photon conversion technology in IR harvesting for photovoltaics, high contrast bioimaging, photoacoustic imaging, photodynamic therapy, and optogenetics. An important application is in Brain research and Neurophotonics for functional mapping and modulation of brain activities. Another new direction pursued is magnetic field control of light in in a chiral polymer nanocomposite to achieve large magneto-optic coefficient which can enable sensing of extremely weak magnetic field due to brain waves. Finally, we will consider the thought provoking concept of utilizing photons to quantify, through magneto-optics, and augment - through nanoptogenetics, the cognitive states, thus paving the path way to a quantified human paradigm.

Ultrasound coefficient of nonlinearity imaging.

PubMed

van Sloun, Ruud; Demi, Libertario; Shan, Caifeng; Mischi, Massimo

2015-07-01

Imaging the acoustical coefficient of nonlinearity, β, is of interest in several healthcare interventional applications. It is an important feature that can be used for discriminating tissues. In this paper, we propose a nonlinearity characterization method with the goal of locally estimating the coefficient of nonlinearity. The proposed method is based on a 1-D solution of the nonlinear lossy Westerfelt equation, thereby deriving a local relation between β and the pressure wave field. Based on several assumptions, a β imaging method is then presented that is based on the ratio between the harmonic and fundamental fields, thereby reducing the effect of spatial amplitude variations of the speckle pattern. By testing the method on simulated ultrasound pressure fields and an in vitro B-mode ultrasound acquisition, we show that the designed algorithm is able to estimate the coefficient of nonlinearity, and that the tissue types of interest are well discriminable. The proposed imaging method provides a new approach to β estimation, not requiring a special measurement setup or transducer, that seems particularly promising for in vivo imaging.

In-TFT-Array-Process Micro Defect Inspection Using Nonlinear Principal Component Analysis

PubMed Central

Liu, Yi-Hung; Wang, Chi-Kai; Ting, Yung; Lin, Wei-Zhi; Kang, Zhi-Hao; Chen, Ching-Shun; Hwang, Jih-Shang

2009-01-01

Defect inspection plays a critical role in thin film transistor liquid crystal display (TFT-LCD) manufacture, and has received much attention in the field of automatic optical inspection (AOI). Previously, most focus was put on the problems of macro-scale Mura-defect detection in cell process, but it has recently been found that the defects which substantially influence the yield rate of LCD panels are actually those in the TFT array process, which is the first process in TFT-LCD manufacturing. Defect inspection in TFT array process is therefore considered a difficult task. This paper presents a novel inspection scheme based on kernel principal component analysis (KPCA) algorithm, which is a nonlinear version of the well-known PCA algorithm. The inspection scheme can not only detect the defects from the images captured from the surface of LCD panels, but also recognize the types of the detected defects automatically. Results, based on real images provided by a LCD manufacturer in Taiwan, indicate that the KPCA-based defect inspection scheme is able to achieve a defect detection rate of over 99% and a high defect classification rate of over 96% when the imbalanced support vector machine (ISVM) with 2-norm soft margin is employed as the classifier. More importantly, the inspection time is less than 1 s per input image. PMID:20057957

On detection of median filtering in digital images

NASA Astrophysics Data System (ADS)

Kirchner, Matthias; Fridrich, Jessica

2010-01-01

In digital image forensics, it is generally accepted that intentional manipulations of the image content are most critical and hence numerous forensic methods focus on the detection of such 'malicious' post-processing. However, it is also beneficial to know as much as possible about the general processing history of an image, including content-preserving operations, since they can affect the reliability of forensic methods in various ways. In this paper, we present a simple yet effective technique to detect median filtering in digital images-a widely used denoising and smoothing operator. As a great variety of forensic methods relies on some kind of a linearity assumption, a detection of non-linear median filtering is of particular interest. The effectiveness of our method is backed with experimental evidence on a large image database.

Image processing with cellular nonlinear networks implemented on field-programmable gate arrays for real-time applications in nuclear fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palazzo, S.; Vagliasindi, G.; Arena, P.

2010-08-15

In the past years cameras have become increasingly common tools in scientific applications. They are now quite systematically used in magnetic confinement fusion, to the point that infrared imaging is starting to be used systematically for real-time machine protection in major devices. However, in order to guarantee that the control system can always react rapidly in case of critical situations, the time required for the processing of the images must be as predictable as possible. The approach described in this paper combines the new computational paradigm of cellular nonlinear networks (CNNs) with field-programmable gate arrays and has been tested inmore » an application for the detection of hot spots on the plasma facing components in JET. The developed system is able to perform real-time hot spot recognition, by processing the image stream captured by JET wide angle infrared camera, with the guarantee that computational time is constant and deterministic. The statistical results obtained from a quite extensive set of examples show that this solution approximates very well an ad hoc serial software algorithm, with no false or missed alarms and an almost perfect overlapping of alarm intervals. The computational time can be reduced to a millisecond time scale for 8 bit 496x560-sized images. Moreover, in our implementation, the computational time, besides being deterministic, is practically independent of the number of iterations performed by the CNN - unlike software CNN implementations.« less

Nonlinear Polarimetric Microscopy for Biomedical Imaging

NASA Astrophysics Data System (ADS)

Samim, Masood

A framework for the nonlinear optical polarimetry and polarimetric microscopy is developed. Mathematical equations are derived in terms of linear and nonlinear Stokes Mueller formalism, which comprehensively characterize the polarization properties of the incoming and outgoing radiations, and provide structural information about the organization of the investigated materials. The algebraic formalism developed in this thesis simplifies many predictions for a nonlinear polarimetry study and provides an intuitive understanding of various polarization properties for radiations and the intervening medium. For polarimetric microscopy experiments, a custom fast-scanning differential polarization microscope is developed, which is also capable of real-time three-dimensional imaging. The setup is equipped with a pair of high-speed resonant and galvanometric scanning mirrors, and supplemented by advanced adaptive optics and data acquisition modules. The scanning mirrors when combined with the adaptive optics deformable mirror enable fast 3D imaging. Deformable membrane mirrors and genetic algorithm optimization routines are employed to improve the imaging conditions including correcting the optical aberrations, maximizing signal intensities, and minimizing point-spread-functions of the focal volume. A field-programmable-gate array (FPGA) chip is exploited to rapidly acquire and process the multidimensional data. Using the nonlinear optical polarimetry framework and the home-built polarization microscope, a few biologically important tissues are measured and analyzed to gain insight as to their structure and dynamics. The structure and distribution of muscle sarcomere myosins, connective tissue collagen, carbohydrate-rich starch, and fruit fly eye retinal molecules are characterized with revealing polarization studies. In each case, using the theoretical framework, polarization sensitive data are analyzed to decipher the molecular orientations and nonlinear optical susceptibilities. The developed nonlinear optical polarimetric microscopy is applicable to a wide variety of structural studies on ordered materials, and provides a non-invasive possibility to study the structural organization and dynamics within biological samples. For example, the technique is well suited for studies of a muscle contraction, histopathology of collagen structure for cancer tissue diagnostics, investigations of the polysacharide structural organization within a starch granule of a plant, or developmental study of the retina in an eye, among other applications.

Optical information-processing systems and architectures II; Proceedings of the Meeting, San Diego, CA, July 9-13, 1990

NASA Astrophysics Data System (ADS)

Javidi, Bahram

The present conference discusses topics in the fields of neural networks, acoustooptic signal processing, pattern recognition, phase-only processing, nonlinear signal processing, image processing, optical computing, and optical information processing. Attention is given to the optical implementation of an inner-product neural associative memory, optoelectronic associative recall via motionless-head/parallel-readout optical disk, a compact real-time acoustooptic image correlator, a multidimensional synthetic estimation filter, and a light-efficient joint transform optical correlator. Also discussed are a high-resolution spatial light modulator, compact real-time interferometric Fourier-transform processors, a fast decorrelation algorithm for permutation arrays, the optical interconnection of optical modules, and carry-free optical binary adders.

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration.

PubMed

Chen, Yunjin; Pock, Thomas

2017-06-01

Image restoration is a long-standing problem in low-level computer vision with many interesting applications. We describe a flexible learning framework based on the concept of nonlinear reaction diffusion models for various image restoration problems. By embodying recent improvements in nonlinear diffusion models, we propose a dynamic nonlinear reaction diffusion model with time-dependent parameters (i.e., linear filters and influence functions). In contrast to previous nonlinear diffusion models, all the parameters, including the filters and the influence functions, are simultaneously learned from training data through a loss based approach. We call this approach TNRD-Trainable Nonlinear Reaction Diffusion. The TNRD approach is applicable for a variety of image restoration tasks by incorporating appropriate reaction force. We demonstrate its capabilities with three representative applications, Gaussian image denoising, single image super resolution and JPEG deblocking. Experiments show that our trained nonlinear diffusion models largely benefit from the training of the parameters and finally lead to the best reported performance on common test datasets for the tested applications. Our trained models preserve the structural simplicity of diffusion models and take only a small number of diffusion steps, thus are highly efficient. Moreover, they are also well-suited for parallel computation on GPUs, which makes the inference procedure extremely fast.

Statistical regularities of art images and natural scenes: spectra, sparseness and nonlinearities.

PubMed

Graham, Daniel J; Field, David J

2007-01-01

Paintings are the product of a process that begins with ordinary vision in the natural world and ends with manipulation of pigments on canvas. Because artists must produce images that can be seen by a visual system that is thought to take advantage of statistical regularities in natural scenes, artists are likely to replicate many of these regularities in their painted art. We have tested this notion by computing basic statistical properties and modeled cell response properties for a large set of digitized paintings and natural scenes. We find that both representational and non-representational (abstract) paintings from our sample (124 images) show basic similarities to a sample of natural scenes in terms of their spatial frequency amplitude spectra, but the paintings and natural scenes show significantly different mean amplitude spectrum slopes. We also find that the intensity distributions of paintings show a lower skewness and sparseness than natural scenes. We account for this by considering the range of luminances found in the environment compared to the range available in the medium of paint. A painting's range is limited by the reflective properties of its materials. We argue that artists do not simply scale the intensity range down but use a compressive nonlinearity. In our studies, modeled retinal and cortical filter responses to the images were less sparse for the paintings than for the natural scenes. But when a compressive nonlinearity was applied to the images, both the paintings' sparseness and the modeled responses to the paintings showed the same or greater sparseness compared to the natural scenes. This suggests that artists achieve some degree of nonlinear compression in their paintings. Because paintings have captivated humans for millennia, finding basic statistical regularities in paintings' spatial structure could grant insights into the range of spatial patterns that humans find compelling.

Anisotropic Diffusion Despeckling for High Resolution SAR Images

DTIC Science & Technology

2004-11-01

Chiang Mai , Thailand 323 Data Processing B-4.2 Anisotropic Diffusion Despeckling for High...18 324 25th ACRS 2004 Chiang Mai , Thailand B-4.2 Data Processing 2 NONLINEAR DIFFUSION FILTERING 2.1...edge-enhancing diffusion model is adopted. |)(|1 σϕ ug ∇= 2.02 =ϕ (4) 25th ACRS 2004 Chiang Mai , Thailand 325 Data

Semisupervised kernel marginal Fisher analysis for face recognition.

PubMed

Wang, Ziqiang; Sun, Xia; Sun, Lijun; Huang, Yuchun

2013-01-01

Dimensionality reduction is a key problem in face recognition due to the high-dimensionality of face image. To effectively cope with this problem, a novel dimensionality reduction algorithm called semisupervised kernel marginal Fisher analysis (SKMFA) for face recognition is proposed in this paper. SKMFA can make use of both labelled and unlabeled samples to learn the projection matrix for nonlinear dimensionality reduction. Meanwhile, it can successfully avoid the singularity problem by not calculating the matrix inverse. In addition, in order to make the nonlinear structure captured by the data-dependent kernel consistent with the intrinsic manifold structure, a manifold adaptive nonparameter kernel is incorporated into the learning process of SKMFA. Experimental results on three face image databases demonstrate the effectiveness of our proposed algorithm.

Time domain simulation of harmonic ultrasound images and beam patterns in 3D using the k-space pseudospectral method.

PubMed

Treeby, Bradley E; Tumen, Mustafa; Cox, B T

2011-01-01

A k-space pseudospectral model is developed for the fast full-wave simulation of nonlinear ultrasound propagation through heterogeneous media. The model uses a novel equation of state to account for nonlinearity in addition to power law absorption. The spectral calculation of the spatial gradients enables a significant reduction in the number of required grid nodes compared to finite difference methods. The model is parallelized using a graphical processing unit (GPU) which allows the simulation of individual ultrasound scan lines using a 256 x 256 x 128 voxel grid in less than five minutes. Several numerical examples are given, including the simulation of harmonic ultrasound images and beam patterns using a linear phased array transducer.

Joint transform correlators with spatially incoherent illumination

NASA Astrophysics Data System (ADS)

Bykovsky, Yuri A.; Karpiouk, Andrey B.; Markilov, Anatoly A.; Rodin, Vladislav G.; Starikov, Sergey N.

1997-03-01

Two variants of joint transform correlators with monochromatic spatially incoherent illumination are considered. The Fourier-holograms of the reference and recognized images are recorded simultaneously or apart in a time on the same spatial light modulator directly by monochromatic spatially incoherent light. To create the signal of mutual correlation of the images it is necessary to execute nonlinear transformation when the hologram is illuminated by coherent light. In the first scheme of the correlator this aim was achieved by using double pas of a restoring coherent wave through the hologram. In the second variant of the correlator the non-linearity of the characteristic of the spatial light modulator for hologram recording was used. Experimental schemes and results on processing teste images by both variants of joint transform correlators with monochromatic spatially incoherent illumination. The use of spatially incoherent light on the input of joint transform correlators permits to reduce the requirements to optical quality of elements, to reduce accuracy requirements on elements positioning and to expand a number of devices suitable to input images in correlators.

Real-space post-processing correction of thermal drift and piezoelectric actuator nonlinearities in scanning tunneling microscope images.

PubMed

Yothers, Mitchell P; Browder, Aaron E; Bumm, Lloyd A

2017-01-01

We have developed a real-space method to correct distortion due to thermal drift and piezoelectric actuator nonlinearities on scanning tunneling microscope images using Matlab. The method uses the known structures typically present in high-resolution atomic and molecularly resolved images as an internal standard. Each image feature (atom or molecule) is first identified in the image. The locations of each feature's nearest neighbors are used to measure the local distortion at that location. The local distortion map across the image is simultaneously fit to our distortion model, which includes thermal drift in addition to piezoelectric actuator hysteresis and creep. The image coordinates of the features and image pixels are corrected using an inverse transform from the distortion model. We call this technique the thermal-drift, hysteresis, and creep transform. Performing the correction in real space allows defects, domain boundaries, and step edges to be excluded with a spatial mask. Additional real-space image analyses are now possible with these corrected images. Using graphite(0001) as a model system, we show lattice fitting to the corrected image, averaged unit cell images, and symmetry-averaged unit cell images. Statistical analysis of the distribution of the image features around their best-fit lattice sites measures the aggregate noise in the image, which can be expressed as feature confidence ellipsoids.

Real-space post-processing correction of thermal drift and piezoelectric actuator nonlinearities in scanning tunneling microscope images

NASA Astrophysics Data System (ADS)

Yothers, Mitchell P.; Browder, Aaron E.; Bumm, Lloyd A.

2017-01-01

We have developed a real-space method to correct distortion due to thermal drift and piezoelectric actuator nonlinearities on scanning tunneling microscope images using Matlab. The method uses the known structures typically present in high-resolution atomic and molecularly resolved images as an internal standard. Each image feature (atom or molecule) is first identified in the image. The locations of each feature's nearest neighbors are used to measure the local distortion at that location. The local distortion map across the image is simultaneously fit to our distortion model, which includes thermal drift in addition to piezoelectric actuator hysteresis and creep. The image coordinates of the features and image pixels are corrected using an inverse transform from the distortion model. We call this technique the thermal-drift, hysteresis, and creep transform. Performing the correction in real space allows defects, domain boundaries, and step edges to be excluded with a spatial mask. Additional real-space image analyses are now possible with these corrected images. Using graphite(0001) as a model system, we show lattice fitting to the corrected image, averaged unit cell images, and symmetry-averaged unit cell images. Statistical analysis of the distribution of the image features around their best-fit lattice sites measures the aggregate noise in the image, which can be expressed as feature confidence ellipsoids.

Research on Airborne SAR Imaging Based on Esc Algorithm

NASA Astrophysics Data System (ADS)

Dong, X. T.; Yue, X. J.; Zhao, Y. H.; Han, C. M.

2017-09-01

Due to the ability of flexible, accurate, and fast obtaining abundant information, airborne SAR is significant in the field of Earth Observation and many other applications. Optimally the flight paths are straight lines, but in reality it is not the case since some portion of deviation from the ideal path is impossible to avoid. A small disturbance from the ideal line will have a major effect on the signal phase, dramatically deteriorating the quality of SAR images and data. Therefore, to get accurate echo information and radar images, it is essential to measure and compensate for nonlinear motion of antenna trajectories. By means of compensating each flying trajectory to its reference track, MOCO method corrects linear phase error and quadratic phase error caused by nonlinear antenna trajectories. Position and Orientation System (POS) data is applied to acquiring accuracy motion attitudes and spatial positions of antenna phase centre (APC). In this paper, extend chirp scaling algorithm (ECS) is used to deal with echo data of airborne SAR. An experiment is done using VV-Polarization raw data of C-band airborne SAR. The quality evaluations of compensated SAR images and uncompensated SAR images are done in the experiment. The former always performs better than the latter. After MOCO processing, azimuth ambiguity is declined, peak side lobe ratio (PSLR) effectively improves and the resolution of images is improved obviously. The result shows the validity and operability of the imaging process for airborne SAR.

A framework for optimal kernel-based manifold embedding of medical image data.

PubMed

Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma

2015-04-01

Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images. Copyright © 2014 Elsevier Ltd. All rights reserved.

Real-Time Symbol Extraction From Grey-Level Images

NASA Astrophysics Data System (ADS)

Massen, R.; Simnacher, M.; Rosch, J.; Herre, E.; Wuhrer, H. W.

1988-04-01

A VME-bus image pipeline processor for extracting vectorized contours from grey-level images in real-time is presented. This 3 Giga operation per second processor uses large kernel convolvers and new non-linear neighbourhood processing algorithms to compute true 1-pixel wide and noise-free contours without thresholding even from grey-level images with quite varying edge sharpness. The local edge orientation is used as an additional cue to compute a list of vectors describing the closed and open contours in real-time and to dump a CAD-like symbolic image description into a symbol memory at pixel clock rate.

Comparison and analysis of nonlinear algorithms for compressed sensing in MRI.

PubMed

Yu, Yeyang; Hong, Mingjian; Liu, Feng; Wang, Hua; Crozier, Stuart

2010-01-01

Compressed sensing (CS) theory has been recently applied in Magnetic Resonance Imaging (MRI) to accelerate the overall imaging process. In the CS implementation, various algorithms have been used to solve the nonlinear equation system for better image quality and reconstruction speed. However, there are no explicit criteria for an optimal CS algorithm selection in the practical MRI application. A systematic and comparative study of those commonly used algorithms is therefore essential for the implementation of CS in MRI. In this work, three typical algorithms, namely, the Gradient Projection For Sparse Reconstruction (GPSR) algorithm, Interior-point algorithm (l(1)_ls), and the Stagewise Orthogonal Matching Pursuit (StOMP) algorithm are compared and investigated in three different imaging scenarios, brain, angiogram and phantom imaging. The algorithms' performances are characterized in terms of image quality and reconstruction speed. The theoretical results show that the performance of the CS algorithms is case sensitive; overall, the StOMP algorithm offers the best solution in imaging quality, while the GPSR algorithm is the most efficient one among the three methods. In the next step, the algorithm performances and characteristics will be experimentally explored. It is hoped that this research will further support the applications of CS in MRI.

Automated seeding-based nuclei segmentation in nonlinear optical microscopy.

PubMed

Medyukhina, Anna; Meyer, Tobias; Heuke, Sandro; Vogler, Nadine; Dietzek, Benjamin; Popp, Jürgen

2013-10-01

Nonlinear optical (NLO) microscopy based, e.g., on coherent anti-Stokes Raman scattering (CARS) or two-photon-excited fluorescence (TPEF) is a fast label-free imaging technique, with a great potential for biomedical applications. However, NLO microscopy as a diagnostic tool is still in its infancy; there is a lack of robust and durable nuclei segmentation methods capable of accurate image processing in cases of variable image contrast, nuclear density, and type of investigated tissue. Nonetheless, such algorithms specifically adapted to NLO microscopy present one prerequisite for the technology to be routinely used, e.g., in pathology or intraoperatively for surgical guidance. In this paper, we compare the applicability of different seeding and boundary detection methods to NLO microscopic images in order to develop an optimal seeding-based approach capable of accurate segmentation of both TPEF and CARS images. Among different methods, the Laplacian of Gaussian filter showed the best accuracy for the seeding of the image, while a modified seeded watershed segmentation was the most accurate in the task of boundary detection. The resulting combination of these methods followed by the verification of the detected nuclei performs high average sensitivity and specificity when applied to various types of NLO microscopy images.

Reduction of noise and image artifacts in computed tomography by nonlinear filtration of projection images

NASA Astrophysics Data System (ADS)

Demirkaya, Omer

2001-07-01

This study investigates the efficacy of filtering two-dimensional (2D) projection images of Computer Tomography (CT) by the nonlinear diffusion filtration in removing the statistical noise prior to reconstruction. The projection images of Shepp-Logan head phantom were degraded by Gaussian noise. The variance of the Gaussian distribution was adaptively changed depending on the intensity at a given pixel in the projection image. The corrupted projection images were then filtered using the nonlinear anisotropic diffusion filter. The filtered projections as well as original noisy projections were reconstructed using filtered backprojection (FBP) with Ram-Lak filter and/or Hanning window. The ensemble variance was computed for each pixel on a slice. The nonlinear filtering of projection images improved the SNR substantially, on the order of fourfold, in these synthetic images. The comparison of intensity profiles across a cross-sectional slice indicated that the filtering did not result in any significant loss of image resolution.

Nonlinear pulse compression in pulse-inversion fundamental imaging.

PubMed

Cheng, Yun-Chien; Shen, Che-Chou; Li, Pai-Chi

2007-04-01

Coded excitation can be applied in ultrasound contrast agent imaging to enhance the signal-to-noise ratio with minimal destruction of the microbubbles. Although the axial resolution is usually compromised by the requirement for a long coded transmit waveforms, this can be restored by using a compression filter to compress the received echo. However, nonlinear responses from microbubbles may cause difficulties in pulse compression and result in severe range side-lobe artifacts, particularly in pulse-inversion-based (PI) fundamental imaging. The efficacy of pulse compression in nonlinear contrast imaging was evaluated by investigating several factors relevant to PI fundamental generation using both in-vitro experiments and simulations. The results indicate that the acoustic pressure and the bubble size can alter the nonlinear characteristics of microbubbles and change the performance of the compression filter. When nonlinear responses from contrast agents are enhanced by using a higher acoustic pressure or when more microbubbles are near the resonance size of the transmit frequency, higher range side lobes are produced in both linear imaging and PI fundamental imaging. On the other hand, contrast detection in PI fundamental imaging significantly depends on the magnitude of the nonlinear responses of the bubbles and thus the resultant contrast-to-tissue ratio (CTR) still increases with acoustic pressure and the nonlinear resonance of microbubbles. It should be noted, however, that the CTR in PI fundamental imaging after compression is consistently lower than that before compression due to obvious side-lobe artifacts. Therefore, the use of coded excitation is not beneficial in PI fundamental contrast detection.

GPU-based acceleration of computations in nonlinear finite element deformation analysis.

PubMed

Mafi, Ramin; Sirouspour, Shahin

2014-03-01

The physics of deformation for biological soft-tissue is best described by nonlinear continuum mechanics-based models, which then can be discretized by the FEM for a numerical solution. However, computational complexity of such models have limited their use in applications requiring real-time or fast response. In this work, we propose a graphic processing unit-based implementation of the FEM using implicit time integration for dynamic nonlinear deformation analysis. This is the most general formulation of the deformation analysis. It is valid for large deformations and strains and can account for material nonlinearities. The data-parallel nature and the intense arithmetic computations of nonlinear FEM equations make it particularly suitable for implementation on a parallel computing platform such as graphic processing unit. In this work, we present and compare two different designs based on the matrix-free and conventional preconditioned conjugate gradients algorithms for solving the FEM equations arising in deformation analysis. The speedup achieved with the proposed parallel implementations of the algorithms will be instrumental in the development of advanced surgical simulators and medical image registration methods involving soft-tissue deformation. Copyright © 2013 John Wiley & Sons, Ltd.

Measurement of the quadratic hyperpolarizability of the collagen triple helix and application to second harmonic imaging of natural and biomimetic collagenous tissues

NASA Astrophysics Data System (ADS)

Deniset-Besseau, A.; Strupler, M.; Duboisset, J.; De Sa Peixoto, P.; Benichou, E.; Fligny, C.; Tharaux, P.-L.; Mosser, G.; Brevet, P.-F.; Schanne-Klein, M.-C.

2009-09-01

Collagen is a major protein of the extracellular matrix that is characterized by triple helical domains. It plays a central role in the formation of fibrillar and microfibrillar networks, basement membranes, as well as other structures of the connective tissue. Remarkably, fibrillar collagen exhibits efficient Second Harmonic Generation (SHG) so that SHG microscopy proved to be a sensitive tool to probe the three-dimensional architecture of fibrillar collagen and to assess the progression of fibrotic pathologies. We obtained sensitive and reproducible measurements of the fibrosis extent, but we needed quantitative data at the molecular level to further process SHG images. We therefore performed Hyper- Rayleigh Scattering (HRS) experiments and measured a second order hyperpolarisability of 1.25 10-27 esu for rat-tail type I collagen. This value is surprisingly large considering that collagen presents no strong harmonophore in its aminoacid sequence. In order to get insight into the physical origin of this nonlinear process, we performed HRS measurements after denaturation of the collagen triple helix and for a collagen-like short model peptide [(Pro-Pro- Gly)10]3. It showed that the collagen large nonlinear response originates in the tight alignment of a large number of weakly efficient harmonophores, presumably the peptide bonds, resulting in a coherent amplification of the nonlinear signal along the triple helix. To illustrate this mechanism, we successfully recorded SHG images in collagenous biomimetic matrices.

Advances in medical image computing.

PubMed

Tolxdorff, T; Deserno, T M; Handels, H; Meinzer, H-P

2009-01-01

Medical image computing has become a key technology in high-tech applications in medicine and an ubiquitous part of modern imaging systems and the related processes of clinical diagnosis and intervention. Over the past years significant progress has been made in the field, both on methodological and on application level. Despite this progress there are still big challenges to meet in order to establish image processing routinely in health care. In this issue, selected contributions of the German Conference on Medical Image Processing (BVM) are assembled to present latest advances in the field of medical image computing. The winners of scientific awards of the German Conference on Medical Image Processing (BVM) 2008 were invited to submit a manuscript on their latest developments and results for possible publication in Methods of Information in Medicine. Finally, seven excellent papers were selected to describe important aspects of recent advances in the field of medical image processing. The selected papers give an impression of the breadth and heterogeneity of new developments. New methods for improved image segmentation, non-linear image registration and modeling of organs are presented together with applications of image analysis methods in different medical disciplines. Furthermore, state-of-the-art tools and techniques to support the development and evaluation of medical image processing systems in practice are described. The selected articles describe different aspects of the intense development in medical image computing. The image processing methods presented enable new insights into the patient's image data and have the future potential to improve medical diagnostics and patient treatment.

Nonlinear plasmonic imaging techniques and their biological applications

NASA Astrophysics Data System (ADS)

Deka, Gitanjal; Sun, Chi-Kuang; Fujita, Katsumasa; Chu, Shi-Wei

2017-01-01

Nonlinear optics, when combined with microscopy, is known to provide advantages including novel contrast, deep tissue observation, and minimal invasiveness. In addition, special nonlinearities, such as switch on/off and saturation, can enhance the spatial resolution below the diffraction limit, revolutionizing the field of optical microscopy. These nonlinear imaging techniques are extremely useful for biological studies on various scales from molecules to cells to tissues. Nevertheless, in most cases, nonlinear optical interaction requires strong illumination, typically at least gigawatts per square centimeter intensity. Such strong illumination can cause significant phototoxicity or even photodamage to fragile biological samples. Therefore, it is highly desirable to find mechanisms that allow the reduction of illumination intensity. Surface plasmon, which is the collective oscillation of electrons in metal under light excitation, is capable of significantly enhancing the local field around the metal nanostructures and thus boosting up the efficiency of nonlinear optical interactions of the surrounding materials or of the metal itself. In this mini-review, we discuss the recent progress of plasmonics in nonlinear optical microscopy with a special focus on biological applications. The advancement of nonlinear imaging modalities (including incoherent/coherent Raman scattering, two/three-photon luminescence, and second/third harmonic generations that have been amalgamated with plasmonics), as well as the novel subdiffraction limit imaging techniques based on nonlinear behaviors of plasmonic scattering, is addressed.

Evolution Nonlinear Diffusion-Convection PDE Models for Spectrogram Enhancement

NASA Astrophysics Data System (ADS)

Dugnol, B.; Fernández, C.; Galiano, G.; Velasco, J.

2008-09-01

In previous works we studied the application of PDE-based image processing techniques applied to the spectrogram of audio signals in order to improve the readability of the signal. In particular we considered the implementation of the nonlinear diffusive model proposed by Álvarez, Lions and Morel [1](ALM) combined with a convective term inspired by the differential reassignment proposed by Chassandre-Mottin, Daubechies, Auger and Flandrin [2]-[3]. In this work we consider the possibility of replacing the diffusive model of ALM by diffusive terms in divergence form. In particular we implement finite element approximations of nonlinear diffusive terms studied by Chen, Levine, Rao [4] and Antontsev, Shmarev [5]-[8] with a convective term.

Verification of nonlinear dynamic structural test results by combined image processing and acoustic analysis

NASA Astrophysics Data System (ADS)

Tene, Yair; Tene, Noam; Tene, G.

1993-08-01

An interactive data fusion methodology of video, audio, and nonlinear structural dynamic analysis for potential application in forensic engineering is presented. The methodology was developed and successfully demonstrated in the analysis of heavy transportable bridge collapse during preparation for testing. Multiple bridge elements failures were identified after the collapse, including fracture, cracks and rupture of high performance structural materials. Videotape recording by hand held camcorder was the only source of information about the collapse sequence. The interactive data fusion methodology resulted in extracting relevant information form the videotape and from dynamic nonlinear structural analysis, leading to full account of the sequence of events during the bridge collapse.

Bio-inspired nano-sensor-enhanced CNN visual computer.

PubMed

Porod, Wolfgang; Werblin, Frank; Chua, Leon O; Roska, Tamas; Rodriguez-Vazquez, Angel; Roska, Botond; Fay, Patrick; Bernstein, Gary H; Huang, Yih-Fang; Csurgay, Arpad I

2004-05-01

Nanotechnology opens new ways to utilize recent discoveries in biological image processing by translating the underlying functional concepts into the design of CNN (cellular neural/nonlinear network)-based systems incorporating nanoelectronic devices. There is a natural intersection joining studies of retinal processing, spatio-temporal nonlinear dynamics embodied in CNN, and the possibility of miniaturizing the technology through nanotechnology. This intersection serves as the springboard for our multidisciplinary project. Biological feature and motion detectors map directly into the spatio-temporal dynamics of CNN for target recognition, image stabilization, and tracking. The neural interactions underlying color processing will drive the development of nanoscale multispectral sensor arrays for image fusion. Implementing such nanoscale sensors on a CNN platform will allow the implementation of device feedback control, a hallmark of biological sensory systems. These biologically inspired CNN subroutines are incorporated into the new world of analog-and-logic algorithms and software, containing also many other active-wave computing mechanisms, including nature-inspired (physics and chemistry) as well as PDE-based sophisticated spatio-temporal algorithms. Our goal is to design and develop several miniature prototype devices for target detection, navigation, tracking, and robotics. This paper presents an example illustrating the synergies emerging from the convergence of nanotechnology, biotechnology, and information and cognitive science.

A cascade model of information processing and encoding for retinal prosthesis.

PubMed

Pei, Zhi-Jun; Gao, Guan-Xin; Hao, Bo; Qiao, Qing-Li; Ai, Hui-Jian

2016-04-01

Retinal prosthesis offers a potential treatment for individuals suffering from photoreceptor degeneration diseases. Establishing biological retinal models and simulating how the biological retina convert incoming light signal into spike trains that can be properly decoded by the brain is a key issue. Some retinal models have been presented, ranking from structural models inspired by the layered architecture to functional models originated from a set of specific physiological phenomena. However, Most of these focus on stimulus image compression, edge detection and reconstruction, but do not generate spike trains corresponding to visual image. In this study, based on state-of-the-art retinal physiological mechanism, including effective visual information extraction, static nonlinear rectification of biological systems and neurons Poisson coding, a cascade model of the retina including the out plexiform layer for information processing and the inner plexiform layer for information encoding was brought forward, which integrates both anatomic connections and functional computations of retina. Using MATLAB software, spike trains corresponding to stimulus image were numerically computed by four steps: linear spatiotemporal filtering, static nonlinear rectification, radial sampling and then Poisson spike generation. The simulated results suggested that such a cascade model could recreate visual information processing and encoding functionalities of the retina, which is helpful in developing artificial retina for the retinally blind.

A novel post-processing scheme for two-dimensional electrical impedance tomography based on artificial neural networks

PubMed Central

2017-01-01

Objective Electrical Impedance Tomography (EIT) is a powerful non-invasive technique for imaging applications. The goal is to estimate the electrical properties of living tissues by measuring the potential at the boundary of the domain. Being safe with respect to patient health, non-invasive, and having no known hazards, EIT is an attractive and promising technology. However, it suffers from a particular technical difficulty, which consists of solving a nonlinear inverse problem in real time. Several nonlinear approaches have been proposed as a replacement for the linear solver, but in practice very few are capable of stable, high-quality, and real-time EIT imaging because of their very low robustness to errors and inaccurate modeling, or because they require considerable computational effort. Methods In this paper, a post-processing technique based on an artificial neural network (ANN) is proposed to obtain a nonlinear solution to the inverse problem, starting from a linear solution. While common reconstruction methods based on ANNs estimate the solution directly from the measured data, the method proposed here enhances the solution obtained from a linear solver. Conclusion Applying a linear reconstruction algorithm before applying an ANN reduces the effects of noise and modeling errors. Hence, this approach significantly reduces the error associated with solving 2D inverse problems using machine-learning-based algorithms. Significance This work presents radical enhancements in the stability of nonlinear methods for biomedical EIT applications. PMID:29206856

[Prediction of Encapsulation Temperatures of Copolymer Films in Photovoltaic Cells Using Hyperspectral Imaging Techniques and Chemometrics].

PubMed

Lin, Ping; Chen, Yong-ming; Yao, Zhi-lei

2015-11-01

A novel method of combination of the chemometrics and the hyperspectral imaging techniques was presented to detect the temperatures of Ethylene-Vinyl Acetate copolymer (EVA) films in photovoltaic cells during the thermal encapsulation process. Four varieties of the EVA films which had been heated at the temperatures of 128, 132, 142 and 148 °C during the photovoltaic cells production process were used for investigation in this paper. These copolymer encapsulation films were firstly scanned by the hyperspectral imaging equipment (Spectral Imaging Ltd. Oulu, Finland). The scanning band range of hyperspectral equipemnt was set between 904.58 and 1700.01 nm. The hyperspectral dataset of copolymer films was randomly divided into two parts for the training and test purpose. Each type of the training set and test set contained 90 and 10 instances, respectively. The obtained hyperspectral images of EVA films were dealt with by using the ENVI (Exelis Visual Information Solutions, USA) software. The size of region of interest (ROI) of each obtained hyperspectral image of EVA film was set as 150 x 150 pixels. The average of reflectance hyper spectra of all the pixels in the ROI was used as the characteristic curve to represent the instance. There kinds of chemometrics methods including partial least squares regression (PLSR), multi-class support vector machine (SVM) and large margin nearest neighbor (LMNN) were used to correlate the characteristic hyper spectra with the encapsulation temperatures of of copolymer films. The plot of weighted regression coefficients illustrated that both bands of short- and long-wave near infrared hyperspectral data contributed to enhancing the prediction accuracy of the forecast model. Because the attained reflectance hyperspectral data of EVA materials displayed the strong nonlinearity, the prediction performance of linear modeling method of PLSR declined and the prediction precision only reached to 95%. The kernel-based forecast models were introduced to eliminate the impact of nonlinear hyperspectral data to some extent through mapping the original nonlinear hyperspectral data to the high dimensional linear feature space, so the relationship between the nonlinear hyperspectral data and the encapsulation temperatures of EVA films was fully disclosed finally. Compared with the prediction results of three proposed models, the prediction performance of LMNN was superior to the other two, whose final recognition accuracy achieved 100%. The results indicated that the methods of combination of LMNN model with the hyperspectral imaging techniques was the best one for accurately and rapidly determining the encapsulation temperatures of EVA films of photovoltaic cells. In addition, this paper had created the ideal conditions for automatically monitoring and effectively controlling the encapsulation temperatures of EVA films in the photovoltaic cells production process.

Novel Image Encryption based on Quantum Walks

PubMed Central

Yang, Yu-Guang; Pan, Qing-Xiang; Sun, Si-Jia; Xu, Peng

2015-01-01

Quantum computation has achieved a tremendous success during the last decades. In this paper, we investigate the potential application of a famous quantum computation model, i.e., quantum walks (QW) in image encryption. It is found that QW can serve as an excellent key generator thanks to its inherent nonlinear chaotic dynamic behavior. Furthermore, we construct a novel QW-based image encryption algorithm. Simulations and performance comparisons show that the proposal is secure enough for image encryption and outperforms prior works. It also opens the door towards introducing quantum computation into image encryption and promotes the convergence between quantum computation and image processing. PMID:25586889

Propagation of hypergeometric Gaussian beams in strongly nonlocal nonlinear media

NASA Astrophysics Data System (ADS)

Tang, Bin; Bian, Lirong; Zhou, Xin; Chen, Kai

2018-01-01

Optical vortex beams have attracted lots of interest due to its potential application in image processing, optical trapping and optical communications, etc. In this work, we theoretically and numerically investigated the propagation properties of hypergeometric Gaussian (HyGG) beams in strongly nonlocal nonlinear media. Based on the Snyder-Mitchell model, analytical expressions for propagation of the HyGG beams in strongly nonlocal nonlinear media were obtained. The influence of input power and optical parameters on the evolutions of the beam width and radius of curvature is illustrated, respectively. The results show that the beam width and radius of curvature of the HyGG beams remain invariant, like a soliton when the input power is equal to the critical power. Otherwise, it varies periodically like a breather, which is the result of competition between the beam diffraction and nonlinearity of the medium.

Quantitative Characterizations of Ultrashort Echo (UTE) Images for Supporting Air-Bone Separation in the Head

PubMed Central

Hsu, Shu-Hui; Cao, Yue; Lawrence, Theodore S.; Tsien, Christina; Feng, Mary; Grodzki, David M.; Balter, James M.

2015-01-01

Accurate separation of air and bone is critical for creating synthetic CT from MRI to support Radiation Oncology workflow. This study compares two different ultrashort echo-time sequences in the separation of air from bone, and evaluates post-processing methods that correct intensity nonuniformity of images and account for intensity gradients at tissue boundaries to improve this discriminatory power. CT and MRI scans were acquired on 12 patients under an institution review board-approved prospective protocol. The two MRI sequences tested were ultra-short TE imaging using 3D radial acquisition (UTE), and using pointwise encoding time reduction with radial acquisition (PETRA). Gradient nonlinearity correction was applied to both MR image volumes after acquisition. MRI intensity nonuniformity was corrected by vendor-provided normalization methods, and then further corrected using the N4itk algorithm. To overcome the intensity-gradient at air-tissue boundaries, spatial dilations, from 0 to 4 mm, were applied to threshold-defined air regions from MR images. Receiver operating characteristic (ROC) analyses, by comparing predicted (defined by MR images) versus “true” regions of air and bone (defined by CT images), were performed with and without residual bias field correction and local spatial expansion. The post-processing corrections increased the areas under the ROC curves (AUC) from 0.944 ± 0.012 to 0.976 ± 0.003 for UTE images, and from 0.850 ± 0.022 to 0.887 ± 0.012 for PETRA images, compared to without corrections. When expanding the threshold-defined air volumes, as expected, sensitivity of air identification decreased with an increase in specificity of bone discrimination, but in a non-linear fashion. A 1-mm air mask expansion yielded AUC increases of 1% and 4% for UTE and PETRA images, respectively. UTE images had significantly greater discriminatory power in separating air from bone than PETRA images. Post-processing strategies improved the discriminatory power of air from bone for both UTE and PETRA images, and reduced the difference between the two imaging sequences. Both postprocessed UTE and PETRA images demonstrated sufficient power to discriminate air from bone to support synthetic CT generation from MRI data. PMID:25776205

Method for extracting long-equivalent wavelength interferometric information

NASA Technical Reports Server (NTRS)

Hochberg, Eric B. (Inventor)

1991-01-01

A process for extracting long-equivalent wavelength interferometric information from a two-wavelength polychromatic or achromatic interferometer. The process comprises the steps of simultaneously recording a non-linear sum of two different frequency visible light interferograms on a high resolution film and then placing the developed film in an optical train for Fourier transformation, low pass spatial filtering and inverse transformation of the film image to produce low spatial frequency fringes corresponding to a long-equivalent wavelength interferogram. The recorded non-linear sum irradiance derived from the two-wavelength interferometer is obtained by controlling the exposure so that the average interferogram irradiance is set at either the noise level threshold or the saturation level threshold of the film.

Recent Advances in Fiber Lasers for Nonlinear Microscopy

PubMed Central

Xu, C.; Wise, F. W.

2013-01-01

Nonlinear microscopy techniques developed over the past two decades have provided dramatic new capabilities for biological imaging. The initial demonstrations of nonlinear microscopies coincided with the development of solid-state femtosecond lasers, which continue to dominate applications of nonlinear microscopy. Fiber lasers offer attractive features for biological and biomedical imaging, and recent advances are leading to high-performance sources with the potential for robust, inexpensive, integrated instruments. This article discusses recent advances, and identifies challenges and opportunities for fiber lasers in nonlinear bioimaging. PMID:24416074

Biomolecular Imaging with Coherent Nonlinear Vibrational Microscopy

PubMed Central

Chung, Chao-Yu; Boik, John; Potma, Eric O.

2014-01-01

Optical imaging with spectroscopic vibrational contrast is a label-free solution for visualizing, identifying, and quantifying a wide range of biomolecular compounds in biological materials. Both linear and nonlinear vibrational microscopy techniques derive their imaging contrast from infrared active or Raman allowed molecular transitions, which provide a rich palette for interrogating chemical and structural details of the sample. Yet nonlinear optical methods, which include both second-order sum-frequency generation (SFG) and third-order coherent Raman scattering (CRS) techniques, offer several improved imaging capabilities over their linear precursors. Nonlinear vibrational microscopy features unprecedented vibrational imaging speeds, provides strategies for higher spatial resolution, and gives access to additional molecular parameters. These advances have turned vibrational microscopy into a premier tool for chemically dissecting live cells and tissues. This review discusses the molecular contrast of SFG and CRS microscopy and highlights several of the advanced imaging capabilities that have impacted biological and biomedical research. PMID:23245525

Z-scan studies of the nonlinear optical properties of gold nanoparticles prepared by electron beam deposition.

PubMed

Mezher, M H; Nady, A; Penny, R; Chong, W Y; Zakaria, R

2015-11-20

This paper details the fabrication process for placing single-layer gold (Au) nanoparticles on a planar substrate, and investigation of the resulting optical properties that can be exploited for nonlinear optics applications. Preparation of Au nanoparticles on the substrate involved electron beam deposition and subsequent thermal dewetting. The obtained thin films of Au had a variation in thicknesses related to the controllable deposition time during the electron beam deposition process. These samples were then subjected to thermal annealing at 600°C to produce a randomly distributed layer of Au nanoparticles. Observation from field-effect scanning electron microscope (FESEM) images indicated the size of Au nanoparticles ranges from ∼13 to ∼48  nm. Details of the optical properties related to peak absorption of localized surface plasmon resonance (LSPR) of the nanoparticle were revealed by use of UV-Vis spectroscopy. The Z-scan technique was used to measure the nonlinear effects on the fabricated Au nanoparticle layers where it strongly relates LSPR and nonlinear optical properties.

Neural response to reward anticipation under risk is nonlinear in probabilities.

PubMed

Hsu, Ming; Krajbich, Ian; Zhao, Chen; Camerer, Colin F

2009-02-18

A widely observed phenomenon in decision making under risk is the apparent overweighting of unlikely events and the underweighting of nearly certain events. This violates standard assumptions in expected utility theory, which requires that expected utility be linear (objective) in probabilities. Models such as prospect theory have relaxed this assumption and introduced the notion of a "probability weighting function," which captures the key properties found in experimental data. This study reports functional magnetic resonance imaging (fMRI) data that neural response to expected reward is nonlinear in probabilities. Specifically, we found that activity in the striatum during valuation of monetary gambles are nonlinear in probabilities in the pattern predicted by prospect theory, suggesting that probability distortion is reflected at the level of the reward encoding process. The degree of nonlinearity reflected in individual subjects' decisions is also correlated with striatal activity across subjects. Our results shed light on the neural mechanisms of reward processing, and have implications for future neuroscientific studies of decision making involving extreme tails of the distribution, where probability weighting provides an explanation for commonly observed behavioral anomalies.

Generalized Wideband Harmonic Imaging of Nonlinearly Loaded Scatterers: Theory, Analysis, and Application for Forward-Looking Radar Target Detection

DTIC Science & Technology

2014-09-01

signal) operations; it is general enough so that it can accommodate high - power (large-signal) sensing as well—which may be needed to detect targets... Generalized Wideband Harmonic Imaging of Nonlinearly Loaded Scatterers: Theory, Analysis, and Application for Forward-Looking Radar Target...Research Laboratory Adelphi, MD 20783-1138 ARL-TR-7121 September 2014 Generalized Wideband Harmonic Imaging of Nonlinearly Loaded

Cascaded K-means convolutional feature learner and its application to face recognition

NASA Astrophysics Data System (ADS)

Zhou, Daoxiang; Yang, Dan; Zhang, Xiaohong; Huang, Sheng; Feng, Shu

2017-09-01

Currently, considerable efforts have been devoted to devise image representation. However, handcrafted methods need strong domain knowledge and show low generalization ability, and conventional feature learning methods require enormous training data and rich parameters tuning experience. A lightened feature learner is presented to solve these problems with application to face recognition, which shares similar topology architecture as a convolutional neural network. Our model is divided into three components: cascaded convolution filters bank learning layer, nonlinear processing layer, and feature pooling layer. Specifically, in the filters learning layer, we use K-means to learn convolution filters. Features are extracted via convoluting images with the learned filters. Afterward, in the nonlinear processing layer, hyperbolic tangent is employed to capture the nonlinear feature. In the feature pooling layer, to remove the redundancy information and incorporate the spatial layout, we exploit multilevel spatial pyramid second-order pooling technique to pool the features in subregions and concatenate them together as the final representation. Extensive experiments on four representative datasets demonstrate the effectiveness and robustness of our model to various variations, yielding competitive recognition results on extended Yale B and FERET. In addition, our method achieves the best identification performance on AR and labeled faces in the wild datasets among the comparative methods.

Nonlinear optical microscopy for immunoimaging: a custom optimized system of high-speed, large-area, multicolor imaging

PubMed Central

Li, Hui; Cui, Quan; Zhang, Zhihong; Luo, Qingming

2015-01-01

Background The nonlinear optical microscopy has become the current state-of-the-art for intravital imaging. Due to its advantages of high resolution, superior tissue penetration, lower photodamage and photobleaching, as well as intrinsic z-sectioning ability, this technology has been widely applied in immunoimaging for a decade. However, in terms of monitoring immune events in native physiological environment, the conventional nonlinear optical microscope system has to be optimized for live animal imaging. Generally speaking, three crucial capabilities are desired, including high-speed, large-area and multicolor imaging. Among numerous high-speed scanning mechanisms used in nonlinear optical imaging, polygon scanning is not only linearly but also dispersion-freely with high stability and tunable rotation speed, which can overcome disadvantages of multifocal scanning, resonant scanner and acousto-optical deflector (AOD). However, low frame rate, lacking large-area or multicolor imaging ability make current polygonbased nonlinear optical microscopes unable to meet the requirements of immune event monitoring. Methods We built up a polygon-based nonlinear optical microscope system which was custom optimized for immunoimaging with high-speed, large-are and multicolor imaging abilities. Results Firstly, we validated the imaging performance of the system by standard methods. Then, to demonstrate the ability to monitor immune events, migration of immunocytes observed by the system based on typical immunological models such as lymph node, footpad and dorsal skinfold chamber are shown. Finally, we take an outlook for the possible advance of related technologies such as sample stabilization and optical clearing for more stable and deeper intravital immunoimaging. Conclusions This study will be helpful for optimizing nonlinear optical microscope to obtain more comprehensive and accurate information of immune events. PMID:25694951

Digital image processing for information extraction.

NASA Technical Reports Server (NTRS)

Billingsley, F. C.

1973-01-01

The modern digital computer has made practical image processing techniques for handling nonlinear operations in both the geometrical and the intensity domains, various types of nonuniform noise cleanup, and the numerical analysis of pictures. An initial requirement is that a number of anomalies caused by the camera (e.g., geometric distortion, MTF roll-off, vignetting, and nonuniform intensity response) must be taken into account or removed to avoid their interference with the information extraction process. Examples illustrating these operations are discussed along with computer techniques used to emphasize details, perform analyses, classify materials by multivariate analysis, detect temporal differences, and aid in human interpretation of photos.

Using polynomials to simplify fixed pattern noise and photometric correction of logarithmic CMOS image sensors.

PubMed

Li, Jing; Mahmoodi, Alireza; Joseph, Dileepan

2015-10-16

An important class of complementary metal-oxide-semiconductor (CMOS) image sensors are those where pixel responses are monotonic nonlinear functions of light stimuli. This class includes various logarithmic architectures, which are easily capable of wide dynamic range imaging, at video rates, but which are vulnerable to image quality issues. To minimize fixed pattern noise (FPN) and maximize photometric accuracy, pixel responses must be calibrated and corrected due to mismatch and process variation during fabrication. Unlike literature approaches, which employ circuit-based models of varying complexity, this paper introduces a novel approach based on low-degree polynomials. Although each pixel may have a highly nonlinear response, an approximately-linear FPN calibration is possible by exploiting the monotonic nature of imaging. Moreover, FPN correction requires only arithmetic, and an optimal fixed-point implementation is readily derived, subject to a user-specified number of bits per pixel. Using a monotonic spline, involving cubic polynomials, photometric calibration is also possible without a circuit-based model, and fixed-point photometric correction requires only a look-up table. The approach is experimentally validated with a logarithmic CMOS image sensor and is compared to a leading approach from the literature. The novel approach proves effective and efficient.

7T MRI subthalamic nucleus atlas for use with 3T MRI.

PubMed

Milchenko, Mikhail; Norris, Scott A; Poston, Kathleen; Campbell, Meghan C; Ushe, Mwiza; Perlmutter, Joel S; Snyder, Abraham Z

2018-01-01

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces motor symptoms in most patients with Parkinson disease (PD), yet may produce untoward effects. Investigation of DBS effects requires accurate localization of the STN, which can be difficult to identify on magnetic resonance images collected with clinically available 3T scanners. The goal of this study is to develop a high-quality STN atlas that can be applied to standard 3T images. We created a high-definition STN atlas derived from seven older participants imaged at 7T. This atlas was nonlinearly registered to a standard template representing 56 patients with PD imaged at 3T. This process required development of methodology for nonlinear multimodal image registration. We demonstrate mm-scale STN localization accuracy by comparison of our 3T atlas with a publicly available 7T atlas. We also demonstrate less agreement with an earlier histological atlas. STN localization error in the 56 patients imaged at 3T was less than 1 mm on average. Our methodology enables accurate STN localization in individuals imaged at 3T. The STN atlas and underlying 3T average template in MNI space are freely available to the research community. The image registration methodology developed in the course of this work may be generally applicable to other datasets.

Nonlinear acoustics in biomedical ultrasound

NASA Astrophysics Data System (ADS)

Cleveland, Robin O.

2015-10-01

Ultrasound is widely used to image inside the body; it is also used therapeutically to treat certain medical conditions. In both imaging and therapy applications the amplitudes employed in biomedical ultrasound are often high enough that nonlinear acoustic effects are present in the propagation: the effects have the potential to be advantageous in some scenarios but a hindrance in others. In the case of ultrasound imaging the nonlinearity produces higher harmonics that result in images of greater quality. However, nonlinear effects interfere with the imaging of ultrasound contrast agents (typically micron sized bubbles with a strong nonlinear response of their own) and nonlinear effects also result in complications when derating of pressure measurements in water to in situ values in tissue. High intensity focused ultrasound (HIFU) is emerging as a non-invasive therapeutic modality which can result in thermal ablation of tissue. For thermal ablation, the extra effective attenuation resulting from nonlinear effects can result in enhanced heating of tissue if shock formation occurs in the target region for ablation - a highly desirable effect. However, if nonlinearity is too strong it can also result in undesired near-field heating and reduced ablation in the target region. The disruption of tissue (histotripsy) and fragmentation of kidney stones (lithotripsy) exploits shock waves to produce mechanically based effects, with minimal heating present. In these scenarios it is necessary for the waves to be of sufficient amplitude that a shock exists when the waveform reaches the target region. This talk will discuss how underlying nonlinear phenomenon act in all the diagnostic and therapeutic applications described above.

Comment on Vaknine, R. and Lorenz, W.J. Lateral filtering of medical ultrasonic B-scans before image generation.

PubMed

Dickinson, R J

1985-04-01

In a recent paper, Vaknine and Lorenz discuss the merits of lateral deconvolution of demodulated B-scans. While this technique will decrease the lateral blurring of single discrete targets, such as the diaphragm in their figure 3, it is inappropriate to apply the method to the echoes arising from inhomogeneous structures such as soft tissue. In this latter case, the echoes from individual scatterers within the resolution cell of the transducer interfere to give random fluctuations in received echo amplitude termed speckle. Although his process can be modeled as a linear convolution similar to that of conventional image formation theory, the process of demodulation is a nonlinear process which loses the all-important phase information, and prevents the subsequent restoration of the image by Wiener filtering, itself a linear process.

Proton imaging of stochastic magnetic fields

NASA Astrophysics Data System (ADS)

Bott, A. F. A.; Graziani, C.; Tzeferacos, P.; White, T. G.; Lamb, D. Q.; Gregori, G.; Schekochihin, A. A.

2017-12-01

Recent laser-plasma experiments (Fox et al., Phys. Rev. Lett., vol. 111, 2013, 225002; Huntington et al., Nat. Phys., vol. 11(2), 2015, 173-176 Tzeferacos et al., Phys. Plasmas, vol. 24(4), 2017a, 041404; Tzeferacos et al., 2017b, arXiv:1702.03016 [physics.plasm-ph]) report the existence of dynamically significant magnetic fields, whose statistical characterisation is essential for a complete understanding of the physical processes these experiments are attempting to investigate. In this paper, we show how a proton-imaging diagnostic can be used to determine a range of relevant magnetic-field statistics, including the magnetic-energy spectrum. To achieve this goal, we explore the properties of an analytic relation between a stochastic magnetic field and the image-flux distribution created upon imaging that field. This `Kugland image-flux relation' was previously derived (Kugland et al., Rev. Sci. Instrum. vol. 83(10), 2012, 101301) under simplifying assumptions typically valid in actual proton-imaging set-ups. We conclude that, as with regular electromagnetic fields, features of the beam's final image-flux distribution often display a universal character determined by a single, field-scale dependent parameter - the contrast parameter s/{\\mathcal{M}}lB$ - which quantifies the relative size of the correlation length B$ of the stochastic field, proton displacements s$ due to magnetic deflections and the image magnification . For stochastic magnetic fields, we establish the existence of four contrast regimes, under which proton-flux images relate to their parent fields in a qualitatively distinct manner. These are linear, nonlinear injective, caustic and diffusive. The diffusive regime is newly identified and characterised. The nonlinear injective regime is distinguished from the caustic regime in manifesting nonlinear behaviour, but as in the linear regime, the path-integrated magnetic field experienced by the beam can be extracted uniquely. Thus, in the linear and nonlinear injective regimes we show that the magnetic-energy spectrum can be obtained under a further statistical assumption of isotropy. This is not the case in the caustic or diffusive regimes. We discuss complications to the contrast-regime characterisation arising for inhomogeneous, multi-scale stochastic fields, which can encompass many contrast regimes, as well as limitations currently placed by experimental capabilities on one's ability to extract magnetic-field statistics. The results presented in this paper are of consequence in providing a comprehensive description of proton images of stochastic magnetic fields, with applications for improved analysis of proton-flux images.

Application of separable parameter space techniques to multi-tracer PET compartment modeling.

PubMed

Zhang, Jeff L; Michael Morey, A; Kadrmas, Dan J

2016-02-07

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

NASA Astrophysics Data System (ADS)

Zhang, Jeff L.; Morey, A. Michael; Kadrmas, Dan J.

2016-02-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg-Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models.

PScan 1.0: flexible software framework for polygon based multiphoton microscopy

NASA Astrophysics Data System (ADS)

Li, Yongxiao; Lee, Woei Ming

2016-12-01

Multiphoton laser scanning microscopes exhibit highly localized nonlinear optical excitation and are powerful instruments for in-vivo deep tissue imaging. Customized multiphoton microscopy has a significantly superior performance for in-vivo imaging because of precise control over the scanning and detection system. To date, there have been several flexible software platforms catered to custom built microscopy systems i.e. ScanImage, HelioScan, MicroManager, that perform at imaging speeds of 30-100fps. In this paper, we describe a flexible software framework for high speed imaging systems capable of operating from 5 fps to 1600 fps. The software is based on the MATLAB image processing toolbox. It has the capability to communicate directly with a high performing imaging card (Matrox Solios eA/XA), thus retaining high speed acquisition. The program is also designed to communicate with LabVIEW and Fiji for instrument control and image processing. Pscan 1.0 can handle high imaging rates and contains sufficient flexibility for users to adapt to their high speed imaging systems.

Camera calibration based on the back projection process

NASA Astrophysics Data System (ADS)

Gu, Feifei; Zhao, Hong; Ma, Yueyang; Bu, Penghui

2015-12-01

Camera calibration plays a crucial role in 3D measurement tasks of machine vision. In typical calibration processes, camera parameters are iteratively optimized in the forward imaging process (FIP). However, the results can only guarantee the minimum of 2D projection errors on the image plane, but not the minimum of 3D reconstruction errors. In this paper, we propose a universal method for camera calibration, which uses the back projection process (BPP). In our method, a forward projection model is used to obtain initial intrinsic and extrinsic parameters with a popular planar checkerboard pattern. Then, the extracted image points are projected back into 3D space and compared with the ideal point coordinates. Finally, the estimation of the camera parameters is refined by a non-linear function minimization process. The proposed method can obtain a more accurate calibration result, which is more physically useful. Simulation and practical data are given to demonstrate the accuracy of the proposed method.

Perceptually lossless fractal image compression

NASA Astrophysics Data System (ADS)

Lin, Huawu; Venetsanopoulos, Anastasios N.

1996-02-01

According to the collage theorem, the encoding distortion for fractal image compression is directly related to the metric used in the encoding process. In this paper, we introduce a perceptually meaningful distortion measure based on the human visual system's nonlinear response to luminance and the visual masking effects. Blackwell's psychophysical raw data on contrast threshold are first interpolated as a function of background luminance and visual angle, and are then used as an error upper bound for perceptually lossless image compression. For a variety of images, experimental results show that the algorithm produces a compression ratio of 8:1 to 10:1 without introducing visual artifacts.

Flame analysis using image processing techniques

NASA Astrophysics Data System (ADS)

Her Jie, Albert Chang; Zamli, Ahmad Faizal Ahmad; Zulazlan Shah Zulkifli, Ahmad; Yee, Joanne Lim Mun; Lim, Mooktzeng

2018-04-01

This paper presents image processing techniques with the use of fuzzy logic and neural network approach to perform flame analysis. Flame diagnostic is important in the industry to extract relevant information from flame images. Experiment test is carried out in a model industrial burner with different flow rates. Flame features such as luminous and spectral parameters are extracted using image processing and Fast Fourier Transform (FFT). Flame images are acquired using FLIR infrared camera. Non-linearities such as thermal acoustic oscillations and background noise affect the stability of flame. Flame velocity is one of the important characteristics that determines stability of flame. In this paper, an image processing method is proposed to determine flame velocity. Power spectral density (PSD) graph is a good tool for vibration analysis where flame stability can be approximated. However, a more intelligent diagnostic system is needed to automatically determine flame stability. In this paper, flame features of different flow rates are compared and analyzed. The selected flame features are used as inputs to the proposed fuzzy inference system to determine flame stability. Neural network is used to test the performance of the fuzzy inference system.

The Role of Nonlinear Gradients in Parallel Imaging: A k-Space Based Analysis.

PubMed

Galiana, Gigi; Stockmann, Jason P; Tam, Leo; Peters, Dana; Tagare, Hemant; Constable, R Todd

2012-09-01

Sequences that encode the spatial information of an object using nonlinear gradient fields are a new frontier in MRI, with potential to provide lower peripheral nerve stimulation, windowed fields of view, tailored spatially-varying resolution, curved slices that mirror physiological geometry, and, most importantly, very fast parallel imaging with multichannel coils. The acceleration for multichannel images is generally explained by the fact that curvilinear gradient isocontours better complement the azimuthal spatial encoding provided by typical receiver arrays. However, the details of this complementarity have been more difficult to specify. We present a simple and intuitive framework for describing the mechanics of image formation with nonlinear gradients, and we use this framework to review some the main classes of nonlinear encoding schemes.

Development of ultrasound transducer diffractive field theory for nonlinear propagation-based imaging

NASA Astrophysics Data System (ADS)

Kharin, Nikolay A.

2000-04-01

In nonlinear ultrasound imaging the images are formed using the second harmonic energy generated due to the nonlinear nature of finite amplitude propagation. This propagation can be modeled using the KZK wave equation. This paper presents further development of nonlinear diffractive field theory based on the KZK equation and its solution by means of the slowly changing profile method for moderate nonlinearity. The analytical expression for amplitudes and phases of sum frequency wave are obtained in addition to the second harmonic wave. Also, the analytical expression for the relative curvature of the wave fronts of fundamental and second harmonic signals are derived. The media with different nonlinear properties and absorption coefficients were investigated to characterize the diffractive field of the transducer at medical frequencies. All expressions demonstrate good agreement with experimental results. The expressions are novel and provide an easy way for prediction of amplitude and phase structure of nonlinearly distorted field of a transducer. The sum frequency signal technique could be implemented as well as second harmonic technique to improve the quality of biomedical images. The results obtained are of importance for medical diagnostic ultrasound equipment design.

Computation of nonlinear ultrasound fields using a linearized contrast source method.

PubMed

Verweij, Martin D; Demi, Libertario; van Dongen, Koen W A

2013-08-01

Nonlinear ultrasound is important in medical diagnostics because imaging of the higher harmonics improves resolution and reduces scattering artifacts. Second harmonic imaging is currently standard, and higher harmonic imaging is under investigation. The efficient development of novel imaging modalities and equipment requires accurate simulations of nonlinear wave fields in large volumes of realistic (lossy, inhomogeneous) media. The Iterative Nonlinear Contrast Source (INCS) method has been developed to deal with spatiotemporal domains measuring hundreds of wavelengths and periods. This full wave method considers the nonlinear term of the Westervelt equation as a nonlinear contrast source, and solves the equivalent integral equation via the Neumann iterative solution. Recently, the method has been extended with a contrast source that accounts for spatially varying attenuation. The current paper addresses the problem that the Neumann iterative solution converges badly for strong contrast sources. The remedy is linearization of the nonlinear contrast source, combined with application of more advanced methods for solving the resulting integral equation. Numerical results show that linearization in combination with a Bi-Conjugate Gradient Stabilized method allows the INCS method to deal with fairly strong, inhomogeneous attenuation, while the error due to the linearization can be eliminated by restarting the iterative scheme.

Single-scale center-surround Retinex based restoration of low-illumination images with edge enhancement

NASA Astrophysics Data System (ADS)

Kwok, Ngaiming; Shi, Haiyan; Peng, Yeping; Wu, Hongkun; Li, Ruowei; Liu, Shilong; Rahman, Md Arifur

2018-04-01

Restoring images captured under low-illuminations is an essential front-end process for most image based applications. The Center-Surround Retinex algorithm has been a popular approach employed to improve image brightness. However, this algorithm in its basic form, is known to produce color degradations. In order to mitigate this problem, here the Single-Scale Retinex algorithm is modifid as an edge extractor while illumination is recovered through a non-linear intensity mapping stage. The derived edges are then integrated with the mapped image to produce the enhanced output. Furthermore, in reducing color distortion, the process is conducted in the magnitude sorted domain instead of the conventional Red-Green-Blue (RGB) color channels. Experimental results had shown that improvements with regard to mean brightness, colorfulness, saturation, and information content can be obtained.

Characteristics of nonlinear imaging of broadband laser stacked by chirped pulses

NASA Astrophysics Data System (ADS)

Wang, Youwen; You, Kaiming; Chen, Liezun; Lu, Shizhuan; Dai, Zhiping; Ling, Xiaohui

2014-11-01

Nanosecond-level pulses of specific shape is usually generated by stacking chirped pulses for high-power inertial confinement fusion driver, in which nonlinear imaging of scatterers may damage precious optical elements. We present a numerical study of the characteristics of nonlinear imaging of scatterers in broadband laser stacked by chirped pulses to disclose the dependence of location and intensity of images on the parameters of the stacked pulse. It is shown that, for sub-nanosecond long sub-pulses with chirp or transform-limited sub-pulses, the time-mean intensity and location of images through normally dispersive and anomalously dispersive self-focusing medium slab are almost identical; While for picosecond-level short sub-pulses with chirp, the time-mean intensity of images for weak normal dispersion is slightly higher than that for weak anomalous dispersion through a thin nonlinear slab; the result is opposite to that for strong dispersion in a thick nonlinear slab; Furthermore, for given time delay between neighboring sub-pulses, the time-mean intensity of images varies periodically with chirp of the sub-pulse increasing; for a given pulse width of sub-pulse, the time-mean intensity of images decreases with the time delay between neighboring sub-pulses increasing; additionally, there is a little difference in the time-mean intensity of images of the laser stacked by different numbers of sub-pulses. Finally, the obtained results are also given physical explanations.

Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology.

PubMed

Wu, Shibin; Yu, Shaode; Yang, Yuhan; Xie, Yaoqin

2013-01-01

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII).

Feature and Contrast Enhancement of Mammographic Image Based on Multiscale Analysis and Morphology

PubMed Central

Wu, Shibin; Xie, Yaoqin

2013-01-01

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII). PMID:24416072

Multipulse technique exploiting the intermodulation of ultrasound waves in a nonlinear medium.

PubMed

Biagi, Elena; Breschi, Luca; Vannacci, Enrico; Masotti, Leonardo

2009-03-01

In recent years, the nonlinear properties of materials have attracted much interest in nondestructive testing and in ultrasound diagnostic applications. Acoustic nonlinear parameters represent an opportunity to improve the information that can be extracted from a medium such as structural organization and pathologic status of tissue. In this paper, a method called pulse subtraction intermodulation (PSI), based on a multipulse technique, is presented and investigated both theoretically and experimentally. This method allows separation of the intermodulation products, which arise when 2 separate frequencies are transmitted in a nonlinear medium, from fundamental and second harmonic components, making them available for improved imaging techniques or signal processing algorithms devoted to tissue characterization. The theory of intermodulation product generation was developed according the Khokhlov-Zabolotskaya-Kuznetsov (KZK) nonlinear propagation equation, which is consistent with experimental results. The description of the proposed method, characterization of the intermodulation spectral contents, and quantitative results coming from in vitro experimentation are reported and discussed in this paper.

Control of polarization rotation in nonlinear propagation of fully structured light

NASA Astrophysics Data System (ADS)

Gibson, Christopher J.; Bevington, Patrick; Oppo, Gian-Luca; Yao, Alison M.

2018-03-01

Knowing and controlling the spatial polarization distribution of a beam is of importance in applications such as optical tweezing, imaging, material processing, and communications. Here we show how the polarization distribution is affected by both linear and nonlinear (self-focusing) propagation. We derive an analytical expression for the polarization rotation of fully structured light (FSL) beams during linear propagation and show that the observed rotation is due entirely to the difference in Gouy phase between the two eigenmodes comprising the FSL beams, in excellent agreement with numerical simulations. We also explore the effect of cross-phase modulation due to a self-focusing (Kerr) nonlinearity and show that polarization rotation can be controlled by changing the eigenmodes of the superposition, and physical parameters such as the beam size, the amount of Kerr nonlinearity, and the input power. Finally, we show that by biasing cylindrical vector beams to have elliptical polarization, we can vary the polarization state from radial through spiral to azimuthal using nonlinear propagation.

Cross-phase modulation spectral shifting: nonlinear phase contrast in a pump-probe microscope

PubMed Central

Wilson, Jesse W.; Samineni, Prathyush; Warren, Warren S.; Fischer, Martin C.

2012-01-01

Microscopy with nonlinear phase contrast is achieved by a simple modification to a nonlinear pump-probe microscope. The technique measures cross-phase modulation by detecting a pump-induced spectral shift in the probe pulse. Images with nonlinear phase contrast are acquired both in transparent and absorptive media. In paraffin-embedded biopsy sections, cross-phase modulation complements the chemically-specific pump-probe images with structural context. PMID:22567580

Review of progress in quantitative NDE

NASA Astrophysics Data System (ADS)

s of 386 papers and plenary presentations are included. The plenary sessions are related to the national technology initiative. The other sessions covered the following NDE topics: corrosion, electromagnetic arrays, elastic wave scattering and backscattering/noise, civil structures, material properties, holography, shearography, UT wave propagation, eddy currents, coatings, signal processing, radiography, computed tomography, EM imaging, adhesive bonds, NMR, laser ultrasonics, composites, thermal techniques, magnetic measurements, nonlinear acoustics, interface modeling and characterization, UT transducers, new techniques, joined materials, probes and systems, fatigue cracks and fracture, imaging and sizing, NDE in engineering and process control, acoustics of cracks, and sensors. An author index is included.

SU-F-J-71: Improving CT Quality for Radiation Therapy Planning and Delivery Guidance Using a Non-Linear Contrast Enhancement Technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Noid, G; Tai, A; Li, X

2016-06-15

Purpose: Advanced image post-processing techniques which enhance soft-tissue contrast in CT have not been widely employed for RT planning or delivery guidance. The purpose of this work is to assess the soft-tissue contrast enhancement from non-linear contrast enhancing filters and its impact in RT. The contrast enhancement reduces patient alignment uncertainties. Methods: Non-linear contrast enhancing methods, such as Best Contrast (Siemens), amplify small differences in X-ray attenuation between two adjacent structure without significantly increasing noise. Best Contrast (BC) separates a CT into two frequency bands. The low frequency band is modified by a non-linear scaling function before recombination with themore » high frequency band. CT data collected using a CT-on-rails (Definition AS Open, Siemens) during daily CT-guided RT for 6 prostate cancer patients and an image quality phantom (The Phantom Laboratory) were analyzed. Images acquired with a standard protocol (120 kVp, 0.6 pitch, 18 mGy CTDIvol) were processed before comparison to the unaltered images. Contrast and noise were measured in the the phantom. Inter-observer variation was assessed by placing prostate contours on the 12 CT study sets, 6 enhanced and 6 unaltered, in a blinded study involving 8 observers. Results: The phantom data demonstrate that BC increased the contrast between the 1.0% supra-slice element and the background substrate by 46.5 HU while noise increased by only 2.3 HU. Thus the contrast to noise ratio increased from 1.28 to 6.71. Furthermore, the variation in centroid position of the prostate contours was decreased from 1.3±0.4 mm to 0.8±0.3 mm. Thus the CTV-to-PTV margin was reduced by 1.1 mm. The uncertainty in delineation of the prostate/rectum edge decreased by 0.5 mm. Conclusion: As demonstrated in phantom and patient scans the BC filter accentuates soft-tissue contrast. This enhancement leads to reduced inter-observer variation, which should improve RT planning and delivery. Supported by Siemens.« less

Optimizing image registration and infarct definition in stroke research.

PubMed

Harston, George W J; Minks, David; Sheerin, Fintan; Payne, Stephen J; Chappell, Michael; Jezzard, Peter; Jenkinson, Mark; Kennedy, James

2017-03-01

Accurate representation of final infarct volume is essential for assessing the efficacy of stroke interventions in imaging-based studies. This study defines the impact of image registration methods used at different timepoints following stroke, and the implications for infarct definition in stroke research. Patients presenting with acute ischemic stroke were imaged serially using magnetic resonance imaging. Infarct volume was defined manually using four metrics: 24-h b1000 imaging; 1-week and 1-month T2-weighted FLAIR; and automatically using predefined thresholds of ADC at 24 h. Infarct overlap statistics and volumes were compared across timepoints following both rigid body and nonlinear image registration to the presenting MRI. The effect of nonlinear registration on a hypothetical trial sample size was calculated. Thirty-seven patients were included. Nonlinear registration improved infarct overlap statistics and consistency of total infarct volumes across timepoints, and reduced infarct volumes by 4.0 mL (13.1%) and 7.1 mL (18.2%) at 24 h and 1 week, respectively, compared to rigid body registration. Infarct volume at 24 h, defined using a predetermined ADC threshold, was less sensitive to infarction than b1000 imaging. 1-week T2-weighted FLAIR imaging was the most accurate representation of final infarct volume. Nonlinear registration reduced hypothetical trial sample size, independent of infarct volume, by an average of 13%. Nonlinear image registration may offer the opportunity of improving the accuracy of infarct definition in serial imaging studies compared to rigid body registration, helping to overcome the challenges of anatomical distortions at subacute timepoints, and reducing sample size for imaging-based clinical trials.

Nonlinear response of lipid-shelled microbubbles to coded excitation: implications for noninvasive atherosclerosis imaging

NASA Astrophysics Data System (ADS)

Shekhar, Himanshu; Doyley, Marvin M.

2013-03-01

Nonlinear (subharmonic/harmonic) imaging with ultrasound contrast agents (UCA) could characterize the vasa vasorum, which could help assess the risk associated with atherosclerosis. However, the sensitivity and specificity of high-frequency nonlinear imaging must be improved to enable its clinical translation. The current excitation scheme employs sine-bursts — a strategy that requires high-peak pressures to produce strong nonlinear response from UCA. In this paper, chirp-coded excitation was evaluated to assess its ability to enhance the subharmonic and harmonic response of UCA. Acoustic measurements were conducted with a pair of single-element transducers at 10-MHz transmit frequencies to evaluate the subharmonic and harmonic response of Targestar-P® (Targeson Inc., San Diego, CA, USA), a commercially available phospholipid-encapsulated contrast agent. The results of this study demonstrated a 2 - 3 fold reduction in the subharmonic threshold, and a 4 - 14 dB increase in nonlinear signal-to-noise ratio, with chirp-coded excitation. Therefore, chirp-coded excitation could be well suited for improving the imaging performance of high-frequency harmonic and subharmonic imaging.

Development of adaptive noise reduction filter algorithm for pediatric body images in a multi-detector CT

NASA Astrophysics Data System (ADS)

Nishimaru, Eiji; Ichikawa, Katsuhiro; Okita, Izumi; Ninomiya, Yuuji; Tomoshige, Yukihiro; Kurokawa, Takehiro; Ono, Yutaka; Nakamura, Yuko; Suzuki, Masayuki

2008-03-01

Recently, several kinds of post-processing image filters which reduce the noise of computed tomography (CT) images have been proposed. However, these image filters are mostly for adults. Because these are not very effective in small (< 20 cm) display fields of view (FOV), we cannot use them for pediatric body images (e.g., premature babies and infant children). We have developed a new noise reduction filter algorithm for pediatric body CT images. This algorithm is based on a 3D post-processing in which the output pixel values are calculated by nonlinear interpolation in z-directions on original volumetric-data-sets. This algorithm does not need the in-plane (axial plane) processing, so the spatial resolution does not change. From the phantom studies, our algorithm could reduce SD up to 40% without affecting the spatial resolution of x-y plane and z-axis, and improved the CNR up to 30%. This newly developed filter algorithm will be useful for the diagnosis and radiation dose reduction of the pediatric body CT images.

Multimodal nonlinear imaging of arabidopsis thaliana root cell

NASA Astrophysics Data System (ADS)

Jang, Bumjoon; Lee, Sung-Ho; Woo, Sooah; Park, Jong-Hyun; Lee, Myeong Min; Park, Seung-Han

2017-07-01

Nonlinear optical microscopy has enabled the possibility to explore inside the living organisms. It utilizes ultrashort laser pulse with long wavelength (greater than 800nm). Ultrashort pulse produces high peak power to induce nonlinear optical phenomenon such as two-photon excitation fluorescence (TPEF) and harmonic generations in the medium while maintaining relatively low average energy pre area. In plant developmental biology, confocal microscopy is widely used in plant cell imaging after the development of biological fluorescence labels in mid-1990s. However, fluorescence labeling itself affects the sample and the sample deviates from intact condition especially when labelling the entire cell. In this work, we report the dynamic images of Arabidopsis thaliana root cells. This demonstrates the multimodal nonlinear optical microscopy is an effective tool for long-term plant cell imaging.

Ultrafast Imaging of Surface Plasmons Propagating on a Gold Surface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gong, Yu; Joly, Alan G.; Hu, Dehong

2015-05-13

We record time-resolved nonlinear photoemission electron microscopy (tr-PEEM) images of propagating surface plasmons (PSPs) launched from a lithographically patterned rectangular trench on a flat gold surface. Our tr-PEEM scheme involves a pair of identical, spatially separated, and interferometrically-locked femtosecond laser pulses. Power dependent PEEM images provide experimental evidence for a sequential coherent nonlinear photoemission process, in which one laser source creates a PSP polarization state through a linear interaction, and the second subsequently probes the prepared state via two photon photoemission. The recorded time-resolved movies of a PSP allow us to directly measure various properties of the surface-bound wave packet,more » including its carrier wavelength (785 nm) and group velocity (0.95c). In addition, tr-PEEM in concert with finite-difference time domain simulations together allow us to set a lower limit of 75 μm for the decay length of the PSP on a 100 nm thick gold film.« less

Computational microscopy: illumination coding and nonlinear optimization enables gigapixel 3D phase imaging

NASA Astrophysics Data System (ADS)

Tian, Lei; Waller, Laura

2017-05-01

Microscope lenses can have either large field of view (FOV) or high resolution, not both. Computational microscopy based on illumination coding circumvents this limit by fusing images from different illumination angles using nonlinear optimization algorithms. The result is a Gigapixel-scale image having both wide FOV and high resolution. We demonstrate an experimentally robust reconstruction algorithm based on a 2nd order quasi-Newton's method, combined with a novel phase initialization scheme. To further extend the Gigapixel imaging capability to 3D, we develop a reconstruction method to process the 4D light field measurements from sequential illumination scanning. The algorithm is based on a 'multislice' forward model that incorporates both 3D phase and diffraction effects, as well as multiple forward scatterings. To solve the inverse problem, an iterative update procedure that combines both phase retrieval and 'error back-propagation' is developed. To avoid local minimum solutions, we further develop a novel physical model-based initialization technique that accounts for both the geometric-optic and 1st order phase effects. The result is robust reconstructions of Gigapixel 3D phase images having both wide FOV and super resolution in all three dimensions. Experimental results from an LED array microscope were demonstrated.

A fast method to emulate an iterative POCS image reconstruction algorithm.

PubMed

Zeng, Gengsheng L

2017-10-01

Iterative image reconstruction algorithms are commonly used to optimize an objective function, especially when the objective function is nonquadratic. Generally speaking, the iterative algorithms are computationally inefficient. This paper presents a fast algorithm that has one backprojection and no forward projection. This paper derives a new method to solve an optimization problem. The nonquadratic constraint, for example, an edge-preserving denoising constraint is implemented as a nonlinear filter. The algorithm is derived based on the POCS (projections onto projections onto convex sets) approach. A windowed FBP (filtered backprojection) algorithm enforces the data fidelity. An iterative procedure, divided into segments, enforces edge-enhancement denoising. Each segment performs nonlinear filtering. The derived iterative algorithm is computationally efficient. It contains only one backprojection and no forward projection. Low-dose CT data are used for algorithm feasibility studies. The nonlinearity is implemented as an edge-enhancing noise-smoothing filter. The patient studies results demonstrate its effectiveness in processing low-dose x ray CT data. This fast algorithm can be used to replace many iterative algorithms. © 2017 American Association of Physicists in Medicine.

In vivo multimodal nonlinear optical imaging of mucosal tissue

NASA Astrophysics Data System (ADS)

Sun, Ju; Shilagard, Tuya; Bell, Brent; Motamedi, Massoud; Vargas, Gracie

2004-05-01

We present a multimodal nonlinear imaging approach to elucidate microstructures and spectroscopic features of oral mucosa and submucosa in vivo. The hamster buccal pouch was imaged using 3-D high resolution multiphoton and second harmonic generation microscopy. The multimodal imaging approach enables colocalization and differentiation of prominent known spectroscopic and structural features such as keratin, epithelial cells, and submucosal collagen at various depths in tissue. Visualization of cellular morphology and epithelial thickness are in excellent agreement with histological observations. These results suggest that multimodal nonlinear optical microscopy can be an effective tool for studying the physiology and pathology of mucosal tissue.

Segmentation of deformable organs from medical images using particle swarm optimization and nonlinear shape priors

NASA Astrophysics Data System (ADS)

Afifi, Ahmed; Nakaguchi, Toshiya; Tsumura, Norimichi

2010-03-01

In many medical applications, the automatic segmentation of deformable organs from medical images is indispensable and its accuracy is of a special interest. However, the automatic segmentation of these organs is a challenging task according to its complex shape. Moreover, the medical images usually have noise, clutter, or occlusion and considering the image information only often leads to meager image segmentation. In this paper, we propose a fully automated technique for the segmentation of deformable organs from medical images. In this technique, the segmentation is performed by fitting a nonlinear shape model with pre-segmented images. The kernel principle component analysis (KPCA) is utilized to capture the complex organs deformation and to construct the nonlinear shape model. The presegmentation is carried out by labeling each pixel according to its high level texture features extracted using the overcomplete wavelet packet decomposition. Furthermore, to guarantee an accurate fitting between the nonlinear model and the pre-segmented images, the particle swarm optimization (PSO) algorithm is employed to adapt the model parameters for the novel images. In this paper, we demonstrate the competence of proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans of different patients.

Performance assessment of a single-pixel compressive sensing imaging system

NASA Astrophysics Data System (ADS)

Du Bosq, Todd W.; Preece, Bradley L.

2016-05-01

Conventional electro-optical and infrared (EO/IR) systems capture an image by measuring the light incident at each of the millions of pixels in a focal plane array. Compressive sensing (CS) involves capturing a smaller number of unconventional measurements from the scene, and then using a companion process known as sparse reconstruction to recover the image as if a fully populated array that satisfies the Nyquist criteria was used. Therefore, CS operates under the assumption that signal acquisition and data compression can be accomplished simultaneously. CS has the potential to acquire an image with equivalent information content to a large format array while using smaller, cheaper, and lower bandwidth components. However, the benefits of CS do not come without compromise. The CS architecture chosen must effectively balance between physical considerations (SWaP-C), reconstruction accuracy, and reconstruction speed to meet operational requirements. To properly assess the value of such systems, it is necessary to fully characterize the image quality, including artifacts and sensitivity to noise. Imagery of the two-handheld object target set at range was collected using a passive SWIR single-pixel CS camera for various ranges, mirror resolution, and number of processed measurements. Human perception experiments were performed to determine the identification performance within the trade space. The performance of the nonlinear CS camera was modeled with the Night Vision Integrated Performance Model (NV-IPM) by mapping the nonlinear degradations to an equivalent linear shift invariant model. Finally, the limitations of CS modeling techniques will be discussed.

Dynamics and morphometric characterization of hippocampus neurons using digital holographic microscopy

NASA Astrophysics Data System (ADS)

Elkatlawy, Saeid; Gomariz, María.; Soto-Sánchez, Cristina; Martínez Navarrete, Gema; Fernández, Eduardo; Fimia, Antonio

2014-05-01

In this paper we report on the use of digital holographic microscopy for 3D real time imaging of cultured neurons and neural networks, in vitro. Digital holographic microscopy is employed as an assessment tool to study the biophysical origin of neurodegenerative diseases. Our study consists in the morphological characterization of the axon, dendrites and cell bodies. The average size and thickness of the soma were 21 and 13 μm, respectively. Furthermore, the average size and diameter of some randomly selected neurites were 4.8 and 0.89 μm, respectively. In addition, the spatiotemporal growth process of cellular bodies and extensions was fitted to by a non-linear behavior of the nerve system. Remarkably, this non-linear process represents the relationship between the growth process of cellular body with respect to the axon and dendrites of the neurons.

On the influence of zero-padding on the nonlinear operations in Quantitative Susceptibility Mapping

PubMed Central

Eskreis-Winkler, Sarah; Zhou, Dong; Liu, Tian; Gupta, Ajay; Gauthier, Susan A.; Wang, Yi; Spincemaille, Pascal

2016-01-01

Purpose Zero padding is a well-studied interpolation technique that improves image visualization without increasing image resolution. This interpolation is often performed as a last step before images are displayed on clinical workstations. Here, we seek to demonstrate the importance of zero padding before rather than after performing non-linear post-processing algorithms, such as Quantitative Susceptibility Mapping (QSM). To do so, we evaluate apparent spatial resolution, relative error and depiction of multiple sclerosis (MS) lesions on images that were zero padded prior to, in the middle of, and after the application of the QSM algorithm. Materials and Methods High resolution gradient echo (GRE) data were acquired on twenty MS patients, from which low resolution data were derived using k-space cropping. Pre-, mid-, and post-zero padded QSM images were reconstructed from these low resolution data by zero padding prior to field mapping, after field mapping, and after susceptibility mapping, respectively. Using high resolution QSM as the gold standard, apparent spatial resolution, relative error, and image quality of the pre-, mid-, and post-zero padded QSM images were measured and compared. Results Both the accuracy and apparent spatial resolution of the pre-zero padded QSM was higher than that of mid-zero padded QSM (p < 0.001; p < 0.001), which was higher than that of post-zero padded QSM (p < 0.001; p < 0.001). The image quality of pre-zero padded reconstructions was higher than that of mid- and post-zero padded reconstructions (p = 0.004; p < 0.001). Conclusion Zero padding of the complex GRE data prior to nonlinear susceptibility mapping improves image accuracy and apparent resolution compared to zero padding afterwards. It also provides better delineation of MS lesion geometry, which may improve lesion subclassification and disease monitoring in MS patients. PMID:27587225

On the influence of zero-padding on the nonlinear operations in Quantitative Susceptibility Mapping.

PubMed

Eskreis-Winkler, Sarah; Zhou, Dong; Liu, Tian; Gupta, Ajay; Gauthier, Susan A; Wang, Yi; Spincemaille, Pascal

2017-01-01

Zero padding is a well-studied interpolation technique that improves image visualization without increasing image resolution. This interpolation is often performed as a last step before images are displayed on clinical workstations. Here, we seek to demonstrate the importance of zero padding before rather than after performing non-linear post-processing algorithms, such as Quantitative Susceptibility Mapping (QSM). To do so, we evaluate apparent spatial resolution, relative error and depiction of multiple sclerosis (MS) lesions on images that were zero padded prior to, in the middle of, and after the application of the QSM algorithm. High resolution gradient echo (GRE) data were acquired on twenty MS patients, from which low resolution data were derived using k-space cropping. Pre-, mid-, and post-zero padded QSM images were reconstructed from these low resolution data by zero padding prior to field mapping, after field mapping, and after susceptibility mapping, respectively. Using high resolution QSM as the gold standard, apparent spatial resolution, relative error, and image quality of the pre-, mid-, and post-zero padded QSM images were measured and compared. Both the accuracy and apparent spatial resolution of the pre-zero padded QSM was higher than that of mid-zero padded QSM (p<0.001; p<0.001), which was higher than that of post-zero padded QSM (p<0.001; p<0.001). The image quality of pre-zero padded reconstructions was higher than that of mid- and post-zero padded reconstructions (p=0.004; p<0.001). Zero padding of the complex GRE data prior to nonlinear susceptibility mapping improves image accuracy and apparent resolution compared to zero padding afterwards. It also provides better delineation of MS lesion geometry, which may improve lesion subclassification and disease monitoring in MS patients. Copyright © 2016 Elsevier Inc. All rights reserved.

Restoration of Static JPEG Images and RGB Video Frames by Means of Nonlinear Filtering in Conditions of Gaussian and Non-Gaussian Noise

NASA Astrophysics Data System (ADS)

Sokolov, R. I.; Abdullin, R. R.

2017-11-01

The use of nonlinear Markov process filtering makes it possible to restore both video stream frames and static photos at the stage of preprocessing. The present paper reflects the results of research in comparison of these types image filtering quality by means of special algorithm when Gaussian or non-Gaussian noises acting. Examples of filter operation at different values of signal-to-noise ratio are presented. A comparative analysis has been performed, and the best filtered kind of noise has been defined. It has been shown the quality of developed algorithm is much better than quality of adaptive one for RGB signal filtering at the same a priori information about the signal. Also, an advantage over median filter takes a place when both fluctuation and pulse noise filtering.

Coherent nonlinear optical imaging: beyond fluorescence microscopy.

PubMed

Min, Wei; Freudiger, Christian W; Lu, Sijia; Xie, X Sunney

2011-01-01

The quest for ultrahigh detection sensitivity with spectroscopic contrasts other than fluorescence has led to various novel approaches to optical microscopy of biological systems. Coherent nonlinear optical imaging, especially the recently developed nonlinear dissipation microscopy (including stimulated Raman scattering and two-photon absorption) and pump-probe microscopy (including excited-state absorption, stimulated emission, and ground-state depletion), provides new image contrasts for nonfluorescent species. Thanks to the high-frequency modulation transfer scheme, these imaging techniques exhibit superb detection sensitivity. By directly interrogating vibrational and/or electronic energy levels of molecules, they offer high molecular specificity. Here we review the underlying principles and excitation and detection schemes, as well as exemplary biomedical applications of this emerging class of molecular imaging techniques.

Simultaneous parametric generation and up-conversion of entangled optical images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saygin, M. Yu., E-mail: mihasyu@gmail.com; Chirkin, A. S., E-mail: aschirkin@rambler.r

A quantum theory of parametric amplification and frequency conversion of an optical image in coupled nonlinear optical processes that include one parametric amplification process at high-frequency pumping and two up-conversion processes in the same pump field is developed. The field momentum operator that takes into account the diffraction and group velocities of the waves is used to derive the quantum equations related to the spatial dynamics of the images during the interaction. An optical scheme for the amplification and conversion of a close image is considered. The mean photon number density and signal-to-noise ratio are calculated in the fixed-pump-field approximationmore » for images at various frequencies. It has been established that the signal-to-noise ratio decreases with increasing interaction length in the amplified image and increases in the images at the generated frequencies, tending to asymptotic values for all interacting waves. The variance of the difference of the numbers of photons is calculated for various pairs of frequencies. The quantum entanglement of the optical images formed in a high-frequency pump field is shown to be converted to higher frequencies during the generation of sum frequencies. Thus, two pairs of entangled optical images are produced in the process considered.« less

Performance assessment of multi-frequency processing of ICU chest images for enhanced visualization of tubes and catheters

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Couwenhoven, Mary E.; Foos, David H.; Doran, James; Yankelevitz, David F.; Henschke, Claudia I.

2008-03-01

An image-processing method has been developed to improve the visibility of tube and catheter features in portable chest x-ray (CXR) images captured in the intensive care unit (ICU). The image-processing method is based on a multi-frequency approach, wherein the input image is decomposed into different spatial frequency bands, and those bands that contain the tube and catheter signals are individually enhanced by nonlinear boosting functions. Using a random sampling strategy, 50 cases were retrospectively selected for the study from a large database of portable CXR images that had been collected from multiple institutions over a two-year period. All images used in the study were captured using photo-stimulable, storage phosphor computed radiography (CR) systems. Each image was processed two ways. The images were processed with default image processing parameters such as those used in clinical settings (control). The 50 images were then separately processed using the new tube and catheter enhancement algorithm (test). Three board-certified radiologists participated in a reader study to assess differences in both detection-confidence performance and diagnostic efficiency between the control and test images. Images were evaluated on a diagnostic-quality, 3-megapixel monochrome monitor. Two scenarios were studied: the baseline scenario, representative of today's workflow (a single-control image presented with the window/level adjustments enabled) vs. the test scenario (a control/test image pair presented with a toggle enabled and the window/level settings disabled). The radiologists were asked to read the images in each scenario as they normally would for clinical diagnosis. Trend analysis indicates that the test scenario offers improved reading efficiency while providing as good or better detection capability compared to the baseline scenario.

Measurement of attenuation coefficients of the fundamental and second harmonic waves in water

NASA Astrophysics Data System (ADS)

Zhang, Shuzeng; Jeong, Hyunjo; Cho, Sungjong; Li, Xiongbing

2016-02-01

Attenuation corrections in nonlinear acoustics play an important role in the study of nonlinear fluids, biomedical imaging, or solid material characterization. The measurement of attenuation coefficients in a nonlinear regime is not easy because they depend on the source pressure and requires accurate diffraction corrections. In this work, the attenuation coefficients of the fundamental and second harmonic waves which come from the absorption of water are measured in nonlinear ultrasonic experiments. Based on the quasilinear theory of the KZK equation, the nonlinear sound field equations are derived and the diffraction correction terms are extracted. The measured sound pressure amplitudes are adjusted first for diffraction corrections in order to reduce the impact on the measurement of attenuation coefficients from diffractions. The attenuation coefficients of the fundamental and second harmonics are calculated precisely from a nonlinear least squares curve-fitting process of the experiment data. The results show that attenuation coefficients in a nonlinear condition depend on both frequency and source pressure, which are much different from a linear regime. In a relatively lower drive pressure, the attenuation coefficients increase linearly with frequency. However, they present the characteristic of nonlinear growth in a high drive pressure. As the diffraction corrections are obtained based on the quasilinear theory, it is important to use an appropriate source pressure for accurate attenuation measurements.

Apodization of spurs in radar receivers using multi-channel processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin W.; Bickel, Douglas L.

The various technologies presented herein relate to identification and mitigation of spurious energies or signals (aka "spurs") in radar imaging. Spurious energy in received radar data can be a consequence of non-ideal component and circuit behavior. Such behavior can result from I/Q imbalance, nonlinear component behavior, additive interference (e.g. cross-talk, etc.), etc. The manifestation of the spurious energy in a radar image (e.g., a range-Doppler map) can be influenced by appropriate pulse-to-pulse phase modulation. Comparing multiple images which have been processed using the same data but of different signal paths and modulations enables identification of undesired spurs, with subsequent croppingmore » or apodization of the undesired spurs from a radar image. Spurs can be identified by comparison with a threshold energy. Removal of an undesired spur enables enhanced identification of true targets in a radar image.« less

Advances in optical information processing IV; Proceedings of the Meeting, Orlando, FL, Apr. 18-20, 1990

NASA Astrophysics Data System (ADS)

Pape, Dennis R.

1990-09-01

The present conference discusses topics in optical image processing, optical signal processing, acoustooptic spectrum analyzer systems and components, and optical computing. Attention is given to tradeoffs in nonlinearly recorded matched filters, miniature spatial light modulators, detection and classification using higher-order statistics of optical matched filters, rapid traversal of an image data base using binary synthetic discriminant filters, wideband signal processing for emitter location, an acoustooptic processor for autonomous SAR guidance, and sampling of Fresnel transforms. Also discussed are an acoustooptic RF signal-acquisition system, scanning acoustooptic spectrum analyzers, the effects of aberrations on acoustooptic systems, fast optical digital arithmetic processors, information utilization in analog and digital processing, optical processors for smart structures, and a self-organizing neural network for unsupervised learning.

The pre-image problem for Laplacian Eigenmaps utilizing L 1 regularization with applications to data fusion

NASA Astrophysics Data System (ADS)

Cloninger, Alexander; Czaja, Wojciech; Doster, Timothy

2017-07-01

As the popularity of non-linear manifold learning techniques such as kernel PCA and Laplacian Eigenmaps grows, vast improvements have been seen in many areas of data processing, including heterogeneous data fusion and integration. One problem with the non-linear techniques, however, is the lack of an easily calculable pre-image. Existence of such pre-image would allow visualization of the fused data not only in the embedded space, but also in the original data space. The ability to make such comparisons can be crucial for data analysts and other subject matter experts who are the end users of novel mathematical algorithms. In this paper, we propose a pre-image algorithm for Laplacian Eigenmaps. Our method offers major improvements over existing techniques, which allow us to address the problem of noisy inputs and the issue of how to calculate the pre-image of a point outside the convex hull of training samples; both of which have been overlooked in previous studies in this field. We conclude by showing that our pre-image algorithm, combined with feature space rotations, allows us to recover occluded pixels of an imaging modality based off knowledge of that image measured by heterogeneous modalities. We demonstrate this data recovery on heterogeneous hyperspectral (HS) cameras, as well as by recovering LIDAR measurements from HS data.

70 nm resolution in subsurface optical imaging of silicon integrated-circuits using pupil-function engineering

NASA Astrophysics Data System (ADS)

Serrels, K. A.; Ramsay, E.; Reid, D. T.

2009-02-01

We present experimental evidence for the resolution-enhancing effect of an annular pupil-plane aperture when performing nonlinear imaging in the vectorial-focusing regime through manipulation of the focal spot geometry. By acquiring two-photon optical beam-induced current images of a silicon integrated-circuit using solid-immersion-lens microscopy at 1550 nm we achieved 70 nm resolution. This result demonstrates a reduction in the minimum effective focal spot diameter of 36%. In addition, the annular-aperture-induced extension of the depth-of-focus causes an observable decrease in the depth contrast of the resulting image and we explain the origins of this using a simulation of the imaging process.

Using Polynomials to Simplify Fixed Pattern Noise and Photometric Correction of Logarithmic CMOS Image Sensors

PubMed Central

Li, Jing; Mahmoodi, Alireza; Joseph, Dileepan

2015-01-01

An important class of complementary metal-oxide-semiconductor (CMOS) image sensors are those where pixel responses are monotonic nonlinear functions of light stimuli. This class includes various logarithmic architectures, which are easily capable of wide dynamic range imaging, at video rates, but which are vulnerable to image quality issues. To minimize fixed pattern noise (FPN) and maximize photometric accuracy, pixel responses must be calibrated and corrected due to mismatch and process variation during fabrication. Unlike literature approaches, which employ circuit-based models of varying complexity, this paper introduces a novel approach based on low-degree polynomials. Although each pixel may have a highly nonlinear response, an approximately-linear FPN calibration is possible by exploiting the monotonic nature of imaging. Moreover, FPN correction requires only arithmetic, and an optimal fixed-point implementation is readily derived, subject to a user-specified number of bits per pixel. Using a monotonic spline, involving cubic polynomials, photometric calibration is also possible without a circuit-based model, and fixed-point photometric correction requires only a look-up table. The approach is experimentally validated with a logarithmic CMOS image sensor and is compared to a leading approach from the literature. The novel approach proves effective and efficient. PMID:26501287

System and method to create three-dimensional images of non-linear acoustic properties in a region remote from a borehole

DOEpatents

Vu, Cung; Nihei, Kurt T.; Schmitt, Denis P.; Skelt, Christopher; Johnson, Paul A.; Guyer, Robert; TenCate, James A.; Le Bas, Pierre-Yves

2013-01-01

In some aspects of the disclosure, a method for creating three-dimensional images of non-linear properties and the compressional to shear velocity ratio in a region remote from a borehole using a conveyed logging tool is disclosed. In some aspects, the method includes arranging a first source in the borehole and generating a steered beam of elastic energy at a first frequency; arranging a second source in the borehole and generating a steerable beam of elastic energy at a second frequency, such that the steerable beam at the first frequency and the steerable beam at the second frequency intercept at a location away from the borehole; receiving at the borehole by a sensor a third elastic wave, created by a three wave mixing process, with a frequency equal to a difference between the first and second frequencies and a direction of propagation towards the borehole; determining a location of a three wave mixing region based on the arrangement of the first and second sources and on properties of the third wave signal; and creating three-dimensional images of the non-linear properties using data recorded by repeating the generating, receiving and determining at a plurality of azimuths, inclinations and longitudinal locations within the borehole. The method is additionally used to generate three dimensional images of the ratio of compressional to shear acoustic velocity of the same volume surrounding the borehole.

Application of separable parameter space techniques to multi-tracer PET compartment modeling

PubMed Central

Zhang, Jeff L; Morey, A Michael; Kadrmas, Dan J

2016-01-01

Multi-tracer positron emission tomography (PET) can image two or more tracers in a single scan, characterizing multiple aspects of biological functions to provide new insights into many diseases. The technique uses dynamic imaging, resulting in time-activity curves that contain contributions from each tracer present. The process of separating and recovering separate images and/or imaging measures for each tracer requires the application of kinetic constraints, which are most commonly applied by fitting parallel compartment models for all tracers. Such multi-tracer compartment modeling presents challenging nonlinear fits in multiple dimensions. This work extends separable parameter space kinetic modeling techniques, previously developed for fitting single-tracer compartment models, to fitting multi-tracer compartment models. The multi-tracer compartment model solution equations were reformulated to maximally separate the linear and nonlinear aspects of the fitting problem, and separable least-squares techniques were applied to effectively reduce the dimensionality of the nonlinear fit. The benefits of the approach are then explored through a number of illustrative examples, including characterization of separable parameter space multi-tracer objective functions and demonstration of exhaustive search fits which guarantee the true global minimum to within arbitrary search precision. Iterative gradient-descent algorithms using Levenberg–Marquardt were also tested, demonstrating improved fitting speed and robustness as compared to corresponding fits using conventional model formulations. The proposed technique overcomes many of the challenges in fitting simultaneous multi-tracer PET compartment models. PMID:26788888

A constructive nonlinear array (CNA) method for barely visible impact detection in composite materials

NASA Astrophysics Data System (ADS)

Malfense Fierro, Gian Piero; Meo, Michele

2017-04-01

Currently there are numerous phased array techniques such as Full Matrix Capture (FMC) and Total Focusing Method (TFM) that provide good damage assessment for composite materials. Although, linear methods struggle to evaluate and assess low levels of damage, while nonlinear methods have shown great promise in early damage detection. A sweep and subtraction evaluation method coupled with a constructive nonlinear array method (CNA) is proposed in order to assess damage specific nonlinearities, address issues with frequency selection when using nonlinear ultrasound imaging techniques and reduce equipment generated nonlinearities. These methods were evaluated using multiple excitation locations on an impacted composite panel with a complex damage (barely visible impact damage). According to various recent works, damage excitation can be accentuated by exciting at local defect resonance (LDR) frequencies; although these frequencies are not always easily determinable. The sweep methodology uses broadband excitation to determine both local defect and material resonances, by assessing local defect generated nonlinearities using a laser vibrometer it is possible to assess which frequencies excite the complex geometry of the crack. The dual effect of accurately determining local defect resonances, the use of an image subtraction method and the reduction of equipment based nonlinearities using CNA result in greater repeatability and clearer nonlinear imaging (NIM).

Phenomenological modeling of nonlinear holograms based on metallic geometric metasurfaces.

PubMed

Ye, Weimin; Li, Xin; Liu, Juan; Zhang, Shuang

2016-10-31

Benefiting from efficient local phase and amplitude control at the subwavelength scale, metasurfaces offer a new platform for computer generated holography with high spatial resolution. Three-dimensional and high efficient holograms have been realized by metasurfaces constituted by subwavelength meta-atoms with spatially varying geometries or orientations. Metasurfaces have been recently extended to the nonlinear optical regime to generate holographic images in harmonic generation waves. Thus far, there has been no vector field simulation of nonlinear metasurface holograms because of the tremendous computational challenge in numerically calculating the collective nonlinear responses of the large number of different subwavelength meta-atoms in a hologram. Here, we propose a general phenomenological method to model nonlinear metasurface holograms based on the assumption that every meta-atom could be described by a localized nonlinear polarizability tensor. Applied to geometric nonlinear metasurfaces, we numerically model the holographic images formed by the second-harmonic waves of different spins. We show that, in contrast to the metasurface holograms operating in the linear optical regime, the wavelength of incident fundamental light should be slightly detuned from the fundamental resonant wavelength to optimize the efficiency and quality of nonlinear holographic images. The proposed modeling provides a general method to simulate nonlinear optical devices based on metallic metasurfaces.

Acousto-optic laser projection systems for displaying TV information

NASA Astrophysics Data System (ADS)

Gulyaev, Yu V.; Kazaryan, M. A.; Mokrushin, Yu M.; Shakin, O. V.

2015-04-01

This review addresses various approaches to television projection imaging on large screens using lasers. Results are presented of theoretical and experimental studies of an acousto-optic projection system operating on the principle of projecting an image of an entire amplitude-modulated television line in a single laser pulse. We consider characteristic features of image formation in such a system and the requirements for its individual components. Particular attention is paid to nonlinear distortions of the image signal, which show up most severely at low modulation signal frequencies. We discuss the feasibility of improving the process efficiency and image quality using acousto-optic modulators and pulsed lasers. Real-time projectors with pulsed line imaging can be used for controlling high-intensity laser radiation.

Nonlinear ultrasound imaging of nanoscale acoustic biomolecules

NASA Astrophysics Data System (ADS)

Maresca, David; Lakshmanan, Anupama; Lee-Gosselin, Audrey; Melis, Johan M.; Ni, Yu-Li; Bourdeau, Raymond W.; Kochmann, Dennis M.; Shapiro, Mikhail G.

2017-02-01

Ultrasound imaging is widely used to probe the mechanical structure of tissues and visualize blood flow. However, the ability of ultrasound to observe specific molecular and cellular signals is limited. Recently, a unique class of gas-filled protein nanostructures called gas vesicles (GVs) was introduced as nanoscale (˜250 nm) contrast agents for ultrasound, accompanied by the possibilities of genetic engineering, imaging of targets outside the vasculature and monitoring of cellular signals such as gene expression. These possibilities would be aided by methods to discriminate GV-generated ultrasound signals from anatomical background. Here, we show that the nonlinear response of engineered GVs to acoustic pressure enables selective imaging of these nanostructures using a tailored amplitude modulation strategy. Finite element modeling predicted a strongly nonlinear mechanical deformation and acoustic response to ultrasound in engineered GVs. This response was confirmed with ultrasound measurements in the range of 10 to 25 MHz. An amplitude modulation pulse sequence based on this nonlinear response allows engineered GVs to be distinguished from linear scatterers and other GV types with a contrast ratio greater than 11.5 dB. We demonstrate the effectiveness of this nonlinear imaging strategy in vitro, in cellulo, and in vivo.

Characterizing tissue microstructure using an ultrasound system-independent spatial autocorrelation function

NASA Astrophysics Data System (ADS)

Dong, Fang

1999-09-01

The research described in this dissertation is related to characterization of tissue microstructure using a system- independent spatial autocorrelation function (SAF). The function was determined using a reference phantom method, which employed a well-defined ``point- scatterer'' reference phantom to account for instrumental factors. The SAF's were estimated for several tissue-mimicking (TM) phantoms and fresh dog livers. Both phantom tests and in vitro dog liver measurements showed that the reference phantom method is relatively simple and fairly accurate, providing the bandwidth of the measurement system is sufficient for the size of the scatterer being involved in the scattering process. Implementation of this method in clinical scanner requires that distortions from patient's body wall be properly accounted for. The SAF's were estimated for two phantoms with body-wall-like distortions. The experimental results demonstrated that body wall distortions have little effect if echo data are acquired from a large scattering volume. One interesting application of the SAF is to form a ``scatterer size image''. The scatterer size image may help providing diagnostic tools for those diseases in which the tissue microstructure is different from the normal. Another method, the BSC method, utilizes information contained in the frequency dependence of the backscatter coefficient to estimate the scatterer size. The SAF technique produced accurate scatterer size images of homogeneous TM phantoms and the BSC method was capable of generating accurate size images for heterogeneous phantoms. In the scatterer size image of dog kidneys, the contrast-to-noise-ratio (CNR) between renal cortex and medulla was improved dramatically compared to the gray- scale image. The effect of nonlinear propagation was investigated by using a custom-designed phantom with overlaying TM fat layer. The results showed that the correlation length decreased when the transmitting power increased. The measurement results support the assumption that nonlinear propagation generates harmonic energies and causes underestimation of scatterer diameters. Nonlinear propagation can be further enhanced by those materials with high B/A value-a parameter which characterizes the degree of nonlinearity. Nine versions of TM fat and non-fat materials were measured for their B/A values using a new measurement technique, the ``simplified finite amplitude insertion substitution'' (SFAIS) method.

Fast epi-detected broadband multiplex CARS and SHG imaging of mouse skull cells

PubMed Central

Capitaine, Erwan; Moussa, Nawel Ould; Louot, Christophe; Bardet, Sylvia M.; Kano, Hideaki; Duponchel, Ludovic; Lévêque, Philippe; Couderc, Vincent; Leproux, Philippe

2017-01-01

We present a bimodal imaging system able to obtain epi-detected mutiplex coherent anti-Stokes Raman scattering (M-CARS) and second harmonic generation (SHG) signals coming from biological samples. We studied a fragment of mouse parietal bone and could detect broadband anti-Stokes and SHG responses originating from bone cells and collagen respectively. In addition we compared two post-processing methods to retrieve the imaginary part of the third-order nonlinear susceptibility related to the spontaneous Raman scattering. PMID:29359100

Digital signal processing and control and estimation theory -- Points of tangency, area of intersection, and parallel directions

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1976-01-01

A number of current research directions in the fields of digital signal processing and modern control and estimation theory were studied. Topics such as stability theory, linear prediction and parameter identification, system analysis and implementation, two-dimensional filtering, decentralized control and estimation, image processing, and nonlinear system theory were examined in order to uncover some of the basic similarities and differences in the goals, techniques, and philosophy of the two disciplines. An extensive bibliography is included.

The parallel-sequential field subtraction techniques for nonlinear ultrasonic imaging

NASA Astrophysics Data System (ADS)

Cheng, Jingwei; Potter, Jack N.; Drinkwater, Bruce W.

2018-04-01

Nonlinear imaging techniques have recently emerged which have the potential to detect cracks at a much earlier stage and have sensitivity to particularly closed defects. This study utilizes two modes of focusing: parallel, in which the elements are fired together with a delay law, and sequential, in which elements are fired independently. In the parallel focusing, a high intensity ultrasonic beam is formed in the specimen at the focal point. However, in sequential focusing only low intensity signals from individual elements enter the sample and the full matrix of transmit-receive signals is recorded; with elastic assumptions, both parallel and sequential images are expected to be identical. Here we measure the difference between these images formed from the coherent component of the field and use this to characterize nonlinearity of closed fatigue cracks. In particular we monitor the reduction in amplitude at the fundamental frequency at each focal point and use this metric to form images of the spatial distribution of nonlinearity. The results suggest the subtracted image can suppress linear features (e.g., back wall or large scatters) and allow damage to be detected at an early stage.

Time-gated imaging using nonlinear optical techniques applications to turbid materials

NASA Astrophysics Data System (ADS)

Reintjes, John F.; Duncan, Michael D.; Mahon, Rita; Tankersley, Lawrence L.; Bashkansky, Mark; Prewitt, Judith M. S.

1993-09-01

We describe the use of various nonlinear interactions based on stimulated Raman scattering for time gated imaging and their application to imaging through turbid media. Results are presented showing images obtained through solutions of non dairy creamer with attenuation of e-33 and 100 micrometers resolution, and through 6 mm of raw chicken meat, and 12 mm of human abdominal fat.

Echodentography based on nonlinear time reversal tomography: Ultrasonic nonlinear signature identification

NASA Astrophysics Data System (ADS)

Santos, Serge Dos; Farova, Zuzana; Kus, Vaclav; Prevorovsky, Zdenek

2012-05-01

This paper examines possibilities of using Nonlinear Elastic Wave Spectroscopy (NEWS) methods in dental investigations. Themain task consisted in imaging cracks or other degradation signatures located in dentin close to the Enamel-Dentine Junction (EDJ). NEWS approach was investigated experimentally with a new bi-modal acousto-optic set-up based on the chirp-coded nonlinear ultrasonic time reversal (TR) concepts. Complex internal structure of the tooth is analyzed by the TR-NEWS procedure adapted to tomography-like imaging of the tooth damages. Ultrasonic instrumentation with 10 MHz bandwidth has been set together including laser vibrometer used to detect responses of the tooth on its excitation carried out by a contact piezoelectric transducer. Bi-modal TR-NEWS images of the tooth were created before and after focusing, which resulted from the time compression. The polar B-scan of the tooth realized with TR-NEWS procedure is suggested to be applied as a new echodentography imaging.

Ultrafast optical pulse delivery with fibers for nonlinear microscopy

PubMed Central

Kim, Daekeun; Choi, Heejin; Yazdanfar, Siavash; So, Peter T. C.

2008-01-01

Nonlinear microscopies including multiphoton excitation fluorescence microscopy and multiple-harmonic generation microscopy have recently gained popularity for cellular and tissue imaging. The optimization of these imaging methods for minimally invasive use will require optical fibers to conduct light into tight space where free space delivery is difficult. The delivery of high peak power laser pulses with optical fibers is limited by dispersion resulting from nonlinear refractive index responses. In this paper, we characterize a variety of commonly used optical fibers in terms of how they affect pulse profile and imaging performance of nonlinear microscopy; the following parameters are quantified: spectral bandwidth and temporal pulse width, two-photon excitation efficiency, and optical resolution. A theoretical explanation for the measured performance of these is also provided. PMID:18816597

Lateral resolution improvement in scanning nonlinear dielectric microscopy by measuring super-higher-order nonlinear dielectric constants

NASA Astrophysics Data System (ADS)

Chinone, N.; Yamasue, K.; Hiranaga, Y.; Honda, K.; Cho, Y.

2012-11-01

Scanning nonlinear dielectric microscopy (SNDM) can be used to visualize polarization distributions in ferroelectric materials and dopant profiles in semiconductor devices. Without using a special sharp tip, we achieved an improved lateral resolution in SNDM through the measurement of super-higher-order nonlinearity up to the fourth order. We observed a multidomain single crystal congruent LiTaO3 (CLT) sample, and a cross section of a metal-oxide-semiconductor (MOS) field-effect-transistor (FET). The imaged domain boundaries of the CLT were narrower in the super-higher-order images than in the conventional image. Compared to the conventional method, the super-higher-order method resolved the more detailed structure of the MOSFET.

Erratum: Sources of Image Degradation in Fundamental and Harmonic Ultrasound Imaging: A Nonlinear, Full-Wave, Simulation Study

PubMed Central

Pinton, Gianmarco F.; Trahey, Gregg E.; Dahl, Jeremy J.

2015-01-01

A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain. This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-and-sum beamforming is used to generate point spread functions (PSFs) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is due to reverberation from near-field structures. Compared with fundamental imaging, reverberation clutter in harmonic imaging is 27.1 dB lower. Simulated tissue with uniform velocity but unchanged impedance characteristics indicates that for harmonic imaging, the primary source of degradation is phase aberration. PMID:21693410

Femtosecond imaging of nonlinear acoustics in gold.

PubMed

Pezeril, Thomas; Klieber, Christoph; Shalagatskyi, Viktor; Vaudel, Gwenaelle; Temnov, Vasily; Schmidt, Oliver G; Makarov, Denys

2014-02-24

We have developed a high-sensitivity, low-noise femtosecond imaging technique based on pump-probe time-resolved measurements with a standard CCD camera. The approach used in the experiment is based on lock-in acquisitions of images generated by a femtosecond laser probe synchronized to modulation of a femtosecond laser pump at the same rate. This technique allows time-resolved imaging of laser-excited phenomena with femtosecond time resolution. We illustrate the technique by time-resolved imaging of the nonlinear reshaping of a laser-excited picosecond acoustic pulse after propagation through a thin gold layer. Image analysis reveals the direct 2D visualization of the nonlinear acoustic propagation of the picosecond acoustic pulse. Many ultrafast pump-probe investigations can profit from this technique because of the wealth of information it provides over a typical single diode and lock-in amplifier setup, for example it can be used to image ultrasonic echoes in biological samples.

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1988-07-01

Principal Investigator B. K. Jenkins Signal and Image Processing Institute University of Southern California Mail Code 0272 Los Angeles, California...ADDRESS (09% SteW. Mnd ZIP Code ) 10. SOURC OF FUNONG NUMBERS Bldg. 410, Bolling AFB PROGAM CT TASK WORK UNIT Washington, D.C. 20332 EEETP.aso o 11...TAB Unmnnncced Justification By Distribution/ I O’ Availablility Codes I - ’_ ji and/or 2 I Summary During the period 1 July 1987 - 30 June 1988, the

Model-based estimation and control for off-axis parabolic mirror alignment

NASA Astrophysics Data System (ADS)

Fang, Joyce; Savransky, Dmitry

2018-02-01

This paper propose an model-based estimation and control method for an off-axis parabolic mirror (OAP) alignment. Current studies in automated optical alignment systems typically require additional wavefront sensors. We propose a self-aligning method using only focal plane images captured by the existing camera. Image processing methods and Karhunen-Loève (K-L) decomposition are used to extract measurements for the observer in closed-loop control system. Our system has linear dynamic in state transition, and a nonlinear mapping from the state to the measurement. An iterative extended Kalman filter (IEKF) is shown to accurately predict the unknown states, and nonlinear observability is discussed. Linear-quadratic regulator (LQR) is applied to correct the misalignments. The method is validated experimentally on the optical bench with a commercial OAP. We conduct 100 tests in the experiment to demonstrate the consistency in between runs.

Face-selective regions show invariance to linear, but not to non-linear, changes in facial images.

PubMed

Baseler, Heidi A; Young, Andrew W; Jenkins, Rob; Mike Burton, A; Andrews, Timothy J

2016-12-01

Familiar face recognition is remarkably invariant across huge image differences, yet little is understood concerning how image-invariant recognition is achieved. To investigate the neural correlates of invariance, we localized the core face-responsive regions and then compared the pattern of fMR-adaptation to different stimulus transformations in each region to behavioural data demonstrating the impact of the same transformations on familiar face recognition. In Experiment 1, we compared linear transformations of size and aspect ratio to a non-linear transformation affecting only part of the face. We found that adaptation to facial identity in face-selective regions showed invariance to linear changes, but there was no invariance to non-linear changes. In Experiment 2, we measured the sensitivity to non-linear changes that fell within the normal range of variation across face images. We found no adaptation to facial identity for any of the non-linear changes in the image, including to faces that varied in different levels of caricature. These results show a compelling difference in the sensitivity to linear compared to non-linear image changes in face-selective regions of the human brain that is only partially consistent with their effect on behavioural judgements of identity. We conclude that while regions such as the FFA may well be involved in the recognition of face identity, they are more likely to contribute to some form of normalisation that underpins subsequent recognition than to form the neural substrate of recognition per se. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-mode of Four and Six Wave Parametric Amplified Process

NASA Astrophysics Data System (ADS)

Zhu, Dayu; Yang, Yiheng; Zhang, Da; Liu, Ruizhou; Ma, Danmeng; Li, Changbiao; Zhang, Yanpeng

2017-03-01

Multiple quantum modes in correlated fields are essential for future quantum information processing and quantum computing. Here we report the generation of multi-mode phenomenon through parametric amplified four- and six-wave mixing processes in a rubidium atomic ensemble. The multi-mode properties in both frequency and spatial domains are studied. On one hand, the multi-mode behavior is dominantly controlled by the intensity of external dressing effect, or nonlinear phase shift through internal dressing effect, in frequency domain; on the other hand, the multi-mode behavior is visually demonstrated from the images of the biphoton fields directly, in spatial domain. Besides, the correlation of the two output fields is also demonstrated in both domains. Our approach supports efficient applications for scalable quantum correlated imaging.

Multi-mode of Four and Six Wave Parametric Amplified Process.

PubMed

Zhu, Dayu; Yang, Yiheng; Zhang, Da; Liu, Ruizhou; Ma, Danmeng; Li, Changbiao; Zhang, Yanpeng

2017-03-03

Multiple quantum modes in correlated fields are essential for future quantum information processing and quantum computing. Here we report the generation of multi-mode phenomenon through parametric amplified four- and six-wave mixing processes in a rubidium atomic ensemble. The multi-mode properties in both frequency and spatial domains are studied. On one hand, the multi-mode behavior is dominantly controlled by the intensity of external dressing effect, or nonlinear phase shift through internal dressing effect, in frequency domain; on the other hand, the multi-mode behavior is visually demonstrated from the images of the biphoton fields directly, in spatial domain. Besides, the correlation of the two output fields is also demonstrated in both domains. Our approach supports efficient applications for scalable quantum correlated imaging.

An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

PubMed Central

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

PubMed

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

Prediction of Moisture Content for Congou Black Tea Withering Leaves Using Image Features and Nonlinear Method.

PubMed

Liang, Gaozhen; Dong, Chunwang; Hu, Bin; Zhu, Hongkai; Yuan, Haibo; Jiang, Yongwen; Hao, Guoshuang

2018-05-18

Withering is the first step in the processing of congou black tea. With respect to the deficiency of traditional water content detection methods, a machine vision based NDT (Non Destructive Testing) method was established to detect the moisture content of withered leaves. First, according to the time sequences using computer visual system collected visible light images of tea leaf surfaces, and color and texture characteristics are extracted through the spatial changes of colors. Then quantitative prediction models for moisture content detection of withered tea leaves was established through linear PLS (Partial Least Squares) and non-linear SVM (Support Vector Machine). The results showed correlation coefficients higher than 0.8 between the water contents and green component mean value (G), lightness component mean value (L * ) and uniformity (U), which means that the extracted characteristics have great potential to predict the water contents. The performance parameters as correlation coefficient of prediction set (Rp), root-mean-square error of prediction (RMSEP), and relative standard deviation (RPD) of the SVM prediction model are 0.9314, 0.0411 and 1.8004, respectively. The non-linear modeling method can better describe the quantitative analytical relations between the image and water content. With superior generalization and robustness, the method would provide a new train of thought and theoretical basis for the online water content monitoring technology of automated production of black tea.

Practical estimate of gradient nonlinearity for implementation of apparent diffusion coefficient bias correction.

PubMed

Malkyarenko, Dariya I; Chenevert, Thomas L

2014-12-01

To describe an efficient procedure to empirically characterize gradient nonlinearity and correct for the corresponding apparent diffusion coefficient (ADC) bias on a clinical magnetic resonance imaging (MRI) scanner. Spatial nonlinearity scalars for individual gradient coils along superior and right directions were estimated via diffusion measurements of an isotropicic e-water phantom. Digital nonlinearity model from an independent scanner, described in the literature, was rescaled by system-specific scalars to approximate 3D bias correction maps. Correction efficacy was assessed by comparison to unbiased ADC values measured at isocenter. Empirically estimated nonlinearity scalars were confirmed by geometric distortion measurements of a regular grid phantom. The applied nonlinearity correction for arbitrarily oriented diffusion gradients reduced ADC bias from 20% down to 2% at clinically relevant offsets both for isotropic and anisotropic media. Identical performance was achieved using either corrected diffusion-weighted imaging (DWI) intensities or corrected b-values for each direction in brain and ice-water. Direction-average trace image correction was adequate only for isotropic medium. Empiric scalar adjustment of an independent gradient nonlinearity model adequately described DWI bias for a clinical scanner. Observed efficiency of implemented ADC bias correction quantitatively agreed with previous theoretical predictions and numerical simulations. The described procedure provides an independent benchmark for nonlinearity bias correction of clinical MRI scanners.

An incompressible fluid flow model with mutual information for MR image registration

NASA Astrophysics Data System (ADS)

Tsai, Leo; Chang, Herng-Hua

2013-03-01

Image registration is one of the fundamental and essential tasks within image processing. It is a process of determining the correspondence between structures in two images, which are called the template image and the reference image, respectively. The challenge of registration is to find an optimal geometric transformation between corresponding image data. This paper develops a new MR image registration algorithm that uses a closed incompressible viscous fluid model associated with mutual information. In our approach, we treat the image pixels as the fluid elements of a viscous fluid flow governed by the nonlinear Navier-Stokes partial differential equation (PDE). We replace the pressure term with the body force mainly used to guide the transformation with a weighting coefficient, which is expressed by the mutual information between the template and reference images. To solve this modified Navier-Stokes PDE, we adopted the fast numerical techniques proposed by Seibold1. The registration process of updating the body force, the velocity and deformation fields is repeated until the mutual information weight reaches a prescribed threshold. We applied our approach to the BrainWeb and real MR images. As consistent with the theory of the proposed fluid model, we found that our method accurately transformed the template images into the reference images based on the intensity flow. Experimental results indicate that our method is of potential in a wide variety of medical image registration applications.

GPU simulation of nonlinear propagation of dual band ultrasound pulse complexes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kvam, Johannes, E-mail: johannes.kvam@ntnu.no; Angelsen, Bjørn A. J., E-mail: bjorn.angelsen@ntnu.no; Elster, Anne C., E-mail: elster@ntnu.no

In a new method of ultrasound imaging, called SURF imaging, dual band pulse complexes composed of overlapping low frequency (LF) and high frequency (HF) pulses are transmitted, where the frequency ratio LF:HF ∼ 1 : 20, and the relative bandwidth of both pulses are ∼ 50 − 70%. The LF pulse length is hence ∼ 20 times the HF pulse length. The LF pulse is used to nonlinearly manipulate the material elasticity observed by the co-propagating HF pulse. This produces nonlinear interaction effects that give more information on the propagation of the pulse complex. Due to the large difference inmore » frequency and pulse length between the LF and the HF pulses, we have developed a dual level simulation where the LF pulse propagation is first simulated independent of the HF pulse, using a temporal sampling frequency matched to the LF pulse. A separate equation for the HF pulse is developed, where the the presimulated LF pulse modifies the propagation velocity. The equations are adapted to parallel processing in a GPU, where nonlinear simulations of a typical HF beam of 10 MHz down to 40 mm is done in ∼ 2 secs in a standard GPU. This simulation is hence very useful for studying the manipulation effect of the LF pulse on the HF pulse.« less

Chunking dynamics: heteroclinics in mind

PubMed Central

Rabinovich, Mikhail I.; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S.

2014-01-01

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components—brain modes—participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles—metastable states—connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics. PMID:24672469

Chunking dynamics: heteroclinics in mind.

PubMed

Rabinovich, Mikhail I; Varona, Pablo; Tristan, Irma; Afraimovich, Valentin S

2014-01-01

Recent results of imaging technologies and non-linear dynamics make possible to relate the structure and dynamics of functional brain networks to different mental tasks and to build theoretical models for the description and prediction of cognitive activity. Such models are non-linear dynamical descriptions of the interaction of the core components-brain modes-participating in a specific mental function. The dynamical images of different mental processes depend on their temporal features. The dynamics of many cognitive functions are transient. They are often observed as a chain of sequentially changing metastable states. A stable heteroclinic channel (SHC) consisting of a chain of saddles-metastable states-connected by unstable separatrices is a mathematical image for robust transients. In this paper we focus on hierarchical chunking dynamics that can represent several forms of transient cognitive activity. Chunking is a dynamical phenomenon that nature uses to perform information processing of long sequences by dividing them in shorter information items. Chunking, for example, makes more efficient the use of short-term memory by breaking up long strings of information (like in language where one can see the separation of a novel on chapters, paragraphs, sentences, and finally words). Chunking is important in many processes of perception, learning, and cognition in humans and animals. Based on anatomical information about the hierarchical organization of functional brain networks, we propose a cognitive network architecture that hierarchically chunks and super-chunks switching sequences of metastable states produced by winnerless competitive heteroclinic dynamics.

Multiphoton microscopy and image guided light activated therapy using nanomaterials (Conference Presentation)

NASA Astrophysics Data System (ADS)

Prasad, Paras N.

2017-02-01

This talk will focus on design and applications of nanomaterials exhibiting strong multiphoton upconversion for multiphoton microscopy as well as for image-guided and light activated therapy .1-3 Such processes can occur by truly nonlinear optical interactions proceeding through virtual intermediate states or by stepwise coupled linear excitations through real intermediate states. Multiphoton processes in biocompatible multifunctional nanoparticles allow for 3D deep tissue imaging. In addition, they can produce in-situ photon conversion of deep tissue penetrating near IR light into a needed shorter wavelength light for photo-activated therapy at a targeted site, thus overcoming the limited penetration of UV or visible light into biological media. We are using near IR emitters such as silicon quantum dots which also exhibit strong multiphoton excitation for multiphoton microscopy. Another approach involves nonlinear nanocrystals such as ZnO which can produce four wave mixing, sum frequency generation as well as second harmonic generation to convert a deep tissue penetrating Near IR light at the targeted biological site to a desired shorter wavelength light suitable for bio imaging or activation of a therapy. We have utilized this approach to activate a photosensitizer for photodynamic therapy. Yet another type of upconversion materials is rare-earth ion doped optical nanotransformers which transform a Near IR (NIR) light from an external source by sequential single photon absorption, in situ and on demand, to a needed wavelength. Applications of these nanotransformers in multiphoton photoacoustic imaging will also be presented. An exciting direction pursued by us using these multiphoton nanoparticles, is functional imaging of brain. Simultaneously, they can effect optogenetics for regioselective stimulation of neurons for providing an effective intervention/augmentation strategy to enhance the cognitive state and lead to a foundation for futuristic vision of super human capabilities. Challenges and opportunities will be discussed.

Rapid virtual H&E histology of breast tissue specimens using a compact fluorescence nonlinear microscope

PubMed Central

Cahill, Lucas C.; Giacomelli, Michael G.; Yoshitake, Tadayuki; Vardeh, Hilde; Faulkner-Jones, Beverly E.; Connolly, James L.; Sun, Chi-Kuang; Fujimoto, James G.

2017-01-01

Up to 40% of patients undergoing breast conserving surgery for breast cancer require repeat surgeries due to close to or positive margins. The lengthy processing required for evaluating surgical margins by standard paraffin embedded histology precludes its use during surgery and therefore, technologies for rapid evaluation of surgical pathology could improve the treatment of breast cancer by reducing the number of surgeries required. We demonstrate real-time histological evaluation of breast cancer surgical specimens by staining specimens with acridine orange (AO) and sulforhodamine 101 (SR101) analogously to hematoxylin and eosin (H&E) and then imaging the specimens with fluorescence nonlinear microscopy (NLM) using a compact femtosecond fiber laser. A video-rate computational light absorption model was used to produce realistic virtual H&E images of tissue in real time and in three dimensions. NLM imaging could be performed to depths of 100 µm below the tissue surface, which is important since many surgical specimens require subsurface evaluation due to artifacts on the tissue surface from electrocautery, surgical ink or debris from specimen handling. We validate this method by expert review of NLM images compared to formalin fixed, paraffin embedded (FFPE) H&E histology. Diagnostically important features such as normal terminal ductal lobular units, fibrous and adipose stromal parenchyma, inflammation, invasive carcinoma, and in-situ lobular and ductal carcinoma were present in NLM images associated with pathologies identified on standard FFPE H&E histology. We demonstrate that AO and SR101 were extracted to undetectable levels after FFPE processing and fluorescence in situ hybridization (FISH) HER2 amplification status was unaffected by the NLM imaging protocol. This method potentially enables cost-effective, real-time histological guidance of surgical resections. PMID:29131161

Effects of finite spatial resolution on quantitative CBF images from dynamic PET

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phelps, M.E.; Huang, S.C.; Mahoney, D.K.

1985-05-01

The finite spatial resolution of PET causes the time-activity responses on pixels around the boundaries between gray and white matter regions to contain kinetic components from tissues of different CBF's. CBF values estimated from kinetics of such mixtures are underestimated because of the nonlinear relationship between the time-activity response and the estimated CBF. Computer simulation is used to investigate these effects on phantoms of circular structures and realistic brain slice in terms of object size and quantitative CBF values. The CBF image calculated is compared to the case of having resolution loss alone. Results show that the size of amore » high flow region in the CBF image is decreased while that of a low flow region is increased. For brain phantoms, the qualitative appearance of CBF images is not seriously affected, but the estimated CBF's are underestimated by 11 to 16 percent in local gray matter regions (of size 1 cm/sup 2/) with about 14 percent reduction in global CBF over the whole slice. It is concluded that the combined effect of finite spatial resolution and the nonlinearity in estimating CBF from dynamic PET is quite significant and must be considered in processing and interpreting quantitative CBF images.« less

Saliency Detection of Stereoscopic 3D Images with Application to Visual Discomfort Prediction

NASA Astrophysics Data System (ADS)

Li, Hong; Luo, Ting; Xu, Haiyong

2017-06-01

Visual saliency detection is potentially useful for a wide range of applications in image processing and computer vision fields. This paper proposes a novel bottom-up saliency detection approach for stereoscopic 3D (S3D) images based on regional covariance matrix. As for S3D saliency detection, besides the traditional 2D low-level visual features, additional 3D depth features should also be considered. However, only limited efforts have been made to investigate how different features (e.g. 2D and 3D features) contribute to the overall saliency of S3D images. The main contribution of this paper is that we introduce a nonlinear feature integration descriptor, i.e., regional covariance matrix, to fuse both 2D and 3D features for S3D saliency detection. The regional covariance matrix is shown to be effective for nonlinear feature integration by modelling the inter-correlation of different feature dimensions. Experimental results demonstrate that the proposed approach outperforms several existing relevant models including 2D extended and pure 3D saliency models. In addition, we also experimentally verified that the proposed S3D saliency map can significantly improve the prediction accuracy of experienced visual discomfort when viewing S3D images.

Computer model for harmonic ultrasound imaging.

PubMed

Li, Y; Zagzebski, J A

2000-01-01

Harmonic ultrasound imaging has received great attention from ultrasound scanner manufacturers and researchers. In this paper, we present a computer model that can generate realistic harmonic images. In this model, the incident ultrasound is modeled after the "KZK" equation, and the echo signal is modeled using linear propagation theory because the echo signal is much weaker than the incident pulse. Both time domain and frequency domain numerical solutions to the "KZK" equation were studied. Realistic harmonic images of spherical lesion phantoms were generated for scans by a circular transducer. This model can be a very useful tool for studying the harmonic buildup and dissipation processes in a nonlinear medium, and it can be used to investigate a wide variety of topics related to B-mode harmonic imaging.

Computer model for harmonic ultrasound imaging.

PubMed

Li, Y; Zagzebski, J A

2000-01-01

Harmonic ultrasound imaging has received great attention from ultrasound scanner manufacturers and researchers. Here, the authors present a computer model that can generate realistic harmonic images. In this model, the incident ultrasound is modeled after the "KZK" equation, and the echo signal is modeled using linear propagation theory because the echo signal is much weaker than the incident pulse. Both time domain and frequency domain numerical solutions to the "KZK" equation were studied. Realistic harmonic images of spherical lesion phantoms were generated for scans by a circular transducer. This model can be a very useful tool for studying the harmonic buildup and dissipation processes in a nonlinear medium, and it can be used to investigate a wide variety of topics related to B-mode harmonic imaging.

Studies of superresolution range-Doppler imaging

NASA Astrophysics Data System (ADS)

Zhu, Zhaoda; Ye, Zhenru; Wu, Xiaoqing; Yin, Jun; She, Zhishun

1993-02-01

This paper presents three superresolution imaging methods, including the linear prediction data extrapolation DFT (LPDEDFT), the dynamic optimization linear least squares (DOLLS), and the Hopfield neural network nonlinear least squares (HNNNLS). Live data of a metalized scale model B-52 aircraft, mounted on a rotating platform in a microwave anechoic chamber, have in this way been processed, as has a flying Boeing-727 aircraft. The imaging results indicate that, compared to the conventional Fourier method, either higher resolution for the same effective bandwidth of transmitted signals and total rotation angle in imaging, or equal-quality images from smaller bandwidth and total rotation, angle may be obtained by these superresolution approaches. Moreover, these methods are compared in respect of their resolution capability and computational complexity.

Inverting Image Data For Optical Testing And Alignment

NASA Technical Reports Server (NTRS)

Shao, Michael; Redding, David; Yu, Jeffrey W.; Dumont, Philip J.

1993-01-01

Data from images produced by slightly incorrectly figured concave primary mirror in telescope processed into estimate of spherical aberration of mirror, by use of algorithm finding nonlinear least-squares best fit between actual images and synthetic images produced by multiparameter mathematical model of telescope optical system. Estimated spherical aberration, in turn, converted into estimate of deviation of reflector surface from nominal precise shape. Algorithm devised as part of effort to determine error in surface figure of primary mirror of Hubble space telescope, so corrective lens designed. Modified versions of algorithm also used to find optical errors in other components of telescope or of other optical systems, for purposes of testing, alignment, and/or correction.

Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis.

PubMed

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

2015-10-01

In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.

Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis

PubMed Central

Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

2015-01-01

In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%. PMID:26504638

Particle model for optical noisy image recovery via stochastic resonance

NASA Astrophysics Data System (ADS)

Zhang, Yongbin; Liu, Hongjun; Huang, Nan; Wang, Zhaolu; Han, Jing

2017-10-01

We propose a particle model for investigating the optical noisy image recovery via stochastic resonance. The light propagating in nonlinear media is regarded as moving particles, which are used for analyzing the nonlinear coupling of signal and noise. Owing to nonlinearity, a signal seeds a potential to reinforce itself at the expense of noise. The applied electric field, noise intensity, and correlation length are important parameters that influence the recovery effects. The noise-hidden image with the signal-to-noise intensity ratio of 1:30 is successfully restored and an optimal cross-correlation gain of 6.1 is theoretically obtained.

A spline-based non-linear diffeomorphism for multimodal prostate registration.

PubMed

Mitra, Jhimli; Kato, Zoltan; Martí, Robert; Oliver, Arnau; Lladó, Xavier; Sidibé, Désiré; Ghose, Soumya; Vilanova, Joan C; Comet, Josep; Meriaudeau, Fabrice

2012-08-01

This paper presents a novel method for non-rigid registration of transrectal ultrasound and magnetic resonance prostate images based on a non-linear regularized framework of point correspondences obtained from a statistical measure of shape-contexts. The segmented prostate shapes are represented by shape-contexts and the Bhattacharyya distance between the shape representations is used to find the point correspondences between the 2D fixed and moving images. The registration method involves parametric estimation of the non-linear diffeomorphism between the multimodal images and has its basis in solving a set of non-linear equations of thin-plate splines. The solution is obtained as the least-squares solution of an over-determined system of non-linear equations constructed by integrating a set of non-linear functions over the fixed and moving images. However, this may not result in clinically acceptable transformations of the anatomical targets. Therefore, the regularized bending energy of the thin-plate splines along with the localization error of established correspondences should be included in the system of equations. The registration accuracies of the proposed method are evaluated in 20 pairs of prostate mid-gland ultrasound and magnetic resonance images. The results obtained in terms of Dice similarity coefficient show an average of 0.980±0.004, average 95% Hausdorff distance of 1.63±0.48 mm and mean target registration and target localization errors of 1.60±1.17 mm and 0.15±0.12 mm respectively. Copyright © 2012 Elsevier B.V. All rights reserved.

Classification of product inspection items using nonlinear features

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.; Lee, H.-W.

1998-03-01

Automated processing and classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a system for automated non-invasive detection of defective product items on a conveyor belt. This approach involves two main steps: preprocessing and classification. Preprocessing locates individual items and segments ones that touch using a modified watershed algorithm. The second stage involves extraction of features that allow discrimination between damaged and clean items (pistachio nuts). This feature extraction and classification stage is the new aspect of this paper. We use a new nonlinear feature extraction scheme called the maximum representation and discriminating feature (MRDF) extraction method to compute nonlinear features that are used as inputs to a classifier. The MRDF is shown to provide better classification and a better ROC (receiver operating characteristic) curve than other methods.

Nonlinear and non-Gaussian Bayesian based handwriting beautification

NASA Astrophysics Data System (ADS)

Shi, Cao; Xiao, Jianguo; Xu, Canhui; Jia, Wenhua

2013-03-01

A framework is proposed in this paper to effectively and efficiently beautify handwriting by means of a novel nonlinear and non-Gaussian Bayesian algorithm. In the proposed framework, format and size of handwriting image are firstly normalized, and then typeface in computer system is applied to optimize vision effect of handwriting. The Bayesian statistics is exploited to characterize the handwriting beautification process as a Bayesian dynamic model. The model parameters to translate, rotate and scale typeface in computer system are controlled by state equation, and the matching optimization between handwriting and transformed typeface is employed by measurement equation. Finally, the new typeface, which is transformed from the original one and gains the best nonlinear and non-Gaussian optimization, is the beautification result of handwriting. Experimental results demonstrate the proposed framework provides a creative handwriting beautification methodology to improve visual acceptance.

A microcomputer program for analysis of nucleic acid hybridization data

PubMed Central

Green, S.; Field, J.K.; Green, C.D.; Beynon, R.J.

1982-01-01

The study of nucleic acid hybridization is facilitated by computer mediated fitting of theoretical models to experimental data. This paper describes a non-linear curve fitting program, using the `Patternsearch' algorithm, written in BASIC for the Apple II microcomputer. The advantages and disadvantages of using a microcomputer for local data processing are discussed. Images PMID:7071017

Gene Expression Data to Mouse Atlas Registration Using a Nonlinear Elasticity Smoother and Landmark Points Constraints

PubMed Central

Lin, Tungyou; Guyader, Carole Le; Dinov, Ivo; Thompson, Paul; Toga, Arthur; Vese, Luminita

2013-01-01

This paper proposes a numerical algorithm for image registration using energy minimization and nonlinear elasticity regularization. Application to the registration of gene expression data to a neuroanatomical mouse atlas in two dimensions is shown. We apply a nonlinear elasticity regularization to allow larger and smoother deformations, and further enforce optimality constraints on the landmark points distance for better feature matching. To overcome the difficulty of minimizing the nonlinear elasticity functional due to the nonlinearity in the derivatives of the displacement vector field, we introduce a matrix variable to approximate the Jacobian matrix and solve for the simplified Euler-Lagrange equations. By comparison with image registration using linear regularization, experimental results show that the proposed nonlinear elasticity model also needs fewer numerical corrections such as regridding steps for binary image registration, it renders better ground truth, and produces larger mutual information; most importantly, the landmark points distance and L2 dissimilarity measure between the gene expression data and corresponding mouse atlas are smaller compared with the registration model with biharmonic regularization. PMID:24273381

Micro-/nanoscale multi-field coupling in nonlinear photonic devices

NASA Astrophysics Data System (ADS)

Yang, Qing; Wang, Yubo; Tang, Mingwei; Xu, Pengfei; Xu, Yingke; Liu, Xu

2017-08-01

The coupling of mechanics/electronics/photonics may improve the performance of nanophotonic devices not only in the linear region but also in the nonlinear region. This review letter mainly presents the recent advances on multi-field coupling in nonlinear photonic devices. The nonlinear piezoelectric effect and piezo-phototronic effects in quantum wells and fibers show that large second-order nonlinear susceptibilities can be achieved, and second harmonic generation and electro-optic modulation can be enhanced and modulated. Strain engineering can tune the lattice structures and induce second order susceptibilities in central symmetry semiconductors. By combining the absorption-based photoacoustic effect and intensity-dependent photobleaching effect, subdiffraction imaging can be achieved. This review will also discuss possible future applications of these novel effects and the perspective of their research. The review can help us develop a deeper knowledge of the substance of photon-electron-phonon interaction in a micro-/nano- system. Moreover, it can benefit the design of nonlinear optical sensors and imaging devices with a faster response rate, higher efficiency, more sensitivity and higher spatial resolution which could be applied in environmental detection, bio-sensors, medical imaging and so on.

Comparative ELM study between the observation by ECEI and linear/nonlinear simulation in the KSTAR plasmas

NASA Astrophysics Data System (ADS)

Kim, Minwoo; Park, Hyeon K.; Yun, Gunsu; Lee, Jaehyun; Lee, Jieun; Lee, Woochang; Jardin, Stephen; Xu, X. Q.; Kstar Team

2015-11-01

The modeling of the Edge-localized-mode (ELM) should be rigorously pursued for reliable and robust ELM control for steady-state long-pulse H-mode operation in ITER as well as DEMO. In the KSTAR discharge #7328, a linear stability of the ELMs is investigated using M3D-C1 and BOUT + + codes. This is achieved by linear simulation for the n = 8 mode structure of the ELM observed by the KSTAR electron cyclotron emission imaging (ECEI) systems. In the process of analysis, variations due to the plasma equilibrium profiles and transport coefficients on the ELM growth rate are investigated and simulation results with the two codes are compared. The numerical simulations are extended to nonlinear phase of the ELM dynamics, which includes saturation and crash of the modes. Preliminary results of the nonlinear simulations are compared with the measured images especially from the saturation to the crash. This work is supported by NRF of Korea under contract no. NRF-2014M1A7A1A03029865, US DoE by LLNL under contract DE-AC52-07NA27344 and US DoE by PPPL under contract DE-AC02-09CH11466.

Double-clad photonic crystal fiber coupler for compact nonlinear optical microscopy imaging.

PubMed

Fu, Ling; Gu, Min

2006-05-15

A 1 x 2 double-clad photonic crystal fiber coupler is fabricated by the fused tapered method, showing a low excess loss of 1.1 dB and a splitting ratio of 97/3 over the entire visible and near-infrared wavelength range. In addition to the property of splitting the laser power, the double-clad feature of the coupler facilitates the separation of a near-infrared single-mode beam from a visible multimode beam, which is ideal for nonlinear optical microscopy imaging. In conjunction with a gradient-index lens, this coupler is used to construct a miniaturized microscope based on two-photon fluorescence and second-harmonic generation. Three-dimensional nonlinear optical images demonstrate potential applications of the coupler to compact all-fiber and nonlinear optical microscopy and endoscopy.

Monitoring the process of pulmonary melanoma metastasis using large area and label-free nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Hua, Daozhu; Qi, Shuhong; Li, Hui; Zhang, Zhihong; Fu, Ling

2012-06-01

We performed large area nonlinear optical microscopy (NOM) for label-free monitoring of the process of pulmonary melanoma metastasis ex vivo with subcellular resolution in C57BL/6 mice. Multiphoton autofluorescence (MAF) and second harmonic generation (SHG) images of lung tissue are obtained in a volume of ~2.2 mm×2.2 mm×30 μm. Qualitative differences in morphologic features and quantitative measurement of pathological lung tissues at different time points are characterized. We find that combined with morphological features, the quantitative parameters, such as the intensity ratio of MAF and SHG between pathological tissue and normal tissue and the MAF to SHG index versus depth clearly shows the tissue physiological changes during the process of pulmonary melanoma metastasis. Our results demonstrate that large area NOM succeeds in monitoring the process of pulmonary melanoma metastasis, which can provide a powerful tool for the research in tumor pathophysiology and therapy evaluation.

Acousto-optic laser projection systems for displaying TV information

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gulyaev, Yu V; Kazaryan, M A; Mokrushin, Yu M

2015-04-30

This review addresses various approaches to television projection imaging on large screens using lasers. Results are presented of theoretical and experimental studies of an acousto-optic projection system operating on the principle of projecting an image of an entire amplitude-modulated television line in a single laser pulse. We consider characteristic features of image formation in such a system and the requirements for its individual components. Particular attention is paid to nonlinear distortions of the image signal, which show up most severely at low modulation signal frequencies. We discuss the feasibility of improving the process efficiency and image quality using acousto-optic modulatorsmore » and pulsed lasers. Real-time projectors with pulsed line imaging can be used for controlling high-intensity laser radiation. (review)« less

A Free Database of Auto-detected Full-sun Coronal Hole Maps

NASA Astrophysics Data System (ADS)

Caplan, R. M.; Downs, C.; Linker, J.

2016-12-01

We present a 4-yr (06/10/2010 to 08/18/14 at 6-hr cadence) database of full-sun synchronic EUV and coronal hole (CH) maps made available on a dedicated web site (http://www.predsci.com/chd). The maps are generated using STEREO/EUVI A&B 195Å and SDO/AIA 193Å images through an automated pipeline (Caplan et al, (2016) Ap.J. 823, 53).Specifically, the original data is preprocessed with PSF-deconvolution, a nonlinear limb-brightening correction, and a nonlinear inter-instrument intensity normalization. Coronal holes are then detected in the preprocessed images using a GPU-accelerated region growing segmentation algorithm. The final results from all three instruments are then merged and projected to form full-sun sine-latitude maps. All the software used in processing the maps is provided, which can easily be adapted for use with other instruments and channels. We describe the data pipeline and show examples from the database. We also detail recent CH-detection validation experiments using synthetic EUV emission images produced from global thermodynamic MHD simulations.

A spectral approach for the quantitative description of cardiac collagen network from nonlinear optical imaging.

PubMed

Masè, Michela; Cristoforetti, Alessandro; Avogaro, Laura; Tessarolo, Francesco; Piccoli, Federico; Caola, Iole; Pederzolli, Carlo; Graffigna, Angelo; Ravelli, Flavia

2015-01-01

The assessment of collagen structure in cardiac pathology, such as atrial fibrillation (AF), is essential for a complete understanding of the disease. This paper introduces a novel methodology for the quantitative description of collagen network properties, based on the combination of nonlinear optical microscopy with a spectral approach of image processing and analysis. Second-harmonic generation (SHG) microscopy was applied to atrial tissue samples from cardiac surgery patients, providing label-free, selective visualization of the collagen structure. The spectral analysis framework, based on 2D-FFT, was applied to the SHG images, yielding a multiparametric description of collagen fiber orientation (angle and anisotropy indexes) and texture scale (dominant wavelength and peak dispersion indexes). The proof-of-concept application of the methodology showed the capability of our approach to detect and quantify differences in the structural properties of the collagen network in AF versus sinus rhythm patients. These results suggest the potential of our approach in the assessment of collagen properties in cardiac pathologies related to a fibrotic structural component.

Microscopie non-lineaire pour l'imagerie des cordes vocales

NASA Astrophysics Data System (ADS)

Deterre, Romain

The vocal cords are two folds of epithelial tissues located in the larynx and are involved in production of the human voice. Despite their apparent simplicity, their internal structure is complex. Each fold can be divided into several layers with different mechanical properties. The gold standard for studying their structure - histology - has the inconvenience of being very invasive. Non-linear microscopy is an optical imaging technique which allows images to be taken in depth within samples in a non invasive manner. It also offers intrinsic contrasts, allowing the identification of certain fibrous proteins - elastin and collagen - which are responsible for the mechanical properties of epithelious tissues. The main goal of this research project was to assess nonlinear microscopy's performances for vocal fold imaging. The study has been broken down in two separate tasks. The first one was to evaluate the nonlinear modalities contrast against histology. For that purpose, we chose to first take images of thin samples and compare them to the corresponding histological slides. The second task was to make tests to transcribe the results obtained to in vivo imaging. A custom-built nonlinear imaging system was used for these experiments. It was developed to allow acquisition of wide-field images. A C++ based software was developped to control the microscope and allow treatment and visualization of the images. After being built, the system was further tested to check its performances in comparison with the theoretical limit as described in the literature. Thin slices of vocal folds were obtained from the team of Pr Christopher J. Hartnick from Massachusetts Eye and Ear Infirmary, Harvard Medical School. Specialists from his team analysed the histological samples to extract structural data from the vocal folds. A good correlation was measured between histological and nonlinear data. A first step in evaluating the possibility for translating these results towards in vivo imaging was performed during this project. A swine's larynx was obtained, and vocal folds were extracted for imaging purposes. This experiment showed that it is indeed possible to localize various macrostructures of the tissues with nonlinear microscopy.

Nonlinear Programming shallow tomography improves deep structure imaging

NASA Astrophysics Data System (ADS)

Li, J.; Morozov, I.

2004-05-01

In areas with strong variations in topography or near-surface lithology, conventional seismic data processing methods do not produce clear images, neither shallow nor deep. The conventional reflection data processing methods do not resolve stacking velocities at very shallow depth; however, refraction tomography can be used to obtain the near-surface velocities. We use Nonlinear Programming (NP) via known velocity and depth in points from shallow boreholes and outcrop as well as derivation of slowness as constraint conditions to gain accurate shallow velocities. We apply this method to a 2D reflection survey shot across the Flame Mountain, a typical mountain with high gas reserve volume in Western China, by PetroChina and BGP in 1990s. The area has a highly rugged topography with strong variations of lithology near the surface. Over its hillside, the quality of reflection data is very good, but on the mountain ridge, reflection quality is poorer. Because of strong noise, only the first breaks are clear in the records, with velocities varying by more than 3 times in the near offsets. Because this region contains a steep cliff and an overthrust fold, it is very difficult to find a standard refraction horizon, therefore, GLI refractive statics conventional field and residual statics do not result in a good image. Our processing approach includes: 1) The Herglotz-Wiechert method to derive a starting velocity model which is better than horizontal velocity model; 2) using shallow boreholes and geological data, construct smoothness constraints on the velocity field as well as; 3) perform tomographic velocity inversion by NP algorithm; 4) by using the resulting accurate shallow velocities, derive the statics to correct the seismic data for the complex near-surface velocity variations. The result indicates that shallow refraction tomography can greatly improve deep seismic images in complex surface conditions.

MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, G; Pan, X; Stayman, J

2014-06-15

Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within themore » reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical applications. Learning Objectives: Learn the general methodologies associated with model-based 3D image reconstruction. Learn the potential advantages in image quality and dose associated with model-based image reconstruction. Learn the challenges associated with computational load and image quality assessment for such reconstruction methods. Learn how imaging task can be incorporated as a means to drive optimal image acquisition and reconstruction techniques. Learn how model-based reconstruction methods can incorporate prior information to improve image quality, ease sampling requirements, and reduce dose.« less

Method and System for Temporal Filtering in Video Compression Systems

NASA Technical Reports Server (NTRS)

Lu, Ligang; He, Drake; Jagmohan, Ashish; Sheinin, Vadim

2011-01-01

Three related innovations combine improved non-linear motion estimation, video coding, and video compression. The first system comprises a method in which side information is generated using an adaptive, non-linear motion model. This method enables extrapolating and interpolating a visual signal, including determining the first motion vector between the first pixel position in a first image to a second pixel position in a second image; determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image; determining a third motion vector between the first pixel position in the first image and the second pixel position in the second image, the second pixel position in the second image, and the third pixel position in the third image using a non-linear model; and determining a position of the fourth pixel in a fourth image based upon the third motion vector. For the video compression element, the video encoder has low computational complexity and high compression efficiency. The disclosed system comprises a video encoder and a decoder. The encoder converts the source frame into a space-frequency representation, estimates the conditional statistics of at least one vector of space-frequency coefficients with similar frequencies, and is conditioned on previously encoded data. It estimates an encoding rate based on the conditional statistics and applies a Slepian-Wolf code with the computed encoding rate. The method for decoding includes generating a side-information vector of frequency coefficients based on previously decoded source data and encoder statistics and previous reconstructions of the source frequency vector. It also performs Slepian-Wolf decoding of a source frequency vector based on the generated side-information and the Slepian-Wolf code bits. The video coding element includes receiving a first reference frame having a first pixel value at a first pixel position, a second reference frame having a second pixel value at a second pixel position, and a third reference frame having a third pixel value at a third pixel position. It determines a first motion vector between the first pixel position and the second pixel position, a second motion vector between the second pixel position and the third pixel position, and a fourth pixel value for a fourth frame based upon a linear or nonlinear combination of the first pixel value, the second pixel value, and the third pixel value. A stationary filtering process determines the estimated pixel values. The parameters of the filter may be predetermined constants.

Scene Analysis: Non-Linear Spatial Filtering for Automatic Target Detection.

DTIC Science & Technology

1982-12-01

In this thesis, a method for two-dimensional pattern recognition was developed and tested. The method included a global search scheme for candidate...test global switch TYPEO Creating negative video file only.W 11=0 12=256 13=512 14=768 GO 70 2 1 TYPE" Creating negative and horizontally flipped video...purpose was to develop a base of image processing software for the AFIT Digital Signal Processing Laboratory NOVA- ECLIPSE minicomputer system, for

Multi-crack imaging using nonclassical nonlinear acoustic method

NASA Astrophysics Data System (ADS)

Zhang, Lue; Zhang, Ying; Liu, Xiao-Zhou; Gong, Xiu-Fen

2014-10-01

Solid materials with cracks exhibit the nonclassical nonlinear acoustical behavior. The micro-defects in solid materials can be detected by nonlinear elastic wave spectroscopy (NEWS) method with a time-reversal (TR) mirror. While defects lie in viscoelastic solid material with different distances from one another, the nonlinear and hysteretic stress—strain relation is established with Preisach—Mayergoyz (PM) model in crack zone. Pulse inversion (PI) and TR methods are used in numerical simulation and defect locations can be determined from images obtained by the maximum value. Since false-positive defects might appear and degrade the imaging when the defects are located quite closely, the maximum value imaging with a time window is introduced to analyze how defects affect each other and how the fake one occurs. Furthermore, NEWS-TR-NEWS method is put forward to improve NEWS-TR scheme, with another forward propagation (NEWS) added to the existing phases (NEWS and TR). In the added phase, scanner locations are determined by locations of all defects imaged in previous phases, so that whether an imaged defect is real can be deduced. NEWS-TR-NEWS method is proved to be effective to distinguish real defects from the false-positive ones. Moreover, it is also helpful to detect the crack that is weaker than others during imaging procedure.

Rational Variety Mapping for Contrast-Enhanced Nonlinear Unsupervised Segmentation of Multispectral Images of Unstained Specimen

PubMed Central

Kopriva, Ivica; Hadžija, Mirko; Popović Hadžija, Marijana; Korolija, Marina; Cichocki, Andrzej

2011-01-01

A methodology is proposed for nonlinear contrast-enhanced unsupervised segmentation of multispectral (color) microscopy images of principally unstained specimens. The methodology exploits spectral diversity and spatial sparseness to find anatomical differences between materials (cells, nuclei, and background) present in the image. It consists of rth-order rational variety mapping (RVM) followed by matrix/tensor factorization. Sparseness constraint implies duality between nonlinear unsupervised segmentation and multiclass pattern assignment problems. Classes not linearly separable in the original input space become separable with high probability in the higher-dimensional mapped space. Hence, RVM mapping has two advantages: it takes implicitly into account nonlinearities present in the image (ie, they are not required to be known) and it increases spectral diversity (ie, contrast) between materials, due to increased dimensionality of the mapped space. This is expected to improve performance of systems for automated classification and analysis of microscopic histopathological images. The methodology was validated using RVM of the second and third orders of the experimental multispectral microscopy images of unstained sciatic nerve fibers (nervus ischiadicus) and of unstained white pulp in the spleen tissue, compared with a manually defined ground truth labeled by two trained pathophysiologists. The methodology can also be useful for additional contrast enhancement of images of stained specimens. PMID:21708116

Demonstration of Nonlinearity Bias in the Measurement of the Apparent Diffusion Coefficient in Multicenter Trials

PubMed Central

Malyarenko, Dariya; Newitt, David; Wilmes, Lisa; Tudorica, Alina; Helmer, Karl G.; Arlinghaus, Lori R.; Jacobs, Michael A.; Jajamovich, Guido; Taouli, Bachir; Yankeelov, Thomas E.; Huang, Wei; Chenevert, Thomas L.

2015-01-01

Purpose Characterize system-specific bias across common magnetic resonance imaging (MRI) platforms for quantitative diffusion measurements in multicenter trials. Methods Diffusion weighted imaging (DWI) was performed on an ice-water phantom along the superior-inferior (SI) and right-left (RL) orientations spanning ±150 mm. The same scanning protocol was implemented on 14 MRI systems at seven imaging centers. The bias was estimated as a deviation of measured from known apparent diffusion coefficient (ADC) along individual DWI directions. The relative contributions of gradient nonlinearity, shim errors, imaging gradients and eddy currents were assessed independently. The observed bias errors were compared to numerical models. Results The measured systematic ADC errors scaled quadratically with offset from isocenter, and ranged between −55% (SI) and 25% (RL). Nonlinearity bias was dependent on system design and diffusion gradient direction. Consistent with numerical models, minor ADC errors (±5%) due to shim, imaging and eddy currents were mitigated by double echo DWI and image co-registration of individual gradient directions. Conclusion The analysis confirms gradient nonlinearity as a major source of spatial DW bias and variability in off-center ADC measurements across MRI platforms, with minor contributions from shim, imaging gradients and eddy currents. The developed protocol enables empiric description of systematic bias in multicenter quantitative DWI studies. PMID:25940607

Demonstration of nonlinearity bias in the measurement of the apparent diffusion coefficient in multicenter trials.

PubMed

Malyarenko, Dariya I; Newitt, David; J Wilmes, Lisa; Tudorica, Alina; Helmer, Karl G; Arlinghaus, Lori R; Jacobs, Michael A; Jajamovich, Guido; Taouli, Bachir; Yankeelov, Thomas E; Huang, Wei; Chenevert, Thomas L

2016-03-01

Characterize system-specific bias across common magnetic resonance imaging (MRI) platforms for quantitative diffusion measurements in multicenter trials. Diffusion weighted imaging (DWI) was performed on an ice-water phantom along the superior-inferior (SI) and right-left (RL) orientations spanning ± 150 mm. The same scanning protocol was implemented on 14 MRI systems at seven imaging centers. The bias was estimated as a deviation of measured from known apparent diffusion coefficient (ADC) along individual DWI directions. The relative contributions of gradient nonlinearity, shim errors, imaging gradients, and eddy currents were assessed independently. The observed bias errors were compared with numerical models. The measured systematic ADC errors scaled quadratically with offset from isocenter, and ranged between -55% (SI) and 25% (RL). Nonlinearity bias was dependent on system design and diffusion gradient direction. Consistent with numerical models, minor ADC errors (± 5%) due to shim, imaging and eddy currents were mitigated by double echo DWI and image coregistration of individual gradient directions. The analysis confirms gradient nonlinearity as a major source of spatial DW bias and variability in off-center ADC measurements across MRI platforms, with minor contributions from shim, imaging gradients and eddy currents. The developed protocol enables empiric description of systematic bias in multicenter quantitative DWI studies. © 2015 Wiley Periodicals, Inc.

Analysis of Particle Image Velocimetry (PIV) Data for Acoustic Velocity Measurements

NASA Technical Reports Server (NTRS)

Blackshire, James L.

1997-01-01

Acoustic velocity measurements were taken using Particle Image Velocimetry (PIV) in a Normal Incidence Tube configuration at various frequency, phase, and amplitude levels. This report presents the results of the PIV analysis and data reduction portions of the test and details the processing that was done. Estimates of lower measurement sensitivity levels were determined based on PIV image quality, correlation, and noise level parameters used in the test. Comparison of measurements with linear acoustic theory are presented. The onset of nonlinear, harmonic frequency acoustic levels were also studied for various decibel and frequency levels ranging from 90 to 132 dB and 500 to 3000 Hz, respectively.

Apodized RFI filtering of synthetic aperture radar images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Doerry, Armin Walter

2014-02-01

Fine resolution Synthetic Aperture Radar (SAR) systems necessarily require wide bandwidths that often overlap spectrum utilized by other wireless services. These other emitters pose a source of Radio Frequency Interference (RFI) to the SAR echo signals that degrades SAR image quality. Filtering, or excising, the offending spectral contaminants will mitigate the interference, but at a cost of often degrading the SAR image in other ways, notably by raising offensive sidelobe levels. This report proposes borrowing an idea from nonlinear sidelobe apodization techniques to suppress interference without the attendant increase in sidelobe levels. The simple post-processing technique is termed Apodized RFImore » Filtering (ARF).« less

Exploring lipids with nonlinear optical microscopy in multiple biological systems

NASA Astrophysics Data System (ADS)

Alfonso-Garcia, Alba

Lipids are crucial biomolecules for the well being of humans. Altered lipid metabolism may give rise to a variety of diseases that affect organs from the cardiovascular to the central nervous system. A deeper understanding of lipid metabolic processes would spur medical research towards developing precise diagnostic tools, treatment methods, and preventive strategies for reducing the impact of lipid diseases. Lipid visualization remains a complex task because of the perturbative effect exerted by traditional biochemical assays and most fluorescence markers. Coherent Raman scattering (CRS) microscopy enables interrogation of biological samples with minimum disturbance, and is particularly well suited for label-free visualization of lipids, providing chemical specificity without compromising on spatial resolution. Hyperspectral imaging yields large datasets that benefit from tailored multivariate analysis. In this thesis, CRS microscopy was combined with Raman spectroscopy and other label-free nonlinear optical techniques to analyze lipid metabolism in multiple biological systems. We used nonlinear Raman techniques to characterize Meibum secretions in the progression of dry eye disease, where the lipid and protein contributions change in ratio and phase segregation. We employed similar tools to examine lipid droplets in mice livers aboard a spaceflight mission, which lose their retinol content contributing to the onset of nonalcoholic fatty-liver disease. We also focused on atherosclerosis, a disease that revolves around lipid-rich plaques in arterial walls. We examined the lipid content of macrophages, whose variable phenotype gives rise to contrasting healing and inflammatory activities. We also proposed new label-free markers, based on lifetime imaging, for macrophage phenotype, and to detect products of lipid oxidation. Cholesterol was also detected in hepatitis C virus infected cells, and in specific strains of age-related macular degeneration diseased cells by spontaneous Raman spectroscopy. We used synthesized highly-deuterated cholesterol to track its compartmentalization in adrenal cells, revealing heterogeneous lipid droplet content. These examples illustrate the potential of label-free nonlinear optical microscopy for unveiling complex physiological processes by direct visualization of lipids. Detailed image analysis and combined microscopy modalities will continue to reveal and quantify fundamental biology that will support the advance of biomedicine.

Support Minimized Inversion of Acoustic and Elastic Wave Scattering

NASA Astrophysics Data System (ADS)

Safaeinili, Ali

Inversion of limited data is common in many areas of NDE such as X-ray Computed Tomography (CT), Ultrasonic and eddy current flaw characterization and imaging. In many applications, it is common to have a bias toward a solution with minimum (L^2)^2 norm without any physical justification. When it is a priori known that objects are compact as, say, with cracks and voids, by choosing "Minimum Support" functional instead of the minimum (L^2)^2 norm, an image can be obtained that is equally in agreement with the available data, while it is more consistent with what is most probably seen in the real world. We have utilized a minimum support functional to find a solution with the smallest volume. This inversion algorithm is most successful in reconstructing objects that are compact like voids and cracks. To verify this idea, we first performed a variational nonlinear inversion of acoustic backscatter data using minimum support objective function. A full nonlinear forward model was used to accurately study the effectiveness of the minimized support inversion without error due to the linear (Born) approximation. After successful inversions using a full nonlinear forward model, a linearized acoustic inversion was developed to increase speed and efficiency in imaging process. The results indicate that by using minimum support functional, we can accurately size and characterize voids and/or cracks which otherwise might be uncharacterizable. An extremely important feature of support minimized inversion is its ability to compensate for unknown absolute phase (zero-of-time). Zero-of-time ambiguity is a serious problem in the inversion of the pulse-echo data. The minimum support inversion was successfully used for the inversion of acoustic backscatter data due to compact scatterers without the knowledge of the zero-of-time. The main drawback to this type of inversion is its computer intensiveness. In order to make this type of constrained inversion available for common use, work needs to be performed in three areas: (1) exploitation of state-of-the-art parallel computation, (2) improvement of theoretical formulation of the scattering process for better computation efficiency, and (3) development of better methods for guiding the non-linear inversion. (Abstract shortened by UMI.).

Intravital microscopy: a novel tool to study cell biology in living animals.

PubMed

Weigert, Roberto; Sramkova, Monika; Parente, Laura; Amornphimoltham, Panomwat; Masedunskas, Andrius

2010-05-01

Intravital microscopy encompasses various optical microscopy techniques aimed at visualizing biological processes in live animals. In the last decade, the development of non-linear optical microscopy resulted in an enormous increase of in vivo studies, which have addressed key biological questions in fields such as neurobiology, immunology and tumor biology. Recently, few studies have shown that subcellular processes can be imaged dynamically in the live animal at a resolution comparable to that achieved in cell cultures, providing new opportunities to study cell biology under physiological conditions. The overall aim of this review is to give the reader a general idea of the potential applications of intravital microscopy with a particular emphasis on subcellular imaging. An overview of some of the most exciting studies in this field will be presented using resolution as a main organizing criterion. Indeed, first we will focus on those studies in which organs were imaged at the tissue level, then on those focusing on single cells imaging, and finally on those imaging subcellular organelles and structures.

Multispectral Image Compression for Improvement of Colorimetric and Spectral Reproducibility by Nonlinear Spectral Transform

NASA Astrophysics Data System (ADS)

Yu, Shanshan; Murakami, Yuri; Obi, Takashi; Yamaguchi, Masahiro; Ohyama, Nagaaki

2006-09-01

The article proposes a multispectral image compression scheme using nonlinear spectral transform for better colorimetric and spectral reproducibility. In the method, we show the reduction of colorimetric error under a defined viewing illuminant and also that spectral accuracy can be improved simultaneously using a nonlinear spectral transform called Labplus, which takes into account the nonlinearity of human color vision. Moreover, we show that the addition of diagonal matrices to Labplus can further preserve the spectral accuracy and has a generalized effect of improving the colorimetric accuracy under other viewing illuminants than the defined one. Finally, we discuss the usage of the first-order Markov model to form the analysis vectors for the higher order channels in Labplus to reduce the computational complexity. We implement a multispectral image compression system that integrates Labplus with JPEG2000 for high colorimetric and spectral reproducibility. Experimental results for a 16-band multispectral image show the effectiveness of the proposed scheme.

Nonlinear Talbot Effect and Its Applications

NASA Astrophysics Data System (ADS)

Yang, Zhening

2018-03-01

Talbot effect, a lenless self-imaging phenomenon, was first discovered in 1836 by H.F. Talbot. The conventional Talbott effect has been studied for over a hundred years. Recently, the rapid development of optical superlattices has brought a great breakthrough in Talbot effect research. A nonlinear self-imaging phenomenon was found in the periodically poled LiTaO3 (PPLT) crystals. [1][2][3] This nonlinear Talbot effect has applications not only in optics but also in many other fields. For example, the phenomenon is realized by frequency-doubled beams, which offers people a new way to enhance the spatial resolution of the self-images of periodic objects. And by observing the self-image of the second harmonic (SH) field on the sample surface, people can detect the domain structure in the crystal without damaging the sample. Throughout this review paper, an overview of nonlinear Talbot effect and two applications of this phenomenon is presented. Breakthroughs like achieving a super-focused spot and realizing an acousto-optic tunable SH Talbot illuminator will be introduced as well.

Compact ultrafast semiconductor disk laser for nonlinear imaging in living organisms

NASA Astrophysics Data System (ADS)

Aviles-Espinosa, Rodrigo; Filippidis, G.; Hamilton, Craig; Malcolm, Graeme; Weingarten, Kurt J.; Südmeyer, Thomas; Barbarin, Yohan; Keller, Ursula; Artigas, David; Loza-Alvarez, Pablo

2011-03-01

Ultrashort pulsed laser systems (such as Ti:sapphire) have been used in nonlinear microscopy during the last years. However, its implementation is not straight forward as they are maintenance-intensive, bulky and expensive. These limitations have prevented their wide-spread use for nonlinear imaging, especially in "real-life" biomedical applications. In this work we present the suitability of a compact ultrafast semiconductor disk laser source, with a footprint of 140x240x70 mm, to be used for nonlinear microscopy. The modelocking mechanism of the laser is based on a quantumdot semiconductor saturable absorber mirror (SESAM). The laser delivers an average output power of 287 mW with 1.5 ps pulses at 500 MHz, corresponding to a peak power of 0.4 kW. Its center wavelength is 965 nm which is ideally suited for two-photon excitation of the widely used Green Fluorescent Protein (GFP) marker as it virtually matches its twophoton action cross section. We reveal that it is possible to obtain two photon excited fluorescence images of GFP labeled neurons and secondharmonic generation images of pharynx and body wall muscles in living C. elegans nematodes. Our results demonstrate that this compact laser is well suited for long-term time-lapse imaging of living samples as very low powers provide a bright signal. Importantly this non expensive, turn-key, compact laser system could be used as a platform to develop portable nonlinear bio-imaging devices, facilitating its wide-spread adoption in "real-life" applications.

Dynamic electrical impedance imaging with the interacting multiple model scheme.

PubMed

Kim, Kyung Youn; Kim, Bong Seok; Kim, Min Chan; Kim, Sin; Isaacson, David; Newell, Jonathan C

2005-04-01

In this paper, an effective dynamical EIT imaging scheme is presented for on-line monitoring of the abruptly changing resistivity distribution inside the object, based on the interacting multiple model (IMM) algorithm. The inverse problem is treated as a stochastic nonlinear state estimation problem with the time-varying resistivity (state) being estimated on-line with the aid of the IMM algorithm. In the design of the IMM algorithm multiple models with different process noise covariance are incorporated to reduce the modeling uncertainty. Simulations and phantom experiments are provided to illustrate the proposed algorithm.

Neural image analysis for estimating aerobic and anaerobic decomposition of organic matter based on the example of straw decomposition

NASA Astrophysics Data System (ADS)

Boniecki, P.; Nowakowski, K.; Slosarz, P.; Dach, J.; Pilarski, K.

2012-04-01

The purpose of the project was to identify the degree of organic matter decomposition by means of a neural model based on graphical information derived from image analysis. Empirical data (photographs of compost content at various stages of maturation) were used to generate an optimal neural classifier (Boniecki et al. 2009, Nowakowski et al. 2009). The best classification properties were found in an RBF (Radial Basis Function) artificial neural network, which demonstrates that the process is non-linear.

Resolution enhancement of multichannel microwave imagery from the Nimbus-7 SMMR for maritime rainfall analysis

NASA Technical Reports Server (NTRS)

Olson, W. S.; Yeh, C. L.; Weinman, J. A.; Chin, R. T.

1985-01-01

A restoration of the 37, 21, 18, 10.7, and 6.6 GHz satellite imagery from the scanning multichannel microwave radiometer (SMMR) aboard Nimbus-7 to 22.2 km resolution is attempted using a deconvolution method based upon nonlinear programming. The images are deconvolved with and without the aid of prescribed constraints, which force the processed image to abide by partial a priori knowledge of the high-resolution result. The restored microwave imagery may be utilized to examined the distribution of precipitating liquid water in marine rain systems.

Efficient, nonlinear phase estimation with the nonmodulated pyramid wavefront sensor

NASA Astrophysics Data System (ADS)

Frazin, Richard A.

2018-04-01

The sensitivity of the the pyramid wavefront sensor (PyWFS) has made it a popular choice for astronomical adaptive optics (AAO) systems, and it is at its most sensitive when it is used without modulation of the input beam. In non-modulated mode, the device is highly nonlinear. Hence, all PyWFS implementations on current AAO systems employ modulation to make the device more linear. The upcoming era of 30-m class telescopes and the demand for ultra-precise wavefront control stemming from science objectives that include direct imaging of exoplanets make using the PyWFS without modulation desirable. This article argues that nonlinear estimation based on Newton's method for nonlinear optimization can be useful for mitigating the effects of nonlinearity in the non-modulated PyWFS. The proposed approach requires all optical modeling to be pre-computed, which has the advantage of avoiding real-time simulations of beam propagation. Further, the required real-time calculations are amenable to massively parallel computation. Numerical experiments simulate a currently operational PyWFS. A singular value analysis shows that the common practice of calculating two "slope" images from the four PyWFS pupil images discards critical information and is unsuitable for the non-modulated PyWFS simulated here. Instead, this article advocates estimators that use the raw pixel values not only from the four geometrical images of the pupil, but from surrounding pixels as well. The simulations indicate that nonlinear estimation can be effective when the Strehl ratio of the input beam is greater than 0.3, and the improvement relative to linear estimation tends to increase at larger Strehl ratios. At Strehl ratios less than about 0.5, the performances of both the nonlinear and linear estimators are relatively insensitive to noise, since they are dominated by nonlinearity error.

Nonlinear air-coupled emission: The signature to reveal and image microdamage in solid materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solodov, Igor; Busse, Gerd

2007-12-17

It is shown that low-frequency elastic vibrations of near-surface planar defects cause high-frequency ultrasonic radiation in surrounding air. The frequency conversion mechanism is concerned with contact nonlinearity of the defect vibrations and provides efficient generation of air-coupled higher-order ultraharmonics, ultrasubharmonics, and combination frequencies. The nonlinear air-coupled ultrasonic emission is applied for location and high-resolution imaging of damage-induced defects in a variety of solid materials.

Ultrasound wave propagation in tissue and scattering from microbubbles for echo particle image velocimetry technique.

PubMed

Mukdadi, Osama; Shandas, Robin

2004-01-01

Nonlinear wave propagation in tissue can be employed for tissue harmonic imaging, ultrasound surgery, and more effective tissue ablation for high intensity focused ultrasound (HIFU). Wave propagation in soft tissue and scattering from microbubbles (ultrasound contrast agents) are modeled to improve detectability, signal-to-noise ratio, and contrast harmonic imaging used for echo particle image velocimetry (Echo-PIV) technique. The wave motion in nonlinear material (tissue) is studied using KZK-type parabolic evolution equation. This model considers ultrasound beam diffraction, attenuation, and tissue nonlinearity. Time-domain numerical model is based on that originally developed by Lee and Hamilton [J. Acoust. Soc. Am 97:906-917 (1995)] for axi-symmetric acoustic field. The initial acoustic waveform emitted from the transducer is assumed to be a broadband wave modulated by Gaussian envelope. Scattering from microbubbles seeded in the blood stream is characterized. Hence, we compute the pressure field impinges the wall of a coated microbubble; the dynamics of oscillating microbubble can be modeled using Rayleigh-Plesset-type equation. Here, the continuity and the radial-momentum equation of encapsulated microbubbles are used to account for the lipid layer surrounding the microbubble. Numerical results show the effects of tissue and microbubble nonlinearities on the propagating pressure wave field. These nonlinearities have a strong influence on the waveform distortion and harmonic generation of the propagating and scattering waves. Results also show that microbubbles have stronger nonlinearity than tissue, and thus improves S/N ratio. These theoretical predictions of wave phenomena provide further understanding of biomedical imaging technique and provide better system design.

A Four-Dimensional Computed Tomography Comparison of Healthy vs. Asthmatic Human Lungs

PubMed Central

Jahani, Nariman; Choi, Sanghun; Choi, Jiwoong; Haghighi, Babak; Hoffman, Eric A.; Comellas, Alejandro P.; Kline, Joel N.; Lin, Ching-Long

2017-01-01

The purpose of this study was to explore new insights in non-linearity, hysteresis and ventilation heterogeneity of asthmatic human lungs using four-dimensional computed tomography (4D-CT) image data acquired during tidal breathing. Volumetric image data were acquired for 5 non-severe and one severe asthmatic volunteers. Besides 4D-CT image data, function residual capacity and total lung capacity image data during breath-hold were acquired for comparison with dynamic scans. Quantitative results were compared with the previously reported analysis of five healthy human lungs. Using an image registration technique, local variables such as regional ventilation and anisotropic deformation index (ADI) were estimated. Regional ventilation characteristics of non-severe asthmatic subjects were similar to those of healthy subjects, but different from the severe asthmatic subject. Lobar airflow fractions were also well correlated between static and dynamic scans (R2 > 0.84). However, local ventilation heterogeneity significantly increased during tidal breathing in both healthy and asthmatic subjects relative to that of breath-hold perhaps because of airway resistance present only in dynamic breathing. ADI was used to quantify non-linearity and hysteresis of lung motion during tidal breathing. Nonlinearity was greater on inhalation than exhalation among all subjects. However, exhalation nonlinearity among asthmatic subjects was greater than healthy subjects and the difference diminished during inhalation. An increase of non-linearity during exhalation in asthmatic subjects accounted for lower hysteresis relative to that of healthy ones. Thus, assessment of nonlinearity differences between healthy and asthmatic lungs during exhalation may provide quantitative metrics for subject identification and outcome assessment of new interventions. PMID:28372795

Nonlinear interferometric vibrational imaging of biological tissue

NASA Astrophysics Data System (ADS)

Jiang, Zhi; Marks, Daniel L.; Geddes, Joseph B., III; Boppart, Stephen A.

2008-02-01

We demonstrate imaging with the technique of nonlinear interferometric vibrational imaging (NIVI). Experimental images using this instrumentation and method have been acquired from both phantom and biological tissues. In our system, coherent anti-Stokes Raman scattering (CARS) signals are detected by spectral interferometry, which is able to fully restore high resolution Raman spectrum on each focal spot of a sample covering multiple Raman bands using broadband pump and Stokes laser beams. Spectral-domain detection has been demonstrated and allows for a significant increase in image acquiring speed, in signal-to-noise, and in interferometric signal stability.

Volumetric three-dimensional intravascular ultrasound visualization using shape-based nonlinear interpolation

PubMed Central

2013-01-01

Background Intravascular ultrasound (IVUS) is a standard imaging modality for identification of plaque formation in the coronary and peripheral arteries. Volumetric three-dimensional (3D) IVUS visualization provides a powerful tool to overcome the limited comprehensive information of 2D IVUS in terms of complex spatial distribution of arterial morphology and acoustic backscatter information. Conventional 3D IVUS techniques provide sub-optimal visualization of arterial morphology or lack acoustic information concerning arterial structure due in part to low quality of image data and the use of pixel-based IVUS image reconstruction algorithms. In the present study, we describe a novel volumetric 3D IVUS reconstruction algorithm to utilize IVUS signal data and a shape-based nonlinear interpolation. Methods We developed an algorithm to convert a series of IVUS signal data into a fully volumetric 3D visualization. Intermediary slices between original 2D IVUS slices were generated utilizing the natural cubic spline interpolation to consider the nonlinearity of both vascular structure geometry and acoustic backscatter in the arterial wall. We evaluated differences in image quality between the conventional pixel-based interpolation and the shape-based nonlinear interpolation methods using both virtual vascular phantom data and in vivo IVUS data of a porcine femoral artery. Volumetric 3D IVUS images of the arterial segment reconstructed using the two interpolation methods were compared. Results In vitro validation and in vivo comparative studies with the conventional pixel-based interpolation method demonstrated more robustness of the shape-based nonlinear interpolation algorithm in determining intermediary 2D IVUS slices. Our shape-based nonlinear interpolation demonstrated improved volumetric 3D visualization of the in vivo arterial structure and more realistic acoustic backscatter distribution compared to the conventional pixel-based interpolation method. Conclusions This novel 3D IVUS visualization strategy has the potential to improve ultrasound imaging of vascular structure information, particularly atheroma determination. Improved volumetric 3D visualization with accurate acoustic backscatter information can help with ultrasound molecular imaging of atheroma component distribution. PMID:23651569

Three dimensional full-wave nonlinear acoustic simulations: Applications to ultrasound imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinton, Gianmarco

Characterization of acoustic waves that propagate nonlinearly in an inhomogeneous medium has significant applications to diagnostic and therapeutic ultrasound. The generation of an ultrasound image of human tissue is based on the complex physics of acoustic wave propagation: diffraction, reflection, scattering, frequency dependent attenuation, and nonlinearity. The nonlinearity of wave propagation is used to the advantage of diagnostic scanners that use the harmonic components of the ultrasonic signal to improve the resolution and penetration of clinical scanners. One approach to simulating ultrasound images is to make approximations that can reduce the physics to systems that have a low computational cost.more » Here a maximalist approach is taken and the full three dimensional wave physics is simulated with finite differences. This paper demonstrates how finite difference simulations for the nonlinear acoustic wave equation can be used to generate physically realistic two and three dimensional ultrasound images anywhere in the body. A specific intercostal liver imaging scenario for two cases: with the ribs in place, and with the ribs removed. This configuration provides an imaging scenario that cannot be performed in vivo but that can test the influence of the ribs on image quality. Several imaging properties are studied, in particular the beamplots, the spatial coherence at the transducer surface, the distributed phase aberration, and the lesion detectability for imaging at the fundamental and harmonic frequencies. The results indicate, counterintuitively, that at the fundamental frequency the beamplot improves due to the apodization effect of the ribs but at the same time there is more degradation from reverberation clutter. At the harmonic frequency there is significantly less improvement in the beamplot and also significantly less degradation from reverberation. It is shown that even though simulating the full propagation physics is computationally challenging it is necessary to quantify ultrasound image quality and its sources of degradation.« less

Air Vehicle Integration and Technology Research (AVIATR). Delivery Order 0013: Nonlinear, Low-Order/Reduced-Order Modeling Applications and Demonstration

DTIC Science & Technology

2011-12-01

image) ................. 114 Figure 156 – Abaqus thermal model attempting to characterize the thermal profile seen in the test data...optimization process ... 118 Figure 159 – Thermal profile for optimized Abaqus thermal solution ....................................... 119 Figure 160 – LVDT...Coefficients of thermal expansion results ................................................................. 121 Table 12 – LVDT correlation results

Interferometric and nonlinear-optical spectral-imaging techniques for outer space and live cells

NASA Astrophysics Data System (ADS)

Itoh, Kazuyoshi

2015-12-01

Multidimensional signals such as the spectral images allow us to have deeper insights into the natures of objects. In this paper the spectral imaging techniques that are based on optical interferometry and nonlinear optics are presented. The interferometric imaging technique is based on the unified theory of Van Cittert-Zernike and Wiener-Khintchine theorems and allows us to retrieve a spectral image of an object in the far zone from the 3D spatial coherence function. The retrieval principle is explained using a very simple object. The promising applications to space interferometers for astronomy that are currently in progress will also be briefly touched on. An interesting extension of interferometric spectral imaging is a 3D and spectral imaging technique that records 4D information of objects where the 3D and spectral information is retrieved from the cross-spectral density function of optical field. The 3D imaging is realized via the numerical inverse propagation of the cross-spectral density. A few techniques suggested recently are introduced. The nonlinear optical technique that utilizes stimulated Raman scattering (SRS) for spectral imaging of biomedical targets is presented lastly. The strong signals of SRS permit us to get vibrational information of molecules in the live cell or tissue in real time. The vibrational information of unstained or unlabeled molecules is crucial especially for medical applications. The 3D information due to the optical nonlinearity is also the attractive feature of SRS spectral microscopy.

An approach to analyze the breast tissues in infrared images using nonlinear adaptive level sets and Riesz transform features.

PubMed

Prabha, S; Suganthi, S S; Sujatha, C M

2015-01-01

Breast thermography is a potential imaging method for the early detection of breast cancer. The pathological conditions can be determined by measuring temperature variations in the abnormal breast regions. Accurate delineation of breast tissues is reported as a challenging task due to inherent limitations of infrared images such as low contrast, low signal to noise ratio and absence of clear edges. Segmentation technique is attempted to delineate the breast tissues by detecting proper lower breast boundaries and inframammary folds. Characteristic features are extracted to analyze the asymmetrical thermal variations in normal and abnormal breast tissues. An automated analysis of thermal variations of breast tissues is attempted using nonlinear adaptive level sets and Riesz transform. Breast thermal images are initially subjected to Stein's unbiased risk estimate based orthonormal wavelet denoising. These denoised images are enhanced using contrast-limited adaptive histogram equalization method. The breast tissues are then segmented using non-linear adaptive level set method. The phase map of enhanced image is integrated into the level set framework for final boundary estimation. The segmented results are validated against the corresponding ground truth images using overlap and regional similarity metrics. The segmented images are further processed with Riesz transform and structural texture features are derived from the transformed coefficients to analyze pathological conditions of breast tissues. Results show that the estimated average signal to noise ratio of denoised images and average sharpness of enhanced images are improved by 38% and 6% respectively. The interscale consideration adopted in the denoising algorithm is able to improve signal to noise ratio by preserving edges. The proposed segmentation framework could delineate the breast tissues with high degree of correlation (97%) between the segmented and ground truth areas. Also, the average segmentation accuracy and sensitivity are found to be 98%. Similarly, the maximum regional overlap between segmented and ground truth images obtained using volume similarity measure is observed to be 99%. Directionality as a feature, showed a considerable difference between normal and abnormal tissues which is found to be 11%. The proposed framework for breast thermal image analysis that is aided with necessary preprocessing is found to be useful in assisting the early diagnosis of breast abnormalities.

A MULTICORE BASED PARALLEL IMAGE REGISTRATION METHOD

PubMed Central

Yang, Lin; Gong, Leiguang; Zhang, Hong; Nosher, John L.; Foran, David J.

2012-01-01

Image registration is a crucial step for many image-assisted clinical applications such as surgery planning and treatment evaluation. In this paper we proposed a landmark based nonlinear image registration algorithm for matching 2D image pairs. The algorithm was shown to be effective and robust under conditions of large deformations. In landmark based registration, the most important step is establishing the correspondence among the selected landmark points. This usually requires an extensive search which is often computationally expensive. We introduced a nonregular data partition algorithm using the K-means clustering algorithm to group the landmarks based on the number of available processing cores. The step optimizes the memory usage and data transfer. We have tested our method using IBM Cell Broadband Engine (Cell/B.E.) platform. PMID:19964921

Optical authentication based on moiré effect of nonlinear gratings in phase space

NASA Astrophysics Data System (ADS)

Liao, Meihua; He, Wenqi; Wu, Jiachen; Lu, Dajiang; Liu, Xiaoli; Peng, Xiang

2015-12-01

An optical authentication scheme based on the moiré effect of nonlinear gratings in phase space is proposed. According to the phase function relationship of the moiré effect in phase space, an arbitrary authentication image can be encoded into two nonlinear gratings which serve as the authentication lock (AL) and the authentication key (AK). The AL is stored in the authentication system while the AK is assigned to the authorized user. The authentication procedure can be performed using an optoelectronic approach, while the design process is accomplished by a digital approach. Furthermore, this optical authentication scheme can be extended for multiple users with different security levels. The proposed scheme can not only verify the legality of a user identity, but can also discriminate and control the security levels of legal users. Theoretical analysis and simulation experiments are provided to verify the feasibility and effectiveness of the proposed scheme.

Wavefront optimized nonlinear microscopy of ex vivo human retinas

NASA Astrophysics Data System (ADS)

Gualda, Emilio J.; Bueno, Juan M.; Artal, Pablo

2010-03-01

A multiphoton microscope incorporating a Hartmann-Shack (HS) wavefront sensor to control the ultrafast laser beam's wavefront aberrations has been developed. This instrument allowed us to investigate the impact of the laser beam aberrations on two-photon autofluorescence imaging of human retinal tissues. We demonstrated that nonlinear microscopy images are improved when laser beam aberrations are minimized by realigning the laser system cavity while wavefront controlling. Nonlinear signals from several human retinal anatomical features have been detected for the first time, without the need of fixation or staining procedures. Beyond the improved image quality, this approach reduces the required excitation power levels, minimizing the side effects of phototoxicity within the imaged sample. In particular, this may be important to study the physiology and function of the healthy and diseased retina.

Meteor tracking via local pattern clustering in spatio-temporal domain

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

2016-09-01

Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

Second harmonic generation imaging of the collagen in myocardium for atrial fibrillation diagnosis

NASA Astrophysics Data System (ADS)

Tsai, Ming-Rung; Chiou, Yu-We; Sun, Chi-Kuang

2009-02-01

Myocardial fibrosis, a common sequela of cardiac hypertrophy, has been shown to be associated with arrhythmias in experimental models. Some research has indicated that myocardial fibrosis plays an important role in predisposing patients to atrial fibrillation. Second harmonic generation (SHG) is an optically nonlinear coherent process to image the collagen network. In this presentation, we observe the SHG images of the collagen matrix in atrial myocardium and we analyzed of collagen fibers arrangement by using Fourier-transform analysis. Moreover, comparing the SHG images of the collagen fibers in atrial myocardium between normal sinus rhythm (NSR) and atrial fibrillation (AF), our result indicated that it is possible to realize the relation between myocardial fibrosis and AF.

The collagen structure of equine articular cartilage characterized using polarization-sensitive optical coherence tomography and non-linear microscopy

NASA Astrophysics Data System (ADS)

Mansfield, Jessica C.; Ugryumova, Nadya; Knapp, Karen M.; Matcher, Stephen J.

2006-09-01

Equine articular cartilage has been imaged using both polarization-sensitive optical coherence tomography (PS-OCT) and non-linear microscopy. PS-OCT has been used to spatially map the birefringence in the cartilage and we have found that in the vicinity of the lesion the images display a characteristic disruption in the regular birefringence bands shown by normal cartilage. We also note that significant (e.g. x2) variations in the apparent birefringence of samples taken from young (18 month) animals that otherwise appear visually homogeneous are found over spatial scales of a few millimeters. We have also imaged the cartilage using non-linear microscopy and compare the scans taken with second harmonic generation (SHG) light and the two photon fluorescence (TPF) light. SHG images collected using 800 nm excitation reveals the spatial distribution of collagen fibers, whilst TPF images clearly shows the distribution of intracellular and pericellular fluorophores.

A Nonlinear Diffusion Equation-Based Model for Ultrasound Speckle Noise Removal

NASA Astrophysics Data System (ADS)

Zhou, Zhenyu; Guo, Zhichang; Zhang, Dazhi; Wu, Boying

2018-04-01

Ultrasound images are contaminated by speckle noise, which brings difficulties in further image analysis and clinical diagnosis. In this paper, we address this problem in the view of nonlinear diffusion equation theories. We develop a nonlinear diffusion equation-based model by taking into account not only the gradient information of the image, but also the information of the gray levels of the image. By utilizing the region indicator as the variable exponent, we can adaptively control the diffusion type which alternates between the Perona-Malik diffusion and the Charbonnier diffusion according to the image gray levels. Furthermore, we analyze the proposed model with respect to the theoretical and numerical properties. Experiments show that the proposed method achieves much better speckle suppression and edge preservation when compared with the traditional despeckling methods, especially in the low gray level and low-contrast regions.

Assessment of fibrotic liver disease with multimodal nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Lu, Fake; Zheng, Wei; Tai, Dean C. S.; Lin, Jian; Yu, Hanry; Huang, Zhiwei

2010-02-01

Liver fibrosis is the excessive accumulation of extracellular matrix proteins such as collagens, which may result in cirrhosis, liver failure, and portal hypertension. In this study, we apply a multimodal nonlinear optical microscopy platform developed to investigate the fibrotic liver diseases in rat models established by performing bile duct ligation (BDL) surgery. The three nonlinear microscopy imaging modalities are implemented on the same sectioned tissues of diseased model sequentially: i.e., second harmonic generation (SHG) imaging quantifies the contents of the collagens, the two-photon excitation fluorescence (TPEF) imaging reveals the morphology of hepatic cells, while coherent anti-Stokes Raman scattering (CARS) imaging maps the distributions of fats or lipids quantitatively across the tissue. Our imaging results show that during the development of liver fibrosis (collagens) in BDL model, fatty liver disease also occurs. The aggregated concentrations of collagen and fat constituents in liver fibrosis model show a certain correlationship between each other.

On use of image quality metrics for perceptual blur modeling: image/video compression case

NASA Astrophysics Data System (ADS)

Cha, Jae H.; Olson, Jeffrey T.; Preece, Bradley L.; Espinola, Richard L.; Abbott, A. Lynn

2018-02-01

Linear system theory is employed to make target acquisition performance predictions for electro-optical/infrared imaging systems where the modulation transfer function (MTF) may be imposed from a nonlinear degradation process. Previous research relying on image quality metrics (IQM) methods, which heuristically estimate perceived MTF has supported that an average perceived MTF can be used to model some types of degradation such as image compression. Here, we discuss the validity of the IQM approach by mathematically analyzing the associated heuristics from the perspective of reliability, robustness, and tractability. Experiments with standard images compressed by x.264 encoding suggest that the compression degradation can be estimated by a perceived MTF within boundaries defined by well-behaved curves with marginal error. Our results confirm that the IQM linearizer methodology provides a credible tool for sensor performance modeling.

All-optical image processing with nonlinear liquid crystals

NASA Astrophysics Data System (ADS)

Hong, Kuan-Lun

Liquid crystals are fascinating materials because of several advantages such as large optical birefringence, dielectric anisotropic, and easily compatible to most kinds of materials. Compared to the electro-optical properties of liquid crystals widely applied in displays and switching application, transparency through most parts of wavelengths also makes liquid crystals a better candidate for all-optical processing. The fast response time of liquid crystals resulting from multiple nonlinear effects, such as thermal and density effect can even make real-time processing realized. In addition, blue phase liquid crystals with spontaneously self-assembled three dimensional cubic structures attracted academic attention. In my dissertation, I will divide the whole contents into six parts. In Chapter 1, a brief introduction of liquid crystals is presented, including the current progress and the classification of liquid crystals. Anisotropy and laser induced director axis reorientation is presented in Chapter 2. In Chapter 3, I will solve the electrostrictive coupled equation and analyze the laser induced thermal and density effect in both static and dynamic ways. Furthermore, a dynamic simulation of laser induced density fluctuation is proposed by applying finite element method. In Chapter 4, two image processing setups are presented. One is the intensity inversion experiment in which intensity dependent phase modulation is the mechanism. The other is the wavelength conversion experiment in which I can read the invisible image with a visible probe beam. Both experiments are accompanied with simulations to realize the matching between the theories and practical experiment results. In Chapter 5, optical properties of blue phase liquid crystals will be introduced and discussed. The results of grating diffractions and thermal refractive index gradient are presented in this chapter. In addition, fiber arrays imaging and switching with BPLCs will be included in this chapter. Finally, I will give a brief summary and mention a few future researches in Chapter 6.

Non-invasive breast biopsy method using GD-DTPA contrast enhanced MRI series and F-18-FDG PET/CT dynamic image series

NASA Astrophysics Data System (ADS)

Magri, Alphonso William

This study was undertaken to develop a nonsurgical breast biopsy from Gd-DTPA Contrast Enhanced Magnetic Resonance (CE-MR) images and F-18-FDG PET/CT dynamic image series. A five-step process was developed to accomplish this. (1) Dynamic PET series were nonrigidly registered to the initial frame using a finite element method (FEM) based registration that requires fiducial skin markers to sample the displacement field between image frames. A commercial FEM package (ANSYS) was used for meshing and FEM calculations. Dynamic PET image series registrations were evaluated using similarity measurements SAVD and NCC. (2) Dynamic CE-MR series were nonrigidly registered to the initial frame using two registration methods: a multi-resolution free-form deformation (FFD) registration driven by normalized mutual information, and a FEM-based registration method. Dynamic CE-MR image series registrations were evaluated using similarity measurements, localization measurements, and qualitative comparison of motion artifacts. FFD registration was found to be superior to FEM-based registration. (3) Nonlinear curve fitting was performed for each voxel of the PET/CT volume of activity versus time, based on a realistic two-compartmental Patlak model. Three parameters for this model were fitted; two of them describe the activity levels in the blood and in the cellular compartment, while the third characterizes the washout rate of F-18-FDG from the cellular compartment. (4) Nonlinear curve fitting was performed for each voxel of the MR volume of signal intensity versus time, based on a realistic two-compartment Brix model. Three parameters for this model were fitted: rate of Gd exiting the compartment, representing the extracellular space of a lesion; rate of Gd exiting a blood compartment; and a parameter that characterizes the strength of signal intensities. Curve fitting used for PET/CT and MR series was accomplished by application of the Levenburg-Marquardt nonlinear regression algorithm. The best-fit parameters were used to create 3D parametric images. Compartmental modeling evaluation was based on the ability of parameter values to differentiate between tissue types. This evaluation was used on registered and unregistered image series and found that registration improved results. (5) PET and MR parametric images were registered through FEM- and FFD-based registration. Parametric image registration was evaluated using similarity measurements, target registration error, and qualitative comparison. Comparing FFD and FEM-based registration results showed that the FEM method is superior. This five-step process constitutes a novel multifaceted approach to a nonsurgical breast biopsy that successfully executes each step. Comparison of this method to biopsy still needs to be done with a larger set of subject data.

Investigation of radio astronomy image processing techniques for use in the passive millimetre-wave security screening environment

NASA Astrophysics Data System (ADS)

Taylor, Christopher T.; Hutchinson, Simon; Salmon, Neil A.; Wilkinson, Peter N.; Cameron, Colin D.

2014-06-01

Image processing techniques can be used to improve the cost-effectiveness of future interferometric Passive MilliMetre Wave (PMMW) imagers. The implementation of such techniques will allow for a reduction in the number of collecting elements whilst ensuring adequate image fidelity is maintained. Various techniques have been developed by the radio astronomy community to enhance the imaging capability of sparse interferometric arrays. The most prominent are Multi- Frequency Synthesis (MFS) and non-linear deconvolution algorithms, such as the Maximum Entropy Method (MEM) and variations of the CLEAN algorithm. This investigation focuses on the implementation of these methods in the defacto standard for radio astronomy image processing, the Common Astronomy Software Applications (CASA) package, building upon the discussion presented in Taylor et al., SPIE 8362-0F. We describe the image conversion process into a CASA suitable format, followed by a series of simulations that exploit the highlighted deconvolution and MFS algorithms assuming far-field imagery. The primary target application used for this investigation is an outdoor security scanner for soft-sided Heavy Goods Vehicles. A quantitative analysis of the effectiveness of the aforementioned image processing techniques is presented, with thoughts on the potential cost-savings such an approach could yield. Consideration is also given to how the implementation of these techniques in CASA might be adapted to operate in a near-field target environment. This may enable a much wider usability by the imaging community outside of radio astronomy and thus would be directly relevant to portal screening security systems in the microwave and millimetre wave bands.

Rational variety mapping for contrast-enhanced nonlinear unsupervised segmentation of multispectral images of unstained specimen.

PubMed

Kopriva, Ivica; Hadžija, Mirko; Popović Hadžija, Marijana; Korolija, Marina; Cichocki, Andrzej

2011-08-01

A methodology is proposed for nonlinear contrast-enhanced unsupervised segmentation of multispectral (color) microscopy images of principally unstained specimens. The methodology exploits spectral diversity and spatial sparseness to find anatomical differences between materials (cells, nuclei, and background) present in the image. It consists of rth-order rational variety mapping (RVM) followed by matrix/tensor factorization. Sparseness constraint implies duality between nonlinear unsupervised segmentation and multiclass pattern assignment problems. Classes not linearly separable in the original input space become separable with high probability in the higher-dimensional mapped space. Hence, RVM mapping has two advantages: it takes implicitly into account nonlinearities present in the image (ie, they are not required to be known) and it increases spectral diversity (ie, contrast) between materials, due to increased dimensionality of the mapped space. This is expected to improve performance of systems for automated classification and analysis of microscopic histopathological images. The methodology was validated using RVM of the second and third orders of the experimental multispectral microscopy images of unstained sciatic nerve fibers (nervus ischiadicus) and of unstained white pulp in the spleen tissue, compared with a manually defined ground truth labeled by two trained pathophysiologists. The methodology can also be useful for additional contrast enhancement of images of stained specimens. Copyright © 2011 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Multimodal nonlinear microscopy of biopsy specimen: towards intraoperative diagnostics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Schmitt, Michael; Heuke, Sandro; Meyer, Tobias; Chernavskaia, Olga; Bocklitz, Thomas W.; Popp, Juergen

2016-03-01

The realization of label-free molecule specific imaging of morphology and chemical composition of tissue at subcellular spatial resolution in real time is crucial for many envisioned applications in medicine, e.g., precise surgical guidance and non-invasive histopathologic examination of tissue. Thus, new approaches for a fast and reliable in vivo and near in vivo (ex corpore in vivo) tissue characterization to supplement routine pathological diagnostics is needed. Spectroscopic imaging approaches are particularly important since they have the potential to provide a pathologist with adequate support in the form of clinically-relevant information under both ex vivo and in vivo conditions. In this contribution it is demonstrated, that multimodal nonlinear microscopy combining coherent anti-Stokes Raman scattering (CARS), two photon excited fluorescence (TPEF) and second harmonic generation (SHG) enables the detection of characteristic structures and the accompanying molecular changes of widespread diseases, particularly of cancer and atherosclerosis. The detailed images enable an objective evaluation of the tissue samples for an early diagnosis of the disease status. Increasing the spectral resolution and analyzing CARS images at multiple Raman resonances improves the chemical specificity. To facilitate handling and interpretation of the image data characteristic properties can be automatically extracted by advanced image processing algorithms, e.g., for tissue classification. Overall, the presented examples show the great potential of multimodal imaging to augment standard intraoperative clinical assessment with functional multimodal CARS/SHG/TPEF images to highlight functional activity and tumor boundaries. It ensures fast, label-free and non-invasive intraoperative tissue classification paving the way towards in vivo optical pathology.

Computer object segmentation by nonlinear image enhancement, multidimensional clustering, and geometrically constrained contour optimization

NASA Astrophysics Data System (ADS)

Bruynooghe, Michel M.

1998-04-01

In this paper, we present a robust method for automatic object detection and delineation in noisy complex images. The proposed procedure is a three stage process that integrates image segmentation by multidimensional pixel clustering and geometrically constrained optimization of deformable contours. The first step is to enhance the original image by nonlinear unsharp masking. The second step is to segment the enhanced image by multidimensional pixel clustering, using our reducible neighborhoods clustering algorithm that has a very interesting theoretical maximal complexity. Then, candidate objects are extracted and initially delineated by an optimized region merging algorithm, that is based on ascendant hierarchical clustering with contiguity constraints and on the maximization of average contour gradients. The third step is to optimize the delineation of previously extracted and initially delineated objects. Deformable object contours have been modeled by cubic splines. An affine invariant has been used to control the undesired formation of cusps and loops. Non linear constrained optimization has been used to maximize the external energy. This avoids the difficult and non reproducible choice of regularization parameters, that are required by classical snake models. The proposed method has been applied successfully to the detection of fine and subtle microcalcifications in X-ray mammographic images, to defect detection by moire image analysis, and to the analysis of microrugosities of thin metallic films. The later implementation of the proposed method on a digital signal processor associated to a vector coprocessor would allow the design of a real-time object detection and delineation system for applications in medical imaging and in industrial computer vision.

Nonlinear optics for the study of human scar tissue

NASA Astrophysics Data System (ADS)

Ferro, D. P.; Vieira-Damiani, G.; Adam, R. L.; Cesar, C. L.; Metze, Konradin

2012-03-01

Collagen fibers are an essential component of the dynamic process of scarring, which accompanies various diseases. Scar tissue may reveal different morphologic expressions, such as hypertrophic scars or keloids. Collagen fibers can be visualized by fluorescent light when stained with eosin. Second Harmonic Generation (SHG) creates a non linear signal that occurs only in molecules without inversion symmetry and is particularly strong in the collagen fibers arranged in triple helices. The aim of this study was to describe the methodology for the analysis of the density and texture of collagen in keloids, hypertrophic scars and conventional scars. Samples were examined in the National Institute of Science and Technology on Photonics Applied to Cell Biology (INFABIC) at the State University of Campinas. The images were acquired in a multiphoton microscopy LSM 780-NLO Zeiss 40X. Both signals, two-photon fluorescence (TPEF) and SHG, were excited by a Mai-Tai Ti:Sapphire laser at 940 nm. We used a LP490/SP485 NDD filter for SHG, and a BP565-610 NDD filter for fluorescence In each case, ten images were acquired serially (512×512 μm) in Z-stack and joined together to one patchwork-image . Image analysis was performed by a gliding-box-system with in-house made software. Keloids, hypertrophic scars and normal scar tissue show different collagen architecture. Inside an individual case differences of the scar process may be found between central and peripheral parts. In summary, the use of nonlinear optics is a helpful tool for the study of scars tissue.

Synchronous-digitization for Video Rate Polarization Modulated Beam Scanning Second Harmonic Generation Microscopy.

PubMed

Sullivan, Shane Z; DeWalt, Emma L; Schmitt, Paul D; Muir, Ryan M; Simpson, Garth J

2015-03-09

Fast beam-scanning non-linear optical microscopy, coupled with fast (8 MHz) polarization modulation and analytical modeling have enabled simultaneous nonlinear optical Stokes ellipsometry (NOSE) and linear Stokes ellipsometry imaging at video rate (15 Hz). NOSE enables recovery of the complex-valued Jones tensor that describes the polarization-dependent observables, in contrast to polarimetry, in which the polarization stated of the exciting beam is recorded. Each data acquisition consists of 30 images (10 for each detector, with three detectors operating in parallel), each of which corresponds to polarization-dependent results. Processing of this image set by linear fitting contracts down each set of 10 images to a set of 5 parameters for each detector in second harmonic generation (SHG) and three parameters for the transmittance of the fundamental laser beam. Using these parameters, it is possible to recover the Jones tensor elements of the sample at video rate. Video rate imaging is enabled by performing synchronous digitization (SD), in which a PCIe digital oscilloscope card is synchronized to the laser (the laser is the master clock.) Fast polarization modulation was achieved by modulating an electro-optic modulator synchronously with the laser and digitizer, with a simple sine-wave at 1/10th the period of the laser, producing a repeating pattern of 10 polarization states. This approach was validated using Z-cut quartz, and NOSE microscopy was performed for micro-crystals of naproxen.

Synchronous-digitization for video rate polarization modulated beam scanning second harmonic generation microscopy

NASA Astrophysics Data System (ADS)

Sullivan, Shane Z.; DeWalt, Emma L.; Schmitt, Paul D.; Muir, Ryan D.; Simpson, Garth J.

2015-03-01

Fast beam-scanning non-linear optical microscopy, coupled with fast (8 MHz) polarization modulation and analytical modeling have enabled simultaneous nonlinear optical Stokes ellipsometry (NOSE) and linear Stokes ellipsometry imaging at video rate (15 Hz). NOSE enables recovery of the complex-valued Jones tensor that describes the polarization-dependent observables, in contrast to polarimetry, in which the polarization stated of the exciting beam is recorded. Each data acquisition consists of 30 images (10 for each detector, with three detectors operating in parallel), each of which corresponds to polarization-dependent results. Processing of this image set by linear fitting contracts down each set of 10 images to a set of 5 parameters for each detector in second harmonic generation (SHG) and three parameters for the transmittance of the fundamental laser beam. Using these parameters, it is possible to recover the Jones tensor elements of the sample at video rate. Video rate imaging is enabled by performing synchronous digitization (SD), in which a PCIe digital oscilloscope card is synchronized to the laser (the laser is the master clock.) Fast polarization modulation was achieved by modulating an electro-optic modulator synchronously with the laser and digitizer, with a simple sine-wave at 1/10th the period of the laser, producing a repeating pattern of 10 polarization states. This approach was validated using Z-cut quartz, and NOSE microscopy was performed for micro-crystals of naproxen.

Reduction of Radiometric Miscalibration—Applications to Pushbroom Sensors

PubMed Central

Rogaß, Christian; Spengler, Daniel; Bochow, Mathias; Segl, Karl; Lausch, Angela; Doktor, Daniel; Roessner, Sigrid; Behling, Robert; Wetzel, Hans-Ulrich; Kaufmann, Hermann

2011-01-01

The analysis of hyperspectral images is an important task in Remote Sensing. Foregoing radiometric calibration results in the assignment of incident electromagnetic radiation to digital numbers and reduces the striping caused by slightly different responses of the pixel detectors. However, due to uncertainties in the calibration some striping remains. This publication presents a new reduction framework that efficiently reduces linear and nonlinear miscalibrations by an image-driven, radiometric recalibration and rescaling. The proposed framework—Reduction Of Miscalibration Effects (ROME)—considering spectral and spatial probability distributions, is constrained by specific minimisation and maximisation principles and incorporates image processing techniques such as Minkowski metrics and convolution. To objectively evaluate the performance of the new approach, the technique was applied to a variety of commonly used image examples and to one simulated and miscalibrated EnMAP (Environmental Mapping and Analysis Program) scene. Other examples consist of miscalibrated AISA/Eagle VNIR (Visible and Near Infrared) and Hawk SWIR (Short Wave Infrared) scenes of rural areas of the region Fichtwald in Germany and Hyperion scenes of the Jalal-Abad district in Southern Kyrgyzstan. Recovery rates of approximately 97% for linear and approximately 94% for nonlinear miscalibrated data were achieved, clearly demonstrating the benefits of the new approach and its potential for broad applicability to miscalibrated pushbroom sensor data. PMID:22163960

Nonlinear spectral imaging of biological tissues

NASA Astrophysics Data System (ADS)

Palero, J. A.

2007-07-01

The work presented in this thesis demonstrates live high resolution 3D imaging of tissue in its native state and environment. The nonlinear interaction between focussed femtosecond light pulses and the biological tissue results in the emission of natural autofluorescence and second-harmonic signal. Because biological intrinsic emission is generally very weak and extends from the ultraviolet to the visible spectral range, a broad-spectral range and high sensitivity 3D spectral imaging system is developed. Imaging the spectral characteristics of the biological intrinsic emission reveals the structure and biochemistry of the cells and extra-cellular components. By using different methods in visualizing the spectral images, discrimination between different tissue structures is achieved without the use of any stain or fluorescent label. For instance, RGB real color spectral images of the intrinsic emission of mouse skin tissues show blue cells, green hair follicles, and purple collagen fibers. The color signature of each tissue component is directly related to its characteristic emission spectrum. The results of this study show that skin tissue nonlinear intrinsic emission is mainly due to the autofluorescence of reduced nicotinamide adenine dinucleotide (phosphate), flavins, keratin, melanin, phospholipids, elastin and collagen and nonlinear Raman scattering and second-harmonic generation in Type I collagen. In vivo time-lapse spectral imaging is implemented to study metabolic changes in epidermal cells in tissues. Optical scattering in tissues, a key factor in determining the maximum achievable imaging depth, is also investigated in this work.

A physiology-based parametric imaging method for FDG-PET data

NASA Astrophysics Data System (ADS)

Scussolini, Mara; Garbarino, Sara; Sambuceti, Gianmario; Caviglia, Giacomo; Piana, Michele

2017-12-01

Parametric imaging is a compartmental approach that processes nuclear imaging data to estimate the spatial distribution of the kinetic parameters governing tracer flow. The present paper proposes a novel and efficient computational method for parametric imaging which is potentially applicable to several compartmental models of diverse complexity and which is effective in the determination of the parametric maps of all kinetic coefficients. We consider applications to [18 F]-fluorodeoxyglucose positron emission tomography (FDG-PET) data and analyze the two-compartment catenary model describing the standard FDG metabolization by an homogeneous tissue and the three-compartment non-catenary model representing the renal physiology. We show uniqueness theorems for both models. The proposed imaging method starts from the reconstructed FDG-PET images of tracer concentration and preliminarily applies image processing algorithms for noise reduction and image segmentation. The optimization procedure solves pixel-wise the non-linear inverse problem of determining the kinetic parameters from dynamic concentration data through a regularized Gauss-Newton iterative algorithm. The reliability of the method is validated against synthetic data, for the two-compartment system, and experimental real data of murine models, for the renal three-compartment system.

Method and system for non-linear motion estimation

NASA Technical Reports Server (NTRS)

Lu, Ligang (Inventor)

2011-01-01

A method and system for extrapolating and interpolating a visual signal including determining a first motion vector between a first pixel position in a first image to a second pixel position in a second image, determining a second motion vector between the second pixel position in the second image and a third pixel position in a third image, determining a third motion vector between one of the first pixel position in the first image and the second pixel position in the second image, and the second pixel position in the second image and the third pixel position in the third image using a non-linear model, determining a position of the fourth pixel in a fourth image based upon the third motion vector.

The heritability of the functional connectome is robust to common nonlinear registration methods

NASA Astrophysics Data System (ADS)

Hafzalla, George W.; Prasad, Gautam; Baboyan, Vatche G.; Faskowitz, Joshua; Jahanshad, Neda; McMahon, Katie L.; de Zubicaray, Greig I.; Wright, Margaret J.; Braskie, Meredith N.; Thompson, Paul M.

2016-03-01

Nonlinear registration algorithms are routinely used in brain imaging, to align data for inter-subject and group comparisons, and for voxelwise statistical analyses. To understand how the choice of registration method affects maps of functional brain connectivity in a sample of 611 twins, we evaluated three popular nonlinear registration methods: Advanced Normalization Tools (ANTs), Automatic Registration Toolbox (ART), and FMRIB's Nonlinear Image Registration Tool (FNIRT). Using both structural and functional MRI, we used each of the three methods to align the MNI152 brain template, and 80 regions of interest (ROIs), to each subject's T1-weighted (T1w) anatomical image. We then transformed each subject's ROIs onto the associated resting state functional MRI (rs-fMRI) scans and computed a connectivity network or functional connectome for each subject. Given the different degrees of genetic similarity between pairs of monozygotic (MZ) and same-sex dizygotic (DZ) twins, we used structural equation modeling to estimate the additive genetic influences on the elements of the function networks, or their heritability. The functional connectome and derived statistics were relatively robust to nonlinear registration effects.

Compensation for the signal processing characteristics of ultrasound B-mode scanners in adaptive speckle reduction.

PubMed

Crawford, D C; Bell, D S; Bamber, J C

1993-01-01

A systematic method to compensate for nonlinear amplification of individual ultrasound B-scanners has been investigated in order to optimise performance of an adaptive speckle reduction (ASR) filter for a wide range of clinical ultrasonic imaging equipment. Three potential methods have been investigated: (1) a method involving an appropriate selection of the speckle recognition feature was successful when the scanner signal processing executes simple logarithmic compressions; (2) an inverse transform (decompression) of the B-mode image was effective in correcting for the measured characteristics of image data compression when the algorithm was implemented in full floating point arithmetic; (3) characterising the behaviour of the statistical speckle recognition feature under conditions of speckle noise was found to be the method of choice for implementation of the adaptive speckle reduction algorithm in limited precision integer arithmetic. In this example, the statistical features of variance and mean were investigated. The third method may be implemented on commercially available fast image processing hardware and is also better suited for transfer into dedicated hardware to facilitate real-time adaptive speckle reduction. A systematic method is described for obtaining ASR calibration data from B-mode images of a speckle producing phantom.

Super-Resolution for “Jilin-1” Satellite Video Imagery via a Convolutional Network

PubMed Central

Wang, Zhongyuan; Wang, Lei; Ren, Yexian

2018-01-01

Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method’s practicality. Experimental results on “Jilin-1” satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods. PMID:29652838

Super-Resolution for "Jilin-1" Satellite Video Imagery via a Convolutional Network.

PubMed

Xiao, Aoran; Wang, Zhongyuan; Wang, Lei; Ren, Yexian

2018-04-13

Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method's practicality. Experimental results on "Jilin-1" satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

Multidimensionally encoded magnetic resonance imaging.

PubMed

Lin, Fa-Hsuan

2013-07-01

Magnetic resonance imaging (MRI) typically achieves spatial encoding by measuring the projection of a q-dimensional object over q-dimensional spatial bases created by linear spatial encoding magnetic fields (SEMs). Recently, imaging strategies using nonlinear SEMs have demonstrated potential advantages for reconstructing images with higher spatiotemporal resolution and reducing peripheral nerve stimulation. In practice, nonlinear SEMs and linear SEMs can be used jointly to further improve the image reconstruction performance. Here, we propose the multidimensionally encoded (MDE) MRI to map a q-dimensional object onto a p-dimensional encoding space where p > q. MDE MRI is a theoretical framework linking imaging strategies using linear and nonlinear SEMs. Using a system of eight surface SEM coils with an eight-channel radiofrequency coil array, we demonstrate the five-dimensional MDE MRI for a two-dimensional object as a further generalization of PatLoc imaging and O-space imaging. We also present a method of optimizing spatial bases in MDE MRI. Results show that MDE MRI with a higher dimensional encoding space can reconstruct images more efficiently and with a smaller reconstruction error when the k-space sampling distribution and the number of samples are controlled. Copyright © 2012 Wiley Periodicals, Inc.

System and method for generating micro-seismic events and characterizing properties of a medium with non-linear acoustic interactions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vu, Cung Khac; Nihei, Kurt; Johnson, Paul A.

2015-12-29

A method and system includes generating a first coded acoustic signal including pulses each having a modulated signal at a central frequency; and a second coded acoustic signal each pulse of which includes a modulated signal a central frequency of which is a fraction d of the central frequency of the modulated signal for the corresponding pulse in the first plurality of pulses. A receiver detects a third signal generated by a non-linear mixing process in the mixing zone and the signal is processed to extract the third signal to obtain an emulated micro-seismic event signal occurring at the mixingmore » zone; and to characterize properties of the medium or creating a 3D image of the properties of the medium, or both, based on the emulated micro-seismic event signal.« less

A spectral water index based on visual bands

NASA Astrophysics Data System (ADS)

Basaeed, Essa; Bhaskar, Harish; Al-Mualla, Mohammed

2013-10-01

Land-water segmentation is an important preprocessing step in a number of remote sensing applications such as target detection, environmental monitoring, and map updating. A Normalized Optical Water Index (NOWI) is proposed to accurately discriminate between land and water regions in multi-spectral satellite imagery data from DubaiSat-1. NOWI exploits the spectral characteristics of water content (using visible bands) and uses a non-linear normalization procedure that renders strong emphasize on small changes in lower brightness values whilst guaranteeing that the segmentation process remains image-independent. The NOWI representation is validated through systematic experiments, evaluated using robust metrics, and compared against various supervised classification algorithms. Analysis has indicated that NOWI has the advantages that it: a) is a pixel-based method that requires no global knowledge of the scene under investigation, b) can be easily implemented in parallel processing, c) is image-independent and requires no training, d) works in different environmental conditions, e) provides high accuracy and efficiency, and f) works directly on the input image without any form of pre-processing.

Non-Uniformly Sampled MR Correlated Spectroscopic Imaging in Breast Cancer and Nonlinear Reconstruction

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-16-1-0524 TITLE: Non-Uniformly Sampled MR Correlated Spectroscopic Imaging in Breast Cancer and Nonlinear Reconstruction...author(s) and should not be construed as an official Department of the Army position, policy or decision unless so designated by other...COVERED 30 Sep 2016 - 29 Sep 2017 5a. CONTRACT NUMBER 4. TITLE AND SUBTITLE Non-Uniformly Sampled MR Correlated Spectroscopic Imaging in Breast

Holographic Associative Memory Employing Phase Conjugation

NASA Astrophysics Data System (ADS)

Soffer, B. H.; Marom, E.; Owechko, Y.; Dunning, G.

1986-12-01

The principle of information retrieval by association has been suggested as a basis for parallel computing and as the process by which human memory functions.1 Various associative processors have been proposed that use electronic or optical means. Optical schemes,2-7 in particular, those based on holographic principles,8'8' are well suited to associative processing because of their high parallelism and information throughput. Previous workers8 demonstrated that holographically stored images can be recalled by using relatively complicated reference images but did not utilize nonlinear feedback to reduce the large cross talk that results when multiple objects are stored and a partial or distorted input is used for retrieval. These earlier approaches were limited in their ability to reconstruct the output object faithfully from a partial input.

Joint image encryption and compression scheme based on IWT and SPIHT

NASA Astrophysics Data System (ADS)

Zhang, Miao; Tong, Xiaojun

2017-03-01

A joint lossless image encryption and compression scheme based on integer wavelet transform (IWT) and set partitioning in hierarchical trees (SPIHT) is proposed to achieve lossless image encryption and compression simultaneously. Making use of the properties of IWT and SPIHT, encryption and compression are combined. Moreover, the proposed secure set partitioning in hierarchical trees (SSPIHT) via the addition of encryption in the SPIHT coding process has no effect on compression performance. A hyper-chaotic system, nonlinear inverse operation, Secure Hash Algorithm-256(SHA-256), and plaintext-based keystream are all used to enhance the security. The test results indicate that the proposed methods have high security and good lossless compression performance.

Ocular-following responses to white noise stimuli in humans reveal a novel nonlinearity that results from temporal sampling

PubMed Central

Sheliga, Boris M.; Quaia, Christian; FitzGibbon, Edmond J.; Cumming, Bruce G.

2016-01-01

White noise stimuli are frequently used to study the visual processing of broadband images in the laboratory. A common goal is to describe how responses are derived from Fourier components in the image. We investigated this issue by recording the ocular-following responses (OFRs) to white noise stimuli in human subjects. For a given speed we compared OFRs to unfiltered white noise with those to noise filtered with band-pass filters and notch filters. Removing components with low spatial frequency (SF) reduced OFR magnitudes, and the SF associated with the greatest reduction matched the SF that produced the maximal response when presented alone. This reduction declined rapidly with SF, compatible with a winner-take-all operation. Removing higher SF components increased OFR magnitudes. For higher speeds this effect became larger and propagated toward lower SFs. All of these effects were quantitatively well described by a model that combined two factors: (a) an excitatory drive that reflected the OFRs to individual Fourier components and (b) a suppression by higher SF channels where the temporal sampling of the display led to flicker. This nonlinear interaction has an important practical implication: Even with high refresh rates (150 Hz), the temporal sampling introduced by visual displays has a significant impact on visual processing. For instance, we show that this distorts speed tuning curves, shifting the peak to lower speeds. Careful attention to spectral content, in the light of this nonlinearity, is necessary to minimize the resulting artifact when using white noise patterns undergoing apparent motion. PMID:26762277

Invited Review Article: Imaging techniques for harmonic and multiphoton absorption fluorescence microscopy

PubMed Central

Carriles, Ramón; Schafer, Dawn N.; Sheetz, Kraig E.; Field, Jeffrey J.; Cisek, Richard; Barzda, Virginijus; Sylvester, Anne W.; Squier, Jeffrey A.

2009-01-01

We review the current state of multiphoton microscopy. In particular, the requirements and limitations associated with high-speed multiphoton imaging are considered. A description of the different scanning technologies such as line scan, multifoci approaches, multidepth microscopy, and novel detection techniques is given. The main nonlinear optical contrast mechanisms employed in microscopy are reviewed, namely, multiphoton excitation fluorescence, second harmonic generation, and third harmonic generation. Techniques for optimizing these nonlinear mechanisms through a careful measurement of the spatial and temporal characteristics of the focal volume are discussed, and a brief summary of photobleaching effects is provided. Finally, we consider three new applications of multiphoton microscopy: nonlinear imaging in microfluidics as applied to chemical analysis and the use of two-photon absorption and self-phase modulation as contrast mechanisms applied to imaging problems in the medical sciences. PMID:19725639

Pump-probe nonlinear phase dispersion spectroscopy.

PubMed

Robles, Francisco E; Samineni, Prathyush; Wilson, Jesse W; Warren, Warren S

2013-04-22

Pump-probe microscopy is an imaging technique that delivers molecular contrast of pigmented samples. Here, we introduce pump-probe nonlinear phase dispersion spectroscopy (PP-NLDS), a method that leverages pump-probe microscopy and spectral-domain interferometry to ascertain information from dispersive and resonant nonlinear effects. PP-NLDS extends the information content to four dimensions (phase, amplitude, wavelength, and pump-probe time-delay) that yield unique insight into a wider range of nonlinear interactions compared to conventional methods. This results in the ability to provide highly specific molecular contrast of pigmented and non-pigmented samples. A theoretical framework is described, and experimental results and simulations illustrate the potential of this method. Implications for biomedical imaging are discussed.

Pump-probe nonlinear phase dispersion spectroscopy

PubMed Central

Robles, Francisco E.; Samineni, Prathyush; Wilson, Jesse W.; Warren, Warren S.

2013-01-01

Pump-probe microscopy is an imaging technique that delivers molecular contrast of pigmented samples. Here, we introduce pump-probe nonlinear phase dispersion spectroscopy (PP-NLDS), a method that leverages pump-probe microscopy and spectral-domain interferometry to ascertain information from dispersive and resonant nonlinear effects. PP-NLDS extends the information content to four dimensions (phase, amplitude, wavelength, and pump-probe time-delay) that yield unique insight into a wider range of nonlinear interactions compared to conventional methods. This results in the ability to provide highly specific molecular contrast of pigmented and non-pigmented samples. A theoretical framework is described, and experimental results and simulations illustrate the potential of this method. Implications for biomedical imaging are discussed. PMID:23609646

Landsat-8 Operational Land Imager (OLI) radiometric performance on-orbit

USGS Publications Warehouse

Morfitt, Ron; Barsi, Julia A.; Levy, Raviv; Markham, Brian L.; Micijevic, Esad; Ong, Lawrence; Scaramuzza, Pat; Vanderwerff, Kelly

2015-01-01

Expectations of the Operational Land Imager (OLI) radiometric performance onboard Landsat-8 have been met or exceeded. The calibration activities that occurred prior to launch provided calibration parameters that enabled ground processing to produce imagery that met most requirements when data were transmitted to the ground. Since launch, calibration updates have improved the image quality even more, so that all requirements are met. These updates range from detector gain coefficients to reduce striping and banding to alignment parameters to improve the geometric accuracy. This paper concentrates on the on-orbit radiometric performance of the OLI, excepting the radiometric calibration performance. Topics discussed in this paper include: signal-to-noise ratios that are an order of magnitude higher than previous Landsat missions; radiometric uniformity that shows little residual banding and striping, and continues to improve; a dynamic range that limits saturation to extremely high radiance levels; extremely stable detectors; slight nonlinearity that is corrected in ground processing; detectors that are stable and 100% operable; and few image artifacts.

Achieving superresolution with illumination-enhanced sparsity.

PubMed

Yu, Jiun-Yann; Becker, Stephen R; Folberth, James; Wallin, Bruce F; Chen, Simeng; Cogswell, Carol J

2018-04-16

Recent advances in superresolution fluorescence microscopy have been limited by a belief that surpassing two-fold resolution enhancement of the Rayleigh resolution limit requires stimulated emission or the fluorophore to undergo state transitions. Here we demonstrate a new superresolution method that requires only image acquisitions with a focused illumination spot and computational post-processing. The proposed method utilizes the focused illumination spot to effectively reduce the object size and enhance the object sparsity and consequently increases the resolution and accuracy through nonlinear image post-processing. This method clearly resolves 70nm resolution test objects emitting ~530nm light with a 1.4 numerical aperture (NA) objective, and, when imaging through a 0.5NA objective, exhibits high spatial frequencies comparable to a 1.4NA widefield image, both demonstrating a resolution enhancement above two-fold of the Rayleigh resolution limit. More importantly, we examine how the resolution increases with photon numbers, and show that the more-than-two-fold enhancement is achievable with realistic photon budgets.

Photocontrollable Fluorescent Proteins for Superresolution Imaging

PubMed Central

Shcherbakova, Daria M.; Sengupta, Prabuddha; Lippincott-Schwartz, Jennifer; Verkhusha, Vladislav V.

2014-01-01

Superresolution fluorescence microscopy permits the study of biological processes at scales small enough to visualize fine subcellular structures that are unresolvable by traditional diffraction-limited light microscopy. Many superresolution techniques, including those applicable to live cell imaging, utilize genetically encoded photocontrollable fluorescent proteins. The fluorescence of these proteins can be controlled by light of specific wavelengths. In this review, we discuss the biochemical and photophysical properties of photocontrollable fluorescent proteins that are relevant to their use in superresolution microscopy. We then describe the recently developed photoactivatable, photoswitchable, and reversibly photoswitchable fluorescent proteins, and we detail their particular usefulness in single-molecule localization–based and nonlinear ensemble–based superresolution techniques. Finally, we discuss recent applications of photocontrollable proteins in superresolution imaging, as well as how these applications help to clarify properties of intracellular structures and processes that are relevant to cell and developmental biology, neuroscience, cancer biology and biomedicine. PMID:24895855

Classification of hyperspectral imagery using MapReduce on a NVIDIA graphics processing unit (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ramirez, Andres; Rahnemoonfar, Maryam

2017-04-01

A hyperspectral image provides multidimensional figure rich in data consisting of hundreds of spectral dimensions. Analyzing the spectral and spatial information of such image with linear and non-linear algorithms will result in high computational time. In order to overcome this problem, this research presents a system using a MapReduce-Graphics Processing Unit (GPU) model that can help analyzing a hyperspectral image through the usage of parallel hardware and a parallel programming model, which will be simpler to handle compared to other low-level parallel programming models. Additionally, Hadoop was used as an open-source version of the MapReduce parallel programming model. This research compared classification accuracy results and timing results between the Hadoop and GPU system and tested it against the following test cases: the CPU and GPU test case, a CPU test case and a test case where no dimensional reduction was applied.

Three-Dimensional Unstained Live-Cell Imaging Using Stimulated Parametric Emission Microscopy

NASA Astrophysics Data System (ADS)

Dang, Hieu M.; Kawasumi, Takehito; Omura, Gen; Umano, Toshiyuki; Kajiyama, Shin'ichiro; Ozeki, Yasuyuki; Itoh, Kazuyoshi; Fukui, Kiichi

2009-09-01

The ability to perform high-resolution unstained live imaging is very important to in vivo study of cell structures and functions. Stimulated parametric emission (SPE) microscopy is a nonlinear-optical microscopy based on ultra-fast electronic nonlinear-optical responses. For the first time, we have successfully applied this technique to archive three-dimensional (3D) images of unstained sub-cellular structures, such as, microtubules, nuclei, nucleoli, etc. in live cells. Observation of a complete cell division confirms the ability of SPE microscopy for long time-scale imaging.

Imaging of normal and pathologic joint synovium using nonlinear optical microscopy as a potential diagnostic tool

NASA Astrophysics Data System (ADS)

Tiwari, Nivedan; Chabra, Sanjay; Mehdi, Sheherbano; Sweet, Paula; Krasieva, Tatiana B.; Pool, Roy; Andrews, Brian; Peavy, George M.

2010-09-01

An estimated 1.3 million people in the United States suffer from rheumatoid arthritis (RA). RA causes profound changes in the synovial membrane of joints, and without early diagnosis and intervention, progresses to permanent alterations in joint structure and function. The purpose of this study is to determine if nonlinear optical microscopy (NLOM) can utilize the natural intrinsic fluorescence properties of tissue to generate images that would allow visualization of the structural and cellular composition of fresh, unfixed normal and pathologic synovial tissue. NLOM is performed on rabbit knee joint synovial samples using 730- and 800-nm excitation wavelengths. Less than 30 mW of excitation power delivered with a 40×, 0.8-NA water immersion objective is sufficient for the visualization of synovial structures to a maximum depth of 70 μm without tissue damage. NLOM imaging of normal and pathologic synovial tissue reveals the cellular structure, synoviocytes, adipocytes, collagen, vascular structures, and differential characteristics of inflammatory infiltrates without requiring tissue processing or staining. Further study to evaluate the ability of NLOM to assess the characteristics of pathologic synovial tissue and its potential role for the management of disease is warranted.

Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

2013-09-01

We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

Processing of CT sinograms acquired using a VRX detector

NASA Astrophysics Data System (ADS)

Jordan, Lawrence M.; DiBianca, Frank A.; Zou, Ping; Laughter, Joseph S.; Zeman, Herbert D.

2000-04-01

A 'variable resolution x-ray detector' (VRX) capable of resolving beyond 100 cycles/main a single dimension has been proposed by DiBianca, et al. The use of detectors of this design for computed-tomography (CT) imaging requires novel preprocessing of data to correct for the detector's non- uniform imaging characteristics over its range of view. This paper describes algorithms developed specifically to adjust VRX data for varying magnification, source-to-detector range and beam obliquity and to sharpen reconstructions by deconvolving the ray impulse function. The preprocessing also incorporates nonlinear interpolation of VRX raw data into canonical CT sinogram formats.

Multi-pose facial correction based on Gaussian process with combined kernel function

NASA Astrophysics Data System (ADS)

Shi, Shuyan; Ji, Ruirui; Zhang, Fan

2018-04-01

In order to improve the recognition rate of various postures, this paper proposes a method of facial correction based on Gaussian Process which build a nonlinear regression model between the front and the side face with combined kernel function. The face images with horizontal angle from -45° to +45° can be properly corrected to front faces. Finally, Support Vector Machine is employed for face recognition. Experiments on CAS PEAL R1 face database show that Gaussian process can weaken the influence of pose changes and improve the accuracy of face recognition to certain extent.

Comparison of mechanisms involved in image enhancement of Tissue Harmonic Imaging

NASA Astrophysics Data System (ADS)

Cleveland, Robin O.; Jing, Yuan

2006-05-01

Processes that have been suggested as responsible for the improved imaging in Tissue Harmonic Imaging (THI) include: 1) reduced sensitivity to reverberation, 2) reduced sensitivity to aberration, and 3) reduction in the amplitude of diffraction side lobes. A three-dimensional model of the forward propagation of nonlinear sound beams in media with arbitrary spatial properties (a generalized KZK equation) was developed and solved using a time-domain code. The numerical simulations were validated through experiments with tissue mimicking phantoms. The impact of aberration from tissue-like media was determined through simulations using three-dimensional maps of tissue properties derived from datasets available through the Visible Female Project. The experiments and simulations demonstrated that second harmonic imaging suffers less clutter from reverberation and side-lobes but is not immune to aberration effects. The results indicate that side lobe suppression is the most significant reason for the improvement of second harmonic imaging.

Supervised local error estimation for nonlinear image registration using convolutional neural networks

NASA Astrophysics Data System (ADS)

Eppenhof, Koen A. J.; Pluim, Josien P. W.

2017-02-01

Error estimation in medical image registration is valuable when validating, comparing, or combining registration methods. To validate a nonlinear image registration method, ideally the registration error should be known for the entire image domain. We propose a supervised method for the estimation of a registration error map for nonlinear image registration. The method is based on a convolutional neural network that estimates the norm of the residual deformation from patches around each pixel in two registered images. This norm is interpreted as the registration error, and is defined for every pixel in the image domain. The network is trained using a set of artificially deformed images. Each training example is a pair of images: the original image, and a random deformation of that image. No manually labeled ground truth error is required. At test time, only the two registered images are required as input. We train and validate the network on registrations in a set of 2D digital subtraction angiography sequences, such that errors up to eight pixels can be estimated. We show that for this range of errors the convolutional network is able to learn the registration error in pairs of 2D registered images at subpixel precision. Finally, we present a proof of principle for the extension to 3D registration problems in chest CTs, showing that the method has the potential to estimate errors in 3D registration problems.

Extended arrays for nonlinear susceptibility magnitude imaging

PubMed Central

Ficko, Bradley W.; Giacometti, Paolo; Diamond, Solomon G.

2016-01-01

This study implements nonlinear susceptibility magnitude imaging (SMI) with multifrequency intermodulation and phase encoding. An imaging grid was constructed of cylindrical wells of 3.5-mm diameter and 4.2-mm height on a hexagonal two-dimensional 61-voxel pattern with 5-mm spacing. Patterns of sample wells were filled with 40-μl volumes of Fe3O4 starch-coated magnetic nanoparticles (mNPs) with a hydrodynamic diameter of 100 nm and a concentration of 25 mg/ml. The imaging hardware was configured with three excitation coils and three detection coils in anticipation that a larger imaging system will have arrays of excitation and detection coils. Hexagonal and bar patterns of mNP were successfully imaged (R2 > 0.9) at several orientations. This SMI demonstration extends our prior work to feature a larger coil array, enlarged field-of-view, effective phase encoding scheme, reduced mNP sample size, and more complex imaging patterns to test the feasibility of extending the method beyond the pilot scale. The results presented in this study show that nonlinear SMI holds promise for further development into a practical imaging system for medical applications. PMID:26124044

Efficient, nonlinear phase estimation with the nonmodulated pyramid wavefront sensor.

PubMed

Frazin, Richard A

2018-04-01

The sensitivity of the pyramid wavefront sensor (PyWFS) has made it a popular choice for astronomical adaptive optics (AAO) systems. The PyWFS is at its most sensitive when it is used without modulation of the input beam. In nonmodulated mode, the device is highly nonlinear. Hence, all PyWFS implementations on current AAO systems employ modulation to make the device more linear. The upcoming era of 30-m class telescopes and the demand for ultra-precise wavefront control stemming from science objectives that include direct imaging of exoplanets make using the PyWFS without modulation desirable. This article argues that nonlinear estimation based on Newton's method for nonlinear optimization can be useful for mitigating the effects of nonlinearity in the nonmodulated PyWFS. The proposed approach requires all optical modeling to be pre-computed, which has the advantage of avoiding real-time simulations of beam propagation. Further, the required real-time calculations are amenable to massively parallel computation. Numerical experiments simulate a PyWFS with faces sloped 3.7° to the horizontal, operating at a wavelength of 0.85 μm, and with an index of refraction of 1.45. A singular value analysis shows that the common practice of calculating two "slope" images from the four PyWFS pupil images discards critical information and is unsuitable for the nonmodulated PyWFS simulated here. Instead, this article advocates estimators that use the raw pixel values not only from the four geometrical images of the pupil, but from surrounding pixels as well. The simulations indicate that nonlinear estimation can be effective when the Strehl ratio of the input beam is greater than 0.3, and the improvement relative to linear estimation tends to increase at larger Strehl ratios. At Strehl ratios less than about 0.5, the performances of both the nonlinear and linear estimators are relatively insensitive to noise since they are dominated by nonlinearity error.

Dual energy CT: How well can pseudo-monochromatic imaging reduce metal artifacts?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuchenbecker, Stefan, E-mail: stefan.kuchenbecker@dkfz.de; Faby, Sebastian; Sawall, Stefan

2015-02-15

Purpose: Dual Energy CT (DECT) provides so-called monoenergetic images based on a linear combination of the original polychromatic images. At certain patient-specific energy levels, corresponding to certain patient- and slice-dependent linear combination weights, e.g., E = 160 keV corresponds to α = 1.57, a significant reduction of metal artifacts may be observed. The authors aimed at analyzing the method for its artifact reduction capabilities to identify its limitations. The results are compared with raw data-based processing. Methods: Clinical DECT uses a simplified version of monochromatic imaging by linearly combining the low and the high kV images and by assigning an energymore » to that linear combination. Those pseudo-monochromatic images can be used by radiologists to obtain images with reduced metal artifacts. The authors analyzed the underlying physics and carried out a series expansion of the polychromatic attenuation equations. The resulting nonlinear terms are responsible for the artifacts, but they are not linearly related between the low and the high kV scan: A linear combination of both images cannot eliminate the nonlinearities, it can only reduce their impact. Scattered radiation yields additional noncanceling nonlinearities. This method is compared to raw data-based artifact correction methods. To quantify the artifact reduction potential of pseudo-monochromatic images, they simulated the FORBILD abdomen phantom with metal implants, and they assessed patient data sets of a clinical dual source CT system (100, 140 kV Sn) containing artifacts induced by a highly concentrated contrast agent bolus and by metal. In each case, they manually selected an optimal α and compared it to a raw data-based material decomposition in case of simulation, to raw data-based material decomposition of inconsistent rays in case of the patient data set containing contrast agent, and to the frequency split normalized metal artifact reduction in case of the metal implant. For each case, the contrast-to-noise ratio (CNR) was assessed. Results: In the simulation, the pseudo-monochromatic images yielded acceptable artifact reduction results. However, the CNR in the artifact-reduced images was more than 60% lower than in the original polychromatic images. In contrast, the raw data-based material decomposition did not significantly reduce the CNR in the virtual monochromatic images. Regarding the patient data with beam hardening artifacts and with metal artifacts from small implants the pseudo-monochromatic method was able to reduce the artifacts, again with the downside of a significant CNR reduction. More intense metal artifacts, e.g., as those caused by an artificial hip joint, could not be suppressed. Conclusions: Pseudo-monochromatic imaging is able to reduce beam hardening, scatter, and metal artifacts in some cases but it cannot remove them. In all cases, the CNR is significantly reduced, thereby rendering the method questionable, unless special post processing algorithms are implemented to restore the high CNR from the original images (e.g., by using a frequency split technique). Raw data-based dual energy decomposition methods should be preferred, in particular, because the CNR penalty is almost negligible.« less

Evaluation of area-based collagen scoring by nonlinear microscopy in chronic hepatitis C-induced liver fibrosis

PubMed Central

Sevrain, David; Dubreuil, Matthieu; Dolman, Grace Elizabeth; Zaitoun, Abed; Irving, William; Guha, Indra Neil; Odin, Christophe; Le Grand, Yann

2015-01-01

In this paper we analyze a fibrosis scoring method based on measurement of the fibrillar collagen area from second harmonic generation (SHG) microscopy images of unstained histological slices from human liver biopsies. The study is conducted on a cohort of one hundred chronic hepatitis C patients with intermediate to strong Metavir and Ishak stages of liver fibrosis. We highlight a key parameter of our scoring method to discriminate between high and low fibrosis stages. Moreover, according to the intensity histograms of the SHG images and simple mathematical arguments, we show that our area-based method is equivalent to an intensity-based method, despite saturation of the images. Finally we propose an improvement of our scoring method using very simple image processing tools. PMID:25909005

Evaluation of area-based collagen scoring by nonlinear microscopy in chronic hepatitis C-induced liver fibrosis.

PubMed

Sevrain, David; Dubreuil, Matthieu; Dolman, Grace Elizabeth; Zaitoun, Abed; Irving, William; Guha, Indra Neil; Odin, Christophe; Le Grand, Yann

2015-04-01

In this paper we analyze a fibrosis scoring method based on measurement of the fibrillar collagen area from second harmonic generation (SHG) microscopy images of unstained histological slices from human liver biopsies. The study is conducted on a cohort of one hundred chronic hepatitis C patients with intermediate to strong Metavir and Ishak stages of liver fibrosis. We highlight a key parameter of our scoring method to discriminate between high and low fibrosis stages. Moreover, according to the intensity histograms of the SHG images and simple mathematical arguments, we show that our area-based method is equivalent to an intensity-based method, despite saturation of the images. Finally we propose an improvement of our scoring method using very simple image processing tools.

3D imaging of hematoxylin and eosin stained thick tissues with a sub-femtoliter resolution by using Cr:forsterite-laser-based nonlinear microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kao, Chien-Ting; Wei, Ming-Liang; Liao, Yi-Hua; Sun, Chi-Kuang

2017-02-01

Intraoperative assessment of excision tissues during cancer surgery is clinically important. The assessment is used to be guided by the examination for residual tumor with frozen pathology, while it is time consuming for preparation and is with low accuracy for diagnosis. Recently, reflection confocal microscopy (RCM) and nonlinear microscopy (NLM) were demonstrated to be promising methods for surgical border assessment. Intraoperative RCM imaging may enable detection of residual tumor directly on skin cancers patients during Mohs surgery. The assessment of benign and malignant breast pathologies in fresh surgical specimens was demonstrated by NLM. Without using hematoxylin and eosin (H and E) that are common dyes for histopathological diagnosis, RCM was proposed to image in vivo by using aluminum chloride for nuclear contrast on surgical wounds directly, while NLM was proposed to detect two photon fluorescence nuclear contrast from acrdine orange staining. In this paper, we propose and demonstrate 3D imaging of H and E stained thick tissues with a sub-femtoliter resolution by using Cr:forsterite-laser-based NLM. With a 1260 nm femtosecond Cr:forsterite laser as the excitation source, the hematoxylin will strongly enhance the third-harmonic generation (THG) signals, while eosin will illuminate strong fluorescence under three photon absorption. Compared with previous works, the 1260 nm excitation light provide high penetration and low photodamage to the exercised tissues so that the possibility to perform other follow-up examination will be preserved. The THG and three-photon process provides high nonlinearity so that the super resolution in 3D is now possible. The staining and the contrast of the imaging is also fully compatible with the current clinical standard on frozen pathology thus facilitate the rapid intraoperative assessment of excision tissues. This work is sponsored by National Health Research Institutes and supported by National Taiwan University Hospital.

Nonlinear metamaterials for holography

PubMed Central

Almeida, Euclides; Bitton, Ora

2016-01-01

A hologram is an optical element storing phase and possibly amplitude information enabling the reconstruction of a three-dimensional image of an object by illumination and scattering of a coherent beam of light, and the image is generated at the same wavelength as the input laser beam. In recent years, it was shown that information can be stored in nanometric antennas giving rise to ultrathin components. Here we demonstrate nonlinear multilayer metamaterial holograms. A background free image is formed at a new frequency—the third harmonic of the illuminating beam. Using e-beam lithography of multilayer plasmonic nanoantennas, we fabricate polarization-sensitive nonlinear elements such as blazed gratings, lenses and other computer-generated holograms. These holograms are analysed and prospects for future device applications are discussed. PMID:27545581

Visible continuum pulses based on enhanced dispersive wave generation for endogenous fluorescence imaging.

PubMed

Cui, Quan; Chen, Zhongyun; Liu, Qian; Zhang, Zhihong; Luo, Qingming; Fu, Ling

2017-09-01

In this study, we demonstrate endogenous fluorescence imaging using visible continuum pulses based on 100-fs Ti:sapphire oscillator and a nonlinear photonic crystal fiber. Broadband (500-700 nm) and high-power (150 mW) continuum pulses are generated through enhanced dispersive wave generation by pumping femtosecond pulses at the anomalous dispersion region near zero-dispersion wavelength of high-nonlinear photonic crystal fibers. We also minimize the continuum pulse width by determining the proper fiber length. The visible-wavelength two-photon microscopy produces NADH and tryptophan images of mice tissues simultaneously. Our 500-700 nm continuum pulses support extending nonlinear microscopy to visible wavelength range that is inaccessible to 100-fs Ti:sapphire oscillators and other applications requiring visible laser pulses.

Medical image processing using neural networks based on multivalued and universal binary neurons

NASA Astrophysics Data System (ADS)

Aizenberg, Igor N.; Aizenberg, Naum N.; Gotko, Eugen S.; Sochka, Vladimir A.

1998-06-01

Cellular Neural Networks (CNN) has become a very good mean for solution of the different kind of image processing problems. CNN based on multi-valued neurons (CNN-MVN) and CNN based on universal binary neurons (CNN-UBN) are the specific kinds of the CNN. MVN and UBN are neurons with complex-valued weights, and complex internal arithmetic. Their main feature is possibility of implementation of the arbitrary mapping between inputs and output described by the MVN, and arbitrary (not only threshold) Boolean function (UBN). Great advantage of the CNN is possibility of implementation of the any linear and many non-linear filters in spatial domain. Together with noise removing using CNN it is possible to implement filters, which can amplify high and medium frequencies. These filters are a very good mean for solution of the enhancement problem, and problem of details extraction against complex background. So, CNN make it possible to organize all the processing process from filtering until extraction of the important details. Organization of this process for medical image processing is considered in the paper. A major attention will be concentrated on the processing of the x-ray and ultrasound images corresponding to different oncology (or closed to oncology) pathologies. Additionally we will consider new structure of the neural network for solution of the problem of differential diagnostics of breast cancer.

On the regularization for nonlinear tomographic absorption spectroscopy

NASA Astrophysics Data System (ADS)

Dai, Jinghang; Yu, Tao; Xu, Lijun; Cai, Weiwei

2018-02-01

Tomographic absorption spectroscopy (TAS) has attracted increased research efforts recently due to the development in both hardware and new imaging concepts such as nonlinear tomography and compressed sensing. Nonlinear TAS is one of the emerging modality that bases on the concept of nonlinear tomography and has been successfully demonstrated both numerically and experimentally. However, all the previous demonstrations were realized using only two orthogonal projections simply for ease of implementation. In this work, we examine the performance of nonlinear TAS using other beam arrangements and test the effectiveness of the beam optimization technique that has been developed for linear TAS. In addition, so far only smoothness prior has been adopted and applied in nonlinear TAS. Nevertheless, there are also other useful priors such as sparseness and model-based prior which have not been investigated yet. This work aims to show how these priors can be implemented and included in the reconstruction process. Regularization through Bayesian formulation will be introduced specifically for this purpose, and a method for the determination of a proper regularization factor will be proposed. The comparative studies performed with different beam arrangements and regularization schemes on a few representative phantoms suggest that the beam optimization method developed for linear TAS also works for the nonlinear counterpart and the regularization scheme should be selected properly according to the available a priori information under specific application scenarios so as to achieve the best reconstruction fidelity. Though this work is conducted under the context of nonlinear TAS, it can also provide useful insights for other tomographic modalities.

Nonlinear image registration with bidirectional metric and reciprocal regularization

PubMed Central

Ying, Shihui; Li, Dan; Xiao, Bin; Peng, Yaxin; Du, Shaoyi; Xu, Meifeng

2017-01-01

Nonlinear registration is an important technique to align two different images and widely applied in medical image analysis. In this paper, we develop a novel nonlinear registration framework based on the diffeomorphic demons, where a reciprocal regularizer is introduced to assume that the deformation between two images is an exact diffeomorphism. In detail, first, we adopt a bidirectional metric to improve the symmetry of the energy functional, whose variables are two reciprocal deformations. Secondly, we slack these two deformations into two independent variables and introduce a reciprocal regularizer to assure the deformations being the exact diffeomorphism. Then, we utilize an alternating iterative strategy to decouple the model into two minimizing subproblems, where a new closed form for the approximate velocity of deformation is calculated. Finally, we compare our proposed algorithm on two data sets of real brain MR images with two relative and conventional methods. The results validate that our proposed method improves accuracy and robustness of registration, as well as the gained bidirectional deformations are actually reciprocal. PMID:28231342

Single Echo MRI

PubMed Central

Galiana, Gigi; Constable, R. Todd

2014-01-01

Purpose Previous nonlinear gradient research has focused on trajectories that reconstruct images with a minimum number of echoes. Here we describe sequences where the nonlinear gradients vary in time to acquire the image in a single readout. The readout is designed to be very smooth so that it can be compressed to minimal time without violating peripheral nerve stimulation limits, yielding an image from a single 4 ms echo. Theory and Methods This sequence was inspired by considering the code of each voxel, i.e. the phase accumulation that a voxel follows through the readout, an approach connected to traditional encoding theory. We present simulations for the initial sequence, a low slew rate analog, and higher resolution reconstructions. Results Extremely fast acquisitions are achievable, though as one would expect, SNR is reduced relative to the slower Cartesian sampling schemes because of the high gradient strengths. Conclusions The prospect that nonlinear gradients can acquire images in a single <10 ms echo makes this a novel and interesting approach to image encoding. PMID:24465837

Method to improve optical parametric oscillator beam quality

DOEpatents

Smith, Arlee V.; Alford, William J.; Bowers, Mark S.

2003-11-11

A method to improving optical parametric oscillator (OPO) beam quality having an optical pump, which generates a pump beam at a pump frequency greater than a desired signal frequency, a nonlinear optical medium oriented so that a signal wave at the desired signal frequency and a corresponding idler wave are produced when the pump beam (wave) propagates through the nonlinear optical medium, resulting in beam walk off of the signal and idler waves, and an optical cavity which directs the signal wave to repeatedly pass through the nonlinear optical medium, said optical cavity comprising an equivalently even number of non-planar mirrors that produce image rotation on each pass through the nonlinear optical medium. Utilizing beam walk off where the signal wave and said idler wave have nonparallel Poynting vectors in the nonlinear medium and image rotation, a correlation zone of distance equal to approximately .rho.L.sub.crystal is created which, through multiple passes through the nonlinear medium, improves the beam quality of the OPO output.

Optical parametric osicllators with improved beam quality

DOEpatents

Smith, Arlee V.; Alford, William J.

2003-11-11

An optical parametric oscillator (OPO) having an optical pump, which generates a pump beam at a pump frequency greater than a desired signal frequency, a nonlinear optical medium oriented so that a signal wave at the desired signal frequency and a corresponding idler wave are produced when the pump beam (wave) propagates through the nonlinear optical medium, resulting in beam walk off of the signal and idler waves, and an optical cavity which directs the signal wave to repeatedly pass through the nonlinear optical medium, said optical cavity comprising an equivalently even number of non-planar mirrors that produce image rotation on each pass through the nonlinear optical medium. Utilizing beam walk off where the signal wave and said idler wave have nonparallel Poynting vectors in the nonlinear medium and image rotation, a correlation zone of distance equal to approximately .rho.L.sub.crystal is created which, through multiple passes through the nonlinear medium, improves the beam quality of the OPO output.

Counter-propagating wave interaction for contrast-enhanced ultrasound imaging

NASA Astrophysics Data System (ADS)

Renaud, G.; Bosch, J. G.; ten Kate, G. L.; Shamdasani, V.; Entrekin, R.; de Jong, N.; van der Steen, A. F. W.

2012-11-01

Most techniques for contrast-enhanced ultrasound imaging require linear propagation to detect nonlinear scattering of contrast agent microbubbles. Waveform distortion due to nonlinear propagation impairs their ability to distinguish microbubbles from tissue. As a result, tissue can be misclassified as microbubbles, and contrast agent concentration can be overestimated; therefore, these artifacts can significantly impair the quality of medical diagnoses. Contrary to biological tissue, lipid-coated gas microbubbles used as a contrast agent allow the interaction of two acoustic waves propagating in opposite directions (counter-propagation). Based on that principle, we describe a strategy to detect microbubbles that is free from nonlinear propagation artifacts. In vitro images were acquired with an ultrasound scanner in a phantom of tissue-mimicking material with a cavity containing a contrast agent. Unlike the default mode of the scanner using amplitude modulation to detect microbubbles, the pulse sequence exploiting counter-propagating wave interaction creates no pseudoenhancement behind the cavity in the contrast image.

Feature-Motivated Simplified Adaptive PCNN-Based Medical Image Fusion Algorithm in NSST Domain.

PubMed

Ganasala, Padma; Kumar, Vinod

2016-02-01

Multimodality medical image fusion plays a vital role in diagnosis, treatment planning, and follow-up studies of various diseases. It provides a composite image containing critical information of source images required for better localization and definition of different organs and lesions. In the state-of-the-art image fusion methods based on nonsubsampled shearlet transform (NSST) and pulse-coupled neural network (PCNN), authors have used normalized coefficient value to motivate the PCNN-processing both low-frequency (LF) and high-frequency (HF) sub-bands. This makes the fused image blurred and decreases its contrast. The main objective of this work is to design an image fusion method that gives the fused image with better contrast, more detail information, and suitable for clinical use. We propose a novel image fusion method utilizing feature-motivated adaptive PCNN in NSST domain for fusion of anatomical images. The basic PCNN model is simplified, and adaptive-linking strength is used. Different features are used to motivate the PCNN-processing LF and HF sub-bands. The proposed method is extended for fusion of functional image with an anatomical image in improved nonlinear intensity hue and saturation (INIHS) color model. Extensive fusion experiments have been performed on CT-MRI and SPECT-MRI datasets. Visual and quantitative analysis of experimental results proved that the proposed method provides satisfactory fusion outcome compared to other image fusion methods.

Epi-detected quadruple-modal nonlinear optical microscopy for label-free imaging of the tooth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Zi; Zheng, Wei; Huang, Zhiwei, E-mail: biehzw@nus.edu.sg

2015-01-19

We present an epi-detected quadruple-modal nonlinear optical microscopic imaging technique (i.e., coherent anti-Stokes Raman scattering (CARS), second-harmonic generation (SHG), third-harmonic generation (THG), and two-photon excited fluorescence (TPEF)) based on a picosecond (ps) laser-pumped optical parametric oscillator system for label-free imaging of the tooth. We demonstrate that high contrast ps-CARS images covering both the fingerprint (500–1800 cm{sup −1}) and high-wavenumber (2500–3800 cm{sup −1}) regions can be acquired to uncover the distributions of mineral and organic biomaterials in the tooth, while high quality TPEF, SHG, and THG images of the tooth can also be acquired under ps laser excitation without damaging the samples. Themore » quadruple-modal nonlinear microscopic images (CARS/SHG/THG/TPEF) acquired provide better understanding of morphological structures and biochemical/biomolecular distributions in the dentin, enamel, and the dentin-enamel junction of the tooth without labeling, facilitating optical diagnosis and characterization of the tooth in dentistry.« less

Multidimensional custom-made non-linear microscope: from ex-vivo to in-vivo imaging

NASA Astrophysics Data System (ADS)

Cicchi, R.; Sacconi, L.; Jasaitis, A.; O'Connor, R. P.; Massi, D.; Sestini, S.; de Giorgi, V.; Lotti, T.; Pavone, F. S.

2008-09-01

We have built a custom-made multidimensional non-linear microscope equipped with a combination of several non-linear laser imaging techniques involving fluorescence lifetime, multispectral two-photon and second-harmonic generation imaging. The optical system was mounted on a vertical honeycomb breadboard in an upright configuration, using two galvo-mirrors relayed by two spherical mirrors as scanners. A double detection system working in non-descanning mode has allowed both photon counting and a proportional regime. This experimental setup offering high spatial (micrometric) and temporal (sub-nanosecond) resolution has been used to image both ex-vivo and in-vivo biological samples, including cells, tissues, and living animals. Multidimensional imaging was used to spectroscopically characterize human skin lesions, as malignant melanoma and naevi. Moreover, two-color detection of two photon excited fluorescence was applied to in-vivo imaging of living mice intact neocortex, as well as to induce neuronal microlesions by femtosecond laser burning. The presented applications demonstrate the capability of the instrument to be used in a wide range of biological and biomedical studies.

Nonlinear secret image sharing scheme.

PubMed

Shin, Sang-Ho; Lee, Gil-Je; Yoo, Kee-Young

2014-01-01

Over the past decade, most of secret image sharing schemes have been proposed by using Shamir's technique. It is based on a linear combination polynomial arithmetic. Although Shamir's technique based secret image sharing schemes are efficient and scalable for various environments, there exists a security threat such as Tompa-Woll attack. Renvall and Ding proposed a new secret sharing technique based on nonlinear combination polynomial arithmetic in order to solve this threat. It is hard to apply to the secret image sharing. In this paper, we propose a (t, n)-threshold nonlinear secret image sharing scheme with steganography concept. In order to achieve a suitable and secure secret image sharing scheme, we adapt a modified LSB embedding technique with XOR Boolean algebra operation, define a new variable m, and change a range of prime p in sharing procedure. In order to evaluate efficiency and security of proposed scheme, we use the embedding capacity and PSNR. As a result of it, average value of PSNR and embedding capacity are 44.78 (dB) and 1.74t⌈log2 m⌉ bit-per-pixel (bpp), respectively.

Nonlinear Secret Image Sharing Scheme

PubMed Central

Shin, Sang-Ho; Yoo, Kee-Young

2014-01-01

Over the past decade, most of secret image sharing schemes have been proposed by using Shamir's technique. It is based on a linear combination polynomial arithmetic. Although Shamir's technique based secret image sharing schemes are efficient and scalable for various environments, there exists a security threat such as Tompa-Woll attack. Renvall and Ding proposed a new secret sharing technique based on nonlinear combination polynomial arithmetic in order to solve this threat. It is hard to apply to the secret image sharing. In this paper, we propose a (t, n)-threshold nonlinear secret image sharing scheme with steganography concept. In order to achieve a suitable and secure secret image sharing scheme, we adapt a modified LSB embedding technique with XOR Boolean algebra operation, define a new variable m, and change a range of prime p in sharing procedure. In order to evaluate efficiency and security of proposed scheme, we use the embedding capacity and PSNR. As a result of it, average value of PSNR and embedding capacity are 44.78 (dB) and 1.74t⌈log2⁡m⌉ bit-per-pixel (bpp), respectively. PMID:25140334

Deep Independence Network Analysis of Structural Brain Imaging: Application to Schizophrenia

PubMed Central

Castro, Eduardo; Hjelm, R. Devon; Plis, Sergey M.; Dinh, Laurent; Turner, Jessica A.; Calhoun, Vince D.

2016-01-01

Linear independent component analysis (ICA) is a standard signal processing technique that has been extensively used on neuroimaging data to detect brain networks with coherent brain activity (functional MRI) or covarying structural patterns (structural MRI). However, its formulation assumes that the measured brain signals are generated by a linear mixture of the underlying brain networks and this assumption limits its ability to detect the inherent nonlinear nature of brain interactions. In this paper, we introduce nonlinear independent component estimation (NICE) to structural MRI data to detect abnormal patterns of gray matter concentration in schizophrenia patients. For this biomedical application, we further addressed the issue of model regularization of nonlinear ICA by performing dimensionality reduction prior to NICE, together with an appropriate control of the complexity of the model and the usage of a proper approximation of the probability distribution functions of the estimated components. We show that our results are consistent with previous findings in the literature, but we also demonstrate that the incorporation of nonlinear associations in the data enables the detection of spatial patterns that are not identified by linear ICA. Specifically, we show networks including basal ganglia, cerebellum and thalamus that show significant differences in patients versus controls, some of which show distinct nonlinear patterns. PMID:26891483

The coalescence instability in solar flares

NASA Technical Reports Server (NTRS)

Tajima, T.; Brunel, F.; Sakai, J.-I.; Vlahos, L.; Kundu, M. R.

1985-01-01

The nonlinear coalescence instability of current carrying solar loops can explain many of the characteristics of the solar flares such as their impulsive nature, heating and high energy particle acceleration, amplitude oscillations of electromagnetic and emission as well as the characteristics of two-dimensional microwave images obtained during a flare. The plasma compressibility leads to the explosive phase of loop coalescence and its overshoot results in amplitude oscillations in temperatures by adiabatic compression and decompression. It is noted that the presence of strong electric fields and super-Alfvenic flows during the course of the instability play an important role in the production of nonthermal particles. A qualitative explanation on the physical processes taking place during the nonlinear stages of the instability is given.

Dielectric Optical-Controllable Magnifying Lens by Nonlinear Negative Refraction

PubMed Central

Cao, Jianjun; Shang, Ce; Zheng, Yuanlin; Feng, Yaming; Chen, Xianfeng; Liang, Xiaogan; Wan, Wenjie

2015-01-01

A simple optical lens plays an important role for exploring the microscopic world in science and technology by refracting light with tailored spatially varying refractive indices. Recent advancements in nanotechnology enable novel lenses, such as, superlens and hyperlens, with sub-wavelength resolution capabilities by specially designed materials’ refractive indices with meta-materials and transformation optics. However, these artificially nano- or micro-engineered lenses usually suffer high losses from metals and are highly demanding in fabrication. Here, we experimentally demonstrate, for the first time, a nonlinear dielectric magnifying lens using negative refraction by degenerate four-wave mixing in a plano-concave glass slide, obtaining magnified images. Moreover, we transform a nonlinear flat lens into a magnifying lens by introducing transformation optics into the nonlinear regime, achieving an all-optical controllable lensing effect through nonlinear wave mixing, which may have many potential applications in microscopy and imaging science. PMID:26149952

Multichannel spectral mode of the ALOHA up-conversion interferometer

NASA Astrophysics Data System (ADS)

Lehmann, L.; Darré, P.; Boulogne, H.; Delage, L.; Grossard, L.; Reynaud, F.

2018-06-01

In this paper, we propose a multichannel spectral configuration of the Astronomical Light Optical Hybrid Analysis (ALOHA) instrument dedicated to high-resolution imaging. A frequency conversion process is implemented in each arm of an interferometer to transfer the astronomical light to a shorter wavelength domain. Exploiting the spectral selectivity of this non-linear optical process, we propose to use a set of independent pump lasers in order to simultaneously study multiple spectral channels. This principle is experimentally demonstrated with a dual-channel configuration as a proof-of-principle.

Low Temperature Performance of High-Speed Neural Network Circuits

NASA Technical Reports Server (NTRS)

Duong, T.; Tran, M.; Daud, T.; Thakoor, A.

1995-01-01

Artificial neural networks, derived from their biological counterparts, offer a new and enabling computing paradigm specially suitable for such tasks as image and signal processing with feature classification/object recognition, global optimization, and adaptive control. When implemented in fully parallel electronic hardware, it offers orders of magnitude speed advantage. Basic building blocks of the new architecture are the processing elements called neurons implemented as nonlinear operational amplifiers with sigmoidal transfer function, interconnected through weighted connections called synapses implemented using circuitry for weight storage and multiply functions either in an analog, digital, or hybrid scheme.

Joint Transform Correlation for face tracking: elderly fall detection application

NASA Astrophysics Data System (ADS)

Katz, Philippe; Aron, Michael; Alfalou, Ayman

2013-03-01

In this paper, an iterative tracking algorithm based on a non-linear JTC (Joint Transform Correlator) architecture and enhanced by a digital image processing method is proposed and validated. This algorithm is based on the computation of a correlation plane where the reference image is updated at each frame. For that purpose, we use the JTC technique in real time to track a patient (target image) in a room fitted with a video camera. The correlation plane is used to localize the target image in the current video frame (frame i). Then, the reference image to be exploited in the next frame (frame i+1) is updated according to the previous one (frame i). In an effort to validate our algorithm, our work is divided into two parts: (i) a large study based on different sequences with several situations and different JTC parameters is achieved in order to quantify their effects on the tracking performances (decimation, non-linearity coefficient, size of the correlation plane, size of the region of interest...). (ii) the tracking algorithm is integrated into an application of elderly fall detection. The first reference image is a face detected by means of Haar descriptors, and then localized into the new video image thanks to our tracking method. In order to avoid a bad update of the reference frame, a method based on a comparison of image intensity histograms is proposed and integrated in our algorithm. This step ensures a robust tracking of the reference frame. This article focuses on face tracking step optimisation and evalutation. A supplementary step of fall detection, based on vertical acceleration and position, will be added and studied in further work.

Single pulse two-photon fluorescence lifetime imaging (SP-FLIM) with MHz pixel rate and an all fiber based setup

NASA Astrophysics Data System (ADS)

Eibl, Matthias; Karpf, Sebastian; Hakert, Hubertus; Weng, Daniel; Pfeiffer, Tom; Kolb, Jan Philip; Huber, Robert

2017-07-01

Newly developed microscopy methods have the goal to give researches in bio-molecular science a better understanding of processes ongoing on a cellular level. Especially two-photon excited fluorescence (TPEF) microscopy is a readily applied and widespread modality. Compared to one photon fluorescence imaging, it is possible to image not only the surface but also deeper lying structures. Together with fluorescence lifetime imaging (FLIM), which provides information on the chemical composition of a specimen, deeper insights on a molecular level can be gained. However, the need for elaborate light sources for TPEF and speed limitations for FLIM hinder an even wider application. In this contribution, we present a way to overcome this limitations by combining a robust and inexpensive fiber laser for nonlinear excitation with a fast analog digitization method for rapid FLIM imaging. The applied sub nanosecond pulsed laser source is perfectly suited for fiber delivery as typically limiting non-linear effects like self-phase or cross-phase modulation (SPM, XPM) are negligible. Furthermore, compared to the typically applied femtosecond pulses, our longer pulses produce much more fluorescence photons per single shot. In this paper, we show that this higher number of fluorescence photons per pulse combined with a high analog bandwidth detection makes it possible to not only use a single pulse per pixel for TPEF imaging but also to resolve the exponential time decay for FLIM. To evaluate our system, we acquired FLIM images of a dye solution with single exponential behavior to assess the accuracy of our lifetime determination and also FLIM images of a plant stem at a pixel rate of 1 MHz to show the speed performance of our single pulse two-photon FLIM (SP-FLIM) system.

Estimating contrast transfer function and associated parameters by constrained non-linear optimization.

PubMed

Yang, C; Jiang, W; Chen, D-H; Adiga, U; Ng, E G; Chiu, W

2009-03-01

The three-dimensional reconstruction of macromolecules from two-dimensional single-particle electron images requires determination and correction of the contrast transfer function (CTF) and envelope function. A computational algorithm based on constrained non-linear optimization is developed to estimate the essential parameters in the CTF and envelope function model simultaneously and automatically. The application of this estimation method is demonstrated with focal series images of amorphous carbon film as well as images of ice-embedded icosahedral virus particles suspended across holes.

Noise Estimation and Quality Assessment of Gaussian Noise Corrupted Images

NASA Astrophysics Data System (ADS)

Kamble, V. M.; Bhurchandi, K.

2018-03-01

Evaluating the exact quantity of noise present in an image and quality of an image in the absence of reference image is a challenging task. We propose a near perfect noise estimation method and a no reference image quality assessment method for images corrupted by Gaussian noise. The proposed methods obtain initial estimate of noise standard deviation present in an image using the median of wavelet transform coefficients and then obtains a near to exact estimate using curve fitting. The proposed noise estimation method provides the estimate of noise within average error of +/-4%. For quality assessment, this noise estimate is mapped to fit the Differential Mean Opinion Score (DMOS) using a nonlinear function. The proposed methods require minimum training and yields the noise estimate and image quality score. Images from Laboratory for image and Video Processing (LIVE) database and Computational Perception and Image Quality (CSIQ) database are used for validation of the proposed quality assessment method. Experimental results show that the performance of proposed quality assessment method is at par with the existing no reference image quality assessment metric for Gaussian noise corrupted images.

Platinum Acetylide Two-Photon Chromophores (Preprint)

DTIC Science & Technology

2007-04-01

nonlinear photonics,6-s microfabrication,9,10 fluorescence imaging, II and photodynamic therapy.12Instantaneous absorption of two lower energy photons...results in initiation of the same photophysical processes as one-photon absorption (lP A) of one high- energy photon. This is advantageous for two...reasons. The first is that because of the use of a lower energy photon a material will be guarded from ionization effects from multiphoton absorption in

Carcinogenic damage to deoxyribonucleic acid is induced by near-infrared laser pulses in multiphoton microscopy via combination of two- and three-photon absorption

NASA Astrophysics Data System (ADS)

Nadiarnykh, Oleg; Thomas, Giju; Van Voskuilen, Johan; Sterenborg, Henricus J. C. M.; Gerritsen, Hans C.

2012-11-01

Nonlinear optical imaging modalities (multiphoton excited fluorescence, second and third harmonic generation) applied in vivo are increasingly promising for clinical diagnostics and the monitoring of cancer and other disorders, as they can probe tissue with high diffraction-limited resolution at near-infrared (IR) wavelengths. However, high peak intensity of femtosecond laser pulses required for two-photon processes causes formation of cyclobutane-pyrimidine-dimers (CPDs) in cellular deoxyribonucleic acid (DNA) similar to damage from exposure to solar ultraviolet (UV) light. Inaccurate repair of subsequent mutations increases the risk of carcinogenesis. In this study, we investigate CPD damage that results in Chinese hamster ovary cells in vitro from imaging them with two-photon excited autofluorescence. The CPD levels are quantified by immunofluorescent staining. We further evaluate the extent of CPD damage with respect to varied wavelength, pulse width at focal plane, and pixel dwell time as compared with more pronounced damage from UV sources. While CPD damage has been expected to result from three-photon absorption, our results reveal that CPDs are induced by competing two- and three-photon absorption processes, where the former accesses UVA absorption band. This finding is independently confirmed by nonlinear dependencies of damage on laser power, wavelength, and pulse width.

Nonlinear response of the anterior cingulate and prefrontal cortex in schizophrenia as a function of variable attentional control.

PubMed

Blasi, Giuseppe; Taurisano, Paolo; Papazacharias, Apostolos; Caforio, Grazia; Romano, Raffaella; Lobianco, Luciana; Fazio, Leonardo; Di Giorgio, Annabella; Latorre, Valeria; Sambataro, Fabio; Popolizio, Teresa; Nardini, Marcello; Mattay, Venkata S; Weinberger, Daniel R; Bertolino, Alessandro

2010-04-01

Previous studies have reported abnormal prefrontal and cingulate activity during attentional control processing in schizophrenia. However, it is not clear how variation in attentional control load modulates activity within these brain regions in this brain disorder. The aim of this study in schizophrenia is to investigate the impact of increasing levels of attentional control processing on prefrontal and cingulate activity. Blood oxygen level-dependent (BOLD) responses of 16 outpatients with schizophrenia were compared with those of 21 healthy subjects while performing a task eliciting increasing levels of attentional control during event-related functional magnetic resonance imaging at 3 T. Results showed reduced behavioral performance in patients at greater attentional control levels. Imaging data indicated greater prefrontal activity at intermediate attentional control levels in patients but greater prefrontal and cingulate responses at high attentional control demands in controls. The BOLD activity profile of these regions in controls increased linearly with increasing cognitive loads, whereas in patients, it was nonlinear. Correlation analysis consistently showed differential region and load-specific relationships between brain activity and behavior in the 2 groups. These results indicate that varying attentional control load is associated in schizophrenia with load- and region-specific modification of the relationship between behavior and brain activity, possibly suggesting earlier saturation of cognitive capacity.

Nonlinear inversion of electrical resistivity imaging using pruning Bayesian neural networks

NASA Astrophysics Data System (ADS)

Jiang, Fei-Bo; Dai, Qian-Wei; Dong, Li

2016-06-01

Conventional artificial neural networks used to solve electrical resistivity imaging (ERI) inversion problem suffer from overfitting and local minima. To solve these problems, we propose to use a pruning Bayesian neural network (PBNN) nonlinear inversion method and a sample design method based on the K-medoids clustering algorithm. In the sample design method, the training samples of the neural network are designed according to the prior information provided by the K-medoids clustering results; thus, the training process of the neural network is well guided. The proposed PBNN, based on Bayesian regularization, is used to select the hidden layer structure by assessing the effect of each hidden neuron to the inversion results. Then, the hyperparameter α k , which is based on the generalized mean, is chosen to guide the pruning process according to the prior distribution of the training samples under the small-sample condition. The proposed algorithm is more efficient than other common adaptive regularization methods in geophysics. The inversion of synthetic data and field data suggests that the proposed method suppresses the noise in the neural network training stage and enhances the generalization. The inversion results with the proposed method are better than those of the BPNN, RBFNN, and RRBFNN inversion methods as well as the conventional least squares inversion.

Photoacoustic Non-Destructive Evaluation and Imaging of Caries in Dental Samples

NASA Astrophysics Data System (ADS)

Li, T.; Dewhurst, R. J.

2010-02-01

Dental caries is a disease wherein bacterial processes damage hard tooth structure. Traditional dental radiography has its limitations for detecting early stage caries. In this study, a photoacoustic (PA) imaging system with the near-infrared light source has been applied to postmortem dental samples to obtain 2-D and 3-D images. Imaging results showed that the PA technique can be used to image human teeth caries. For non-destructive photoacoustic evaluation and imaging, the induced temperature and pressure rises within biotissues should not cause physical damage to the tissue. For example, temperature rises above 5 °C within live human teeth will cause pulpal necrosis. Therefore, several simulations based on the thermoelastic effect have been applied to predict temperature and pressure fields within samples. Predicted temperature levels are below corresponding safety limits, but care is required to avoid nonlinear absorption phenomena. Furthermore, PA imaging results from the phantom provide evidence for high sensitivity, which shows the imaging potential of the PA technique for detecting early stage disease.

Improved GSO Optimized ESN Soft-Sensor Model of Flotation Process Based on Multisource Heterogeneous Information Fusion

PubMed Central

Wang, Jie-sheng; Han, Shuang; Shen, Na-na

2014-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, an echo state network (ESN) based fusion soft-sensor model optimized by the improved glowworm swarm optimization (GSO) algorithm is proposed. Firstly, the color feature (saturation and brightness) and texture features (angular second moment, sum entropy, inertia moment, etc.) based on grey-level co-occurrence matrix (GLCM) are adopted to describe the visual characteristics of the flotation froth image. Then the kernel principal component analysis (KPCA) method is used to reduce the dimensionality of the high-dimensional input vector composed by the flotation froth image characteristics and process datum and extracts the nonlinear principal components in order to reduce the ESN dimension and network complex. The ESN soft-sensor model of flotation process is optimized by the GSO algorithm with congestion factor. Simulation results show that the model has better generalization and prediction accuracy to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:24982935

Multimodal Nonlinear Optical Imaging for Sensitive Detection of Multiple Pharmaceutical Solid-State Forms and Surface Transformations.

PubMed

Novakovic, Dunja; Saarinen, Jukka; Rojalin, Tatu; Antikainen, Osmo; Fraser-Miller, Sara J; Laaksonen, Timo; Peltonen, Leena; Isomäki, Antti; Strachan, Clare J

2017-11-07

Two nonlinear imaging modalities, coherent anti-Stokes Raman scattering (CARS) and sum-frequency generation (SFG), were successfully combined for sensitive multimodal imaging of multiple solid-state forms and their changes on drug tablet surfaces. Two imaging approaches were used and compared: (i) hyperspectral CARS combined with principal component analysis (PCA) and SFG imaging and (ii) simultaneous narrowband CARS and SFG imaging. Three different solid-state forms of indomethacin-the crystalline gamma and alpha forms, as well as the amorphous form-were clearly distinguished using both approaches. Simultaneous narrowband CARS and SFG imaging was faster, but hyperspectral CARS and SFG imaging has the potential to be applied to a wider variety of more complex samples. These methodologies were further used to follow crystallization of indomethacin on tablet surfaces under two storage conditions: 30 °C/23% RH and 30 °C/75% RH. Imaging with (sub)micron resolution showed that the approach allowed detection of very early stage surface crystallization. The surfaces progressively crystallized to predominantly (but not exclusively) the gamma form at lower humidity and the alpha form at higher humidity. Overall, this study suggests that multimodal nonlinear imaging is a highly sensitive, solid-state (and chemically) specific, rapid, and versatile imaging technique for understanding and hence controlling (surface) solid-state forms and their complex changes in pharmaceuticals.

MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods.

PubMed

Schmidt, Johannes F M; Santelli, Claudio; Kozerke, Sebastian

2016-01-01

An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods.

Brain plasticity and functionality explored by nonlinear optical microscopy

NASA Astrophysics Data System (ADS)

Sacconi, L.; Allegra, L.; Buffelli, M.; Cesare, P.; D'Angelo, E.; Gandolfi, D.; Grasselli, G.; Lotti, J.; Mapelli, J.; Strata, P.; Pavone, F. S.

2010-02-01

In combination with fluorescent protein (XFP) expression techniques, two-photon microscopy has become an indispensable tool to image cortical plasticity in living mice. In parallel to its application in imaging, multi-photon absorption has also been used as a tool for the dissection of single neurites with submicrometric precision without causing any visible collateral damage to the surrounding neuronal structures. In this work, multi-photon nanosurgery is applied to dissect single climbing fibers expressing GFP in the cerebellar cortex. The morphological consequences are then characterized with time lapse 3-dimensional two-photon imaging over a period of minutes to days after the procedure. Preliminary investigations show that the laser induced fiber dissection recalls a regenerative process in the fiber itself over a period of days. These results show the possibility of this innovative technique to investigate regenerative processes in adult brain. In parallel with imaging and manipulation technique, non-linear microscopy offers the opportunity to optically record electrical activity in intact neuronal networks. In this work, we combined the advantages of second-harmonic generation (SHG) with a random access (RA) excitation scheme to realize a new microscope (RASH) capable of optically recording fast membrane potential events occurring in a wide-field of view. The RASH microscope, in combination with bulk loading of tissue with FM4-64 dye, was used to simultaneously record electrical activity from clusters of Purkinje cells in acute cerebellar slices. Complex spikes, both synchronous and asynchronous, were optically recorded simultaneously across a given population of neurons. Spontaneous electrical activity was also monitored simultaneously in pairs of neurons, where action potentials were recorded without averaging across trials. These results show the strength of this technique in describing the temporal dynamics of neuronal assemblies, opening promising perspectives in understanding the computations of neuronal networks.

Cross-matching: a modified cross-correlation underlying threshold energy model and match-based depth perception

PubMed Central

Doi, Takahiro; Fujita, Ichiro

2014-01-01

Three-dimensional visual perception requires correct matching of images projected to the left and right eyes. The matching process is faced with an ambiguity: part of one eye's image can be matched to multiple parts of the other eye's image. This stereo correspondence problem is complicated for random-dot stereograms (RDSs), because dots with an identical appearance produce numerous potential matches. Despite such complexity, human subjects can perceive a coherent depth structure. A coherent solution to the correspondence problem does not exist for anticorrelated RDSs (aRDSs), in which luminance contrast is reversed in one eye. Neurons in the visual cortex reduce disparity selectivity for aRDSs progressively along the visual processing hierarchy. A disparity-energy model followed by threshold nonlinearity (threshold energy model) can account for this reduction, providing a possible mechanism for the neural matching process. However, the essential computation underlying the threshold energy model is not clear. Here, we propose that a nonlinear modification of cross-correlation, which we term “cross-matching,” represents the essence of the threshold energy model. We placed half-wave rectification within the cross-correlation of the left-eye and right-eye images. The disparity tuning derived from cross-matching was attenuated for aRDSs. We simulated a psychometric curve as a function of graded anticorrelation (graded mixture of aRDS and normal RDS); this simulated curve reproduced the match-based psychometric function observed in human near/far discrimination. The dot density was 25% for both simulation and observation. We predicted that as the dot density increased, the performance for aRDSs should decrease below chance (i.e., reversed depth), and the level of anticorrelation that nullifies depth perception should also decrease. We suggest that cross-matching serves as a simple computation underlying the match-based disparity signals in stereoscopic depth perception. PMID:25360107

Associative Memory In A Phase Conjugate Resonator Cavity Utilizing A Hologram

NASA Astrophysics Data System (ADS)

Owechko, Y.; Marom, E.; Soffer, B. H.; Dunning, G.

1987-01-01

The principle of information retrieval by association has been suggested as a basis for parallel computing and as the process by which human memory functions.1 Various associative processors have been proposed that use electronic or optical means. Optical schemes,2-7 in particular, those based on holographic principles,3,6,7 are well suited to associative processing because of their high parallelism and information throughput. Previous workers8 demonstrated that holographically stored images can be recalled by using relatively complicated reference images but did not utilize nonlinear feedback to reduce the large cross talk that results when multiple objects are stored and a partial or distorted input is used for retrieval. These earlier approaches were limited in their ability to reconstruct the output object faithfully from a partial input.

Numerical simulation and analysis of accurate blood oxygenation measurement by using optical resolution photoacoustic microscopy

NASA Astrophysics Data System (ADS)

Yu, Tianhao; Li, Qian; Li, Lin; Zhou, Chuanqing

2016-10-01

Accuracy of photoacoustic signal is the crux on measurement of oxygen saturation in functional photoacoustic imaging, which is influenced by factors such as defocus of laser beam, curve shape of large vessels and nonlinear saturation effect of optical absorption in biological tissues. We apply Monte Carlo model to simulate energy deposition in tissues and obtain photoacoustic signals reaching a simulated focused surface detector to investigate corresponding influence of these factors. We also apply compensation on photoacoustic imaging of in vivo cat cerebral cortex blood vessels, in which signals from different lateral positions of vessels are corrected based on simulation results. And this process on photoacoustic images can improve the smoothness and accuracy of oxygen saturation results.

Coherent Femtosecond Spectroscopy and Nonlinear Optical Imaging on the Nanoscale

NASA Astrophysics Data System (ADS)

Kravtsov, Vasily

Optical properties of many materials and macroscopic systems are defined by ultrafast dynamics of electronic, vibrational, and spin excitations localized on the nanoscale. Harnessing these excitations for material engineering, optical computing, and control of chemical reactions has been a long-standing goal in science and technology. However, it is challenging due to the lack of spectroscopic techniques that can resolve processes simultaneously on the nanometer spatial and femtosecond temporal scales. This thesis describes the fundamental principles, implementation, and experimental demonstration of a novel type of ultrafast microscopy based on the concept of adiabatic plasmonic nanofocusing. Simultaneous spatio-temporal resolution on a nanometer-femtosecond scale is achieved by using a near-field nonlinear optical response induced by ultrafast surface plasmon polaritons nanofocused on a metal tip. First, we study the surface plasmon response in metallic structures and evaluate its prospects and limitations for ultrafast near-field microscopy. Through plasmon emission-based spectroscopy, we investigate dephasing times and interplay between radiative and non-radiative decay rates of localized plasmons and their modification due to coupling. We identify a new regime of quantum plasmonic coupling, which limits the achievable spatial resolution to several angstroms but at the same time provides a potential channel for generating ultrafast electron currents at optical frequencies. Next, we study propagation of femtosecond wavepackets of surface plasmon polaritons on a metal tip. In time-domain interferometric measurements we detect group delays that correspond to slowing of the plasmon polaritons down to 20% of the speed of light at the tip apex. This provides direct experimental verification of the plasmonic nanofocusing mechanism and suggests enhanced nonlinear optical interactions at the tip apex. We then measure a plasmon-generated third-order nonlinear optical four-wave mixing response from the tip apex and investigate its microscopic mechanism. Our results reveal a significant contribution to the third order nonlinearity of plasmonic structures due to large near-field gradients associated with nanofocused plasmons. In combination with scanning probe imaging and femtosecond pulse shaping, the nanofocused four-wave mixing response provides a basis for a novel type of ultrafast optical microscopy on the nanoscale. We demonstrate its capabilities by nano-imaging the coherent dynamics of localized plasmonic modes in a rough gold film edge with simultaneous sub-50 nm spatial and sub-5 fs temporal resolution. We capture the coherent decay and extract the dephasing times of individual plasmonic modes. Lastly, we apply our technique to study nanoscale spatial heterogeneity of the nonlinear optical response in novel two-dimensional materials: monolayer and few-layer graphene. An enhanced four-wave mixing signal is revealed on the edges of graphene flakes. We investigate the mechanism of this enhancement by performing nano-imaging on a graphene field-effect transistor with the variable carrier density controlled by electrostatic gating.

Laser nanosurgery and manipulation in living cells

NASA Astrophysics Data System (ADS)

Sacconi, Leonardo; Tolic-Norrelykke, Iva M.; Antolini, Renzo; Pavone, Francesco S.

2005-03-01

We present a combination of nonlinear microscopy, laser nanosurgery and optical trapping applied to the 3D imaging and manipulation of intracellular structures in live cells. We use Titanium-sapphire laser pulses for a combined nonlinear microscopy and nanosurgery on microtubules tagged with green fluorescent protein (GFP) in fission yeast. The same laser source is also used to trap small round lipid droplets naturally present in the cell. The trapped droplets are used as handles to exert a pushing force on the nucleus, allowing for a displacement of the nucleus away from its normal position in the center of the cell. We show that nonlinear nanosurgery and optical manipulation can be performed with sub-micrometer precision and without visible collateral damage to the cell. We present this combination as an important tool in cell biology for the manipulation of specific structures in alternative to genetic methods or chemical agents. This technique can be applied to several fundamental problems in cell biology, including the study of dynamics processes in cell division.

[Investigation on remote measurement of air pollution by a method of infrared passive scanning imaging].

PubMed

Jiao, Yang; Xu, Liang; Gao, Min-Guang; Feng, Ming-Chun; Jin, Ling; Tong, Jing-Jing; Li, Sheng

2012-07-01

Passive remote sensing by Fourier-transform infrared (FTIR) spectrometry allows detection of air pollution. However, for the localization of a leak and a complete assessment of the situation in the case of the release of a hazardous cloud, information about the position and the distribution of a cloud is essential. Therefore, an imaging passive remote sensing system comprising an interferometer, a data acquisition and processing software, scan system, a video system, and a personal computer has been developed. The remote sensing of SF6 was done. The column densities of all directions in which a target compound has been identified may be retrieved by a nonlinear least squares fitting algorithm and algorithm of radiation transfer, and a false color image is displayed. The results were visualized by a video image, overlaid by false color concentration distribution image. The system has a high selectivity, and allows visualization and quantification of pollutant clouds.

The Fringe-Imaging Skin Friction Technique PC Application User's Manual

NASA Technical Reports Server (NTRS)

Zilliac, Gregory G.

1999-01-01

A personal computer application (CXWIN4G) has been written which greatly simplifies the task of extracting skin friction measurements from interferograms of oil flows on the surface of wind tunnel models. Images are first calibrated, using a novel approach to one-camera photogrammetry, to obtain accurate spatial information on surfaces with curvature. As part of the image calibration process, an auxiliary file containing the wind tunnel model geometry is used in conjunction with a two-dimensional direct linear transformation to relate the image plane to the physical (model) coordinates. The application then applies a nonlinear regression model to accurately determine the fringe spacing from interferometric intensity records as required by the Fringe Imaging Skin Friction (FISF) technique. The skin friction is found through application of a simple expression that makes use of lubrication theory to relate fringe spacing to skin friction.

Image-algebraic design of multispectral target recognition algorithms

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.

1994-06-01

In this paper, we discuss methods for multispectral ATR (Automated Target Recognition) of small targets that are sensed under suboptimal conditions, such as haze, smoke, and low light levels. In particular, we discuss our ongoing development of algorithms and software that effect intelligent object recognition by selecting ATR filter parameters according to ambient conditions. Our algorithms are expressed in terms of IA (image algebra), a concise, rigorous notation that unifies linear and nonlinear mathematics in the image processing domain. IA has been implemented on a variety of parallel computers, with preprocessors available for the Ada and FORTRAN languages. An image algebra C++ class library has recently been made available. Thus, our algorithms are both feasible implementationally and portable to numerous machines. Analyses emphasize the aspects of image algebra that aid the design of multispectral vision algorithms, such as parameterized templates that facilitate the flexible specification of ATR filters.

Model of anisotropic nonlinearity in self-defocusing photorefractive media.

PubMed

Barsi, C; Fleischer, J W

2015-09-21

We develop a phenomenological model of anisotropy in self-defocusing photorefractive crystals. In addition to an independent term due to nonlinear susceptibility, we introduce a nonlinear, non-separable correction to the spectral diffraction operator. The model successfully describes the crossover between photovoltaic and photorefractive responses and the spatially dispersive shock wave behavior of a nonlinearly spreading Gaussian input beam. It should prove useful for characterizing internal charge dynamics in complex materials and for accurate image reconstruction through nonlinear media.

Nonlinear PET parametric image reconstruction with MRI information using kernel method

NASA Astrophysics Data System (ADS)

Gong, Kuang; Wang, Guobao; Chen, Kevin T.; Catana, Ciprian; Qi, Jinyi

2017-03-01

Positron Emission Tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neurology. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information. Previously we have used kernel learning to embed MR information in static PET reconstruction and direct Patlak reconstruction. Here we extend this method to direct reconstruction of nonlinear parameters in a compartment model by using the alternating direction of multiplier method (ADMM) algorithm. Simulation studies show that the proposed method can produce superior parametric images compared with existing methods.

Image enhancement by non-linear extrapolation in frequency space

NASA Technical Reports Server (NTRS)

Anderson, Charles H. (Inventor); Greenspan, Hayit K. (Inventor)

1998-01-01

An input image is enhanced to include spatial frequency components having frequencies higher than those in an input image. To this end, an edge map is generated from the input image using a high band pass filtering technique. An enhancing map is subsequently generated from the edge map, with the enhanced map having spatial frequencies exceeding an initial maximum spatial frequency of the input image. The enhanced map is generated by applying a non-linear operator to the edge map in a manner which preserves the phase transitions of the edges of the input image. The enhanced map is added to the input image to achieve a resulting image having spatial frequencies greater than those in the input image. Simplicity of computations and ease of implementation allow for image sharpening after enlargement and for real-time applications such as videophones, advanced definition television, zooming, and restoration of old motion pictures.

A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier.

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

The proposed system provides new textural information for segmenting tumours, efficiently and accurately and with less computational time, from benign and malignant tumour images, especially in smaller dimensions of tumour regions of computed tomography (CT) images. Region-based segmentation of tumour from brain CT image data is an important but time-consuming task performed manually by medical experts. The objective of this work is to segment brain tumour from CT images using combined grey and texture features with new edge features and nonlinear support vector machine (SVM) classifier. The selected optimal features are used to model and train the nonlinear SVM classifier to segment the tumour from computed tomography images and the segmentation accuracies are evaluated for each slice of the tumour image. The method is applied on real data of 80 benign, malignant tumour images. The results are compared with the radiologist labelled ground truth. Quantitative analysis between ground truth and the segmented tumour is presented in terms of segmentation accuracy and the overlap similarity measure dice metric. From the analysis and performance measures such as segmentation accuracy and dice metric, it is inferred that better segmentation accuracy and higher dice metric are achieved with the normalized cut segmentation method than with the fuzzy c-means clustering method.

Application and Miniaturization of Linear and Nonlinear Raman Microscopy for Biomedical Imaging

NASA Astrophysics Data System (ADS)

Mittal, Richa

Current diagnostics for several disorders rely on surgical biopsy or evaluation of ex vivo bodily fluids, which have numerous drawbacks. We evaluated the potential for vibrational techniques (both linear and nonlinear Raman) as a reliable and noninvasive diagnostic tool. Raman spectroscopy is an optical technique for molecular analysis that has been used extensively in various biomedical applications. Based on demonstrated capabilities of Raman spectroscopy we evaluated the potential of the technique for providing a noninvasive diagnosis of mucopolysaccharidosis (MPS). These studies show that Raman spectroscopy can detect subtle changes in tissue biochemistry. In applications where sub-micrometer visualization of tissue compositional change is required, a transition from spectroscopy to high quality imaging is necessary. Nonlinear vibrational microscopy is sensitive to the same molecular vibrations as linear Raman, but features fast imaging capabilities. Coherent Raman scattering when combined with other nonlinear optical (NLO) techniques (like two-photon excited fluorescence and second harmonic generation) forms a collection of advanced optical techniques that provide noninvasive chemical contrast at submicron resolution. This capability to examine tissues without external molecular agents is driving the NLO approach towards clinical applications. However, the unique imaging capabilities of NLO microscopy are accompanied by complex instrument requirements. Clinical examination requires portable imaging systems for rapid inspection of tissues. Optical components utilized in NLO microscopy would then need substantial miniaturization and optimization to enable in vivo use. The challenges in designing compact microscope objective lenses and laser beam scanning mechanisms are discussed. The development of multimodal NLO probes for imaging oral cavity tissue is presented. Our prototype has been examined for ex vivo tissue imaging based on intrinsic fluorescence and SHG contrast. These studies show a potential for multiphoton compact probes to be used for real time imaging in the clinic.

Hierarchical Heteroclinics in Dynamical Model of Cognitive Processes: Chunking

NASA Astrophysics Data System (ADS)

Afraimovich, Valentin S.; Young, Todd R.; Rabinovich, Mikhail I.

Combining the results of brain imaging and nonlinear dynamics provides a new hierarchical vision of brain network functionality that is helpful in understanding the relationship of the network to different mental tasks. Using these ideas it is possible to build adequate models for the description and prediction of different cognitive activities in which the number of variables is usually small enough for analysis. The dynamical images of different mental processes depend on their temporal organization and, as a rule, cannot be just simple attractors since cognition is characterized by transient dynamics. The mathematical image for a robust transient is a stable heteroclinic channel consisting of a chain of saddles connected by unstable separatrices. We focus here on hierarchical chunking dynamics that can represent several cognitive activities. Chunking is the dynamical phenomenon that means dividing a long information chain into shorter items. Chunking is known to be important in many processes of perception, learning, memory and cognition. We prove that in the phase space of the model that describes chunking there exists a new mathematical object — heteroclinic sequence of heteroclinic cycles — using the technique of slow-fast approximations. This new object serves as a skeleton of motions reflecting sequential features of hierarchical chunking dynamics and is an adequate image of the chunking processing.

Ultrasound imaging based on nonlinear pressure field properties

NASA Astrophysics Data System (ADS)

Bouakaz, Ayache; Frinking, Peter J. A.; de Jong, Nico

2000-07-01

Ultrasound image quality has experienced a significant improvement over the past years with the utilization of harmonic frequencies. This brings the need to understand the physical processes involved in the propagation of finite amplitude sound beams, and the issues for redesigning and optimizing the phased array transducers. New arrays with higher imaging performances are essential for tissue imaging and contrast imaging as well. This study presents measurements and simulations on a 4.6 MHz square transducer. The numerical scheme used solves the KZK equation in the time domain. Comparison of measured and computed data showed good agreement for low and high excitation levels. In a similar way, a numerical simulation was performed on a linear array with five elements. The simulation showed that the second harmonic beam is narrower than the fundamental with less energy in the near field. In addition, the grating lobes are significantly lower. Accordingly, selective harmonic imaging shows less near field artifacts and will lower the clutter, resulting in much cleaner images.

Multiphoton tomography of the human eye

NASA Astrophysics Data System (ADS)

König, Karsten; Batista, Ana; Hager, Tobias; Seitz, Berthold

2017-02-01

Multiphoton tomography (MPT) is a novel label-free clinical imaging method for non-invasive tissue imaging with high spatial (300 nm) and temporal (100 ps) resolutions. In vivo optical histology can be realized due to the nonlinear excitation of endogenous fluorophores and second-harmonic generation (SHG) of collagen. Furthermore, optical metabolic imaging (OMI) is performed by two-photon autofluorescence lifetime imaging (FLIM). So far, applications of the multiphoton tomographs DermaInspect and MPTflex were limited to dermatology. Novel applications include intraoperative brain tumor imaging as well as cornea imaging. In this work we describe two-photon imaging of ex vivo human corneas unsuitable for transplantation. Furthermore, the cross-linking (CXL) process of corneal collagen based on UVA exposure and 0.1 % riboflavin was studied. The pharmacokinetics of the photosensitizer could be detected with high spatial resolution. Interestingly, an increase in the stromal autofluorescence intensity and modifications of the autofluorescence lifetimes were observed in the human corneal samples within a few days following CXL.

Double-image storage optimized by cross-phase modulation in a cold atomic system

NASA Astrophysics Data System (ADS)

Qiu, Tianhui; Xie, Min

2017-09-01

A tripod-type cold atomic system driven by double-probe fields and a coupling field is explored to store double images based on the electromagnetically induced transparency (EIT). During the storage time, an intensity-dependent signal field is applied further to extend the system with the fifth level involved, then the cross-phase modulation is introduced for coherently manipulating the stored images. Both analytical analysis and numerical simulation clearly demonstrate a tunable phase shift with low nonlinear absorption can be imprinted on the stored images, which effectively can improve the visibility of the reconstructed images. The phase shift and the energy retrieving rate of the probe fields are immune to the coupling intensity and the atomic optical density. The proposed scheme can easily be extended to the simultaneous storage of multiple images. This work may be exploited toward the end of EIT-based multiple-image storage devices for all-optical classical and quantum information processings.

A high-precision instrument for analyzing nonlinear dynamic behavior of bearing cage.

PubMed

Yang, Z; Chen, H; Yu, T; Li, B

2016-08-01

The high-precision ball bearing is fundamental to the performance of complex mechanical systems. As the speed increases, the cage behavior becomes a key factor in influencing the bearing performance, especially life and reliability. This paper develops a high-precision instrument for analyzing nonlinear dynamic behavior of the bearing cage. The trajectory of the rotational center and non-repetitive run-out (NRRO) of the cage are used to evaluate the instability of cage motion. This instrument applied an aerostatic spindle to support and spin test the bearing to decrease the influence of system error. Then, a high-speed camera is used to capture images when the bearing works at high speeds. A 3D trajectory tracking software tema Motion is used to track the spot which marked the cage surface. Finally, by developing the matlab program, a Lissajous' figure was used to evaluate the nonlinear dynamic behavior of the cage with different speeds. The trajectory of rotational center and NRRO of the cage with various speeds are analyzed. The results can be used to predict the initial failure and optimize cage structural parameters. In addition, the repeatability precision of instrument is also validated. In the future, the motorized spindle will be applied to increase testing speed and image processing algorithms will be developed to analyze the trajectory of the cage.

A high-precision instrument for analyzing nonlinear dynamic behavior of bearing cage

NASA Astrophysics Data System (ADS)

Yang, Z.; Chen, H.; Yu, T.; Li, B.

2016-08-01

The high-precision ball bearing is fundamental to the performance of complex mechanical systems. As the speed increases, the cage behavior becomes a key factor in influencing the bearing performance, especially life and reliability. This paper develops a high-precision instrument for analyzing nonlinear dynamic behavior of the bearing cage. The trajectory of the rotational center and non-repetitive run-out (NRRO) of the cage are used to evaluate the instability of cage motion. This instrument applied an aerostatic spindle to support and spin test the bearing to decrease the influence of system error. Then, a high-speed camera is used to capture images when the bearing works at high speeds. A 3D trajectory tracking software tema Motion is used to track the spot which marked the cage surface. Finally, by developing the matlab program, a Lissajous' figure was used to evaluate the nonlinear dynamic behavior of the cage with different speeds. The trajectory of rotational center and NRRO of the cage with various speeds are analyzed. The results can be used to predict the initial failure and optimize cage structural parameters. In addition, the repeatability precision of instrument is also validated. In the future, the motorized spindle will be applied to increase testing speed and image processing algorithms will be developed to analyze the trajectory of the cage.

A high-precision instrument for analyzing nonlinear dynamic behavior of bearing cage

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Z., E-mail: zhaohui@nwpu.edu.cn; Yu, T.; Chen, H.

2016-08-15

The high-precision ball bearing is fundamental to the performance of complex mechanical systems. As the speed increases, the cage behavior becomes a key factor in influencing the bearing performance, especially life and reliability. This paper develops a high-precision instrument for analyzing nonlinear dynamic behavior of the bearing cage. The trajectory of the rotational center and non-repetitive run-out (NRRO) of the cage are used to evaluate the instability of cage motion. This instrument applied an aerostatic spindle to support and spin test the bearing to decrease the influence of system error. Then, a high-speed camera is used to capture images whenmore » the bearing works at high speeds. A 3D trajectory tracking software TEMA Motion is used to track the spot which marked the cage surface. Finally, by developing the MATLAB program, a Lissajous’ figure was used to evaluate the nonlinear dynamic behavior of the cage with different speeds. The trajectory of rotational center and NRRO of the cage with various speeds are analyzed. The results can be used to predict the initial failure and optimize cage structural parameters. In addition, the repeatability precision of instrument is also validated. In the future, the motorized spindle will be applied to increase testing speed and image processing algorithms will be developed to analyze the trajectory of the cage.« less

3D temporal subtraction on multislice CT images using nonlinear warping technique

NASA Astrophysics Data System (ADS)

Ishida, Takayuki; Katsuragawa, Shigehiko; Kawashita, Ikuo; Kim, Hyounseop; Itai, Yoshinori; Awai, Kazuo; Li, Qiang; Doi, Kunio

2007-03-01

The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval changes between previous and current multislice CT images based on a nonlinear image warping technique. Our method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our computerized method includes global and local image matching techniques for accurate registration of current and previous CT images. For global image matching, we selected the corresponding previous section image for each current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred previous CT image. For local image matching, we applied the 3D template matching technique with translation and rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT images.

Brain tumor image segmentation using kernel dictionary learning.

PubMed

Jeon Lee; Seung-Jun Kim; Rong Chen; Herskovits, Edward H

2015-08-01

Automated brain tumor image segmentation with high accuracy and reproducibility holds a big potential to enhance the current clinical practice. Dictionary learning (DL) techniques have been applied successfully to various image processing tasks recently. In this work, kernel extensions of the DL approach are adopted. Both reconstructive and discriminative versions of the kernel DL technique are considered, which can efficiently incorporate multi-modal nonlinear feature mappings based on the kernel trick. Our novel discriminative kernel DL formulation allows joint learning of a task-driven kernel-based dictionary and a linear classifier using a K-SVD-type algorithm. The proposed approaches were tested using real brain magnetic resonance (MR) images of patients with high-grade glioma. The obtained preliminary performances are competitive with the state of the art. The discriminative kernel DL approach is seen to reduce computational burden without much sacrifice in performance.

Nonlinear imaging (NIM) of barely visible impact damage (BVID) in composite panels using a semi and full air-coupled linear and nonlinear ultrasound technique

NASA Astrophysics Data System (ADS)

Malfense Fierro, Gian Piero; Meo, Michele

2018-03-01

Two non-contact methods were evaluated to address the reliability and reproducibility concerns affecting industry adoption of nonlinear ultrasound techniques for non-destructive testing and evaluation (NDT/E) purposes. A semi and a fully air-coupled linear and nonlinear ultrasound method was evaluated by testing for barely visible impact damage (BVID) in composite materials. Air coupled systems provide various advantages over contact driven systems; such as: ease of inspection, no contact and lubrication issues and a great potential for non-uniform geometry evaluation. The semi air-coupled setup used a suction attached piezoelectric transducer to excite the sample and an array of low-cost microphones to capture the signal over the inspection area, while the second method focused on a purely air-coupled setup, using an air-coupled transducer to excite the structure and capture the signal. One of the issues facing nonlinear and any air-coupled systems is transferring enough energy to stimulate wave propagation and in the case of nonlinear ultrasound; damage regions. Results for both methods provided nonlinear imaging (NIM) of damage regions using a sweep excitation methodology, with the semi aircoupled system providing clearer results.

3-D zebrafish embryo image filtering by nonlinear partial differential equations.

PubMed

Rizzi, Barbara; Campana, Matteo; Zanella, Cecilia; Melani, Camilo; Cunderlik, Robert; Krivá, Zuzana; Bourgine, Paul; Mikula, Karol; Peyriéras, Nadine; Sarti, Alessandro

2007-01-01

We discuss application of nonlinear PDE based methods to filtering of 3-D confocal images of embryogenesis. We focus on the mean curvature driven and the regularized Perona-Malik equations, where standard as well as newly suggested edge detectors are used. After presenting the related mathematical models, the practical results are given and discussed by visual inspection and quantitatively using the mean Hausdorff distance.

An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS.

PubMed

Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu

2017-01-23

Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

Nonlinear optical cryptosystem based on joint Fresnel transform correlator under vector wave illumination

NASA Astrophysics Data System (ADS)

Xueju, Shen; Chao, Lin; Xiao, Zou; Jianjun, Cai

2015-05-01

We present a nonlinear optical cryptosystem with multi-dimensional keys including phase, polarization and diffraction distance. To make full use of the degrees of freedom that optical processing offers, an elaborately designed vector wave with both a space-variant phase and locally linear polarization is generated with a common-path interferometer for illumination. The joint transform correlator in the Fresnel domain, implemented with a double optical wedge, is utilized as the encryption framework which provides an additional key known as the Fresnel diffraction distance. Two nonlinear operations imposed on the recorded joint Fresnel power distribution (JFPD) by a charge coupled device (CCD) are adopted. The first one is the division of power distribution of the reference window random function which is previously proposed by researchers and can improve the quality of the decrypted image. The second one is the recording of a hybrid JFPD using a micro-polarizers array with orthogonal and random transmissive axes attached to the CCD. Then the hybrid JFPD is further scrambled by substituting random noise for partial power distribution. The two nonlinear operations break the linearity of this cryptosystem and provide ultra security. We verify our proposal using a quick response code for noise-free recovery.

Preprocessing of 2-Dimensional Gel Electrophoresis Images Applied to Proteomic Analysis: A Review.

PubMed

Goez, Manuel Mauricio; Torres-Madroñero, Maria Constanza; Röthlisberger, Sarah; Delgado-Trejos, Edilson

2018-02-01

Various methods and specialized software programs are available for processing two-dimensional gel electrophoresis (2-DGE) images. However, due to the anomalies present in these images, a reliable, automated, and highly reproducible system for 2-DGE image analysis has still not been achieved. The most common anomalies found in 2-DGE images include vertical and horizontal streaking, fuzzy spots, and background noise, which greatly complicate computational analysis. In this paper, we review the preprocessing techniques applied to 2-DGE images for noise reduction, intensity normalization, and background correction. We also present a quantitative comparison of non-linear filtering techniques applied to synthetic gel images, through analyzing the performance of the filters under specific conditions. Synthetic proteins were modeled into a two-dimensional Gaussian distribution with adjustable parameters for changing the size, intensity, and degradation. Three types of noise were added to the images: Gaussian, Rayleigh, and exponential, with signal-to-noise ratios (SNRs) ranging 8-20 decibels (dB). We compared the performance of wavelet, contourlet, total variation (TV), and wavelet-total variation (WTTV) techniques using parameters SNR and spot efficiency. In terms of spot efficiency, contourlet and TV were more sensitive to noise than wavelet and WTTV. Wavelet worked the best for images with SNR ranging 10-20 dB, whereas WTTV performed better with high noise levels. Wavelet also presented the best performance with any level of Gaussian noise and low levels (20-14 dB) of Rayleigh and exponential noise in terms of SNR. Finally, the performance of the non-linear filtering techniques was evaluated using a real 2-DGE image with previously identified proteins marked. Wavelet achieved the best detection rate for the real image. Copyright © 2018 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China. Production and hosting by Elsevier B.V. All rights reserved.

Theory of multinonlinear media and its application to the soliton processes in ferrite–ferroelectric structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cherkasskii, M. A., E-mail: macherkasskii@hotmail.com; Nikitin, A. A.; Kalinikos, B. A.

A theory is developed to describe the wave processes that occur in waveguide media having several types of nonlinearity, specifically, multinonlinear media. It is shown that the nonlinear Schrödinger equation can be used to describe the general wave process that occurs in such media. The competition between the electric wave nonlinearity and the magnetic wave nonlinearity in a layered multinonlinear ferrite–ferroelectric structure is found to change a total repulsive nonlinearity into a total attractive nonlinearity.

Nonlinear association criterion, nonlinear Granger causality and related issues with applications to neuroimage studies.

PubMed

Tao, Chenyang; Feng, Jianfeng

2016-03-15

Quantifying associations in neuroscience (and many other scientific disciplines) is often challenged by high-dimensionality, nonlinearity and noisy observations. Many classic methods have either poor power or poor scalability on data sets of the same or different scales such as genetical, physiological and image data. Based on the framework of reproducing kernel Hilbert spaces we proposed a new nonlinear association criteria (NAC) with an efficient numerical algorithm and p-value approximation scheme. We also presented mathematical justification that links the proposed method to related methods such as kernel generalized variance, kernel canonical correlation analysis and Hilbert-Schmidt independence criteria. NAC allows the detection of association between arbitrary input domain as long as a characteristic kernel is defined. A MATLAB package was provided to facilitate applications. Extensive simulation examples and four real world neuroscience examples including functional MRI causality, Calcium imaging and imaging genetic studies on autism [Brain, 138(5):13821393 (2015)] and alcohol addiction [PNAS, 112(30):E4085-E4093 (2015)] are used to benchmark NAC. It demonstrates the superior performance over the existing procedures we tested and also yields biologically significant results for the real world examples. NAC beats its linear counterparts when nonlinearity is presented in the data. It also shows more robustness against different experimental setups compared with its nonlinear counterparts. In this work we presented a new and robust statistical approach NAC for measuring associations. It could serve as an interesting alternative to the existing methods for datasets where nonlinearity and other confounding factors are present. Copyright © 2016 Elsevier B.V. All rights reserved.

A mixed-order nonlinear diffusion compressed sensing MR image reconstruction.

PubMed

Joy, Ajin; Paul, Joseph Suresh

2018-03-07

Avoid formation of staircase artifacts in nonlinear diffusion-based MR image reconstruction without compromising computational speed. Whereas second-order diffusion encourages the evolution of pixel neighborhood with uniform intensities, fourth-order diffusion considers smooth region to be not necessarily a uniform intensity region but also a planar region. Therefore, a controlled application of fourth-order diffusivity function is used to encourage second-order diffusion to reconstruct the smooth regions of the image as a plane rather than a group of blocks, while not being strong enough to introduce the undesirable speckle effect. Proposed method is compared with second- and fourth-order nonlinear diffusion reconstruction, total variation (TV), total generalized variation, and higher degree TV using in vivo data sets for different undersampling levels with application to dictionary learning-based reconstruction. It is observed that the proposed technique preserves sharp boundaries in the image while preventing the formation of staircase artifacts in the regions of smoothly varying pixel intensities. It also shows reduced error measures compared with second-order nonlinear diffusion reconstruction or TV and converges faster than TV-based methods. Because nonlinear diffusion is known to be an effective alternative to TV for edge-preserving reconstruction, the crucial aspect of staircase artifact removal is addressed. Reconstruction is found to be stable for the experimentally determined range of fourth-order regularization parameter, and therefore not does not introduce a parameter search. Hence, the computational simplicity of second-order diffusion is retained. © 2018 International Society for Magnetic Resonance in Medicine.

Comparison of line shortening assessed by aerial image and wafer measurements

NASA Astrophysics Data System (ADS)

Ziegler, Wolfram; Pforr, Rainer; Thiele, Joerg; Maurer, Wilhelm

1997-02-01

Increasing number of patterns per area and decreasing linewidth demand enhancement technologies for optical lithography. OPC, the correction of systematic non-linearity in the pattern transfer process by correction of design data is one possibility to tighten process control and to increase the lifetime of existing lithographic equipment. The two most prominent proximity effects to be corrected by OPC are CD variation and line shortening. Line shortening measured on a wafer is up to 2 times larger than full resist simulation results. Therefore, the influence of mask geometry to line shortening is a key item to parameterize lithography. The following paper discusses the effect of adding small serifs to line ends with 0.25 micrometer ground-rule design. For reticles produced on an ALTA 3000 with standard wet etch process, the corner rounding on them mask can be reduced by adding serifs of a certain size. The corner rounding was measured and the effect on line shortening on the wafer is determined. This was investigated by resist measurements on wafer, aerial image plus resist simulation and aerial image measurements on the AIMS microscope.

Advanced 3D image processing techniques for liver and hepatic tumor location and volumetry

NASA Astrophysics Data System (ADS)

Chemouny, Stephane; Joyeux, Henri; Masson, Bruno; Borne, Frederic; Jaeger, Marc; Monga, Olivier

1999-05-01

To assist radiologists and physicians in diagnosing, and in treatment planning and evaluating in liver oncology, we have developed a fast and accurate segmentation of the liver and its lesions within CT-scan exams. The first step of our method is to reduce spatial resolution of CT images. This will have two effects: obtain near isotropic 3D data space and drastically decrease computational time for further processing. On a second step a 3D non-linear `edge- preserving' smoothing filtering is performed throughout the entire exam. On a third step the 3D regions coming out from the second step are homogeneous enough to allow a quite simple segmentation process, based on morphological operations, under supervisor control, ending up with accurate 3D regions of interest (ROI) of the liver and all the hepatic tumors. On a fourth step the ROIs are eventually set back into the original images, features like volume and location are immediately computed and displayed. The segmentation we get is as precise as a manual one but is much faster.

Generalized image contrast enhancement technique based on the Heinemann contrast discrimination model

NASA Astrophysics Data System (ADS)

Liu, Hong; Nodine, Calvin F.

1996-07-01

This paper presents a generalized image contrast enhancement technique, which equalizes the perceived brightness distribution based on the Heinemann contrast discrimination model. It is based on the mathematically proven existence of a unique solution to a nonlinear equation, and is formulated with easily tunable parameters. The model uses a two-step log-log representation of luminance contrast between targets and surround in a luminous background setting. The algorithm consists of two nonlinear gray scale mapping functions that have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear functions of the gray-level distribution of the given image, and can be uniquely determined once the previous three are set. Tests have been carried out to demonstrate the effectiveness of the algorithm for increasing the overall contrast of radiology images. The traditional histogram equalization can be reinterpreted as an image enhancement technique based on the knowledge of human contrast perception. In fact, it is a special case of the proposed algorithm.

Polarization Control with Plasmonic Antenna Tips: A Universal Approach to Optical Nanocrystallography and Vector-Field Imaging

NASA Astrophysics Data System (ADS)

Park, Kyoung-Duck; Raschke, Markus B.

2018-05-01

Controlling the propagation and polarization vectors in linear and nonlinear optical spectroscopy enables to probe the anisotropy of optical responses providing structural symmetry selective contrast in optical imaging. Here we present a novel tilted antenna-tip approach to control the optical vector-field by breaking the axial symmetry of the nano-probe in tip-enhanced near-field microscopy. This gives rise to a localized plasmonic antenna effect with significantly enhanced optical field vectors with control of both \\textit{in-plane} and \\textit{out-of-plane} components. We use the resulting vector-field specificity in the symmetry selective nonlinear optical response of second-harmonic generation (SHG) for a generalized approach to optical nano-crystallography and -imaging. In tip-enhanced SHG imaging of monolayer MoS$_2$ films and single-crystalline ferroelectric YMnO$_3$, we reveal nano-crystallographic details of domain boundaries and domain topology with enhanced sensitivity and nanoscale spatial resolution. The approach is applicable to any anisotropic linear and nonlinear optical response, and provides for optical nano-crystallographic imaging of molecular or quantum materials.

Projection of Stabilized Aerial Imagery Onto Digital Elevation Maps for Geo-Rectified and Jitter-Free Viewing

NASA Technical Reports Server (NTRS)

Ansar, Adnan I.; Brennan, Shane; Clouse, Daniel S.

2012-01-01

As imagery is collected from an airborne platform, an individual viewing the images wants to know from where on the Earth the images were collected. To do this, some information about the camera needs to be known, such as its position and orientation relative to the Earth. This can be provided by common inertial navigation systems (INS). Once the location of the camera is known, it is useful to project an image onto some representation of the Earth. Due to the non-smooth terrain of the Earth (mountains, valleys, etc.), this projection is highly non-linear. Thus, to ensure accurate projection, one needs to project onto a digital elevation map (DEM). This allows one to view the images overlaid onto a representation of the Earth. A code has been developed that takes an image, a model of the camera used to acquire that image, the pose of the camera during acquisition (as provided by an INS), and a DEM, and outputs an image that has been geo-rectified. The world coordinate of the bounds of the image are provided for viewing purposes. The code finds a mapping from points on the ground (DEM) to pixels in the image. By performing this process for all points on the ground, one can "paint" the ground with the image, effectively performing a projection of the image onto the ground. In order to make this process efficient, a method was developed for finding a region of interest (ROI) on the ground to where the image will project. This code is useful in any scenario involving an aerial imaging platform that moves and rotates over time. Many other applications are possible in processing aerial and satellite imagery.

Signal Construction-Based Dispersion Compensation of Lamb Waves Considering Signal Waveform and Amplitude Spectrum Preservation

PubMed Central

Cai, Jian; Yuan, Shenfang; Wang, Tongguang

2016-01-01

The results of Lamb wave identification for the aerospace structures could be easily affected by the nonlinear-dispersion characteristics. In this paper, dispersion compensation of Lamb waves is of particular concern. Compared with the similar research works on the traditional signal domain transform methods, this study is based on signal construction from the viewpoint of nonlinear wavenumber linearization. Two compensation methods of linearly-dispersive signal construction (LDSC) and non-dispersive signal construction (NDSC) are proposed. Furthermore, to improve the compensation effect, the influence of the signal construction process on the other crucial signal properties, including the signal waveform and amplitude spectrum, is considered during the investigation. The linear-dispersion and non-dispersion effects are firstly analyzed. Then, after the basic signal construction principle is explored, the numerical realization of LDSC and NDSC is discussed, in which the signal waveform and amplitude spectrum preservation is especially regarded. Subsequently, associated with the delay-and-sum algorithm, LDSC or NDSC is employed for high spatial resolution damage imaging, so that the adjacent multi-damage or quantitative imaging capacity of Lamb waves can be strengthened. To verify the proposed signal construction and damage imaging methods, the experimental and numerical validation is finally arranged on the aluminum plates. PMID:28772366

Robust gaze-steering of an active vision system against errors in the estimated parameters

NASA Astrophysics Data System (ADS)

Han, Youngmo

2015-01-01

Gaze-steering is often used to broaden the viewing range of an active vision system. Gaze-steering procedures are usually based on estimated parameters such as image position, image velocity, depth and camera calibration parameters. However, there may be uncertainties in these estimated parameters because of measurement noise and estimation errors. In this case, robust gaze-steering cannot be guaranteed. To compensate for such problems, this paper proposes a gaze-steering method based on a linear matrix inequality (LMI). In this method, we first propose a proportional derivative (PD) control scheme on the unit sphere that does not use depth parameters. This proposed PD control scheme can avoid uncertainties in the estimated depth and camera calibration parameters, as well as inconveniences in their estimation process, including the use of auxiliary feature points and highly non-linear computation. Furthermore, the control gain of the proposed PD control scheme on the unit sphere is designed using LMI such that the designed control is robust in the presence of uncertainties in the other estimated parameters, such as image position and velocity. Simulation results demonstrate that the proposed method provides a better compensation for uncertainties in the estimated parameters than the contemporary linear method and steers the gaze of the camera more steadily over time than the contemporary non-linear method.

Signal Construction-Based Dispersion Compensation of Lamb Waves Considering Signal Waveform and Amplitude Spectrum Preservation.

PubMed

Cai, Jian; Yuan, Shenfang; Wang, Tongguang

2016-12-23

The results of Lamb wave identification for the aerospace structures could be easily affected by the nonlinear-dispersion characteristics. In this paper, dispersion compensation of Lamb waves is of particular concern. Compared with the similar research works on the traditional signal domain transform methods, this study is based on signal construction from the viewpoint of nonlinear wavenumber linearization. Two compensation methods of linearly-dispersive signal construction (LDSC) and non-dispersive signal construction (NDSC) are proposed. Furthermore, to improve the compensation effect, the influence of the signal construction process on the other crucial signal properties, including the signal waveform and amplitude spectrum, is considered during the investigation. The linear-dispersion and non-dispersion effects are firstly analyzed. Then, after the basic signal construction principle is explored, the numerical realization of LDSC and NDSC is discussed, in which the signal waveform and amplitude spectrum preservation is especially regarded. Subsequently, associated with the delay-and-sum algorithm, LDSC or NDSC is employed for high spatial resolution damage imaging, so that the adjacent multi-damage or quantitative imaging capacity of Lamb waves can be strengthened. To verify the proposed signal construction and damage imaging methods, the experimental and numerical validation is finally arranged on the aluminum plates.

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Malenovský, Zbyněk; Van der Tol, Christiaan; Camps-Valls, Gustau; Gastellu-Etchegorry, Jean-Philippe; Lewis, Philip; North, Peter; Moreno, Jose

2018-06-01

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given.

Beam-hardening correction by a surface fitting and phase classification by a least square support vector machine approach for tomography images of geological samples

NASA Astrophysics Data System (ADS)

Khan, F.; Enzmann, F.; Kersten, M.

2015-12-01

In X-ray computed microtomography (μXCT) image processing is the most important operation prior to image analysis. Such processing mainly involves artefact reduction and image segmentation. We propose a new two-stage post-reconstruction procedure of an image of a geological rock core obtained by polychromatic cone-beam μXCT technology. In the first stage, the beam-hardening (BH) is removed applying a best-fit quadratic surface algorithm to a given image data set (reconstructed slice), which minimizes the BH offsets of the attenuation data points from that surface. The final BH-corrected image is extracted from the residual data, or the difference between the surface elevation values and the original grey-scale values. For the second stage, we propose using a least square support vector machine (a non-linear classifier algorithm) to segment the BH-corrected data as a pixel-based multi-classification task. A combination of the two approaches was used to classify a complex multi-mineral rock sample. The Matlab code for this approach is provided in the Appendix. A minor drawback is that the proposed segmentation algorithm may become computationally demanding in the case of a high dimensional training data set.

Multimodal nonlinear optical imaging of obesity-induced liver steatosis and fibrosis

NASA Astrophysics Data System (ADS)

Lin, Jian; Lu, Fake; Zheng, Wei; Tai, Dean C. S.; Yu, Hanry; Sheppard, Colin; Huang, Zhiwei

2011-03-01

Liver steatosis/fibrosis represents the major conditions and symptoms for many liver diseases. Nonlinear optical microscopy has emerged as a powerful tool for label-free tissue imaging with high sensitivity and chemical specificity for several typical biochemical compounds. Three nonlinear microscopy imaging modalities are implemented on the sectioned tissues from diseased livers induced by high fat diet (HFD). Coherent anti-Stokes Raman scattering (CARS) imaging visualizes and quantifies the lipid droplets accumulated in the liver, Second harmonic generation (SHG) is used to map the distribution of aggregated collagen fibers, and two-photon excitation fluorescence (TPEF) reveals the morphology of hepatic cells based on the autofluorescence signals from NADH and flavins within the hepatocytes. Our results demonstrate that obesity induces liver steatosis in the beginning stage, which may progress into liver fibrosis with high risk. There is a certain correlation between liver steatosis and fibrosis. This study may provide new insights into the understanding of the mechanisms of steatosis/fibrosis transformations at the cellular and molecular levels.

Graphical user interface to optimize image contrast parameters used in object segmentation - biomed 2009.

PubMed

Anderson, Jeffrey R; Barrett, Steven F

2009-01-01

Image segmentation is the process of isolating distinct objects within an image. Computer algorithms have been developed to aid in the process of object segmentation, but a completely autonomous segmentation algorithm has yet to be developed [1]. This is because computers do not have the capability to understand images and recognize complex objects within the image. However, computer segmentation methods [2], requiring user input, have been developed to quickly segment objects in serial sectioned images, such as magnetic resonance images (MRI) and confocal laser scanning microscope (CLSM) images. In these cases, the segmentation process becomes a powerful tool in visualizing the 3D nature of an object. The user input is an important part of improving the performance of many segmentation methods. A double threshold segmentation method has been investigated [3] to separate objects in gray scaled images, where the gray level of the object is among the gray levels of the background. In order to best determine the threshold values for this segmentation method the image must be manipulated for optimal contrast. The same is true of other segmentation and edge detection methods as well. Typically, the better the image contrast, the better the segmentation results. This paper describes a graphical user interface (GUI) that allows the user to easily change image contrast parameters that will optimize the performance of subsequent object segmentation. This approach makes use of the fact that the human brain is extremely effective in object recognition and understanding. The GUI provides the user with the ability to define the gray scale range of the object of interest. These lower and upper bounds of this range are used in a histogram stretching process to improve image contrast. Also, the user can interactively modify the gamma correction factor that provides a non-linear distribution of gray scale values, while observing the corresponding changes to the image. This interactive approach gives the user the power to make optimal choices in the contrast enhancement parameters.

Nonlinear time dependence of dark current in charge-coupled devices

NASA Astrophysics Data System (ADS)

Dunlap, Justin C.; Bodegom, Erik; Widenhorn, Ralf

2011-03-01

It is generally assumed that charge-coupled device (CCD) imagers produce a linear response of dark current versus exposure time except near saturation. We found a large number of pixels with nonlinear dark current response to exposure time to be present in two scientific CCD imagers. These pixels are found to exhibit distinguishable behavior with other analogous pixels and therefore can be characterized in groupings. Data from two Kodak CCD sensors are presented for exposure times from a few seconds up to two hours. Linear behavior is traditionally taken for granted when carrying out dark current correction and as a result, pixels with nonlinear behavior will be corrected inaccurately.

Autonomous control systems: applications to remote sensing and image processing

NASA Astrophysics Data System (ADS)

Jamshidi, Mohammad

2001-11-01

One of the main challenges of any control (or image processing) paradigm is being able to handle complex systems under unforeseen uncertainties. A system may be called complex here if its dimension (order) is too high and its model (if available) is nonlinear, interconnected, and information on the system is uncertain such that classical techniques cannot easily handle the problem. Examples of complex systems are power networks, space robotic colonies, national air traffic control system, and integrated manufacturing plant, the Hubble Telescope, the International Space Station, etc. Soft computing, a consortia of methodologies such as fuzzy logic, neuro-computing, genetic algorithms and genetic programming, has proven to be powerful tools for adding autonomy and semi-autonomy to many complex systems. For such systems the size of soft computing control architecture will be nearly infinite. In this paper new paradigms using soft computing approaches are utilized to design autonomous controllers and image enhancers for a number of application areas. These applications are satellite array formations for synthetic aperture radar interferometry (InSAR) and enhancement of analog and digital images.

Orientation diffusions.

PubMed

Perona, P

1998-01-01

Diffusions are useful for image processing and computer vision because they provide a convenient way of smoothing noisy data, analyzing images at multiple scales, and enhancing discontinuities. A number of diffusions of image brightness have been defined and studied so far; they may be applied to scalar and vector-valued quantities that are naturally associated with intervals of either the real line, or other flat manifolds. Some quantities of interest in computer vision, and other areas of engineering that deal with images, are defined on curved manifolds;typical examples are orientation and hue that are defined on the circle. Generalizing brightness diffusions to orientation is not straightforward, especially in the case where a discrete implementation is sought. An example of what may go wrong is presented.A method is proposed to define diffusions of orientation-like quantities. First a definition in the continuum is discussed, then a discrete orientation diffusion is proposed. The behavior of such diffusions is explored both analytically and experimentally. It is shown how such orientation diffusions contain a nonlinearity that is reminiscent of edge-process and anisotropic diffusion. A number of open questions are proposed at the end.

The crack detection algorithm of pavement image based on edge information

NASA Astrophysics Data System (ADS)

Yang, Chunde; Geng, Mingyue

2018-05-01

As the images of pavement cracks are affected by a large amount of complicated noises, such as uneven illumination and water stains, the detected cracks are discontinuous and the main body information at the edge of the cracks is easily lost. In order to solve the problem, a crack detection algorithm in pavement image based on edge information is proposed. Firstly, the image is pre-processed by the nonlinear gray-scale transform function and reconstruction filter to enhance the linear characteristic of the crack. At the same time, an adaptive thresholding method is designed to coarsely extract the cracks edge according to the gray-scale gradient feature and obtain the crack gradient information map. Secondly, the candidate edge points are obtained according to the gradient information, and the edge is detected based on the single pixel percolation processing, which is improved by using the local difference between pixels in the fixed region. Finally, complete crack is obtained by filling the crack edge. Experimental results show that the proposed method can accurately detect pavement cracks and preserve edge information.

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

PubMed Central

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

All-Optical Control of Linear and Nonlinear Energy Transfer via the Zeno Effect

NASA Astrophysics Data System (ADS)

Guo, Xiang; Zou, Chang-Ling; Jiang, Liang; Tang, Hong X.

2018-05-01

Microresonator-based nonlinear processes are fundamental to applications including microcomb generation, parametric frequency conversion, and harmonics generation. While nonlinear processes involving either second- (χ(2 )) or third- (χ(3 )) order nonlinearity have been extensively studied, the interaction between these two basic nonlinear processes has seldom been reported. In this paper we demonstrate a coherent interplay between second- and third- order nonlinear processes. The parametric (χ(2 ) ) coupling to a lossy ancillary mode shortens the lifetime of the target photonic mode and suppresses its density of states, preventing the photon emissions into the target photonic mode via the Zeno effect. Such an effect is then used to control the stimulated four-wave mixing process and realize a suppression ratio of 34.5.

Nonlinear Real-Time Optical Signal Processing.

DTIC Science & Technology

1981-06-30

bandwidth and space-bandwidth products. Real-time homonorphic and loga- rithmic filtering by halftone nonlinear processing has been achieved. A...Page ABSTRACT 1 1. RESEARCH OBJECTIVES AND PROGRESS 3 I-- 1.1 Introduction and Project overview 3 1.2 Halftone Processing 9 1.3 Direct Nonlinear...time homomorphic and logarithmic filtering by halftone nonlinear processing has been achieved. A detailed analysis of degradation due to the finite gamma

Autofocus and fusion using nonlinear correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cabazos-Marín, Alma Rocío; Álvarez-Borrego, Josué, E-mail: josue@cicese.mx; Coronel-Beltrán, Ángel

2014-10-06

In this work a new algorithm is proposed for auto focusing and images fusion captured by microscope's CCD. The proposed algorithm for auto focusing implements the spiral scanning of each image in the stack f(x, y){sub w} to define the V{sub w} vector. The spectrum of the vector FV{sub w} is calculated by fast Fourier transform. The best in-focus image is determined by a focus measure that is obtained by the FV{sub 1} nonlinear correlation vector, of the reference image, with each other FV{sub W} images in the stack. In addition, fusion is performed with a subset of selected imagesmore » f(x, y){sub SBF} like the images with best focus measurement. Fusion creates a new improved image f(x, y){sub F} with the selection of pixels of higher intensity.« less

Non-Linearity in Wide Dynamic Range CMOS Image Sensors Utilizing a Partial Charge Transfer Technique.

PubMed

Shafie, Suhaidi; Kawahito, Shoji; Halin, Izhal Abdul; Hasan, Wan Zuha Wan

2009-01-01

The partial charge transfer technique can expand the dynamic range of a CMOS image sensor by synthesizing two types of signal, namely the long and short accumulation time signals. However the short accumulation time signal obtained from partial transfer operation suffers of non-linearity with respect to the incident light. In this paper, an analysis of the non-linearity in partial charge transfer technique has been carried, and the relationship between dynamic range and the non-linearity is studied. The results show that the non-linearity is caused by two factors, namely the current diffusion, which has an exponential relation with the potential barrier, and the initial condition of photodiodes in which it shows that the error in the high illumination region increases as the ratio of the long to the short accumulation time raises. Moreover, the increment of the saturation level of photodiodes also increases the error in the high illumination region.

Applications of compressed sensing image reconstruction to sparse view phase tomography

NASA Astrophysics Data System (ADS)

Ueda, Ryosuke; Kudo, Hiroyuki; Dong, Jian

2017-10-01

X-ray phase CT has a potential to give the higher contrast in soft tissue observations. To shorten the measure- ment time, sparse-view CT data acquisition has been attracting the attention. This paper applies two major compressed sensing (CS) approaches to image reconstruction in the x-ray sparse-view phase tomography. The first CS approach is the standard Total Variation (TV) regularization. The major drawbacks of TV regularization are a patchy artifact and loss in smooth intensity changes due to the piecewise constant nature of image model. The second CS method is a relatively new approach of CS which uses a nonlinear smoothing filter to design the regularization term. The nonlinear filter based CS is expected to reduce the major artifact in the TV regular- ization. The both cost functions can be minimized by the very fast iterative reconstruction method. However, in the past research activities, it is not clearly demonstrated how much image quality difference occurs between the TV regularization and the nonlinear filter based CS in x-ray phase CT applications. We clarify the issue by applying the two CS applications to the case of x-ray phase tomography. We provide results with numerically simulated data, which demonstrates that the nonlinear filter based CS outperforms the TV regularization in terms of textures and smooth intensity changes.

Detection and measurement of tubulitis in renal allograft rejection

NASA Astrophysics Data System (ADS)

Hiller, John B.; Chen, Qi; Jin, Jesse S.; Wang, Yung; Yong, James L. C.

1997-04-01

Tubulitis is one of the most reliable signs of acute renal allograft rejection. It occurs when mononuclear cells are localized between the lining tubular epithelial cells with or without disruption of the tubular basement membrane. It has been found that tubulitis takes place predominantly in the regions of the distal convoluted tubules and the cortical collecting system. The image processing tasks are to find the tubule boundaries and to find the relative location of the lymphocytes and epithelial cells and tubule boundaries. The requirement for accuracy applies to determining the relative locations of the lymphocytes and the tubule boundaries. This paper will show how the different sizes and grey values of the lymphocytes and epithelial cells simplify their identification and location. Difficulties in finding the tubule boundaries image processing will be illustrated. It will be shown how proximate location of epithelial cells and the tubule boundary leads to distortion in determination of the calculated boundary. However, in tubulitis the lymphocytes and the tubule boundaries are proximate.In these cases the tubule boundary is adequately resolved and the image processing is satisfactory to determining relativity in location. An adaptive non-linear anisotropic diffusion process is presented for image filtering and segmentation. Multi-layer analysis is used to extract lymphocytes and tubulitis from images. This paper will discuss grading of tissue using the Banff system. The ability to use computer to use computer processing will be argued as obviating problems of reproducability of values for this classification. This paper will also feature discussion of alternative approaches to image processing and provide an assessment of their capability for improving the identification of the tubule boundaries.

Initial On-Orbit Spatial Resolution Characterization of OrbView-3 Panchromatic Images

NASA Technical Reports Server (NTRS)

Blonski, Slawomir

2006-01-01

Characterization was conducted under the Memorandum of Understanding among Orbital Sciences Corp., ORBIMAGE, Inc., and NASA Applied Sciences Directorate. Acquired five OrbView-3 panchromatic images of the permanent Stennis Space Center edge targets painted on a concrete surface. Each image is available at two processing levels: Georaw and Basic. Georaw is an intermediate image in which individual pixels are aligned by a nominal shift in the along-scan direction to adjust for the staggered layout of the panchromatic detectors along the focal plane array. Georaw images are engineering data and are not delivered to customers. The Basic product includes a cubic interpolation to align the pixels better along the focal plane and to correct for sensor artifacts, such as smile and attitude smoothing. This product retains satellite geometry - no rectification is performed. Processing of the characterized images did not include image sharpening, which is applied by default to OrbView-3 image products delivered by ORBIMAGE to customers. Edge responses were extracted from images of tilted edges in two directions: along-scan and cross-scan. Each edge response was approximated with a superposition of three sigmoidal functions through a nonlinear least-squares curve-fitting. Line Spread Functions (LSF) were derived by differentiation of the analytical approximation. Modulation Transfer Functions (MTF) were obtained after applying the discrete Fourier transform to the LSF.

Image restoration and superresolution as probes of small scale far-IR structure in star forming regions

NASA Technical Reports Server (NTRS)

Lester, D. F.; Harvey, P. M.; Joy, M.; Ellis, H. B., Jr.

1986-01-01

Far-infrared continuum studies from the Kuiper Airborne Observatory are described that are designed to fully exploit the small-scale spatial information that this facility can provide. This work gives the clearest picture to data on the structure of galactic and extragalactic star forming regions in the far infrared. Work is presently being done with slit scans taken simultaneously at 50 and 100 microns, yielding one-dimensional data. Scans of sources in different directions have been used to get certain information on two dimensional structure. Planned work with linear arrays will allow us to generalize our techniques to two dimensional image restoration. For faint sources, spatial information at the diffraction limit of the telescope is obtained, while for brighter sources, nonlinear deconvolution techniques have allowed us to improve over the diffraction limit by as much as a factor of four. Information on the details of the color temperature distribution is derived as well. This is made possible by the accuracy with which the instrumental point-source profile (PSP) is determined at both wavelengths. While these two PSPs are different, data at different wavelengths can be compared by proper spatial filtering. Considerable effort has been devoted to implementing deconvolution algorithms. Nonlinear deconvolution methods offer the potential of superresolution -- that is, inference of power at spatial frequencies that exceed D lambda. This potential is made possible by the implicit assumption by the algorithm of positivity of the deconvolved data, a universally justifiable constraint for photon processes. We have tested two nonlinear deconvolution algorithms on our data; the Richardson-Lucy (R-L) method and the Maximum Entropy Method (MEM). The limits of image deconvolution techniques for achieving spatial resolution are addressed.

Poster — Thur Eve — 44: Linearization of Compartmental Models for More Robust Estimates of Regional Hemodynamic, Metabolic and Functional Parameters using DCE-CT/PET Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blais, AR; Dekaban, M; Lee, T-Y

2014-08-15

Quantitative analysis of dynamic positron emission tomography (PET) data usually involves minimizing a cost function with nonlinear regression, wherein the choice of starting parameter values and the presence of local minima affect the bias and variability of the estimated kinetic parameters. These nonlinear methods can also require lengthy computation time, making them unsuitable for use in clinical settings. Kinetic modeling of PET aims to estimate the rate parameter k{sub 3}, which is the binding affinity of the tracer to a biological process of interest and is highly susceptible to noise inherent in PET image acquisition. We have developed linearized kineticmore » models for kinetic analysis of dynamic contrast enhanced computed tomography (DCE-CT)/PET imaging, including a 2-compartment model for DCE-CT and a 3-compartment model for PET. Use of kinetic parameters estimated from DCE-CT can stabilize the kinetic analysis of dynamic PET data, allowing for more robust estimation of k{sub 3}. Furthermore, these linearized models are solved with a non-negative least squares algorithm and together they provide other advantages including: 1) only one possible solution and they do not require a choice of starting parameter values, 2) parameter estimates are comparable in accuracy to those from nonlinear models, 3) significantly reduced computational time. Our simulated data show that when blood volume and permeability are estimated with DCE-CT, the bias of k{sub 3} estimation with our linearized model is 1.97 ± 38.5% for 1,000 runs with a signal-to-noise ratio of 10. In summary, we have developed a computationally efficient technique for accurate estimation of k{sub 3} from noisy dynamic PET data.« less

Femtosecond pulsed laser processing of electronic materials: Fundamentals and micro/nano-scale applications

NASA Astrophysics Data System (ADS)

Choi, Tae-Youl

Ultra-short pulsed laser radiation has been shown to be effective for precision materials processing and surface micro-modification. One of advantages is the substantial reduction of the heat penetration depth, which leads to minimal lateral damage. Other advantages include non-thermal nature of ablation process, controlled ablation and ideal characteristics for precision micro-structuring. Yet, fundamental questions remain unsolved regarding the nature of melting and ablation mechanisms in femtosecond laser processing of materials. In addition to micro engineering problems, nano-structuring and nano-fabrication are emerging fields that are of particular interest in conjunction with femtosecond laser processing. A comprehensive experimental study as well as theoretical development is presented to address these issues. Ultra-short pulsed laser irradiation was used to crystallize 100 nm amorphous silicon (a-Si) films. The crystallization process was observed by time-resolved pump-and-probe reflection imaging in the range of 0.2 ps to 100 ns. The in-situ images in conjunction with post-processed SEM and AFM mapping of the crystallized structure provide evidence for non-thermal ultra-fast phase transition and subsequent surface-initiated crystallization. Mechanisms of ultra-fast laser-induced ablation on crystalline silicon and copper are investigated by time-resolved pump-and-probe microscopy in normal imaging and shadowgraph arrangements. A one-dimensional model of the energy transport is utilized to predict the carrier temperature and lattice temperature as well as the electron and vapor flux emitted from the surface. The temporal delay between the pump and probe pulses was set by a precision translation stage up to about 500 ps and then extended to the nanosecond regime by an optical fiber assembly. The ejection of material was observed at several picoseconds to tens of nanoseconds after the main (pump) pulse by high-resolution, ultra-fast shadowgraphs. The ultrashort laser pulse accompanied by the pre-pulse induces air breakdown that can be detrimental to materials processing. A time-resolved pump-and-probe experiment provides distinct evidence for the occurrence of an air plasma and air breakdown. This highly nonlinear phenomenon takes place before the commencement of the ablation process, which is traced beyond elapsed time of the order of 10 ps with respect to the ablating pulse. The nonlinear refractive index of the generated air plasma is calculated as a function of electron density. The self-focusing of the main pulse is identified by the third order nonlinear susceptibility. A crystalline silicon sample is subjected to two optically separated ultra-fast laser pulses of full-width-half-maximum (FWHM) duration of about 80 femtoseconds. These pulses are delivered at wavelength, lambda = 800 nm. Femtosecond-resolved imaging pump-and-probe experiments in reflective and Schlieren configurations have been performed to investigate plasma dynamics and shock wave propagation during the sample ablation process. By using a diffractive optical element (DOE) for beam shaping, microchannels were fabricated. A super-long working distance objective lens was used to machine silicon materials in the sub-micrometer scale. As an extension of micro-machining, the finite difference time domain (FDTD) method is used to assess the feasibility of using near-field distribution of laser light. Gold coated films were machined with nano-scale dimensions and characterized with atomic force microscopy (AFM).

Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration.

PubMed

Wittek, Adam; Joldes, Grand; Couton, Mathieu; Warfield, Simon K; Miller, Karol

2010-12-01

Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using an NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer. Copyright © 2010 Elsevier Ltd. All rights reserved.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Overlay of multiframe SEM images including nonlinear field distortions

NASA Astrophysics Data System (ADS)

Babin, S.; Borisov, S.; Ivonin, I.; Nakazawa, S.; Yamazaki, Y.

2018-03-01

To reduce charging and shrinkage, CD-SEMs utilize low electron energies and multiframe imaging. This results in every next frame being altered due to stage and beam instability, as well as due to charging. Regular averaging of the frames blurs the edges; this directly effects the extracted values of critical dimensions. A technique was developed to overlay multiframe images without the loss of quality. This method takes into account drift, rotation, and magnification corrections, as well as nonlinear distortions due to wafer charging. A significant improvement in the signal to noise ratio and overall image quality without degradation of the feature's edge quality was achieved. The developed software is capable of working with regular and large size images up to 32K pixels in each direction.

Second-harmonic generation imaging of collagen fibers in myocardium for atrial fibrillation diagnosis

NASA Astrophysics Data System (ADS)

Tsai, Ming-Rung; Chiu, Yu-Wei; Lo, Men Tzung; Sun, Chi-Kuang

2010-03-01

Atrial fibrillation (AF) is the most common irregular heart rhythm and the mortality rate for patients with AF is approximately twice the mortality rate for patients with normal sinus rhythm (NSR). Some research has indicated that myocardial fibrosis plays an important role in predisposing patients to AF. Therefore, realizing the relationship between myocardial collagen fibrosis and AF is significant. Second-harmonic generation (SHG) is an optically nonlinear coherent process to image the collagen network. We perform SHG microscopic imaging of the collagen fibers in the human atrial myocardium. Utilizing the SHG images, we can identify the differences in morphology and the arrangement of collagen fibers between NSR and AF tissues. We also quantify the arrangement of the collagen fibers using Fourier transform images and calculating the values of angle entropy. We indicate that SHG imaging, a nondestructive and reproducible method to analyze the arrangement of collagen fibers, can provide explicit information about the relationship between myocardial fibrosis and AF.

Imaging complex objects using learning tomography

NASA Astrophysics Data System (ADS)

Lim, JooWon; Goy, Alexandre; Shoreh, Morteza Hasani; Unser, Michael; Psaltis, Demetri

2018-02-01

Optical diffraction tomography (ODT) can be described using the scattering process through an inhomogeneous media. An inherent nonlinearity exists relating the scattering medium and the scattered field due to multiple scattering. Multiple scattering is often assumed to be negligible in weakly scattering media. This assumption becomes invalid as the sample gets more complex resulting in distorted image reconstructions. This issue becomes very critical when we image a complex sample. Multiple scattering can be simulated using the beam propagation method (BPM) as the forward model of ODT combined with an iterative reconstruction scheme. The iterative error reduction scheme and the multi-layer structure of BPM are similar to neural networks. Therefore we refer to our imaging method as learning tomography (LT). To fairly assess the performance of LT in imaging complex samples, we compared LT with the conventional iterative linear scheme using Mie theory which provides the ground truth. We also demonstrate the capacity of LT to image complex samples using experimental data of a biological cell.

Super Resolution Algorithm for CCTVs

NASA Astrophysics Data System (ADS)

Gohshi, Seiichi

2015-03-01

Recently, security cameras and CCTV systems have become an important part of our daily lives. The rising demand for such systems has created business opportunities in this field, especially in big cities. Analogue CCTV systems are being replaced by digital systems, and HDTV CCTV has become quite common. HDTV CCTV can achieve images with high contrast and decent quality if they are clicked in daylight. However, the quality of an image clicked at night does not always have sufficient contrast and resolution because of poor lighting conditions. CCTV systems depend on infrared light at night to compensate for insufficient lighting conditions, thereby producing monochrome images and videos. However, these images and videos do not have high contrast and are blurred. We propose a nonlinear signal processing technique that significantly improves visual and image qualities (contrast and resolution) of low-contrast infrared images. The proposed method enables the use of infrared cameras for various purposes such as night shot and poor lighting environments under poor lighting conditions.

High power THz sources for nonlinear imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tekavec, Patrick F.; Kozlov, Vladimir G.

2014-02-18

Many biological and chemical compounds have unique absorption features in the THz (0.1 - 10 THz) region, making the use of THz waves attractive for imaging in defense, security, biomedical imaging, and monitoring of industrial processes. Unlike optical radiation, THz frequencies can pass through many substances such as paper, clothing, ceramic, etc. with little attenuation. The use of currently available THz systems is limited by lack of highpower, sources as well as sensitive detectors and detector arrays operating at room temperature. Here we present a novel, high power THz source based on intracavity downconverison of optical pulses. The source deliversmore » 6 ps pulses at 1.5 THz, with an average power of >300 μW and peak powers >450 mW. We propose an imaging method based on frequency upconverison that is ideally suited to use the narrow bandwidth and high peak powers produced by the source. By upconverting the THz image to the infrared, commercially available detectors can be used for real time imaging.« less

High power THz sources for nonlinear imaging

NASA Astrophysics Data System (ADS)

Tekavec, Patrick F.; Kozlov, Vladimir G.

2014-02-01

Many biological and chemical compounds have unique absorption features in the THz (0.1 - 10 THz) region, making the use of THz waves attractive for imaging in defense, security, biomedical imaging, and monitoring of industrial processes. Unlike optical radiation, THz frequencies can pass through many substances such as paper, clothing, ceramic, etc. with little attenuation. The use of currently available THz systems is limited by lack of highpower, sources as well as sensitive detectors and detector arrays operating at room temperature. Here we present a novel, high power THz source based on intracavity downconverison of optical pulses. The source delivers 6 ps pulses at 1.5 THz, with an average power of >300 μW and peak powers >450 mW. We propose an imaging method based on frequency upconverison that is ideally suited to use the narrow bandwidth and high peak powers produced by the source. By upconverting the THz image to the infrared, commercially available detectors can be used for real time imaging.

CLASSIFYING MEDICAL IMAGES USING MORPHOLOGICAL APPEARANCE MANIFOLDS.

PubMed

Varol, Erdem; Gaonkar, Bilwaj; Davatzikos, Christos

2013-12-31

Input features for medical image classification algorithms are extracted from raw images using a series of pre processing steps. One common preprocessing step in computational neuroanatomy and functional brain mapping is the nonlinear registration of raw images to a common template space. Typically, the registration methods used are parametric and their output varies greatly with changes in parameters. Most results reported previously perform registration using a fixed parameter setting and use the results as input to the subsequent classification step. The variation in registration results due to choice of parameters thus translates to variation of performance of the classifiers that depend on the registration step for input. Analogous issues have been investigated in the computer vision literature, where image appearance varies with pose and illumination, thereby making classification vulnerable to these confounding parameters. The proposed methodology addresses this issue by sampling image appearances as registration parameters vary, and shows that better classification accuracies can be obtained this way, compared to the conventional approach.

Self-phase modulation and two-photon absorption imaging of cells and active neurons

NASA Astrophysics Data System (ADS)

Fischer, Martin C.; Liu, Henry; Piletic, Ivan R.; Ye, Tong; Yasuda, Ryohei; Warren, Warren S.

2007-02-01

Even though multi-photon fluorescence microscopy offers higher resolution and better penetration depth than traditional fluorescence microscopy, its use is restricted to the detection of molecules that fluoresce. Two-photon absorption (TPA) imaging can provide contrast in non-fluorescent molecules while retaining the high resolution and sectioning capabilities of nonlinear imaging modalities. In the long-wavelength water window, tissue TPA is dominated by the endogenous molecules melanin and hemoglobin with an almost complete absence of endogenous two-photon fluorescence. A complementary nonlinear contrast mechanism is self-phase modulation (SPM), which can provide intrinsic signatures that can depend on local tissue anisotropy, chemical environment, or other structural properties. We have developed a spectral hole refilling measurement technique for TPA and SPM measurements using shaped ultrafast laser pulses. Here we report on a microscopy setup to simultaneously acquire 3D, high-resolution TPA and SPM images. We have acquired data in mounted B16 melanoma cells with very modest laser power levels. We will also discuss the possible application of this measurement technique to neuronal imaging. Since SPM is sensitive to material structure we can expect SPM properties of neurons to change during neuronal firing. Using our hole-refilling technique we have now demonstrated strong novel intrinsic nonlinear signatures of neuronal activation in a hippocampal brain slice. The observed changes in nonlinear signal upon collective activation were up to factors of two, unlike other intrinsic optical signal changes on the percent level. These results show that TPA and SPM imaging can provide important novel functional contrast in tissue using very modest power levels suitable for in vivo applications.

Dispersion-based stimulated Raman scattering spectroscopy, holography, and optical coherence tomography

PubMed Central

Robles, Francisco E.; Fischer, Martin C.; Warren, Warren S.

2016-01-01

Stimulated Raman scattering (SRS) enables fast, high resolution imaging of chemical constituents important to biological structures and functional processes, both in a label-free manner and using exogenous biomarkers. While this technology has shown remarkable potential, it is currently limited to point scanning and can only probe a few Raman bands at a time (most often, only one). In this work we take a fundamentally different approach to detecting the small nonlinear signals based on dispersion effects that accompany the loss/gain processes in SRS. In this proof of concept, we demonstrate that the dispersive measurements are more robust to noise compared to amplitude-based measurements, which then permit spectral or spatial multiplexing (potentially both, simultaneously). Finally, we illustrate how this method may enable different strategies for biochemical imaging using phase microscopy and optical coherence tomography. PMID:26832279

Estimation of Image Sensor Fill Factor Using a Single Arbitrary Image

PubMed Central

Wen, Wei; Khatibi, Siamak

2017-01-01

Achieving a high fill factor is a bottleneck problem for capturing high-quality images. There are hardware and software solutions to overcome this problem. In the solutions, the fill factor is known. However, this is an industrial secrecy by most image sensor manufacturers due to its direct effect on the assessment of the sensor quality. In this paper, we propose a method to estimate the fill factor of a camera sensor from an arbitrary single image. The virtual response function of the imaging process and sensor irradiance are estimated from the generation of virtual images. Then the global intensity values of the virtual images are obtained, which are the result of fusing the virtual images into a single, high dynamic range radiance map. A non-linear function is inferred from the original and global intensity values of the virtual images. The fill factor is estimated by the conditional minimum of the inferred function. The method is verified using images of two datasets. The results show that our method estimates the fill factor correctly with significant stability and accuracy from one single arbitrary image according to the low standard deviation of the estimated fill factors from each of images and for each camera. PMID:28335459

All-optical regenerator of multi-channel signals.

PubMed

Li, Lu; Patki, Pallavi G; Kwon, Young B; Stelmakh, Veronika; Campbell, Brandon D; Annamalai, Muthiah; Lakoba, Taras I; Vasilyev, Michael

2017-10-12

One of the main reasons why nonlinear-optical signal processing (regeneration, logic, etc.) has not yet become a practical alternative to electronic processing is that the all-optical elements with nonlinear input-output relationship have remained inherently single-channel devices (just like their electronic counterparts) and, hence, cannot fully utilise the parallel processing potential of optical fibres and amplifiers. The nonlinear input-output transfer function requires strong optical nonlinearity, e.g. self-phase modulation, which, for fundamental reasons, is always accompanied by cross-phase modulation and four-wave mixing. In processing multiple wavelength-division-multiplexing channels, large cross-phase modulation and four-wave mixing crosstalks among the channels destroy signal quality. Here we describe a solution to this problem: an optical signal processor employing a group-delay-managed nonlinear medium where strong self-phase modulation is achieved without such nonlinear crosstalk. We demonstrate, for the first time to our knowledge, simultaneous all-optical regeneration of up to 16 wavelength-division-multiplexing channels by one device. This multi-channel concept can be extended to other nonlinear-optical processing schemes.Nonlinear optical processing devices are not yet fully practical as they are single channel. Here the authors demonstrate all-optical regeneration of up to 16 channels by one device, employing a group-delay-managed nonlinear medium where strong self-phase modulation is achieved without nonlinear inter-channel crosstalk.

Nonlinear dynamics that appears in the dynamical model of drying process of a polymer solution coated on a flat substrate

NASA Astrophysics Data System (ADS)

Kagami, Hiroyuki

2007-01-01

We have proposed and modified the dynamical model of drying process of polymer solution coated on a flat substrate for flat polymer film fabrication and have presented the fruits through some meetings and so on. Though basic equations of the dynamical model have characteristic nonlinearity, character of the nonlinearity has not been studied enough yet. In this paper, at first, we derive nonlinear equations from the dynamical model of drying process of polymer solution. Then we introduce results of numerical simulations of the nonlinear equations and consider roles of various parameters. Some of them are indirectly concerned in strength of non-equilibriumity. Through this study, we approach essential qualities of nonlinearity in non-equilibrium process of drying process.

Nonlinear ultrasonic stimulated thermography for damage assessment in isotropic fatigued structures

NASA Astrophysics Data System (ADS)

Fierro, Gian Piero Malfense; Calla', Danielle; Ginzburg, Dmitri; Ciampa, Francesco; Meo, Michele

2017-09-01

Traditional non-destructive evaluation (NDE) and structural health monitoring (SHM) systems are used to analyse that a structure is free of any harmful damage. However, these techniques still lack sensitivity to detect the presence of material micro-flaws in the form of fatigue damage and often require time-consuming procedures and expensive equipment. This research work presents a novel "nonlinear ultrasonic stimulated thermography" (NUST) method able to overcome some of the limitations of traditional linear ultrasonic/thermography NDE-SHM systems and to provide a reliable, rapid and cost effective estimation of fatigue damage in isotropic materials. Such a hybrid imaging approach combines the high sensitivity of nonlinear acoustic/ultrasonic techniques to detect micro-damage, with local defect frequency selection and infrared imaging. When exciting structures with an optimised frequency, nonlinear elastic waves are observed and higher frictional work at the fatigue damaged area is generated due to clapping and rubbing of the crack faces. This results in heat at cracked location that can be measured using an infrared camera. A Laser Vibrometer (LV) was used to evaluate the extent that individual frequency components contribute to the heating of the damage region by quantifying the out-of-plane velocity associated with the fundamental and second order harmonic responses. It was experimentally demonstrated the relationship between a nonlinear ultrasound parameter (βratio) of the material nonlinear response to the actual temperature rises near the crack. These results demonstrated that heat generation at damaged regions could be amplified by exciting at frequencies that provide nonlinear responses, thus improving the imaging of material damage and the reliability of NUST in a quick and reproducible manner.

Fault Detection for Nonlinear Process With Deterministic Disturbances: A Just-In-Time Learning Based Data Driven Method.

PubMed

Yin, Shen; Gao, Huijun; Qiu, Jianbin; Kaynak, Okyay

2017-11-01

Data-driven fault detection plays an important role in industrial systems due to its applicability in case of unknown physical models. In fault detection, disturbances must be taken into account as an inherent characteristic of processes. Nevertheless, fault detection for nonlinear processes with deterministic disturbances still receive little attention, especially in data-driven field. To solve this problem, a just-in-time learning-based data-driven (JITL-DD) fault detection method for nonlinear processes with deterministic disturbances is proposed in this paper. JITL-DD employs JITL scheme for process description with local model structures to cope with processes dynamics and nonlinearity. The proposed method provides a data-driven fault detection solution for nonlinear processes with deterministic disturbances, and owns inherent online adaptation and high accuracy of fault detection. Two nonlinear systems, i.e., a numerical example and a sewage treatment process benchmark, are employed to show the effectiveness of the proposed method.

Analytical Model of the Nonlinear Dynamics of Cantilever Tip-Sample Surface Interactions for Various Acoustic-Atomic Force Microscopies

NASA Technical Reports Server (NTRS)

Cantrell, John H., Jr.; Cantrell, Sean A.

2008-01-01

A comprehensive analytical model of the interaction of the cantilever tip of the atomic force microscope (AFM) with the sample surface is developed that accounts for the nonlinearity of the tip-surface interaction force. The interaction is modeled as a nonlinear spring coupled at opposite ends to linear springs representing cantilever and sample surface oscillators. The model leads to a pair of coupled nonlinear differential equations that are solved analytically using a standard iteration procedure. Solutions are obtained for the phase and amplitude signals generated by various acoustic-atomic force microscope (A-AFM) techniques including force modulation microscopy, atomic force acoustic microscopy, ultrasonic force microscopy, heterodyne force microscopy, resonant difference-frequency atomic force ultrasonic microscopy (RDF-AFUM), and the commonly used intermittent contact mode (TappingMode) generally available on AFMs. The solutions are used to obtain a quantitative measure of image contrast resulting from variations in the Young modulus of the sample for the amplitude and phase images generated by the A-AFM techniques. Application of the model to RDF-AFUM and intermittent soft contact phase images of LaRC-cp2 polyimide polymer is discussed. The model predicts variations in the Young modulus of the material of 24 percent from the RDF-AFUM image and 18 percent from the intermittent soft contact image. Both predictions are in good agreement with the literature value of 21 percent obtained from independent, macroscopic measurements of sheet polymer material.

Whole-body PET parametric imaging employing direct 4D nested reconstruction and a generalized non-linear Patlak model

NASA Astrophysics Data System (ADS)

Karakatsanis, Nicolas A.; Rahmim, Arman

2014-03-01

Graphical analysis is employed in the research setting to provide quantitative estimation of PET tracer kinetics from dynamic images at a single bed. Recently, we proposed a multi-bed dynamic acquisition framework enabling clinically feasible whole-body parametric PET imaging by employing post-reconstruction parameter estimation. In addition, by incorporating linear Patlak modeling within the system matrix, we enabled direct 4D reconstruction in order to effectively circumvent noise amplification in dynamic whole-body imaging. However, direct 4D Patlak reconstruction exhibits a relatively slow convergence due to the presence of non-sparse spatial correlations in temporal kinetic analysis. In addition, the standard Patlak model does not account for reversible uptake, thus underestimating the influx rate Ki. We have developed a novel whole-body PET parametric reconstruction framework in the STIR platform, a widely employed open-source reconstruction toolkit, a) enabling accelerated convergence of direct 4D multi-bed reconstruction, by employing a nested algorithm to decouple the temporal parameter estimation from the spatial image update process, and b) enhancing the quantitative performance particularly in regions with reversible uptake, by pursuing a non-linear generalized Patlak 4D nested reconstruction algorithm. A set of published kinetic parameters and the XCAT phantom were employed for the simulation of dynamic multi-bed acquisitions. Quantitative analysis on the Ki images demonstrated considerable acceleration in the convergence of the nested 4D whole-body Patlak algorithm. In addition, our simulated and patient whole-body data in the postreconstruction domain indicated the quantitative benefits of our extended generalized Patlak 4D nested reconstruction for tumor diagnosis and treatment response monitoring.

A Locally Generated High-Mode Nonlinear Internal Wave Detected on the Shelf of the Northern South China Sea From Marine Seismic Observations

NASA Astrophysics Data System (ADS)

Tang, Qunshu; Xu, Min; Zheng, Chan; Xu, Xing; Xu, Jiang

2018-02-01

In this work, a secondary nonlinear internal wave (NIW) on the continental shelf of the northern South China Sea is investigated using high-resolution seismic imaging and joint inversion of water structure properties combined with in situ hydrographic observations. It is an extraordinary wave combination with two mode-2 NIWs and one elevated NIW occurring within a short distance of 2 km. The most energetic part of the NIW could be regarded as a mode-2 NIW in the upper layer between 40 and 120 m depth. The vertical particle velocity of ˜41 cm/s may exceed the critical value of wave breaking and thus collapse the strong stratification followed by a series of processes including internal wave breaking, overturning, Kelvin-Helmholtz instability, stratification splitting, and eventual restratification. Among these processes, the shear-induced Kelvin-Helmholtz instability is directly imaged using the seismic method for the first time. The stratification splitting and restratification show that the unstable stage lasts only for a few hours and spans several kilometers. It is a new observation that the elevated NIW could be generated in a deepwater region (as deep as ˜370 m). Different from the periodical NIWs originating from the Luzon Strait, this secondary NIW is most likely generated locally, at the continental shelf break during ebb tide.

A Core-Particle Model for Periodically Focused Ion Beams with Intense Space-Charge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lund, S M; Barnard, J J; Bukh, B

2006-08-02

A core-particle model is derived to analyze transverse orbits of test particles evolving in the presence of a core ion beam described by the KV distribution. The core beam has uniform density within an elliptical cross-section and can be applied to model both quadrupole and solenoidal focused beams in periodic or aperiodic lattices. Efficient analytical descriptions of electrostatic space-charge fields external to the beam core are derived to simplify model equations. Image charge effects are analyzed for an elliptical beam centered in a round, conducting pipe to estimate model corrections resulting from image charge nonlinearities. Transformations are employed to removemore » coherent utter motion associated with oscillations of the ion beam core due to rapidly varying, linear applied focusing forces. Diagnostics for particle trajectories, Poincare phase-space projections, and single-particle emittances based on these transformations better illustrate the effects of nonlinear forces acting on particles evolving outside the core. A numerical code has been written based on this model. Example applications illustrate model characteristics. The core-particle model described has recently been applied to identify physical processes leading to space-charge transport limits for an rms matched beam in a periodic quadrupole focusing channel [Lund and Chawla, Nuc. Instr. and Meth. A 561, 203 (2006)]. Further characteristics of these processes are presented here.« less

Comparison of in vivo and ex vivo imaging of the microvasculature with 2-photon fluorescence microscopy

NASA Astrophysics Data System (ADS)

Steinman, Joe; Koletar, Margaret; Stefanovic, Bojana; Sled, John G.

2016-03-01

This study evaluates 2-Photon fluorescence microscopy of in vivo and ex vivo cleared samples for visualizing cortical vasculature. Four mice brains were imaged with in vivo 2PFM. Mice were then perfused with a FITC gel and cleared in fructose. The same regions imaged in vivo were imaged ex vivo. Vessels were segmented automatically in both images using an in-house developed algorithm that accounts for the anisotropic and spatially varying PSF ex vivo. Through non-linear warping, the ex vivo image and tracing were aligned to the in vivo image. The corresponding vessels were identified through a local search algorithm. This enabled comparison of identical vessels in vivo/ex vivo. A similar process was conducted on the in vivo tracing to determine the percentage of vessels perfused. Of all the vessels identified over the four brains in vivo, 98% were present ex vivo. There was a trend towards reduced vessel diameter ex vivo by 12.7%, and the shrinkage varied between specimens (0% to 26%). Large diameter surface vessels, through a process termed 'shadowing', attenuated in vivo signal from deeper cortical vessels by 40% at 300 μm below the cortical surface, which does not occur ex vivo. In summary, though there is a mean diameter shrinkage ex vivo, ex vivo imaging has a reduced shadowing artifact. Additionally, since imaging depths are only limited by the working distance of the microscope objective, ex vivo imaging is more suitable for imaging large portions of the brain.

Towards two-photon excited endogenous fluorescence lifetime imaging microendoscopy

PubMed Central

Hage, C. H.; Leclerc, P.; Brevier, J.; Fabert, M.; Le Nézet, C.; Kudlinski, A.; Héliot, L.; Louradour, F.

2017-01-01

In situ fluorescence lifetime imaging microscopy (FLIM) in an endoscopic configuration of the endogenous biomarker nicotinamide adenine dinucleotide (NADH) has a great potential for malignant tissue diagnosis. Moreover, two-photon nonlinear excitation provides intrinsic optical sectioning along with enhanced imaging depth. We demonstrate, for the first time to our knowledge, nonlinear endogenous FLIM in a fibered microscope with proximal detection, applied to NADH in cultured cells, as a first step to a nonlinear endomicroscope, using a double-clad microstructured fiber with convenient fiber length (> 3 m) and excitation pulse duration (≈50 fs). Fluorescence photons are collected by the fiber inner cladding and we show that its contribution to the impulse response function (IRF), which originates from its intermodal and chromatic dispersions, is small (< 600 ps) and stable for lengths up to 8 m and allows for short lifetime measurements. We use the phasor representation as a quick visualization tool adapted to the endoscopy speed requirements. PMID:29359093

Breaking the acoustic diffraction limit via nonlinear effect and thermal confinement for potential deep-tissue high-resolution imaging

PubMed Central

Yuan, Baohong; Pei, Yanbo; Kandukuri, Jayanth

2013-01-01

Our recently developed ultrasound-switchable fluorescence (USF) imaging technique showed that it was feasible to conduct high-resolution fluorescence imaging in a centimeter-deep turbid medium. Because the spatial resolution of this technique highly depends on the ultrasound-induced temperature focal size (UTFS), minimization of UTFS becomes important for further improving the spatial resolution USF technique. In this study, we found that UTFS can be significantly reduced below the diffraction-limited acoustic intensity focal size via nonlinear acoustic effects and thermal confinement by appropriately controlling ultrasound power and exposure time, which can be potentially used for deep-tissue high-resolution imaging. PMID:23479498

PHOTOACOUSTIC NON-DESTRUCTIVE EVALUATION AND IMAGING OF CARIES IN DENTAL SAMPLES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, T.; Dewhurst, R. J.

Dental caries is a disease wherein bacterial processes damage hard tooth structure. Traditional dental radiography has its limitations for detecting early stage caries. In this study, a photoacoustic (PA) imaging system with the near-infrared light source has been applied to postmortem dental samples to obtain 2-D and 3-D images. Imaging results showed that the PA technique can be used to image human teeth caries. For non-destructive photoacoustic evaluation and imaging, the induced temperature and pressure rises within biotissues should not cause physical damage to the tissue. For example, temperature rises above 5 deg. C within live human teeth will causemore » pulpal necrosis. Therefore, several simulations based on the thermoelastic effect have been applied to predict temperature and pressure fields within samples. Predicted temperature levels are below corresponding safety limits, but care is required to avoid nonlinear absorption phenomena. Furthermore, PA imaging results from the phantom provide evidence for high sensitivity, which shows the imaging potential of the PA technique for detecting early stage disease.« less

QR images: optimized image embedding in QR codes.

PubMed

Garateguy, Gonzalo J; Arce, Gonzalo R; Lau, Daniel L; Villarreal, Ofelia P

2014-07-01

This paper introduces the concept of QR images, an automatic method to embed QR codes into color images with bounded probability of detection error. These embeddings are compatible with standard decoding applications and can be applied to any color image with full area coverage. The QR information bits are encoded into the luminance values of the image, taking advantage of the immunity of QR readers against local luminance disturbances. To mitigate the visual distortion of the QR image, the algorithm utilizes halftoning masks for the selection of modified pixels and nonlinear programming techniques to locally optimize luminance levels. A tractable model for the probability of error is developed and models of the human visual system are considered in the quality metric used to optimize the luminance levels of the QR image. To minimize the processing time, the optimization techniques proposed to consider the mechanics of a common binarization method and are designed to be amenable for parallel implementations. Experimental results show the graceful degradation of the decoding rate and the perceptual quality as a function the embedding parameters. A visual comparison between the proposed and existing methods is presented.

A novel pre-processing technique for improving image quality in digital breast tomosynthesis.

PubMed

Kim, Hyeongseok; Lee, Taewon; Hong, Joonpyo; Sabir, Sohail; Lee, Jung-Ryun; Choi, Young Wook; Kim, Hak Hee; Chae, Eun Young; Cho, Seungryong

2017-02-01

Nonlinear pre-reconstruction processing of the projection data in computed tomography (CT) where accurate recovery of the CT numbers is important for diagnosis is usually discouraged, for such a processing would violate the physics of image formation in CT. However, one can devise a pre-processing step to enhance detectability of lesions in digital breast tomosynthesis (DBT) where accurate recovery of the CT numbers is fundamentally impossible due to the incompleteness of the scanned data. Since the detection of lesions such as micro-calcifications and mass in breasts is the purpose of using DBT, it is justified that a technique producing higher detectability of lesions is a virtue. A histogram modification technique was developed in the projection data domain. Histogram of raw projection data was first divided into two parts: One for the breast projection data and the other for background. Background pixel values were set to a single value that represents the boundary between breast and background. After that, both histogram parts were shifted by an appropriate amount of offset and the histogram-modified projection data were log-transformed. Filtered-backprojection (FBP) algorithm was used for image reconstruction of DBT. To evaluate performance of the proposed method, we computed the detectability index for the reconstructed images from clinically acquired data. Typical breast border enhancement artifacts were greatly suppressed and the detectability of calcifications and masses was increased by use of the proposed method. Compared to a global threshold-based post-reconstruction processing technique, the proposed method produced images of higher contrast without invoking additional image artifacts. In this work, we report a novel pre-processing technique that improves detectability of lesions in DBT and has potential advantages over the global threshold-based post-reconstruction processing technique. The proposed method not only increased the lesion detectability but also reduced typical image artifacts pronounced in conventional FBP-based DBT. © 2016 American Association of Physicists in Medicine.

Quantum image median filtering in the spatial domain

NASA Astrophysics Data System (ADS)

Li, Panchi; Liu, Xiande; Xiao, Hong

2018-03-01

Spatial filtering is one principal tool used in image processing for a broad spectrum of applications. Median filtering has become a prominent representation of spatial filtering because its performance in noise reduction is excellent. Although filtering of quantum images in the frequency domain has been described in the literature, and there is a one-to-one correspondence between linear spatial filters and filters in the frequency domain, median filtering is a nonlinear process that cannot be achieved in the frequency domain. We therefore investigated the spatial filtering of quantum image, focusing on the design method of the quantum median filter and applications in image de-noising. To this end, first, we presented the quantum circuits for three basic modules (i.e., Cycle Shift, Comparator, and Swap), and then, we design two composite modules (i.e., Sort and Median Calculation). We next constructed a complete quantum circuit that implements the median filtering task and present the results of several simulation experiments on some grayscale images with different noise patterns. Although experimental results show that the proposed scheme has almost the same noise suppression capacity as its classical counterpart, the complexity analysis shows that the proposed scheme can reduce the computational complexity of the classical median filter from the exponential function of image size n to the second-order polynomial function of image size n, so that the classical method can be speeded up.

Assessment of breast pathologies using nonlinear microscopy

PubMed Central

Tao, Yuankai K.; Shen, Dejun; Sheikine, Yuri; Ahsen, Osman O.; Wang, Helen H.; Schmolze, Daniel B.; Johnson, Nicole B.; Brooker, Jeffrey S.; Cable, Alex E.; Connolly, James L.; Fujimoto, James G.

2014-01-01

Rapid intraoperative assessment of breast excision specimens is clinically important because up to 40% of patients undergoing breast-conserving cancer surgery require reexcision for positive or close margins. We demonstrate nonlinear microscopy (NLM) for the assessment of benign and malignant breast pathologies in fresh surgical specimens. A total of 179 specimens from 50 patients was imaged with NLM using rapid extrinsic nuclear staining with acridine orange and intrinsic second harmonic contrast generation from collagen. Imaging was performed on fresh, intact specimens without the need for fixation, embedding, and sectioning required for conventional histopathology. A visualization method to aid pathological interpretation is presented that maps NLM contrast from two-photon fluorescence and second harmonic signals to features closely resembling histopathology using hematoxylin and eosin staining. Mosaicking is used to overcome trade-offs between resolution and field of view, enabling imaging of subcellular features over square-centimeter specimens. After NLM examination, specimens were processed for standard paraffin-embedded histology using a protocol that coregistered histological sections to NLM images for paired assessment. Blinded NLM reading by three pathologists achieved 95.4% sensitivity and 93.3% specificity, compared with paraffin-embedded histology, for identifying invasive cancer and ductal carcinoma in situ versus benign breast tissue. Interobserver agreement was κ = 0.88 for NLM and κ = 0.89 for histology. These results show that NLM achieves high diagnostic accuracy, can be rapidly performed on unfixed specimens, and is a promising method for intraoperative margin assessment. PMID:25313045

Image Algebra Matlab language version 2.3 for image processing and compression research

NASA Astrophysics Data System (ADS)

Schmalz, Mark S.; Ritter, Gerhard X.; Hayden, Eric

2010-08-01

Image algebra is a rigorous, concise notation that unifies linear and nonlinear mathematics in the image domain. Image algebra was developed under DARPA and US Air Force sponsorship at University of Florida for over 15 years beginning in 1984. Image algebra has been implemented in a variety of programming languages designed specifically to support the development of image processing and computer vision algorithms and software. The University of Florida has been associated with development of the languages FORTRAN, Ada, Lisp, and C++. The latter implementation involved a class library, iac++, that supported image algebra programming in C++. Since image processing and computer vision are generally performed with operands that are array-based, the Matlab™ programming language is ideal for implementing the common subset of image algebra. Objects include sets and set operations, images and operations on images, as well as templates and image-template convolution operations. This implementation, called Image Algebra Matlab (IAM), has been found to be useful for research in data, image, and video compression, as described herein. Due to the widespread acceptance of the Matlab programming language in the computing community, IAM offers exciting possibilities for supporting a large group of users. The control over an object's computational resources provided to the algorithm designer by Matlab means that IAM programs can employ versatile representations for the operands and operations of the algebra, which are supported by the underlying libraries written in Matlab. In a previous publication, we showed how the functionality of IAC++ could be carried forth into a Matlab implementation, and provided practical details of a prototype implementation called IAM Version 1. In this paper, we further elaborate the purpose and structure of image algebra, then present a maturing implementation of Image Algebra Matlab called IAM Version 2.3, which extends the previous implementation of IAM to include polymorphic operations over different point sets, as well as recursive convolution operations and functional composition. We also show how image algebra and IAM can be employed in image processing and compression research, as well as algorithm development and analysis.

Expression-dependent susceptibility to face distortions in processing of facial expressions of emotion.

PubMed

Guo, Kun; Soornack, Yoshi; Settle, Rebecca

2018-03-05

Our capability of recognizing facial expressions of emotion under different viewing conditions implies the existence of an invariant expression representation. As natural visual signals are often distorted and our perceptual strategy changes with external noise level, it is essential to understand how expression perception is susceptible to face distortion and whether the same facial cues are used to process high- and low-quality face images. We systematically manipulated face image resolution (experiment 1) and blur (experiment 2), and measured participants' expression categorization accuracy, perceived expression intensity and associated gaze patterns. Our analysis revealed a reasonable tolerance to face distortion in expression perception. Reducing image resolution up to 48 × 64 pixels or increasing image blur up to 15 cycles/image had little impact on expression assessment and associated gaze behaviour. Further distortion led to decreased expression categorization accuracy and intensity rating, increased reaction time and fixation duration, and stronger central fixation bias which was not driven by distortion-induced changes in local image saliency. Interestingly, the observed distortion effects were expression-dependent with less deterioration impact on happy and surprise expressions, suggesting this distortion-invariant facial expression perception might be achieved through the categorical model involving a non-linear configural combination of local facial features. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sub-40 fs, 1060-nm Yb-fiber laser enhances penetration depth in nonlinear optical microscopy of human skin

NASA Astrophysics Data System (ADS)

Balu, Mihaela; Saytashev, Ilyas; Hou, Jue; Dantus, Marcos; Tromberg, Bruce J.

2015-12-01

Advancing the practical utility of nonlinear optical microscopy requires continued improvement in imaging depth and contrast. We evaluated second-harmonic generation (SHG) and third-harmonic generation images from ex vivo human skin and showed that a sub-40 fs, 1060-nm Yb-fiber laser can enhance SHG penetration depth by up to 80% compared to a >100 fs, 800 nm Ti:sapphire source. These results demonstrate the potential of fiber-based laser systems to address a key performance limitation related to nonlinear optical microscopy (NLOM) technology while providing a low-barrier-to-access alternative to Ti:sapphire sources that could help accelerate the movement of NLOM into clinical practice.

L1-Based Approximations of PDEs and Applications

DTIC Science & Technology

2012-09-05

the analysis of the Navier-Stokes equations. The early versions of artificial vis- cosities being overly dissipative, the interest for these technique ...Guermond, and B. Popov. Stability analysis of explicit en- tropy viscosity methods for non-linear scalar conservation equations. Math. Comp., 2012... methods for solv- ing mathematical models of nonlinear phenomena such as nonlinear conservation laws, surface/image/data reconstruction problems

Gold nanoparticles on the surface of soda-lime glass: morphological, linear and nonlinear optical characterization.

PubMed

Romani, E C; Vitoreti, Douglas; Gouvêa, Paula M P; Caldas, P G; Prioli, R; Paciornik, S; Fokine, Michael; Braga, Arthur M B; Gomes, Anderson S L; Carvalho, Isabel C S

2012-02-27

Materials presenting high optical nonlinearity, such as materials containing metal nanoparticles (NPs), can be used in various applications in photonics. This motivated the research presented in this paper, where morphological, linear and nonlinear optical characteristics of gold NPs on the surface of bulk soda-lime glass substrates were investigated as a function of nanoparticle height. The NPs were obtained by annealing gold (Au) thin films previously deposited on the substrates. Pixel intensity histogram fitting on Atomic Force Microscopy (AFM) images was performed to obtain the thickness of the deposited film. Image analysis was employed to obtain the statistical distribution of the average height of the NPs. In addition, absorbance spectra of the samples before and after annealing were measured. Finally, the nonlinear refractive index (n2) and the nonlinear absorption index (α2) at 800 nm were obtained before and after annealing by using the thermally managed eclipse Z-scan (TM-EZ) technique with a Ti:Sapphire laser (150 fs pulses). Results show that both n2 and α2 at this wavelength change signs after the annealing and that the samples presented a high nonlinear refractive index.

Multimodal optical workstation for simultaneous linear, nonlinear microscopy and nanomanipulation: upgrading a commercial confocal inverted microscope.

PubMed

Mathew, Manoj; Santos, Susana I C O; Zalvidea, Dobryna; Loza-Alvarez, Pablo

2009-07-01

In this work we propose and build a multimodal optical workstation that extends a commercially available confocal microscope (Nikon Confocal C1-Si) to include nonlinear/multiphoton microscopy and optical manipulation/stimulation tools such as nanosurgery. The setup allows both subsystems (confocal and nonlinear) to work independently and simultaneously. The workstation enables, for instance, nanosurgery along with simultaneous confocal and brightfield imaging. The nonlinear microscopy capabilities are added around the commercial confocal microscope by exploiting all the flexibility offered by this microscope and without need for any mechanical or electronic modification of the confocal microscope systems. As an example, the standard differential interference contrast condenser and diascopic detector in the confocal microscope are readily used as a forward detection mount for second harmonic generation imaging. The various capabilities of this workstation, as applied directly to biology, are demonstrated using the model organism Caenorhabditis elegans.

Laser Imaging of Airborne Acoustic Emission by Nonlinear Defects

NASA Astrophysics Data System (ADS)

Solodov, Igor; Döring, Daniel; Busse, Gerd

2008-06-01

Strongly nonlinear vibrations of near-surface fractured defects driven by an elastic wave radiate acoustic energy into adjacent air in a wide frequency range. The variations of pressure in the emitted airborne waves change the refractive index of air thus providing an acoustooptic interaction with a collimated laser beam. Such an air-coupled vibrometry (ACV) is proposed for detecting and imaging of acoustic radiation of nonlinear spectral components by cracked defects. The photoelastic relation in air is used to derive induced phase modulation of laser light in the heterodyne interferometer setup. The sensitivity of the scanning ACV to different spatial components of the acoustic radiation is analyzed. The animated airborne emission patterns are visualized for the higher harmonic and frequency mixing fields radiated by planar defects. The results confirm a high localization of the nonlinear acoustic emission around the defects and complicated directivity patterns appreciably different from those observed for fundamental frequencies.

Nonlinear Markov Control Processes and Games

DTIC Science & Technology

2012-11-15

the analysis of a new class of stochastic games , nonlinear Markov games , as they arise as a ( competitive ) controlled version of nonlinear Markov... competitive interests) a nonlinear Markov game that we are investigating. I 0. :::tUt::JJt:.l.. I I t:t11VI;:, nonlinear Markov game , nonlinear Markov...corresponding stochastic game Γ+(T, h). In a slightly different setting one can assume that changes in a competitive control process occur as a

Research on the feature set construction method for spherical stereo vision

NASA Astrophysics Data System (ADS)

Zhu, Junchao; Wan, Li; Röning, Juha; Feng, Weijia

2015-01-01

Spherical stereo vision is a kind of stereo vision system built by fish-eye lenses, which discussing the stereo algorithms conform to the spherical model. Epipolar geometry is the theory which describes the relationship of the two imaging plane in cameras for the stereo vision system based on perspective projection model. However, the epipolar in uncorrected fish-eye image will not be a line but an arc which intersects at the poles. It is polar curve. In this paper, the theory of nonlinear epipolar geometry will be explored and the method of nonlinear epipolar rectification will be proposed to eliminate the vertical parallax between two fish-eye images. Maximally Stable Extremal Region (MSER) utilizes grayscale as independent variables, and uses the local extremum of the area variation as the testing results. It is demonstrated in literatures that MSER is only depending on the gray variations of images, and not relating with local structural characteristics and resolution of image. Here, MSER will be combined with the nonlinear epipolar rectification method proposed in this paper. The intersection of the rectified epipolar and the corresponding MSER region is determined as the feature set of spherical stereo vision. Experiments show that this study achieved the expected results.

Super-resolution method for face recognition using nonlinear mappings on coherent features.

PubMed

Huang, Hua; He, Huiting

2011-01-01

Low-resolution (LR) of face images significantly decreases the performance of face recognition. To address this problem, we present a super-resolution method that uses nonlinear mappings to infer coherent features that favor higher recognition of the nearest neighbor (NN) classifiers for recognition of single LR face image. Canonical correlation analysis is applied to establish the coherent subspaces between the principal component analysis (PCA) based features of high-resolution (HR) and LR face images. Then, a nonlinear mapping between HR/LR features can be built by radial basis functions (RBFs) with lower regression errors in the coherent feature space than in the PCA feature space. Thus, we can compute super-resolved coherent features corresponding to an input LR image according to the trained RBF model efficiently and accurately. And, face identity can be obtained by feeding these super-resolved features to a simple NN classifier. Extensive experiments on the Facial Recognition Technology, University of Manchester Institute of Science and Technology, and Olivetti Research Laboratory databases show that the proposed method outperforms the state-of-the-art face recognition algorithms for single LR image in terms of both recognition rate and robustness to facial variations of pose and expression.

Joint level-set and spatio-temporal motion detection for cell segmentation.

PubMed

Boukari, Fatima; Makrogiannis, Sokratis

2016-08-10

Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan-Vese techniques, and 4 % compared to the nonlinear spatio-temporal diffusion method. Despite the wide variation in cell shape, density, mitotic events, and image quality among the datasets, our proposed method produced promising segmentation results. These results indicate the efficiency and robustness of this method especially for mitotic events and low SNR imaging, enabling the application of subsequent quantification tasks.

Supervised nonlinear spectral unmixing using a postnonlinear mixing model for hyperspectral imagery.

PubMed

Altmann, Yoann; Halimi, Abderrahim; Dobigeon, Nicolas; Tourneret, Jean-Yves

2012-06-01

This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise. These nonlinear functions are approximated using polynomial functions leading to a polynomial postnonlinear mixing model. A Bayesian algorithm and optimization methods are proposed to estimate the parameters involved in the model. The performance of the unmixing strategies is evaluated by simulations conducted on synthetic and real data.

Phase Equilibrium and Crystal Growth Studies on AgGaSe2 and Related Nonlinear Optical Materials

DTIC Science & Technology

1989-09-01

identify by block number) IELD GROUP SUB-GROUP - "°Silver selenogallate, AgGaSe2, nonlinear optical materials, infrared materials, optical defects 19...materials has unique nonlinear infrared optical properties( 1-4 ) including high nonlinear coefficients, and the ability to be phase matched through a...have a milky appearance in thin section or when viewed with a commercial infrared image converter. Microscopic examination of AgGaSe2 in both reflected

Nonlinear, non-stationary image processing technique for eddy current NDE

NASA Astrophysics Data System (ADS)

Yang, Guang; Dib, Gerges; Kim, Jaejoon; Zhang, Lu; Xin, Junjun; Udpa, Lalita

2012-05-01

Automatic analysis of eddy current (EC) data has facilitated the analysis of large volumes of data generated in the inspection of steam generator tubes in nuclear power plants. The traditional procedure for analysis of EC data includes data calibration, pre-processing, region of interest (ROI) detection, feature extraction and classification. Accurate ROI detection has been enhanced by pre-processing, which involves reducing noise and other undesirable components as well as enhancing defect indications in the raw measurement. This paper presents the Hilbert-Huang Transform (HHT) for feature extraction and support vector machine (SVM) for classification. The performance is shown to significantly better than the existing rule based classification approach used in industry.

Nonlinear Interferometric Vibrational Imaging (NIVI) with Novel Optical Sources

NASA Astrophysics Data System (ADS)

Boppart, Stephen A.; King, Matthew D.; Liu, Yuan; Tu, Haohua; Gruebele, Martin

Optical imaging is essential in medicine and in fundamental studies of biological systems. Although many existing imaging modalities can supply valuable information, not all are capable of label-free imaging with high-contrast and molecular specificity. The application of molecular or nanoparticle contrast agents may adversely influence the biological system under investigation. These substances also present ongoing concerns over toxicity or particle clearance, which must be properly addressed before their approval for in vivo human imaging. Hence there is an increasing appreciation for label-free imaging techniques. It is of primary importance to develop imaging techniques that can indiscriminately identify and quantify biochemical compositions to high degrees of sensitivity and specificity through only the intrinsic optical response of endogenous molecular species. The development and use of nonlinear interferometric vibrational imaging, which is based on the interferometric detection of optical signals from coherent anti-Stokes Raman scattering (CARS), along with novel optical sources, offers the potential for label-free molecular imaging.

Improved measurement linearity and precision for AMCW time-of-flight range imaging cameras.

PubMed

Payne, Andrew D; Dorrington, Adrian A; Cree, Michael J; Carnegie, Dale A

2010-08-10

Time-of-flight range imaging systems utilizing the amplitude modulated continuous wave (AMCW) technique often suffer from measurement nonlinearity due to the presence of aliased harmonics within the amplitude modulation signals. Typically a calibration is performed to correct these errors. We demonstrate an alternative phase encoding approach that attenuates the harmonics during the sampling process, thereby improving measurement linearity in the raw measurements. This mitigates the need to measure the system's response or calibrate for environmental changes. In conjunction with improved linearity, we demonstrate that measurement precision can also be increased by reducing the duty cycle of the amplitude modulated illumination source (while maintaining overall illumination power).

Image encryption based on nonlinear encryption system and public-key cryptography

NASA Astrophysics Data System (ADS)

Zhao, Tieyu; Ran, Qiwen; Chi, Yingying

2015-03-01

Recently, optical asymmetric cryptosystem (OACS) has became the focus of discussion and concern of researchers. Some researchers pointed out that OACS was not tenable because of misunderstanding the concept of asymmetric cryptosystem (ACS). We propose an improved cryptosystem using RSA public-key algorithm based on existing OACS and the new system conforms to the basic agreement of public key cryptosystem. At the beginning of the encryption process, the system will produce an independent phase matrix and allocate the input image, which also conforms to one-time pad cryptosystem. The simulation results show that the validity of the improved cryptosystem and the high robustness against attack scheme using phase retrieval technique.

Long-Range Reduced Predictive Information Transfers of Autistic Youths in EEG Sensor-Space During Face Processing.

PubMed

Khadem, Ali; Hossein-Zadeh, Gholam-Ali; Khorrami, Anahita

2016-03-01

The majority of previous functional/effective connectivity studies conducted on the autistic patients converged to the underconnectivity theory of ASD: "long-range underconnectivity and sometimes short-rang overconnectivity". However, to the best of our knowledge the total (linear and nonlinear) predictive information transfers (PITs) of autistic patients have not been investigated yet. Also, EEG data have rarely been used for exploring the information processing deficits in autistic subjects. This study is aimed at comparing the total (linear and nonlinear) PITs of autistic and typically developing healthy youths during human face processing by using EEG data. The ERPs of 12 autistic youths and 19 age-matched healthy control (HC) subjects were recorded while they were watching upright and inverted human face images. The PITs among EEG channels were quantified using two measures separately: transfer entropy with self-prediction optimality (TESPO), and modified transfer entropy with self-prediction optimality (MTESPO). Afterwards, the directed differential connectivity graphs (dDCGs) were constructed to characterize the significant changes in the estimated PITs of autistic subjects compared with HC ones. By using both TESPO and MTESPO, long-range reduction of PITs of ASD group during face processing was revealed (particularly from frontal channels to right temporal channels). Also, it seemed the orientation of face images (upright or upside down) did not modulate the binary pattern of PIT-based dDCGs, significantly. Moreover, compared with TESPO, the results of MTESPO were more compatible with the underconnectivity theory of ASD in the sense that MTESPO showed no long-range increase in PIT. It is also noteworthy that to the best of our knowledge it is the first time that a version of MTE is applied for patients (here ASD) and it is also its first use for EEG data analysis.

Variable importance in nonlinear kernels (VINK): classification of digitized histopathology.

PubMed

Ginsburg, Shoshana; Ali, Sahirzeeshan; Lee, George; Basavanhally, Ajay; Madabhushi, Anant

2013-01-01

Quantitative histomorphometry is the process of modeling appearance of disease morphology on digitized histopathology images via image-based features (e.g., texture, graphs). Due to the curse of dimensionality, building classifiers with large numbers of features requires feature selection (which may require a large training set) or dimensionality reduction (DR). DR methods map the original high-dimensional features in terms of eigenvectors and eigenvalues, which limits the potential for feature transparency or interpretability. Although methods exist for variable selection and ranking on embeddings obtained via linear DR schemes (e.g., principal components analysis (PCA)), similar methods do not yet exist for nonlinear DR (NLDR) methods. In this work we present a simple yet elegant method for approximating the mapping between the data in the original feature space and the transformed data in the kernel PCA (KPCA) embedding space; this mapping provides the basis for quantification of variable importance in nonlinear kernels (VINK). We show how VINK can be implemented in conjunction with the popular Isomap and Laplacian eigenmap algorithms. VINK is evaluated in the contexts of three different problems in digital pathology: (1) predicting five year PSA failure following radical prostatectomy, (2) predicting Oncotype DX recurrence risk scores for ER+ breast cancers, and (3) distinguishing good and poor outcome p16+ oropharyngeal tumors. We demonstrate that subsets of features identified by VINK provide similar or better classification or regression performance compared to the original high dimensional feature sets.

Spontaneous Polarization in Bio-organic Materials Studied by Scanning Pyroelectric Microscopy (SPEM) and Second Harmonic Generation Microscopy (SHGM)

NASA Astrophysics Data System (ADS)

Putzeys, T.; Wübbenhorst, M.; van der Veen, M. A.

2015-06-01

Bio-organic materials such as bones, teeth, and tendon generally show nonlinear optical (Masters and So in Handbook of Biomedical Nonlinear Optical Microscopy, 2008), pyro- and piezoelectric (Fukada and Yasuda in J Phys Soc Jpn 12:1158, 1957) properties, implying a permanent polarization, the presence of which can be rationalized by describing the growth of the sample and the creation of a polar axis according to Markov's theory of stochastic processes (Hulliger in Biophys J 84:3501, 2003; Batagiannis et al. in Curr Opin Solid State Mater Sci 17:107, 2010). Two proven, versatile techniques for probing spontaneous polarization distributions in solids are scanning pyroelectric microscopy (SPEM) and second harmonic generation microscopy (SHGM). The combination of pyroelectric scanning with SHG-microscopy in a single experimental setup leading to complementary pyroelectric and nonlinear optical data is demonstrated, providing us with a more complete image of the polarization in organic materials. Crystals consisting of a known polar and hyperpolarizable material, CNS (4-chloro-4-nitrostilbene) are used as a reference sample, to verify the functionality of the setup, with both SPEM and SHGM images revealing the same polarization domain information. In contrast, feline and human nails exhibit a pyroelectric response, but a second harmonic response is absent for both keratin containing materials, implying that there may be symmetry-allowed SHG, but with very inefficient second harmonophores. This new approach to polarity detection provides additional information on the polar and hyperpolar nature in a variety of (bio) materials.

Image analysis-based modelling for flower number estimation in grapevine.

PubMed

Millan, Borja; Aquino, Arturo; Diago, Maria P; Tardaguila, Javier

2017-02-01

Grapevine flower number per inflorescence provides valuable information that can be used for assessing yield. Considerable research has been conducted at developing a technological tool, based on image analysis and predictive modelling. However, the behaviour of variety-independent predictive models and yield prediction capabilities on a wide set of varieties has never been evaluated. Inflorescence images from 11 grapevine Vitis vinifera L. varieties were acquired under field conditions. The flower number per inflorescence and the flower number visible in the images were calculated manually, and automatically using an image analysis algorithm. These datasets were used to calibrate and evaluate the behaviour of two linear (single-variable and multivariable) and a nonlinear variety-independent model. As a result, the integrated tool composed of the image analysis algorithm and the nonlinear approach showed the highest performance and robustness (RPD = 8.32, RMSE = 37.1). The yield estimation capabilities of the flower number in conjunction with fruit set rate (R 2  = 0.79) and average berry weight (R 2  = 0.91) were also tested. This study proves the accuracy of flower number per inflorescence estimation using an image analysis algorithm and a nonlinear model that is generally applicable to different grapevine varieties. This provides a fast, non-invasive and reliable tool for estimation of yield at harvest. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Arbitrary-ratio power splitter based on nonlinear multimode interference coupler

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tajaldini, Mehdi; Young Researchers and Elite Club, Baft Branch, Islamic Azad University, Baft; Jafri, Mohd Zubir Mat

2015-04-24

We propose an ultra-compact multimode interference (MMI) power splitter based on nonlinear effects from simulations using nonlinear modal propagation analysis (NMPA) cooperation with finite difference Method (FDM) to access free choice of splitting ratio. Conventional multimode interference power splitter could only obtain a few discrete ratios. The power splitting ratio may be adjusted continuously while the input set power is varying by a tunable laser. In fact, using an ultra- compact MMI with a simple structure that is launched by a tunable nonlinear input fulfills the problem of arbitrary-ratio in integrated photonics circuits. Silicon on insulator (SOI) is used asmore » the offered material due to the high contrast refractive index and Centro symmetric properties. The high-resolution images at the end of the multimode waveguide in the simulated power splitter have a high power balance, whereas access to a free choice of splitting ratio is not possible under the linear regime in the proposed length range except changes in the dimension for any ratio. The compact dimensions and ideal performance of the device are established according to optimized parameters. The proposed regime can be extended to the design of M×N arbitrary power splitters ratio for programmable logic devices in all optical digital signal processing. The results of this study indicate that nonlinear modal propagation analysis solves the miniaturization problem for all-optical devices based on MMI couplers to achieve multiple functions in a compact planar integrated circuit and also overcomes the limitations of previously proposed methods for nonlinear MMI.« less

Nonlinear laser scanning microscopy of human vocal folds.

PubMed

Miri, Amir K; Tripathy, Umakanta; Mongeau, Luc; Wiseman, Paul W

2012-02-01

The purpose of this work was to apply nonlinear laser scanning microscopy (NLSM) for visualizing the morphology of extracellular matrix proteins within human vocal folds. This technique may potentially assist clinicians in making rapid diagnoses of vocal fold tissue disease or damage. Microstructural characterization based on NLSM provides valuable information for better understanding molecular mechanisms and tissue structure. Experimental, ex vivo human vocal fold. A custom-built multimodal nonlinear laser scanning microscope was used to scan fibrillar proteins in three 4% formaldehyde-fixed cadaveric samples. Collagen and elastin, key extracellular matrix proteins in the vocal fold lamina propria, were imaged by two nonlinear microscopy modalities: second harmonic generation (SHG) and two-photon fluorescence (TPF), respectively. An experimental protocol was introduced to characterize the geometrical properties of the imaged fibrous proteins. NLSM revealed the biomorphology of the human vocal fold fibrous proteins. No photobleaching was observed for the incident laser power of ∼60 mW before the excitation objective. Types I and III fibrillar collagen were imaged without label in the tissue by intrinsic SHG. Imaging while rotating the incident laser light-polarization direction confirmed a helical shape for the collagen fibers. The amplitude, periodicity, and overall orientation were then computed for the helically distributed collagen network. The elastin network was simultaneously imaged via TPF and found to have a basket-like structure. In some regions, particularly close to the epithelium, colocalization of both extracellular matrix components were observed. A benchmark study is presented for quantitative real-time, ex vivo, NLSM imaging of the extracellular macromolecules in human vocal fold lamina propria. The results are promising for clinical applications. Copyright © 2011 The American Laryngological, Rhinological, and Otological Society, Inc.

Time and space analysis of turbulence of gravity surface waves

NASA Astrophysics Data System (ADS)

Mordant, Nicolas; Aubourg, Quentin; Viboud, Samuel; Sommeria, Joel

2016-11-01

Wave turbulence is a statistical state made of a very large number of nonlinearly interacting waves. The Weak Turbulence Theory was developed to describe such a situation in the weakly nonlinear regime. Although, oceanic data tend to be compatible with the theory, laboratory data fail to fulfill the theoretical predictions. A space-time resolved measurement of the waves have proven to be especially fruitful to identify the mechanism at play in turbulence of gravity-capillary waves. We developed an image processing algorithm to measure the motion of the surface of water with both space and time resolution. We first seed the surface with slightly buoyant polystyrene particles and use 3 cameras to reconstruct the surface. Our stereoscopic algorithm is coupled to PIV so that to obtain both the surface deformation and the velocity of the water surface. Such a coupling is shown to improve the sensitivity of the measurement by one order of magnitude. We use this technique to probe the existence of weakly nonlinear turbulence excited by two small wedge wavemakers in a 13-m diameter wave flume. We observe a truly weakly nonlinear regime of isotropic wave turbulence. This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (Grant Agreement No 647018-WATU).

Dynamics of Ultrasound Contrast Agents and Nonlinear Acoustic Waves: Experiments, Modeling, and Theories

NASA Astrophysics Data System (ADS)

Xia, Lang

Bubbles occur in many natural and biological flows as well as in numerous industrial phenomena, such as pumps, propellers, turbines, and chemical processing plants. They have been widely studied in the past leading to a large body of literature. However, bubbles appearing in different situations differ significantly in their physical characteristics and behaviors. Recently, bubbles of diameter less than 10 micrometers have found applications in diagnostic ultrasound imaging. These microbubble-based ultrasound contrast agents (UCA) are intravenously administered in patients before ultrasound imaging. Due to the compressive gas core, they generate substantial ultrasound echoes leading to significant enhancement of image quality and contrast. Free bubbles of a micrometer diameter experience a large surface tension induced Laplace pressure leading to their quick dissolution in milliseconds. UCAs are stabilized by coating them with a shell of lipids, polymers, proteins, and other surface-active materials and changing the gas content from air to a high molecular weight low solubility gas such as perfluorocarbon. The past literature of bubble dynamics are mostly restricted to free bubbles. The stabilizing shell of UCAs, however, critically affects their dynamics. In this thesis, we performed acoustic characterization of several UCAs coated with polymer and lipids. We experimentally measured their acoustic attenuation and scattering, of which the data were used in mathematical models to determine shell properties and nonlinear dynamics. Several different interfacial rheological models were employed. Experimental acoustic characterization was also extended to a novel type of nanoparticle suspension--polymersomes, vesicles encapsulated by amphiphilic polymers. The later part of the thesis is devoted to modeling the effects of the presence of coated microbubbles to the overall effective bulk properties of bubbly liquids. Introduction of microbubbles in the liquids does not only modify the bulk properties of the medium (bubbly liquids) but also significantly changes the natures of the propagating waves (e.g., the sound velocity in bubble suspension was found to be as low as 20 m/s). We investigate the nonlinear nature of the acoustic wave in bubbly liquids. Specifically, we theoretically show that microbubbles could change the nonlinearity of the medium, characterized by quantity B/A.

Image-based gradient non-linearity characterization to determine higher-order spherical harmonic coefficients for improved spatial position accuracy in magnetic resonance imaging.

PubMed

Weavers, Paul T; Tao, Shengzhen; Trzasko, Joshua D; Shu, Yunhong; Tryggestad, Erik J; Gunter, Jeffrey L; McGee, Kiaran P; Litwiller, Daniel V; Hwang, Ken-Pin; Bernstein, Matt A

2017-05-01

Spatial position accuracy in magnetic resonance imaging (MRI) is an important concern for a variety of applications, including radiation therapy planning, surgical planning, and longitudinal studies of morphologic changes to study neurodegenerative diseases. Spatial accuracy is strongly influenced by gradient linearity. This work presents a method for characterizing the gradient non-linearity fields on a per-system basis, and using this information to provide improved and higher-order (9th vs. 5th) spherical harmonic coefficients for better spatial accuracy in MRI. A large fiducial phantom containing 5229 water-filled spheres in a grid pattern is scanned with the MR system, and the positions all the fiducials are measured and compared to the corresponding ground truth fiducial positions as reported from a computed tomography (CT) scan of the object. Systematic errors from off-resonance (i.e., B0) effects are minimized with the use of increased receiver bandwidth (±125kHz) and two acquisitions with reversed readout gradient polarity. The spherical harmonic coefficients are estimated using an iterative process, and can be subsequently used to correct for gradient non-linearity. Test-retest stability was assessed with five repeated measurements on a single scanner, and cross-scanner variation on four different, identically-configured 3T wide-bore systems. A decrease in the root-mean-square error (RMSE) over a 50cm diameter spherical volume from 1.80mm to 0.77mm is reported here in the case of replacing the vendor's standard 5th order spherical harmonic coefficients with custom fitted 9th order coefficients, and from 1.5mm to 1mm by extending custom fitted 5th order correction to the 9th order. Minimum RMSE varied between scanners, but was stable with repeated measurements in the same scanner. The results suggest that the proposed methods may be used on a per-system basis to more accurately calibrate MR gradient non-linearity coefficients when compared to vendor standard corrections. Copyright © 2016 Elsevier Inc. All rights reserved.

Imaging and sensing based on dual-pulse nonlinear photoacoustic contrast: a preliminary study on fatty liver

NASA Astrophysics Data System (ADS)

Tian, Chao; Xie, Zhixing; Fabiilli, Mario; Wang, Xueding

2015-03-01

We developed a simple and effective contrast for tissue characterization based on the recently proposed dual-pulse nonlinear photoacoustic technology. The new contrast takes advantage of the temperature dependence of Grüneisen parameter of tissue and involves a dual-pulse laser excitation process. A short pulse first heats the sample and causes a temperature jump, which then leads to the change of Grüneisen parameter and amplitude of the photoacoustic signal of the second pulse. For different tissues, the induced rate or trend of change is expected to be different, which constitutes the basis of the new contrast. Preliminary phantom experiment in blood and lipid mixtures and in vitro experiment in fatty rat liver have demonstrated that the proposed contrast has the capability of fast characterization of lipid-rich and blood-rich tissues.