Estimating radiofrequency power deposition in body NMR imaging.

PubMed

Bottomley, P A; Redington, R W; Edelstein, W A; Schenck, J F

1985-08-01

Simple theoretical estimates of the average, maximum, and spatial variation of the radiofrequency power deposition (specific absorption rate) during hydrogen nuclear magnetic resonance imaging are deduced for homogeneous spheres and for cylinders of biological tissue with a uniformly penetrating linear rf field directed axially and transverse to the cylindrical axis. These are all simple scalar multiples of the expression for the cylinder in an axial field published earlier (Med. Phys. 8, 510 (1981]. Exact solutions for the power deposition in the cylinder with axial (Phys. Med. Biol. 23, 630 (1978] and transversely directed rf field are also presented, and the spatial variation of power deposition in head and body models is examined. In the exact models, the specific absorption rates decrease rapidly and monotonically with decreasing radius despite local increases in rf field amplitude. Conversion factors are provided for calculating the power deposited by Gaussian and sinc-modulated rf pulses used for slice selection in NMR imaging, relative to rectangular profiled pulses. Theoretical estimates are compared with direct measurements of the total power deposited in the bodies of nine adult males by a 63-MHz body-imaging system with transversely directed field, taking account of cable and NMR coil losses. The results for the average power deposition agree within about 20% for the exact model of the cylinder with axial field, when applied to the exposed torso volume enclosed by the rf coil. The average values predicted by the simple spherical and cylindrical models with axial fields, the exact cylindrical model with transverse field, and the simple truncated cylinder model with transverse field were about two to three times that measured, while the simple model consisting of an infinitely long cylinder with transverse field gave results about six times that measured. The surface power deposition measured by observing the incremental power as a function of external torso radius was comparable to the average value. This is consistent with the presence of a variable thickness peripheral adipose layer which does not substantially increase surface power deposition with increasing torso radius. The absence of highly localized intensity artifacts in 63-MHz body images does not suggest anomalously intense power deposition at localized internal sites, although peak power is difficult to measure.

Building an Open-source Simulation Platform of Acoustic Radiation Force-based Breast Elastography

PubMed Central

Wang, Yu; Peng, Bo; Jiang, Jingfeng

2017-01-01

Ultrasound-based elastography including strain elastography (SE), acoustic radiation force Impulse (ARFI) imaging, point shear wave elastography (pSWE) and supersonic shear imaging (SSI) have been used to differentiate breast tumors among other clinical applications. The objective of this study is to extend a previously published virtual simulation platform built for ultrasound quasi-static breast elastography toward acoustic radiation force-based breast elastography. Consequently, the extended virtual breast elastography simulation platform can be used to validate image pixels with known underlying soft tissue properties (i.e. “ground truth”) in complex, heterogeneous media, enhancing confidence in elastographic image interpretations. The proposed virtual breast elastography system inherited four key components from the previously published virtual simulation platform: an ultrasound simulator (Field II), a mesh generator (Tetgen), a finite element solver (FEBio) and a visualization and data processing package (VTK). Using a simple message passing mechanism, functionalities have now been extended to acoustic radiation force-based elastography simulations. Examples involving three different numerical breast models with increasing complexity – one uniform model, one simple inclusion model and one virtual complex breast model derived from magnetic resonance imaging data, were used to demonstrate capabilities of this extended virtual platform. Overall, simulation results were compared with the published results. In the uniform model, the estimated shear wave speed (SWS) values were within 4% compared to the predetermined SWS values. In the simple inclusion and the complex breast models, SWS values of all hard inclusions in soft backgrounds were slightly underestimated, similar to what has been reported. The elastic contrast values and visual observation show that ARFI images have higher spatial resolution, while SSI images can provide higher inclusion-to-background contrast. In summary, our initial results were consistent with our expectations and what have been reported in the literature. The proposed (open-source) simulation platform can serve as a single gateway to perform many elastographic simulations in a transparent manner, thereby promoting collaborative developments. PMID:28075330

Building an open-source simulation platform of acoustic radiation force-based breast elastography

NASA Astrophysics Data System (ADS)

Wang, Yu; Peng, Bo; Jiang, Jingfeng

2017-03-01

Ultrasound-based elastography including strain elastography, acoustic radiation force impulse (ARFI) imaging, point shear wave elastography and supersonic shear imaging (SSI) have been used to differentiate breast tumors among other clinical applications. The objective of this study is to extend a previously published virtual simulation platform built for ultrasound quasi-static breast elastography toward acoustic radiation force-based breast elastography. Consequently, the extended virtual breast elastography simulation platform can be used to validate image pixels with known underlying soft tissue properties (i.e. ‘ground truth’) in complex, heterogeneous media, enhancing confidence in elastographic image interpretations. The proposed virtual breast elastography system inherited four key components from the previously published virtual simulation platform: an ultrasound simulator (Field II), a mesh generator (Tetgen), a finite element solver (FEBio) and a visualization and data processing package (VTK). Using a simple message passing mechanism, functionalities have now been extended to acoustic radiation force-based elastography simulations. Examples involving three different numerical breast models with increasing complexity—one uniform model, one simple inclusion model and one virtual complex breast model derived from magnetic resonance imaging data, were used to demonstrate capabilities of this extended virtual platform. Overall, simulation results were compared with the published results. In the uniform model, the estimated shear wave speed (SWS) values were within 4% compared to the predetermined SWS values. In the simple inclusion and the complex breast models, SWS values of all hard inclusions in soft backgrounds were slightly underestimated, similar to what has been reported. The elastic contrast values and visual observation show that ARFI images have higher spatial resolution, while SSI images can provide higher inclusion-to-background contrast. In summary, our initial results were consistent with our expectations and what have been reported in the literature. The proposed (open-source) simulation platform can serve as a single gateway to perform many elastographic simulations in a transparent manner, thereby promoting collaborative developments.

Testing the uniqueness of mass models using gravitational lensing

NASA Astrophysics Data System (ADS)

Walls, Levi; Williams, Liliya L. R.

2018-06-01

The positions of images produced by the gravitational lensing of background-sources provide insight to lens-galaxy mass distributions. Simple elliptical mass density profiles do not agree well with observations of the population of known quads. It has been shown that the most promising way to reconcile this discrepancy is via perturbations away from purely elliptical mass profiles by assuming two super-imposed, somewhat misaligned mass distributions: one is dark matter (DM), the other is a stellar distribution. In this work, we investigate if mass modelling of individual lenses can reveal if the lenses have this type of complex structure, or simpler elliptical structure. In other words, we test mass model uniqueness, or how well an extended source lensed by a non-trivial mass distribution can be modeled by a simple elliptical mass profile. We used the publicly-available lensing software, Lensmodel, to generate and numerically model gravitational lenses and “observed” image positions. We then compared “observed” and modeled image positions via root mean square (RMS) of their difference. We report that, in most cases, the RMS is ≤0.05‧‧ when averaged over an extended source. Thus, we show it is possible to fit a smooth mass model to a system that contains a stellar-component with varying levels of misalignment with a DM-component, and hence mass modelling cannot differentiate between simple elliptical versus more complex lenses.

Image Discrimination Models for Object Detection in Natural Backgrounds

NASA Technical Reports Server (NTRS)

Ahumada, A. J., Jr.

2000-01-01

This paper reviews work accomplished and in progress at NASA Ames relating to visual target detection. The focus is on image discrimination models, starting with Watson's pioneering development of a simple spatial model and progressing through this model's descendents and extensions. The application of image discrimination models to target detection will be described and results reviewed for Rohaly's vehicle target data and the Search 2 data. The paper concludes with a description of work we have done to model the process by which observers learn target templates and methods for elucidating those templates.

Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies

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

Häggström, Ida, E-mail: haeggsti@mskcc.org; Beattie, Bradley J.; Schmidtlein, C. Ross

2016-06-15

Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuationmore » are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dPETSTEP can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.« less

Modeling of video traffic in packet networks, low rate video compression, and the development of a lossy+lossless image compression algorithm

NASA Technical Reports Server (NTRS)

Sayood, K.; Chen, Y. C.; Wang, X.

1992-01-01

During this reporting period we have worked on three somewhat different problems. These are modeling of video traffic in packet networks, low rate video compression, and the development of a lossy + lossless image compression algorithm, which might have some application in browsing algorithms. The lossy + lossless scheme is an extension of work previously done under this grant. It provides a simple technique for incorporating browsing capability. The low rate coding scheme is also a simple variation on the standard discrete cosine transform (DCT) coding approach. In spite of its simplicity, the approach provides surprisingly high quality reconstructions. The modeling approach is borrowed from the speech recognition literature, and seems to be promising in that it provides a simple way of obtaining an idea about the second order behavior of a particular coding scheme. Details about these are presented.

Wide dynamic logarithmic InGaAs sensor suitable for eye-safe active imaging

NASA Astrophysics Data System (ADS)

Ni, Yang; Bouvier, Christian; Arion, Bogdan; Noguier, Vincent

2016-05-01

In this paper, we present a simple method to analyze the injection efficiency of the photodiode interface circuit under fast shuttering conditions for active Imaging applications. This simple model has been inspired from the companion model for reactive elements largely used in CAD. In this paper, we demonstrate that traditional CTIA photodiode interface is not adequate for active imaging where fast and precise shuttering operation is necessary. Afterwards we present a direct amplification based photodiode interface which can provide an accurate and fast shuttering operation on photodiode. These considerations have been used in NIT's newly developed ROIC and corresponding SWIR sensors both in VGA 15um pitch (NSC1201) and also in QVGA 25um pitch (NSC1401).

An Emphasis on Perception: Teaching Image Formation Using a Mechanistic Model of Vision.

ERIC Educational Resources Information Center

Allen, Sue; And Others

An effective way to teach the concept of image is to give students a model of human vision which incorporates a simple mechanism of depth perception. In this study two almost identical versions of a curriculum in geometrical optics were created. One used a mechanistic, interpretive eye model, and in the other the eye was modeled as a passive,…

Robust image modeling techniques with an image restoration application

NASA Astrophysics Data System (ADS)

Kashyap, Rangasami L.; Eom, Kie-Bum

1988-08-01

A robust parameter-estimation algorithm for a nonsymmetric half-plane (NSHP) autoregressive model, where the driving noise is a mixture of a Gaussian and an outlier process, is presented. The convergence of the estimation algorithm is proved. An algorithm to estimate parameters and original image intensity simultaneously from the impulse-noise-corrupted image, where the model governing the image is not available, is also presented. The robustness of the parameter estimates is demonstrated by simulation. Finally, an algorithm to restore realistic images is presented. The entire image generally does not obey a simple image model, but a small portion (e.g., 8 x 8) of the image is assumed to obey an NSHP model. The original image is divided into windows and the robust estimation algorithm is applied for each window. The restoration algorithm is tested by comparing it to traditional methods on several different images.

Sky camera geometric calibration using solar observations

DOE PAGES

Urquhart, Bryan; Kurtz, Ben; Kleissl, Jan

2016-09-05

A camera model and associated automated calibration procedure for stationary daytime sky imaging cameras is presented. The specific modeling and calibration needs are motivated by remotely deployed cameras used to forecast solar power production where cameras point skyward and use 180° fisheye lenses. Sun position in the sky and on the image plane provides a simple and automated approach to calibration; special equipment or calibration patterns are not required. Sun position in the sky is modeled using a solar position algorithm (requiring latitude, longitude, altitude and time as inputs). Sun position on the image plane is detected using a simple image processing algorithm. Themore » performance evaluation focuses on the calibration of a camera employing a fisheye lens with an equisolid angle projection, but the camera model is general enough to treat most fixed focal length, central, dioptric camera systems with a photo objective lens. Calibration errors scale with the noise level of the sun position measurement in the image plane, but the calibration is robust across a large range of noise in the sun position. In conclusion, calibration performance on clear days ranged from 0.94 to 1.24 pixels root mean square error.« less

In vivo neuronal calcium imaging in C. elegans.

PubMed

Chung, Samuel H; Sun, Lin; Gabel, Christopher V

2013-04-10

The nematode worm C. elegans is an ideal model organism for relatively simple, low cost neuronal imaging in vivo. Its small transparent body and simple, well-characterized nervous system allows identification and fluorescence imaging of any neuron within the intact animal. Simple immobilization techniques with minimal impact on the animal's physiology allow extended time-lapse imaging. The development of genetically-encoded calcium sensitive fluorophores such as cameleon and GCaMP allow in vivo imaging of neuronal calcium relating both cell physiology and neuronal activity. Numerous transgenic strains expressing these fluorophores in specific neurons are readily available or can be constructed using well-established techniques. Here, we describe detailed procedures for measuring calcium dynamics within a single neuron in vivo using both GCaMP and cameleon. We discuss advantages and disadvantages of both as well as various methods of sample preparation (animal immobilization) and image analysis. Finally, we present results from two experiments: 1) Using GCaMP to measure the sensory response of a specific neuron to an external electrical field and 2) Using cameleon to measure the physiological calcium response of a neuron to traumatic laser damage. Calcium imaging techniques such as these are used extensively in C. elegans and have been extended to measurements in freely moving animals, multiple neurons simultaneously and comparison across genetic backgrounds. C. elegans presents a robust and flexible system for in vivo neuronal imaging with advantages over other model systems in technical simplicity and cost.

Modeling the Effects of Beam Size and Flaw Morphology on Ultrasonic Pulse/Echo Sizing of Delaminations in Carbon Composites

NASA Technical Reports Server (NTRS)

Margetan, Frank J.; Leckey, Cara A.; Barnard, Dan

2012-01-01

The size and shape of a delamination in a multi-layered structure can be estimated in various ways from an ultrasonic pulse/echo image. For example the -6dB contours of measured response provide one simple estimate of the boundary. More sophisticated approaches can be imagined where one adjusts the proposed boundary to bring measured and predicted UT images into optimal agreement. Such approaches require suitable models of the inspection process. In this paper we explore issues pertaining to model-based size estimation for delaminations in carbon fiber reinforced laminates. In particular we consider the influence on sizing when the delamination is non-planar or partially transmitting in certain regions. Two models for predicting broadband sonic time-domain responses are considered: (1) a fast "simple" model using paraxial beam expansions and Kirchhoff and phase-screen approximations; and (2) the more exact (but computationally intensive) 3D elastodynamic finite integration technique (EFIT). Model-to-model and model-to experiment comparisons are made for delaminations in uniaxial composite plates, and the simple model is then used to critique the -6dB rule for delamination sizing.

Binary encoding of multiplexed images in mixed noise.

PubMed

Lalush, David S

2008-09-01

Binary coding of multiplexed signals and images has been studied in the context of spectroscopy with models of either purely constant or purely proportional noise, and has been shown to result in improved noise performance under certain conditions. We consider the case of mixed noise in an imaging system consisting of multiple individually-controllable sources (X-ray or near-infrared, for example) shining on a single detector. We develop a mathematical model for the noise in such a system and show that the noise is dependent on the properties of the binary coding matrix and on the average number of sources used for each code. Each binary matrix has a characteristic linear relationship between the ratio of proportional-to-constant noise and the noise level in the decoded image. We introduce a criterion for noise level, which is minimized via a genetic algorithm search. The search procedure results in the discovery of matrices that outperform the Hadamard S-matrices at certain levels of mixed noise. Simulation of a seven-source radiography system demonstrates that the noise model predicts trends and rank order of performance in regions of nonuniform images and in a simple tomosynthesis reconstruction. We conclude that the model developed provides a simple framework for analysis, discovery, and optimization of binary coding patterns used in multiplexed imaging systems.

Modeling down-scattered neutron images from cryogenic fuel implosions at the National Ignition Facility

NASA Astrophysics Data System (ADS)

Raman, Kumar; Casey, Dan; Callahan, Debra; Clark, Dan; Fittinghoff, David; Grim, Gary; Hatchett, Steve; Hinkel, Denise; Jones, Ogden; Kritcher, Andrea; Seek, Scott; Suter, Larry; Merrill, Frank; Wilson, Doug

2016-10-01

In experiments with cryogenic deuterium-tritium (DT) fuel layers at the National Ignition Facility (NIF), an important technique for visualizing the stagnated fuel assembly is to image the 6-12 MeV neutrons created by scatters of the 14 MeV hotspot neutrons in the surrounding cold fuel. However, such down-scattered neutron images are difficult to interpret without a model of the fuel assembly, because of the nontrivial neutron kinematics involved in forming the images. For example, the dominant scattering modes are at angles other than forward scattering and the 14 MeV neutron fluence is not uniform. Therefore, the intensity patterns in these images usually do not correspond in a simple way to patterns in the fuel distribution, even for simple fuel distributions. We describe our efforts to model synthetic images from ICF design simulations with data from the National Ignition Campaign and after. We discuss the insight this gives, both to understand how well the models are predicting fuel asymmetries and to inform how to optimize the diagnostic for the types of fuel distributions being predicted. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

A simple underwater imaging model.

PubMed

Hou, Weilin

2009-09-01

It is commonly known that underwater imaging is hindered by both absorption and scattering by particles of various origins. However, evidence also indicates that the turbulence in natural underwater environments can cause severe image-quality degradation. A model is presented to include the effects of both particle and turbulence on underwater optical imaging through optical transfer functions to help quantify the limiting factors under different circumstances. The model utilizes Kolmogorov-type index of refraction power spectra found in the ocean, along with field examples, to demonstrate that optical turbulence can limit imaging resolution by affecting high spatial frequencies. The effects of the path radiance are also discussed.

Recognition of simple visual images using a sparse distributed memory: Some implementations and experiments

NASA Technical Reports Server (NTRS)

Jaeckel, Louis A.

1990-01-01

Previously, a method was described of representing a class of simple visual images so that they could be used with a Sparse Distributed Memory (SDM). Herein, two possible implementations are described of a SDM, for which these images, suitably encoded, will serve both as addresses to the memory and as data to be stored in the memory. A key feature of both implementations is that a pattern that is represented as an unordered set with a variable number of members can be used as an address to the memory. In the 1st model, an image is encoded as a 9072 bit string to be used as a read or write address; the bit string may also be used as data to be stored in the memory. Another representation, in which an image is encoded as a 256 bit string, may be used with either model as data to be stored in the memory, but not as an address. In the 2nd model, an image is not represented as a vector of fixed length to be used as an address. Instead, a rule is given for determining which memory locations are to be activated in response to an encoded image. This activation rule treats the pieces of an image as an unordered set. With this model, the memory can be simulated, based on a method of computing the approximate result of a read operation.

Directional x-ray dark-field imaging of strongly ordered systems

NASA Astrophysics Data System (ADS)

Jensen, Torben Haugaard; Bech, Martin; Zanette, Irene; Weitkamp, Timm; David, Christian; Deyhle, Hans; Rutishauser, Simon; Reznikova, Elena; Mohr, Jürgen; Feidenhans'L, Robert; Pfeiffer, Franz

2010-12-01

Recently a novel grating based x-ray imaging approach called directional x-ray dark-field imaging was introduced. Directional x-ray dark-field imaging yields information about the local texture of structures smaller than the pixel size of the imaging system. In this work we extend the theoretical description and data processing schemes for directional dark-field imaging to strongly scattering systems, which could not be described previously. We develop a simple scattering model to account for these recent observations and subsequently demonstrate the model using experimental data. The experimental data includes directional dark-field images of polypropylene fibers and a human tooth slice.

A comparison of quantitative methods for clinical imaging with hyperpolarized (13)C-pyruvate.

PubMed

Daniels, Charlie J; McLean, Mary A; Schulte, Rolf F; Robb, Fraser J; Gill, Andrew B; McGlashan, Nicholas; Graves, Martin J; Schwaiger, Markus; Lomas, David J; Brindle, Kevin M; Gallagher, Ferdia A

2016-04-01

Dissolution dynamic nuclear polarization (DNP) enables the metabolism of hyperpolarized (13)C-labelled molecules, such as the conversion of [1-(13)C]pyruvate to [1-(13)C]lactate, to be dynamically and non-invasively imaged in tissue. Imaging of this exchange reaction in animal models has been shown to detect early treatment response and correlate with tumour grade. The first human DNP study has recently been completed, and, for widespread clinical translation, simple and reliable methods are necessary to accurately probe the reaction in patients. However, there is currently no consensus on the most appropriate method to quantify this exchange reaction. In this study, an in vitro system was used to compare several kinetic models, as well as simple model-free methods. Experiments were performed using a clinical hyperpolarizer, a human 3 T MR system, and spectroscopic imaging sequences. The quantitative methods were compared in vivo by using subcutaneous breast tumours in rats to examine the effect of pyruvate inflow. The two-way kinetic model was the most accurate method for characterizing the exchange reaction in vitro, and the incorporation of a Heaviside step inflow profile was best able to describe the in vivo data. The lactate time-to-peak and the lactate-to-pyruvate area under the curve ratio were simple model-free approaches that accurately represented the full reaction, with the time-to-peak method performing indistinguishably from the best kinetic model. Finally, extracting data from a single pixel was a robust and reliable surrogate of the whole region of interest. This work has identified appropriate quantitative methods for future work in the analysis of human hyperpolarized (13)C data. © 2016 The Authors. NMR in Biomedicine published by John Wiley & Sons Ltd.

Charge Transfer Inefficiency in Pinned Photodiode CMOS image sensors: Simple Montecarlo modeling and experimental measurement based on a pulsed storage-gate method

NASA Astrophysics Data System (ADS)

Pelamatti, Alice; Goiffon, Vincent; Chabane, Aziouz; Magnan, Pierre; Virmontois, Cédric; Saint-Pé, Olivier; de Boisanger, Michel Breart

2016-11-01

The charge transfer time represents the bottleneck in terms of temporal resolution in Pinned Photodiode (PPD) CMOS image sensors. This work focuses on the modeling and estimation of this key parameter. A simple numerical model of charge transfer in PPDs is presented. The model is based on a Montecarlo simulation and takes into account both charge diffusion in the PPD and the effect of potential obstacles along the charge transfer path. This work also presents a new experimental approach for the estimation of the charge transfer time, called pulsed Storage Gate (SG) method. This method, which allows reproduction of a ;worst-case; transfer condition, is based on dedicated SG pixel structures and is particularly suitable to compare transfer efficiency performances for different pixel geometries.

Geological terrain models

NASA Technical Reports Server (NTRS)

Kaupp, V. H.; Macdonald, H. C.; Waite, W. P.

1981-01-01

The initial phase of a program to determine the best interpretation strategy and sensor configuration for a radar remote sensing system for geologic applications is discussed. In this phase, terrain modeling and radar image simulation were used to perform parametric sensitivity studies. A relatively simple computer-generated terrain model is presented, and the data base, backscatter file, and transfer function for digital image simulation are described. Sets of images are presented that simulate the results obtained with an X-band radar from an altitude of 800 km and at three different terrain-illumination angles. The simulations include power maps, slant-range images, ground-range images, and ground-range images with statistical noise incorporated. It is concluded that digital image simulation and computer modeling provide cost-effective methods for evaluating terrain variations and sensor parameter changes, for predicting results, and for defining optimum sensor parameters.

Stroke-model-based character extraction from gray-level document images.

PubMed

Ye, X; Cheriet, M; Suen, C Y

2001-01-01

Global gray-level thresholding techniques such as Otsu's method, and local gray-level thresholding techniques such as edge-based segmentation or the adaptive thresholding method are powerful in extracting character objects from simple or slowly varying backgrounds. However, they are found to be insufficient when the backgrounds include sharply varying contours or fonts in different sizes. A stroke-model is proposed to depict the local features of character objects as double-edges in a predefined size. This model enables us to detect thin connected components selectively, while ignoring relatively large backgrounds that appear complex. Meanwhile, since the stroke width restriction is fully factored in, the proposed technique can be used to extract characters in predefined font sizes. To process large volumes of documents efficiently, a hybrid method is proposed for character extraction from various backgrounds. Using the measurement of class separability to differentiate images with simple backgrounds from those with complex backgrounds, the hybrid method can process documents with different backgrounds by applying the appropriate methods. Experiments on extracting handwriting from a check image, as well as machine-printed characters from scene images demonstrate the effectiveness of the proposed model.

Spatial Pattern of Cell Damage in Tissue from Heavy Ions

NASA Technical Reports Server (NTRS)

Ponomarev, Artem L.; Huff, Janice L.; Cucinotta, Francis A.

2007-01-01

A new Monte Carlo algorithm was developed that can model passage of heavy ions in a tissue, and their action on the cellular matrix for 2- or 3-dimensional cases. The build-up of secondaries such as projectile fragments, target fragments, other light fragments, and delta-rays was simulated. Cells were modeled as a cell culture monolayer in one example, where the data were taken directly from microscopy (2-d cell matrix). A simple model of tissue was given as abstract spheres with close approximation to real cell geometries (3-d cell matrix), as well as a realistic model of tissue was proposed based on microscopy images. Image segmentation was used to identify cells in an irradiated cell culture monolayer, or slices of tissue. The cells were then inserted into the model box pixel by pixel. In the case of cell monolayers (2-d), the image size may exceed the modeled box size. Such image was is moved with respect to the box in order to sample as many cells as possible. In the case of the simple tissue (3-d), the tissue box is modeled with periodic boundary conditions, which extrapolate the technique to macroscopic volumes of tissue. For real tissue, specific spatial patterns for cell apoptosis and necrosis are expected. The cell patterns were modeled based on action cross sections for apoptosis and necrosis estimated based on BNL data, and other experimental data.

libprofit: Image creation from luminosity profiles

NASA Astrophysics Data System (ADS)

Robotham, A. S. G.; Taranu, D.; Tobar, R.

2016-12-01

libprofit is a C++ library for image creation based on different luminosity profiles. It offers fast and accurate two-dimensional integration for a useful number of profiles, including Sersic, Core-Sersic, broken-exponential, Ferrer, Moffat, empirical King, point-source and sky, with a simple mechanism for adding new profiles. libprofit provides a utility to read the model and profile parameters from the command-line and generate the corresponding image. It can output the resulting image as text values, a binary stream, or as a simple FITS file. It also provides a shared library exposing an API that can be used by any third-party application. R and Python interfaces are available: ProFit (ascl:1612.004) and PyProfit (ascl:1612.005).

Modeling of the laser device for the stress therapy

NASA Astrophysics Data System (ADS)

Matveev, Nikolai V.; Shcheglov, Sergey A.; Romanova, Galina E.; Koneva, Ð.¢atiana A.

2017-05-01

Recently there is a great interest to the drug-free methods of treatment of various diseases. For example, audiovisual therapy is used for the stress therapy. The main destination of the method is the health care and well-being. Visual content in the given case is formed when laser radiation is passing through the optical mediums and elements. The therapy effect is achieved owing to the color varying and complicated structure of the picture which is produced by the refraction, dispersion effects, diffraction and interference. As the laser source we use three laser sources with wavelengths of 445 nm, 520 nm and 640 nm and the optical power up to 1 W. The beam is guided to the optical element which is responsible for the final image of the dome surface. The dynamic image can be achieved by the rotating of the optical element when the laser beam is static or by scanning the surface of the element. Previous research has shown that the complexity of the image connected to the therapy effect. The image was chosen experimentally in practice. The evaluation was performed using the fractal dimension calculation for the produced image. In this work we model the optical image on the surface formed by the laser sources together with the optical elements. Modeling is performed in two stages. On the first stage we perform the simple modeling taking into account simple geometrical effects and specify the optical models of the sources.

2D hybrid analysis: Approach for building three-dimensional atomic model by electron microscopy image matching.

PubMed

Matsumoto, Atsushi; Miyazaki, Naoyuki; Takagi, Junichi; Iwasaki, Kenji

2017-03-23

In this study, we develop an approach termed "2D hybrid analysis" for building atomic models by image matching from electron microscopy (EM) images of biological molecules. The key advantage is that it is applicable to flexible molecules, which are difficult to analyze by 3DEM approach. In the proposed approach, first, a lot of atomic models with different conformations are built by computer simulation. Then, simulated EM images are built from each atomic model. Finally, they are compared with the experimental EM image. Two kinds of models are used as simulated EM images: the negative stain model and the simple projection model. Although the former is more realistic, the latter is adopted to perform faster computations. The use of the negative stain model enables decomposition of the averaged EM images into multiple projection images, each of which originated from a different conformation or orientation. We apply this approach to the EM images of integrin to obtain the distribution of the conformations, from which the pathway of the conformational change of the protein is deduced.

COSMOGRAIL: the COSmological MOnitoring of GRAvItational Lenses. VIII. Deconvolution of high resolution near-IR images and simple mass models for 7 gravitationally lensed quasars

NASA Astrophysics Data System (ADS)

Chantry, V.; Sluse, D.; Magain, P.

2010-11-01

Aims: We attempt to place very accurate positional constraints on seven gravitationally lensed quasars currently being monitored by the COSMOGRAIL collaboration, and shape parameters for the light distribution of the lensing galaxy. We attempt to determine simple mass models that reproduce the observed configuration and predict time delays. We finally test, for the quads, whether there is evidence of astrometric perturbations produced by substructures in the lensing galaxy, which may preclude a good fit with the simple models. Methods: We apply the iterative MCS deconvolution method to near-IR HST archival data of seven gravitationally lensed quasars. This deconvolution method allows us to differentiate the contributions of the point sources from those of extended structures such as Einstein rings. This method leads to an accuracy of 1-2 mas in the relative positions of the sources and lens. The limiting factor of the method is the uncertainty in the instrumental geometric distortions. We then compute mass models of the lensing galaxy using state-of-the-art modeling techniques. Results: We determine the relative positions of the lensed images and lens shape parameters of seven lensed quasars: HE 0047-1756, RX J1131-1231, SDSS J1138+0314, SDSS J1155+6346, SDSS J1226-0006, WFI J2026-4536, and HS 2209+1914. The lensed image positions are derived with 1-2 mas accuracy. Isothermal and de Vaucouleurs mass models are calculated for the whole sample. The effect of the lens environment on the lens mass models is taken into account with a shear term. Doubly imaged quasars are equally well fitted by each of these models. A large amount of shear is necessary to reproduce SDSS J1155+6346 and SDSS J1226-006. In the latter case, we identify a nearby galaxy as the dominant source of shear. The quadruply imaged quasar SDSS J1138+0314 is reproduced well by simple lens models, which is not the case for the two other quads, RX J1131-1231 and WFI J2026-4536. This might be the signature of astrometric perturbations caused by massive substructures in the galaxy, which are unaccounted for by the models. Other possible explanations are also presented. Based on observations made with the NASA/ESA HST Hubble Space Telescope, obtained from the data archive at the Space Science Institute, which is operated by AURA, the Association of Universities for Research in Astronomy, Inc., under NASA contract NAS-5-26555.

Reconstruction of implanted marker trajectories from cone-beam CT projection images using interdimensional correlation modeling

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

Chung, Hyekyun

Purpose: Cone-beam CT (CBCT) is a widely used imaging modality for image-guided radiotherapy. Most vendors provide CBCT systems that are mounted on a linac gantry. Thus, CBCT can be used to estimate the actual 3-dimensional (3D) position of moving respiratory targets in the thoracic/abdominal region using 2D projection images. The authors have developed a method for estimating the 3D trajectory of respiratory-induced target motion from CBCT projection images using interdimensional correlation modeling. Methods: Because the superior–inferior (SI) motion of a target can be easily analyzed on projection images of a gantry-mounted CBCT system, the authors investigated the interdimensional correlation ofmore » the SI motion with left–right and anterior–posterior (AP) movements while the gantry is rotating. A simple linear model and a state-augmented model were implemented and applied to the interdimensional correlation analysis, and their performance was compared. The parameters of the interdimensional correlation models were determined by least-square estimation of the 2D error between the actual and estimated projected target position. The method was validated using 160 3D tumor trajectories from 46 thoracic/abdominal cancer patients obtained during CyberKnife treatment. The authors’ simulations assumed two application scenarios: (1) retrospective estimation for the purpose of moving tumor setup used just after volumetric matching with CBCT; and (2) on-the-fly estimation for the purpose of real-time target position estimation during gating or tracking delivery, either for full-rotation volumetric-modulated arc therapy (VMAT) in 60 s or a stationary six-field intensity-modulated radiation therapy (IMRT) with a beam delivery time of 20 s. Results: For the retrospective CBCT simulations, the mean 3D root-mean-square error (RMSE) for all 4893 trajectory segments was 0.41 mm (simple linear model) and 0.35 mm (state-augmented model). In the on-the-fly simulations, prior projections over more than 60° appear to be necessary for reliable estimations. The mean 3D RMSE during beam delivery after the simple linear model had established with a prior 90° projection data was 0.42 mm for VMAT and 0.45 mm for IMRT. Conclusions: The proposed method does not require any internal/external correlation or statistical modeling to estimate the target trajectory and can be used for both retrospective image-guided radiotherapy with CBCT projection images and real-time target position monitoring for respiratory gating or tracking.« less

Markov source model for printed music decoding

NASA Astrophysics Data System (ADS)

Kopec, Gary E.; Chou, Philip A.; Maltz, David A.

1995-03-01

This paper describes a Markov source model for a simple subset of printed music notation. The model is based on the Adobe Sonata music symbol set and a message language of our own design. Chord imaging is the most complex part of the model. Much of the complexity follows from a rule of music typography that requires the noteheads for adjacent pitches to be placed on opposite sides of the chord stem. This rule leads to a proliferation of cases for other typographic details such as dot placement. We describe the language of message strings accepted by the model and discuss some of the imaging issues associated with various aspects of the message language. We also point out some aspects of music notation that appear problematic for a finite-state representation. Development of the model was greatly facilitated by the duality between image synthesis and image decoding. Although our ultimate objective was a music image model for use in decoding, most of the development proceeded by using the evolving model for image synthesis, since it is computationally far less costly to image a message than to decode an image.

Incorporating User Input in Template-Based Segmentation

PubMed Central

Vidal, Camille; Beggs, Dale; Younes, Laurent; Jain, Sanjay K.; Jedynak, Bruno

2015-01-01

We present a simple and elegant method to incorporate user input in a template-based segmentation method for diseased organs. The user provides a partial segmentation of the organ of interest, which is used to guide the template towards its target. The user also highlights some elements of the background that should be excluded from the final segmentation. We derive by likelihood maximization a registration algorithm from a simple statistical image model in which the user labels are modeled as Bernoulli random variables. The resulting registration algorithm minimizes the sum of square differences between the binary template and the user labels, while preventing the template from shrinking, and penalizing for the inclusion of background elements into the final segmentation. We assess the performance of the proposed algorithm on synthetic images in which the amount of user annotation is controlled. We demonstrate our algorithm on the segmentation of the lungs of Mycobacterium tuberculosis infected mice from μCT images. PMID:26146532

Analysis of lithology: Vegetation mixes in multispectral images

NASA Technical Reports Server (NTRS)

Adams, J. B.; Smith, M.; Adams, J. D.

1982-01-01

Discrimination and identification of lithologies from multispectral images is discussed. Rock/soil identification can be facilitated by removing the component of the signal in the images that is contributed by the vegetation. Mixing models were developed to predict the spectra of combinations of pure end members, and those models were refined using laboratory measurements of real mixtures. Models in use include a simple linear (checkerboard) mix, granular mixing, semi-transparent coatings, and combinations of the above. The use of interactive computer techniques that allow quick comparison of the spectrum of a pixel stack (in a multiband set) with laboratory spectra is discussed.

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines

PubMed Central

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-01-01

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately. PMID:27879843

Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines.

PubMed

Karas, Ismail Rakip; Bayram, Bulent; Batuk, Fatmagul; Akay, Abdullah Emin; Baz, Ibrahim

2008-04-15

This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction), for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD), indicated that the model can successfully vectorize the specified raster data quickly and accurately.

The Top 10 List of Gravitational Lens Candidates from the HUBBLE SPACE TELESCOPE Medium Deep Survey

NASA Astrophysics Data System (ADS)

Ratnatunga, Kavan U.; Griffiths, Richard E.; Ostrander, Eric J.

1999-05-01

A total of 10 good candidates for gravitational lensing have been discovered in the WFPC2 images from the Hubble Space Telescope (HST) Medium Deep Survey (MDS) and archival primary observations. These candidate lenses are unique HST discoveries, i.e., they are faint systems with subarcsecond separations between the lensing objects and the lensed source images. Most of them are difficult objects for ground-based spectroscopic confirmation or for measurement of the lens and source redshifts. Seven are ``strong lens'' candidates that appear to have multiple images of the source. Three are cases in which the single image of the source galaxy has been significantly distorted into an arc. The first two quadruply lensed candidates were reported by Ratnatunga et al. We report on the subsequent eight candidates and describe them with simple models based on the assumption of singular isothermal potentials. Residuals from the simple models for some of the candidates indicate that a more complex model for the potential will probably be required to explain the full structural detail of the observations once they are confirmed to be lenses. We also discuss the effective survey area that was searched for these candidate lens objects.

A simple inertial model for Neptune's zonal circulation

NASA Technical Reports Server (NTRS)

Allison, Michael; Lumetta, James T.

1990-01-01

Voyager imaging observations of zonal cloud-tracked winds on Neptune revealed a strongly subrotational equatorial jet with a speed approaching 500 m/s and generally decreasing retrograde motion toward the poles. The wind data are interpreted with a speculative but revealingly simple model based on steady gradient flow balance and an assumed global homogenization of potential vorticity for shallow layer motion. The prescribed model flow profile relates the equatorial velocity to the mid-latitude shear, in reasonable agreement with the available data, and implies a global horizontal deformation scale L(D) of about 3000 km.

Estimation of color filter array data from JPEG images for improved demosaicking

NASA Astrophysics Data System (ADS)

Feng, Wei; Reeves, Stanley J.

2006-02-01

On-camera demosaicking algorithms are necessarily simple and therefore do not yield the best possible images. However, off-camera demosaicking algorithms face the additional challenge that the data has been compressed and therefore corrupted by quantization noise. We propose a method to estimate the original color filter array (CFA) data from JPEG-compressed images so that more sophisticated (and better) demosaicking schemes can be applied to get higher-quality images. The JPEG image formation process, including simple demosaicking, color space transformation, chrominance channel decimation and DCT, is modeled as a series of matrix operations followed by quantization on the CFA data, which is estimated by least squares. An iterative method is used to conserve memory and speed computation. Our experiments show that the mean square error (MSE) with respect to the original CFA data is reduced significantly using our algorithm, compared to that of unprocessed JPEG and deblocked JPEG data.

A simple model for deep tissue attenuation correction and large organ analysis of Cerenkov luminescence imaging

NASA Astrophysics Data System (ADS)

Habte, Frezghi; Natarajan, Arutselvan; Paik, David S.; Gambhir, Sanjiv S.

2014-03-01

Cerenkov luminescence imaging (CLI) is an emerging cost effective modality that uses conventional small animal optical imaging systems and clinically available radionuclide probes for light emission. CLI has shown good correlation with PET for organs of high uptake such as kidney, spleen, thymus and subcutaneous tumors in mouse models. However, CLI has limitations for deep tissue quantitative imaging since the blue-weighted spectral characteristics of Cerenkov radiation attenuates highly by mammalian tissue. Large organs such as the liver have also shown higher signal due to the contribution of emission of light from a greater thickness of tissue. In this study, we developed a simple model that estimates the effective tissue attenuation coefficient in order to correct the CLI signal intensity with a priori estimated depth and thickness of specific organs. We used several thin slices of ham to build a phantom with realistic attenuation. We placed radionuclide sources inside the phantom at different tissue depths and imaged it using an IVIS Spectrum (Perkin-Elmer, Waltham, MA, USA) and Inveon microPET (Preclinical Solutions Siemens, Knoxville, TN). We also performed CLI and PET of mouse models and applied the proposed attenuation model to correct CLI measurements. Using calibration factors obtained from phantom study that converts the corrected CLI measurements to %ID/g, we obtained an average difference of less that 10% for spleen and less than 35% for liver compared to conventional PET measurements. Hence, the proposed model has a capability of correcting the CLI signal to provide comparable measurements with PET data.

Luminance-model-based DCT quantization for color image compression

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Peterson, Heidi A.

1992-01-01

A model is developed to approximate visibility thresholds for discrete cosine transform (DCT) coefficient quantization error based on the peak-to-peak luminance of the error image. Experimentally measured visibility thresholds for R, G, and B DCT basis functions can be predicted by a simple luminance-based detection model. This model allows DCT coefficient quantization matrices to be designed for display conditions other than those of the experimental measurements: other display luminances, other veiling luminances, and other spatial frequencies (different pixel spacings, viewing distances, and aspect ratios).

The Money-Creation Model: An Alternative Pedagogy.

ERIC Educational Resources Information Center

Thornton, Mark; And Others

1991-01-01

Presents a teaching model that is consistent with the traditional approach to demonstrating the expansion and contraction of the money supply. Suggests that the model provides a simple and convenient visual image of changes in the monetary system. Describes the model as juxtaposing the behavior of the moneyholding public with that of the…

Dosimetry in x-ray-based breast imaging

PubMed Central

Dance, David R; Sechopoulos, Ioannis

2016-01-01

The estimation of the mean glandular dose to the breast (MGD) for x-ray based imaging modalities forms an essential part of quality control and is needed for risk estimation and for system design and optimisation. This review considers the development of methods for estimating the MGD for mammography, digital breast tomosynthesis (DBT) and dedicated breast CT (DBCT). Almost all of the methodology used employs Monte Carlo calculated conversion factors to relate the measurable quantity, generally the incident air kerma, to the MGD. After a review of the size and composition of the female breast, the various mathematical models used are discussed, with particular emphasis on models for mammography. These range from simple geometrical shapes, to the more recent complex models based on patient DBCT examinations. The possibility of patient-specific dose estimates is considered as well as special diagnostic views and the effect of breast implants. Calculations using the complex models show that the MGD for mammography is overestimated by about 30% when the simple models are used. The design and uses of breast-simulating test phantoms for measuring incident air kerma are outlined and comparisons made between patient and phantom-based dose estimates. The most widely used national and international dosimetry protocols for mammography are based on different simple geometrical models of the breast, and harmonisation of these protocols using more complex breast models is desirable. PMID:27617767

Dosimetry in x-ray-based breast imaging

NASA Astrophysics Data System (ADS)

Dance, David R.; Sechopoulos, Ioannis

2016-10-01

The estimation of the mean glandular dose to the breast (MGD) for x-ray based imaging modalities forms an essential part of quality control and is needed for risk estimation and for system design and optimisation. This review considers the development of methods for estimating the MGD for mammography, digital breast tomosynthesis (DBT) and dedicated breast CT (DBCT). Almost all of the methodology used employs Monte Carlo calculated conversion factors to relate the measurable quantity, generally the incident air kerma, to the MGD. After a review of the size and composition of the female breast, the various mathematical models used are discussed, with particular emphasis on models for mammography. These range from simple geometrical shapes, to the more recent complex models based on patient DBCT examinations. The possibility of patient-specific dose estimates is considered as well as special diagnostic views and the effect of breast implants. Calculations using the complex models show that the MGD for mammography is overestimated by about 30% when the simple models are used. The design and uses of breast-simulating test phantoms for measuring incident air kerma are outlined and comparisons made between patient and phantom-based dose estimates. The most widely used national and international dosimetry protocols for mammography are based on different simple geometrical models of the breast, and harmonisation of these protocols using more complex breast models is desirable.

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

NASA Technical Reports Server (NTRS)

Abbey, Craig K.; Eckstein, Miguel P.

2002-01-01

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

MAPPING ANNUAL MEAN GROUND-LEVEL PM2.5 CONCENTRATIONS USING MULTIANGLE IMAGING SPECTRORADIOMETER AEROSOL OPTICAL THICKNESS OVER THE CONTIGUOUS UNITED STATES

EPA Science Inventory

We present a simple approach to estimating ground-level fine particle (PM2.5, particles smaller than 2.5 um in diameter) concentration using global atmospheric chemistry models and aerosol optical thickness (AOT) measurements from the Multi- angle Imaging SpectroRadiometer (MISR)...

A data compression technique for synthetic aperture radar images

NASA Technical Reports Server (NTRS)

Frost, V. S.; Minden, G. J.

1986-01-01

A data compression technique is developed for synthetic aperture radar (SAR) imagery. The technique is based on an SAR image model and is designed to preserve the local statistics in the image by an adaptive variable rate modification of block truncation coding (BTC). A data rate of approximately 1.6 bit/pixel is achieved with the technique while maintaining the image quality and cultural (pointlike) targets. The algorithm requires no large data storage and is computationally simple.

Full-wave Nonlinear Inverse Scattering for Acoustic and Electromagnetic Breast Imaging

NASA Astrophysics Data System (ADS)

Haynes, Mark Spencer

Acoustic and electromagnetic full-wave nonlinear inverse scattering techniques are explored in both theory and experiment with the ultimate aim of noninvasively mapping the material properties of the breast. There is evidence that benign and malignant breast tissue have different acoustic and electrical properties and imaging these properties directly could provide higher quality images with better diagnostic certainty. In this dissertation, acoustic and electromagnetic inverse scattering algorithms are first developed and validated in simulation. The forward solvers and optimization cost functions are modified from traditional forms in order to handle the large or lossy imaging scenes present in ultrasonic and microwave breast imaging. An antenna model is then presented, modified, and experimentally validated for microwave S-parameter measurements. Using the antenna model, a new electromagnetic volume integral equation is derived in order to link the material properties of the inverse scattering algorithms to microwave S-parameters measurements allowing direct comparison of model predictions and measurements in the imaging algorithms. This volume integral equation is validated with several experiments and used as the basis of a free-space inverse scattering experiment, where images of the dielectric properties of plastic objects are formed without the use of calibration targets. These efforts are used as the foundation of a solution and formulation for the numerical characterization of a microwave near-field cavity-based breast imaging system. The system is constructed and imaging results of simple targets are given. Finally, the same techniques are used to explore a new self-characterization method for commercial ultrasound probes. The method is used to calibrate an ultrasound inverse scattering experiment and imaging results of simple targets are presented. This work has demonstrated the feasibility of quantitative microwave inverse scattering by way of a self-consistent characterization formalism, and has made headway in the same area for ultrasound.

A simple method for imaging axonal transport in aging neurons using the adult Drosophila wing.

PubMed

Vagnoni, Alessio; Bullock, Simon L

2016-09-01

There is growing interest in the link between axonal cargo transport and age-associated neuronal dysfunction. The study of axonal transport in neurons of adult animals requires intravital or ex vivo imaging approaches, which are laborious and expensive in vertebrate models. We describe simple, noninvasive procedures for imaging cargo motility within axons using sensory neurons of the translucent Drosophila wing. A key aspect is a method for mounting the intact fly that allows detailed imaging of transport in wing neurons. Coupled with existing genetic tools in Drosophila, this is a tractable system for studying axonal transport over the life span of an animal and thus for characterization of the relationship between cargo dynamics, neuronal aging and disease. Preparation of a sample for imaging takes ∼5 min, with transport typically filmed for 2-3 min per wing. We also document procedures for the quantification of transport parameters from the acquired images and describe how the protocol can be adapted to study other cell biological processes in aging neurons.

The Evolution of Transition Region Loops Using IRIS and AIA

NASA Technical Reports Server (NTRS)

Winebarger, Amy R.; DePontieu, Bart

2014-01-01

Over the past 50 years, the model for the structure of the solar transition region has evolved from a simple transition layer between the cooler chromosphere to the hotter corona to a complex and diverse region that is dominated by complete loops that never reach coronal temperatures. The IRIS slitjaw images show many complete transition region loops. Several of the "coronal" channels in the SDO AIA instrument include contributions from weak transition region lines. In this work, we combine slitjaw images from IRIS with these channels to determine the evolution of the loops. We develop a simple model for the temperature and density evolution of the loops that can explain the simultaneous observations. Finally, we estimate the percentage of AIA emission that originates in the transition region.

Phase Diagrams of Three-Dimensional Anderson and Quantum Percolation Models Using Deep Three-Dimensional Convolutional Neural Network

NASA Astrophysics Data System (ADS)

Mano, Tomohiro; Ohtsuki, Tomi

2017-11-01

The three-dimensional Anderson model is a well-studied model of disordered electron systems that shows the delocalization-localization transition. As in our previous papers on two- and three-dimensional (2D, 3D) quantum phase transitions [J. Phys. Soc. Jpn. 85, 123706 (2016), 86, 044708 (2017)], we used an image recognition algorithm based on a multilayered convolutional neural network. However, in contrast to previous papers in which 2D image recognition was used, we applied 3D image recognition to analyze entire 3D wave functions. We show that a full phase diagram of the disorder-energy plane is obtained once the 3D convolutional neural network has been trained at the band center. We further demonstrate that the full phase diagram for 3D quantum bond and site percolations can be drawn by training the 3D Anderson model at the band center.

CCD image sensor induced error in PIV applications

NASA Astrophysics Data System (ADS)

Legrand, M.; Nogueira, J.; Vargas, A. A.; Ventas, R.; Rodríguez-Hidalgo, M. C.

2014-06-01

The readout procedure of charge-coupled device (CCD) cameras is known to generate some image degradation in different scientific imaging fields, especially in astrophysics. In the particular field of particle image velocimetry (PIV), widely extended in the scientific community, the readout procedure of the interline CCD sensor induces a bias in the registered position of particle images. This work proposes simple procedures to predict the magnitude of the associated measurement error. Generally, there are differences in the position bias for the different images of a certain particle at each PIV frame. This leads to a substantial bias error in the PIV velocity measurement (˜0.1 pixels). This is the order of magnitude that other typical PIV errors such as peak-locking may reach. Based on modern CCD technology and architecture, this work offers a description of the readout phenomenon and proposes a modeling for the CCD readout bias error magnitude. This bias, in turn, generates a velocity measurement bias error when there is an illumination difference between two successive PIV exposures. The model predictions match the experiments performed with two 12-bit-depth interline CCD cameras (MegaPlus ES 4.0/E incorporating the Kodak KAI-4000M CCD sensor with 4 megapixels). For different cameras, only two constant values are needed to fit the proposed calibration model and predict the error from the readout procedure. Tests by different researchers using different cameras would allow verification of the model, that can be used to optimize acquisition setups. Simple procedures to obtain these two calibration values are also described.

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.

The Two-Dimensional Gabor Function Adapted to Natural Image Statistics: A Model of Simple-Cell Receptive Fields and Sparse Structure in Images.

PubMed

Loxley, P N

2017-10-01

The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple cell receptive field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor function parameters representing the size and spatial frequency of the two-dimensional Gabor function and characterized by a nonuniform probability distribution with heavy tails. All three parameters are found to be strongly correlated, resulting in a basis of multiscale Gabor functions with similar aspect ratios and size-dependent spatial frequencies. A key finding is that the distribution of receptive-field sizes is scale invariant over a wide range of values, so there is no characteristic receptive field size selected by natural image statistics. The Gabor function aspect ratio is found to be approximately conserved by the learning rules and is therefore not well determined by natural image statistics. This allows for three distinct solutions: a basis of Gabor functions with sharp orientation resolution at the expense of spatial-frequency resolution, a basis of Gabor functions with sharp spatial-frequency resolution at the expense of orientation resolution, or a basis with unit aspect ratio. Arbitrary mixtures of all three cases are also possible. Two parameters controlling the shape of the marginal distributions in a probabilistic generative model fully account for all three solutions. The best-performing probabilistic generative model for sparse coding applications is found to be a gaussian copula with Pareto marginal probability density functions.

Correlation Imaging Reveals Specific Crowding Dynamics of Kinesin Motor Proteins

NASA Astrophysics Data System (ADS)

Miedema, Daniël M.; Kushwaha, Vandana S.; Denisov, Dmitry V.; Acar, Seyda; Nienhuis, Bernard; Peterman, Erwin J. G.; Schall, Peter

2017-10-01

Molecular motor proteins fulfill the critical function of transporting organelles and other building blocks along the biopolymer network of the cell's cytoskeleton, but crowding effects are believed to crucially affect this motor-driven transport due to motor interactions. Physical transport models, like the paradigmatic, totally asymmetric simple exclusion process (TASEP), have been used to predict these crowding effects based on simple exclusion interactions, but verifying them in experiments remains challenging. Here, we introduce a correlation imaging technique to precisely measure the motor density, velocity, and run length along filaments under crowding conditions, enabling us to elucidate the physical nature of crowding and test TASEP model predictions. Using the kinesin motor proteins kinesin-1 and OSM-3, we identify crowding effects in qualitative agreement with TASEP predictions, and we achieve excellent quantitative agreement by extending the model with motor-specific interaction ranges and crowding-dependent detachment probabilities. These results confirm the applicability of basic nonequilibrium models to the intracellular transport and highlight motor-specific strategies to deal with crowding.

A Mathematical Model for Storage and Recall of Images using Targeted Synchronization of Coupled Maps.

PubMed

Palaniyandi, P; Rangarajan, Govindan

2017-08-21

We propose a mathematical model for storage and recall of images using coupled maps. We start by theoretically investigating targeted synchronization in coupled map systems wherein only a desired (partial) subset of the maps is made to synchronize. A simple method is introduced to specify coupling coefficients such that targeted synchronization is ensured. The principle of this method is extended to storage/recall of images using coupled Rulkov maps. The process of adjusting coupling coefficients between Rulkov maps (often used to model neurons) for the purpose of storing a desired image mimics the process of adjusting synaptic strengths between neurons to store memories. Our method uses both synchronisation and synaptic weight modification, as the human brain is thought to do. The stored image can be recalled by providing an initial random pattern to the dynamical system. The storage and recall of the standard image of Lena is explicitly demonstrated.

The application of infrared speckle interferometry to the imaging of remote galaxies and AGN

NASA Technical Reports Server (NTRS)

Olivares, Robert O.

1995-01-01

A 1.5 meter reflector, used for both infrared and optical astronomy, is also being used for infrared speckle interferometry and CCD imaging. The application of these imaging techniques to remote galaxies and active galactic nuclei are discussed. A simple model for the origin of speckle in coherent imaging systems is presented. Very careful photometry of the continuum of the galaxy M31 is underway using CCD images. It involves extremely intensive data reduction because the object itself is very large and has low surface brightness.

A position and attitude vision measurement system for wind tunnel slender model

NASA Astrophysics Data System (ADS)

Cheng, Lei; Yang, Yinong; Xue, Bindang; Zhou, Fugen; Bai, Xiangzhi

2014-11-01

A position and attitude vision measurement system for drop test slender model in wind tunnel is designed and developed. The system used two high speed cameras, one is put to the side of the model and another is put to the position where the camera can look up the model. Simple symbols are set on the model. The main idea of the system is based on image matching technique between the 3D-digital model projection image and the image captured by the camera. At first, we evaluate the pitch angles, the roll angles and the position of the centroid of a model through recognizing symbols in the images captured by the side camera. And then, based on the evaluated attitude info, giving a series of yaw angles, a series of projection images of the 3D-digital model are obtained. Finally, these projection images are matched with the image which captured by the looking up camera, and the best match's projection images corresponds to the yaw angle is the very yaw angle of the model. Simulation experiments are conducted and the results show that the maximal error of attitude measurement is less than 0.05°, which can meet the demand of test in wind tunnel.

Forest canopy height from Multiangle Imaging SpectroRadiometer (MISR) assessed with high resolution discrete return lidar

Treesearch

Mark Chopping; Anne Nolin; Gretchen G. Moisen; John V. Martonchik; Michael Bull

2009-01-01

In this study retrievals of forest canopy height were obtained through adjustment of a simple geometricoptical (GO) model against red band surface bidirectional reflectance estimates from NASA's Multiangle Imaging SpectroRadiometer (MISR), mapped to a 250 m grid. The soil-understory background contribution was partly isolated prior to inversion using regression...

Alternating Direction Implicit (ADI) schemes for a PDE-based image osmosis model

NASA Astrophysics Data System (ADS)

Calatroni, L.; Estatico, C.; Garibaldi, N.; Parisotto, S.

2017-10-01

We consider Alternating Direction Implicit (ADI) splitting schemes to compute efficiently the numerical solution of the PDE osmosis model considered by Weickert et al. in [10] for several imaging applications. The discretised scheme is shown to preserve analogous properties to the continuous model. The dimensional splitting strategy traduces numerically into the solution of simple tridiagonal systems for which standard matrix factorisation techniques can be used to improve upon the performance of classical implicit methods, even for large time steps. Applications to the shadow removal problem are presented.

A Simple Model for Nonlinear Confocal Ultrasonic Beams

NASA Astrophysics Data System (ADS)

Zhang, Dong; Zhou, Lin; Si, Li-Sheng; Gong, Xiu-Fen

2007-01-01

A confocally and coaxially arranged pair of focused transmitter and receiver represents one of the best geometries for medical ultrasonic imaging and non-invasive detection. We develop a simple theoretical model for describing the nonlinear propagation of a confocal ultrasonic beam in biological tissues. On the basis of the parabolic approximation and quasi-linear approximation, the nonlinear Khokhlov-Zabolotskaya-Kuznetsov (KZK) equation is solved by using the angular spectrum approach. Gaussian superposition technique is applied to simplify the solution, and an analytical solution for the second harmonics in the confocal ultrasonic beam is presented. Measurements are performed to examine the validity of the theoretical model. This model provides a preliminary model for acoustic nonlinear microscopy.

Anthropometric body measurements based on multi-view stereo image reconstruction.

PubMed

Li, Zhaoxin; Jia, Wenyan; Mao, Zhi-Hong; Li, Jie; Chen, Hsin-Chen; Zuo, Wangmeng; Wang, Kuanquan; Sun, Mingui

2013-01-01

Anthropometric measurements, such as the circumferences of the hip, arm, leg and waist, waist-to-hip ratio, and body mass index, are of high significance in obesity and fitness evaluation. In this paper, we present a home based imaging system capable of conducting anthropometric measurements. Body images are acquired at different angles using a home camera and a simple rotating disk. Advanced image processing algorithms are utilized for 3D body surface reconstruction. A coarse body shape model is first established from segmented body silhouettes. Then, this model is refined through an inter-image consistency maximization process based on an energy function. Our experimental results using both a mannequin surrogate and a real human body validate the feasibility of the proposed system.

Anthropometric Body Measurements Based on Multi-View Stereo Image Reconstruction*

PubMed Central

Li, Zhaoxin; Jia, Wenyan; Mao, Zhi-Hong; Li, Jie; Chen, Hsin-Chen; Zuo, Wangmeng; Wang, Kuanquan; Sun, Mingui

2013-01-01

Anthropometric measurements, such as the circumferences of the hip, arm, leg and waist, waist-to-hip ratio, and body mass index, are of high significance in obesity and fitness evaluation. In this paper, we present a home based imaging system capable of conducting automatic anthropometric measurements. Body images are acquired at different angles using a home camera and a simple rotating disk. Advanced image processing algorithms are utilized for 3D body surface reconstruction. A coarse body shape model is first established from segmented body silhouettes. Then, this model is refined through an inter-image consistency maximization process based on an energy function. Our experimental results using both a mannequin surrogate and a real human body validate the feasibility of proposed system. PMID:24109700

An application of the MPP to the interactive manipulation of stereo images of digital terrain models

NASA Technical Reports Server (NTRS)

Pol, Sanjay; Mcallister, David; Davis, Edward

1987-01-01

Massively Parallel Processor algorithms were developed for the interactive manipulation of flat shaded digital terrain models defined over grids. The emphasis is on real time manipulation of stereo images. Standard graphics transformations are applied to a 128 x 128 grid of elevations followed by shading and a perspective projection to produce the right eye image. The surface is then rendered using a simple painter's algorithm for hidden surface removal. The left eye image is produced by rotating the surface 6 degs about the viewer's y axis followed by a perspective projection and rendering of the image as described above. The left and right eye images are then presented on a graphics device using standard stereo technology. Performance evaluations and comparisons are presented.

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques.

PubMed

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images.

Imaging skeletal muscle with linearly polarized light

NASA Astrophysics Data System (ADS)

Li, X.; Ranasinghesagara, J.; Yao, G.

2008-04-01

We developed a polarization sensitive imaging system that can acquire reflectance images in turbid samples using incident light of different polarization states. Using this system, we studied polarization imaging on bovine sternomandibularis muscle strips using light of two orthogonal linearly polarized states. We found the obtained polarization sensitive reflectance images had interesting patterns depending on the polarization states. In addition, we computed four elements of the Mueller matrix from the acquired images. As a comparison, we also obtained polarization images of a 20% Intralipid"R" solution and compared the results with those from muscle samples. We found that the polarization imaging patterns from Intralipid solution can be described with a model based on single-scattering approximation. However, the polarization images in muscle had distinct patterns and can not be explained by this simple model. These results implied that the unique structural properties of skeletal muscle play important roles in modulating the propagation of polarized light.

Metal Artifact Suppression in Dental Cone Beam Computed Tomography Images Using Image Processing Techniques

PubMed Central

Johari, Masoumeh; Abdollahzadeh, Milad; Esmaeili, Farzad; Sakhamanesh, Vahideh

2018-01-01

Background: Dental cone beam computed tomography (CBCT) images suffer from severe metal artifacts. These artifacts degrade the quality of acquired image and in some cases make it unsuitable to use. Streaking artifacts and cavities around teeth are the main reason of degradation. Methods: In this article, we have proposed a new artifact reduction algorithm which has three parallel components. The first component extracts teeth based on the modeling of image histogram with a Gaussian mixture model. Striking artifact reduction component reduces artifacts using converting image into the polar domain and applying morphological filtering. The third component fills cavities through a simple but effective morphological filtering operation. Results: Finally, results of these three components are combined into a fusion step to create a visually good image which is more compatible to human visual system. Conclusions: Results show that the proposed algorithm reduces artifacts of dental CBCT images and produces clean images. PMID:29535920

Quantitative characterization of edge enhancement in phase contrast x-ray imaging.

PubMed

Monnin, P; Bulling, S; Hoszowska, J; Valley, J F; Meuli, R; Verdun, F R

2004-06-01

The aim of this study was to model the edge enhancement effect in in-line holography phase contrast imaging. A simple analytical approach was used to quantify refraction and interference contrasts in terms of beam energy and imaging geometry. The model was applied to predict the peak intensity and frequency of the edge enhancement for images of cylindrical fibers. The calculations were compared with measurements, and the relationship between the spatial resolution of the detector and the amplitude of the phase contrast signal was investigated. Calculations using the analytical model were in good agreement with experimental results for nylon, aluminum and copper wires of 50 to 240 microm diameter, and with numerical simulations based on Fresnel-Kirchhoff theory. A relationship between the defocusing distance and the pixel size of the image detector was established. This analytical model is a useful tool for optimizing imaging parameters in phase contrast in-line holography, including defocusing distance, detector resolution and beam energy.

Improving cerebellar segmentation with statistical fusion

NASA Astrophysics Data System (ADS)

Plassard, Andrew J.; Yang, Zhen; Prince, Jerry L.; Claassen, Daniel O.; Landman, Bennett A.

2016-03-01

The cerebellum is a somatotopically organized central component of the central nervous system well known to be involved with motor coordination and increasingly recognized roles in cognition and planning. Recent work in multiatlas labeling has created methods that offer the potential for fully automated 3-D parcellation of the cerebellar lobules and vermis (which are organizationally equivalent to cortical gray matter areas). This work explores the trade offs of using different statistical fusion techniques and post hoc optimizations in two datasets with distinct imaging protocols. We offer a novel fusion technique by extending the ideas of the Selective and Iterative Method for Performance Level Estimation (SIMPLE) to a patch-based performance model. We demonstrate the effectiveness of our algorithm, Non- Local SIMPLE, for segmentation of a mixed population of healthy subjects and patients with severe cerebellar anatomy. Under the first imaging protocol, we show that Non-Local SIMPLE outperforms previous gold-standard segmentation techniques. In the second imaging protocol, we show that Non-Local SIMPLE outperforms previous gold standard techniques but is outperformed by a non-locally weighted vote with the deeper population of atlases available. This work advances the state of the art in open source cerebellar segmentation algorithms and offers the opportunity for routinely including cerebellar segmentation in magnetic resonance imaging studies that acquire whole brain T1-weighted volumes with approximately 1 mm isotropic resolution.

Reionization Models Classifier using 21cm Map Deep Learning

NASA Astrophysics Data System (ADS)

Hassan, Sultan; Liu, Adrian; Kohn, Saul; Aguirre, James E.; La Plante, Paul; Lidz, Adam

2018-05-01

Next-generation 21cm observations will enable imaging of reionization on very large scales. These images will contain more astrophysical and cosmological information than the power spectrum, and hence providing an alternative way to constrain the contribution of different reionizing sources populations to cosmic reionization. Using Convolutional Neural Networks, we present a simple network architecture that is sufficient to discriminate between Galaxy-dominated versus AGN-dominated models, even in the presence of simulated noise from different experiments such as the HERA and SKA.

Acceleration of the direct reconstruction of linear parametric images using nested algorithms.

PubMed

Wang, Guobao; Qi, Jinyi

2010-03-07

Parametric imaging using dynamic positron emission tomography (PET) provides important information for biological research and clinical diagnosis. Indirect and direct methods have been developed for reconstructing linear parametric images from dynamic PET data. Indirect methods are relatively simple and easy to implement because the image reconstruction and kinetic modeling are performed in two separate steps. Direct methods estimate parametric images directly from raw PET data and are statistically more efficient. However, the convergence rate of direct algorithms can be slow due to the coupling between the reconstruction and kinetic modeling. Here we present two fast gradient-type algorithms for direct reconstruction of linear parametric images. The new algorithms decouple the reconstruction and linear parametric modeling at each iteration by employing the principle of optimization transfer. Convergence speed is accelerated by running more sub-iterations of linear parametric estimation because the computation cost of the linear parametric modeling is much less than that of the image reconstruction. Computer simulation studies demonstrated that the new algorithms converge much faster than the traditional expectation maximization (EM) and the preconditioned conjugate gradient algorithms for dynamic PET.

Functional Renal Imaging with 2-Deoxy-2-18F-Fluorosorbitol PET in Rat Models of Renal Disorders.

PubMed

Werner, Rudolf A; Wakabayashi, Hiroshi; Chen, Xinyu; Hirano, Mitsuru; Shinaji, Tetsuya; Lapa, Constantin; Rowe, Steven P; Javadi, Mehrbod S; Higuchi, Takahiro

2018-05-01

Precise regional quantitative assessment of renal function is limited with conventional 99m Tc-labeled renal radiotracers. A recent study reported that the PET radiotracer 2-deoxy-2- 18 F-fluorosorbitol ( 18 F-FDS) has ideal pharmacokinetics for functional renal imaging. Furthermore, 18 F-FDS is available via simple reduction from routinely used 18 F-FDG. We aimed to further investigate the potential of 18 F-FDS PET as a functional renal imaging agent using rat models of kidney disease. Methods: Two different rat models of renal impairment were investigated: induction of acute renal failure by intramuscular administration of glycerol in the hind legs, and induction of unilateral ureteral obstruction by ligation of the left ureter. At 24 h after these procedures, dynamic 30-min 18 F-FDS PET data were acquired using a dedicated small-animal PET system. Urine 18 F-FDS radioactivity 30 min after radiotracer injection was measured together with coinjected 99m Tc-diethylenetriaminepentaacetic acid urine activity. Results: Dynamic PET imaging demonstrated rapid 18 F-FDS accumulation in the renal cortex and rapid radiotracer excretion via the kidneys in healthy control rats. On the other hand, significantly delayed renal radiotracer uptake (continuous slow uptake) was observed in acute renal failure rats and unilateral ureteral obstruction kidneys. Measured urine radiotracer concentrations of 18 F-FDS and 99m Tc-diethylenetriaminepentaacetic acid correlated well with each other ( R = 0.84, P < 0.05). Conclusion: 18 F-FDS PET demonstrated favorable kinetics for functional renal imaging in rat models of kidney diseases. 18 F-FDS PET imaging, with its advantages of high spatiotemporal resolution and simple tracer production, could potentially complement or replace conventional renal scintigraphy in select cases and significantly improve the diagnostic performance of renal functional imaging. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Regression Models for Identifying Noise Sources in Magnetic Resonance Images

PubMed Central

Zhu, Hongtu; Li, Yimei; Ibrahim, Joseph G.; Shi, Xiaoyan; An, Hongyu; Chen, Yashen; Gao, Wei; Lin, Weili; Rowe, Daniel B.; Peterson, Bradley S.

2009-01-01

Stochastic noise, susceptibility artifacts, magnetic field and radiofrequency inhomogeneities, and other noise components in magnetic resonance images (MRIs) can introduce serious bias into any measurements made with those images. We formally introduce three regression models including a Rician regression model and two associated normal models to characterize stochastic noise in various magnetic resonance imaging modalities, including diffusion-weighted imaging (DWI) and functional MRI (fMRI). Estimation algorithms are introduced to maximize the likelihood function of the three regression models. We also develop a diagnostic procedure for systematically exploring MR images to identify noise components other than simple stochastic noise, and to detect discrepancies between the fitted regression models and MRI data. The diagnostic procedure includes goodness-of-fit statistics, measures of influence, and tools for graphical display. The goodness-of-fit statistics can assess the key assumptions of the three regression models, whereas measures of influence can isolate outliers caused by certain noise components, including motion artifacts. The tools for graphical display permit graphical visualization of the values for the goodness-of-fit statistic and influence measures. Finally, we conduct simulation studies to evaluate performance of these methods, and we analyze a real dataset to illustrate how our diagnostic procedure localizes subtle image artifacts by detecting intravoxel variability that is not captured by the regression models. PMID:19890478

Large area, label-free imaging of extracellular matrix using telecentricity

NASA Astrophysics Data System (ADS)

Visbal Onufrak, Michelle A.; Konger, Raymond L.; Kim, Young L.

2017-02-01

Subtle alterations in stromal tissue structures and organizations within the extracellular matrix (ECM) have been observed in several types of tissue abnormalities, including early skin cancer and wounds. Current microscopic imaging methods often lack the ability to accurately determine the extent of malignancy over a large area, due to their limited field of view. In this research we focus on the development of simple mesoscopic (i.e. between microscopic and macroscopic) biomedical imaging device for non-invasive assessment of ECM alterations over a large, heterogeneous area. In our technology development, a telecentric lens, commonly used in machine vision systems but rarely used in biomedical imaging, serves as a key platform to visualize alterations in tissue microenvironments in a label-free manner over a clinically relevant area. In general, telecentric imaging represents a simple, alternative method for reducing unwanted scattering or diffuse light caused by the highly anisotropic scattering properties of biological tissue. In particular, under telecentric imaging the light intensity backscattered from biological tissue is mainly sensitive to the scattering anisotropy factor, possibly associated with the ECM. We demonstrate the inherent advantages of combining telecentric lens systems with hyperspectral imaging for providing optical information of tissue scattering in biological tissue of murine models, as well as light absorption of hemoglobin in blood vessel tissue phantoms. Thus, we envision that telecentric imaging could potentially serve for simple site-specific, tissue-based assessment of stromal alterations over a clinically relevant field of view in a label-free manner, for studying diseases associated with disruption of homeostasis in ECM.

Image charge models for accurate construction of the electrostatic self-energy of 3D layered nanostructure devices.

PubMed

Barker, John R; Martinez, Antonio

2018-04-04

Efficient analytical image charge models are derived for the full spatial variation of the electrostatic self-energy of electrons in semiconductor nanostructures that arises from dielectric mismatch using semi-classical analysis. The methodology provides a fast, compact and physically transparent computation for advanced device modeling. The underlying semi-classical model for the self-energy has been established and validated during recent years and depends on a slight modification of the macroscopic static dielectric constants for individual homogeneous dielectric regions. The model has been validated for point charges as close as one interatomic spacing to a sharp interface. A brief introduction to image charge methodology is followed by a discussion and demonstration of the traditional failure of the methodology to derive the electrostatic potential at arbitrary distances from a source charge. However, the self-energy involves the local limit of the difference between the electrostatic Green functions for the full dielectric heterostructure and the homogeneous equivalent. It is shown that high convergence may be achieved for the image charge method for this local limit. A simple re-normalisation technique is introduced to reduce the number of image terms to a minimum. A number of progressively complex 3D models are evaluated analytically and compared with high precision numerical computations. Accuracies of 1% are demonstrated. Introducing a simple technique for modeling the transition of the self-energy between disparate dielectric structures we generate an analytical model that describes the self-energy as a function of position within the source, drain and gated channel of a silicon wrap round gate field effect transistor on a scale of a few nanometers cross-section. At such scales the self-energies become large (typically up to ~100 meV) close to the interfaces as well as along the channel. The screening of a gated structure is shown to reduce the self-energy relative to un-gated nanowires.

Image charge models for accurate construction of the electrostatic self-energy of 3D layered nanostructure devices

NASA Astrophysics Data System (ADS)

Barker, John R.; Martinez, Antonio

2018-04-01

Efficient analytical image charge models are derived for the full spatial variation of the electrostatic self-energy of electrons in semiconductor nanostructures that arises from dielectric mismatch using semi-classical analysis. The methodology provides a fast, compact and physically transparent computation for advanced device modeling. The underlying semi-classical model for the self-energy has been established and validated during recent years and depends on a slight modification of the macroscopic static dielectric constants for individual homogeneous dielectric regions. The model has been validated for point charges as close as one interatomic spacing to a sharp interface. A brief introduction to image charge methodology is followed by a discussion and demonstration of the traditional failure of the methodology to derive the electrostatic potential at arbitrary distances from a source charge. However, the self-energy involves the local limit of the difference between the electrostatic Green functions for the full dielectric heterostructure and the homogeneous equivalent. It is shown that high convergence may be achieved for the image charge method for this local limit. A simple re-normalisation technique is introduced to reduce the number of image terms to a minimum. A number of progressively complex 3D models are evaluated analytically and compared with high precision numerical computations. Accuracies of 1% are demonstrated. Introducing a simple technique for modeling the transition of the self-energy between disparate dielectric structures we generate an analytical model that describes the self-energy as a function of position within the source, drain and gated channel of a silicon wrap round gate field effect transistor on a scale of a few nanometers cross-section. At such scales the self-energies become large (typically up to ~100 meV) close to the interfaces as well as along the channel. The screening of a gated structure is shown to reduce the self-energy relative to un-gated nanowires.

Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection

PubMed Central

Goldsmith, Jeff; Huang, Lei; Crainiceanu, Ciprian M.

2013-01-01

We develop scalar-on-image regression models when images are registered multidimensional manifolds. We propose a fast and scalable Bayes inferential procedure to estimate the image coefficient. The central idea is the combination of an Ising prior distribution, which controls a latent binary indicator map, and an intrinsic Gaussian Markov random field, which controls the smoothness of the nonzero coefficients. The model is fit using a single-site Gibbs sampler, which allows fitting within minutes for hundreds of subjects with predictor images containing thousands of locations. The code is simple and is provided in less than one page in the Appendix. We apply this method to a neuroimaging study where cognitive outcomes are regressed on measures of white matter microstructure at every voxel of the corpus callosum for hundreds of subjects. PMID:24729670

The Wide-Field Imaging Interferometry Testbed: Enabling Techniques for High Angular Resolution Astronomy

NASA Technical Reports Server (NTRS)

Rinehart, S. A.; Armstrong, T.; Frey, Bradley J.; Jung, J.; Kirk, J.; Leisawitz, David T.; Leviton, Douglas B.; Lyon, R.; Maher, Stephen; Martino, Anthony J.;

Temporal changes in endmember abundances, liquid water and water vapor over vegetation at Jasper Ridge

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Green, Robert O.; Sabol, Donald E.; Adams, John B.

1993-01-01

Imaging spectrometry offers a new way of deriving ecological information about vegetation communities from remote sensing. Applications include derivation of canopy chemistry, measurement of column atmospheric water vapor and liquid water, improved detectability of materials, more accurate estimation of green vegetation cover and discrimination of spectrally distinct green leaf, non-photosynthetic vegetation (NPV: litter, wood, bark, etc.) and shade spectra associated with different vegetation communities. Much of our emphasis has been on interpreting Airborne Visible/Infrared Imaging Spectrometry (AVIRIS) data spectral mixtures. Two approaches have been used, simple models, where the data are treated as a mixture of 3 to 4 laboratory/field measured spectra, known as reference endmembers (EM's), applied uniformly to the whole image, to more complex models where both the number of EM's and the types of EM's vary on a per-pixel basis. Where simple models are applied, materials, such as NPV, which are spectrally similar to soils, can be discriminated on the basis of residual spectra. One key aspect is that the data are calibrated to reflectance and modeled as mixtures of reference EM's, permitting temporal comparison of EM fractions, independent of scene location or data type. In previous studies the calibration was performed using a modified-empirical line calibration, assuming a uniform atmosphere across the scene. In this study, a Modtran-based calibration approach was used to map liquid water and atmospheric water vapor and retrieve surface reflectance from three AVIRIS scenes acquired in 1992 over the Jasper Ridge Biological Preserve. The data were acquired on June 2nd, September 4th and October 6th. Reflectance images were analyzed as spectral mixtures of reference EM's using a simple 4 EM model. Atmospheric water vapor derived from Modtran was compared to elevation, and community type. Liquid water was compare to the abundance of NPV, Shade and Green Vegetation (VG) for select sites to determine whether a relationship existed, and under what conditions the relationship broke down. Temporal trends in endmember fractions, liquid water and atmospheric water vapor were investigated also. The combination of spectral mixture analysis and the Modtran based atmospheric/liquid water models was used to develop a unique vegetation community description.

Supermassive black holes and their host galaxies. I. Bulge luminosities from dedicated near-infrared data

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

Läsker, Ronald; Van de Ven, Glenn; Ferrarese, Laura, E-mail: laesker@mpia.de

2014-01-01

In an effort to secure, refine, and supplement the relation between central supermassive black hole masses, M {sub •}, and the bulge luminosities of their host galaxies, L {sub bul}, we obtained deep, high spatial resolution K-band images of 35 nearby galaxies with securely measured M {sub •}, using the wide-field WIRCam imager at the Canada-France-Hawaii-Telescope. A dedicated data reduction and sky subtraction strategy was adopted to estimate the brightness and structure of the sky, a critical step when tracing the light distribution of extended objects in the near-infrared. From the final image product, bulge and total magnitudes were extractedmore » via two-dimensional profile fitting. As a first order approximation, all galaxies were modeled using a simple Sérsic-bulge+exponential-disk decomposition. However, we found that such models did not adequately describe the structure that we observed in a large fraction of our sample galaxies which often include cores, bars, nuclei, inner disks, spiral arms, rings, and envelopes. In such cases, we adopted profile modifications and/or more complex models with additional components. The derived bulge magnitudes are very sensitive to the details and number of components used in the models, although total magnitudes remain almost unaffected. Usually, but not always, the luminosities and sizes of the bulges are overestimated when a simple bulge+disk decomposition is adopted in lieu of a more complex model. Furthermore, we found that some spheroids are not well fit when the ellipticity of the Sérsic model is held fixed. This paper presents the details of the image processing and analysis, while we discuss how model-induced biases and systematics in bulge magnitudes impact the M {sub •}-L {sub bul} relation in a companion paper.« less

Supermassive Black Holes and Their Host Galaxies. I. Bulge Luminosities from Dedicated Near-infrared Data

NASA Astrophysics Data System (ADS)

Läsker, Ronald; Ferrarese, Laura; van de Ven, Glenn

2014-01-01

In an effort to secure, refine, and supplement the relation between central supermassive black hole masses, M •, and the bulge luminosities of their host galaxies, L bul, we obtained deep, high spatial resolution K-band images of 35 nearby galaxies with securely measured M •, using the wide-field WIRCam imager at the Canada-France-Hawaii-Telescope. A dedicated data reduction and sky subtraction strategy was adopted to estimate the brightness and structure of the sky, a critical step when tracing the light distribution of extended objects in the near-infrared. From the final image product, bulge and total magnitudes were extracted via two-dimensional profile fitting. As a first order approximation, all galaxies were modeled using a simple Sérsic-bulge+exponential-disk decomposition. However, we found that such models did not adequately describe the structure that we observed in a large fraction of our sample galaxies which often include cores, bars, nuclei, inner disks, spiral arms, rings, and envelopes. In such cases, we adopted profile modifications and/or more complex models with additional components. The derived bulge magnitudes are very sensitive to the details and number of components used in the models, although total magnitudes remain almost unaffected. Usually, but not always, the luminosities and sizes of the bulges are overestimated when a simple bulge+disk decomposition is adopted in lieu of a more complex model. Furthermore, we found that some spheroids are not well fit when the ellipticity of the Sérsic model is held fixed. This paper presents the details of the image processing and analysis, while we discuss how model-induced biases and systematics in bulge magnitudes impact the M •-L bul relation in a companion paper.

On the bandwidth of the plenoptic function.

PubMed

Do, Minh N; Marchand-Maillet, Davy; Vetterli, Martin

2012-02-01

The plenoptic function (POF) provides a powerful conceptual tool for describing a number of problems in image/video processing, vision, and graphics. For example, image-based rendering is shown as sampling and interpolation of the POF. In such applications, it is important to characterize the bandwidth of the POF. We study a simple but representative model of the scene where band-limited signals (e.g., texture images) are "painted" on smooth surfaces (e.g., of objects or walls). We show that, in general, the POF is not band limited unless the surfaces are flat. We then derive simple rules to estimate the essential bandwidth of the POF for this model. Our analysis reveals that, in addition to the maximum and minimum depths and the maximum frequency of painted signals, the bandwidth of the POF also depends on the maximum surface slope. With a unifying formalism based on multidimensional signal processing, we can verify several key results in POF processing, such as induced filtering in space and depth-corrected interpolation, and quantify the necessary sampling rates. © 2011 IEEE

Object detection in natural backgrounds predicted by discrimination performance and models

NASA Technical Reports Server (NTRS)

Rohaly, A. M.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Many models of visual performance predict image discriminability, the visibility of the difference between a pair of images. We compared the ability of three image discrimination models to predict the detectability of objects embedded in natural backgrounds. The three models were: a multiple channel Cortex transform model with within-channel masking; a single channel contrast sensitivity filter model; and a digital image difference metric. Each model used a Minkowski distance metric (generalized vector magnitude) to summate absolute differences between the background and object plus background images. For each model, this summation was implemented with three different exponents: 2, 4 and infinity. In addition, each combination of model and summation exponent was implemented with and without a simple contrast gain factor. The model outputs were compared to measures of object detectability obtained from 19 observers. Among the models without the contrast gain factor, the multiple channel model with a summation exponent of 4 performed best, predicting the pattern of observer d's with an RMS error of 2.3 dB. The contrast gain factor improved the predictions of all three models for all three exponents. With the factor, the best exponent was 4 for all three models, and their prediction errors were near 1 dB. These results demonstrate that image discrimination models can predict the relative detectability of objects in natural scenes.

Terahertz reflection imaging using Kirchhoff migration.

PubMed

Dorney, T D; Johnson, J L; Van Rudd, J; Baraniuk, R G; Symes, W W; Mittleman, D M

2001-10-01

We describe a new imaging method that uses single-cycle pulses of terahertz (THz) radiation. This technique emulates data-collection and image-processing procedures developed for geophysical prospecting and is made possible by the availability of fiber-coupled THz receiver antennas. We use a simple migration procedure to solve the inverse problem; this permits us to reconstruct the location and shape of targets. These results demonstrate the feasibility of the THz system as a test-bed for the exploration of new seismic processing methods involving complex model systems.

Granular convection observed by magnetic resonance imaging.

PubMed

Ehrichs, E E; Jaeger, H M; Karczmar, G S; Knight, J B; Kuperman, V Y; Nagel, S R

1995-03-17

Vibrations in a granular material can spontaneously produce convection rolls reminiscent of those seen in fluids. Magnetic resonance imaging provides a sensitive and noninvasive probe for the detection of these convection currents, which have otherwise been difficult to observe. A magnetic resonance imaging study of convection in a column of poppy seeds yielded data about the detailed shape of the convection rolls and the depth dependence of the convection velocity. The velocity was found to decrease exponentially with depth; a simple model for this behavior is presented here.

System and method for automated object detection in an image

DOEpatents

Kenyon, Garrett T.; Brumby, Steven P.; George, John S.; Paiton, Dylan M.; Schultz, Peter F.

2015-10-06

A contour/shape detection model may use relatively simple and efficient kernels to detect target edges in an object within an image or video. A co-occurrence probability may be calculated for two or more edge features in an image or video using an object definition. Edge features may be differentiated between in response to measured contextual support, and prominent edge features may be extracted based on the measured contextual support. The object may then be identified based on the extracted prominent edge features.

Generative Models in Deep Learning: Constraints for Galaxy Evolution

NASA Astrophysics Data System (ADS)

Turp, Maximilian Dennis; Schawinski, Kevin; Zhang, Ce; Weigel, Anna K.

2018-01-01

New techniques are essential to make advances in the field of galaxy evolution. Recent developments in the field of artificial intelligence and machine learning have proven that these tools can be applied to problems far more complex than simple image recognition. We use these purely data driven approaches to investigate the process of star formation quenching. We show that Variational Autoencoders provide a powerful method to forward model the process of galaxy quenching. Our results imply that simple changes in specific star formation rate and bulge to disk ratio cannot fully describe the properties of the quenched population.

Color matrix display simulation based upon luminance and chromatic contrast sensitivity of early vision

NASA Technical Reports Server (NTRS)

Martin, Russel A.; Ahumada, Albert J., Jr.; Larimer, James O.

1992-01-01

This paper describes the design and operation of a new simulation model for color matrix display development. It models the physical structure, the signal processing, and the visual perception of static displays, to allow optimization of display design parameters through image quality measures. The model is simple, implemented in the Mathematica computer language, and highly modular. Signal processing modules operate on the original image. The hardware modules describe backlights and filters, the pixel shape, and the tiling of the pixels over the display. Small regions of the displayed image can be visualized on a CRT. Visual perception modules assume static foveal images. The image is converted into cone catches and then into luminance, red-green, and blue-yellow images. A Haar transform pyramid separates the three images into spatial frequency and direction-specific channels. The channels are scaled by weights taken from human contrast sensitivity measurements of chromatic and luminance mechanisms at similar frequencies and orientations. Each channel provides a detectability measure. These measures allow the comparison of images displayed on prospective devices and, by that, the optimization of display designs.

The impact of temporal sampling resolution on parameter inference for biological transport models.

PubMed

Harrison, Jonathan U; Baker, Ruth E

2018-06-25

Imaging data has become an essential tool to explore key biological questions at various scales, for example the motile behaviour of bacteria or the transport of mRNA, and it has the potential to transform our understanding of important transport mechanisms. Often these imaging studies require us to compare biological species or mutants, and to do this we need to quantitatively characterise their behaviour. Mathematical models offer a quantitative description of a system that enables us to perform this comparison, but to relate mechanistic mathematical models to imaging data, we need to estimate their parameters. In this work we study how collecting data at different temporal resolutions impacts our ability to infer parameters of biological transport models; performing exact inference for simple velocity jump process models in a Bayesian framework. The question of how best to choose the frequency with which data is collected is prominent in a host of studies because the majority of imaging technologies place constraints on the frequency with which images can be taken, and the discrete nature of observations can introduce errors into parameter estimates. In this work, we mitigate such errors by formulating the velocity jump process model within a hidden states framework. This allows us to obtain estimates of the reorientation rate and noise amplitude for noisy observations of a simple velocity jump process. We demonstrate the sensitivity of these estimates to temporal variations in the sampling resolution and extent of measurement noise. We use our methodology to provide experimental guidelines for researchers aiming to characterise motile behaviour that can be described by a velocity jump process. In particular, we consider how experimental constraints resulting in a trade-off between temporal sampling resolution and observation noise may affect parameter estimates. Finally, we demonstrate the robustness of our methodology to model misspecification, and then apply our inference framework to a dataset that was generated with the aim of understanding the localization of RNA-protein complexes.

A simple rapid process for semi-automated brain extraction from magnetic resonance images of the whole mouse head.

PubMed

Delora, Adam; Gonzales, Aaron; Medina, Christopher S; Mitchell, Adam; Mohed, Abdul Faheem; Jacobs, Russell E; Bearer, Elaine L

2016-01-15

Magnetic resonance imaging (MRI) is a well-developed technique in neuroscience. Limitations in applying MRI to rodent models of neuropsychiatric disorders include the large number of animals required to achieve statistical significance, and the paucity of automation tools for the critical early step in processing, brain extraction, which prepares brain images for alignment and voxel-wise statistics. This novel timesaving automation of template-based brain extraction ("skull-stripping") is capable of quickly and reliably extracting the brain from large numbers of whole head images in a single step. The method is simple to install and requires minimal user interaction. This method is equally applicable to different types of MR images. Results were evaluated with Dice and Jacquard similarity indices and compared in 3D surface projections with other stripping approaches. Statistical comparisons demonstrate that individual variation of brain volumes are preserved. A downloadable software package not otherwise available for extraction of brains from whole head images is included here. This software tool increases speed, can be used with an atlas or a template from within the dataset, and produces masks that need little further refinement. Our new automation can be applied to any MR dataset, since the starting point is a template mask generated specifically for that dataset. The method reliably and rapidly extracts brain images from whole head images, rendering them useable for subsequent analytical processing. This software tool will accelerate the exploitation of mouse models for the investigation of human brain disorders by MRI. Copyright © 2015 Elsevier B.V. All rights reserved.

Web-based segmentation and display of three-dimensional radiologic image data.

PubMed

Silverstein, J; Rubenstein, J; Millman, A; Panko, W

1998-01-01

In many clinical circumstances, viewing sequential radiological image data as three-dimensional models is proving beneficial. However, designing customized computer-generated radiological models is beyond the scope of most physicians, due to specialized hardware and software requirements. We have created a simple method for Internet users to remotely construct and locally display three-dimensional radiological models using only a standard web browser. Rapid model construction is achieved by distributing the hardware intensive steps to a remote server. Once created, the model is automatically displayed on the requesting browser and is accessible to multiple geographically distributed users. Implementation of our server software on large scale systems could be of great service to the worldwide medical community.

Ultrasound breast imaging using frequency domain reverse time migration

NASA Astrophysics Data System (ADS)

Roy, O.; Zuberi, M. A. H.; Pratt, R. G.; Duric, N.

2016-04-01

Conventional ultrasonography reconstruction techniques, such as B-mode, are based on a simple wave propagation model derived from a high frequency approximation. Therefore, to minimize model mismatch, the central frequency of the input pulse is typically chosen between 3 and 15 megahertz. Despite the increase in theoretical resolution, operating at higher frequencies comes at the cost of lower signal-to-noise ratio. This ultimately degrades the image contrast and overall quality at higher imaging depths. To address this issue, we investigate a reflection imaging technique, known as reverse time migration, which uses a more accurate propagation model for reconstruction. We present preliminary simulation results as well as physical phantom image reconstructions obtained using data acquired with a breast imaging ultrasound tomography prototype. The original reconstructions are filtered to remove low-wavenumber artifacts that arise due to the inclusion of the direct arrivals. We demonstrate the advantage of using an accurate sound speed model in the reverse time migration process. We also explain how the increase in computational complexity can be mitigated using a frequency domain approach and a parallel computing platform.

Modeling loosely annotated images using both given and imagined annotations

NASA Astrophysics Data System (ADS)

Tang, Hong; Boujemaa, Nozha; Chen, Yunhao; Deng, Lei

2011-12-01

In this paper, we present an approach to learn latent semantic analysis models from loosely annotated images for automatic image annotation and indexing. The given annotation in training images is loose due to: 1. ambiguous correspondences between visual features and annotated keywords; 2. incomplete lists of annotated keywords. The second reason motivates us to enrich the incomplete annotation in a simple way before learning a topic model. In particular, some ``imagined'' keywords are poured into the incomplete annotation through measuring similarity between keywords in terms of their co-occurrence. Then, both given and imagined annotations are employed to learn probabilistic topic models for automatically annotating new images. We conduct experiments on two image databases (i.e., Corel and ESP) coupled with their loose annotations, and compare the proposed method with state-of-the-art discrete annotation methods. The proposed method improves word-driven probability latent semantic analysis (PLSA-words) up to a comparable performance with the best discrete annotation method, while a merit of PLSA-words is still kept, i.e., a wider semantic range.

Quantitative Imaging of Microwave Electric Fields through Near-Field Scanning Microwave Microscopy

NASA Astrophysics Data System (ADS)

Dutta, S. K.; Vlahacos, C. P.; Steinhauer, D. E.; Thanawalla, A.; Feenstra, B. J.; Wellstood, F. C.; Anlage, Steven M.; Newman, H. S.

1998-03-01

The ability to non-destructively image electric field patterns generated by operating microwave devices (e.g. filters, antennas, circulators, etc.) would greatly aid in the design and testing of these structures. Such detailed information can be used to reconcile discrepancies between simulated behavior and experimental data (such as scattering parameters). The near-field scanning microwave microscope we present uses a coaxial probe to provide a simple, broadband method of imaging electric fields.(S. M. Anlage, et al.) IEEE Trans. Appl. Supercond. 7, 3686 (1997).^,(See http://www.csr.umd.edu/research/hifreq/micr_microscopy.html) The signal that is measured is related to the incident electric flux normal to the face of the center conductor of the probe, allowing different components of the field to be measured by orienting the probe appropriately. By using a simple model of the system, we can also convert raw data to absolute electric field. Detailed images of standing waves on copper microstrip will be shown and compared to theory.

Generic Features of Tertiary Chromatin Structure as Detected in Natural Chromosomes

PubMed Central

Müller, Waltraud G.; Rieder, Dietmar; Kreth, Gregor; Cremer, Christoph; Trajanoski, Zlatko; McNally, James G.

2004-01-01

Knowledge of tertiary chromatin structure in mammalian interphase chromosomes is largely derived from artificial tandem arrays. In these model systems, light microscope images reveal fibers or beaded fibers after high-density targeting of transactivators to insertional domains spanning several megabases. These images of fibers have lent support to chromonema fiber models of tertiary structure. To assess the relevance of these studies to natural mammalian chromatin, we identified two different ∼400-kb regions on human chromosomes 6 and 22 and then examined light microscope images of interphase tertiary chromatin structure when the regions were transcriptionally active and inactive. When transcriptionally active, these natural chromosomal regions elongated, yielding images characterized by a series of adjacent puncta or “beads”, referred to hereafter as beaded images. These elongated structures required transcription for their maintenance. Thus, despite marked differences in the density and the mode of transactivation, the natural and artificial systems showed similarities, suggesting that beaded images are generic features of transcriptionally active tertiary chromatin. We show here, however, that these images do not necessarily favor chromonema fiber models but can also be explained by a radial-loop model or even a simple nucleosome affinity, random-chain model. Thus, light microscope images of tertiary structure cannot distinguish among competing models, although they do impose key constraints: chromatin must be clustered to yield beaded images and then packaged within each cluster to enable decondensation into adjacent clusters. PMID:15485905

High-resolution Episcopic Microscopy (HREM) - Simple and Robust Protocols for Processing and Visualizing Organic Materials

PubMed Central

Geyer, Stefan H.; Maurer-Gesek, Barbara; Reissig, Lukas F.; Weninger, Wolfgang J.

2017-01-01

We provide simple protocols for generating digital volume data with the high-resolution episcopic microscopy (HREM) method. HREM is capable of imaging organic materials with volumes up to 5 x 5 x 7 mm3 in typical numeric resolutions between 1 x 1 x 1 and 5 x 5 x 5 µm3. Specimens are embedded in methacrylate resin and sectioned on a microtome. After each section an image of the block surface is captured with a digital video camera that sits on the phototube connected to the compound microscope head. The optical axis passes through a green fluorescent protein (GFP) filter cube and is aligned with a position, at which the bock holder arm comes to rest after each section. In this way, a series of inherently aligned digital images, displaying subsequent block surfaces are produced. Loading such an image series in three-dimensional (3D) visualization software facilitates the immediate conversion to digital volume data, which permit virtual sectioning in various orthogonal and oblique planes and the creation of volume and surface rendered computer models. We present three simple, tissue specific protocols for processing various groups of organic specimens, including mouse, chick, quail, frog and zebra fish embryos, human biopsy material, uncoated paper and skin replacement material. PMID:28715372

High-resolution Episcopic Microscopy (HREM) - Simple and Robust Protocols for Processing and Visualizing Organic Materials.

PubMed

Geyer, Stefan H; Maurer-Gesek, Barbara; Reissig, Lukas F; Weninger, Wolfgang J

2017-07-07

We provide simple protocols for generating digital volume data with the high-resolution episcopic microscopy (HREM) method. HREM is capable of imaging organic materials with volumes up to 5 x 5 x 7 mm 3 in typical numeric resolutions between 1 x 1 x 1 and 5 x 5 x 5 µm 3 . Specimens are embedded in methacrylate resin and sectioned on a microtome. After each section an image of the block surface is captured with a digital video camera that sits on the phototube connected to the compound microscope head. The optical axis passes through a green fluorescent protein (GFP) filter cube and is aligned with a position, at which the bock holder arm comes to rest after each section. In this way, a series of inherently aligned digital images, displaying subsequent block surfaces are produced. Loading such an image series in three-dimensional (3D) visualization software facilitates the immediate conversion to digital volume data, which permit virtual sectioning in various orthogonal and oblique planes and the creation of volume and surface rendered computer models. We present three simple, tissue specific protocols for processing various groups of organic specimens, including mouse, chick, quail, frog and zebra fish embryos, human biopsy material, uncoated paper and skin replacement material.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

PubMed Central

Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

2015-01-01

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

Physics Based Modeling and Rendering of Vegetation in the Thermal Infrared

NASA Technical Reports Server (NTRS)

Smith, J. A.; Ballard, J. R., Jr.

1999-01-01

We outline a procedure for rendering physically-based thermal infrared images of simple vegetation scenes. Our approach incorporates the biophysical processes that affect the temperature distribution of the elements within a scene. Computer graphics plays a key role in two respects. First, in computing the distribution of scene shaded and sunlit facets and, second, in the final image rendering once the temperatures of all the elements in the scene have been computed. We illustrate our approach for a simple corn scene where the three-dimensional geometry is constructed based on measured morphological attributes of the row crop. Statistical methods are used to construct a representation of the scene in agreement with the measured characteristics. Our results are quite good. The rendered images exhibit realistic behavior in directional properties as a function of view and sun angle. The root-mean-square error in measured versus predicted brightness temperatures for the scene was 2.1 deg C.

RenderMan design principles

NASA Technical Reports Server (NTRS)

Apodaca, Tony; Porter, Tom

1989-01-01

The two worlds of interactive graphics and realistic graphics have remained separate. Fast graphics hardware runs simple algorithms and generates simple looking images. Photorealistic image synthesis software runs slowly on large expensive computers. The time has come for these two branches of computer graphics to merge. The speed and expense of graphics hardware is no longer the barrier to the wide acceptance of photorealism. There is every reason to believe that high quality image synthesis will become a standard capability of every graphics machine, from superworkstation to personal computer. The significant barrier has been the lack of a common language, an agreed-upon set of terms and conditions, for 3-D modeling systems to talk to 3-D rendering systems for computing an accurate rendition of that scene. Pixar has introduced RenderMan to serve as that common language. RenderMan, specifically the extensibility it offers in shading calculations, is discussed.

Physical basis of tap test as a quantitative imaging tool for composite structures on aircraft

NASA Astrophysics Data System (ADS)

Hsu, David K.; Barnard, Daniel J.; Peters, John J.; Dayal, Vinay

2000-05-01

Tap test is a simple but effective way for finding flaws in composite and honeycomb sandwich structures; it has been practiced in aircraft inspection for decades. The mechanics of tap test was extensively researched by P. Cawley et al., and several versions of instrumented tap test have emerged in recent years. This paper describes a quantitative study of the impact duration as a function of the mass, radius, velocity, and material property of the impactor. The impact response is compared to the predictions of Hertzian-type contact theory and a simple spring model. The electronically measured impact duration, τ, is used for generating images of the tapped region. Using the spring model, the images are converted into images of a spring constant, k, which is a measure of the local contact stiffness. The images of k, largely independent of tapper mass and impact velocity, reveal the size, shape and severity (cf. Percent stiffness reduction) of defects and damages, as well as the presence of substructures and the associated stiffness increase. The studies are carried out on a variety of real aircraft components and the results serve to guide the development of a fieldable tap test imaging system for aircraft inspection.—This material is based upon work supported by the Federal Aviation Administration under Contract #DTFA03-98-D-00008, Delivery Order No. IA016 and performed at Iowa State University's Center for NDE as part of the Center for Aviation Systems Reliability program.

Automatic building detection based on Purposive FastICA (PFICA) algorithm using monocular high resolution Google Earth images

NASA Astrophysics Data System (ADS)

Ghaffarian, Saman; Ghaffarian, Salar

2014-11-01

This paper proposes an improved FastICA model named as Purposive FastICA (PFICA) with initializing by a simple color space transformation and a novel masking approach to automatically detect buildings from high resolution Google Earth imagery. ICA and FastICA algorithms are defined as Blind Source Separation (BSS) techniques for unmixing source signals using the reference data sets. In order to overcome the limitations of the ICA and FastICA algorithms and make them purposeful, we developed a novel method involving three main steps: 1-Improving the FastICA algorithm using Moore-Penrose pseudo inverse matrix model, 2-Automated seeding of the PFICA algorithm based on LUV color space and proposed simple rules to split image into three regions; shadow + vegetation, baresoil + roads and buildings, respectively, 3-Masking out the final building detection results from PFICA outputs utilizing the K-means clustering algorithm with two number of clusters and conducting simple morphological operations to remove noises. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.6% and 85.5% overall pixel-based and object-based precision performances, respectively.

Personalized models of bones based on radiographic photogrammetry.

PubMed

Berthonnaud, E; Hilmi, R; Dimnet, J

2009-07-01

The radiographic photogrammetry is applied, for locating anatomical landmarks in space, from their two projected images. The goal of this paper is to define a personalized geometric model of bones, based uniquely on photogrammetric reconstructions. The personalized models of bones are obtained from two successive steps: their functional frameworks are first determined experimentally, then, the 3D bone representation results from modeling techniques. Each bone functional framework is issued from direct measurements upon two radiographic images. These images may be obtained using either perpendicular (spine and sacrum) or oblique incidences (pelvis and lower limb). Frameworks link together their functional axes and punctual landmarks. Each global bone volume is decomposed in several elementary components. Each volumic component is represented by simple geometric shapes. Volumic shapes are articulated to the patient's bone structure. The volumic personalization is obtained by best fitting the geometric model projections to their real images, using adjustable articulations. Examples are presented to illustrating the technique of personalization of bone volumes, directly issued from the treatment of only two radiographic images. The chosen techniques for treating data are then discussed. The 3D representation of bones completes, for clinical users, the information brought by radiographic images.

Visualization of small lesions in rat cartilage by means of laboratory-based x-ray phase contrast imaging

NASA Astrophysics Data System (ADS)

Marenzana, Massimo; Hagen, Charlotte K.; Das Neves Borges, Patricia; Endrizzi, Marco; Szafraniec, Magdalena B.; Ignatyev, Konstantin; Olivo, Alessandro

2012-12-01

Being able to quantitatively assess articular cartilage in three-dimensions (3D) in small rodent animal models, with a simple laboratory set-up, would prove extremely important for the development of pre-clinical research focusing on cartilage pathologies such as osteoarthritis (OA). These models are becoming essential tools for the development of new drugs for OA, a disease affecting up to 1/3 of the population older than 50 years for which there is no cure except prosthetic surgery. However, due to limitations in imaging technology, high-throughput 3D structural imaging has not been achievable in small rodent models, thereby limiting their translational potential and their efficiency as research tools. We show that a simple laboratory system based on coded-aperture x-ray phase contrast imaging (CAXPCi) can correctly visualize the cartilage layer in slices of an excised rat tibia imaged both in air and in saline solution. Moreover, we show that small, surgically induced lesions are also correctly detected by the CAXPCi system, and we support this finding with histopathology examination. Following these successful proof-of-concept results in rat cartilage, we expect that an upgrade of the system to higher resolutions (currently underway) will enable extending the method to the imaging of mouse cartilage as well. From a technological standpoint, by showing the capability of the system to detect cartilage also in water, we demonstrate phase sensitivity comparable to other lab-based phase methods (e.g. grating interferometry). In conclusion, CAXPCi holds a strong potential for being adopted as a routine laboratory tool for non-destructive, high throughput assessment of 3D structural changes in murine articular cartilage, with a possible impact in the field similar to the revolution that conventional microCT brought into bone research.

Learning to represent spatial transformations with factored higher-order Boltzmann machines.

PubMed

Memisevic, Roland; Hinton, Geoffrey E

2010-06-01

To allow the hidden units of a restricted Boltzmann machine to model the transformation between two successive images, Memisevic and Hinton (2007) introduced three-way multiplicative interactions that use the intensity of a pixel in the first image as a multiplicative gain on a learned, symmetric weight between a pixel in the second image and a hidden unit. This creates cubically many parameters, which form a three-dimensional interaction tensor. We describe a low-rank approximation to this interaction tensor that uses a sum of factors, each of which is a three-way outer product. This approximation allows efficient learning of transformations between larger image patches. Since each factor can be viewed as an image filter, the model as a whole learns optimal filter pairs for efficiently representing transformations. We demonstrate the learning of optimal filter pairs from various synthetic and real image sequences. We also show how learning about image transformations allows the model to perform a simple visual analogy task, and we show how a completely unsupervised network trained on transformations perceives multiple motions of transparent dot patterns in the same way as humans.

Statistical wiring of thalamic receptive fields optimizes spatial sampling of the retinal image

PubMed Central

Wang, Xin; Sommer, Friedrich T.; Hirsch, Judith A.

2014-01-01

Summary It is widely assumed that mosaics of retinal ganglion cells establish the optimal representation of visual space. However, relay cells in the visual thalamus often receive convergent input from several retinal afferents and, in cat, outnumber ganglion cells. To explore how the thalamus transforms the retinal image, we built a model of the retinothalamic circuit using experimental data and simple wiring rules. The model shows how the thalamus might form a resampled map of visual space with the potential to facilitate detection of stimulus position in the presence of sensor noise. Bayesian decoding conducted with the model provides support for this scenario. Despite its benefits, however, resampling introduces image blur, thus impairing edge perception. Whole-cell recordings obtained in vivo suggest that this problem is mitigated by arrangements of excitation and inhibition within the receptive field that effectively boost contrast borders, much like strategies used in digital image processing. PMID:24559681

Notes on Experiments.

ERIC Educational Resources Information Center

Physics Education, 1989

1989-01-01

Described are the purposes, laboratory set-ups, and procedures of four classroom experiments: ultrasound speedometer; vibrating-bar depth gauge; folding three-dimensional model of equipotential surfaces; and a simple optical system for the reconstruction of images from computer-generated holograms. Diagrams and pictures are provided. (YP)

The Plaque-Antiserum Method: an Assay of Virus Infectivity and an Experimental Model of Virus Infection

PubMed Central

De Flora, Silvio

1974-01-01

Areas of cytopathic effect can be circumscribed in cell monolayers by adding antiserum to the liquid nutrient medium after adsorption of virus. This procedure represents a simple and reliable tool for the titration of virus infectivity and provides an experimental model for studying some aspects of virus infection. Images PMID:4364462

Experimental and rendering-based investigation of laser radar cross sections of small unmanned aerial vehicles

NASA Astrophysics Data System (ADS)

Laurenzis, Martin; Bacher, Emmanuel; Christnacher, Frank

2017-12-01

Laser imaging systems are prominent candidates for detection and tracking of small unmanned aerial vehicles (UAVs) in current and future security scenarios. Laser reflection characteristics for laser imaging (e.g., laser gated viewing) of small UAVs are investigated to determine their laser radar cross section (LRCS) by analyzing the intensity distribution of laser reflection in high resolution images. For the first time, LRCSs are determined in a combined experimental and computational approaches by high resolution laser gated viewing and three-dimensional rendering. An optimized simple surface model is calculated taking into account diffuse and specular reflectance properties based on the Oren-Nayar and the Cook-Torrance reflectance models, respectively.

Photogrammetric 3d Building Reconstruction from Thermal Images

NASA Astrophysics Data System (ADS)

Maset, E.; Fusiello, A.; Crosilla, F.; Toldo, R.; Zorzetto, D.

2017-08-01

This paper addresses the problem of 3D building reconstruction from thermal infrared (TIR) images. We show that a commercial Computer Vision software can be used to automatically orient sequences of TIR images taken from an Unmanned Aerial Vehicle (UAV) and to generate 3D point clouds, without requiring any GNSS/INS data about position and attitude of the images nor camera calibration parameters. Moreover, we propose a procedure based on Iterative Closest Point (ICP) algorithm to create a model that combines high resolution and geometric accuracy of RGB images with the thermal information deriving from TIR images. The process can be carried out entirely by the aforesaid software in a simple and efficient way.

Robust optical flow using adaptive Lorentzian filter for image reconstruction under noisy condition

NASA Astrophysics Data System (ADS)

Kesrarat, Darun; Patanavijit, Vorapoj

2017-02-01

In optical flow for motion allocation, the efficient result in Motion Vector (MV) is an important issue. Several noisy conditions may cause the unreliable result in optical flow algorithms. We discover that many classical optical flows algorithms perform better result under noisy condition when combined with modern optimized model. This paper introduces effective robust models of optical flow by using Robust high reliability spatial based optical flow algorithms using the adaptive Lorentzian norm influence function in computation on simple spatial temporal optical flows algorithm. Experiment on our proposed models confirm better noise tolerance in optical flow's MV under noisy condition when they are applied over simple spatial temporal optical flow algorithms as a filtering model in simple frame-to-frame correlation technique. We illustrate the performance of our models by performing an experiment on several typical sequences with differences in movement speed of foreground and background where the experiment sequences are contaminated by the additive white Gaussian noise (AWGN) at different noise decibels (dB). This paper shows very high effectiveness of noise tolerance models that they are indicated by peak signal to noise ratio (PSNR).

A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers.

PubMed

Bellesi, Luca; Wyttenbach, Rolf; Gaudino, Diego; Colleoni, Paolo; Pupillo, Francesco; Carrara, Mauro; Braghetti, Antonio; Puligheddu, Carla; Presilla, Stefano

2017-01-01

The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment. Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images. Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result. IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

The Role of Diffusion-Weighted Magnetic Resonance Imaging in the Differential Diagnosis of Simple and Hydatid Cysts of the Liver.

PubMed

Aksoy, S; Erdil, I; Hocaoglu, E; Inci, E; Adas, G T; Kemik, O; Turkay, R

2018-02-01

The present study indicates that simple and hydatid cysts in liver are a common health problem in Turkey. The aim of the study is to differentiate different types of hydatid cysts from simple cysts by using diffusion-weighted images. In total, 37 hydatid cysts and 36 simple cysts in the liver were diagnosed. We retrospectively reviewed the medical records of the patients who had both ultrasonography and magnetic resonance imaging. We measured apparent diffusion coefficient (ADC) values of all the cysts and then compared the findings. There was no statistically meaningful difference between the ADC values of simple cysts and type 1 hydatid cysts. However, for the other types of hydatid cysts, it is possible to differentiate hydatid cysts from simple cysts using the ADC values. Although in our study we cannot differentiate between type I hydatid cysts and simple cysts in the liver, diffusion-weighted images are very useful to differentiate different types of hydatid cysts from simple cysts using the ADC values.

Content dependent selection of image enhancement parameters for mobile displays

NASA Astrophysics Data System (ADS)

Lee, Yoon-Gyoo; Kang, Yoo-Jin; Kim, Han-Eol; Kim, Ka-Hee; Kim, Choon-Woo

2011-01-01

Mobile devices such as cellular phones and portable multimedia player with capability of playing terrestrial digital multimedia broadcasting (T-DMB) contents have been introduced into consumer market. In this paper, content dependent image quality enhancement method for sharpness and colorfulness and noise reduction is presented to improve perceived image quality on mobile displays. Human visual experiments are performed to analyze viewers' preference. Relationship between the objective measures and the optimal values of image control parameters are modeled by simple lookup tables based on the results of human visual experiments. Content dependent values of image control parameters are determined based on the calculated measures and predetermined lookup tables. Experimental results indicate that dynamic selection of image control parameters yields better image quality.

Image Formation in Lenses and Mirrors, a Complete Representation

ERIC Educational Resources Information Center

Bartlett, Albert A.

1976-01-01

Provides tables and graphs that give a complete and simple picture of the relationships of image distance, object distance, and magnification in all formations of images by simple lenses and mirrors. (CP)

PCANet: A Simple Deep Learning Baseline for Image Classification?

PubMed

Chan, Tsung-Han; Jia, Kui; Gao, Shenghua; Lu, Jiwen; Zeng, Zinan; Ma, Yi

2015-12-01

In this paper, we propose a very simple deep learning network for image classification that is based on very basic data processing components: 1) cascaded principal component analysis (PCA); 2) binary hashing; and 3) blockwise histograms. In the proposed architecture, the PCA is employed to learn multistage filter banks. This is followed by simple binary hashing and block histograms for indexing and pooling. This architecture is thus called the PCA network (PCANet) and can be extremely easily and efficiently designed and learned. For comparison and to provide a better understanding, we also introduce and study two simple variations of PCANet: 1) RandNet and 2) LDANet. They share the same topology as PCANet, but their cascaded filters are either randomly selected or learned from linear discriminant analysis. We have extensively tested these basic networks on many benchmark visual data sets for different tasks, including Labeled Faces in the Wild (LFW) for face verification; the MultiPIE, Extended Yale B, AR, Facial Recognition Technology (FERET) data sets for face recognition; and MNIST for hand-written digit recognition. Surprisingly, for all tasks, such a seemingly naive PCANet model is on par with the state-of-the-art features either prefixed, highly hand-crafted, or carefully learned [by deep neural networks (DNNs)]. Even more surprisingly, the model sets new records for many classification tasks on the Extended Yale B, AR, and FERET data sets and on MNIST variations. Additional experiments on other public data sets also demonstrate the potential of PCANet to serve as a simple but highly competitive baseline for texture classification and object recognition.

Stochastic performance modeling and evaluation of obstacle detectability with imaging range sensors

NASA Technical Reports Server (NTRS)

Matthies, Larry; Grandjean, Pierrick

1993-01-01

Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGVs) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms applied to the range data. We review existing models of the quality of range data from stereo vision and AM-CW LADAR, then use these to derive a new model for the quality of a simple obstacle detection algorithm. This model predicts the probability of detecting obstacles and the probability of false alarms, as a function of the size and distance of the obstacle, the resolution of the sensor, and the level of noise in the range data. We evaluate these models experimentally using range data from stereo image pairs of a gravel road with known obstacles at several distances. The results show that the approach is a promising tool for predicting and evaluating the performance of obstacle detection with imaging range sensors.

Epithelium-Stroma Classification via Convolutional Neural Networks and Unsupervised Domain Adaptation in Histopathological Images.

PubMed

Huang, Yue; Zheng, Han; Liu, Chi; Ding, Xinghao; Rohde, Gustavo K

2017-11-01

Epithelium-stroma classification is a necessary preprocessing step in histopathological image analysis. Current deep learning based recognition methods for histology data require collection of large volumes of labeled data in order to train a new neural network when there are changes to the image acquisition procedure. However, it is extremely expensive for pathologists to manually label sufficient volumes of data for each pathology study in a professional manner, which results in limitations in real-world applications. A very simple but effective deep learning method, that introduces the concept of unsupervised domain adaptation to a simple convolutional neural network (CNN), has been proposed in this paper. Inspired by transfer learning, our paper assumes that the training data and testing data follow different distributions, and there is an adaptation operation to more accurately estimate the kernels in CNN in feature extraction, in order to enhance performance by transferring knowledge from labeled data in source domain to unlabeled data in target domain. The model has been evaluated using three independent public epithelium-stroma datasets by cross-dataset validations. The experimental results demonstrate that for epithelium-stroma classification, the proposed framework outperforms the state-of-the-art deep neural network model, and it also achieves better performance than other existing deep domain adaptation methods. The proposed model can be considered to be a better option for real-world applications in histopathological image analysis, since there is no longer a requirement for large-scale labeled data in each specified domain.

Using color histogram normalization for recovering chromatic illumination-changed images.

PubMed

Pei, S C; Tseng, C L; Wu, C C

2001-11-01

We propose a novel image-recovery method using the covariance matrix of the red-green-blue (R-G-B) color histogram and tensor theories. The image-recovery method is called the color histogram normalization algorithm. It is known that the color histograms of an image taken under varied illuminations are related by a general affine transformation of the R-G-B coordinates when the illumination is changed. We propose a simplified affine model for application with illumination variation. This simplified affine model considers the effects of only three basic forms of distortion: translation, scaling, and rotation. According to this principle, we can estimate the affine transformation matrix necessary to recover images whose color distributions are varied as a result of illumination changes. We compare the normalized color histogram of the standard image with that of the tested image. By performing some operations of simple linear algebra, we can estimate the matrix of the affine transformation between two images under different illuminations. To demonstrate the performance of the proposed algorithm, we divide the experiments into two parts: computer-simulated images and real images corresponding to illumination changes. Simulation results show that the proposed algorithm is effective for both types of images. We also explain the noise-sensitive skew-rotation estimation that exists in the general affine model and demonstrate that the proposed simplified affine model without the use of skew rotation is better than the general affine model for such applications.

A simple approach to quantitative analysis using three-dimensional spectra based on selected Zernike moments.

PubMed

Zhai, Hong Lin; Zhai, Yue Yuan; Li, Pei Zhen; Tian, Yue Li

2013-01-21

A very simple approach to quantitative analysis is proposed based on the technology of digital image processing using three-dimensional (3D) spectra obtained by high-performance liquid chromatography coupled with a diode array detector (HPLC-DAD). As the region-based shape features of a grayscale image, Zernike moments with inherently invariance property were employed to establish the linear quantitative models. This approach was applied to the quantitative analysis of three compounds in mixed samples using 3D HPLC-DAD spectra, and three linear models were obtained, respectively. The correlation coefficients (R(2)) for training and test sets were more than 0.999, and the statistical parameters and strict validation supported the reliability of established models. The analytical results suggest that the Zernike moment selected by stepwise regression can be used in the quantitative analysis of target compounds. Our study provides a new idea for quantitative analysis using 3D spectra, which can be extended to the analysis of other 3D spectra obtained by different methods or instruments.

A novel method for fast imaging of brain function, non-invasively, with light

NASA Astrophysics Data System (ADS)

Chance, Britton; Anday, Endla; Nioka, Shoko; Zhou, Shuoming; Hong, Long; Worden, Katherine; Li, C.; Murray, T.; Ovetsky, Y.; Pidikiti, D.; Thomas, R.

1998-05-01

Imaging of the human body by any non-invasive technique has been an appropriate goal of physics and medicine, and great success has been obtained with both Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) in brain imaging. Non-imaging responses to functional activation using near infrared spectroscopy of brain (fNIR) obtained in 1993 (Chance, et al. [1]) and in 1994 (Tamura, et al. [2]) are now complemented with images of pre-frontal and parietal stimulation in adults and pre-term neonates in this communication (see also [3]). Prior studies used continuous [4], pulsed [3] or modulated [5] light. The amplitude and phase cancellation of optical patterns as demonstrated for single source detector pairs affords remarkable sensitivity of small object detection in model systems [6]. The methods have now been elaborated with multiple source detector combinations (nine sources, four detectors). Using simple back projection algorithms it is now possible to image sensorimotor and cognitive activation of adult and pre- and full-term neonate human brain function in times < 30 sec and with two dimensional resolutions of < 1 cm in two dimensional displays. The method can be used in evaluation of adult and neonatal cerebral dysfunction in a simple, portable and affordable method that does not require immobilization, as contrasted to MRI and PET.

Simple and robust image-based autofocusing for digital microscopy.

PubMed

Yazdanfar, Siavash; Kenny, Kevin B; Tasimi, Krenar; Corwin, Alex D; Dixon, Elizabeth L; Filkins, Robert J

2008-06-09

A simple image-based autofocusing scheme for digital microscopy is demonstrated that uses as few as two intermediate images to bring the sample into focus. The algorithm is adapted to a commercial inverted microscope and used to automate brightfield and fluorescence imaging of histopathology tissue sections.

Image texture segmentation using a neural network

NASA Astrophysics Data System (ADS)

Sayeh, Mohammed R.; Athinarayanan, Ragu; Dhali, Pushpuak

1992-09-01

In this paper we use a neural network called the Lyapunov associative memory (LYAM) system to segment image texture into different categories or clusters. The LYAM system is constructed by a set of ordinary differential equations which are simulated on a digital computer. The clustering can be achieved by using a single tuning parameter in the simplest model. Pattern classes are represented by the stable equilibrium states of the system. Design of the system is based on synthesizing two local energy functions, namely, the learning and recall energy functions. Before the implementation of the segmentation process, a Gauss-Markov random field (GMRF) model is applied to the raw image. This application suitably reduces the image data and prepares the texture information for the neural network process. We give a simple image example illustrating the capability of the technique. The GMRF-generated features are also used for a clustering, based on the Euclidean distance.

Inferring Biological Structures from Super-Resolution Single Molecule Images Using Generative Models

PubMed Central

Maji, Suvrajit; Bruchez, Marcel P.

2012-01-01

Localization-based super resolution imaging is presently limited by sampling requirements for dynamic measurements of biological structures. Generating an image requires serial acquisition of individual molecular positions at sufficient density to define a biological structure, increasing the acquisition time. Efficient analysis of biological structures from sparse localization data could substantially improve the dynamic imaging capabilities of these methods. Using a feature extraction technique called the Hough Transform simple biological structures are identified from both simulated and real localization data. We demonstrate that these generative models can efficiently infer biological structures in the data from far fewer localizations than are required for complete spatial sampling. Analysis at partial data densities revealed efficient recovery of clathrin vesicle size distributions and microtubule orientation angles with as little as 10% of the localization data. This approach significantly increases the temporal resolution for dynamic imaging and provides quantitatively useful biological information. PMID:22629348

Segmentation by fusion of histogram-based k-means clusters in different color spaces.

PubMed

Mignotte, Max

2008-05-01

This paper presents a new, simple, and efficient segmentation approach, based on a fusion procedure which aims at combining several segmentation maps associated to simpler partition models in order to finally get a more reliable and accurate segmentation result. The different label fields to be fused in our application are given by the same and simple (K-means based) clustering technique on an input image expressed in different color spaces. Our fusion strategy aims at combining these segmentation maps with a final clustering procedure using as input features, the local histogram of the class labels, previously estimated and associated to each site and for all these initial partitions. This fusion framework remains simple to implement, fast, general enough to be applied to various computer vision applications (e.g., motion detection and segmentation), and has been successfully applied on the Berkeley image database. The experiments herein reported in this paper illustrate the potential of this approach compared to the state-of-the-art segmentation methods recently proposed in the literature.

FluoroSim: A Visual Problem-Solving Environment for Fluorescence Microscopy

PubMed Central

Quammen, Cory W.; Richardson, Alvin C.; Haase, Julian; Harrison, Benjamin D.; Taylor, Russell M.; Bloom, Kerry S.

2010-01-01

Fluorescence microscopy provides a powerful method for localization of structures in biological specimens. However, aspects of the image formation process such as noise and blur from the microscope's point-spread function combine to produce an unintuitive image transformation on the true structure of the fluorescing molecules in the specimen, hindering qualitative and quantitative analysis of even simple structures in unprocessed images. We introduce FluoroSim, an interactive fluorescence microscope simulator that can be used to train scientists who use fluorescence microscopy to understand the artifacts that arise from the image formation process, to determine the appropriateness of fluorescence microscopy as an imaging modality in an experiment, and to test and refine hypotheses of model specimens by comparing the output of the simulator to experimental data. FluoroSim renders synthetic fluorescence images from arbitrary geometric models represented as triangle meshes. We describe three rendering algorithms on graphics processing units for computing the convolution of the specimen model with a microscope's point-spread function and report on their performance. We also discuss several cases where the microscope simulator has been used to solve real problems in biology. PMID:20431698

Modeling Impact of Urbanization in US Cities Using Simple Biosphere Model SiB2

NASA Technical Reports Server (NTRS)

Zhang, Ping; Bounoua, Lahouari; Thome, Kurtis; Wolfe, Robert

2016-01-01

We combine Landsat- and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based products, as well as climate drivers from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) in a Simple Biosphere land surface model (SiB2) to assess the impact of urbanization in continental USA (excluding Alaska and Hawaii). More than 300 cities and their surrounding suburban and rural areas are defined in this study to characterize the impact of urbanization on surface climate including surface energy, carbon budget, and water balance. These analyses reveal an uneven impact of urbanization across the continent that should inform upon policy options for improving urban growth including heat mitigation and energy use, carbon sequestration and flood prevention.

A New Model for Inquiry: Is the Scientific Method Dead?

ERIC Educational Resources Information Center

Harwood, William S.

2004-01-01

There has been renewed discussion of the scientific method, with many voices arguing that it presents a very limited or even wholly incorrect image of the way science is really done. At the same time, the idea of a scientific method is pervasive. This article identifies the scientific method as a simple model for the process of scientific inquiry.…

Image Search Reranking With Hierarchical Topic Awareness.

PubMed

Tian, Xinmei; Yang, Linjun; Lu, Yijuan; Tian, Qi; Tao, Dacheng

2015-10-01

With much attention from both academia and industrial communities, visual search reranking has recently been proposed to refine image search results obtained from text-based image search engines. Most of the traditional reranking methods cannot capture both relevance and diversity of the search results at the same time. Or they ignore the hierarchical topic structure of search result. Each topic is treated equally and independently. However, in real applications, images returned for certain queries are naturally in hierarchical organization, rather than simple parallel relation. In this paper, a new reranking method "topic-aware reranking (TARerank)" is proposed. TARerank describes the hierarchical topic structure of search results in one model, and seamlessly captures both relevance and diversity of the image search results simultaneously. Through a structured learning framework, relevance and diversity are modeled in TARerank by a set of carefully designed features, and then the model is learned from human-labeled training samples. The learned model is expected to predict reranking results with high relevance and diversity for testing queries. To verify the effectiveness of the proposed method, we collect an image search dataset and conduct comparison experiments on it. The experimental results demonstrate that the proposed TARerank outperforms the existing relevance-based and diversified reranking methods.

The propagation of sound in tunnels

NASA Astrophysics Data System (ADS)

Li, Kai Ming; Iu, King Kwong

2002-11-01

The sound propagation in tunnels is addressed theoretically and experimentally. In many previous studies, the image source method is frequently used. However, these early theoretical models are somewhat inadequate because the effect of multiple reflections in long enclosures is often modeled by the incoherent summation of contributions from all image sources. Ignoring the phase effect, these numerical models are unlikely to be satisfactory for predicting the intricate interference patterns due to contributions from each image source. In the present paper, the interference effect is incorporated by summing the contributions from the image sources coherently. To develop a simple numerical model, tunnels are represented by long rectangular enclosures with either geometrically reflecting or impedance boundaries. Scale model experiments are conducted for the validation of the numerical model. In some of the scale model experiments, the enclosure walls are lined with a carpet for simulating the impedance boundary condition. Large-scale outdoor measurements have also been conducted in two tunnels designed originally for road traffic use. It has been shown that the proposed numerical model agrees reasonably well with experimental data. [Work supported by the Research Grants Council, The Industry Department, NAP Acoustics (Far East) Ltd., and The Hong Kong Polytechnic University.

Portal dosimetry for VMAT using integrated images obtained during treatment

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

Bedford, James L., E-mail: James.Bedford@icr.ac.uk; Hanson, Ian M.; Hansen, Vibeke Nordmark

2014-02-15

Purpose: Portal dosimetry provides an accurate and convenient means of verifying dose delivered to the patient. A simple method for carrying out portal dosimetry for volumetric modulated arc therapy (VMAT) is described, together with phantom measurements demonstrating the validity of the approach. Methods: Portal images were predicted by projecting dose in the isocentric plane through to the portal image plane, with exponential attenuation and convolution with a double-Gaussian scatter function. Appropriate parameters for the projection were selected by fitting the calculation model to portal images measured on an iViewGT portal imager (Elekta AB, Stockholm, Sweden) for a variety of phantommore » thicknesses and field sizes. This model was then used to predict the portal image resulting from each control point of a VMAT arc. Finally, all these control point images were summed to predict the overall integrated portal image for the whole arc. The calculated and measured integrated portal images were compared for three lung and three esophagus plans delivered to a thorax phantom, and three prostate plans delivered to a homogeneous phantom, using a gamma index for 3% and 3 mm. A 0.6 cm{sup 3} ionization chamber was used to verify the planned isocentric dose. The sensitivity of this method to errors in monitor units, field shaping, gantry angle, and phantom position was also evaluated by means of computer simulations. Results: The calculation model for portal dose prediction was able to accurately compute the portal images due to simple square fields delivered to solid water phantoms. The integrated images of VMAT treatments delivered to phantoms were also correctly predicted by the method. The proportion of the images with a gamma index of less than unity was 93.7% ± 3.0% (1SD) and the difference between isocenter dose calculated by the planning system and measured by the ionization chamber was 0.8% ± 1.0%. The method was highly sensitive to errors in monitor units and field shape, but less sensitive to errors in gantry angle or phantom position. Conclusions: This method of predicting integrated portal images provides a convenient means of verifying dose delivered using VMAT, with minimal image acquisition and data processing requirements.« less

Vacuum ultraviolet images of the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Smith, Andrew M.; Cornett, Robert H.; Hill, Robert S.

1987-09-01

Images with 50arcsec resolution of the Large Magellanic Cloud (LMC), obtained with sounding-rocket instrumentation in two vacuum ultraviolet (VUV) bandpasses, are presented. The bandpasses are each ≡200 Å wide and are centered, for hot stars, near 1500 Å and 1900 Å. Photometry was done on the digitized images for all associations in the list of Lucke and Hodge. The authors discuss the results and their relationship to the overall characteristics of star formation in the LMC. They present a simple model for propagating star formation in the LMC whose results closely resemble the distribution of associations as revealed by VUV images.

Image discrimination models predict detection in fixed but not random noise

NASA Technical Reports Server (NTRS)

Ahumada, A. J. Jr; Beard, B. L.; Watson, A. B. (Principal Investigator)

1997-01-01

By means of a two-interval forced-choice procedure, contrast detection thresholds for an aircraft positioned on a simulated airport runway scene were measured with fixed and random white-noise masks. The term fixed noise refers to a constant, or unchanging, noise pattern for each stimulus presentation. The random noise was either the same or different in the two intervals. Contrary to simple image discrimination model predictions, the same random noise condition produced greater masking than the fixed noise. This suggests that observers seem unable to hold a new noisy image for comparison. Also, performance appeared limited by internal process variability rather than by external noise variability, since similar masking was obtained for both random noise types.

Imaging, microscopic analysis, and modeling of a CdTe module degraded by heat and light

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

Johnston, Steve; Albin, David; Hacke, Peter

Photoluminescence (PL), electroluminescence (EL), and dark lock-in thermography are collected during stressing of a CdTe module under one-Sun light at an elevated temperature of 100 degrees C. The PL imaging system is simple and economical. The PL images show differing degrees of degradation across the module and are less sensitive to effects of shunting and resistance that appear on the EL images. Regions of varying degradation are chosen based on avoiding pre-existing shunt defects. These regions are evaluated using time-of-flight secondary ion-mass spectrometry and Kelvin probe force microscopy. Reduced PL intensity correlates to increased Cu concentration at the front interface.more » Numerical modeling and measurements agree that the increased Cu concentration at the junction also correlates to a reduced space charge region.« less

Imaging, microscopic analysis, and modeling of a CdTe module degraded by heat and light

DOE PAGES

Johnston, Steve; Albin, David; Hacke, Peter; ...

2018-01-12

Photoluminescence (PL), electroluminescence (EL), and dark lock-in thermography are collected during stressing of a CdTe module under one-Sun light at an elevated temperature of 100 degrees C. The PL imaging system is simple and economical. The PL images show differing degrees of degradation across the module and are less sensitive to effects of shunting and resistance that appear on the EL images. Regions of varying degradation are chosen based on avoiding pre-existing shunt defects. These regions are evaluated using time-of-flight secondary ion-mass spectrometry and Kelvin probe force microscopy. Reduced PL intensity correlates to increased Cu concentration at the front interface.more » Numerical modeling and measurements agree that the increased Cu concentration at the junction also correlates to a reduced space charge region.« less

Compressive Hyperspectral Imaging and Anomaly Detection

DTIC Science & Technology

2010-02-01

Level Set Systems 1058 Embury Street Pacific Palisades , CA 90272 8. PERFORMING ORGANIZATION REPORT NUMBER 1A-2010 9. SPONSORING/MONITORING...were obtained from a simple algorithm, namely, the atoms in the trained image were very similar to the simple cell receptive fields in early vision...Field, "Emergence of simple- cell receptive field properties by learning a sparse code for natural images,’" Nature 381(6583), pp. 607-609, 1996. M

J-Plus Web Portal

NASA Astrophysics Data System (ADS)

Civera Lorenzo, Tamara

2017-10-01

Brief presentation about the J-PLUS EDR data access web portal (http://archive.cefca.es/catalogues/jplus-edr) where the different services available to retrieve images and catalogues data have been presented.J-PLUS Early Data Release (EDR) archive includes two types of data: images and dual and single catalogue data which include parameters measured from images. J-PLUS web portal offers catalogue data and images through several different online data access tools or services each suited to a particular need. The different services offered are: Coverage map Sky navigator Object visualization Image search Cone search Object list search Virtual observatory services: Simple Cone Search Simple Image Access Protocol Simple Spectral Access Protocol Table Access Protocol

Flow-induced Flutter of Heart Valves: Experiments with Canonical Models

NASA Astrophysics Data System (ADS)

Dou, Zhongwang; Seo, Jung-Hee; Mittal, Rajat

2017-11-01

For the better understanding of hemodynamics associated with valvular function in health and disease, the flow-induced flutter of heart valve leaflets is studied using benchtop experiments with canonical valve models. A simple experimental model with flexible leaflets is constructed and a pulsatile pump drives the flow through the leaflets. We quantify the leaflet dynamics using digital image analysis and also characterize the dynamics of the flow around the leaflets using particle imaging velocimetry. Experiments are conducted over a wide range of flow and leaflet parameters and data curated for use as a benchmark for validation of computational fluid-structure interaction models. The authors would like to acknowledge Supported from NSF Grants IIS-1344772, CBET-1511200 and NSF XSEDE Grant TG-CTS100002.

Accelerated Edge-Preserving Image Restoration Without Boundary Artifacts

PubMed Central

Matakos, Antonios; Ramani, Sathish; Fessler, Jeffrey A.

2013-01-01

To reduce blur in noisy images, regularized image restoration methods have been proposed that use non-quadratic regularizers (like l1 regularization or total-variation) that suppress noise while preserving edges in the image. Most of these methods assume a circulant blur (periodic convolution with a blurring kernel) that can lead to wraparound artifacts along the boundaries of the image due to the implied periodicity of the circulant model. Using a non-circulant model could prevent these artifacts at the cost of increased computational complexity. In this work we propose to use a circulant blur model combined with a masking operator that prevents wraparound artifacts. The resulting model is non-circulant, so we propose an efficient algorithm using variable splitting and augmented Lagrangian (AL) strategies. Our variable splitting scheme, when combined with the AL framework and alternating minimization, leads to simple linear systems that can be solved non-iteratively using FFTs, eliminating the need for more expensive CG-type solvers. The proposed method can also efficiently tackle a variety of convex regularizers including edge-preserving (e.g., total-variation) and sparsity promoting (e.g., l1 norm) regularizers. Simulation results show fast convergence of the proposed method, along with improved image quality at the boundaries where the circulant model is inaccurate. PMID:23372080

Path planning on cellular nonlinear network using active wave computing technique

NASA Astrophysics Data System (ADS)

Yeniçeri, Ramazan; Yalçın, Müstak E.

2009-05-01

This paper introduces a simple algorithm to solve robot path finding problem using active wave computing techniques. A two-dimensional Cellular Neural/Nonlinear Network (CNN), consist of relaxation oscillators, has been used to generate active waves and to process the visual information. The network, which has been implemented on a Field Programmable Gate Array (FPGA) chip, has the feature of being programmed, controlled and observed by a host computer. The arena of the robot is modelled as the medium of the active waves on the network. Active waves are employed to cover the whole medium with their own dynamics, by starting from an initial point. The proposed algorithm is achieved by observing the motion of the wave-front of the active waves. Host program first loads the arena model onto the active wave generator network and command to start the generation. Then periodically pulls the network image from the generator hardware to analyze evolution of the active waves. When the algorithm is completed, vectorial data image is generated. The path from any of the pixel on this image to the active wave generating pixel is drawn by the vectors on this image. The robot arena may be a complicated labyrinth or may have a simple geometry. But, the arena surface always must be flat. Our Autowave Generator CNN implementation which is settled on the Xilinx University Program Virtex-II Pro Development System is operated by a MATLAB program running on the host computer. As the active wave generator hardware has 16, 384 neurons, an arena with 128 × 128 pixels can be modeled and solved by the algorithm. The system also has a monitor and network image is depicted on the monitor simultaneously.

A non-iterative twin image elimination method with two in-line digital holograms

NASA Astrophysics Data System (ADS)

Kim, Jongwu; Lee, Heejung; Jeon, Philjun; Kim, Dug Young

2018-02-01

We propose a simple non-iterative in-line holographic measurement method which can effectively eliminate a twin image in digital holographic 3D imaging. It is shown that a twin image can be effectively eliminated with only two measured holograms by using a simple numerical propagation algorithm and arithmetic calculations.

Slantwise convection on fluid planets: Interpreting convective adjustment from Juno observations

NASA Astrophysics Data System (ADS)

O'Neill, M. E.; Kaspi, Y.; Galanti, E.

2016-12-01

NASA's Juno mission provides unprecedented microwave measurements that pierce Jupiter's weather layer and image the transition to an adiabatic fluid below. This region is expected to be highly turbulent and complex, but to date most models use the moist-to-dry transition as a simple boundary. We present simple theoretical arguments and GCM results to argue that columnar convection is important even in the relatively thin boundary layer, particularly in the equatorial region. We first demonstrate how surface cooling can lead to very horizontal parcel paths, using a simple parcel model. Next we show the impact of this horizontal motion on angular momentum flux in a high-resolution Jovian model. The GCM is a state-of-the-art modification of the MITgcm, with deep geometry, compressibility and interactive two-stream radiation. We show that slantwise convection primarily mixes fluid along columnar surfaces of angular momentum, and discuss the impacts this should have on lapse rate interpretation of both the Galileo probe sounding and the Juno microwave observations.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-05-25

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-11-23

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

PubMed

Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

2015-09-30

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. Copyright © 2015 the authors 0270-6474/15/3513402-17$15.00/0.

Marangoni Convection and Deviations from Maxwells' Evaporation Model

NASA Technical Reports Server (NTRS)

Segre, P. N.; Snell, E. H.; Adamek, D. H.

2003-01-01

We investigate the convective dynamics of evaporating pools of volatile liquids using an ultra-sensitive thermal imaging camera. During evaporation, there are significant convective flows inside the liquid due to Marangoni forces. We find that Marangoni convection during evaporation can dramatically affect the evaporation rates of volatile liquids. A simple heat balance model connects the convective velocities and temperature gradients to the evaporation rates.

Intrinsic dimensionality predicts the saliency of natural dynamic scenes.

PubMed

Vig, Eleonora; Dorr, Michael; Martinetz, Thomas; Barth, Erhardt

2012-06-01

Since visual attention-based computer vision applications have gained popularity, ever more complex, biologically inspired models seem to be needed to predict salient locations (or interest points) in naturalistic scenes. In this paper, we explore how far one can go in predicting eye movements by using only basic signal processing, such as image representations derived from efficient coding principles, and machine learning. To this end, we gradually increase the complexity of a model from simple single-scale saliency maps computed on grayscale videos to spatiotemporal multiscale and multispectral representations. Using a large collection of eye movements on high-resolution videos, supervised learning techniques fine-tune the free parameters whose addition is inevitable with increasing complexity. The proposed model, although very simple, demonstrates significant improvement in predicting salient locations in naturalistic videos over four selected baseline models and two distinct data labeling scenarios.

Edge Detection Based On the Characteristic of Primary Visual Cortex Cells

NASA Astrophysics Data System (ADS)

Zhu, M. M.; Xu, Y. L.; Ma, H. Q.

2018-01-01

Aiming at the problem that it is difficult to balance the accuracy of edge detection and anti-noise performance, and referring to the dynamic and static perceptions of the primary visual cortex (V1) cells, a V1 cell model is established to perform edge detection. A spatiotemporal filter is adopted to simulate the receptive field of V1 simple cells, the model V1 cell is obtained after integrating the responses of simple cells by half-wave rectification and normalization, Then the natural image edge is detected by using static perception of V1 cells. The simulation results show that, the V1 model can basically fit the biological data and has the universality of biology. What’s more, compared with other edge detection operators, the proposed model is more effective and has better robustness

Improved quality of intrafraction kilovoltage images by triggered readout of unexposed frames

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

Poulsen, Per Rugaard, E-mail: per.poulsen@rm.dk; Jonassen, Johnny; Jensen, Carsten

2015-11-15

Purpose: The gantry-mounted kilovoltage (kV) imager of modern linear accelerators can be used for real-time tumor localization during radiation treatment delivery. However, the kV image quality often suffers from cross-scatter from the megavoltage (MV) treatment beam. This study investigates readout of unexposed kV frames as a means to improve the kV image quality in a series of experiments and a theoretical model of the observed image quality improvements. Methods: A series of fluoroscopic images were acquired of a solid water phantom with an embedded gold marker and an air cavity with and without simultaneous radiation of the phantom with amore » 6 MV beam delivered perpendicular to the kV beam with 300 and 600 monitor units per minute (MU/min). An in-house built device triggered readout of zero, one, or multiple unexposed frames between the kV exposures. The unexposed frames contained part of the MV scatter, consequently reducing the amount of MV scatter accumulated in the exposed frames. The image quality with and without unexposed frame readout was quantified as the contrast-to-noise ratio (CNR) of the gold marker and air cavity for a range of imaging frequencies from 1 to 15 Hz. To gain more insight into the observed CNR changes, the image lag of the kV imager was measured and used as input in a simple model that describes the CNR with unexposed frame readout in terms of the contrast, kV noise, and MV noise measured without readout of unexposed frames. Results: Without readout of unexposed kV frames, the quality of intratreatment kV images decreased dramatically with reduced kV frequencies due to MV scatter. The gold marker was only visible for imaging frequencies ≥3 Hz at 300 MU/min and ≥5 Hz for 600 MU/min. Visibility of the air cavity required even higher imaging frequencies. Readout of multiple unexposed frames ensured visibility of both structures at all imaging frequencies and a CNR that was independent of the kV frame rate. The image lag was 12.2%, 2.2%, and 0.9% in the first, second, and third frame after an exposure. The CNR model predicted the CNR with triggered image readout with a mean absolute error of 2.0% for the gold marker. Conclusions: A device that triggers readout of unexposed frames during kV fluoroscopy was built and shown to greatly improve the quality of intratreatment kV images. A simple theoretical model successfully described the CNR improvements with the device.« less

Mechanisms of Neuronal Computation in Mammalian Visual Cortex

PubMed Central

Priebe, Nicholas J.; Ferster, David

2012-01-01

Orientation selectivity in the primary visual cortex (V1) is a receptive field property that is at once simple enough to make it amenable to experimental and theoretical approaches and yet complex enough to represent a significant transformation in the representation of the visual image. As a result, V1 has become an area of choice for studying cortical computation and its underlying mechanisms. Here we consider the receptive field properties of the simple cells in cat V1—the cells that receive direct input from thalamic relay cells—and explore how these properties, many of which are highly nonlinear, arise. We have found that many receptive field properties of V1 simple cells fall directly out of Hubel and Wiesel’s feedforward model when the model incorporates realistic neuronal and synaptic mechanisms, including threshold, synaptic depression, response variability, and the membrane time constant. PMID:22841306

Comparison analysis between filtered back projection and algebraic reconstruction technique on microwave imaging

NASA Astrophysics Data System (ADS)

Ramadhan, Rifqi; Prabowo, Rian Gilang; Aprilliyani, Ria; Basari

2018-02-01

Victims of acute cancer and tumor are growing each year and cancer becomes one of the causes of human deaths in the world. Cancers or tumor tissue cells are cells that grow abnormally and turn to take over and damage the surrounding tissues. At the beginning, cancers or tumors do not have definite symptoms in its early stages, and can even attack the tissues inside of the body. This phenomena is not identifiable under visual human observation. Therefore, an early detection system which is cheap, quick, simple, and portable is essensially required to anticipate the further development of cancer or tumor. Among all of the modalities, microwave imaging is considered to be a cheaper, simple, and portable system method. There are at least two simple image reconstruction algorithms i.e. Filtered Back Projection (FBP) and Algebraic Reconstruction Technique (ART), which have been adopted in some common modalities. In this paper, both algorithms will be compared by reconstructing the image from an artificial tissue model (i.e. phantom), which has two different dielectric distributions. We addressed two performance comparisons, namely quantitative and qualitative analysis. Qualitative analysis includes the smoothness of the image and also the success in distinguishing dielectric differences by observing the image with human eyesight. In addition, quantitative analysis includes Histogram, Structural Similarity Index (SSIM), Mean Squared Error (MSE), and Peak Signal-to-Noise Ratio (PSNR) calculation were also performed. As a result, quantitative parameters of FBP might show better values than the ART. However, ART is likely more capable to distinguish two different dielectric value than FBP, due to higher contrast in ART and wide distribution grayscale level.

The monocular visual imaging technology model applied in the airport surface surveillance

NASA Astrophysics Data System (ADS)

Qin, Zhe; Wang, Jian; Huang, Chao

2013-08-01

At present, the civil aviation airports use the surface surveillance radar monitoring and positioning systems to monitor the aircrafts, vehicles and the other moving objects. Surface surveillance radars can cover most of the airport scenes, but because of the terminals, covered bridges and other buildings geometry, surface surveillance radar systems inevitably have some small segment blind spots. This paper presents a monocular vision imaging technology model for airport surface surveillance, achieving the perception of scenes of moving objects such as aircrafts, vehicles and personnel location. This new model provides an important complement for airport surface surveillance, which is different from the traditional surface surveillance radar techniques. Such technique not only provides clear objects activities screen for the ATC, but also provides image recognition and positioning of moving targets in this area. Thereby it can improve the work efficiency of the airport operations and avoid the conflict between the aircrafts and vehicles. This paper first introduces the monocular visual imaging technology model applied in the airport surface surveillance and then the monocular vision measurement accuracy analysis of the model. The monocular visual imaging technology model is simple, low cost, and highly efficient. It is an advanced monitoring technique which can make up blind spot area of the surface surveillance radar monitoring and positioning systems.

Laser interference microscopy: a novel approach to the visualization of structural changes in myelin during the propagation of nerve impulses

NASA Astrophysics Data System (ADS)

Yusipovich, A. I.; Cherkashin, A. A.; Verdiyan, E. E.; Sogomonyan, I. A.; Maksimov, G. V.

2016-08-01

We used 3D phase images obtained by laser interference microscopy (LIM) for ex vivo evaluation of changes in the structure of myelin during repetitive stimulation. In this work we propose a simple model of myelinated nerve fiber (mNF), which describes phase images as a result of different geometry and membrane-to-cytoplasm ratio in various regions, particularly, the internode and paranodal-nodal-paranodal region, including the node of Ranvier. Application of this model provides clear interpretation of the phase images and also demonstrates that repetitive action potentials are accompanied by structural changes in myelin in the internode and cytoplasmic modification in the node of Ranvier. The first 20 min of stimulation did not induce significant changes in the measured parameters, but then the optical path difference at the periphery of mNF and at the node of Ranvier declined reversibly. We believe that our model is also applicable to other modifications of interference and non-interference imaging.

Validation of a partial coherence interferometry method for estimating retinal shape

PubMed Central

Verkicharla, Pavan K.; Suheimat, Marwan; Pope, James M.; Sepehrband, Farshid; Mathur, Ankit; Schmid, Katrina L.; Atchison, David A.

2015-01-01

To validate a simple partial coherence interferometry (PCI) based retinal shape method, estimates of retinal shape were determined in 60 young adults using off-axis PCI, with three stages of modeling using variants of the Le Grand model eye, and magnetic resonance imaging (MRI). Stage 1 and 2 involved a basic model eye without and with surface ray deviation, respectively and Stage 3 used model with individual ocular biometry and ray deviation at surfaces. Considering the theoretical uncertainty of MRI (12-14%), the results of the study indicate good agreement between MRI and all three stages of PCI modeling with <4% and <7% differences in retinal shapes along horizontal and vertical meridians, respectively. Stage 2 and Stage 3 gave slightly different retinal co-ordinates than Stage 1 and we recommend the intermediate Stage 2 as providing a simple and valid method of determining retinal shape from PCI data. PMID:26417496

Validation of a partial coherence interferometry method for estimating retinal shape.

PubMed

Verkicharla, Pavan K; Suheimat, Marwan; Pope, James M; Sepehrband, Farshid; Mathur, Ankit; Schmid, Katrina L; Atchison, David A

2015-09-01

To validate a simple partial coherence interferometry (PCI) based retinal shape method, estimates of retinal shape were determined in 60 young adults using off-axis PCI, with three stages of modeling using variants of the Le Grand model eye, and magnetic resonance imaging (MRI). Stage 1 and 2 involved a basic model eye without and with surface ray deviation, respectively and Stage 3 used model with individual ocular biometry and ray deviation at surfaces. Considering the theoretical uncertainty of MRI (12-14%), the results of the study indicate good agreement between MRI and all three stages of PCI modeling with <4% and <7% differences in retinal shapes along horizontal and vertical meridians, respectively. Stage 2 and Stage 3 gave slightly different retinal co-ordinates than Stage 1 and we recommend the intermediate Stage 2 as providing a simple and valid method of determining retinal shape from PCI data.

G0-WISHART Distribution Based Classification from Polarimetric SAR Images

NASA Astrophysics Data System (ADS)

Hu, G. C.; Zhao, Q. H.

2017-09-01

Enormous scientific and technical developments have been carried out to further improve the remote sensing for decades, particularly Polarimetric Synthetic Aperture Radar(PolSAR) technique, so classification method based on PolSAR images has getted much more attention from scholars and related department around the world. The multilook polarmetric G0-Wishart model is a more flexible model which describe homogeneous, heterogeneous and extremely heterogeneous regions in the image. Moreover, the polarmetric G0-Wishart distribution dose not include the modified Bessel function of the second kind. It is a kind of simple statistical distribution model with less parameter. To prove its feasibility, a process of classification has been tested with the full-polarized Synthetic Aperture Radar (SAR) image by the method. First, apply multilook polarimetric SAR data process and speckle filter to reduce speckle influence for classification result. Initially classify the image into sixteen classes by H/A/α decomposition. Using the ICM algorithm to classify feature based on the G0-Wshart distance. Qualitative and quantitative results show that the proposed method can classify polaimetric SAR data effectively and efficiently.

Asymptotic solutions for the case of nearly symmetric gravitational lens systems

NASA Astrophysics Data System (ADS)

Wertz, O.; Pelgrims, V.; Surdej, J.

2012-08-01

Gravitational lensing provides a powerful tool to determine the Hubble parameter H0 from the measurement of the time delay Δt between two lensed images of a background variable source. Nevertheless, knowledge of the deflector mass distribution constitutes a hurdle. We propose in the present work interesting solutions for the case of nearly symmetric gravitational lens systems. For the case of a small misalignment between the source, the deflector and the observer, we first consider power-law (ɛ) axially symmetric models for which we derive an analytical relation between the amplification ratio and source position which is independent of the power-law slope ɛ. According to this relation, we deduce an expression for H0 also irrespective of the value ɛ. Secondly, we consider the power-law axially symmetric lens models with an external large-scale gravitational field, the shear γ, resulting in the so-called ɛ-γ models, for which we deduce simple first-order equations linking the model parameters and the lensed image positions, the latter being observable quantities. We also deduce simple relations between H0 and observables quantities only. From these equations, we may estimate the value of the Hubble parameter in a robust way. Nevertheless, comparison between the ɛ-γ and singular isothermal ellipsoid (SIE) models leads to the conclusion that these models remain most often distinct. Therefore, even for the case of a small misalignment, use of the first-order equations and precise astrometric measurements of the positions of the lensed images with respect to the centre of the deflector enables one to discriminate between these two families of models. Finally, we confront the models with numerical simulations to evaluate the intrinsic error of the first-order expressions used when deriving the model parameters under the assumption of a quasi-alignment between the source, the deflector and the observer. From these same simulations, we estimate for the case of the ɛ-γ family of models that the standard deviation affecting H0 is ? which merely reflects the adopted astrometric uncertainties on the relative image positions, typically ? arcsec. In conclusions, we stress the importance of getting very accurate measurements of the relative positions of the multiple lensed images and of the time delays for the case of nearly symmetric gravitational lens systems, in order to derive robust and precise values of the Hubble parameter.

The L0 Regularized Mumford-Shah Model for Bias Correction and Segmentation of Medical Images.

PubMed

Duan, Yuping; Chang, Huibin; Huang, Weimin; Zhou, Jiayin; Lu, Zhongkang; Wu, Chunlin

2015-11-01

We propose a new variant of the Mumford-Shah model for simultaneous bias correction and segmentation of images with intensity inhomogeneity. First, based on the model of images with intensity inhomogeneity, we introduce an L0 gradient regularizer to model the true intensity and a smooth regularizer to model the bias field. In addition, we derive a new data fidelity using the local intensity properties to allow the bias field to be influenced by its neighborhood. Second, we use a two-stage segmentation method, where the fast alternating direction method is implemented in the first stage for the recovery of true intensity and bias field and a simple thresholding is used in the second stage for segmentation. Different from most of the existing methods for simultaneous bias correction and segmentation, we estimate the bias field and true intensity without fixing either the number of the regions or their values in advance. Our method has been validated on medical images of various modalities with intensity inhomogeneity. Compared with the state-of-art approaches and the well-known brain software tools, our model is fast, accurate, and robust with initializations.

On-orbit point spread function estimation for THEOS imaging system

NASA Astrophysics Data System (ADS)

Khetkeeree, Suphongsa; Liangrocapart, Sompong

2018-03-01

In this paper, we present two approaches for net Point Spread Function (net-PSF) estimation of Thailand Earth Observation System (THEOS) imaging system. In the first approach, we estimate the net- PSF by employing the specification information of the satellite. The analytic model of the net- PSF based on the simple model of push-broom imaging system. This model consists of a scanner, optical system, detector and electronics system. The mathematical PSF model of each component is demonstrated in spatial domain. In the second approach, the specific target images from THEOS imaging system are analyzed to determine the net-PSF. For panchromatic imaging system, the images of the checkerboard target at Salon de Provence airport are used to analysis the net-PSF by slant-edge method. For multispectral imaging system, the new man-made targets are proposed. It is a pier bridge in Lamchabang, Chonburi, Thailand. This place has had a lot of bridges which have several width sizes and orientation. The pulse method is used to analysis the images of this bridge for estimating the net-PSF. Finally, the Full Width at Half Maximums (FWHMs) of the net-PSF of both approaches is compared. The results show that both approaches coincide and all Modulation Transfer Functions (MTFs) at Nyquist of both approaches are better than the requirement. However, the FWHM of multispectral system more deviate than panchromatic system, because the targets are not specially constructed for estimating the characteristics of the satellite imaging system.

Statistical iterative material image reconstruction for spectral CT using a semi-empirical forward model

NASA Astrophysics Data System (ADS)

Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.

2017-03-01

In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.

Milli-arcsecond images of the Herbig Ae star HD 163296

NASA Astrophysics Data System (ADS)

Renard, S.; Malbet, F.; Benisty, M.; Thiébaut, E.; Berger, J.-P.

2010-09-01

Context. The very close environments of young stars are the hosts of fundamental physical processes, such as planet formation, star-disk interactions, mass accretion, and ejection. The complex morphological structure of these environments has been confirmed by the now quite rich data sets obtained for a few objects by near-infrared long-baseline interferometry. Aims: We gathered numerous interferometric measurements for the young star HD 163296 with various interferometers (VLTI, IOTA, KeckI and CHARA), allowing for the first time an image independent of any a priori model to be reconstructed. Methods: Using the Multi-aperture image Reconstruction Algorithm (MiRA), we reconstruct images of HD 163296 in the H and K bands. We compare these images with reconstructed images obtained from simulated data using a physical model of the environment of HD 163296. Results: We obtain model-independent H and K-band images of the surroundings of HD 163296. The images detect several significant features that we can relate to an inclined asymmetric flared disk around HD 163296 with the strongest intensity at about 4-5 mas. Because of the incomplete spatial frequency coverage, we cannot state whether each of them individually is peculiar in any way. Conclusions: For the first time, milli-arcsecond images of the environment of a young star are produced. These images confirm that the morphology of the close environment of young stars is more complex than the simple models used in the literature so far.

LLSURE: local linear SURE-based edge-preserving image filtering.

PubMed

Qiu, Tianshuang; Wang, Aiqi; Yu, Nannan; Song, Aimin

2013-01-01

In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.

Medical image segmentation based on SLIC superpixels model

NASA Astrophysics Data System (ADS)

Chen, Xiang-ting; Zhang, Fan; Zhang, Ruo-ya

2017-01-01

Medical imaging has been widely used in clinical practice. It is an important basis for medical experts to diagnose the disease. However, medical images have many unstable factors such as complex imaging mechanism, the target displacement will cause constructed defect and the partial volume effect will lead to error and equipment wear, which increases the complexity of subsequent image processing greatly. The segmentation algorithm which based on SLIC (Simple Linear Iterative Clustering, SLIC) superpixels is used to eliminate the influence of constructed defect and noise by means of the feature similarity in the preprocessing stage. At the same time, excellent clustering effect can reduce the complexity of the algorithm extremely, which provides an effective basis for the rapid diagnosis of experts.

Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection.

PubMed

Jackman, Patrick; Sun, Da-Wen; Allen, Paul; Valous, Nektarios A; Mendoza, Fernando; Ward, Paddy

2010-04-01

A method to discriminate between various grades of pork and turkey ham was developed using colour and wavelet texture features. Image analysis methods originally developed for predicting the palatability of beef were applied to rapidly identify the ham grade. With high quality digital images of 50-94 slices per ham it was possible to identify the greyscale that best expressed the differences between the various ham grades. The best 10 discriminating image features were then found with a genetic algorithm. Using the best 10 image features, simple linear discriminant analysis models produced 100% correct classifications for both pork and turkey on both calibration and validation sets. 2009 Elsevier Ltd. All rights reserved.

Ecological statistics of Gestalt laws for the perceptual organization of contours.

PubMed

Elder, James H; Goldberg, Richard M

2002-01-01

Although numerous studies have measured the strength of visual grouping cues for controlled psychophysical stimuli, little is known about the statistical utility of these various cues for natural images. In this study, we conducted experiments in which human participants trace perceived contours in natural images. These contours are automatically mapped to sequences of discrete tangent elements detected in the image. By examining relational properties between pairs of successive tangents on these traced curves, and between randomly selected pairs of tangents, we are able to estimate the likelihood distributions required to construct an optimal Bayesian model for contour grouping. We employed this novel methodology to investigate the inferential power of three classical Gestalt cues for contour grouping: proximity, good continuation, and luminance similarity. The study yielded a number of important results: (1) these cues, when appropriately defined, are approximately uncorrelated, suggesting a simple factorial model for statistical inference; (2) moderate image-to-image variation of the statistics indicates the utility of general probabilistic models for perceptual organization; (3) these cues differ greatly in their inferential power, proximity being by far the most powerful; and (4) statistical modeling of the proximity cue indicates a scale-invariant power law in close agreement with prior psychophysics.

Dem Reconstruction Using Light Field and Bidirectional Reflectance Function from Multi-View High Resolution Spatial Images

NASA Astrophysics Data System (ADS)

de Vieilleville, F.; Ristorcelli, T.; Delvit, J.-M.

2016-06-01

This paper presents a method for dense DSM reconstruction from high resolution, mono sensor, passive imagery, spatial panchromatic image sequence. The interest of our approach is four-fold. Firstly, we extend the core of light field approaches using an explicit BRDF model from the Image Synthesis community which is more realistic than the Lambertian model. The chosen model is the Cook-Torrance BRDF which enables us to model rough surfaces with specular effects using specific material parameters. Secondly, we extend light field approaches for non-pinhole sensors and non-rectilinear motion by using a proper geometric transformation on the image sequence. Thirdly, we produce a 3D volume cost embodying all the tested possible heights and filter it using simple methods such as Volume Cost Filtering or variational optimal methods. We have tested our method on a Pleiades image sequence on various locations with dense urban buildings and report encouraging results with respect to classic multi-label methods such as MIC-MAC, or more recent pipelines such as S2P. Last but not least, our method also produces maps of material parameters on the estimated points, allowing us to simplify building classification or road extraction.

Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

PubMed

Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

2012-10-01

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Two-dimensional simulation and modeling in scanning electron microscope imaging and metrology research.

PubMed

Postek, Michael T; Vladár, András E; Lowney, Jeremiah R; Keery, William J

2002-01-01

Traditional Monte Carlo modeling of the electron beam-specimen interactions in a scanning electron microscope (SEM) produces information about electron beam penetration and output signal generation at either a single beam-landing location, or multiple landing positions. If the multiple landings lie on a line, the results can be graphed in a line scan-like format. Monte Carlo results formatted as line scans have proven useful in providing one-dimensional information about the sample (e.g., linewidth). When used this way, this process is called forward line scan modeling. In the present work, the concept of image simulation (or the first step in the inverse modeling of images) is introduced where the forward-modeled line scan data are carried one step further to construct theoretical two-dimensional (2-D) micrographs (i.e., theoretical SEM images) for comparison with similar experimentally obtained micrographs. This provides an ability to mimic and closely match theory and experiment using SEM images. Calculated and/or measured libraries of simulated images can be developed with this technique. The library concept will prove to be very useful in the determination of dimensional and other properties of simple structures, such as integrated circuit parts, where the shape of the features is preferably measured from a single top-down image or a line scan. This paper presents one approach to the generation of 2-D simulated images and presents some suggestions as to their application to critical dimension metrology.

Hyperpolarized 13C pyruvate mouse brain metabolism with absorptive-mode EPSI at 1 T

NASA Astrophysics Data System (ADS)

Miloushev, Vesselin Z.; Di Gialleonardo, Valentina; Salamanca-Cardona, Lucia; Correa, Fabian; Granlund, Kristin L.; Keshari, Kayvan R.

2017-02-01

The expected signal in echo-planar spectroscopic imaging experiments was explicitly modeled jointly in spatial and spectral dimensions. Using this as a basis, absorptive-mode type detection can be achieved by appropriate choice of spectral delays and post-processing techniques. We discuss the effects of gradient imperfections and demonstrate the implementation of this sequence at low field (1.05 T), with application to hyperpolarized [1-13C] pyruvate imaging of the mouse brain. The sequence achieves sufficient signal-to-noise to monitor the conversion of hyperpolarized [1-13C] pyruvate to lactate in the mouse brain. Hyperpolarized pyruvate imaging of mouse brain metabolism using an absorptive-mode EPSI sequence can be applied to more sophisticated murine disease and treatment models. The simple modifications presented in this work, which permit absorptive-mode detection, are directly translatable to human clinical imaging and generate improved absorptive-mode spectra without the need for refocusing pulses.

Transformations based on continuous piecewise-affine velocity fields

DOE PAGES

Freifeld, Oren; Hauberg, Soren; Batmanghelich, Kayhan; ...

2017-01-11

Here, we propose novel finite-dimensional spaces of well-behaved Rn → Rn transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volume preservation and/or boundary conditions), and supports convenient modeling choices such as smoothing priors and coarse-to-fine analysis. Importantly, the proposed approach, partly due to its rapid likelihood evaluations and partly due to its other properties, facilitates tractable inference over rich transformation spaces, including using Markov-Chain Monte-Carlo methods. Its applications include, but are not limited to: monotonic regression (more generally, optimization overmore » monotonic functions); modeling cumulative distribution functions or histograms; time-warping; image warping; image registration; real-time diffeomorphic image editing; data augmentation for image classifiers. Our GPU-based code is publicly available.« less

Transformations Based on Continuous Piecewise-Affine Velocity Fields

PubMed Central

Freifeld, Oren; Hauberg, Søren; Batmanghelich, Kayhan; Fisher, Jonn W.

2018-01-01

We propose novel finite-dimensional spaces of well-behaved ℝn → ℝn transformations. The latter are obtained by (fast and highly-accurate) integration of continuous piecewise-affine velocity fields. The proposed method is simple yet highly expressive, effortlessly handles optional constraints (e.g., volume preservation and/or boundary conditions), and supports convenient modeling choices such as smoothing priors and coarse-to-fine analysis. Importantly, the proposed approach, partly due to its rapid likelihood evaluations and partly due to its other properties, facilitates tractable inference over rich transformation spaces, including using Markov-Chain Monte-Carlo methods. Its applications include, but are not limited to: monotonic regression (more generally, optimization over monotonic functions); modeling cumulative distribution functions or histograms; time-warping; image warping; image registration; real-time diffeomorphic image editing; data augmentation for image classifiers. Our GPU-based code is publicly available. PMID:28092517

Accelerated Gaussian mixture model and its application on image segmentation

NASA Astrophysics Data System (ADS)

Zhao, Jianhui; Zhang, Yuanyuan; Ding, Yihua; Long, Chengjiang; Yuan, Zhiyong; Zhang, Dengyi

2013-03-01

Gaussian mixture model (GMM) has been widely used for image segmentation in recent years due to its superior adaptability and simplicity of implementation. However, traditional GMM has the disadvantage of high computational complexity. In this paper an accelerated GMM is designed, for which the following approaches are adopted: establish the lookup table for Gaussian probability matrix to avoid the repetitive probability calculations on all pixels, employ the blocking detection method on each block of pixels to further decrease the complexity, change the structure of lookup table from 3D to 1D with more simple data type to reduce the space requirement. The accelerated GMM is applied on image segmentation with the help of OTSU method to decide the threshold value automatically. Our algorithm has been tested through image segmenting of flames and faces from a set of real pictures, and the experimental results prove its efficiency in segmentation precision and computational cost.

Scattering Removal for Finger-Vein Image Restoration

PubMed Central

Yang, Jinfeng; Zhang, Ben; Shi, Yihua

2012-01-01

Finger-vein recognition has received increased attention recently. However, the finger-vein images are always captured in poor quality. This certainly makes finger-vein feature representation unreliable, and further impairs the accuracy of finger-vein recognition. In this paper, we first give an analysis of the intrinsic factors causing finger-vein image degradation, and then propose a simple but effective image restoration method based on scattering removal. To give a proper description of finger-vein image degradation, a biological optical model (BOM) specific to finger-vein imaging is proposed according to the principle of light propagation in biological tissues. Based on BOM, the light scattering component is sensibly estimated and properly removed for finger-vein image restoration. Finally, experimental results demonstrate that the proposed method is powerful in enhancing the finger-vein image contrast and in improving the finger-vein image matching accuracy. PMID:22737028

Simple spectroscope used with solid state image amplifier over wide spectral range

NASA Technical Reports Server (NTRS)

Brown, R. L., Sr.

1971-01-01

Prism plus image amplifier panel provides visual image of many infrared spectral lines from carbon arc impregnated with metal compound. Different metal compounds generate various desired spectra. Panel also aligns and focuses simple spectroscopes for detecting spectral lines inside and outside visible region.

Finite element model for MOI applications using A-V formulation

NASA Astrophysics Data System (ADS)

Xuan, L.; Shanker, B.; Udpa, L.; Shih, W.; Fitzpatrick, G.

2001-04-01

Magneto-optic imaging (MOI) is a relatively new sensor application of an extension of bubble memory technology to NDT and produce easy-to-interpret, real time analog images. MOI systems use a magneto-optic (MO) sensor to produce analog images of magnetic flux leakage from surface and subsurface defects. The instrument's capability in detecting the relatively weak magnetic fields associated with subsurface defects depends on the sensitivity of the magneto-optic sensor. The availability of a theoretical model that can simulate the MOI system performance is extremely important for optimization of the MOI sensor and hardware system. A nodal finite element model based on magnetic vector potential formulation has been developed for simulating MOI phenomenon. This model has been used for predicting the magnetic fields in simple test geometry with corrosion dome defects. In the case of test samples with multiple discontinuities, a more robust model using the magnetic vector potential Ā and electrical scalar potential V is required. In this paper, a finite element model based on A-V formulation is developed to model complex circumferential crack under aluminum rivets in dimpled countersink.

Classification of Large-Scale Remote Sensing Images for Automatic Identification of Health Hazards: Smoke Detection Using an Autologistic Regression Classifier.

PubMed

Wolters, Mark A; Dean, C B

2017-01-01

Remote sensing images from Earth-orbiting satellites are a potentially rich data source for monitoring and cataloguing atmospheric health hazards that cover large geographic regions. A method is proposed for classifying such images into hazard and nonhazard regions using the autologistic regression model, which may be viewed as a spatial extension of logistic regression. The method includes a novel and simple approach to parameter estimation that makes it well suited to handling the large and high-dimensional datasets arising from satellite-borne instruments. The methodology is demonstrated on both simulated images and a real application to the identification of forest fire smoke.

Optical turbulence on underwater image degradation in natural environments.

PubMed

Hou, Weilin; Woods, Sarah; Jarosz, Ewa; Goode, Wesley; Weidemann, Alan

2012-05-10

It is a well-known fact that the major degradation source on electro-optical imaging underwater is from scattering by particles of various origins and sizes. Recent research indicates that, under certain conditions, the apparent degradation could also be caused by the variations of index of refraction associated with temperature and salinity microstructures in the ocean and lakes. The combined impact has been modeled previously through the simple underwater imaging model. The current study presents the first attempts in quantifying the level of image degradation due to optical turbulence in natural waters in terms of modulation transfer functions using measured turbulence dissipation rates. Image data collected from natural environments during the Skaneateles Optical Turbulence Exercise are presented. Accurate assessments of the turbulence conditions are critical to the model validation and were measured by two instruments to ensure consistency and accuracy. Optical properties of the water column in the field were also measured in coordination with temperature, conductivity, and depth. The results show that optical turbulence degrades the image quality as predicted and on a level comparable to that caused by the particle scattering just above the thermocline. Other contributing elements involving model closure, including temporal and spatial measurement scale differences among sensors and mitigation efforts, are discussed.

Speckle interferometry of asteroids

NASA Technical Reports Server (NTRS)

Drummond, Jack

1988-01-01

By studying the image two-dimensional power spectra or autocorrelations projected by an asteroid as it rotates, it is possible to locate its rotational pole and derive its three axes dimensions through speckle interferometry under certain assumptions of uniform, geometric scattering, and triaxial ellipsoid shape. However, in cases where images can be reconstructed, the need for making the assumptions is obviated. Furthermore, the ultimate goal for speckle interferometry of image reconstruction will lead to mapping albedo features (if they exist) as impact areas or geological units. The first glimpses of the surface of an asteroid were obtained from images of 4 Vesta reconstructed from speckle interferometric observations. These images reveal that Vesta is quite Moon-like in having large hemispheric-scale albedo features. All of its lightcurves can be produced from a simple model developed from the images. Although undoubtedly more intricate than the model, Vesta's lightcurves can be matched by a model with three dark and four bright spots. The dark areas so dominate one hemisphere that a lightcurve minimum occurs when the maximum cross-section area is visible. The triaxial ellipsoid shape derived for Vesta is not consistent with the notion that the asteroid has an equilibrium shape in spite of its having apparently been differentiated.

Unsupervised change detection of multispectral images based on spatial constraint chi-squared transform and Markov random field model

NASA Astrophysics Data System (ADS)

Shi, Aiye; Wang, Chao; Shen, Shaohong; Huang, Fengchen; Ma, Zhenli

2016-10-01

Chi-squared transform (CST), as a statistical method, can describe the difference degree between vectors. The CST-based methods operate directly on information stored in the difference image and are simple and effective methods for detecting changes in remotely sensed images that have been registered and aligned. However, the technique does not take spatial information into consideration, which leads to much noise in the result of change detection. An improved unsupervised change detection method is proposed based on spatial constraint CST (SCCST) in combination with a Markov random field (MRF) model. First, the mean and variance matrix of the difference image of bitemporal images are estimated by an iterative trimming method. In each iteration, spatial information is injected to reduce scattered changed points (also known as "salt and pepper" noise). To determine the key parameter confidence level in the SCCST method, a pseudotraining dataset is constructed to estimate the optimal value. Then, the result of SCCST, as an initial solution of change detection, is further improved by the MRF model. The experiments on simulated and real multitemporal and multispectral images indicate that the proposed method performs well in comprehensive indices compared with other methods.

Least Median of Squares Filtering of Locally Optimal Point Matches for Compressible Flow Image Registration

PubMed Central

Castillo, Edward; Castillo, Richard; White, Benjamin; Rojo, Javier; Guerrero, Thomas

2012-01-01

Compressible flow based image registration operates under the assumption that the mass of the imaged material is conserved from one image to the next. Depending on how the mass conservation assumption is modeled, the performance of existing compressible flow methods is limited by factors such as image quality, noise, large magnitude voxel displacements, and computational requirements. The Least Median of Squares Filtered Compressible Flow (LFC) method introduced here is based on a localized, nonlinear least squares, compressible flow model that describes the displacement of a single voxel that lends itself to a simple grid search (block matching) optimization strategy. Spatially inaccurate grid search point matches, corresponding to erroneous local minimizers of the nonlinear compressible flow model, are removed by a novel filtering approach based on least median of squares fitting and the forward search outlier detection method. The spatial accuracy of the method is measured using ten thoracic CT image sets and large samples of expert determined landmarks (available at www.dir-lab.com). The LFC method produces an average error within the intra-observer error on eight of the ten cases, indicating that the method is capable of achieving a high spatial accuracy for thoracic CT registration. PMID:22797602

Semi-Automatic Building Models and FAÇADE Texture Mapping from Mobile Phone Images

NASA Astrophysics Data System (ADS)

Jeong, J.; Kim, T.

2016-06-01

Research on 3D urban modelling has been actively carried out for a long time. Recently the need of 3D urban modelling research is increased rapidly due to improved geo-web services and popularized smart devices. Nowadays 3D urban models provided by, for example, Google Earth use aerial photos for 3D urban modelling but there are some limitations: immediate update for the change of building models is difficult, many buildings are without 3D model and texture, and large resources for maintaining and updating are inevitable. To resolve the limitations mentioned above, we propose a method for semi-automatic building modelling and façade texture mapping from mobile phone images and analyze the result of modelling with actual measurements. Our method consists of camera geometry estimation step, image matching step, and façade mapping step. Models generated from this method were compared with actual measurement value of real buildings. Ratios of edge length of models and measurements were compared. Result showed 5.8% average error of length ratio. Through this method, we could generate a simple building model with fine façade textures without expensive dedicated tools and dataset.

Processing-optimised imaging of analog geological models by electrical capacitance tomography

NASA Astrophysics Data System (ADS)

Ortiz Alemán, C.; Espíndola-Carmona, A.; Hernández-Gómez, J. J.; Orozco Del Castillo, MG

2017-06-01

In this work, the electrical capacitance tomography (ECT) technique is applied in monitoring internal deformation of geological analog models, which are used to study structural deformation mechanisms, in particular for simulating migration and emplacement of allochtonous salt bodies. A rectangular ECT sensor was used for internal visualization of analog geologic deformation. The monitoring of analog models consists in the reconstruction of permittivity images from the capacitance measurements obtained by introducing the model inside the ECT sensor. A simulated annealing (SA) algorithm is used as a reconstruction method, and is optimized by taking full advantage of some special features in a linearized version of this inverse approach. As a second part of this work our SA image reconstruction algorithm is applied to synthetic models, where its performance is evaluated in comparison to other commonly used algorithms such as linear back-projection and iterative Landweber methods. Finally, the SA method is applied to visualise two simple geological analog models. Encouraging results were obtained in terms of the quality of the reconstructed images, as interfaces corresponding to main geological units in the analog model were clearly distinguishable in them. We found reliable results quite useful for real time non-invasive monitoring of internal deformation of analog geological models.

A Monte Carlo model for mean glandular dose evaluation in spot compression mammography.

PubMed

Sarno, Antonio; Dance, David R; van Engen, Ruben E; Young, Kenneth C; Russo, Paolo; Di Lillo, Francesca; Mettivier, Giovanni; Bliznakova, Kristina; Fei, Baowei; Sechopoulos, Ioannis

2017-07-01

To characterize the dependence of normalized glandular dose (DgN) on various breast model and image acquisition parameters during spot compression mammography and other partial breast irradiation conditions, and evaluate alternative previously proposed dose-related metrics for this breast imaging modality. Using Monte Carlo simulations with both simple homogeneous breast models and patient-specific breasts, three different dose-related metrics for spot compression mammography were compared: the standard DgN, the normalized glandular dose to only the directly irradiated portion of the breast (DgNv), and the DgN obtained by the product of the DgN for full field irradiation and the ratio of the mid-height area of the irradiated breast to the entire breast area (DgN M ). How these metrics vary with field-of-view size, spot area thickness, x-ray energy, spot area and position, breast shape and size, and system geometry was characterized for the simple breast model and a comparison of the simple model results to those with patient-specific breasts was also performed. The DgN in spot compression mammography can vary considerably with breast area. However, the difference in breast thickness between the spot compressed area and the uncompressed area does not introduce a variation in DgN. As long as the spot compressed area is completely within the breast area and only the compressed breast portion is directly irradiated, its position and size does not introduce a variation in DgN for the homogeneous breast model. As expected, DgN is lower than DgNv for all partial breast irradiation areas, especially when considering spot compression areas within the clinically used range. DgN M underestimates DgN by 6.7% for a W/Rh spectrum at 28 kVp and for a 9 × 9 cm 2 compression paddle. As part of the development of a new breast dosimetry model, a task undertaken by the American Association of Physicists in Medicine and the European Federation of Organizations of Medical Physics, these results provide insight on how DgN and two alternative dose metrics behave with various image acquisition and model parameters. © 2017 American Association of Physicists in Medicine.

Independent component model for cognitive functions of multiple subjects using [15O]H2O PET images.

PubMed

Park, Hae-Jeong; Kim, Jae-Jin; Youn, Tak; Lee, Dong Soo; Lee, Myung Chul; Kwon, Jun Soo

2003-04-01

An independent component model of multiple subjects' positron emission tomography (PET) images is proposed to explore the overall functional components involved in a task and to explain subject specific variations of metabolic activities under altered experimental conditions utilizing the Independent component analysis (ICA) concept. As PET images represent time-compressed activities of several cognitive components, we derived a mathematical model to decompose functional components from cross-sectional images based on two fundamental hypotheses: (1) all subjects share basic functional components that are common to subjects and spatially independent of each other in relation to the given experimental task, and (2) all subjects share common functional components throughout tasks which are also spatially independent. The variations of hemodynamic activities according to subjects or tasks can be explained by the variations in the usage weight of the functional components. We investigated the plausibility of the model using serial cognitive experiments of simple object perception, object recognition, two-back working memory, and divided attention of a syntactic process. We found that the independent component model satisfactorily explained the functional components involved in the task and discuss here the application of ICA in multiple subjects' PET images to explore the functional association of brain activations. Copyright 2003 Wiley-Liss, Inc.

A three-layer model of natural image statistics.

PubMed

Gutmann, Michael U; Hyvärinen, Aapo

2013-11-01

An important property of visual systems is to be simultaneously both selective to specific patterns found in the sensory input and invariant to possible variations. Selectivity and invariance (tolerance) are opposing requirements. It has been suggested that they could be joined by iterating a sequence of elementary selectivity and tolerance computations. It is, however, unknown what should be selected or tolerated at each level of the hierarchy. We approach this issue by learning the computations from natural images. We propose and estimate a probabilistic model of natural images that consists of three processing layers. Two natural image data sets are considered: image patches, and complete visual scenes downsampled to the size of small patches. For both data sets, we find that in the first two layers, simple and complex cell-like computations are performed. In the third layer, we mainly find selectivity to longer contours; for patch data, we further find some selectivity to texture, while for the downsampled complete scenes, some selectivity to curvature is observed. Copyright © 2013 Elsevier Ltd. All rights reserved.

A remote sensing computer-assisted learning tool developed using the unified modeling language

NASA Astrophysics Data System (ADS)

Friedrich, J.; Karslioglu, M. O.

The goal of this work has been to create an easy-to-use and simple-to-make learning tool for remote sensing at an introductory level. Many students struggle to comprehend what seems to be a very basic knowledge of digital images, image processing and image arithmetic, for example. Because professional programs are generally too complex and overwhelming for beginners and often not tailored to the specific needs of a course regarding functionality, a computer-assisted learning (CAL) program was developed based on the unified modeling language (UML), the present standard for object-oriented (OO) system development. A major advantage of this approach is an easier transition from modeling to coding of such an application, if modern UML tools are being used. After introducing the constructed UML model, its implementation is briefly described followed by a series of learning exercises. They illustrate how the resulting CAL tool supports students taking an introductory course in remote sensing at the author's institution.

Monte Carlo modeling of a conventional X-ray computed tomography scanner for gel dosimetry purposes.

PubMed

Hayati, Homa; Mesbahi, Asghar; Nazarpoor, Mahmood

2016-01-01

Our purpose in the current study was to model an X-ray CT scanner with the Monte Carlo (MC) method for gel dosimetry. In this study, a conventional CT scanner with one array detector was modeled with use of the MCNPX MC code. The MC calculated photon fluence in detector arrays was used for image reconstruction of a simple water phantom as well as polyacrylamide polymer gel (PAG) used for radiation therapy. Image reconstruction was performed with the filtered back-projection method with a Hann filter and the Spline interpolation method. Using MC results, we obtained the dose-response curve for images of irradiated gel at different absorbed doses. A spatial resolution of about 2 mm was found for our simulated MC model. The MC-based CT images of the PAG gel showed a reliable increase in the CT number with increasing absorbed dose for the studied gel. Also, our results showed that the current MC model of a CT scanner can be used for further studies on the parameters that influence the usability and reliability of results, such as the photon energy spectra and exposure techniques in X-ray CT gel dosimetry.

CMOS Active-Pixel Image Sensor With Simple Floating Gates

NASA Technical Reports Server (NTRS)

Fossum, Eric R.; Nakamura, Junichi; Kemeny, Sabrina E.

1996-01-01

Experimental complementary metal-oxide/semiconductor (CMOS) active-pixel image sensor integrated circuit features simple floating-gate structure, with metal-oxide/semiconductor field-effect transistor (MOSFET) as active circuit element in each pixel. Provides flexibility of readout modes, no kTC noise, and relatively simple structure suitable for high-density arrays. Features desirable for "smart sensor" applications.

A Simple Endoscopic Technique for Measuring the Cross-Sectional Area of the Upper Airway in a Rabbit Model.

PubMed

Wistermayer, Paul R; McIlwain, Wesley R; Ieronimakis, Nicholas; Rogers, Derek J

2018-04-01

Validate an accurate and reproducible method of measuring the cross-sectional area (CSA) of the upper airway. This is a prospective animal study done at a tertiary care medical treatment facility. Control images were obtained using endotracheal tubes of varying sizes. In vivo images were obtained from various timepoints of a concurrent study on subglottic stenosis. Using a 0° rod telescope, an instrument was placed at the level of interest, and a photo was obtained. Three independent and blinded raters then measured the CSA of the narrowest portion of the airway using open source image analysis software. Each blinded rater measured the CSA of 79 photos. The t testing to assess for accuracy showed no difference between measured and known CSAs of the control images ( P = .86), with an average error of 1.5% (SD = 5.5%). All intraclass correlation (ICC) values for intrarater agreement showed excellent agreement (ICC > .75). Interrater reliability among all raters in control (ICC = .975; 95% CI, .817-.995) and in vivo (ICC = .846;, 95% CI, .780-.896) images showed excellent agreement. We validate a simple, accurate, and reproducible method of measuring the CSA of the airway that can be used in a clinical or research setting.

Predicting location of recurrence using FDG, FLT, and Cu-ATSM PET in canine sinonasal tumors treated with radiotherapy

NASA Astrophysics Data System (ADS)

Bradshaw, Tyler; Fu, Rau; Bowen, Stephen; Zhu, Jun; Forrest, Lisa; Jeraj, Robert

2015-07-01

Dose painting relies on the ability of functional imaging to identify resistant tumor subvolumes to be targeted for additional boosting. This work assessed the ability of FDG, FLT, and Cu-ATSM PET imaging to predict the locations of residual FDG PET in canine tumors following radiotherapy. Nineteen canines with spontaneous sinonasal tumors underwent PET/CT imaging with radiotracers FDG, FLT, and Cu-ATSM prior to hypofractionated radiotherapy. Therapy consisted of 10 fractions of 4.2 Gy to the sinonasal cavity with or without an integrated boost of 0.8 Gy to the GTV. Patients had an additional FLT PET/CT scan after fraction 2, a Cu-ATSM PET/CT scan after fraction 3, and follow-up FDG PET/CT scans after radiotherapy. Following image registration, simple and multiple linear and logistic voxel regressions were performed to assess how well pre- and mid-treatment PET imaging predicted post-treatment FDG uptake. R2 and pseudo R2 were used to assess the goodness of fits. For simple linear regression models, regression coefficients for all pre- and mid-treatment PET images were significantly positive across the population (P < 0.05). However, there was large variability among patients in goodness of fits: R2 ranged from 0.00 to 0.85, with a median of 0.12. Results for logistic regression models were similar. Multiple linear regression models resulted in better fits (median R2 = 0.31), but there was still large variability between patients in R2. The R2 from regression models for different predictor variables were highly correlated across patients (R ≈ 0.8), indicating tumors that were poorly predicted with one tracer were also poorly predicted by other tracers. In conclusion, the high inter-patient variability in goodness of fits indicates that PET was able to predict locations of residual tumor in some patients, but not others. This suggests not all patients would be good candidates for dose painting based on a single biological target.

Predicting location of recurrence using FDG, FLT, and Cu-ATSM PET in canine sinonasal tumors treated with radiotherapy.

PubMed

Bradshaw, Tyler; Fu, Rau; Bowen, Stephen; Zhu, Jun; Forrest, Lisa; Jeraj, Robert

2015-07-07

Dose painting relies on the ability of functional imaging to identify resistant tumor subvolumes to be targeted for additional boosting. This work assessed the ability of FDG, FLT, and Cu-ATSM PET imaging to predict the locations of residual FDG PET in canine tumors following radiotherapy. Nineteen canines with spontaneous sinonasal tumors underwent PET/CT imaging with radiotracers FDG, FLT, and Cu-ATSM prior to hypofractionated radiotherapy. Therapy consisted of 10 fractions of 4.2 Gy to the sinonasal cavity with or without an integrated boost of 0.8 Gy to the GTV. Patients had an additional FLT PET/CT scan after fraction 2, a Cu-ATSM PET/CT scan after fraction 3, and follow-up FDG PET/CT scans after radiotherapy. Following image registration, simple and multiple linear and logistic voxel regressions were performed to assess how well pre- and mid-treatment PET imaging predicted post-treatment FDG uptake. R(2) and pseudo R(2) were used to assess the goodness of fits. For simple linear regression models, regression coefficients for all pre- and mid-treatment PET images were significantly positive across the population (P < 0.05). However, there was large variability among patients in goodness of fits: R(2) ranged from 0.00 to 0.85, with a median of 0.12. Results for logistic regression models were similar. Multiple linear regression models resulted in better fits (median R(2) = 0.31), but there was still large variability between patients in R(2). The R(2) from regression models for different predictor variables were highly correlated across patients (R ≈ 0.8), indicating tumors that were poorly predicted with one tracer were also poorly predicted by other tracers. In conclusion, the high inter-patient variability in goodness of fits indicates that PET was able to predict locations of residual tumor in some patients, but not others. This suggests not all patients would be good candidates for dose painting based on a single biological target.

Efficient Workflows for Curation of Heterogeneous Data Supporting Modeling of U-Nb Alloy Aging

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

Ward, Logan Timothy; Hackenberg, Robert Errol

These are slides from a presentation summarizing a graduate research associate's summer project. The following topics are covered in these slides: data challenges in materials, aging in U-Nb Alloys, Building an Aging Model, Different Phase Trans. in U-Nb, the Challenge, Storing Materials Data, Example Data Source, Organizing Data: What is a Schema?, What does a "XML Schema" look like?, Our Data Schema: Nice and Simple, Storing Data: Materials Data Curation System (MDCS), Problem with MDCS: Slow Data Entry, Getting Literature into MDCS, Staging Data in Excel Document, Final Result: MDCS Records, Analyzing Image Data, Process for Making TTT Diagram, Bottleneckmore » Number 1: Image Analysis, Fitting a TTP Boundary, Fitting a TTP Curve: Comparable Results, How Does it Compare to Our Data?, Image Analysis Workflow, Curating Hardness Records, Hardness Data: Two Key Decisions, Before Peak Age? - Automation, Interactive Viz, Which Transformation?, Microstructure-Informed Model, Tracking the Entire Process, General Problem with Property Models, Pinyon: Toolkit for Managing Model Creation, Tracking Individual Decisions, Jupyter: Docs and Code in One File, Hardness Analysis Workflow, Workflow for Aging Models, and conclusions.« less

Combined self-learning based single-image super-resolution and dual-tree complex wavelet transform denoising for medical images

NASA Astrophysics Data System (ADS)

Yang, Guang; Ye, Xujiong; Slabaugh, Greg; Keegan, Jennifer; Mohiaddin, Raad; Firmin, David

2016-03-01

In this paper, we propose a novel self-learning based single-image super-resolution (SR) method, which is coupled with dual-tree complex wavelet transform (DTCWT) based denoising to better recover high-resolution (HR) medical images. Unlike previous methods, this self-learning based SR approach enables us to reconstruct HR medical images from a single low-resolution (LR) image without extra training on HR image datasets in advance. The relationships between the given image and its scaled down versions are modeled using support vector regression with sparse coding and dictionary learning, without explicitly assuming reoccurrence or self-similarity across image scales. In addition, we perform DTCWT based denoising to initialize the HR images at each scale instead of simple bicubic interpolation. We evaluate our method on a variety of medical images. Both quantitative and qualitative results show that the proposed approach outperforms bicubic interpolation and state-of-the-art single-image SR methods while effectively removing noise.

Evaluation of image features and classification methods for Barrett's cancer detection using VLE imaging

NASA Astrophysics Data System (ADS)

Klomp, Sander; van der Sommen, Fons; Swager, Anne-Fré; Zinger, Svitlana; Schoon, Erik J.; Curvers, Wouter L.; Bergman, Jacques J.; de With, Peter H. N.

2017-03-01

Volumetric Laser Endomicroscopy (VLE) is a promising technique for the detection of early neoplasia in Barrett's Esophagus (BE). VLE generates hundreds of high resolution, grayscale, cross-sectional images of the esophagus. However, at present, classifying these images is a time consuming and cumbersome effort performed by an expert using a clinical prediction model. This paper explores the feasibility of using computer vision techniques to accurately predict the presence of dysplastic tissue in VLE BE images. Our contribution is threefold. First, a benchmarking is performed for widely applied machine learning techniques and feature extraction methods. Second, three new features based on the clinical detection model are proposed, having superior classification accuracy and speed, compared to earlier work. Third, we evaluate automated parameter tuning by applying simple grid search and feature selection methods. The results are evaluated on a clinically validated dataset of 30 dysplastic and 30 non-dysplastic VLE images. Optimal classification accuracy is obtained by applying a support vector machine and using our modified Haralick features and optimal image cropping, obtaining an area under the receiver operating characteristic of 0.95 compared to the clinical prediction model at 0.81. Optimal execution time is achieved using a proposed mean and median feature, which is extracted at least factor 2.5 faster than alternative features with comparable performance.

a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

NASA Astrophysics Data System (ADS)

Haigang, Sui; Zhina, Song

2016-06-01

Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

Investigating an Aerial Image First

ERIC Educational Resources Information Center

Wyrembeck, Edward P.; Elmer, Jeffrey S.

2006-01-01

Most introductory optics lab activities begin with students locating the real image formed by a converging lens. The method is simple and straightforward--students move a screen back and forth until the real image is in sharp focus on the screen. Students then draw a simple ray diagram to explain the observation using only two or three special…

Complex Geometric Models of Diffusion and Relaxation in Healthy and Damaged White Matter

PubMed Central

Farrell, Jonathan A.D.; Smith, Seth A.; Reich, Daniel S.; Calabresi, Peter A.; van Zijl, Peter C.M.

2010-01-01

Which aspects of tissue microstructure affect diffusion weighted MRI signals? Prior models, many of which use Monte-Carlo simulations, have focused on relatively simple models of the cellular microenvironment and have not considered important anatomic details. With the advent of higher-order analysis models for diffusion imaging, such as high-angular-resolution diffusion imaging (HARDI), more realistic models are necessary. This paper presents and evaluates the reproducibility of simulations of diffusion in complex geometries. Our framework is quantitative, does not require specialized hardware, is easily implemented with little programming experience, and is freely available as open-source software. Models may include compartments with different diffusivities, permeabilities, and T2 time constants using both parametric (e.g., spheres and cylinders) and arbitrary (e.g., mesh-based) geometries. Three-dimensional diffusion displacement-probability functions are mapped with high reproducibility, and thus can be readily used to assess reproducibility of diffusion-derived contrasts. PMID:19739233

Generic distortion model for metrology under optical microscopes

NASA Astrophysics Data System (ADS)

Liu, Xingjian; Li, Zhongwei; Zhong, Kai; Chao, YuhJin; Miraldo, Pedro; Shi, Yusheng

2018-04-01

For metrology under optical microscopes, lens distortion is the dominant source of error. Previous distortion models and correction methods mostly rely on the assumption that parametric distortion models require a priori knowledge of the microscopes' lens systems. However, because of the numerous optical elements in a microscope, distortions can be hardly represented by a simple parametric model. In this paper, a generic distortion model considering both symmetric and asymmetric distortions is developed. Such a model is obtained by using radial basis functions (RBFs) to interpolate the radius and distortion values of symmetric distortions (image coordinates and distortion rays for asymmetric distortions). An accurate and easy to implement distortion correction method is presented. With the proposed approach, quantitative measurement with better accuracy can be achieved, such as in Digital Image Correlation for deformation measurement when used with an optical microscope. The proposed technique is verified by both synthetic and real data experiments.

Horizon Brightness Revisited: Measurements and a Model of Clear-Sky Radiances

DTIC Science & Technology

1994-07-20

Clear daytime skies persistently display a subtle local maximum of radiance near the astronomical horizon. Spectroradiometry and digital image analysis confirm this maximum’s reality, and they show that its angular width and elevation vary with solar elevation, azimuth relative to the Sun, and aerosol optical depth. Many existing models of atmospheric scattering do not generate this near-horizon radiance maximum, but a simple second-order scattering model does, and it reproduces many of the maximum’s details.

Radiotherapy volume delineation using dynamic [18F]-FDG PET/CT imaging in patients with oropharyngeal cancer: a pilot study.

PubMed

Silvoniemi, Antti; Din, Mueez U; Suilamo, Sami; Shepherd, Tony; Minn, Heikki

2016-11-01

Delineation of gross tumour volume in 3D is a critical step in the radiotherapy (RT) treatment planning for oropharyngeal cancer (OPC). Static [ 18 F]-FDG PET/CT imaging has been suggested as a method to improve the reproducibility of tumour delineation, but it suffers from low specificity. We undertook this pilot study in which dynamic features in time-activity curves (TACs) of [ 18 F]-FDG PET/CT images were applied to help the discrimination of tumour from inflammation and adjacent normal tissue. Five patients with OPC underwent dynamic [ 18 F]-FDG PET/CT imaging in treatment position. Voxel-by-voxel analysis was performed to evaluate seven dynamic features developed with the knowledge of differences in glucose metabolism in different tissue types and visual inspection of TACs. The Gaussian mixture model and K-means algorithms were used to evaluate the performance of the dynamic features in discriminating tumour voxels compared to the performance of standardized uptake values obtained from static imaging. Some dynamic features showed a trend towards discrimination of different metabolic areas but lack of consistency means that clinical application is not recommended based on these results alone. Impact of inflammatory tissue remains a problem for volume delineation in RT of OPC, but a simple dynamic imaging protocol proved practicable and enabled simple data analysis techniques that show promise for complementing the information in static uptake values.

Patch-Based Generative Shape Model and MDL Model Selection for Statistical Analysis of Archipelagos

NASA Astrophysics Data System (ADS)

Ganz, Melanie; Nielsen, Mads; Brandt, Sami

We propose a statistical generative shape model for archipelago-like structures. These kind of structures occur, for instance, in medical images, where our intention is to model the appearance and shapes of calcifications in x-ray radio graphs. The generative model is constructed by (1) learning a patch-based dictionary for possible shapes, (2) building up a time-homogeneous Markov model to model the neighbourhood correlations between the patches, and (3) automatic selection of the model complexity by the minimum description length principle. The generative shape model is proposed as a probability distribution of a binary image where the model is intended to facilitate sequential simulation. Our results show that a relatively simple model is able to generate structures visually similar to calcifications. Furthermore, we used the shape model as a shape prior in the statistical segmentation of calcifications, where the area overlap with the ground truth shapes improved significantly compared to the case where the prior was not used.

Photometric detection of high proper motions in dense stellar fields using difference image analysis

NASA Astrophysics Data System (ADS)

Eyer, L.; Woźniak, P. R.

2001-10-01

The difference image analysis (DIA) of the images obtained by the Optical Gravitational Lensing Experiment (OGLE-II) revealed a peculiar artefact in the sample of stars proposed as variable by Woźniak in one of the Galactic bulge fields: the occurrence of pairs of candidate variables showing anti-correlated light curves monotonic over a period of 3yr. This effect can be understood, quantified and related to the stellar proper motions. DIA photometry supplemented with a simple model offers an effective and easy way to detect high proper motion stars in very dense stellar fields, where conventional astrometric searches are extremely inefficient.

Upper bound on the efficiency of certain nonimaging concentrators in the physical-optics model

NASA Astrophysics Data System (ADS)

Welford, W. T.; Winston, R.

1982-09-01

Upper bounds on the performance of nonimaging concentrators are obtained within the framework of scalar-wave theory by using a simple approach to avoid complex calculations on multiple phase fronts. The approach consists in treating a theoretically perfect image-forming device and postulating that no non-image-forming concentrator can have a better performance than such an ideal image-forming system. The performance of such a system can be calculated according to wave theory, and this will provide, in accordance with the postulate, upper bounds on the performance of nonimaging systems. The method is demonstrated for a two-dimensional compound parabolic concentrator.

The "Best Worst" Field Optimization and Focusing

NASA Technical Reports Server (NTRS)

Vaughnn, David; Moore, Ken; Bock, Noah; Zhou, Wei; Ming, Liang; Wilson, Mark

2008-01-01

A simple algorithm for optimizing and focusing lens designs is presented. The goal of the algorithm is to simultaneously create the best and most uniform image quality over the field of view. Rather than relatively weighting multiple field points, only the image quality from the worst field point is considered. When optimizing a lens design, iterations are made to make this worst field point better until such a time as a different field point becomes worse. The same technique is used to determine focus position. The algorithm works with all the various image quality metrics. It works with both symmetrical and asymmetrical systems. It works with theoretical models and real hardware.

On estimation of secret message length in LSB steganography in spatial domain

NASA Astrophysics Data System (ADS)

Fridrich, Jessica; Goljan, Miroslav

2004-06-01

In this paper, we present a new method for estimating the secret message length of bit-streams embedded using the Least Significant Bit embedding (LSB) at random pixel positions. We introduce the concept of a weighted stego image and then formulate the problem of determining the unknown message length as a simple optimization problem. The methodology is further refined to obtain more stable and accurate results for a wide spectrum of natural images. One of the advantages of the new method is its modular structure and a clean mathematical derivation that enables elegant estimator accuracy analysis using statistical image models.

A Model-Based Approach for Microvasculature Structure Distortion Correction in Two-Photon Fluorescence Microscopy Images

PubMed Central

Dao, Lam; Glancy, Brian; Lucotte, Bertrand; Chang, Lin-Ching; Balaban, Robert S; Hsu, Li-Yueh

2015-01-01

SUMMARY This paper investigates a post-processing approach to correct spatial distortion in two-photon fluorescence microscopy images for vascular network reconstruction. It is aimed at in vivo imaging of large field-of-view, deep-tissue studies of vascular structures. Based on simple geometric modeling of the object-of-interest, a distortion function is directly estimated from the image volume by deconvolution analysis. Such distortion function is then applied to sub volumes of the image stack to adaptively adjust for spatially varying distortion and reduce the image blurring through blind deconvolution. The proposed technique was first evaluated in phantom imaging of fluorescent microspheres that are comparable in size to the underlying capillary vascular structures. The effectiveness of restoring three-dimensional spherical geometry of the microspheres using the estimated distortion function was compared with empirically measured point-spread function. Next, the proposed approach was applied to in vivo vascular imaging of mouse skeletal muscle to reduce the image distortion of the capillary structures. We show that the proposed method effectively improve the image quality and reduce spatially varying distortion that occurs in large field-of-view deep-tissue vascular dataset. The proposed method will help in qualitative interpretation and quantitative analysis of vascular structures from fluorescence microscopy images. PMID:26224257

Evaluation of the MTF for a-Si:H imaging arrays

NASA Astrophysics Data System (ADS)

Yorkston, John; Antonuk, Larry E.; Seraji, N.; Huang, Weidong; Siewerdsen, Jeffrey H.; El-Mohri, Youcef

1994-05-01

Hydrogenated amorphous silicon imaging arrays are being developed for numerous applications in medical imaging. Diagnostic and megavoltage images have previously been reported and a number of the intrinsic properties of the arrays have been investigated. This paper reports on the first attempt to characterize the intrinsic spatial resolution of the imaging pixels on a 450 micrometers pitch, n-i-p imaging array fabricated at Xerox P.A.R.C. The pre- sampled modulation transfer function was measured by scanning a approximately 25 micrometers wide slit of visible wavelength light across a pixel in both the DATA and FET directions. The results show that the response of the pixel in these orthogonal directions is well described by a simple model that accounts for asymmetries in the pixel response due to geometric aspects of the pixel design.

Maximizing fluorescence collection efficiency in multiphoton microscopy

PubMed Central

Zinter, Joseph P.; Levene, Michael J.

2011-01-01

Understanding fluorescence propagation through a multiphoton microscope is of critical importance in designing high performance systems capable of deep tissue imaging. Optical models of a scattering tissue sample and the Olympus 20X 0.95NA microscope objective were used to simulate fluorescence propagation as a function of imaging depth for physiologically relevant scattering parameters. The spatio-angular distribution of fluorescence at the objective back aperture derived from these simulations was used to design a simple, maximally efficient post-objective fluorescence collection system. Monte Carlo simulations corroborated by data from experimental tissue phantoms demonstrate collection efficiency improvements of 50% – 90% over conventional, non-optimized fluorescence collection geometries at large imaging depths. Imaging performance was verified by imaging layer V neurons in mouse cortex to a depth of 850 μm. PMID:21934897

DAVIS: A direct algorithm for velocity-map imaging system

NASA Astrophysics Data System (ADS)

Harrison, G. R.; Vaughan, J. C.; Hidle, B.; Laurent, G. M.

2018-05-01

In this work, we report a direct (non-iterative) algorithm to reconstruct the three-dimensional (3D) momentum-space picture of any charged particles collected with a velocity-map imaging system from the two-dimensional (2D) projected image captured by a position-sensitive detector. The method consists of fitting the measured image with the 2D projection of a model 3D velocity distribution defined by the physics of the light-matter interaction. The meaningful angle-correlated information is first extracted from the raw data by expanding the image with a complete set of Legendre polynomials. Both the particle's angular and energy distributions are then directly retrieved from the expansion coefficients. The algorithm is simple, easy to implement, fast, and explicitly takes into account the pixelization effect in the measurement.

On an image reconstruction method for ECT

NASA Astrophysics Data System (ADS)

Sasamoto, Akira; Suzuki, Takayuki; Nishimura, Yoshihiro

2007-04-01

An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that a very simple relationship between measured data and source were described by a convolution of response function and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method, Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its validity to holes and line flaw have been shown by many results that much finer image than original image have been reconstructed.

A joint source-channel distortion model for JPEG compressed images.

PubMed

Sabir, Muhammad F; Sheikh, Hamid Rahim; Heath, Robert W; Bovik, Alan C

2006-06-01

The need for efficient joint source-channel coding (JSCC) is growing as new multimedia services are introduced in commercial wireless communication systems. An important component of practical JSCC schemes is a distortion model that can predict the quality of compressed digital multimedia such as images and videos. The usual approach in the JSCC literature for quantifying the distortion due to quantization and channel errors is to estimate it for each image using the statistics of the image for a given signal-to-noise ratio (SNR). This is not an efficient approach in the design of real-time systems because of the computational complexity. A more useful and practical approach would be to design JSCC techniques that minimize average distortion for a large set of images based on some distortion model rather than carrying out per-image optimizations. However, models for estimating average distortion due to quantization and channel bit errors in a combined fashion for a large set of images are not available for practical image or video coding standards employing entropy coding and differential coding. This paper presents a statistical model for estimating the distortion introduced in progressive JPEG compressed images due to quantization and channel bit errors in a joint manner. Statistical modeling of important compression techniques such as Huffman coding, differential pulse-coding modulation, and run-length coding are included in the model. Examples show that the distortion in terms of peak signal-to-noise ratio (PSNR) can be predicted within a 2-dB maximum error over a variety of compression ratios and bit-error rates. To illustrate the utility of the proposed model, we present an unequal power allocation scheme as a simple application of our model. Results show that it gives a PSNR gain of around 6.5 dB at low SNRs, as compared to equal power allocation.

Image based method for aberration measurement of lithographic tools

NASA Astrophysics Data System (ADS)

Xu, Shuang; Tao, Bo; Guo, Yongxing; Li, Gongfa

2018-01-01

Information of lens aberration of lithographic tools is important as it directly affects the intensity distribution in the image plane. Zernike polynomials are commonly used for a mathematical description of lens aberrations. Due to the advantage of lower cost and easier implementation of tools, image based measurement techniques have been widely used. Lithographic tools are typically partially coherent systems that can be described by a bilinear model, which entails time consuming calculations and does not lend a simple and intuitive relationship between lens aberrations and the resulted images. Previous methods for retrieving lens aberrations in such partially coherent systems involve through-focus image measurements and time-consuming iterative algorithms. In this work, we propose a method for aberration measurement in lithographic tools, which only requires measuring two images of intensity distribution. Two linear formulations are derived in matrix forms that directly relate the measured images to the unknown Zernike coefficients. Consequently, an efficient non-iterative solution is obtained.

Ultra Wideband Wireless Body Area Network for Medical Applications

DTIC Science & Technology

2010-04-01

gastrointestinal tract. They originally were devised to transmit still images of the digestive tract for subsequent diagnosis and detection of gastrointestinal...considered nondispersive and the skin layer is omitted. As depicted in Figure 6, the model is a semicylinder centred at the origin with radius br . All...Medical Applications RTO-MP-HFM-182 42 - 11 z x y Tumour Fat Skin Chest Figure 8: A Simple Hemispherical Brest Model. Table 2

Levels of detail analysis of microwave scattering from human head models for brain stroke detection

PubMed Central

2017-01-01

In this paper, we have presented a microwave scattering analysis from multiple human head models. This study incorporates different levels of detail in the human head models and its effect on microwave scattering phenomenon. Two levels of detail are taken into account; (i) Simplified ellipse shaped head model (ii) Anatomically realistic head model, implemented using 2-D geometry. In addition, heterogenic and frequency-dispersive behavior of the brain tissues has also been incorporated in our head models. It is identified during this study that the microwave scattering phenomenon changes significantly once the complexity of head model is increased by incorporating more details using magnetic resonance imaging database. It is also found out that the microwave scattering results match in both types of head model (i.e., geometrically simple and anatomically realistic), once the measurements are made in the structurally simplified regions. However, the results diverge considerably in the complex areas of brain due to the arbitrary shape interface of tissue layers in the anatomically realistic head model. After incorporating various levels of detail, the solution of subject microwave scattering problem and the measurement of transmitted and backscattered signals were obtained using finite element method. Mesh convergence analysis was also performed to achieve error free results with a minimum number of mesh elements and a lesser degree of freedom in the fast computational time. The results were promising and the E-Field values converged for both simple and complex geometrical models. However, the E-Field difference between both types of head model at the same reference point differentiated a lot in terms of magnitude. At complex location, a high difference value of 0.04236 V/m was measured compared to the simple location, where it turned out to be 0.00197 V/m. This study also contributes to provide a comparison analysis between the direct and iterative solvers so as to find out the solution of subject microwave scattering problem in a minimum computational time along with memory resources requirement. It is seen from this study that the microwave imaging may effectively be utilized for the detection, localization and differentiation of different types of brain stroke. The simulation results verified that the microwave imaging can be efficiently exploited to study the significant contrast between electric field values of the normal and abnormal brain tissues for the investigation of brain anomalies. In the end, a specific absorption rate analysis was carried out to compare the ionizing effects of microwave signals to different types of head model using a factor of safety for brain tissues. It is also suggested after careful study of various inversion methods in practice for microwave head imaging, that the contrast source inversion method may be more suitable and computationally efficient for such problems. PMID:29177115

Imaging latex–carbon nanotube composites by subsurface electrostatic force microscopy

DOE PAGES

Patel, Sajan; Petty, Clayton W.; Krafcik, Karen Lee; ...

2016-09-08

Electrostatic modes of atomic force microscopy have shown to be non-destructive and relatively simple methods for imaging conductors embedded in insulating polymers. Here we use electrostatic force microscopy to image the dispersion of carbon nanotubes in a latex-based conductive composite, which brings forth features not observed in previously studied systems employing linear polymer films. A fixed-potential model of the probe-nanotube electrostatics is presented which in principle gives access to the conductive nanoparticle's depth and radius, and the polymer film dielectric constant. Comparing this model to the data results in nanotube depths that appear to be slightly above the film–air interface.more » Furthermore, this result suggests that water-mediated charge build-up at the film–air interface may be the source of electrostatic phase contrast in ambient conditions.« less

Mathematical analysis of the 1D model and reconstruction schemes for magnetic particle imaging

NASA Astrophysics Data System (ADS)

Erb, W.; Weinmann, A.; Ahlborg, M.; Brandt, C.; Bringout, G.; Buzug, T. M.; Frikel, J.; Kaethner, C.; Knopp, T.; März, T.; Möddel, M.; Storath, M.; Weber, A.

2018-05-01

Magnetic particle imaging (MPI) is a promising new in vivo medical imaging modality in which distributions of super-paramagnetic nanoparticles are tracked based on their response in an applied magnetic field. In this paper we provide a mathematical analysis of the modeled MPI operator in the univariate situation. We provide a Hilbert space setup, in which the MPI operator is decomposed into simple building blocks and in which these building blocks are analyzed with respect to their mathematical properties. In turn, we obtain an analysis of the MPI forward operator and, in particular, of its ill-posedness properties. We further get that the singular values of the MPI core operator decrease exponentially. We complement our analytic results by some numerical studies which, in particular, suggest a rapid decay of the singular values of the MPI operator.

Acoustic backscatter models of fish: Gradual or punctuated evolution

NASA Astrophysics Data System (ADS)

Horne, John K.

2004-05-01

Sound-scattering characteristics of aquatic organisms are routinely investigated using theoretical and numerical models. Development of the inverse approach by van Holliday and colleagues in the 1970s catalyzed the development and validation of backscatter models for fish and zooplankton. As the understanding of biological scattering properties increased, so did the number and computational sophistication of backscatter models. The complexity of data used to represent modeled organisms has also evolved in parallel to model development. Simple geometric shapes representing body components or the whole organism have been replaced by anatomically accurate representations derived from imaging sensors such as computer-aided tomography (CAT) scans. In contrast, Medwin and Clay (1998) recommend that fish and zooplankton should be described by simple theories and models, without acoustically superfluous extensions. Since van Holliday's early work, how has data and computational complexity influenced accuracy and precision of model predictions? How has the understanding of aquatic organism scattering properties increased? Significant steps in the history of model development will be identified and changes in model results will be characterized and compared. [Work supported by ONR and the Alaska Fisheries Science Center.

Cover estimation and payload location using Markov random fields

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2014-02-01

Payload location is an approach to find the message bits hidden in steganographic images, but not necessarily their logical order. Its success relies primarily on the accuracy of the underlying cover estimators and can be improved if more estimators are used. This paper presents an approach based on Markov random field to estimate the cover image given a stego image. It uses pairwise constraints to capture the natural two-dimensional statistics of cover images and forms a basis for more sophisticated models. Experimental results show that it is competitive against current state-of-the-art estimators and can locate payload embedded by simple LSB steganography and group-parity steganography. Furthermore, when combined with existing estimators, payload location accuracy improves significantly.

Experimental validation of a linear model for data reduction in chirp-pulse microwave CT.

PubMed

Miyakawa, M; Orikasa, K; Bertero, M; Boccacci, P; Conte, F; Piana, M

2002-04-01

Chirp-pulse microwave computerized tomography (CP-MCT) is an imaging modality developed at the Department of Biocybernetics, University of Niigata (Niigata, Japan), which intends to reduce the microwave-tomography problem to an X-ray-like situation. We have recently shown that data acquisition in CP-MCT can be described in terms of a linear model derived from scattering theory. In this paper, we validate this model by showing that the theoretically computed response function is in good agreement with the one obtained from a regularized multiple deconvolution of three data sets measured with the prototype of CP-MCT. Furthermore, the reliability of the model as far as image restoration in concerned, is tested in the case of space-invariant conditions by considering the reconstruction of simple on-axis cylindrical phantoms.

Graph cuts for curvature based image denoising.

PubMed

Bae, Egil; Shi, Juan; Tai, Xue-Cheng

2011-05-01

Minimization of total variation (TV) is a well-known method for image denoising. Recently, the relationship between TV minimization problems and binary MRF models has been much explored. This has resulted in some very efficient combinatorial optimization algorithms for the TV minimization problem in the discrete setting via graph cuts. To overcome limitations, such as staircasing effects, of the relatively simple TV model, variational models based upon higher order derivatives have been proposed. The Euler's elastica model is one such higher order model of central importance, which minimizes the curvature of all level lines in the image. Traditional numerical methods for minimizing the energy in such higher order models are complicated and computationally complex. In this paper, we will present an efficient minimization algorithm based upon graph cuts for minimizing the energy in the Euler's elastica model, by simplifying the problem to that of solving a sequence of easy graph representable problems. This sequence has connections to the gradient flow of the energy function, and converges to a minimum point. The numerical experiments show that our new approach is more effective in maintaining smooth visual results while preserving sharp features better than TV models.

Webcam classification using simple features

NASA Astrophysics Data System (ADS)

Pramoun, Thitiporn; Choe, Jeehyun; Li, He; Chen, Qingshuang; Amornraksa, Thumrongrat; Lu, Yung-Hsiang; Delp, Edward J.

2015-03-01

Thousands of sensors are connected to the Internet and many of these sensors are cameras. The "Internet of Things" will contain many "things" that are image sensors. This vast network of distributed cameras (i.e. web cams) will continue to exponentially grow. In this paper we examine simple methods to classify an image from a web cam as "indoor/outdoor" and having "people/no people" based on simple features. We use four types of image features to classify an image as indoor/outdoor: color, edge, line, and text. To classify an image as having people/no people we use HOG and texture features. The features are weighted based on their significance and combined. A support vector machine is used for classification. Our system with feature weighting and feature combination yields 95.5% accuracy.

Achilles tendons from decorin- and biglycan-null mouse models have inferior mechanical and structural properties predicted by an image-based empirical damage model

PubMed Central

Gordon, J.A.; Freedman, B.R.; Zuskov, A.; Iozzo, R.V.; Birk, D.E.; Soslowsky, L.J.

2015-01-01

Achilles tendons are a common source of pain and injury, and their pathology may originate from aberrant structure function relationships. Small leucine rich proteoglycans (SLRPs) influence mechanical and structural properties in a tendon-specific manner. However, their roles in the Achilles tendon have not been defined. The objective of this study was to evaluate the mechanical and structural differences observed in mouse Achilles tendons lacking class I SLRPs; either decorin or biglycan. In addition, empirical modeling techniques based on mechanical and image-based measures were employed. Achilles tendons from decorin-null (Dcn−/−) and biglycan-null (Bgn−/−) C57BL/6 female mice (N=102) were used. Each tendon underwent a dynamic mechanical testing protocol including simultaneous polarized light image capture to evaluate both structural and mechanical properties of each Achilles tendon. An empirical damage model was adapted for application to genetic variation and for use with image based structural properties to predict tendon dynamic mechanical properties. We found that Achilles tendons lacking decorin and biglycan had inferior mechanical and structural properties that were age dependent; and that simple empirical models, based on previously described damage models, were predictive of Achilles tendon dynamic modulus in both decorin- and biglycan-null mice. PMID:25888014

Achilles tendons from decorin- and biglycan-null mouse models have inferior mechanical and structural properties predicted by an image-based empirical damage model.

PubMed

Gordon, J A; Freedman, B R; Zuskov, A; Iozzo, R V; Birk, D E; Soslowsky, L J

2015-07-16

Achilles tendons are a common source of pain and injury, and their pathology may originate from aberrant structure function relationships. Small leucine rich proteoglycans (SLRPs) influence mechanical and structural properties in a tendon-specific manner. However, their roles in the Achilles tendon have not been defined. The objective of this study was to evaluate the mechanical and structural differences observed in mouse Achilles tendons lacking class I SLRPs; either decorin or biglycan. In addition, empirical modeling techniques based on mechanical and image-based measures were employed. Achilles tendons from decorin-null (Dcn(-/-)) and biglycan-null (Bgn(-/-)) C57BL/6 female mice (N=102) were used. Each tendon underwent a dynamic mechanical testing protocol including simultaneous polarized light image capture to evaluate both structural and mechanical properties of each Achilles tendon. An empirical damage model was adapted for application to genetic variation and for use with image based structural properties to predict tendon dynamic mechanical properties. We found that Achilles tendons lacking decorin and biglycan had inferior mechanical and structural properties that were age dependent; and that simple empirical models, based on previously described damage models, were predictive of Achilles tendon dynamic modulus in both decorin- and biglycan-null mice. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

PubMed

Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L

2018-02-01

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Estimate of the shielding effect on secondary cancer risk due to cone-beam CT in image-guided radiotherapy

NASA Astrophysics Data System (ADS)

Sung, Jiwon; Baek, Tae Seong; Yoon, Myonggeun; Kim, Dong Wook; Kim, Dong Hyun

2014-09-01

This study evaluated the effect of a simple shielding method using a thin lead sheet on the imaging dose caused by cone-beam computed tomography (CBCT) in image-guided radiation therapy (IGRT). Reduction of secondary doses from CBCT was measured using a radio-photoluminescence glass dosimeter (RPLGD) placed inside an anthropomorphic phantom. The entire body, except for the region scanned by using CBCT, was shielded by wrapping it with a 2-mm lead sheet. Changes in secondary cancer risk due to shielding were calculated using BEIR VII models. Doses to out-of-field organs for head-and-neck, chest, and pelvis scans were decreased 15 ~ 100%, 23 ~ 90%, and 23 ~ 98%, respectively, and the average reductions in lifetime secondary cancer risk due to the 2-mm lead shielding were 1.6, 11.5, and 12.7 persons per 100,000, respectively. These findings suggest that a simple, thin-lead-sheet-based shielding method can effectively decrease secondary doses to out-of-field regions for CBCT, which reduces the lifetime cancer risk on average by 9 per 100,000 patients.

Photon migration in non-scattering tissue and the effects on image reconstruction

NASA Astrophysics Data System (ADS)

Dehghani, H.; Delpy, D. T.; Arridge, S. R.

1999-12-01

Photon propagation in tissue can be calculated using the relationship described by the transport equation. For scattering tissue this relationship is often simplified and expressed in terms of the diffusion approximation. This approximation, however, is not valid for non-scattering regions, for example cerebrospinal fluid (CSF) below the skull. This study looks at the effects of a thin clear layer in a simple model representing the head and examines its effect on image reconstruction. Specifically, boundary photon intensities (total number of photons exiting at a point on the boundary due to a source input at another point on the boundary) are calculated using the transport equation and compared with data calculated using the diffusion approximation for both non-scattering and scattering regions. The effect of non-scattering regions on the calculated boundary photon intensities is presented together with the advantages and restrictions of the transport code used. Reconstructed images are then presented where the forward problem is solved using the transport equation for a simple two-dimensional system containing a non-scattering ring and the inverse problem is solved using the diffusion approximation to the transport equation.

Skeletonization and Partitioning of Digital Images Using Discrete Morse Theory.

PubMed

Delgado-Friedrichs, Olaf; Robins, Vanessa; Sheppard, Adrian

2015-03-01

We show how discrete Morse theory provides a rigorous and unifying foundation for defining skeletons and partitions of grayscale digital images. We model a grayscale image as a cubical complex with a real-valued function defined on its vertices (the voxel values). This function is extended to a discrete gradient vector field using the algorithm presented in Robins, Wood, Sheppard TPAMI 33:1646 (2011). In the current paper we define basins (the building blocks of a partition) and segments of the skeleton using the stable and unstable sets associated with critical cells. The natural connection between Morse theory and homology allows us to prove the topological validity of these constructions; for example, that the skeleton is homotopic to the initial object. We simplify the basins and skeletons via Morse-theoretic cancellation of critical cells in the discrete gradient vector field using a strategy informed by persistent homology. Simple working Python code for our algorithms for efficient vector field traversal is included. Example data are taken from micro-CT images of porous materials, an application area where accurate topological models of pore connectivity are vital for fluid-flow modelling.

GRMHD Simulations of Visibility Amplitude Variability for Event Horizon Telescope Images of Sgr A*

NASA Astrophysics Data System (ADS)

Medeiros, Lia; Chan, Chi-kwan; Özel, Feryal; Psaltis, Dimitrios; Kim, Junhan; Marrone, Daniel P.; Sa¸dowski, Aleksander

2018-04-01

The Event Horizon Telescope will generate horizon scale images of the black hole in the center of the Milky Way, Sgr A*. Image reconstruction using interferometric visibilities rests on the assumption of a stationary image. We explore the limitations of this assumption using high-cadence disk- and jet-dominated GRMHD simulations of Sgr A*. We also employ analytic models that capture the basic characteristics of the images to understand the origin of the variability in the simulated visibility amplitudes. We find that, in all simulations, the visibility amplitudes for baselines oriented parallel and perpendicular to the spin axis of the black hole follow general trends that do not depend strongly on accretion-flow properties. This suggests that fitting Event Horizon Telescope observations with simple geometric models may lead to a reasonably accurate determination of the orientation of the black hole on the plane of the sky. However, in the disk-dominated models, the locations and depths of the minima in the visibility amplitudes are highly variable and are not related simply to the size of the black hole shadow. This suggests that using time-independent models to infer additional black hole parameters, such as the shadow size or the spin magnitude, will be severely affected by the variability of the accretion flow.

A Bayesian Model of the Memory Colour Effect.

PubMed

Witzel, Christoph; Olkkonen, Maria; Gegenfurtner, Karl R

2018-01-01

According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration. Here, we model memory colour effects using prior knowledge about typical colours as priors for the grey adjustments in a Bayesian model. This simple model does not involve any fitting of free parameters. The Bayesian model roughly captured the magnitude of the measured memory colour effect for photographs of objects. To some extent, the model predicted observed differences in memory colour effects across objects. The model could not account for the differences in memory colour effects across different levels of realism in the object images. The Bayesian model provides a particularly simple account of memory colour effects, capturing some of the multiple sources of variation of these effects.

A Bayesian Model of the Memory Colour Effect

PubMed Central

Olkkonen, Maria; Gegenfurtner, Karl R.

2018-01-01

According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration. Here, we model memory colour effects using prior knowledge about typical colours as priors for the grey adjustments in a Bayesian model. This simple model does not involve any fitting of free parameters. The Bayesian model roughly captured the magnitude of the measured memory colour effect for photographs of objects. To some extent, the model predicted observed differences in memory colour effects across objects. The model could not account for the differences in memory colour effects across different levels of realism in the object images. The Bayesian model provides a particularly simple account of memory colour effects, capturing some of the multiple sources of variation of these effects. PMID:29760874

Vehicle track segmentation using higher order random fields

DOE PAGES

Quach, Tu -Thach

2017-01-09

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less

Vehicle track segmentation using higher order random fields

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

Quach, Tu -Thach

Here, we present an approach to segment vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times. The approach uses multiscale higher order random field models to capture track statistics, such as curvatures and their parallel nature, that are not currently utilized in existing methods. These statistics are encoded as 3-by-3 patterns at different scales. The model can complete disconnected tracks often caused by sensor noise and various environmental effects. Coupling the model with a simple classifier, our approach is effective at segmenting salient tracks. We improve the F-measure onmore » a standard vehicle track data set to 0.963, up from 0.897 obtained by the current state-of-the-art method.« less

Hierarchical Probabilistic Inference of Cosmic Shear

NASA Astrophysics Data System (ADS)

Schneider, Michael D.; Hogg, David W.; Marshall, Philip J.; Dawson, William A.; Meyers, Joshua; Bard, Deborah J.; Lang, Dustin

2015-07-01

Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.

Functional imaging of the angiogenic switch in a transgenic mouse model of human breast cancer by dynamic contrast enhanced magnetic resonance imaging.

PubMed

Consolino, Lorena; Longo, Dario Livio; Dastrù, Walter; Cutrin, Juan Carlos; Dettori, Daniela; Lanzardo, Stefania; Oliviero, Salvatore; Cavallo, Federica; Aime, Silvio

2016-07-15

Tumour progression depends on several sequential events that include the microenvironment remodelling processes and the switch to the angiogenic phenotype, leading to new blood vessels recruitment. Non-invasive imaging techniques allow the monitoring of functional alterations in tumour vascularity and cellularity. The aim of this work was to detect functional changes in vascularisation and cellularity through Dynamic Contrast Enhanced (DCE) and Diffusion Weighted (DW) Magnetic Resonance Imaging (MRI) modalities during breast cancer initiation and progression of a transgenic mouse model (BALB-neuT mice). Histological examination showed that BALB-neuT mammary glands undergo a slow neoplastic progression from simple hyperplasia to invasive carcinoma, still preserving normal parts of mammary glands. DCE-MRI results highlighted marked functional changes in terms of vessel permeability (K(trans) , volume transfer constant) and vascularisation (vp , vascular volume fraction) in BALB-neuT hyperplastic mammary glands if compared to BALB/c ones. When breast tissue progressed from simple to atypical hyperplasia, a strong increase in DCE-MRI biomarkers was observed in BALB-neuT in comparison to BALB/c mice (K(trans)  = 5.3 ± 0.7E-4 and 3.1 ± 0.5E-4; vp  = 7.4 ± 0.8E-2 and 4.7 ± 0.6E-2 for BALB-neuT and BALB/c, respectively) that remained constant during the successive steps of the neoplastic transformation. Consistent with DCE-MRI observations, microvessel counting revealed a significant increase in tumour vessels. Our study showed that DCE-MRI estimates can accurately detect the angiogenic switch at early step of breast cancer carcinogenesis. These results support the view that this imaging approach is an excellent tool to characterize microvasculature changes, despite only small portions of the mammary glands developed neoplastic lesions in a transgenic mouse model. © 2016 UICC.

Application of RNAMlet to surface defect identification of steels

NASA Astrophysics Data System (ADS)

Xu, Ke; Xu, Yang; Zhou, Peng; Wang, Lei

2018-06-01

As three main production lines of steels, continuous casting slabs, hot rolled steel plates and cold rolled steel strips have different surface appearances and are produced at different speeds of their production lines. Therefore, the algorithms for the surface defect identifications of the three steel products have different requirements for real-time and anti-interference. The existing algorithms cannot be adaptively applied to surface defect identification of the three steel products. A new method of adaptive multi-scale geometric analysis named RNAMlet was proposed. The idea of RNAMlet came from the non-symmetry anti-packing pattern representation model (NAM). The image is decomposed into a set of rectangular blocks asymmetrically according to gray value changes of image pixels. Then two-dimensional Haar wavelet transform is applied to all blocks. If the image background is complex, the number of blocks is large, and more details of the image are utilized. If the image background is simple, the number of blocks is small, and less computation time is needed. RNAMlet was tested with image samples of the three steel products, and compared with three classical methods of multi-scale geometric analysis, including Contourlet, Shearlet and Tetrolet. For the image samples with complicated backgrounds, such as continuous casting slabs and hot rolled steel plates, the defect identification rate obtained by RNAMlet was 1% higher than other three methods. For the image samples with simple backgrounds, such as cold rolled steel strips, the computation time of RNAMlet was one-tenth of the other three MGA methods, while the defect identification rates obtained by RNAMlet were higher than the other three methods.

Elementary Teachers' Selection and Use of Visual Models

NASA Astrophysics Data System (ADS)

Lee, Tammy D.; Gail Jones, M.

2018-02-01

As science grows in complexity, science teachers face an increasing challenge of helping students interpret models that represent complex science systems. Little is known about how teachers select and use models when planning lessons. This mixed methods study investigated the pedagogical approaches and visual models used by elementary in-service and preservice teachers in the development of a science lesson about a complex system (e.g., water cycle). Sixty-seven elementary in-service and 69 elementary preservice teachers completed a card sort task designed to document the types of visual models (e.g., images) that teachers choose when planning science instruction. Quantitative and qualitative analyses were conducted to analyze the card sort task. Semistructured interviews were conducted with a subsample of teachers to elicit the rationale for image selection. Results from this study showed that both experienced in-service teachers and novice preservice teachers tended to select similar models and use similar rationales for images to be used in lessons. Teachers tended to select models that were aesthetically pleasing and simple in design and illustrated specific elements of the water cycle. The results also showed that teachers were not likely to select images that represented the less obvious dimensions of the water cycle. Furthermore, teachers selected visual models more as a pedagogical tool to illustrate specific elements of the water cycle and less often as a tool to promote student learning related to complex systems.

On-chip immobilization of planarians for in vivo imaging.

PubMed

Dexter, Joseph P; Tamme, Mary B; Lind, Christine H; Collins, Eva-Maria S

2014-09-17

Planarians are an important model organism for regeneration and stem cell research. A complete understanding of stem cell and regeneration dynamics in these animals requires time-lapse imaging in vivo, which has been difficult to achieve due to a lack of tissue-specific markers and the strong negative phototaxis of planarians. We have developed the Planarian Immobilization Chip (PIC) for rapid, stable immobilization of planarians for in vivo imaging without injury or biochemical alteration. The chip is easy and inexpensive to fabricate, and worms can be mounted for and removed after imaging within minutes. We show that the PIC enables significantly higher-stability immobilization than can be achieved with standard techniques, allowing for imaging of planarians at sub-cellular resolution in vivo using brightfield and fluorescence microscopy. We validate the performance of the PIC by performing time-lapse imaging of planarian wound closure and sequential imaging over days of head regeneration. We further show that the device can be used to immobilize Hydra, another photophobic regenerative model organism. The simple fabrication, low cost, ease of use, and enhanced specimen stability of the PIC should enable its broad application to in vivo studies of stem cell and regeneration dynamics in planarians and Hydra.

On-chip immobilization of planarians for in vivo imaging

PubMed Central

Dexter, Joseph P.; Tamme, Mary B.; Lind, Christine H.; Collins, Eva-Maria S.

2014-01-01

Planarians are an important model organism for regeneration and stem cell research. A complete understanding of stem cell and regeneration dynamics in these animals requires time-lapse imaging in vivo, which has been difficult to achieve due to a lack of tissue-specific markers and the strong negative phototaxis of planarians. We have developed the Planarian Immobilization Chip (PIC) for rapid, stable immobilization of planarians for in vivo imaging without injury or biochemical alteration. The chip is easy and inexpensive to fabricate, and worms can be mounted for and removed after imaging within minutes. We show that the PIC enables significantly higher-stability immobilization than can be achieved with standard techniques, allowing for imaging of planarians at sub-cellular resolution in vivo using brightfield and fluorescence microscopy. We validate the performance of the PIC by performing time-lapse imaging of planarian wound closure and sequential imaging over days of head regeneration. We further show that the device can be used to immobilize Hydra, another photophobic regenerative model organism. The simple fabrication, low cost, ease of use, and enhanced specimen stability of the PIC should enable its broad application to in vivo studies of stem cell and regeneration dynamics in planarians and Hydra. PMID:25227263

Digital imaging and remote sensing image generator (DIRSIG) as applied to NVESD sensor performance modeling

NASA Astrophysics Data System (ADS)

Kolb, Kimberly E.; Choi, Hee-sue S.; Kaur, Balvinder; Olson, Jeffrey T.; Hill, Clayton F.; Hutchinson, James A.

2016-05-01

The US Army's Communications Electronics Research, Development and Engineering Center (CERDEC) Night Vision and Electronic Sensors Directorate (referred to as NVESD) is developing a virtual detection, recognition, and identification (DRI) testing methodology using simulated imagery as a means of augmenting the field testing component of sensor performance evaluation, which is expensive, resource intensive, time consuming, and limited to the available target(s) and existing atmospheric visibility and environmental conditions at the time of testing. Existing simulation capabilities such as the Digital Imaging Remote Sensing Image Generator (DIRSIG) and NVESD's Integrated Performance Model Image Generator (NVIPM-IG) can be combined with existing detection algorithms to reduce cost/time, minimize testing risk, and allow virtual/simulated testing using full spectral and thermal object signatures, as well as those collected in the field. NVESD has developed an end-to-end capability to demonstrate the feasibility of this approach. Simple detection algorithms have been used on the degraded images generated by NVIPM-IG to determine the relative performance of the algorithms on both DIRSIG-simulated and collected images. Evaluating the degree to which the algorithm performance agrees between simulated versus field collected imagery is the first step in validating the simulated imagery procedure.

An Information-Based Machine Learning Approach to Elasticity Imaging

PubMed Central

Hoerig, Cameron; Ghaboussi, Jamshid; Insana, Michael. F.

2016-01-01

An information-based technique is described for applications in mechanical-property imaging of soft biological media under quasi-static loads. We adapted the Autoprogressive method that was originally developed for civil engineering applications for this purpose. The Autoprogressive method is a computational technique that combines knowledge of object shape and a sparse distribution of force and displacement measurements with finite-element analyses and artificial neural networks to estimate a complete set of stress and strain vectors. Elasticity imaging parameters are then computed from estimated stresses and strains. We introduce the technique using ultrasonic pulse-echo measurements in simple gelatin imaging phantoms having linear-elastic properties so that conventional finite-element modeling can be used to validate results. The Autoprogressive algorithm does not require any assumptions about the material properties and can, in principle, be used to image media with arbitrary properties. We show that by selecting a few well-chosen force-displacement measurements that are appropriately applied during training and establish convergence, we can estimate all nontrivial stress and strain vectors throughout an object and accurately estimate an elastic modulus at high spatial resolution. This new method of modeling the mechanical properties of tissue-like materials introduces a unique method of solving the inverse problem and is the first technique for imaging stress without assuming the underlying constitutive model. PMID:27858175

Resting electrocardiogram and stress myocardial perfusion imaging in the determination of left ventricular systolic function: an assessment enhancing the performance of gated SPET.

PubMed

Moralidis, Efstratios; Spyridonidis, Tryfon; Arsos, Georgios; Skeberis, Vassilios; Anagnostopoulos, Constantinos; Gavrielidis, Stavros

2010-01-01

This study aimed to determine systolic dysfunction and estimate resting left ventricular ejection fraction (LVEF) from information collected during routine evaluation of patients with suspected or known coronary heart disease. This approach was then compared to gated single photon emission tomography (SPET). Patients having undergone stress (201)Tl myocardial perfusion imaging followed by equilibrium radionuclide angiography (ERNA) were separated into derivation (n=954) and validation (n=309) groups. Logistic regression analysis was used to develop scoring systems, containing clinical, electrocardiographic (ECG) and scintigraphic data, for the discrimination of an ERNA-LVEF<0.50. Linear regression analysis provided equations predicting ERNA-LVEF from those scores. In 373 patients LVEF was also assessed with (201)Tl gated SPET. Our results showed that an ECG-Scintigraphic scoring system was the best simple predictor of an ERNA-LVEF<0.50 in comparison to other models including ECG, clinical and scintigraphic variables in both the derivation and validation subpopulations. A simple linear equation was derived also for the assessment of resting LVEF from the ECG-Scintigraphic model. Equilibrium radionuclide angiography-LVEF had a good correlation with the ECG-Scintigraphic model LVEF (r=0.716, P=0.000), (201)Tl gated SPET LVEF (r=0.711, P=0.000) and the average LVEF from those assessments (r=0.796, P=0.000). The Bland-Altman statistic (mean+/-2SD) provided values of 0.001+/-0.176, 0.071+/-0.196 and 0.040+/-0.152, respectively. The average LVEF was a better discriminator of systolic dysfunction than gated SPET-LVEF in receiver operating characteristic (ROC) analysis and identified more patients (89%) with a

One-point fitting of the flux density produced by a heliostat

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

Collado, Francisco J.

Accurate and simple models for the flux density reflected by an isolated heliostat should be one of the basic tools for the design and optimization of solar power tower systems. In this work, the ability and the accuracy of the Universidad de Zaragoza (UNIZAR) and the DLR (HFCAL) flux density models to fit actual energetic spots are checked against heliostat energetic images measured at Plataforma Solar de Almeria (PSA). Both the fully analytic models are able to acceptably fit the spot with only one-point fitting, i.e., the measured maximum flux. As a practical validation of this one-point fitting, the interceptmore » percentage of the measured images, i.e., the percentage of the energetic spot sent by the heliostat that gets the receiver surface, is compared with the intercept calculated through the UNIZAR and HFCAL models. As main conclusions, the UNIZAR and the HFCAL models could be quite appropriate tools for the design and optimization, provided the energetic images from the heliostats to be used in the collector field were previously analyzed. Also note that the HFCAL model is much simpler and slightly more accurate than the UNIZAR model. (author)« less

Radiation dose reduction in computed tomography perfusion using spatial-temporal Bayesian methods

NASA Astrophysics Data System (ADS)

Fang, Ruogu; Raj, Ashish; Chen, Tsuhan; Sanelli, Pina C.

2012-03-01

In current computed tomography (CT) examinations, the associated X-ray radiation dose is of significant concern to patients and operators, especially CT perfusion (CTP) imaging that has higher radiation dose due to its cine scanning technique. A simple and cost-effective means to perform the examinations is to lower the milliampere-seconds (mAs) parameter as low as reasonably achievable in data acquisition. However, lowering the mAs parameter will unavoidably increase data noise and degrade CT perfusion maps greatly if no adequate noise control is applied during image reconstruction. To capture the essential dynamics of CT perfusion, a simple spatial-temporal Bayesian method that uses a piecewise parametric model of the residual function is used, and then the model parameters are estimated from a Bayesian formulation of prior smoothness constraints on perfusion parameters. From the fitted residual function, reliable CTP parameter maps are obtained from low dose CT data. The merit of this scheme exists in the combination of analytical piecewise residual function with Bayesian framework using a simpler prior spatial constrain for CT perfusion application. On a dataset of 22 patients, this dynamic spatial-temporal Bayesian model yielded an increase in signal-tonoise-ratio (SNR) of 78% and a decrease in mean-square-error (MSE) of 40% at low dose radiation of 43mA.

Computing local edge probability in natural scenes from a population of oriented simple cells

PubMed Central

Ramachandra, Chaithanya A.; Mel, Bartlett W.

2013-01-01

A key computation in visual cortex is the extraction of object contours, where the first stage of processing is commonly attributed to V1 simple cells. The standard model of a simple cell—an oriented linear filter followed by a divisive normalization—fits a wide variety of physiological data, but is a poor performing local edge detector when applied to natural images. The brain's ability to finely discriminate edges from nonedges therefore likely depends on information encoded by local simple cell populations. To gain insight into the corresponding decoding problem, we used Bayes's rule to calculate edge probability at a given location/orientation in an image based on a surrounding filter population. Beginning with a set of ∼ 100 filters, we culled out a subset that were maximally informative about edges, and minimally correlated to allow factorization of the joint on- and off-edge likelihood functions. Key features of our approach include a new, efficient method for ground-truth edge labeling, an emphasis on achieving filter independence, including a focus on filters in the region orthogonal rather than tangential to an edge, and the use of a customized parametric model to represent the individual filter likelihood functions. The resulting population-based edge detector has zero parameters, calculates edge probability based on a sum of surrounding filter influences, is much more sharply tuned than the underlying linear filters, and effectively captures fine-scale edge structure in natural scenes. Our findings predict nonmonotonic interactions between cells in visual cortex, wherein a cell may for certain stimuli excite and for other stimuli inhibit the same neighboring cell, depending on the two cells' relative offsets in position and orientation, and their relative activation levels. PMID:24381295

Local figure-ground cues are valid for natural images.

PubMed

Fowlkes, Charless C; Martin, David R; Malik, Jitendra

2007-06-08

Figure-ground organization refers to the visual perception that a contour separating two regions belongs to one of the regions. Recent studies have found neural correlates of figure-ground assignment in V2 as early as 10-25 ms after response onset, providing strong support for the role of local bottom-up processing. How much information about figure-ground assignment is available from locally computed cues? Using a large collection of natural images, in which neighboring regions were assigned a figure-ground relation by human observers, we quantified the extent to which figural regions locally tend to be smaller, more convex, and lie below ground regions. Our results suggest that these Gestalt cues are ecologically valid, and we quantify their relative power. We have also developed a simple bottom-up computational model of figure-ground assignment that takes image contours as input. Using parameters fit to natural image statistics, the model is capable of matching human-level performance when scene context limited.

Road extraction from aerial images using a region competition algorithm.

PubMed

Amo, Miriam; Martínez, Fernando; Torre, Margarita

2006-05-01

In this paper, we present a user-guided method based on the region competition algorithm to extract roads, and therefore we also provide some clues concerning the placement of the points required by the algorithm. The initial points are analyzed in order to find out whether it is necessary to add more initial points, and this process will be based on image information. Not only is the algorithm able to obtain the road centerline, but it also recovers the road sides. An initial simple model is deformed by using region growing techniques to obtain a rough road approximation. This model will be refined by region competition. The result of this approach is that it delivers the simplest output vector information, fully recovering the road details as they are on the image, without performing any kind of symbolization. Therefore, we tried to refine a general road model by using a reliable method to detect transitions between regions. This method is proposed in order to obtain information for feeding large-scale Geographic Information System.

Convolutional networks for vehicle track segmentation

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2017-10-01

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple and fast models to label track pixels. These models, however, are unable to capture natural track features, such as continuity and parallelism. More powerful but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3×3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate in low power and have limited training data. As a result, we aim for small and efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our six-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.

A CTRW-based model of time-resolved fluorescence lifetime imaging in a turbid medium

NASA Astrophysics Data System (ADS)

Chernomordik, Victor; Gandjbakhche, Amir H.; Hassan, Moinuddin; Pajevic, Sinisa; Weiss, George H.

2010-12-01

We develop an analytic model of time-resolved fluorescent imaging of photons migrating through a semi-infinite turbid medium bounded by an infinite plane in the presence of a single stationary point fluorophore embedded in the medium. In contrast to earlier models of fluorescent imaging in which photon motion is assumed to be some form of continuous diffusion process, the present analysis is based on a continuous-time random walk (CTRW) on a simple cubic lattice, the objective being to estimate the position and lifetime of the fluorophore. This can provide information related to local variations in pH and temperature with potential medical significance. Aspects of the theory were tested using time-resolved measurements of the fluorescence from small inclusions inside tissue-like phantoms. The experimental results were found to be in good agreement with theoretical predictions provided that the fluorophore was not located too close to the planar boundary, a common problem in many diffusive systems.

Real-time Non-invasive Spectral Imaging of Orthotopic Red Fluorescent Protein-expressing Lung Tumor Growth in Nude Mice.

PubMed

Zhang, Yong; Zhang, Nan; Zhao, Ming; Hoffman, Robert M

2015-07-01

Orthotopic implantation of cancer allows metastasis to occur. The most patient-like metastatic orthotopic models are developed with surgical orthotopic implantation using intact tissue in order to preserve the natural tissue structure of the tumor which contains both cancer cells and stroma. In the present study, we performed a simple thoracotomy by making an intercostal incision between the fourth and fifth ribs on the left side of the chest of nude mice. Lung tumor fragments expressing red fluorescent protein were then implanted on the left lung. It was possible to monitor tumor formation in the lung non-invasively by spectral imaging using the Maestro system with a liquid tunable filter. The model described here has high tumorigenicity in the lung (100%) and a low mortality rate (5%). This imageable nude mouse model using surgical orthotopic implantation of lung cancer will be useful for all types of longitudinal studies. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Interpreting sea surface slicks on the basis of the normalized radar cross-section model using RADARSAT-2 copolarization dual-channel SAR images

NASA Astrophysics Data System (ADS)

Ivonin, D. V.; Skrunes, S.; Brekke, C.; Ivanov, A. Yu.

2016-03-01

A simple automatic multipolarization technique for discrimination of main types of thin oil films (of thickness less than the radio wave skin depth) from natural ones is proposed. It is based on a new multipolarization parameter related to the ratio between the damping in the slick of specially normalized resonant and nonresonant signals calculated using the normalized radar cross-section model proposed by Kudryavtsev et al. (2003a). The technique is tested on RADARSAT-2 copolarization (VV/HH) synthetic aperture radar images of slicks of a priori known provenance (mineral oils, e.g., emulsion and crude oil, and plant oil served to model a natural slick) released during annual oil-on-water exercises in the North Sea in 2011 and 2012. It has been shown that the suggested multipolarization parameter gives new capabilities in interpreting slicks visible on synthetic aperture radar images while allowing discrimination between mineral oil and plant oil slicks.

GIS Toolsets for Planetary Geomorphology and Landing-Site Analysis

NASA Astrophysics Data System (ADS)

Nass, Andrea; van Gasselt, Stephan

2015-04-01

Modern Geographic Information Systems (GIS) allow expert and lay users alike to load and position geographic data and perform simple to highly complex surface analyses. For many applications dedicated and ready-to-use GIS tools are available in standard software systems while other applications require the modular combination of available basic tools to answer more specific questions. This also applies to analyses in modern planetary geomorphology where many of such (basic) tools can be used to build complex analysis tools, e.g. in image- and terrain model analysis. Apart from the simple application of sets of different tools, many complex tasks require a more sophisticated design for storing and accessing data using databases (e.g. ArcHydro for hydrological data analysis). In planetary sciences, complex database-driven models are often required to efficiently analyse potential landings sites or store rover data, but also geologic mapping data can be efficiently stored and accessed using database models rather than stand-alone shapefiles. For landings-site analyses, relief and surface roughness estimates are two common concepts that are of particular interest and for both, a number of different definitions co-exist. We here present an advanced toolset for the analysis of image and terrain-model data with an emphasis on extraction of landing site characteristics using established criteria. We provide working examples and particularly focus on the concepts of terrain roughness as it is interpreted in geomorphology and engineering studies.

Classification Comparisons Between Compact Polarimetric and Quad-Pol SAR Imagery

NASA Astrophysics Data System (ADS)

Souissi, Boularbah; Doulgeris, Anthony P.; Eltoft, Torbjørn

2015-04-01

Recent interest in dual-pol SAR systems has lead to a novel approach, the so-called compact polarimetric imaging mode (CP) which attempts to reconstruct fully polarimetric information based on a few simple assumptions. In this work, the CP image is simulated from the full quad-pol (QP) image. We present here the initial comparison of polarimetric information content between QP and CP imaging modes. The analysis of multi-look polarimetric covariance matrix data uses an automated statistical clustering method based upon the expectation maximization (EM) algorithm for finite mixture modeling, using the complex Wishart probability density function. Our results showed that there are some different characteristics between the QP and CP modes. The classification is demonstrated using a E-SAR and Radarsat2 polarimetric SAR images acquired over DLR Oberpfaffenhofen in Germany and Algiers in Algeria respectively.

TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis

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

Krafft, S; The University of Texas Graduate School of Biomedical Sciences, Houston, TX; Briere, T

2015-06-15

Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. Amore » total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP NTCP modeling is warranted. This work was supported by the Rosalie B. Hite Fellowship in Cancer research awarded to SPK.« less

Image denoising for real-time MRI.

PubMed

Klosowski, Jakob; Frahm, Jens

2017-03-01

To develop an image noise filter suitable for MRI in real time (acquisition and display), which preserves small isolated details and efficiently removes background noise without introducing blur, smearing, or patch artifacts. The proposed method extends the nonlocal means algorithm to adapt the influence of the original pixel value according to a simple measure for patch regularity. Detail preservation is improved by a compactly supported weighting kernel that closely approximates the commonly used exponential weight, while an oracle step ensures efficient background noise removal. Denoising experiments were conducted on real-time images of healthy subjects reconstructed by regularized nonlinear inversion from radial acquisitions with pronounced undersampling. The filter leads to a signal-to-noise ratio (SNR) improvement of at least 60% without noticeable artifacts or loss of detail. The method visually compares to more complex state-of-the-art filters as the block-matching three-dimensional filter and in certain cases better matches the underlying noise model. Acceleration of the computation to more than 100 complex frames per second using graphics processing units is straightforward. The sensitivity of nonlocal means to small details can be significantly increased by the simple strategies presented here, which allows partial restoration of SNR in iteratively reconstructed images without introducing a noticeable time delay or image artifacts. Magn Reson Med 77:1340-1352, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Simple and Inexpensive Classroom Demonstrations of Nuclear Magnetic Resonance and Magnetic Resonance Imaging.

ERIC Educational Resources Information Center

Olson, Joel A.; Nordell, Karen J.; Chesnik, Marla A.; Landis, Clark R.; Ellis, Arthur B.; Rzchowski, M. S.; Condren, S. Michael; Lisensky, George C.

2000-01-01

Describes a set of simple, inexpensive, classical demonstrations of nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) principles that illustrate the resonance condition associated with magnetic dipoles and the dependence of the resonance frequency on environment. (WRM)

Using genetically modified tomato crop plants with purple leaves for absolute weed/crop classification.

PubMed

Lati, Ran N; Filin, Sagi; Aly, Radi; Lande, Tal; Levin, Ilan; Eizenberg, Hanan

2014-07-01

Weed/crop classification is considered the main problem in developing precise weed-management methodologies, because both crops and weeds share similar hues. Great effort has been invested in the development of classification models, most based on expensive sensors and complicated algorithms. However, satisfactory results are not consistently obtained due to imaging conditions in the field. We report on an innovative approach that combines advances in genetic engineering and robust image-processing methods to detect weeds and distinguish them from crop plants by manipulating the crop's leaf color. We demonstrate this on genetically modified tomato (germplasm AN-113) which expresses a purple leaf color. An autonomous weed/crop classification is performed using an invariant-hue transformation that is applied to images acquired by a standard consumer camera (visible wavelength) and handles variations in illumination intensities. The integration of these methodologies is simple and effective, and classification results were accurate and stable under a wide range of imaging conditions. Using this approach, we simplify the most complicated stage in image-based weed/crop classification models. © 2013 Society of Chemical Industry.

Simple Scaling of Multi-Stream Jet Plumes for Aeroacoustic Modeling

NASA Technical Reports Server (NTRS)

Bridges, James

2015-01-01

When creating simplified, semi-empirical models for the noise of simple single-stream jets near surfaces it has proven useful to be able to generalize the geometry of the jet plume. Having a model that collapses the mean and turbulent velocity fields for a range of flows allows the problem to become one of relating the normalized jet field and the surface. However, most jet flows of practical interest involve jets of two or more co-annular flows for which standard models for the plume geometry do not exist. The present paper describes one attempt to relate the mean and turbulent velocity fields of multi-stream jets to that of an equivalent single-stream jet. The normalization of single-stream jets is briefly reviewed, from the functional form of the flow model to the results of the modeling. Next, PIV (Particle Image Velocimetry) data from a number of multi-stream jets is analyzed in a similar fashion. The results of several single-stream approximations of the multi-stream jet plume are demonstrated, with a 'best' approximation determined and the shortcomings of the model highlighted.

Classification of simple vegetation types using POLSAR image data

NASA Technical Reports Server (NTRS)

Freeman, A.

1993-01-01

Mapping basic vegetation or land cover types is a fairly common problem in remote sensing. Knowledge of the land cover type is a key input to algorithms which estimate geophysical parameters, such as soil moisture, surface roughness, leaf area index or biomass from remotely sensed data. In an earlier paper, an algorithm for fitting a simple three-component scattering model to POLSAR data was presented. The algorithm yielded estimates for surface scatter, double-bounce scatter and volume scatter for each pixel in a POLSAR image data set. In this paper, we show how the relative levels of each of the three components can be used as inputs to simple classifier for vegetation type. Vegetation classes include no vegetation cover (e.g. bare soil or desert), low vegetation cover (e.g. grassland), moderate vegetation cover (e.g. fully developed crops), forest and urban areas. Implementation of the approach requires estimates for the three components from all three frequencies available using the NASA/JPL AIRSAR, i.e. C-, L- and P-bands. The research described in this paper was carried out by the Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration.

A discrimination model in waste plastics sorting using NIR hyperspectral imaging system.

PubMed

Zheng, Yan; Bai, Jiarui; Xu, Jingna; Li, Xiayang; Zhang, Yimin

2018-02-01

Classification of plastics is important in the recycling industry. A plastic identification model in the near infrared spectroscopy wavelength range 1000-2500 nm is proposed for the characterization and sorting of waste plastics using acrylonitrile butadiene styrene (ABS), polystyrene (PS), polypropylene (PP), polyethylene (PE), polyethylene terephthalate (PET), and polyvinyl chloride (PVC). The model is built by the feature wavelengths of standard samples applying the principle component analysis (PCA), and the accuracy, property and cross-validation of the model were analyzed. The model just contains a simple equation, center of mass coordinates, and radial distance, with which it is easy to develop classification and sorting software. A hyperspectral imaging system (HIS) with the identification model verified its practical application by using the unknown plastics. Results showed that the identification accuracy of unknown samples is 100%. All results suggested that the discrimination model was potential to an on-line characterization and sorting platform of waste plastics based on HIS. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visual Recognition Software for Binary Classification and Its Application to Spruce Pollen Identification

PubMed Central

Tcheng, David K.; Nayak, Ashwin K.; Fowlkes, Charless C.; Punyasena, Surangi W.

2016-01-01

Discriminating between black and white spruce (Picea mariana and Picea glauca) is a difficult palynological classification problem that, if solved, would provide valuable data for paleoclimate reconstructions. We developed an open-source visual recognition software (ARLO, Automated Recognition with Layered Optimization) capable of differentiating between these two species at an accuracy on par with human experts. The system applies pattern recognition and machine learning to the analysis of pollen images and discovers general-purpose image features, defined by simple features of lines and grids of pixels taken at different dimensions, size, spacing, and resolution. It adapts to a given problem by searching for the most effective combination of both feature representation and learning strategy. This results in a powerful and flexible framework for image classification. We worked with images acquired using an automated slide scanner. We first applied a hash-based “pollen spotting” model to segment pollen grains from the slide background. We next tested ARLO’s ability to reconstruct black to white spruce pollen ratios using artificially constructed slides of known ratios. We then developed a more scalable hash-based method of image analysis that was able to distinguish between the pollen of black and white spruce with an estimated accuracy of 83.61%, comparable to human expert performance. Our results demonstrate the capability of machine learning systems to automate challenging taxonomic classifications in pollen analysis, and our success with simple image representations suggests that our approach is generalizable to many other object recognition problems. PMID:26867017

Enabling patients to manage altered body image.

PubMed

Price, Bob

2016-12-14

The author presented a model in the 1990s to explain altered body image, which has been used to characterise the difficulties encountered by patients who experience body change as a result of illness, injury or disability. However, it remains a challenge for nurses to establish care plans that can assist patients to manage the psychological adjustments associated with disfigurement. This article presents some simple questions to help patients narrate their psychological experiences and needs, and proposes a model of psychological change, based on the work of Kübler-Ross, to enable nurses to anticipate patient requirements that might arise at different stages of the individual's recovery and rehabilitation. Body-image rehabilitation may be protracted. Therefore, it is essential for nurses to understand what the patient is thinking and feeling throughout the rehabilitation process and which stage of psychological change the patient is working through.

A framework for interactive visualization of digital medical images.

PubMed

Koehring, Andrew; Foo, Jung Leng; Miyano, Go; Lobe, Thom; Winer, Eliot

2008-10-01

The visualization of medical images obtained from scanning techniques such as computed tomography and magnetic resonance imaging is a well-researched field. However, advanced tools and methods to manipulate these data for surgical planning and other tasks have not seen widespread use among medical professionals. Radiologists have begun using more advanced visualization packages on desktop computer systems, but most physicians continue to work with basic two-dimensional grayscale images or not work directly with the data at all. In addition, new display technologies that are in use in other fields have yet to be fully applied in medicine. It is our estimation that usability is the key aspect in keeping this new technology from being more widely used by the medical community at large. Therefore, we have a software and hardware framework that not only make use of advanced visualization techniques, but also feature powerful, yet simple-to-use, interfaces. A virtual reality system was created to display volume-rendered medical models in three dimensions. It was designed to run in many configurations, from a large cluster of machines powering a multiwalled display down to a single desktop computer. An augmented reality system was also created for, literally, hands-on interaction when viewing models of medical data. Last, a desktop application was designed to provide a simple visualization tool, which can be run on nearly any computer at a user's disposal. This research is directed toward improving the capabilities of medical professionals in the tasks of preoperative planning, surgical training, diagnostic assistance, and patient education.

A novel photoacoustic nanoprobe of ICG@PEG-Ag2S for atherosclerosis targeting and imaging in vivo

NASA Astrophysics Data System (ADS)

Wu, Chenxin; Zhang, Yejun; Li, Zhen; Li, Chunyan; Wang, Qiangbin

2016-06-01

Atherosclerosis is a major cause of cardiovascular and cerebrovascular diseases that have high mortality and disability rates. Because of its unclear pathogenic mechanism and heterogeneous distribution feature, it is still a big challenge to achieve precise diagnosis and therapy of atherosclerosis at its early stage in vivo. Herein, we fabricated a new ICG@PEG-Ag2S nanoprobe by a simple self-assembly of DT-Ag2S QDs, amphipathic C18/PEG polymer molecules and ICG. The ICG@PEG-Ag2S nanoprobe showed relatively long blood retention and was selectively accumulated in the region of atherosclerotic plaque due to the lipophilicity of the C18 chain to the atherosclerosis microenvironment, and thus the atherosclerosis was real-time monitored by high contrast-enhanced photoacoustic (PA) imaging of ICG. Combining the high signal-to-noise ratio (SNR) and high spatial resolution fluorescence imaging of Ag2S QDs in the second near-infrared window (NIR-II) and related histological assessment in vitro, the feasibility of this new nanoprobe for atherosclerosis targeting in an Apoe-/- mouse model was verified. Additionally, hemolysis and coagulation assays of the ICG@PEG-Ag2S revealed its decent hemocompatibility and no histological changes were observed in the main organs of the mouse. Such a simple, multifunctional nanoprobe for targeting and PA imaging of atherosclerosis will have a great potential for future clinical applications.Atherosclerosis is a major cause of cardiovascular and cerebrovascular diseases that have high mortality and disability rates. Because of its unclear pathogenic mechanism and heterogeneous distribution feature, it is still a big challenge to achieve precise diagnosis and therapy of atherosclerosis at its early stage in vivo. Herein, we fabricated a new ICG@PEG-Ag2S nanoprobe by a simple self-assembly of DT-Ag2S QDs, amphipathic C18/PEG polymer molecules and ICG. The ICG@PEG-Ag2S nanoprobe showed relatively long blood retention and was selectively accumulated in the region of atherosclerotic plaque due to the lipophilicity of the C18 chain to the atherosclerosis microenvironment, and thus the atherosclerosis was real-time monitored by high contrast-enhanced photoacoustic (PA) imaging of ICG. Combining the high signal-to-noise ratio (SNR) and high spatial resolution fluorescence imaging of Ag2S QDs in the second near-infrared window (NIR-II) and related histological assessment in vitro, the feasibility of this new nanoprobe for atherosclerosis targeting in an Apoe-/- mouse model was verified. Additionally, hemolysis and coagulation assays of the ICG@PEG-Ag2S revealed its decent hemocompatibility and no histological changes were observed in the main organs of the mouse. Such a simple, multifunctional nanoprobe for targeting and PA imaging of atherosclerosis will have a great potential for future clinical applications. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00060f

Speckle reduction in optical coherence tomography using two-step iteration method (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wang, Xianghong; Liu, Xinyu; Wang, Nanshuo; Yu, Xiaojun; Bo, En; Chen, Si; Liu, Linbo

2017-02-01

Optical coherence tomography (OCT) provides high resolution and cross-sectional images of biological tissue and is widely used for diagnosis of ocular diseases. However, OCT images suffer from speckle noise, which typically considered as multiplicative noise in nature, reducing the image resolution and contrast. In this study, we propose a two-step iteration (TSI) method to suppress those noises. We first utilize augmented Lagrange method to recover a low-rank OCT image and remove additive Gaussian noise, and then employ the simple and efficient split Bregman method to solve the Total-Variation Denoising model. We validated such proposed method using images of swine, rabbit and human retina. Results demonstrate that our TSI method outperforms the other popular methods in achieving higher peak signal-to-noise ratio (PSNR) and structure similarity (SSIM) while preserving important structural details, such as tiny capillaries and thin layers in retinal OCT images. In addition, the results of our TSI method show clearer boundaries and maintains high image contrast, which facilitates better image interpretations and analyses.

Projecting 2D gene expression data into 3D and 4D space.

PubMed

Gerth, Victor E; Katsuyama, Kaori; Snyder, Kevin A; Bowes, Jeff B; Kitayama, Atsushi; Ueno, Naoto; Vize, Peter D

2007-04-01

Video games typically generate virtual 3D objects by texture mapping an image onto a 3D polygonal frame. The feeling of movement is then achieved by mathematically simulating camera movement relative to the polygonal frame. We have built customized scripts that adapt video game authoring software to texture mapping images of gene expression data onto b-spline based embryo models. This approach, known as UV mapping, associates two-dimensional (U and V) coordinates within images to the three dimensions (X, Y, and Z) of a b-spline model. B-spline model frameworks were built either from confocal data or de novo extracted from 2D images, once again using video game authoring approaches. This system was then used to build 3D models of 182 genes expressed in developing Xenopus embryos and to implement these in a web-accessible database. Models can be viewed via simple Internet browsers and utilize openGL hardware acceleration via a Shockwave plugin. Not only does this database display static data in a dynamic and scalable manner, the UV mapping system also serves as a method to align different images to a common framework, an approach that may make high-throughput automated comparisons of gene expression patterns possible. Finally, video game systems also have elegant methods for handling movement, allowing biomechanical algorithms to drive the animation of models. With further development, these biomechanical techniques offer practical methods for generating virtual embryos that recapitulate morphogenesis.

3D Documentation and BIM Modeling of Cultural Heritage Structures Using UAVs: The Case of the Foinikaria Church

NASA Astrophysics Data System (ADS)

Themistocleous, K.; Agapiou, A.; Hadjimitsis, D.

2016-10-01

The documentation of architectural cultural heritage sites has traditionally been expensive and labor-intensive. New innovative technologies, such as Unmanned Aerial Vehicles (UAVs), provide an affordable, reliable and straightforward method of capturing cultural heritage sites, thereby providing a more efficient and sustainable approach to documentation of cultural heritage structures. In this study, hundreds of images of the Panagia Chryseleousa church in Foinikaria, Cyprus were taken using a UAV with an attached high resolution camera. The images were processed to generate an accurate digital 3D model by using Structure in Motion techniques. Building Information Model (BIM) was then used to generate drawings of the church. The methodology described in the paper provides an accurate, simple and cost-effective method of documenting cultural heritage sites and generating digital 3D models using novel techniques and innovative methods.

Hemodynamics model of fluid–solid interaction in internal carotid artery aneurysms

PubMed Central

Fu-Yu, Wang; Lei, Liu; Xiao-Jun, Zhang; Hai-Yue, Ju

2010-01-01

The objective of this study is to present a relatively simple method to reconstruct cerebral aneurysms as 3D numerical grids. The method accurately duplicates the geometry to provide computer simulations of the blood flow. Initial images were obtained by using CT angiography and 3D digital subtraction angiography in DICOM format. The image was processed by using MIMICS software, and the 3D fluid model (blood flow) and 3D solid model (wall) were generated. The subsequent output was exported to the ANSYS workbench software to generate the volumetric mesh for further hemodynamic study. The fluid model was defined and simulated in CFX software while the solid model was calculated in ANSYS software. The force data calculated firstly in the CFX software were transferred to the ANSYS software, and after receiving the force data, total mesh displacement data were calculated in the ANSYS software. Then, the mesh displacement data were transferred back to the CFX software. The data exchange was processed in workbench software. The results of simulation could be visualized in CFX-post. Two examples of grid reconstruction and blood flow simulation for patients with internal carotid artery aneurysms were presented. The wall shear stress, wall total pressure, and von Mises stress could be visualized. This method seems to be relatively simple and suitable for direct use by neurosurgeons or neuroradiologists, and maybe a practical tool for planning treatment and follow-up of patients after neurosurgical or endovascular interventions with 3D angiography. PMID:20812022

Hemodynamics model of fluid-solid interaction in internal carotid artery aneurysms.

PubMed

Bai-Nan, Xu; Fu-Yu, Wang; Lei, Liu; Xiao-Jun, Zhang; Hai-Yue, Ju

2011-01-01

The objective of this study is to present a relatively simple method to reconstruct cerebral aneurysms as 3D numerical grids. The method accurately duplicates the geometry to provide computer simulations of the blood flow. Initial images were obtained by using CT angiography and 3D digital subtraction angiography in DICOM format. The image was processed by using MIMICS software, and the 3D fluid model (blood flow) and 3D solid model (wall) were generated. The subsequent output was exported to the ANSYS workbench software to generate the volumetric mesh for further hemodynamic study. The fluid model was defined and simulated in CFX software while the solid model was calculated in ANSYS software. The force data calculated firstly in the CFX software were transferred to the ANSYS software, and after receiving the force data, total mesh displacement data were calculated in the ANSYS software. Then, the mesh displacement data were transferred back to the CFX software. The data exchange was processed in workbench software. The results of simulation could be visualized in CFX-post. Two examples of grid reconstruction and blood flow simulation for patients with internal carotid artery aneurysms were presented. The wall shear stress, wall total pressure, and von Mises stress could be visualized. This method seems to be relatively simple and suitable for direct use by neurosurgeons or neuroradiologists, and maybe a practical tool for planning treatment and follow-up of patients after neurosurgical or endovascular interventions with 3D angiography.

First Steps to Automated Interior Reconstruction from Semantically Enriched Point Clouds and Imagery

NASA Astrophysics Data System (ADS)

Obrock, L. S.; Gülch, E.

2018-05-01

The automated generation of a BIM-Model from sensor data is a huge challenge for the modeling of existing buildings. Currently the measurements and analyses are time consuming, allow little automation and require expensive equipment. We do lack an automated acquisition of semantical information of objects in a building. We are presenting first results of our approach based on imagery and derived products aiming at a more automated modeling of interior for a BIM building model. We examine the building parts and objects visible in the collected images using Deep Learning Methods based on Convolutional Neural Networks. For localization and classification of building parts we apply the FCN8s-Model for pixel-wise Semantic Segmentation. We, so far, reach a Pixel Accuracy of 77.2 % and a mean Intersection over Union of 44.2 %. We finally use the network for further reasoning on the images of the interior room. We combine the segmented images with the original images and use photogrammetric methods to produce a three-dimensional point cloud. We code the extracted object types as colours of the 3D-points. We thus are able to uniquely classify the points in three-dimensional space. We preliminary investigate a simple extraction method for colour and material of building parts. It is shown, that the combined images are very well suited to further extract more semantic information for the BIM-Model. With the presented methods we see a sound basis for further automation of acquisition and modeling of semantic and geometric information of interior rooms for a BIM-Model.

SimpleITK Image-Analysis Notebooks: a Collaborative Environment for Education and Reproducible Research.

PubMed

Yaniv, Ziv; Lowekamp, Bradley C; Johnson, Hans J; Beare, Richard

2018-06-01

Modern scientific endeavors increasingly require team collaborations to construct and interpret complex computational workflows. This work describes an image-analysis environment that supports the use of computational tools that facilitate reproducible research and support scientists with varying levels of software development skills. The Jupyter notebook web application is the basis of an environment that enables flexible, well-documented, and reproducible workflows via literate programming. Image-analysis software development is made accessible to scientists with varying levels of programming experience via the use of the SimpleITK toolkit, a simplified interface to the Insight Segmentation and Registration Toolkit. Additional features of the development environment include user friendly data sharing using online data repositories and a testing framework that facilitates code maintenance. SimpleITK provides a large number of examples illustrating educational and research-oriented image analysis workflows for free download from GitHub under an Apache 2.0 license: github.com/InsightSoftwareConsortium/SimpleITK-Notebooks .

Technical Note: Procedure for the calibration and validation of kilo-voltage cone-beam CT models

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

Vilches-Freixas, Gloria; Létang, Jean Michel; Rit,

2016-09-15

Purpose: The aim of this work is to propose a general and simple procedure for the calibration and validation of kilo-voltage cone-beam CT (kV CBCT) models against experimental data. Methods: The calibration and validation of the CT model is a two-step procedure: the source model then the detector model. The source is described by the direction dependent photon energy spectrum at each voltage while the detector is described by the pixel intensity value as a function of the direction and the energy of incident photons. The measurements for the source consist of a series of dose measurements in air performedmore » at each voltage with varying filter thicknesses and materials in front of the x-ray tube. The measurements for the detector are acquisitions of projection images using the same filters and several tube voltages. The proposed procedure has been applied to calibrate and assess the accuracy of simple models of the source and the detector of three commercial kV CBCT units. If the CBCT system models had been calibrated differently, the current procedure would have been exclusively used to validate the models. Several high-purity attenuation filters of aluminum, copper, and silver combined with a dosimeter which is sensitive to the range of voltages of interest were used. A sensitivity analysis of the model has also been conducted for each parameter of the source and the detector models. Results: Average deviations between experimental and theoretical dose values are below 1.5% after calibration for the three x-ray sources. The predicted energy deposited in the detector agrees with experimental data within 4% for all imaging systems. Conclusions: The authors developed and applied an experimental procedure to calibrate and validate any model of the source and the detector of a CBCT unit. The present protocol has been successfully applied to three x-ray imaging systems. The minimum requirements in terms of material and equipment would make its implementation suitable in most clinical environments.« less

The Scallop's Eye--A Concave Mirror in the Context of Biology

ERIC Educational Resources Information Center

Colicchia, Giuseppe; Waltner, Christine; Hopf, Martin; Wiesner, Hartmut

2009-01-01

Teaching physics in the context of medicine or biology is a way to generate students' interest in physics. A more uncommon type of eye, the scallop's eye (an eye with a spherical concave mirror, which is similar to a Newtonian or Schmidt telescope) and the image-forming mechanism in this eye are described. Also, a simple eye model, which can…

Using Targeting Outcomes of Programs as a Framework to Target Photographic Events in Nonformal Educational Programs

ERIC Educational Resources Information Center

Rockwell, S. Kay; Albrecht, Julie A.; Nugent, Gwen C.; Kunz, Gina M.

2012-01-01

Targeting Outcomes of Programs (TOP) is a seven-step hierarchical programming model in which the program development and performance sides are mirror images of each other. It served as a framework to identify a simple method for targeting photographic events in nonformal education programs, indicating why, when, and how photographs would be useful…

Virtual Ray Tracing as a Conceptual Tool for Image Formation in Mirrors and Lenses

ERIC Educational Resources Information Center

Heikkinen, Lasse; Savinainen, Antti; Saarelainen, Markku

2016-01-01

The ray tracing method is widely used in teaching geometrical optics at the upper secondary and university levels. However, using simple and straightforward examples may lead to a situation in which students use the model of ray tracing too narrowly. Previous studies show that students seem to use the ray tracing method too concretely instead of…

Known-component 3D-2D registration for quality assurance of spine surgery pedicle screw placement

NASA Astrophysics Data System (ADS)

Uneri, A.; De Silva, T.; Stayman, J. W.; Kleinszig, G.; Vogt, S.; Khanna, A. J.; Gokaslan, Z. L.; Wolinsky, J.-P.; Siewerdsen, J. H.

2015-10-01

A 3D-2D image registration method is presented that exploits knowledge of interventional devices (e.g. K-wires or spine screws—referred to as ‘known components’) to extend the functionality of intraoperative radiography/fluoroscopy by providing quantitative measurement and quality assurance (QA) of the surgical product. The known-component registration (KC-Reg) algorithm uses robust 3D-2D registration combined with 3D component models of surgical devices known to be present in intraoperative 2D radiographs. Component models were investigated that vary in fidelity from simple parametric models (e.g. approximation of a screw as a simple cylinder, referred to as ‘parametrically-known’ component [pKC] registration) to precise models based on device-specific CAD drawings (referred to as ‘exactly-known’ component [eKC] registration). 3D-2D registration from three intraoperative radiographs was solved using the covariance matrix adaptation evolution strategy (CMA-ES) to maximize image-gradient similarity, relating device placement relative to 3D preoperative CT of the patient. Spine phantom and cadaver studies were conducted to evaluate registration accuracy and demonstrate QA of the surgical product by verification of the type of devices delivered and conformance within the ‘acceptance window’ of the spinal pedicle. Pedicle screws were successfully registered to radiographs acquired from a mobile C-arm, providing TRE 1-4 mm and  <5° using simple parametric (pKC) models, further improved to  <1 mm and  <1° using eKC registration. Using advanced pKC models, screws that did not match the device models specified in the surgical plan were detected with an accuracy of  >99%. Visualization of registered devices relative to surgical planning and the pedicle acceptance window provided potentially valuable QA of the surgical product and reliable detection of pedicle screw breach. 3D-2D registration combined with 3D models of known surgical devices offers a novel method for intraoperative QA. The method provides a near-real-time independent check against pedicle breach, facilitating revision within the same procedure if necessary and providing more rigorous verification of the surgical product.

High-throughput live-imaging of embryos in microwell arrays using a modular specimen mounting system.

PubMed

Donoughe, Seth; Kim, Chiyoung; Extavour, Cassandra G

2018-04-30

High-throughput live-imaging of embryos is an essential technique in developmental biology, but it is difficult and costly to mount and image embryos in consistent conditions. Here, we present OMMAwell, a simple, reusable device to easily mount dozens of embryos in arrays of agarose microwells with customizable dimensions and spacing. OMMAwell can be configured to mount specimens for upright or inverted microscopes, and includes a reservoir to hold live-imaging medium to maintain constant moisture and osmolarity of specimens during time-lapse imaging. All device components can be fabricated by cutting pieces from a sheet of acrylic using a laser cutter or by making them with a 3D printer. We demonstrate how to design a custom mold and use it to live-image dozens of embryos at a time. We include descriptions, schematics, and design files for 13 additional molds for nine animal species, including most major traditional laboratory models and a number of emerging model systems. Finally, we provide instructions for researchers to customize OMMAwell inserts for embryos or tissues not described herein. © 2018. Published by The Company of Biologists Ltd.

Noninvasive Differentiation between Hepatic Steatosis and Steatohepatitis with MR Imaging Enhanced with USPIOs in Patients with Nonalcoholic Fatty Liver Disease: A Proof-of-Concept Study.

PubMed

Smits, Loek P; Coolen, Bram F; Panno, Maria D; Runge, Jurgen H; Nijhof, Wouter H; Verheij, Joanne; Nieuwdorp, Max; Stoker, Jaap; Beuers, Ulrich H; Nederveen, Aart J; Stroes, Erik S

2016-03-01

To (a) study the optimal timing and dosing for ultrasmall superparamagnetic iron oxide particle (USPIO)-enhanced magnetic resonance (MR) imaging of the liver in nonalcoholic fatty liver disease, (b) evaluate whether hepatic USPIO uptake is decreased in nonalcoholic steatohepatitis (NASH), and (c) study the diagnostic accuracy of USPIO-enhanced MR imaging to distinguish between NASH and simple steatosis. This prospective study was approved by the local institutional review board, and informed consent was obtained from all patients. Quantitative R2* MR imaging of the liver was performed at baseline and 72 hours after USPIO administration in patients with biopsy-proven NASH (n = 13), hepatic steatosis without NASH (n = 11), and healthy control subjects (n = 9). The hepatic USPIO uptake in the liver was quantified by the difference in R2* (ΔR2*) between the contrast material-enhanced images and baseline images. Between-group differences in mean ΔR2* were tested with the Student t test, and diagnostic accuracy was tested by calculating the area under the receiver operating characteristic curve. Patients with NASH had a significantly lower ΔR2* 72 hours after USPIO administration when compared with patients who had simple steatosis and healthy control subjects (mean ± standard deviation for patients with NASH, 37.0 sec(-1) ± 16.1; patients with simple steatosis, 61.0 sec(-1) ± 17.3; and healthy control subjects, 72.2 sec(-1) ± 22.0; P = .006 for NASH vs simple steatosis; P < .001 for NASH vs healthy control subjects). The area under the receiver operating characteristic curve to distinguish NASH from simple steatosis was 0.87 (95% confidence interval: 0.72, 1.00). This proof-of-concept study provides clues that hepatic USPIO uptake in patients with NASH is decreased and that USPIO MR imaging can be used to differentiate NASH from simple steatosis.

A novel end-to-end classifier using domain transferred deep convolutional neural networks for biomedical images.

PubMed

Pang, Shuchao; Yu, Zhezhou; Orgun, Mehmet A

2017-03-01

Highly accurate classification of biomedical images is an essential task in the clinical diagnosis of numerous medical diseases identified from those images. Traditional image classification methods combined with hand-crafted image feature descriptors and various classifiers are not able to effectively improve the accuracy rate and meet the high requirements of classification of biomedical images. The same also holds true for artificial neural network models directly trained with limited biomedical images used as training data or directly used as a black box to extract the deep features based on another distant dataset. In this study, we propose a highly reliable and accurate end-to-end classifier for all kinds of biomedical images via deep learning and transfer learning. We first apply domain transferred deep convolutional neural network for building a deep model; and then develop an overall deep learning architecture based on the raw pixels of original biomedical images using supervised training. In our model, we do not need the manual design of the feature space, seek an effective feature vector classifier or segment specific detection object and image patches, which are the main technological difficulties in the adoption of traditional image classification methods. Moreover, we do not need to be concerned with whether there are large training sets of annotated biomedical images, affordable parallel computing resources featuring GPUs or long times to wait for training a perfect deep model, which are the main problems to train deep neural networks for biomedical image classification as observed in recent works. With the utilization of a simple data augmentation method and fast convergence speed, our algorithm can achieve the best accuracy rate and outstanding classification ability for biomedical images. We have evaluated our classifier on several well-known public biomedical datasets and compared it with several state-of-the-art approaches. We propose a robust automated end-to-end classifier for biomedical images based on a domain transferred deep convolutional neural network model that shows a highly reliable and accurate performance which has been confirmed on several public biomedical image datasets. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

New learning based super-resolution: use of DWT and IGMRF prior.

PubMed

Gajjar, Prakash P; Joshi, Manjunath V

2010-05-01

In this paper, we propose a new learning-based approach for super-resolving an image captured at low spatial resolution. Given the low spatial resolution test image and a database consisting of low and high spatial resolution images, we obtain super-resolution for the test image. We first obtain an initial high-resolution (HR) estimate by learning the high-frequency details from the available database. A new discrete wavelet transform (DWT) based approach is proposed for learning that uses a set of low-resolution (LR) images and their corresponding HR versions. Since the super-resolution is an ill-posed problem, we obtain the final solution using a regularization framework. The LR image is modeled as the aliased and noisy version of the corresponding HR image, and the aliasing matrix entries are estimated using the test image and the initial HR estimate. The prior model for the super-resolved image is chosen as an Inhomogeneous Gaussian Markov random field (IGMRF) and the model parameters are estimated using the same initial HR estimate. A maximum a posteriori (MAP) estimation is used to arrive at the cost function which is minimized using a simple gradient descent approach. We demonstrate the effectiveness of the proposed approach by conducting the experiments on gray scale as well as on color images. The method is compared with the standard interpolation technique and also with existing learning-based approaches. The proposed approach can be used in applications such as wildlife sensor networks, remote surveillance where the memory, the transmission bandwidth, and the camera cost are the main constraints.

Optical tomography in the presence of void regions

PubMed

Dehghani; Arridge; Schweiger; Delpy

2000-09-01

There is a growing interest in the use of near-infrared spectroscopy for the noninvasive determination of the oxygenation level within biological tissue. Stemming from this application, there has been further research in the use of this technique for obtaining tomographic images of the neonatal head, with the view of determining the levels of oxygenated and deoxygenated blood within the brain. Owing to computational complexity, methods used for numerical modeling of photon transfer within tissue have usually been limited to the diffusion approximation of the Boltzmann transport equation. The diffusion approximation, however, is not valid in regions of low scatter, such as the cerebrospinal fluid. Methods have been proposed for dealing with nonscattering regions within diffusing materials through the use of a radiosity-diffusion model. Currently, this new model assumes prior knowledge of the void region location; therefore it is instructive to examine the errors introduced in applying a simple diffusion-based reconstruction scheme in cases in which there exists a nonscattering region. We present reconstructed images of objects that contain a nonscattering region within a diffusive material. Here the forward data is calculated with the radiosity-diffusion model, and the inverse problem is solved with either the radiosity-diffusion model or the diffusion-only model. The reconstructed images show that even in the presence of only a thin nonscattering layer, a diffusion-only reconstruction will fail. When a radiosity-diffusion model is used for image reconstruction, together with a priori information about the position of the nonscattering region, the quality of the reconstructed image is considerably improved. The accuracy of the reconstructed images depends largely on the position of the anomaly with respect to the nonscattering region as well as the thickness of the nonscattering region.

A novel method of the image processing on irregular triangular meshes

NASA Astrophysics Data System (ADS)

Vishnyakov, Sergey; Pekhterev, Vitaliy; Sokolova, Elizaveta

2018-04-01

The paper describes a novel method of the image processing based on irregular triangular meshes implementation. The triangular mesh is adaptive to the image content, least mean square linear approximation is proposed for the basic interpolation within the triangle. It is proposed to use triangular numbers to simplify using of the local (barycentric) coordinates for the further analysis - triangular element of the initial irregular mesh is to be represented through the set of the four equilateral triangles. This allows to use fast and simple pixels indexing in local coordinates, e.g. "for" or "while" loops for access to the pixels. Moreover, representation proposed allows to use discrete cosine transform of the simple "rectangular" symmetric form without additional pixels reordering (as it is used for shape-adaptive DCT forms). Furthermore, this approach leads to the simple form of the wavelet transform on triangular mesh. The results of the method application are presented. It is shown that advantage of the method proposed is a combination of the flexibility of the image-adaptive irregular meshes with the simple form of the pixel indexing in local triangular coordinates and the using of the common forms of the discrete transforms for triangular meshes. Method described is proposed for the image compression, pattern recognition, image quality improvement, image search and indexing. It also may be used as a part of video coding (intra-frame or inter-frame coding, motion detection).

A De-Identification Pipeline for Ultrasound Medical Images in DICOM Format.

PubMed

Monteiro, Eriksson; Costa, Carlos; Oliveira, José Luís

2017-05-01

Clinical data sharing between healthcare institutions, and between practitioners is often hindered by privacy protection requirements. This problem is critical in collaborative scenarios where data sharing is fundamental for establishing a workflow among parties. The anonymization of patient information burned in DICOM images requires elaborate processes somewhat more complex than simple de-identification of textual information. Usually, before sharing, there is a need for manual removal of specific areas containing sensitive information in the images. In this paper, we present a pipeline for ultrasound medical image de-identification, provided as a free anonymization REST service for medical image applications, and a Software-as-a-Service to streamline automatic de-identification of medical images, which is freely available for end-users. The proposed approach applies image processing functions and machine-learning models to bring about an automatic system to anonymize medical images. To perform character recognition, we evaluated several machine-learning models, being Convolutional Neural Networks (CNN) selected as the best approach. For accessing the system quality, 500 processed images were manually inspected showing an anonymization rate of 89.2%. The tool can be accessed at https://bioinformatics.ua.pt/dicom/anonymizer and it is available with the most recent version of Google Chrome, Mozilla Firefox and Safari. A Docker image containing the proposed service is also publicly available for the community.

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.

Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages.

PubMed

Choi, Youn-Kyung; Kim, Jinmi; Yamaguchi, Tetsutaro; Maki, Koutaro; Ko, Ching-Chang; Kim, Yong-Il

2016-01-01

This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5-18 years of age). We performed Pearson's correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P < 0.05). The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level.

Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages

PubMed Central

Choi, Youn-Kyung; Kim, Jinmi; Maki, Koutaro; Ko, Ching-Chang

2016-01-01

This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5–18 years of age). We performed Pearson's correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P < 0.05). The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level. PMID:27340668

Learning to rank for blind image quality assessment.

PubMed

Gao, Fei; Tao, Dacheng; Gao, Xinbo; Li, Xuelong

2015-10-01

Blind image quality assessment (BIQA) aims to predict perceptual image quality scores without access to reference images. State-of-the-art BIQA methods typically require subjects to score a large number of images to train a robust model. However, subjective quality scores are imprecise, biased, and inconsistent, and it is challenging to obtain a large-scale database, or to extend existing databases, because of the inconvenience of collecting images, training the subjects, conducting subjective experiments, and realigning human quality evaluations. To combat these limitations, this paper explores and exploits preference image pairs (PIPs) such as the quality of image Ia is better than that of image Ib for training a robust BIQA model. The preference label, representing the relative quality of two images, is generally precise and consistent, and is not sensitive to image content, distortion type, or subject identity; such PIPs can be generated at a very low cost. The proposed BIQA method is one of learning to rank. We first formulate the problem of learning the mapping from the image features to the preference label as one of classification. In particular, we investigate the utilization of a multiple kernel learning algorithm based on group lasso to provide a solution. A simple but effective strategy to estimate perceptual image quality scores is then presented. Experiments show that the proposed BIQA method is highly effective and achieves a performance comparable with that of state-of-the-art BIQA algorithms. Moreover, the proposed method can be easily extended to new distortion categories.

Modeling of light distribution in the brain for topographical imaging

NASA Astrophysics Data System (ADS)

Okada, Eiji; Hayashi, Toshiyuki; Kawaguchi, Hiroshi

2004-07-01

Multi-channel optical imaging system can obtain a topographical distribution of the activated region in the brain cortex by a simple mapping algorithm. Near-infrared light is strongly scattered in the head and the volume of tissue that contributes to the change in the optical signal detected with source-detector pair on the head surface is broadly distributed in the brain. This scattering effect results in poor resolution and contrast in the topographic image of the brain activity. We report theoretical investigations on the spatial resolution of the topographic imaging of the brain activity. The head model for the theoretical study consists of five layers that imitate the scalp, skull, subarachnoid space, gray matter and white matter. The light propagation in the head model is predicted by Monte Carlo simulation to obtain the spatial sensitivity profile for a source-detector pair. The source-detector pairs are one dimensionally arranged on the surface of the model and the distance between the adjoining source-detector pairs are varied from 4 mm to 32 mm. The change in detected intensity caused by the absorption change is obtained by Monte Carlo simulation. The position of absorption change is reconstructed by the conventional mapping algorithm and the reconstruction algorithm using the spatial sensitivity profiles. We discuss the effective interval between the source-detector pairs and the choice of reconstruction algorithms to improve the topographic images of brain activity.

Dynamical System Approach for Edge Detection Using Coupled FitzHugh-Nagumo Neurons.

PubMed

Li, Shaobai; Dasmahapatra, Srinandan; Maharatna, Koushik

2015-12-01

The prospect of emulating the impressive computational capabilities of biological systems has led to considerable interest in the design of analog circuits that are potentially implementable in very large scale integration CMOS technology and are guided by biologically motivated models. For example, simple image processing tasks, such as the detection of edges in binary and grayscale images, have been performed by networks of FitzHugh-Nagumo-type neurons using the reaction-diffusion models. However, in these studies, the one-to-one mapping of image pixels to component neurons makes the size of the network a critical factor in any such implementation. In this paper, we develop a simplified version of the employed reaction-diffusion model in three steps. In the first step, we perform a detailed study to locate this threshold using continuous Lyapunov exponents from dynamical system theory. Furthermore, we render the diffusion in the system to be anisotropic, with the degree of anisotropy being set by the gradients of grayscale values in each image. The final step involves a simplification of the model that is achieved by eliminating the terms that couple the membrane potentials of adjacent neurons. We apply our technique to detect edges in data sets of artificially generated and real images, and we demonstrate that the performance is as good if not better than that of the previous methods without increasing the size of the network.

Construction of multi-functional open modulized Matlab simulation toolbox for imaging ladar system

NASA Astrophysics Data System (ADS)

Wu, Long; Zhao, Yuan; Tang, Meng; He, Jiang; Zhang, Yong

2011-06-01

Ladar system simulation is to simulate the ladar models using computer simulation technology in order to predict the performance of the ladar system. This paper presents the developments of laser imaging radar simulation for domestic and overseas studies and the studies of computer simulation on ladar system with different application requests. The LadarSim and FOI-LadarSIM simulation facilities of Utah State University and Swedish Defence Research Agency are introduced in details. This paper presents the low level of simulation scale, un-unified design and applications of domestic researches in imaging ladar system simulation, which are mostly to achieve simple function simulation based on ranging equations for ladar systems. Design of laser imaging radar simulation with open and modularized structure is proposed to design unified modules for ladar system, laser emitter, atmosphere models, target models, signal receiver, parameters setting and system controller. Unified Matlab toolbox and standard control modules have been built with regulated input and output of the functions, and the communication protocols between hardware modules. A simulation based on ICCD gain-modulated imaging ladar system for a space shuttle is made based on the toolbox. The simulation result shows that the models and parameter settings of the Matlab toolbox are able to simulate the actual detection process precisely. The unified control module and pre-defined parameter settings simplify the simulation of imaging ladar detection. Its open structures enable the toolbox to be modified for specialized requests. The modulization gives simulations flexibility.

Non-Relative Value Unit-Generating Activities Represent One-Fifth of Academic Neuroradiologist Productivity.

PubMed

Wintermark, M; Zeineh, M; Zaharchuk, G; Srivastava, A; Fischbein, N

2016-07-01

A neuroradiologist's activity includes many tasks beyond interpreting relative value unit-generating imaging studies. Our aim was to test a simple method to record and quantify the non-relative value unit-generating clinical activity represented by consults and clinical conferences, including tumor boards. Four full-time neuroradiologists, working an average of 50% clinical and 50% academic activity, systematically recorded all the non-relative value unit-generating consults and conferences in which they were involved during 3 months by using a simple, Web-based, computer-based application accessible from smartphones, tablets, or computers. The number and type of imaging studies they interpreted during the same period and the associated relative value units were extracted from our billing system. During 3 months, the 4 neuroradiologists working an average of 50% clinical activity interpreted 4241 relative value unit-generating imaging studies, representing 8152 work relative value units. During the same period, they recorded 792 non-relative value unit-generating study reviews as part of consults and conferences (not including reading room consults), representing 19% of the interpreted relative value unit-generating imaging studies. We propose a simple Web-based smartphone app to record and quantify non-relative value unit-generating activities including consults, clinical conferences, and tumor boards. The quantification of non-relative value unit-generating activities is paramount in this time of a paradigm shift from volume to value. It also represents an important tool for determining staffing levels, which cannot be performed on the basis of relative value unit only, considering the importance of time spent by radiologists on non-relative value unit-generating activities. It may also influence payment models from medical centers to radiology departments or practices. © 2016 by American Journal of Neuroradiology.

A motion algorithm to extract physical and motion parameters of mobile targets from cone-beam computed tomographic images.

PubMed

Alsbou, Nesreen; Ahmad, Salahuddin; Ali, Imad

2016-05-17

A motion algorithm has been developed to extract length, CT number level and motion amplitude of a mobile target from cone-beam CT (CBCT) images. The algorithm uses three measurable parameters: Apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm are tested with mobile targets having different well-known sizes that are made from tissue-equivalent gel which is inserted into a thorax phantom. The phantom moves sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0-20 mm. Using this motion algorithm, three unknown parameters are extracted that include: Length of the target, CT number level, speed or motion amplitude for the mobile targets from CBCT images. The motion algorithm solves for the three unknown parameters using measured length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agrees with the measured lengths which are dependent on the target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, the target length and motion amplitude. Motion frequency and phase do not affect the elongation and CT number distribution of the mobile target and could not be determined. A motion algorithm has been developed to extract three parameters that include length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement of motion tracking and sorting of the images into different breathing phases. The motion model developed here works well for tumors that have simple shapes, high contrast relative to surrounding tissues and move nearly in regular motion pattern that can be approximated with a simple sinusoidal function. This algorithm has potential applications in diagnostic CT imaging and radiotherapy in terms of motion management.

Principal components colour display of ERTS imagery

NASA Technical Reports Server (NTRS)

Taylor, M. M.

1974-01-01

In the technique presented, colours are not derived from single bands, but rather from independent linear combinations of the bands. Using a simple model of the processing done by the visual system, three informationally independent linear combinations of the four ERTS bands are mapped onto the three visual colour dimensions of brightness, redness-greenness and blueness-yellowness. The technique permits user-specific transformations which enhance particular features, but this is not usually needed, since a single transformation provides a picture which conveys much of the information implicit in the ERTS data. Examples of experimental vector images with matched individual band images are shown.

Describing contrast across scales

NASA Astrophysics Data System (ADS)

Syed, Sohaib Ali; Iqbal, Muhammad Zafar; Riaz, Muhammad Mohsin

2017-06-01

Due to its sensitive nature against illumination and noise distributions, contrast is not widely used for image description. On the contrary, the human perception of contrast along different spatial frequency bandwidths provides a powerful discriminator function that can be modeled in a robust manner against local illumination. Based upon this observation, a dense local contrast descriptor is proposed and its potential in different applications of computer vision is discussed. Extensive experiments reveal that this simple yet effective description performs well in comparison with state of the art image descriptors. We also show the importance of this description in multiresolution pansharpening framework.

Color segmentation in the HSI color space using the K-means algorithm

NASA Astrophysics Data System (ADS)

Weeks, Arthur R.; Hague, G. Eric

1997-04-01

Segmentation of images is an important aspect of image recognition. While grayscale image segmentation has become quite a mature field, much less work has been done with regard to color image segmentation. Until recently, this was predominantly due to the lack of available computing power and color display hardware that is required to manipulate true color images (24-bit). TOday, it is not uncommon to find a standard desktop computer system with a true-color 24-bit display, at least 8 million bytes of memory, and 2 gigabytes of hard disk storage. Segmentation of color images is not as simple as segmenting each of the three RGB color components separately. The difficulty of using the RGB color space is that it doesn't closely model the psychological understanding of color. A better color model, which closely follows that of human visual perception is the hue, saturation, intensity model. This color model separates the color components in terms of chromatic and achromatic information. Strickland et al. was able to show the importance of color in the extraction of edge features form an image. His method enhances the edges that are detectable in the luminance image with information from the saturation image. Segmentation of both the saturation and intensity components is easily accomplished with any gray scale segmentation algorithm, since these spaces are linear. The modulus 2(pi) nature of the hue color component makes its segmentation difficult. For example, a hue of 0 and 2(pi) yields the same color tint. Instead of applying separate image segmentation to each of the hue, saturation, and intensity components, a better method is to segment the chromatic component separately from the intensity component because of the importance that the chromatic information plays in the segmentation of color images. This paper presents a method of using the gray scale K-means algorithm to segment 24-bit color images. Additionally, this paper will show the importance the hue component plays in the segmentation of color images.

Multi-spectral imaging of oxygen saturation

NASA Astrophysics Data System (ADS)

Savelieva, Tatiana A.; Stratonnikov, Aleksander A.; Loschenov, Victor B.

2008-06-01

The system of multi-spectral imaging of oxygen saturation is an instrument that can record both spectral and spatial information about a sample. In this project, the spectral imaging technique is used for monitoring of oxygen saturation of hemoglobin in human tissues. This system can be used for monitoring spatial distribution of oxygen saturation in photodynamic therapy, surgery or sports medicine. Diffuse reflectance spectroscopy in the visible range is an effective and extensively used technique for the non-invasive study and characterization of various biological tissues. In this article, a short review of modeling techniques being currently in use for diffuse reflection from semi-infinite turbid media is presented. A simple and practical model for use with a real-time imaging system is proposed. This model is based on linear approximation of the dependence of the diffuse reflectance coefficient on relation between absorbance and reduced scattering coefficient. This dependence was obtained with the Monte Carlo simulation of photon propagation in turbid media. Spectra of the oxygenated and deoxygenated forms of hemoglobin differ mostly in the red area (520 - 600 nm) and have several characteristic points there. Thus four band-pass filters were used for multi-spectral imaging. After having measured the reflectance, the data obtained are used for fitting the concentration of oxygenated and free hemoglobin, and hemoglobin oxygen saturation.

A Multi-Objective Decision Making Approach for Solving the Image Segmentation Fusion Problem.

PubMed

Khelifi, Lazhar; Mignotte, Max

2017-08-01

Image segmentation fusion is defined as the set of methods which aim at merging several image segmentations, in a manner that takes full advantage of the complementarity of each one. Previous relevant researches in this field have been impeded by the difficulty in identifying an appropriate single segmentation fusion criterion, providing the best possible, i.e., the more informative, result of fusion. In this paper, we propose a new model of image segmentation fusion based on multi-objective optimization which can mitigate this problem, to obtain a final improved result of segmentation. Our fusion framework incorporates the dominance concept in order to efficiently combine and optimize two complementary segmentation criteria, namely, the global consistency error and the F-measure (precision-recall) criterion. To this end, we present a hierarchical and efficient way to optimize the multi-objective consensus energy function related to this fusion model, which exploits a simple and deterministic iterative relaxation strategy combining the different image segments. This step is followed by a decision making task based on the so-called "technique for order performance by similarity to ideal solution". Results obtained on two publicly available databases with manual ground truth segmentations clearly show that our multi-objective energy-based model gives better results than the classical mono-objective one.

Fast single image dehazing based on image fusion

NASA Astrophysics Data System (ADS)

Liu, Haibo; Yang, Jie; Wu, Zhengping; Zhang, Qingnian

2015-01-01

Images captured in foggy weather conditions often fade the colors and reduce the contrast of the observed objects. An efficient image fusion method is proposed to remove haze from a single input image. First, the initial medium transmission is estimated based on the dark channel prior. Second, the method adopts an assumption that the degradation level affected by haze of each region is the same, which is similar to the Retinex theory, and uses a simple Gaussian filter to get the coarse medium transmission. Then, pixel-level fusion is achieved between the initial medium transmission and coarse medium transmission. The proposed method can recover a high-quality haze-free image based on the physical model, and the complexity of the proposed method is only a linear function of the number of input image pixels. Experimental results demonstrate that the proposed method can allow a very fast implementation and achieve better restoration for visibility and color fidelity compared to some state-of-the-art methods.

Simulation of nanoparticle-mediated near-infrared thermal therapy using GATE

PubMed Central

Cuplov, Vesna; Pain, Frédéric; Jan, Sébastien

2017-01-01

Application of nanotechnology for biomedicine in cancer therapy allows for direct delivery of anticancer agents to tumors. An example of such therapies is the nanoparticle-mediated near-infrared hyperthermia treatment. In order to investigate the influence of nanoparticle properties on the spatial distribution of heat in the tumor and healthy tissues, accurate simulations are required. The Geant4 Application for Emission Tomography (GATE) open-source simulation platform, based on the Geant4 toolkit, is widely used by the research community involved in molecular imaging, radiotherapy and optical imaging. We present an extension of GATE that can model nanoparticle-mediated hyperthermal therapy as well as simple heat diffusion in biological tissues. This new feature of GATE combined with optical imaging allows for the simulation of a theranostic scenario in which the patient is injected with theranostic nanosystems that can simultaneously deliver therapeutic (i.e. hyperthermia therapy) and imaging agents (i.e. fluorescence imaging). PMID:28663855

High resolution NMR imaging using a high field yokeless permanent magnet.

PubMed

Kose, Katsumi; Haishi, Tomoyuki

2011-01-01

We measured the homogeneity and stability of the magnetic field of a high field (about 1.04 tesla) yokeless permanent magnet with 40-mm gap for high resolution nuclear magnetic resonance (NMR) imaging. Homogeneity was evaluated using a 3-dimensional (3D) lattice phantom and 3D spin-echo imaging sequences. In the central sphere (20-mm diameter), peak-to-peak magnetic field inhomogeneity was about 60 ppm, and the root-mean-square was 8 ppm. We measured room temperature, magnet temperature, and NMR frequency of the magnet simultaneously every minute for about 68 hours with and without the thermal insulator of the magnet. A simple mathematical model described the magnet's thermal property. Based on magnet performance, we performed high resolution (up to [20 µm](2)) imaging with internal NMR lock sequences of several biological samples. Our results demonstrated the usefulness of the high field small yokeless permanent magnet for high resolution NMR imaging.

Diffusion processes in tumors: A nuclear medicine approach

NASA Astrophysics Data System (ADS)

Amaya, Helman

2016-07-01

The number of counts used in nuclear medicine imaging techniques, only provides physical information about the desintegration of the nucleus present in the the radiotracer molecules that were uptaken in a particular anatomical region, but that information is not a real metabolic information. For this reason a mathematical method was used to find a correlation between number of counts and 18F-FDG mass concentration. This correlation allows a better interpretation of the results obtained in the study of diffusive processes in an agar phantom, and based on it, an image from the PETCETIX DICOM sample image set from OsiriX-viewer software was processed. PET-CT gradient magnitude and Laplacian images could show direct information on diffusive processes for radiopharmaceuticals that enter into the cells by simple diffusion. In the case of the radiopharmaceutical 18F-FDG is necessary to include pharmacokinetic models, to make a correct interpretation of the gradient magnitude and Laplacian of counts images.

A scene-analysis approach to remote sensing. [San Francisco, California

NASA Technical Reports Server (NTRS)

Tenenbaum, J. M. (Principal Investigator); Fischler, M. A.; Wolf, H. C.

1978-01-01

The author has identified the following significant results. Geometric correspondance between a sensed image and a symbolic map is established in an initial stage of processing by adjusting parameters of a sensed model so that the image features predicted from the map optimally match corresponding features extracted from the sensed image. Information in the map is then used to constrain where to look in an image, what to look for, and how to interpret what is seen. For simple monitoring tasks involving multispectral classification, these constraints significantly reduce computation, simplify interpretation, and improve the utility of the resulting information. Previously intractable tasks requiring spatial and textural analysis may become straightforward in the context established by the map knowledge. The use of map-guided image analysis in monitoring the volume of water in a reservoir, the number of boxcars in a railyard, and the number of ships in a harbor is demonstrated.

Photoresist and stochastic modeling

NASA Astrophysics Data System (ADS)

Hansen, Steven G.

2018-01-01

Analysis of physical modeling results can provide unique insights into extreme ultraviolet stochastic variation, which augment, and sometimes refute, conclusions based on physical intuition and even wafer experiments. Simulations verify the primacy of "imaging critical" counting statistics (photons, electrons, and net acids) and the image/blur-dependent dose sensitivity in describing the local edge or critical dimension variation. But the failure of simple counting when resist thickness is varied highlights a limitation of this exact analytical approach, so a calibratable empirical model offers useful simplicity and convenience. Results presented here show that a wide range of physical simulation results can be well matched by an empirical two-parameter model based on blurred image log-slope (ILS) for lines/spaces and normalized ILS for holes. These results are largely consistent with a wide range of published experimental results; however, there is some disagreement with the recently published dataset of De Bisschop. The present analysis suggests that the origin of this model failure is an unexpected blurred ILS:dose-sensitivity relationship failure in that resist process. It is shown that a photoresist mechanism based on high photodecomposable quencher loading and high quencher diffusivity can give rise to pitch-dependent blur, which may explain the discrepancy.

Perception of multi-stable dot lattices in the visual periphery: an effect of internal positional noise.

PubMed

Põder, Endel

2011-02-16

Dot lattices are very simple multi-stable images where the dots can be perceived as being grouped in different ways. The probabilities of grouping along different orientations as dependent on inter-dot distances along these orientations can be predicted by a simple quantitative model. L. Bleumers, P. De Graef, K. Verfaillie, and J. Wagemans (2008) found that for peripheral presentation, this model should be combined with random guesses on a proportion of trials. The present study shows that the probability of random responses decreases with decreasing ambiguity of lattices and is different for bi-stable and tri-stable lattices. With central presentation, similar effects can be produced by adding positional noise to the dots. The results suggest that different levels of internal positional noise might explain the differences between peripheral and central proximity grouping.

Performance Considerations for the SIMPL Single Photon, Polarimetric, Two-Color Laser Altimeter as Applied to Measurements of Forest Canopy Structure and Composition

NASA Technical Reports Server (NTRS)

Dabney, Philip W.; Harding, David J.; Valett, Susan R.; Vasilyev, Aleksey A.; Yu, Anthony W.

2012-01-01

The Slope Imaging Multi-polarization Photon-counting Lidar (SIMPL) is a multi-beam, micropulse airborne laser altimeter that acquires active and passive polarimetric optical remote sensing measurements at visible and near-infrared wavelengths. SIMPL was developed to demonstrate advanced measurement approaches of potential benefit for improved, more efficient spaceflight laser altimeter missions. SIMPL data have been acquired for wide diversity of forest types in the summers of 2010 and 2011 in order to assess the potential of its novel capabilities for characterization of vegetation structure and composition. On each of its four beams SIMPL provides highly-resolved measurements of forest canopy structure by detecting single-photons with 15 cm ranging precision using a narrow-beam system operating at a laser repetition rate of 11 kHz. Associated with that ranging data SIMPL provides eight amplitude parameters per beam unlike the single amplitude provided by typical laser altimeters. Those eight parameters are received energy that is parallel and perpendicular to that of the plane-polarized transmit pulse at 532 nm (green) and 1064 nm (near IR), for both the active laser backscatter retro-reflectance and the passive solar bi-directional reflectance. This poster presentation will cover the instrument architecture and highlight the performance of the SIMPL instrument with examples taken from measurements for several sites with distinct canopy structures and compositions. Specific performance areas such as probability of detection, after pulsing, and dead time, will be highlighted and addressed, along with examples of their impact on the measurements and how they limit the ability to accurately model and recover the canopy properties. To assess the sensitivity of SIMPL's measurements to canopy properties an instrument model has been implemented in the FLIGHT radiative transfer code, based on Monte Carlo simulation of photon transport. SIMPL data collected in 2010 over the Smithsonian Environmental Research Center, MD are currently being modelled and compared to other remote sensing and in situ data sets. Results on the adaptation of FLIGHT to model micropulse, single'photon ranging measurements are presented elsewhere at this conference. NASA's ICESat-2 spaceflight mission, scheduled for launch in 2016, will utilize a multi-beam, micropulse, single-photon ranging measurement approach (although non-polarimetric and only at 532 nm). Insights gained from the analysis and modelling of SIMPL data will help guide preparations for that mission, including development of calibration/validation plans and algorithms for the estimation of forest biophysical parameters.

A high resolution and high speed 3D imaging system and its application on ATR

NASA Astrophysics Data System (ADS)

Lu, Thomas T.; Chao, Tien-Hsin

2006-04-01

The paper presents an advanced 3D imaging system based on a combination of stereo vision and light projection methods. A single digital camera is used to take only one shot of the object and reconstruct the 3D model of an object. The stereo vision is achieved by employing a prism and mirror setup to split the views and combine them side by side in the camera. The advantage of this setup is its simple system architecture, easy synchronization, fast 3D imaging speed and high accuracy. The 3D imaging algorithms and potential applications are discussed. For ATR applications, it is critically important to extract maximum information for the potential targets and to separate the targets from the background and clutter noise. The added dimension of a 3D model provides additional features of surface profile, range information of the target. It is capable of removing the false shadow from camouflage and reveal the 3D profile of the object. It also provides arbitrary viewing angles and distances for training the filter bank for invariant ATR. The system architecture can be scaled to take large objects and to perform area 3D modeling onboard a UAV.

Improving color constancy by discounting the variation of camera spectral sensitivity

NASA Astrophysics Data System (ADS)

Gao, Shao-Bing; Zhang, Ming; Li, Chao-Yi; Li, Yong-Jie

2017-08-01

It is an ill-posed problem to recover the true scene colors from a color biased image by discounting the effects of scene illuminant and camera spectral sensitivity (CSS) at the same time. Most color constancy (CC) models have been designed to first estimate the illuminant color, which is then removed from the color biased image to obtain an image taken under white light, without the explicit consideration of CSS effect on CC. This paper first studies the CSS effect on illuminant estimation arising in the inter-dataset-based CC (inter-CC), i.e., training a CC model on one dataset and then testing on another dataset captured by a distinct CSS. We show the clear degradation of existing CC models for inter-CC application. Then a simple way is proposed to overcome such degradation by first learning quickly a transform matrix between the two distinct CSSs (CSS-1 and CSS-2). The learned matrix is then used to convert the data (including the illuminant ground truth and the color biased images) rendered under CSS-1 into CSS-2, and then train and apply the CC model on the color biased images under CSS-2, without the need of burdensome acquiring of training set under CSS-2. Extensive experiments on synthetic and real images show that our method can clearly improve the inter-CC performance for traditional CC algorithms. We suggest that by taking the CSS effect into account, it is more likely to obtain the truly color constant images invariant to the changes of both illuminant and camera sensors.

Finding regions of interest in pathological images: an attentional model approach

NASA Astrophysics Data System (ADS)

Gómez, Francisco; Villalón, Julio; Gutierrez, Ricardo; Romero, Eduardo

2009-02-01

This paper introduces an automated method for finding diagnostic regions-of-interest (RoIs) in histopathological images. This method is based on the cognitive process of visual selective attention that arises during a pathologist's image examination. Specifically, it emulates the first examination phase, which consists in a coarse search for tissue structures at a "low zoom" to separate the image into relevant regions.1 The pathologist's cognitive performance depends on inherent image visual cues - bottom-up information - and on acquired clinical medicine knowledge - top-down mechanisms -. Our pathologist's visual attention model integrates the latter two components. The selected bottom-up information includes local low level features such as intensity, color, orientation and texture information. Top-down information is related to the anatomical and pathological structures known by the expert. A coarse approximation to these structures is achieved by an oversegmentation algorithm, inspired by psychological grouping theories. The algorithm parameters are learned from an expert pathologist's segmentation. Top-down and bottom-up integration is achieved by calculating a unique index for each of the low level characteristics inside the region. Relevancy is estimated as a simple average of these indexes. Finally, a binary decision rule defines whether or not a region is interesting. The method was evaluated on a set of 49 images using a perceptually-weighted evaluation criterion, finding a quality gain of 3dB when comparing to a classical bottom-up model of attention.

Bayesian depth estimation from monocular natural images.

PubMed

Su, Che-Chun; Cormack, Lawrence K; Bovik, Alan C

2017-05-01

Estimating an accurate and naturalistic dense depth map from a single monocular photographic image is a difficult problem. Nevertheless, human observers have little difficulty understanding the depth structure implied by photographs. Two-dimensional (2D) images of the real-world environment contain significant statistical information regarding the three-dimensional (3D) structure of the world that the vision system likely exploits to compute perceived depth, monocularly as well as binocularly. Toward understanding how this might be accomplished, we propose a Bayesian model of monocular depth computation that recovers detailed 3D scene structures by extracting reliable, robust, depth-sensitive statistical features from single natural images. These features are derived using well-accepted univariate natural scene statistics (NSS) models and recent bivariate/correlation NSS models that describe the relationships between 2D photographic images and their associated depth maps. This is accomplished by building a dictionary of canonical local depth patterns from which NSS features are extracted as prior information. The dictionary is used to create a multivariate Gaussian mixture (MGM) likelihood model that associates local image features with depth patterns. A simple Bayesian predictor is then used to form spatial depth estimates. The depth results produced by the model, despite its simplicity, correlate well with ground-truth depths measured by a current-generation terrestrial light detection and ranging (LIDAR) scanner. Such a strong form of statistical depth information could be used by the visual system when creating overall estimated depth maps incorporating stereopsis, accommodation, and other conditions. Indeed, even in isolation, the Bayesian predictor delivers depth estimates that are competitive with state-of-the-art "computer vision" methods that utilize highly engineered image features and sophisticated machine learning algorithms.

HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR

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

Schneider, Michael D.; Dawson, William A.; Hogg, David W.

2015-07-01

Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxymore » properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.« less

Development of the local magnification method for quantitative evaluation of endoscope geometric distortion

NASA Astrophysics Data System (ADS)

Wang, Quanzeng; Cheng, Wei-Chung; Suresh, Nitin; Hua, Hong

2016-05-01

With improved diagnostic capabilities and complex optical designs, endoscopic technologies are advancing. As one of the several important optical performance characteristics, geometric distortion can negatively affect size estimation and feature identification related diagnosis. Therefore, a quantitative and simple distortion evaluation method is imperative for both the endoscopic industry and the medical device regulatory agent. However, no such method is available yet. While the image correction techniques are rather mature, they heavily depend on computational power to process multidimensional image data based on complex mathematical model, i.e., difficult to understand. Some commonly used distortion evaluation methods, such as the picture height distortion (DPH) or radial distortion (DRAD), are either too simple to accurately describe the distortion or subject to the error of deriving a reference image. We developed the basic local magnification (ML) method to evaluate endoscope distortion. Based on the method, we also developed ways to calculate DPH and DRAD. The method overcomes the aforementioned limitations, has clear physical meaning in the whole field of view, and can facilitate lesion size estimation during diagnosis. Most importantly, the method can facilitate endoscopic technology to market and potentially be adopted in an international endoscope standard.

Development of virtual patient models for permanent implant brachytherapy Monte Carlo dose calculations: interdependence of CT image artifact mitigation and tissue assignment.

PubMed

Miksys, N; Xu, C; Beaulieu, L; Thomson, R M

2015-08-07

This work investigates and compares CT image metallic artifact reduction (MAR) methods and tissue assignment schemes (TAS) for the development of virtual patient models for permanent implant brachytherapy Monte Carlo (MC) dose calculations. Four MAR techniques are investigated to mitigate seed artifacts from post-implant CT images of a homogeneous phantom and eight prostate patients: a raw sinogram approach using the original CT scanner data and three methods (simple threshold replacement (STR), 3D median filter, and virtual sinogram) requiring only the reconstructed CT image. Virtual patient models are developed using six TAS ranging from the AAPM-ESTRO-ABG TG-186 basic approach of assigning uniform density tissues (resulting in a model not dependent on MAR) to more complex models assigning prostate, calcification, and mixtures of prostate and calcification using CT-derived densities. The EGSnrc user-code BrachyDose is employed to calculate dose distributions. All four MAR methods eliminate bright seed spot artifacts, and the image-based methods provide comparable mitigation of artifacts compared with the raw sinogram approach. However, each MAR technique has limitations: STR is unable to mitigate low CT number artifacts, the median filter blurs the image which challenges the preservation of tissue heterogeneities, and both sinogram approaches introduce new streaks. Large local dose differences are generally due to differences in voxel tissue-type rather than mass density. The largest differences in target dose metrics (D90, V100, V150), over 50% lower compared to the other models, are when uncorrected CT images are used with TAS that consider calcifications. Metrics found using models which include calcifications are generally a few percent lower than prostate-only models. Generally, metrics from any MAR method and any TAS which considers calcifications agree within 6%. Overall, the studied MAR methods and TAS show promise for further retrospective MC dose calculation studies for various permanent implant brachytherapy treatments.

MO-AB-BRA-02: A Novel Scatter Imaging Modality for Real-Time Image Guidance During Lung SBRT

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

Redler, G; Bernard, D; Templeton, A

2015-06-15

Purpose: A novel scatter imaging modality is developed and its feasibility for image-guided radiation therapy (IGRT) during stereotactic body radiation therapy (SBRT) for lung cancer patients is assessed using analytic and Monte Carlo models as well as experimental testing. Methods: During treatment, incident radiation interacts and scatters from within the patient. The presented methodology forms an image of patient anatomy from the scattered radiation for real-time localization of the treatment target. A radiographic flat panel-based pinhole camera provides spatial information regarding the origin of detected scattered radiation. An analytical model is developed, which provides a mathematical formalism for describing themore » scatter imaging system. Experimental scatter images are acquired by irradiating an object using a Varian TrueBeam accelerator. The differentiation between tissue types is investigated by imaging simple objects of known compositions (water, lung, and cortical bone equivalent). A lung tumor phantom, simulating materials and geometry encountered during lung SBRT treatments, is fabricated and imaged to investigate image quality for various quantities of delivered radiation. Monte Carlo N-Particle (MCNP) code is used for validation and testing by simulating scatter image formation using the experimental pinhole camera setup. Results: Analytical calculations, MCNP simulations, and experimental results when imaging the water, lung, and cortical bone equivalent objects show close agreement, thus validating the proposed models and demonstrating that scatter imaging differentiates these materials well. Lung tumor phantom images have sufficient contrast-to-noise ratio (CNR) to clearly distinguish tumor from surrounding lung tissue. CNR=4.1 and CNR=29.1 for 10MU and 5000MU images (equivalent to 0.5 and 250 second images), respectively. Conclusion: Lung SBRT provides favorable treatment outcomes, but depends on accurate target localization. A comprehensive approach, employing multiple simulation techniques and experiments, is taken to demonstrate the feasibility of a novel scatter imaging modality for the necessary real-time image guidance.« less

A spatially adaptive spectral re-ordering technique for lossless coding of hyper-spectral images

NASA Technical Reports Server (NTRS)

Memon, Nasir D.; Galatsanos, Nikolas

1995-01-01

In this paper, we propose a new approach, applicable to lossless compression of hyper-spectral images, that alleviates some limitations of linear prediction as applied to this problem. According to this approach, an adaptive re-ordering of the spectral components of each pixel is performed prior to prediction and encoding. This re-ordering adaptively exploits, on a pixel-by pixel basis, the presence of inter-band correlations for prediction. Furthermore, the proposed approach takes advantage of spatial correlations, and does not introduce any coding overhead to transmit the order of the spectral bands. This is accomplished by using the assumption that two spatially adjacent pixels are expected to have similar spectral relationships. We thus have a simple technique to exploit spectral and spatial correlations in hyper-spectral data sets, leading to compression performance improvements as compared to our previously reported techniques for lossless compression. We also look at some simple error modeling techniques for further exploiting any structure that remains in the prediction residuals prior to entropy coding.

Increasing the realism of a laparoscopic box trainer: a simple, inexpensive method.

PubMed

Hull, Louise; Kassab, Eva; Arora, Sonal; Kneebone, Roger

2010-01-01

Simulation-based training in medical education is increasing. Realism is an integral element of creating an engaging, effective training environment. Although physical trainers offer a low-cost alternative to expensive virtual reality (VR) simulators, many lack in realism. The aim of this research was to enhance the realism of a laparoscopic box trainer by using a simple, inexpensive method. Digital images of the abdominal cavity were captured from a VR simulator. The images were printed onto a laminated card that lined the bottom and sides of the box-trainer cavity. The standard black neoprene material that encloses the abdominal cavity was replaced with a skin-colored silicon model. The realism of the modified box trainer was assessed by surgeons, using quantitative and qualitative methodologies. Results suggest that the modified box trainer was more realistic than a standard box trainer alone. Incorporating this technique in the training of laparoscopic skills is an inexpensive means of emulating surgical reality that may enhance the engagement of the learner in simulation.

Establishment of a simple and quantitative immunospot assay for detecting anti-type II collagen antibody using an infrared fluorescence imaging system (IFIS).

PubMed

Ota, Shusuke; Kanazawa, Satoshi; Kobayashi, Masaaki; Otsuka, Takanobu; Okamoto, Takashi

2005-04-01

Antibodies to type II collagen (col II) have been detected in patients with rheumatoid arthritis and in animal models of collagen induced arthritis. Here, we describe a novel method to detect anti-col II antibodies using an immunospot assay with an infrared fluorescence imaging system. This method showed very high sensitivity and specificity, and was simple, with low background levels. It also showed higher reproducibility and linearity, with a dynamic range of approximately 500-fold, than the conventional immunospot assay with enhanced chemiluminescence detection. Using this method we were able to demonstrate the antibody affinity maturation process in mice immunized with col II. In these immunized mice, although cross-reactive antibodies reacting with other collagen species were detected in earlier stages of immunization, the titers of cross-reactive antibodies rapidly diminished after the antigen boost, concomitantly with the elevation of the anti-col II antibody. The method and its possible applications are discussed.

A robust collagen scoring method for human liver fibrosis by second harmonic microscopy.

PubMed

Guilbert, Thomas; Odin, Christophe; Le Grand, Yann; Gailhouste, Luc; Turlin, Bruno; Ezan, Frédérick; Désille, Yoann; Baffet, Georges; Guyader, Dominique

2010-12-06

Second Harmonic Generation (SHG) microscopy offers the opportunity to image collagen of type I without staining. We recently showed that a simple scoring method, based on SHG images of histological human liver biopsies, correlates well with the Metavir assessment of fibrosis level (Gailhouste et al., J. Hepatol., 2010). In this article, we present a detailed study of this new scoring method with two different objective lenses. By using measurements of the objectives point spread functions and of the photomultiplier gain, and a simple model of the SHG intensity, we show that our scoring method, applied to human liver biopsies, is robust to the objective's numerical aperture (NA) for low NA, the choice of the reference sample and laser power, and the spatial sampling rate. The simplicity and robustness of our collagen scoring method may open new opportunities in the quantification of collagen content in different organs, which is of main importance in providing diagnostic information and evaluation of therapeutic efficiency.

Image-based Modeling of PSF Deformation with Application to Limited Angle PET Data

PubMed Central

Matej, Samuel; Li, Yusheng; Panetta, Joseph; Karp, Joel S.; Surti, Suleman

2016-01-01

The point-spread-functions (PSFs) of reconstructed images can be deformed due to detector effects such as resolution blurring and parallax error, data acquisition geometry such as insufficient sampling or limited angular coverage in dual-panel PET systems, or reconstruction imperfections/simplifications. PSF deformation decreases quantitative accuracy and its spatial variation lowers consistency of lesion uptake measurement across the imaging field-of-view (FOV). This can be a significant problem with dual panel PET systems even when using TOF data and image reconstruction models of the detector and data acquisition process. To correct for the spatially variant reconstructed PSF distortions we propose to use an image-based resolution model (IRM) that includes such image PSF deformation effects. Originally the IRM was mostly used for approximating data resolution effects of standard PET systems with full angular coverage in a computationally efficient way, but recently it was also used to mitigate effects of simplified geometric projectors. Our work goes beyond this by including into the IRM reconstruction imperfections caused by combination of the limited angle, parallax errors, and any other (residual) deformation effects and testing it for challenging dual panel data with strongly asymmetric and variable PSF deformations. We applied and tested these concepts using simulated data based on our design for a dedicated breast imaging geometry (B-PET) consisting of dual-panel, time-of-flight (TOF) detectors. We compared two image-based resolution models; i) a simple spatially invariant approximation to PSF deformation, which captures only the general PSF shape through an elongated 3D Gaussian function, and ii) a spatially variant model using a Gaussian mixture model (GMM) to more accurately capture the asymmetric PSF shape in images reconstructed from data acquired with the B-PET scanner geometry. Results demonstrate that while both IRMs decrease the overall uptake bias in the reconstructed image, the second one with the spatially variant and accurate PSF shape model is also able to ameliorate the spatially variant deformation effects to provide consistent uptake results independent of the lesion location within the FOV. PMID:27812222

A New Global Core Plasma Model of the Plasmasphere

NASA Technical Reports Server (NTRS)

Gallagher, D. L.; Comfort, R. H.; Craven, P. D.

2014-01-01

The Global Core Plasma Model (GCPM) is the first empirical model for thermal inner magnetospheric plasma designed to integrate previous models and observations into a continuous in value and gradient representation of typical total densities. New information about the plasmasphere, in particular, make possible significant improvement. The IMAGE Mission Radio Plasma Imager (RPI) has obtained the first observations of total plasma densities along magnetic field lines in the plasmasphere and polar cap. Dynamics Explorer 1 Retarding Ion Mass Spectrometer (RIMS) has provided densities in temperatures in the plasmasphere for 5 ion species. These and other works enable a new more detailed empirical model of thermal in the inner magnetosphere that will be presented. Specifically shown here are the inner-plasmasphere RIMS measurements, radial fits to densities and temperatures for H(+), He(+), He(++), O(+), and O(+) and the error associated with these initial simple fits. Also shown are more subtle dependencies on the f10.7 P-value (see Richards et al. [1994]).

relaxGUI: a new software for fast and simple NMR relaxation data analysis and calculation of ps-ns and μs motion of proteins.

PubMed

Bieri, Michael; d'Auvergne, Edward J; Gooley, Paul R

2011-06-01

Investigation of protein dynamics on the ps-ns and μs-ms timeframes provides detailed insight into the mechanisms of enzymes and the binding properties of proteins. Nuclear magnetic resonance (NMR) is an excellent tool for studying protein dynamics at atomic resolution. Analysis of relaxation data using model-free analysis can be a tedious and time consuming process, which requires good knowledge of scripting procedures. The software relaxGUI was developed for fast and simple model-free analysis and is fully integrated into the software package relax. It is written in Python and uses wxPython to build the graphical user interface (GUI) for maximum performance and multi-platform use. This software allows the analysis of NMR relaxation data with ease and the generation of publication quality graphs as well as color coded images of molecular structures. The interface is designed for simple data analysis and management. The software was tested and validated against the command line version of relax.

Optically sectioned in vivo imaging with speckle illumination HiLo microscopy

PubMed Central

Lim, Daryl; Ford, Tim N.; Chu, Kengyeh K.; Mertz, Jerome

2011-01-01

We present a simple wide-field imaging technique, called HiLo microscopy, that is capable of producing optically sectioned images in real time, comparable in quality to confocal laser scanning microscopy. The technique is based on the fusion of two raw images, one acquired with speckle illumination and another with standard uniform illumination. The fusion can be numerically adjusted, using a single parameter, to produce optically sectioned images of varying thicknesses with the same raw data. Direct comparison between our HiLo microscope and a commercial confocal laser scanning microscope is made on the basis of sectioning strength and imaging performance. Specifically, we show that HiLo and confocal 3-D imaging of a GFP-labeled mouse brain hippocampus are comparable in quality. Moreover, HiLo microscopy is capable of faster, near video rate imaging over larger fields of view than attainable with standard confocal microscopes. The goal of this paper is to advertise the simplicity, robustness, and versatility of HiLo microscopy, which we highlight with in vivo imaging of common model organisms including planaria, C. elegans, and zebrafish. PMID:21280920

Optically sectioned in vivo imaging with speckle illumination HiLo microscopy.

PubMed

Lim, Daryl; Ford, Tim N; Chu, Kengyeh K; Mertz, Jerome

2011-01-01

We present a simple wide-field imaging technique, called HiLo microscopy, that is capable of producing optically sectioned images in real time, comparable in quality to confocal laser scanning microscopy. The technique is based on the fusion of two raw images, one acquired with speckle illumination and another with standard uniform illumination. The fusion can be numerically adjusted, using a single parameter, to produce optically sectioned images of varying thicknesses with the same raw data. Direct comparison between our HiLo microscope and a commercial confocal laser scanning microscope is made on the basis of sectioning strength and imaging performance. Specifically, we show that HiLo and confocal 3-D imaging of a GFP-labeled mouse brain hippocampus are comparable in quality. Moreover, HiLo microscopy is capable of faster, near video rate imaging over larger fields of view than attainable with standard confocal microscopes. The goal of this paper is to advertise the simplicity, robustness, and versatility of HiLo microscopy, which we highlight with in vivo imaging of common model organisms including planaria, C. elegans, and zebrafish.

Optically sectioned in vivo imaging with speckle illumination HiLo microscopy

NASA Astrophysics Data System (ADS)

Lim, Daryl; Ford, Tim N.; Chu, Kengyeh K.; Mertz, Jerome

2011-01-01

We present a simple wide-field imaging technique, called HiLo microscopy, that is capable of producing optically sectioned images in real time, comparable in quality to confocal laser scanning microscopy. The technique is based on the fusion of two raw images, one acquired with speckle illumination and another with standard uniform illumination. The fusion can be numerically adjusted, using a single parameter, to produce optically sectioned images of varying thicknesses with the same raw data. Direct comparison between our HiLo microscope and a commercial confocal laser scanning microscope is made on the basis of sectioning strength and imaging performance. Specifically, we show that HiLo and confocal 3-D imaging of a GFP-labeled mouse brain hippocampus are comparable in quality. Moreover, HiLo microscopy is capable of faster, near video rate imaging over larger fields of view than attainable with standard confocal microscopes. The goal of this paper is to advertise the simplicity, robustness, and versatility of HiLo microscopy, which we highlight with in vivo imaging of common model organisms including planaria, C. elegans, and zebrafish.

Measuring bacterial cells size with AFM

PubMed Central

Osiro, Denise; Filho, Rubens Bernardes; Assis, Odilio Benedito Garrido; Jorge, Lúcio André de Castro; Colnago, Luiz Alberto

2012-01-01

Atomic Force Microscopy (AFM) can be used to obtain high-resolution topographical images of bacteria revealing surface details and cell integrity. During scanning however, the interactions between the AFM probe and the membrane results in distortion of the images. Such distortions or artifacts are the result of geometrical effects related to bacterial cell height, specimen curvature and the AFM probe geometry. The most common artifact in imaging is surface broadening, what can lead to errors in bacterial sizing. Several methods of correction have been proposed to compensate for these artifacts and in this study we describe a simple geometric model for the interaction between the tip (a pyramidal shaped AFM probe) and the bacterium (Escherichia coli JM-109 strain) to minimize the enlarging effect. Approaches to bacteria immobilization and examples of AFM images analysis are also described. PMID:24031837

Particle image velocimetry based on wavelength division multiplexing

NASA Astrophysics Data System (ADS)

Tang, Chunxiao; Li, Enbang; Li, Hongqiang

2018-01-01

This paper introduces a technical approach of wavelength division multiplexing (WDM) based particle image velocimetry (PIV). It is designed to measure transient flows with different scales of velocity by capturing multiple particle images in one exposure. These images are separated by different wavelengths, and thus the pulse separation time is not influenced by the frame rate of the camera. A triple-pulsed PIV system has been created in order to prove the feasibility of WDM-PIV. This is demonstrated in a sieve plate extraction column model by simultaneously measuring the fast flow in the downcomer and the slow vortices inside the plates. A simple displacement/velocity field combination method has also been developed. The constraints imposed by WDM-PIV are limited wavelength choices of available light sources and cameras. The usage of WDM technique represents a feasible way to realize multiple-pulsed PIV.

Statistical mechanics of simple models of protein folding and design.

PubMed Central

Pande, V S; Grosberg, A Y; Tanaka, T

1997-01-01

It is now believed that the primary equilibrium aspects of simple models of protein folding are understood theoretically. However, current theories often resort to rather heavy mathematics to overcome some technical difficulties inherent in the problem or start from a phenomenological model. To this end, we take a new approach in this pedagogical review of the statistical mechanics of protein folding. The benefit of our approach is a drastic mathematical simplification of the theory, without resort to any new approximations or phenomenological prescriptions. Indeed, the results we obtain agree precisely with previous calculations. Because of this simplification, we are able to present here a thorough and self contained treatment of the problem. Topics discussed include the statistical mechanics of the random energy model (REM), tests of the validity of REM as a model for heteropolymer freezing, freezing transition of random sequences, phase diagram of designed ("minimally frustrated") sequences, and the degree to which errors in the interactions employed in simulations of either folding and design can still lead to correct folding behavior. Images FIGURE 2 FIGURE 3 FIGURE 4 FIGURE 6 PMID:9414231

Crosstalk in automultiscopic 3-D displays: blessing in disguise?

NASA Astrophysics Data System (ADS)

Jain, Ashish; Konrad, Janusz

2007-02-01

Most of 3-D displays suffer from interocular crosstalk, i.e., the perception of an unintended view in addition to intended one. The resulting "ghosting" at high-contrast object boundaries is objectionable and interferes with depth perception. In automultiscopic (no glasses, multiview) displays using microlenses or parallax barrier, the effect is compounded since several unintended views may be perceived at once. However, we recently discovered that crosstalk in automultiscopic displays can be also beneficial. Since spatial multiplexing of views in order to prepare a composite image for automultiscopic viewing involves sub-sampling, prior anti-alias filtering is required. To date, anti-alias filter design has ignored the presence of crosstalk in automultiscopic displays. In this paper, we propose a simple multiplexing model that takes crosstalk into account. Using this model we derive a mathematical expression for the spectrum of single view with crosstalk, and we show that it leads to reduced spectral aliasing compared to crosstalk-free case. We then propose a new criterion for the characterization of ideal anti-alias pre-filter. In the experimental part, we describe a simple method to measure optical crosstalk between views using digital camera. We use the measured crosstalk parameters to find the ideal frequency response of anti-alias filter and we design practical digital filters approximating this response. Having applied the designed filters to a number of multiview images prior to multiplexing, we conclude that, due to their increased bandwidth, the filters lead to visibly sharper 3-D images without increasing aliasing artifacts.

Quantification of the cerebrospinal fluid from a new whole body MRI sequence

NASA Astrophysics Data System (ADS)

Lebret, Alain; Petit, Eric; Durning, Bruno; Hodel, Jérôme; Rahmouni, Alain; Decq, Philippe

2012-03-01

Our work aims to develop a biomechanical model of hydrocephalus both intended to perform clinical research and to assist the neurosurgeon in diagnosis decisions. Recently, we have defined a new MR imaging sequence based on SPACE (Sampling Perfection with Application optimized Contrast using different flip-angle Evolution). On these images, the cerebrospinal fluid (CSF) appears as a homogeneous hypersignal. Therefore such images are suitable for segmentation and for volume assessment of the CSF. In this paper we present a fully automatic 3D segmentation of such SPACE MRI sequences. We choose a topological approach considering that CSF can be modeled as a simply connected object (i.e. a filled sphere). First an initial object which must be strictly included in the CSF and homotopic to a filled sphere, is determined by using a moment-preserving thresholding. Then a priority function based on an Euclidean distance map is computed in order to control the thickening process that adds "simple points" to the initial thresholded object. A point is called simple if its addition or its suppression does not result in change of topology neither for the object, nor for the background. The method is validated by measuring fluid volume of brain phantoms and by comparing our volume assessments on clinical data to those derived from a segmentation controlled by expert physicians. Then we show that a distinction between pathological cases and healthy adult people can be achieved by a linear discriminant analysis on volumes of the ventricular and intracranial subarachnoid spaces.

Bladder control, urgency, and urge incontinence: evidence from functional brain imaging.

PubMed

Griffiths, Derek; Tadic, Stasa D

2008-01-01

To review brain imaging studies of bladder control in subjects with normal control and urge incontinence; to define a simple model of supraspinal bladder control; and to propose a neural correlate of urgency and possible origins of urge incontinence. Review of published reports of brain imaging relevant to urine storage, and secondary analyses of our own recent observations. In a simple model of normal urine storage, bladder and urethral afferents received in the periaqueductal gray (PAG) are mapped in the insula, forming the basis of sensation; the anterior cingulate gyrus (ACG) provides monitoring and control; the prefrontal cortex makes voiding decisions. The net result, as the bladder fills, is inhibition of the pontine micturition center (PMC) and of voiding, together with gradual increase in insular response, corresponding to increasing desire to void. In urge-incontinent subjects, brain responses differ. At large bladder volumes and strong sensation, but without detrusor overactivity (DO), most cortical responses become exaggerated, especially in ACG. This may be both a learned reaction to previous incontinence episodes and the neural correlate of urgency. The neural signature of DO itself seems to be prefrontal deactivation. Possible causes of urge incontinence include dysfunction of prefrontal cortex or limbic system, suggested by weak responses and/or deactivation, as well as abnormal afferent signals or re-emergence of infantile reflexes. Bladder control depends on an extensive network of brain regions. Dysfunction in various parts may contribute to urge incontinence, suggesting that there are different phenotypes requiring different treatments. (c) 2007 Wiley-Liss, Inc.

Imaging Gravity Waves in Lower Stratospheric AMSU-A Radiances. Part 1: Simple Forward Model

DTIC Science & Technology

2006-08-14

brightening” of microwave radiances acquired from purely vertical background temperature profiles by cross- track scanners. Waves propagating along track...three-dimensional wave fields. For example, some limb sensors return high- resolution vertical temperature profiles with wave oscilla- tions...provide only ver- tical profiles of wave oscillations, similar to radiosonde and rocketsonde data. Similarly, limb-tracking measurements from the

The Wernicke area

PubMed Central

2015-01-01

The term “Wernicke's area” is most often used as an anatomical label for the gyri forming the lower posterior left sylvian fissure. Although traditionally this region was held to support language comprehension, modern imaging and neuropsychological studies converge on the conclusion that this region plays a much larger role in speech production. This evidence is briefly reviewed, and a simple schematic model of posterior cortical language processing is described. PMID:26567270

An Active Patch Model for Real World Texture and Appearance Classification

PubMed Central

Mao, Junhua; Zhu, Jun; Yuille, Alan L.

2014-01-01

This paper addresses the task of natural texture and appearance classification. Our goal is to develop a simple and intuitive method that performs at state of the art on datasets ranging from homogeneous texture (e.g., material texture), to less homogeneous texture (e.g., the fur of animals), and to inhomogeneous texture (the appearance patterns of vehicles). Our method uses a bag-of-words model where the features are based on a dictionary of active patches. Active patches are raw intensity patches which can undergo spatial transformations (e.g., rotation and scaling) and adjust themselves to best match the image regions. The dictionary of active patches is required to be compact and representative, in the sense that we can use it to approximately reconstruct the images that we want to classify. We propose a probabilistic model to quantify the quality of image reconstruction and design a greedy learning algorithm to obtain the dictionary. We classify images using the occurrence frequency of the active patches. Feature extraction is fast (about 100 ms per image) using the GPU. The experimental results show that our method improves the state of the art on a challenging material texture benchmark dataset (KTH-TIPS2). To test our method on less homogeneous or inhomogeneous images, we construct two new datasets consisting of appearance image patches of animals and vehicles cropped from the PASCAL VOC dataset. Our method outperforms competing methods on these datasets. PMID:25531013

A novel vehicle tracking algorithm based on mean shift and active contour model in complex environment

NASA Astrophysics Data System (ADS)

Cai, Lei; Wang, Lin; Li, Bo; Zhang, Libao; Lv, Wen

2017-06-01

Vehicle tracking technology is currently one of the most active research topics in machine vision. It is an important part of intelligent transportation system. However, in theory and technology, it still faces many challenges including real-time and robustness. In video surveillance, the targets need to be detected in real-time and to be calculated accurate position for judging the motives. The contents of video sequence images and the target motion are complex, so the objects can't be expressed by a unified mathematical model. Object-tracking is defined as locating the interest moving target in each frame of a piece of video. The current tracking technology can achieve reliable results in simple environment over the target with easy identified characteristics. However, in more complex environment, it is easy to lose the target because of the mismatch between the target appearance and its dynamic model. Moreover, the target usually has a complex shape, but the tradition target tracking algorithm usually represents the tracking results by simple geometric such as rectangle or circle, so it cannot provide accurate information for the subsequent upper application. This paper combines a traditional object-tracking technology, Mean-Shift algorithm, with a kind of image segmentation algorithm, Active-Contour model, to get the outlines of objects while the tracking process and automatically handle topology changes. Meanwhile, the outline information is used to aid tracking algorithm to improve it.

Robustifying blind image deblurring methods by simple filters

NASA Astrophysics Data System (ADS)

Liu, Yan; Zeng, Xiangrong; Huangpeng, Qizi; Fan, Jun; Zhou, Jinglun; Feng, Jing

2016-07-01

The state-of-the-art blind image deblurring (BID) methods are sensitive to noise, and most of them can deal with only small levels of Gaussian noise. In this paper, we use simple filters to present a robust BID framework which is able to robustify exiting BID methods to high-level Gaussian noise or/and Non-Gaussian noise. Experiments on images in presence of Gaussian noise, impulse noise (salt-and-pepper noise and random-valued noise) and mixed Gaussian-impulse noise, and a real-world blurry and noisy image show that the proposed method can faster estimate sharper kernels and better images, than that obtained by other methods.

Spatial land-use inventory, modeling, and projection/Denver metropolitan area, with inputs from existing maps, airphotos, and LANDSAT imagery

NASA Technical Reports Server (NTRS)

Tom, C.; Miller, L. D.; Christenson, J. W.

1978-01-01

A landscape model was constructed with 34 land-use, physiographic, socioeconomic, and transportation maps. A simple Markov land-use trend model was constructed from observed rates of change and nonchange from photointerpreted 1963 and 1970 airphotos. Seven multivariate land-use projection models predicting 1970 spatial land-use changes achieved accuracies from 42 to 57 percent. A final modeling strategy was designed, which combines both Markov trend and multivariate spatial projection processes. Landsat-1 image preprocessing included geometric rectification/resampling, spectral-band, and band/insolation ratioing operations. A new, systematic grid-sampled point training-set approach proved to be useful when tested on the four orginal MSS bands, ten image bands and ratios, and all 48 image and map variables (less land use). Ten variable accuracy was raised over 15 percentage points from 38.4 to 53.9 percent, with the use of the 31 ancillary variables. A land-use classification map was produced with an optimal ten-channel subset of four image bands and six ancillary map variables. Point-by-point verification of 331,776 points against a 1972/1973 U.S. Geological Survey (UGSG) land-use map prepared with airphotos and the same classification scheme showed average first-, second-, and third-order accuracies of 76.3, 58.4, and 33.0 percent, respectively.

A CCA+ICA based model for multi-task brain imaging data fusion and its application to schizophrenia.

PubMed

Sui, Jing; Adali, Tülay; Pearlson, Godfrey; Yang, Honghui; Sponheim, Scott R; White, Tonya; Calhoun, Vince D

2010-05-15

Collection of multiple-task brain imaging data from the same subject has now become common practice in medical imaging studies. In this paper, we propose a simple yet effective model, "CCA+ICA", as a powerful tool for multi-task data fusion. This joint blind source separation (BSS) model takes advantage of two multivariate methods: canonical correlation analysis and independent component analysis, to achieve both high estimation accuracy and to provide the correct connection between two datasets in which sources can have either common or distinct between-dataset correlation. In both simulated and real fMRI applications, we compare the proposed scheme with other joint BSS models and examine the different modeling assumptions. The contrast images of two tasks: sensorimotor (SM) and Sternberg working memory (SB), derived from a general linear model (GLM), were chosen to contribute real multi-task fMRI data, both of which were collected from 50 schizophrenia patients and 50 healthy controls. When examining the relationship with duration of illness, CCA+ICA revealed a significant negative correlation with temporal lobe activation. Furthermore, CCA+ICA located sensorimotor cortex as the group-discriminative regions for both tasks and identified the superior temporal gyrus in SM and prefrontal cortex in SB as task-specific group-discriminative brain networks. In summary, we compared the new approach to some competitive methods with different assumptions, and found consistent results regarding each of their hypotheses on connecting the two tasks. Such an approach fills a gap in existing multivariate methods for identifying biomarkers from brain imaging data.

A simple and low-cost biofilm quantification method using LED and CMOS image sensor.

PubMed

Kwak, Yeon Hwa; Lee, Junhee; Lee, Junghoon; Kwak, Soo Hwan; Oh, Sangwoo; Paek, Se-Hwan; Ha, Un-Hwan; Seo, Sungkyu

2014-12-01

A novel biofilm detection platform, which consists of a cost-effective red, green, and blue light-emitting diode (RGB LED) as a light source and a lens-free CMOS image sensor as a detector, is designed. This system can measure the diffraction patterns of cells from their shadow images, and gather light absorbance information according to the concentration of biofilms through a simple image processing procedure. Compared to a bulky and expensive commercial spectrophotometer, this platform can provide accurate and reproducible biofilm concentration detection and is simple, compact, and inexpensive. Biofilms originating from various bacterial strains, including Pseudomonas aeruginosa (P. aeruginosa), were tested to demonstrate the efficacy of this new biofilm detection approach. The results were compared with the results obtained from a commercial spectrophotometer. To utilize a cost-effective light source (i.e., an LED) for biofilm detection, the illumination conditions were optimized. For accurate and reproducible biofilm detection, a simple, custom-coded image processing algorithm was developed and applied to a five-megapixel CMOS image sensor, which is a cost-effective detector. The concentration of biofilms formed by P. aeruginosa was detected and quantified by varying the indole concentration, and the results were compared with the results obtained from a commercial spectrophotometer. The correlation value of the results from those two systems was 0.981 (N = 9, P < 0.01) and the coefficients of variation (CVs) were approximately threefold lower at the CMOS image-sensor platform. Copyright © 2014 Elsevier B.V. All rights reserved.

Characterization and Upscaling of Pore Scale Hydrodynamic Mass Transfer

NASA Astrophysics Data System (ADS)

Gouze, P.; Roubinet, D.; Dentz, M.; Planes, V.; Russian, A.

2017-12-01

Imaging reservoir rocks in 3D using X-ray microtomography with spatial resolution ranging from about 1 to 10 mm provides us a unique opportunity not only to characterize pore space geometry but also for simulating hydrodynamical processes. Yet, pores and throats displaying sizes smaller than the resolution cannot be distinguished on the images and must be assigned to a so called microporous phase during the process of image segmentation. Accordingly one simulated mass transfers caused by advection and diffusion in the connected pores (mobile domain) and diffusion in the microporous clusters (immobile domain) using Time Domain Random Walk (TDRW) and developed a set of metrics that can be used to monitor the different mechanisms of transport in the sample, the final objective being of proposing a simple but accurate upscaled 1D model in which the particle travel times in the mobile and immobile domain and the number of mobile-immobile transfer events (called trapping events) are independently distributed random variables characterized by PDFs. For TDRW the solute concentration is represented by the density distribution of non-interacting point-like solute particles which move due to advection and dispersion. The set of metrics derives from different spatial and temporal statistical analyses of the particle motion, and is used for characterizing the particles transport (i) in the mobile domain in relation with the velocity field properties, (ii) in the immobile domain in relation with the structure and the properties of microporous phase and at the mobile-immobile interface. We specifically focused on how to model the trapping frequency and rate into the immobile domain in relation with the structure and the spatial distribution of the mobile-immobile domain interface. This thorough analysis of the particle motion for both simple artificial structures and real rock images allowed us to derive the parametrization of the upscaled 1D model.

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

Patel, Sajan; Petty, Clayton W.; Krafcik, Karen Lee

Electrostatic modes of atomic force microscopy have shown to be non-destructive and relatively simple methods for imaging conductors embedded in insulating polymers. Here we use electrostatic force microscopy to image the dispersion of carbon nanotubes in a latex-based conductive composite, which brings forth features not observed in previously studied systems employing linear polymer films. A fixed-potential model of the probe-nanotube electrostatics is presented which in principle gives access to the conductive nanoparticle's depth and radius, and the polymer film dielectric constant. Comparing this model to the data results in nanotube depths that appear to be slightly above the film–air interface.more » Furthermore, this result suggests that water-mediated charge build-up at the film–air interface may be the source of electrostatic phase contrast in ambient conditions.« less

Virtual Resting Pd/Pa From Coronary Angiography and Blood Flow Modelling: Diagnostic Performance Against Fractional Flow Reserve.

PubMed

Papafaklis, Michail I; Muramatsu, Takashi; Ishibashi, Yuki; Bourantas, Christos V; Fotiadis, Dimitrios I; Brilakis, Emmanouil S; Garcia-Garcia, Héctor M; Escaned, Javier; Serruys, Patrick W; Michalis, Lampros K

2018-03-01

Fractional flow reserve (FFR) has been established as a useful diagnostic tool. The distal coronary pressure to aortic pressure (Pd/Pa) ratio at rest is a simpler physiologic index but also requires the use of the pressure wire, whereas recently proposed virtual functional indices derived from coronary imaging require complex blood flow modelling and/or are time-consuming. Our aim was to test the diagnostic performance of virtual resting Pd/Pa using routine angiographic images and a simple flow model. Three-dimensional quantitative coronary angiography (3D-QCA) was performed in 139 vessels (120 patients) with intermediate lesions assessed by FFR. The resting Pd/Pa for each lesion was assessed by computational fluid dynamics. The discriminatory power of virtual resting Pd/Pa against FFR (reference: ≤0.80) was high (area under the receiver operator characteristic curve [AUC]: 90.5% [95% CI: 85.4-95.6%]). Diagnostic accuracy, sensitivity and specificity for the optimal virtual resting Pd/Pa cut-off (≤0.94) were 84.9%, 90.4% and 81.6%, respectively. Virtual resting Pd/Pa demonstrated superior performance (p<0.001) versus 3D-QCA %area stenosis (AUC: 77.5% [95% CI: 69.8-85.3%]). There was a good correlation between virtual resting Pd/Pa and FFR (r=0.69, p<0.001). Virtual resting Pd/Pa using routine angiographic data and a simple flow model provides fast functional assessment of coronary lesions without requiring the pressure-wire and hyperaemia induction. The high diagnostic performance of virtual resting Pd/Pa for predicting FFR shows promise for using this simple/fast virtual index in clinical practice. Copyright © 2017 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

Hyperspectral and multispectral satellite sensors for mapping chlorophyll content in a Mediterranean Pinus sylvestris L. plantation

NASA Astrophysics Data System (ADS)

Navarro-Cerrillo, Rafael Mª; Trujillo, Jesus; de la Orden, Manuel Sánchez; Hernández-Clemente, Rocío

2014-02-01

A new generation of narrow-band hyperspectral remote sensing data offers an alternative to broad-band multispectral data for the estimation of vegetation chlorophyll content. This paper examines the potential of some of these sensors comparing red-edge and simple ratio indices to develop a rapid and cost-effective system for monitoring Mediterranean pine plantations in Spain. Chlorophyll content retrieval was analyzed with the red-edge R750/R710 index and the simple ratio R800/R560 index using the PROSPECT-5 leaf model and the Discrete Anisotropic Radiative Transfer (DART) and experimental approach. Five sensors were used: AHS, CHRIS/Proba, Hyperion, Landsat and QuickBird. The model simulation results obtained with synthetic spectra demonstrated the feasibility of estimating Ca + b content in conifers using the simple ratio R800/R560 index formulated with different full widths at half maximum (FWHM) at the leaf level. This index yielded a r2 = 0.69 for a FWHM of 30 nm and r2 = 0.55 for a FWHM of 70 nm. Experimental results compared the regression coefficients obtained with various multispectral and hyperspectral images with different spatial resolutions at the stand level. The strongest relationships where obtained using high-resolution hyperspectral images acquired with the AHS sensor (r2 = 0.65) while coarser spatial and spectral resolution images yielded a lower root mean square error (QuickBird r2 = 0.42; Landsat r2 = 0.48; Hyperion r2 = 0.56; CHRIS/Proba r2 = 0.57). This study shows the need to estimate chlorophyll content in forest plantations at the stand level with high spatial and spectral resolution sensors. Nevertheless, these results also show the accuracy obtained with medium-resolution sensors when monitoring physiological processes. Generating biochemical maps at the stand level could play a critical rule in the early detection of forest decline processes enabling their use in precision forestry.

Simple quality assurance method of dynamic tumor tracking with the gimbaled linac system using a light field.

PubMed

Miura, Hideharu; Ozawa, Shuichi; Hayata, Masahiro; Tsuda, Shintaro; Yamada, Kiyoshi; Nagata, Yasushi

2016-09-08

We proposed a simple visual method for evaluating the dynamic tumor tracking (DTT) accuracy of a gimbal mechanism using a light field. A single photon beam was set with a field size of 30 × 30 mm2 at a gantry angle of 90°. The center of a cube phantom was set up at the isocenter of a motion table, and 4D modeling was performed based on the tumor and infrared (IR) marker motion. After 4D modeling, the cube phantom was replaced with a sheet of paper, which was placed perpen-dicularly, and a light field was projected on the sheet of paper. The light field was recorded using a web camera in a treatment room that was as dark as possible. Calculated images from each image obtained using the camera were summed to compose a total summation image. Sinusoidal motion sequences were produced by moving the phantom with a fixed amplitude of 20 mm and different breathing periods of 2, 4, 6, and 8 s. The light field was projected on the sheet of paper under three conditions: with the moving phantom and DTT based on the motion of the phantom, with the moving phantom and non-DTT, and with a stationary phantom for comparison. The values of tracking errors using the light field were 1.12 ± 0.72, 0.31 ± 0.19, 0.27 ± 0.12, and 0.15 ± 0.09 mm for breathing periods of 2, 4, 6, and 8s, respectively. The tracking accuracy showed dependence on the breath-ing period. We proposed a simple quality assurance (QA) process for the tracking accuracy of a gimbal mechanism system using a light field and web camera. Our method can assess the tracking accuracy using a light field without irradiation and clearly visualize distributions like film dosimetry. © 2016 The Authors.

Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT

PubMed Central

Gang, Grace J.; Zbijewski, Wojciech; Webster Stayman, J.; Siewerdsen, Jeffrey H.

2012-01-01

Purpose: Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization. Methods: The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d′). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d′ as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background. Results: Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans. Conclusions: This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose. PMID:22894440

Capillarity Guided Patterning of Microliquids.

PubMed

Kang, Myeongwoo; Park, Woohyun; Na, Sangcheol; Paik, Sang-Min; Lee, Hyunjae; Park, Jae Woo; Kim, Ho-Young; Jeon, Noo Li

2015-06-01

Soft lithography and other techniques have been developed to investigate biological and chemical phenomena as an alternative to photolithography-based patterning methods that have compatibility problems. Here, a simple approach for nonlithographic patterning of liquids and gels inside microchannels is described. Using a design that incorporates strategically placed microstructures inside the channel, microliquids or gels can be spontaneously trapped and patterned when the channel is drained. The ability to form microscale patterns inside microfluidic channels using simple fluid drain motion offers many advantages. This method is geometrically analyzed based on hydrodynamics and verified with simulation and experiments. Various materials (i.e., water, hydrogels, and other liquids) are successfully patterned with complex shapes that are isolated from each other. Multiple cell types are patterned within the gels. Capillarity guided patterning (CGP) is fast, simple, and robust. It is not limited by pattern shape, size, cell type, and material. In a simple three-step process, a 3D cancer model that mimics cell-cell and cell-extracellular matrix interactions is engineered. The simplicity and robustness of the CGP will be attractive for developing novel in vitro models of organ-on-a-chip and other biological experimental platforms amenable to long-term observation of dynamic events using advanced imaging and analytical techniques. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Localization of Diagnostically Relevant Regions of Interest in Whole Slide Images: a Comparative Study.

PubMed

Mercan, Ezgi; Aksoy, Selim; Shapiro, Linda G; Weaver, Donald L; Brunyé, Tad T; Elmore, Joann G

2016-08-01

Whole slide digital imaging technology enables researchers to study pathologists' interpretive behavior as they view digital slides and gain new understanding of the diagnostic medical decision-making process. In this study, we propose a simple yet important analysis to extract diagnostically relevant regions of interest (ROIs) from tracking records using only pathologists' actions as they viewed biopsy specimens in the whole slide digital imaging format (zooming, panning, and fixating). We use these extracted regions in a visual bag-of-words model based on color and texture features to predict diagnostically relevant ROIs on whole slide images. Using a logistic regression classifier in a cross-validation setting on 240 digital breast biopsy slides and viewport tracking logs of three expert pathologists, we produce probability maps that show 74 % overlap with the actual regions at which pathologists looked. We compare different bag-of-words models by changing dictionary size, visual word definition (patches vs. superpixels), and training data (automatically extracted ROIs vs. manually marked ROIs). This study is a first step in understanding the scanning behaviors of pathologists and the underlying reasons for diagnostic errors.

A Bayesian framework for extracting human gait using strong prior knowledge.

PubMed

Zhou, Ziheng; Prügel-Bennett, Adam; Damper, Robert I

2006-11-01

Extracting full-body motion of walking people from monocular video sequences in complex, real-world environments is an important and difficult problem, going beyond simple tracking, whose satisfactory solution demands an appropriate balance between use of prior knowledge and learning from data. We propose a consistent Bayesian framework for introducing strong prior knowledge into a system for extracting human gait. In this work, the strong prior is built from a simple articulated model having both time-invariant (static) and time-variant (dynamic) parameters. The model is easily modified to cater to situations such as walkers wearing clothing that obscures the limbs. The statistics of the parameters are learned from high-quality (indoor laboratory) data and the Bayesian framework then allows us to "bootstrap" to accurate gait extraction on the noisy images typical of cluttered, outdoor scenes. To achieve automatic fitting, we use a hidden Markov model to detect the phases of images in a walking cycle. We demonstrate our approach on silhouettes extracted from fronto-parallel ("sideways on") sequences of walkers under both high-quality indoor and noisy outdoor conditions. As well as high-quality data with synthetic noise and occlusions added, we also test walkers with rucksacks, skirts, and trench coats. Results are quantified in terms of chamfer distance and average pixel error between automatically extracted body points and corresponding hand-labeled points. No one part of the system is novel in itself, but the overall framework makes it feasible to extract gait from very much poorer quality image sequences than hitherto. This is confirmed by comparing person identification by gait using our method and a well-established baseline recognition algorithm.

Convolutional networks for vehicle track segmentation

DOE PAGES

Quach, Tu-Thach

2017-08-19

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate inmore » low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.« less

Calculation of local optical properties in highly scattering media using a-priori structural information for application to simultaneous NIR-MR breast examination

NASA Astrophysics Data System (ADS)

Ntziachristos, Vasilis; Yodh, Arjun G.; Schnall, Mitchell D.; Ma, XuHui; Chance, Britton

1998-12-01

A single photon counting NIR imager designed to work simultaneously with an MRI scanner for concurrent NIR-MR mammography has recently been developed. The combination of imaging modalities aims in effectively investigating the competence of optical imaging as a stand along modality and as an MRI add-on in order to increase the sensitivity and specificity of the mammoraphic examination. In this work we focus on the second aim. We present the methodology developed to employ the MR anatomical information in order to simplify the forward problem and accurately calculate local tissue optical properties, by fitting the NIR data to this model. Derivation of local optical properties due to intrinsic or extrinsic may identify the existence of malignant and benign breast tissue NIR signatures. We have evaluated the performance of the solver with experimental measurements, also presented here, from models with known absorption perturbations. The average quantification error of absolute absorption of local lesions has been found to be less than 10% in simple models and algorithm convergence is always ensured.

SOFT: a synthetic synchrotron diagnostic for runaway electrons

NASA Astrophysics Data System (ADS)

Hoppe, M.; Embréus, O.; Tinguely, R. A.; Granetz, R. S.; Stahl, A.; Fülöp, T.

2018-02-01

Improved understanding of the dynamics of runaway electrons can be obtained by measurement and interpretation of their synchrotron radiation emission. Models for synchrotron radiation emitted by relativistic electrons are well established, but the question of how various geometric effects—such as magnetic field inhomogeneity and camera placement—influence the synchrotron measurements and their interpretation remains open. In this paper we address this issue by simulating synchrotron images and spectra using the new synthetic synchrotron diagnostic tool SOFT (Synchrotron-detecting Orbit Following Toolkit). We identify the key parameters influencing the synchrotron radiation spot and present scans in those parameters. Using a runaway electron distribution function obtained by Fokker-Planck simulations for parameters from an Alcator C-Mod discharge, we demonstrate that the corresponding synchrotron image is well-reproduced by SOFT simulations, and we explain how it can be understood in terms of the parameter scans. Geometric effects are shown to significantly influence the synchrotron spectrum, and we show that inherent inconsistencies in a simple emission model (i.e. not modeling detection) can lead to incorrect interpretation of the images.

Convolutional networks for vehicle track segmentation

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

Quach, Tu-Thach

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate inmore » low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.« less

Laboratory implementation of edge illumination X-ray phase-contrast imaging with energy-resolved detectors

NASA Astrophysics Data System (ADS)

Diemoz, P. C.; Endrizzi, M.; Vittoria, F. A.; Hagen, C. K.; Kallon, G.; Basta, D.; Marenzana, M.; Delogu, P.; Vincenzi, A.; De Ruvo, L.; Spandre, G.; Brez, A.; Bellazzini, R.; Olivo, A.

2015-03-01

Edge illumination (EI) X-ray phase-contrast imaging (XPCI) has potential for applications in different fields of research, including materials science, non-destructive industrial testing, small-animal imaging, and medical imaging. One of its main advantages is the compatibility with laboratory equipment, in particular with conventional non-microfocal sources, which makes its exploitation in normal research laboratories possible. In this work, we demonstrate that the signal in laboratory implementations of EI can be correctly described with the use of the simplified geometrical optics. Besides enabling the derivation of simple expressions for the sensitivity and spatial resolution of a given EI setup, this model also highlights the EI's achromaticity. With the aim of improving image quality, as well as to take advantage of the fact that all energies in the spectrum contribute to the image contrast, we carried out EI acquisitions using a photon-counting energy-resolved detector. The obtained results demonstrate that this approach has great potential for future laboratory implementations of EI.

Predicting pulsar scintillation from refractive plasma sheets

NASA Astrophysics Data System (ADS)

Simard, Dana; Pen, Ue-Li

2018-07-01

The dynamic and secondary spectra of many pulsars show evidence for long-lived, aligned images of the pulsar that are stationary on a thin scattering sheet. One explanation for this phenomenon considers the effects of wave crests along sheets in the ionized interstellar medium, such as those due to Alfvén waves propagating along current sheets. If these sheets are closely aligned to our line of sight to the pulsar, high bending angles arise at the wave crests and a selection effect causes alignment of images produced at different crests, similar to grazing reflection off of a lake. Using geometric optics, we develop a simple parametrized model of these corrugated sheets that can be constrained with a single observation and that makes observable predictions for variations in the scintillation of the pulsar over time and frequency. This model reveals qualitative differences between lensing from overdense and underdense corrugated sheets: only if the sheet is overdense compared to the surrounding interstellar medium can the lensed images be brighter than the line-of-sight image to the pulsar, and the faint lensed images are closer to the pulsar at higher frequencies if the sheet is underdense, but at lower frequencies if the sheet is overdense.

Predicting Pulsar Scintillation from Refractive Plasma Sheets

NASA Astrophysics Data System (ADS)

Simard, Dana; Pen, Ue-Li

2018-05-01

The dynamic and secondary spectra of many pulsars show evidence for long-lived, aligned images of the pulsar that are stationary on a thin scattering sheet. One explanation for this phenomenon considers the effects of wave crests along sheets in the ionized interstellar medium, such as those due to Alfvén waves propagating along current sheets. If these sheets are closely aligned to our line-of-sight to the pulsar, high bending angles arise at the wave crests and a selection effect causes alignment of images produced at different crests, similar to grazing reflection off of a lake. Using geometric optics, we develop a simple parameterized model of these corrugated sheets that can be constrained with a single observation and that makes observable predictions for variations in the scintillation of the pulsar over time and frequency. This model reveals qualitative differences between lensing from overdense and underdense corrugated sheets: Only if the sheet is overdense compared to the surrounding interstellar medium can the lensed images be brighter than the line-of-sight image to the pulsar, and the faint lensed images are closer to the pulsar at higher frequencies if the sheet is underdense, but at lower frequencies if the sheet is overdense.

Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets

PubMed Central

Xiao, Xun; Geyer, Veikko F.; Bowne-Anderson, Hugo; Howard, Jonathon; Sbalzarini, Ivo F.

2016-01-01

Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy. PMID:27104582

Salient regions detection using convolutional neural networks and color volume

NASA Astrophysics Data System (ADS)

Liu, Guang-Hai; Hou, Yingkun

2018-03-01

Convolutional neural network is an important technique in machine learning, pattern recognition and image processing. In order to reduce the computational burden and extend the classical LeNet-5 model to the field of saliency detection, we propose a simple and novel computing model based on LeNet-5 network. In the proposed model, hue, saturation and intensity are utilized to extract depth cues, and then we integrate depth cues and color volume to saliency detection following the basic structure of the feature integration theory. Experimental results show that the proposed computing model outperforms some existing state-of-the-art methods on MSRA1000 and ECSSD datasets.

Validation of the thermal code of RadTherm-IR, IR-Workbench, and F-TOM

NASA Astrophysics Data System (ADS)

Schwenger, Frédéric; Grossmann, Peter; Malaplate, Alain

2009-05-01

System assessment by image simulation requires synthetic scenarios that can be viewed by the device to be simulated. In addition to physical modeling of the camera, a reliable modeling of scene elements is necessary. Software products for modeling of target data in the IR should be capable of (i) predicting surface temperatures of scene elements over a long period of time and (ii) computing sensor views of the scenario. For such applications, FGAN-FOM acquired the software products RadTherm-IR (ThermoAnalytics Inc., Calumet, USA; IR-Workbench (OKTAL-SE, Toulouse, France). Inspection of the accuracy of simulation results by validation is necessary before using these products for applications. In the first step of validation, the performance of both "thermal solvers" was determined through comparison of the computed diurnal surface temperatures of a simple object with the corresponding values from measurements. CUBI is a rather simple geometric object with well known material parameters which makes it suitable for testing and validating object models in IR. It was used in this study as a test body. Comparison of calculated and measured surface temperature values will be presented, together with the results from the FGAN-FOM thermal object code F-TOM. In the second validation step, radiances of the simulated sensor views computed by RadTherm-IR and IR-Workbench will be compared with radiances retrieved from the recorded sensor images taken by the sensor that was simulated. Strengths and weaknesses of the models RadTherm-IR, IR-Workbench and F-TOM will be discussed.

Virtual environments from panoramic images

NASA Astrophysics Data System (ADS)

Chapman, David P.; Deacon, Andrew

1998-12-01

A number of recent projects have demonstrated the utility of Internet-enabled image databases for the documentation of complex, inaccessible and potentially hazardous environments typically encountered in the petrochemical and nuclear industries. Unfortunately machine vision and image processing techniques have not, to date, enabled the automatic extraction geometrical data from such images and thus 3D CAD modeling remains an expensive and laborious manual activity. Recent developments in panoramic image capture and presentation offer an alternative intermediate deliverable which, in turn, offers some of the benefits of a 3D model at a fraction of the cost. Panoramic image display tools such as Apple's QuickTime VR (QTVR) and Live Spaces RealVR provide compelling and accessible digital representations of the real world and justifiably claim to 'put the reality in Virtual Reality.' This paper will demonstrate how such technologies can be customized, extended and linked to facility management systems delivered over a corporate intra-net to enable end users to become familiar with remote sites and extract simple dimensional data. In addition strategies for the integration of such images with documents gathered from 2D or 3D CAD and Process and Instrumentation Diagrams (P&IDs) will be described as will techniques for precise 'As-Built' modeling using the calibrated images from which panoramas have been derived and the use of textures from these images to increase the realism of rendered scenes. A number of case studies relating to both nuclear and process engineering will demonstrate the extent to which such solution are scaleable in order to deal with the very large volumes of image data required to fully document the large, complex facilities typical of these industry sectors.

High-frequency Ultrasound Imaging of Mouse Cervical Lymph Nodes.

PubMed

Walk, Elyse L; McLaughlin, Sarah L; Weed, Scott A

2015-07-25

High-frequency ultrasound (HFUS) is widely employed as a non-invasive method for imaging internal anatomic structures in experimental small animal systems. HFUS has the ability to detect structures as small as 30 µm, a property that has been utilized for visualizing superficial lymph nodes in rodents in brightness (B)-mode. Combining power Doppler with B-mode imaging allows for measuring circulatory blood flow within lymph nodes and other organs. While HFUS has been utilized for lymph node imaging in a number of mouse  model systems, a detailed protocol describing HFUS imaging and characterization of the cervical lymph nodes in mice has not been reported. Here, we show that HFUS can be adapted to detect and characterize cervical lymph nodes in mice. Combined B-mode and power Doppler imaging can be used to detect increases in blood flow in immunologically-enlarged cervical nodes. We also describe the use of B-mode imaging to conduct fine needle biopsies of cervical lymph nodes to retrieve lymph tissue for histological  analysis. Finally, software-aided steps are described to calculate changes in lymph node volume and to visualize changes in lymph node morphology following image reconstruction. The ability to visually monitor changes in cervical lymph node biology over time provides a simple and powerful technique for the non-invasive monitoring of cervical lymph node alterations in preclinical mouse models of oral cavity disease.

A label field fusion bayesian model and its penalized maximum rand estimator for image segmentation.

PubMed

Mignotte, Max

2010-06-01

This paper presents a novel segmentation approach based on a Markov random field (MRF) fusion model which aims at combining several segmentation results associated with simpler clustering models in order to achieve a more reliable and accurate segmentation result. The proposed fusion model is derived from the recently introduced probabilistic Rand measure for comparing one segmentation result to one or more manual segmentations of the same image. This non-parametric measure allows us to easily derive an appealing fusion model of label fields, easily expressed as a Gibbs distribution, or as a nonstationary MRF model defined on a complete graph. Concretely, this Gibbs energy model encodes the set of binary constraints, in terms of pairs of pixel labels, provided by each segmentation results to be fused. Combined with a prior distribution, this energy-based Gibbs model also allows for definition of an interesting penalized maximum probabilistic rand estimator with which the fusion of simple, quickly estimated, segmentation results appears as an interesting alternative to complex segmentation models existing in the literature. This fusion framework has been successfully applied on the Berkeley image database. The experiments reported in this paper demonstrate that the proposed method is efficient in terms of visual evaluation and quantitative performance measures and performs well compared to the best existing state-of-the-art segmentation methods recently proposed in the literature.

Controllable Synthesis of a Smart Multifunctional Nanoscale Metal-Organic Framework for Magnetic Resonance/Optical Imaging and Targeted Drug Delivery.

PubMed

Gao, Xuechuan; Zhai, Manjue; Guan, Weihua; Liu, Jingjuan; Liu, Zhiliang; Damirin, Alatangaole

2017-02-01

As a result of their extraordinarily large surfaces and well-defined pores, the design of a multifunctional metal-organic framework (MOF) is crucial for drug delivery but has rarely been reported. In this paper, a novel drug delivery system (DDS) based on nanoscale MOF was developed for use in cancer diagnosis and therapy. This MOF-based tumor targeting DDS was fabricated by a simple postsynthetic surface modification process. First, magnetic mesoporous nanomaterial Fe-MIL-53-NH 2 was used for encapsulating the drug and served as a magnetic resonance contrast agent. Moreover, the Fe-MIL-53-NH 2 nanomaterial exhibited a high loading capacity for the model anticancer drug 5-fluorouracil (5-FU). Subsequently, the fluorescence imaging agent 5-carboxyfluorescein (5-FAM) and the targeting reagent folic acid (FA) were conjugated to the 5-FU-loaded Fe-MIL-53-NH 2 , resulting in the advanced DDS Fe-MIL-53-NH 2 -FA-5-FAM/5-FU. Owing to the multifunctional surface modification, the obtained DDS Fe-MIL-53-NH 2 -FA-5-FAM/5-FU shows good biocompatibility, tumor enhanced cellular uptake, strong cancer cell growth inhibitory effect, excellent fluorescence imaging, and outstanding magnetic resonance imaging capability. Taken together, this study integrates diagnostic and treatment aspects into a single platform by a simple and efficient strategy, aiming for facilitating new possibilities for MOF use for multifunctional drug delivery.

Identifying mechanisms for superdiffusive dynamics in cell trajectories

NASA Astrophysics Data System (ADS)

Passucci, Giuseppe; Brasch, Megan; Henderson, James; Manning, M. Lisa

Self-propelled particle (SPP) models have been used to explore features of active matter such as motility-induced phase separation, jamming, and flocking, and are often used to model biological cells. However, many cells exhibit super-diffusive trajectories, where displacements scale faster than t 1 / 2 in all directions, and these are not captured by traditional SPP models. We extract cell trajectories from image stacks of mouse fibroblast cells moving on 2D substrates and find super-diffusive mean-squared displacements in all directions across varying densities. Two SPP model modifications have been proposed to capture super-diffusive dynamics: Levy walks and heterogeneous motility parameters. In mouse fibroblast cells displacement probability distributions collapse when time is rescaled by a power greater than 1/2, which is consistent with Levy walks. We show that a simple SPP model with heterogeneous rotational noise can also generate a similar collapse. Furthermore, a close examination of statistics extracted directly from cell trajectories is consistent with a heterogeneous mobility SPP model and inconsistent with a Levy walk model. Our work demonstrates that a simple set of analyses can distinguish between mechanisms for anomalous diffusion in active matter.

Evaporation estimation of rift valley lakes: comparison of models.

PubMed

Melesse, Assefa M; Abtew, Wossenu; Dessalegne, Tibebe

2009-01-01

Evapotranspiration (ET) accounts for a substantial amount of the water flux in the arid and semi-arid regions of the World. Accurate estimation of ET has been a challenge for hydrologists, mainly because of the spatiotemporal variability of the environmental and physical parameters governing the latent heat flux. In addition, most available ET models depend on intensive meteorological information for ET estimation. Such data are not available at the desired spatial and temporal scales in less developed and remote parts of the world. This limitation has necessitated the development of simple models that are less data intensive and provide ET estimates with acceptable level of accuracy. Remote sensing approach can also be applied to large areas where meteorological data are not available and field scale data collection is costly, time consuming and difficult. In areas like the Rift Valley regions of Ethiopia, the applicability of the Simple Method (Abtew Method) of lake evaporation estimation and surface energy balance approach using remote sensing was studied. The Simple Method and a remote sensing-based lake evaporation estimates were compared to the Penman, Energy balance, Pan, Radiation and Complementary Relationship Lake Evaporation (CRLE) methods applied in the region. Results indicate a good correspondence of the models outputs to that of the above methods. Comparison of the 1986 and 2000 monthly lake ET from the Landsat images to the Simple and Penman Methods show that the remote sensing and surface energy balance approach is promising for large scale applications to understand the spatial variation of the latent heat flux.

Dual-Energy Computed Tomography for the Characterization of Intracranial Hemorrhage and Calcification: A Systematic Approach in a Phantom System.

PubMed

Nute, Jessica L; Jacobsen, Megan C; Chandler, Adam; Cody, Dianna D; Schellingerhout, Dawid

2017-01-01

The aim of this study was to develop a diagnostic framework for distinguishing calcific from hemorrhagic cerebral lesions using dual-energy computed tomography (DECT) in an anthropomorphic phantom system. An anthropomorphic phantom was designed to mimic the CT imaging characteristics of the human head. Cylindrical lesion models containing either calcium or iron, mimicking calcification or hemorrhage, respectively, were developed to exhibit matching, and therefore indistinguishable, single-energy CT (SECT) attenuation values from 40 to 100 HU. These lesion models were fabricated at 0.5, 1, and 1.5 cm in diameter and positioned in simulated cerebrum and skull base locations within the anthropomorphic phantom. All lesion sizes were modeled in the cerebrum, while only 1.5-cm lesions were modeled in the skull base. Images were acquired using a GE 750HD CT scanner and an expansive dual-energy protocol that covered variations in dose (36.7-132.6 mGy CTDIvol, n = 12), image thickness (0.625-5 mm, n = 4), and reconstruction filter (soft, standard, detail, n = 3) for a total of 144 unique technique combinations. Images representing each technique combination were reconstructed into water and calcium material density images, as well as a monoenergetic image chosen to mimic the attenuation of a 120-kVp SECT scan. A true single-energy routine brain protocol was also included for verification of lesion SECT attenuation. Points representing the 3 dual-energy reconstructions were plotted into a 3-dimensional space (water [milligram/milliliter], calcium [milligram/milliliter], monoenergetic Hounsfield unit as x, y, and z axes, respectively), and the distribution of points analyzed using 2 approaches: support vector machines and a simple geometric bisector (GB). Each analysis yielded a plane of optimal differentiation between the calcification and hemorrhage lesion model distributions. By comparing the predicted lesion composition to the known lesion composition, we identified the optimal combination of CTDIvol, image thickness, and reconstruction filter to maximize differentiation between the lesion model types. To validate these results, a new set of hemorrhage and calcification lesion models were created, scanned in a blinded fashion, and prospectively classified using the planes of differentiation derived from support vector machine and GB methods. Accuracy of differentiation improved with increasing dose (CTDIvol) and image thickness. Reconstruction filter had no effect on the accuracy of differentiation. Using an optimized protocol consisting of the maximum CTDIvol of 132.6 mGy, 5-mm-thick images, and a standard filter, hemorrhagic and calcific lesion models with equal SECT attenuation (Hounsfield unit) were differentiated with over 90% accuracy down to 70 HU for skull base lesions of 1.5 cm, and down to 100 HU, 60 HU, and 60 HU for cerebrum lesions of 0.5, 1.0, and 1.5 cm, respectively. The analytic method that yielded the best results was a simple GB plane through the 3-dimensional DECT space. In the validation study, 96% of unknown lesions were correctly classified across all lesion sizes and locations investigated. We define the optimal scan parameters and expected limitations for the accurate classification of hemorrhagic versus calcific cerebral lesions in an anthropomorphic phantom with DECT. Although our proposed DECT protocol represents an increase in dose compared with routine brain CT, this method is intended as a specialized evaluation of potential brain hemorrhage and is thus counterbalanced by increased diagnostic benefit. This work provides justification for the application of this technique in human clinical trials.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography).

PubMed

Siegel, Nisan; Storrie, Brian; Bruce, Marc; Brooker, Gary

2015-02-07

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called "CINCH". An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution.

Cu-Au alloy nanostructures coated with aptamers: a simple, stable and highly effective platform for in vivo cancer theranostics

NASA Astrophysics Data System (ADS)

Ye, Xiaosheng; Shi, Hui; He, Xiaoxiao; Yu, Yanru; He, Dinggeng; Tang, Jinlu; Lei, Yanli; Wang, Kemin

2016-01-01

As a star material in cancer theranostics, photoresponsive gold (Au) nanostructures may still have drawbacks, such as low thermal conductivity, irradiation-induced melting effect and high cost. To solve the problem, copper (Cu) with a much higher thermal conductivity and lower cost was introduced to generate a novel Cu-Au alloy nanostructure produced by a simple, gentle and one-pot synthetic method. Having the good qualities of both Cu and Au, the irregularly-shaped Cu-Au alloy nanostructures showed several advantages over traditional Au nanorods, including a broad and intense near-infrared (NIR) absorption band from 400 to 1100 nm, an excellent heating performance under laser irradiation at different wavelengths and even a notable photostability against melting. Then, via a simple conjugation of fluorophore-labeled aptamers on the Cu-Au alloy nanostructures, active targeting and signal output were simultaneously introduced, thus constructing a theranostic platform based on fluorophore-labeled, aptamer-coated Cu-Au alloy nanostructures. By using human leukemia CCRF-CEM cancer and Cy5-labeled aptamer Sgc8c (Cy5-Sgc8c) as the model, a selective fluorescence imaging and NIR photothermal therapy was successfully realized for both in vitro cancer cells and in vivo tumor tissues. It was revealed that Cy5-Sgc8c-coated Cu-Au alloy nanostructures were not only capable of robust target recognition and stable signal output for molecular imaging in complex biological systems, but also killed target cancer cells in mice with only five minutes of 980 nm irradiation. The platform was found to be simple, stable, biocompatible and highly effective, and shows great potential as a versatile tool for cancer theranostics.As a star material in cancer theranostics, photoresponsive gold (Au) nanostructures may still have drawbacks, such as low thermal conductivity, irradiation-induced melting effect and high cost. To solve the problem, copper (Cu) with a much higher thermal conductivity and lower cost was introduced to generate a novel Cu-Au alloy nanostructure produced by a simple, gentle and one-pot synthetic method. Having the good qualities of both Cu and Au, the irregularly-shaped Cu-Au alloy nanostructures showed several advantages over traditional Au nanorods, including a broad and intense near-infrared (NIR) absorption band from 400 to 1100 nm, an excellent heating performance under laser irradiation at different wavelengths and even a notable photostability against melting. Then, via a simple conjugation of fluorophore-labeled aptamers on the Cu-Au alloy nanostructures, active targeting and signal output were simultaneously introduced, thus constructing a theranostic platform based on fluorophore-labeled, aptamer-coated Cu-Au alloy nanostructures. By using human leukemia CCRF-CEM cancer and Cy5-labeled aptamer Sgc8c (Cy5-Sgc8c) as the model, a selective fluorescence imaging and NIR photothermal therapy was successfully realized for both in vitro cancer cells and in vivo tumor tissues. It was revealed that Cy5-Sgc8c-coated Cu-Au alloy nanostructures were not only capable of robust target recognition and stable signal output for molecular imaging in complex biological systems, but also killed target cancer cells in mice with only five minutes of 980 nm irradiation. The platform was found to be simple, stable, biocompatible and highly effective, and shows great potential as a versatile tool for cancer theranostics. Electronic supplementary information (ESI) available: Fig. S1, S2 and Table S1. See DOI: 10.1039/c5nr07017a

Near-Field Terahertz Transmission Imaging at 0.210 Terahertz Using a Simple Aperture Technique

DTIC Science & Technology

2015-10-01

This report discusses a simple aperture useful for terahertz near-field imaging at .2010 terahertz ( lambda = 1.43 millimeters). The aperture requires...achieve a spatial resolution of lambda /7. The aperture can be scaled with the assistance of machinery found in conventional machine shops to achieve similar results using shorter terahertz wavelengths.

A Simple BODIPY-Based Viscosity Probe for Imaging of Cellular Viscosity in Live Cells

PubMed Central

Su, Dongdong; Teoh, Chai Lean; Gao, Nengyue; Xu, Qing-Hua; Chang, Young-Tae

2016-01-01

Intracellular viscosity is a fundamental physical parameter that indicates the functioning of cells. In this work, we developed a simple boron-dipyrromethene (BODIPY)-based probe, BTV, for cellular mitochondria viscosity imaging by coupling a simple BODIPY rotor with a mitochondria-targeting unit. The BTV exhibited a significant fluorescence intensity enhancement of more than 100-fold as the solvent viscosity increased. Also, the probe showed a direct linear relationship between the fluorescence lifetime and the media viscosity, which makes it possible to trace the change of the medium viscosity. Furthermore, it was demonstrated that BTV could achieve practical applicability in the monitoring of mitochondrial viscosity changes in live cells through fluorescence lifetime imaging microscopy (FLIM). PMID:27589762

A Simple BODIPY-Based Viscosity Probe for Imaging of Cellular Viscosity in Live Cells.

PubMed

Su, Dongdong; Teoh, Chai Lean; Gao, Nengyue; Xu, Qing-Hua; Chang, Young-Tae

2016-08-31

Intracellular viscosity is a fundamental physical parameter that indicates the functioning of cells. In this work, we developed a simple boron-dipyrromethene (BODIPY)-based probe, BTV, for cellular mitochondria viscosity imaging by coupling a simple BODIPY rotor with a mitochondria-targeting unit. The BTV exhibited a significant fluorescence intensity enhancement of more than 100-fold as the solvent viscosity increased. Also, the probe showed a direct linear relationship between the fluorescence lifetime and the media viscosity, which makes it possible to trace the change of the medium viscosity. Furthermore, it was demonstrated that BTV could achieve practical applicability in the monitoring of mitochondrial viscosity changes in live cells through fluorescence lifetime imaging microscopy (FLIM).

Geometry-aware multiscale image registration via OBBTree-based polyaffine log-demons.

PubMed

Seiler, Christof; Pennec, Xavier; Reyes, Mauricio

2011-01-01

Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.

Testing the Two-Layer Model for Correcting Near Cloud Reflectance Enhancement Using LES SHDOM Simulated Radiances

NASA Technical Reports Server (NTRS)

Wen, Guoyong; Marshak, Alexander; Varnai, Tamas; Levy, Robert

2016-01-01

A transition zone exists between cloudy skies and clear sky; such that, clouds scatter solar radiation into clear-sky regions. From a satellite perspective, it appears that clouds enhance the radiation nearby. We seek a simple method to estimate this enhancement, since it is so computationally expensive to account for all three-dimensional (3-D) scattering processes. In previous studies, we developed a simple two-layer model (2LM) that estimated the radiation scattered via cloud-molecular interactions. Here we have developed a new model to account for cloud-surface interaction (CSI). We test the models by comparing to calculations provided by full 3-D radiative transfer simulations of realistic cloud scenes. For these scenes, the Moderate Resolution Imaging Spectroradiometer (MODIS)-like radiance fields were computed from the Spherical Harmonic Discrete Ordinate Method (SHDOM), based on a large number of cumulus fields simulated by the University of California, Los Angeles (UCLA) large eddy simulation (LES) model. We find that the original 2LM model that estimates cloud-air molecule interactions accounts for 64 of the total reflectance enhancement and the new model (2LM+CSI) that also includes cloud-surface interactions accounts for nearly 80. We discuss the possibility of accounting for cloud-aerosol radiative interactions in 3-D cloud-induced reflectance enhancement, which may explain the remaining 20 of enhancements. Because these are simple models, these corrections can be applied to global satellite observations (e.g., MODIS) and help to reduce biases in aerosol and other clear-sky retrievals.

Weibull Multiplicative Model and Machine Learning Models for Full-Automatic Dark-Spot Detection from SAR Images

NASA Astrophysics Data System (ADS)

Taravat, A.; Del Frate, F.

2013-09-01

As a major aspect of marine pollution, oil release into the sea has serious biological and environmental impacts. Among remote sensing systems (which is a tool that offers a non-destructive investigation method), synthetic aperture radar (SAR) can provide valuable synoptic information about the position and size of the oil spill due to its wide area coverage and day/night, and all-weather capabilities. In this paper we present a new automated method for oil-spill monitoring. A new approach is based on the combination of Weibull Multiplicative Model and machine learning techniques to differentiate between dark spots and the background. First, the filter created based on Weibull Multiplicative Model is applied to each sub-image. Second, the sub-image is segmented by two different neural networks techniques (Pulsed Coupled Neural Networks and Multilayer Perceptron Neural Networks). As the last step, a very simple filtering process is used to eliminate the false targets. The proposed approaches were tested on 20 ENVISAT and ERS2 images which contained dark spots. The same parameters were used in all tests. For the overall dataset, the average accuracies of 94.05 % and 95.20 % were obtained for PCNN and MLP methods, respectively. The average computational time for dark-spot detection with a 256 × 256 image in about 4 s for PCNN segmentation using IDL software which is the fastest one in this field at present. Our experimental results demonstrate that the proposed approach is very fast, robust and effective. The proposed approach can be applied to the future spaceborne SAR images.

Salient region detection by fusing bottom-up and top-down features extracted from a single image.

PubMed

Tian, Huawei; Fang, Yuming; Zhao, Yao; Lin, Weisi; Ni, Rongrong; Zhu, Zhenfeng

2014-10-01

Recently, some global contrast-based salient region detection models have been proposed based on only the low-level feature of color. It is necessary to consider both color and orientation features to overcome their limitations, and thus improve the performance of salient region detection for images with low-contrast in color and high-contrast in orientation. In addition, the existing fusion methods for different feature maps, like the simple averaging method and the selective method, are not effective sufficiently. To overcome these limitations of existing salient region detection models, we propose a novel salient region model based on the bottom-up and top-down mechanisms: the color contrast and orientation contrast are adopted to calculate the bottom-up feature maps, while the top-down cue of depth-from-focus from the same single image is used to guide the generation of final salient regions, since depth-from-focus reflects the photographer's preference and knowledge of the task. A more general and effective fusion method is designed to combine the bottom-up feature maps. According to the degree-of-scattering and eccentricities of feature maps, the proposed fusion method can assign adaptive weights to different feature maps to reflect the confidence level of each feature map. The depth-from-focus of the image as a significant top-down feature for visual attention in the image is used to guide the salient regions during the fusion process; with its aid, the proposed fusion method can filter out the background and highlight salient regions for the image. Experimental results show that the proposed model outperforms the state-of-the-art models on three public available data sets.

Three-dimensional in vitro cancer spheroid models for Photodynamic Therapy: Strengths and Opportunities

NASA Astrophysics Data System (ADS)

Evans, Conor

2015-03-01

Three dimensional, in vitro spheroid cultures offer considerable utility for the development and testing of anticancer photodynamic therapy regimens. More complex than monolayer cultures, three-dimensional spheroid systems replicate many of the important cell-cell and cell-matrix interactions that modulate treatment response in vivo. Simple enough to be grown by the thousands and small enough to be optically interrogated, spheroid cultures lend themselves to high-content and high-throughput imaging approaches. These advantages have enabled studies investigating photosensitizer uptake, spatiotemporal patterns of therapeutic response, alterations in oxygen diffusion and consumption during therapy, and the exploration of mechanisms that underlie therapeutic synergy. The use of quantitative imaging methods, in particular, has accelerated the pace of three-dimensional in vitro photodynamic therapy studies, enabling the rapid compilation of multiple treatment response parameters in a single experiment. Improvements in model cultures, the creation of new molecular probes of cell state and function, and innovations in imaging toolkits will be important for the advancement of spheroid culture systems for future photodynamic therapy studies.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

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.

MCAT to XCAT: The Evolution of 4-D Computerized Phantoms for Imaging Research: Computer models that take account of body movements promise to provide evaluation and improvement of medical imaging devices and technology.

PubMed

Paul Segars, W; Tsui, Benjamin M W

2009-12-01

Recent work in the development of computerized phantoms has focused on the creation of ideal "hybrid" models that seek to combine the realism of a patient-based voxelized phantom with the flexibility of a mathematical or stylized phantom. We have been leading the development of such computerized phantoms for use in medical imaging research. This paper will summarize our developments dating from the original four-dimensional (4-D) Mathematical Cardiac-Torso (MCAT) phantom, a stylized model based on geometric primitives, to the current 4-D extended Cardiac-Torso (XCAT) and Mouse Whole-Body (MOBY) phantoms, hybrid models of the human and laboratory mouse based on state-of-the-art computer graphics techniques. This paper illustrates the evolution of computerized phantoms toward more accurate models of anatomy and physiology. This evolution was catalyzed through the introduction of nonuniform rational b-spline (NURBS) and subdivision (SD) surfaces, tools widely used in computer graphics, as modeling primitives to define a more ideal hybrid phantom. With NURBS and SD surfaces as a basis, we progressed from a simple geometrically based model of the male torso (MCAT) containing only a handful of structures to detailed, whole-body models of the male and female (XCAT) anatomies (at different ages from newborn to adult), each containing more than 9000 structures. The techniques we applied for modeling the human body were similarly used in the creation of the 4-D MOBY phantom, a whole-body model for the mouse designed for small animal imaging research. From our work, we have found the NURBS and SD surface modeling techniques to be an efficient and flexible way to describe the anatomy and physiology for realistic phantoms. Based on imaging data, the surfaces can accurately model the complex organs and structures in the body, providing a level of realism comparable to that of a voxelized phantom. In addition, they are very flexible. Like stylized models, they can easily be manipulated to model anatomical variations and patient motion. With the vast improvement in realism, the phantoms developed in our lab can be combined with accurate models of the imaging process (SPECT, PET, CT, magnetic resonance imaging, and ultrasound) to generate simulated imaging data close to that from actual human or animal subjects. As such, they can provide vital tools to generate predictive imaging data from many different subjects under various scanning parameters from which to quantitatively evaluate and improve imaging devices and techniques. From the MCAT to XCAT, we will demonstrate how NURBS and SD surface modeling have resulted in a major evolutionary advance in the development of computerized phantoms for imaging research.

Turbulent shear layers in confining channels

NASA Astrophysics Data System (ADS)

Benham, Graham P.; Castrejon-Pita, Alfonso A.; Hewitt, Ian J.; Please, Colin P.; Style, Rob W.; Bird, Paul A. D.

2018-06-01

We present a simple model for the development of shear layers between parallel flows in confining channels. Such flows are important across a wide range of topics from diffusers, nozzles and ducts to urban air flow and geophysical fluid dynamics. The model approximates the flow in the shear layer as a linear profile separating uniform-velocity streams. Both the channel geometry and wall drag affect the development of the flow. The model shows good agreement with both particle image velocimetry experiments and computational turbulence modelling. The simplicity and low computational cost of the model allows it to be used for benchmark predictions and design purposes, which we demonstrate by investigating optimal pressure recovery in diffusers with non-uniform inflow.

Molray--a web interface between O and the POV-Ray ray tracer.

PubMed

Harris, M; Jones, T A

2001-08-01

A publicly available web-based interface is presented for producing high-quality ray-traced images and movies from the molecular-modelling program O [Jones et al. (1991), Acta Cryst. A47, 110-119]. The interface allows the user to select O-plot files and set parameters to create standard input files for the popular ray-tracing renderer POV-Ray, which can then produce publication-quality still images or simple movies. To ensure ease of use, we have made this service available to the O user community via the World Wide Web. The public Molray server is available at http://xray.bmc.uu.se/molray.

Polar synthetic imaging

NASA Astrophysics Data System (ADS)

George, Jonathan K.

2013-05-01

In the search for low-cost wide spectrum imagers it may become necessary to sacrifice the expense of the focal plane array and revert to a scanning methodology. In many cases the sensor may be too unwieldy to physically scan and mirrors may have adverse effects on particular frequency bands. In these cases, photonic masks can be devised to modulate the incoming light field with a code over time. This is in essence code-division multiplexing of the light field into a lower dimension channel. In this paper a simple method for modulating the light field with masks of the Archimedes' spiral is presented and a mathematical model of the two-dimensional mask set is developed.

Analysis of the multigroup model for muon tomography based threat detection

NASA Astrophysics Data System (ADS)

Perry, J. O.; Bacon, J. D.; Borozdin, K. N.; Fabritius, J. M.; Morris, C. L.

2014-02-01

We compare different algorithms for detecting a 5 cm tungsten cube using cosmic ray muon technology. In each case, a simple tomographic technique was used for position reconstruction, but the scattering angles were used differently to obtain a density signal. Receiver operating characteristic curves were used to compare images made using average angle squared, median angle squared, average of the squared angle, and a multi-energy group fit of the angular distributions for scenes with and without a 5 cm tungsten cube. The receiver operating characteristic curves show that the multi-energy group treatment of the scattering angle distributions is the superior method for image reconstruction.

Determination of chromophore distribution in skin by spectral imaging

NASA Astrophysics Data System (ADS)

Saknite, Inga; Lange, Marta; Jakovels, Dainis; Spigulis, Janis

2012-10-01

Possibilities to determine chromophore distribution in skin by spectral imaging were explored. Simple RGB sensor devices were used for image acquisition. Totally 200 images of 40 different bruises of 20 people were obtained in order to map chromophores bilirubin and haemoglobin. Possibilities to detect water in vitro and in vivo were estimated by using silicon photodetectors and narrow band LEDs. The results show that it is possible to obtain bilirubin and haemoglobin distribution maps and observe changes of chromophore parameter values over time by using a simple RGB imaging device. Water in vitro was detected by using differences in absorption at 450 nm and 950 nm, and 650 nm and 950 nm.

Rinsing paired-agent model (RPAM) to quantify cell-surface receptor concentrations in topical staining applications of thick tissues

NASA Astrophysics Data System (ADS)

Xu, Xiaochun; Wang, Yu; Xiang, Jialing; Liu, Jonathan T. C.; Tichauer, Kenneth M.

2017-06-01

Conventional molecular assessment of tissue through histology, if adapted to fresh thicker samples, has the potential to enhance cancer detection in surgical margins and monitoring of 3D cell culture molecular environments. However, in thicker samples, substantial background staining is common despite repeated rinsing, which can significantly reduce image contrast. Recently, ‘paired-agent’ methods—which employ co-administration of a control (untargeted) imaging agent—have been applied to thick-sample staining applications to account for background staining. To date, these methods have included (1) a simple ratiometric method that is relatively insensitive to noise in the data but has accuracy that is dependent on the staining protocol and the characteristics of the sample; and (2) a complex paired-agent kinetic modeling method that is more accurate but is more noise-sensitive and requires a precise serial rinsing protocol. Here, a new simplified mathematical model—the rinsing paired-agent model (RPAM)—is derived and tested that offers a good balance between the previous models, is adaptable to arbitrary rinsing-imaging protocols, and does not require calibration of the imaging system. RPAM is evaluated against previous models and is validated by comparison to estimated concentrations of targeted biomarkers on the surface of 3D cell culture and tumor xenograft models. This work supports the use of RPAM as a preferable model to quantitatively analyze targeted biomarker concentrations in topically stained thick tissues, as it was found to match the accuracy of the complex paired-agent kinetic model while retaining the low noise-sensitivity characteristics of the ratiometric method.

Prospects for Classifying Complex Imagery Using a Self-Organizing Neural Network

DTIC Science & Technology

1989-01-11

complex imagery. In his original re- port, Fukushima demonstrated that this system could discriminate between simple alphabetical characters...on a VAX-8600 minicomputer. Wire frame models of three different vehicles were used to test the properties which Fukushima had demonstrated. The...Table No. Page 3-1 Parameters for Training on Three Input Images 14 3-2 Trained Results 17 vn 1. INTRODUCTION The Neocognitron of Fukushima [2

Imaging approach to mechanistic study of nanoparticle interactions with the blood-brain barrier.

PubMed

Bramini, Mattia; Ye, Dong; Hallerbach, Anna; Nic Raghnaill, Michelle; Salvati, Anna; Aberg, Christoffer; Dawson, Kenneth A

2014-05-27

Understanding nanoparticle interactions with the central nervous system, in particular the blood-brain barrier, is key to advances in therapeutics, as well as assessing the safety of nanoparticles. Challenges in achieving insights have been significant, even for relatively simple models. Here we use a combination of live cell imaging and computational analysis to directly study nanoparticle translocation across a human in vitro blood-brain barrier model. This approach allows us to identify and avoid problems in more conventional inferential in vitro measurements by identifying the catalogue of events of barrier internalization and translocation as they occur. Potentially this approach opens up the window of applicability of in vitro models, thereby enabling in depth mechanistic studies in the future. Model nanoparticles are used to illustrate the method. For those, we find that translocation, though rare, appears to take place. On the other hand, barrier uptake is efficient, and since barrier export is small, there is significant accumulation within the barrier.

Iterative method for in situ measurement of lens aberrations in lithographic tools using CTC-based quadratic aberration model.

PubMed

Liu, Shiyuan; Xu, Shuang; Wu, Xiaofei; Liu, Wei

2012-06-18

This paper proposes an iterative method for in situ lens aberration measurement in lithographic tools based on a quadratic aberration model (QAM) that is a natural extension of the linear model formed by taking into account interactions among individual Zernike coefficients. By introducing a generalized operator named cross triple correlation (CTC), the quadratic model can be calculated very quickly and accurately with the help of fast Fourier transform (FFT). The Zernike coefficients up to the 37th order or even higher are determined by solving an inverse problem through an iterative procedure from several through-focus aerial images of a specially designed mask pattern. The simulation work has validated the theoretical derivation and confirms that such a method is simple to implement and yields a superior quality of wavefront estimate, particularly for the case when the aberrations are relatively large. It is fully expected that this method will provide a useful practical means for the in-line monitoring of the imaging quality of lithographic tools.

Lack of sex effect on brain activity during a visuomotor response task: functional MR imaging study.

PubMed

Mikhelashvili-Browner, Nina; Yousem, David M; Wu, Colin; Kraut, Michael A; Vaughan, Christina L; Oguz, Kader Karli; Calhoun, Vince D

2003-03-01

As more individuals are enrolled in clinical functional MR imaging (fMRI) studies, an understanding of how sex may influence fMRI-measured brain activation is critical. We used fixed- and random-effects models to study the influence of sex on fMRI patterns of brain activation during a simple visuomotor reaction time task in the group of 26 age-matched men and women. We evaluated the right visual, left visual, left primary motor, left supplementary motor, and left anterior cingulate areas. Volumes of activations did not significantly differ between the groups in any defined regions. Analysis of variance failed to show any significant correlations between sex and volumes of brain activation in any location studied. Mean percentage signal-intensity changes for all locations were similar between men and women. A two-way t test of brain activation in men and women, performed as a part of random-effects modeling, showed no significant difference at any site. Our results suggest that sex seems to have little influence on fMRI brain activation when we compared performance on the simple reaction-time task. The need to control for sex effects is not critical in the analysis of this task with fMRI.

Let your fingers do the walking: A simple spectral signature model for "remote" fossil prospecting.

PubMed

Conroy, Glenn C; Emerson, Charles W; Anemone, Robert L; Townsend, K E Beth

2012-07-01

Even with the most meticulous planning, and utilizing the most experienced fossil-hunters, fossil prospecting in remote and/or extensive areas can be time-consuming, expensive, logistically challenging, and often hit or miss. While nothing can predict or guarantee with 100% assurance that fossils will be found in any particular location, any procedures or techniques that might increase the odds of success would be a major benefit to the field. Here we describe, and test, one such technique that we feel has great potential for increasing the probability of finding fossiliferous sediments - a relatively simple spectral signature model using the spatial analysis and image classification functions of ArcGIS(®)10 that creates interactive thematic land cover maps that can be used for "remote" fossil prospecting. Our test case is the extensive Eocene sediments of the Uinta Basin, Utah - a fossil prospecting area encompassing ∼1200 square kilometers. Using Landsat 7 ETM+ satellite imagery, we "trained" the spatial analysis and image classification algorithms using the spectral signatures of known fossil localities discovered in the Uinta Basin prior to 2005 and then created interactive probability models highlighting other regions in the Basin having a high probability of containing fossiliferous sediments based on their spectral signatures. A fortuitous "post-hoc" validation of our model presented itself. Our model identified several paleontological "hotspots", regions that, while not producing any fossil localities prior to 2005, had high probabilities of being fossiliferous based on the similarities of their spectral signatures to those of previously known fossil localities. Subsequent fieldwork found fossils in all the regions predicted by the model. Copyright © 2012 Elsevier Ltd. All rights reserved.

External Prior Guided Internal Prior Learning for Real-World Noisy Image Denoising

NASA Astrophysics Data System (ADS)

Xu, Jun; Zhang, Lei; Zhang, David

2018-06-01

Most of existing image denoising methods learn image priors from either external data or the noisy image itself to remove noise. However, priors learned from external data may not be adaptive to the image to be denoised, while priors learned from the given noisy image may not be accurate due to the interference of corrupted noise. Meanwhile, the noise in real-world noisy images is very complex, which is hard to be described by simple distributions such as Gaussian distribution, making real noisy image denoising a very challenging problem. We propose to exploit the information in both external data and the given noisy image, and develop an external prior guided internal prior learning method for real noisy image denoising. We first learn external priors from an independent set of clean natural images. With the aid of learned external priors, we then learn internal priors from the given noisy image to refine the prior model. The external and internal priors are formulated as a set of orthogonal dictionaries to efficiently reconstruct the desired image. Extensive experiments are performed on several real noisy image datasets. The proposed method demonstrates highly competitive denoising performance, outperforming state-of-the-art denoising methods including those designed for real noisy images.

Modeling of polychromatic attenuation using computed tomography reconstructed images

NASA Technical Reports Server (NTRS)

Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.

1999-01-01

This paper presents a procedure for estimating an accurate model of the CT imaging process including spectral effects. As raw projection data are typically unavailable to the end-user, we adopt a post-processing approach that utilizes the reconstructed images themselves. This approach includes errors from x-ray scatter and the nonidealities of the built-in soft tissue correction into the beam characteristics, which is crucial to beam hardening correction algorithms that are designed to be applied directly to CT reconstructed images. We formulate this approach as a quadratic programming problem and propose two different methods, dimension reduction and regularization, to overcome ill conditioning in the model. For the regularization method we use a statistical procedure, Cross Validation, to select the regularization parameter. We have constructed step-wedge phantoms to estimate the effective beam spectrum of a GE CT-I scanner. Using the derived spectrum, we computed the attenuation ratios for the wedge phantoms and found that the worst case modeling error is less than 3% of the corresponding attenuation ratio. We have also built two test (hybrid) phantoms to evaluate the effective spectrum. Based on these test phantoms, we have shown that the effective beam spectrum provides an accurate model for the CT imaging process. Last, we used a simple beam hardening correction experiment to demonstrate the effectiveness of the estimated beam profile for removing beam hardening artifacts. We hope that this estimation procedure will encourage more independent research on beam hardening corrections and will lead to the development of application-specific beam hardening correction algorithms.

Simple, fast, and low-cost camera-based water content measurement with colorimetric fluorescent indicator

NASA Astrophysics Data System (ADS)

Song, Seok-Jeong; Kim, Tae-Il; Kim, Youngmi; Nam, Hyoungsik

2018-05-01

Recently, a simple, sensitive, and low-cost fluorescent indicator has been proposed to determine water contents in organic solvents, drugs, and foodstuffs. The change of water content leads to the change of the indicator's fluorescence color under the ultra-violet (UV) light. Whereas the water content values could be estimated from the spectrum obtained by a bulky and expensive spectrometer in the previous research, this paper demonstrates a simple and low-cost camera-based water content measurement scheme with the same fluorescent water indicator. Water content is calculated over the range of 0-30% by quadratic polynomial regression models with color information extracted from the captured images of samples. Especially, several color spaces such as RGB, xyY, L∗a∗b∗, u‧v‧, HSV, and YCBCR have been investigated to establish the optimal color information features over both linear and nonlinear RGB data given by a camera before and after gamma correction. In the end, a 2nd order polynomial regression model along with HSV in a linear domain achieves the minimum mean square error of 1.06% for a 3-fold cross validation method. Additionally, the resultant water content estimation model is implemented and evaluated in an off-the-shelf Android-based smartphone.

A Versatile Strategy for Characterization and Imaging of Drip Flow Microbial Biofilms.

PubMed

Li, Bin; Dunham, Sage J B; Ellis, Joseph F; Lange, Justin D; Smith, Justin R; Yang, Ning; King, Travis L; Amaya, Kensey R; Arnett, Clint M; Sweedler, Jonathan V

2018-06-05

The inherent architectural and chemical complexities of microbial biofilms mask our understanding of how these communities form, survive, propagate, and influence their surrounding environment. Here we describe a simple and versatile workflow for the cultivation and characterization of model flow-cell-based microbial ecosystems. A customized low-shear drip flow reactor was designed and employed to cultivate single and coculture flow-cell biofilms at the air-liquid interface of several metal surfaces. Pseudomonas putida F1 and Shewanella oneidensis MR-1 were selected as model organisms for this study. The utility and versatility of this platform was demonstrated via the application of several chemical and morphological imaging techniques-including matrix-assisted laser desorption/ionization mass spectrometry imaging, secondary ion mass spectrometry imaging, and scanning electron microscopy-and through the examination of model systems grown on iron substrates of varying compositions. Implementation of these techniques in combination with tandem mass spectrometry and a two-step imaging principal component analysis strategy resulted in the identification and characterization of 23 lipids and 3 oligosaccharides in P. putida F1 biofilms, the discovery of interaction-specific analytes, and the observation of several variations in cell and substrate morphology present during microbially influenced corrosion. The presented workflow is well-suited for examination of both single and multispecies drip flow biofilms and offers a platform for fundamental inquiries into biofilm formation, microbe-microbe interactions, and microbially influenced corrosion.

Integration of Irma tactical scene generator into directed-energy weapon system simulation

NASA Astrophysics Data System (ADS)

Owens, Monte A.; Cole, Madison B., III; Laine, Mark R.

2003-08-01

Integrated high-fidelity physics-based simulations that include engagement models, image generation, electro-optical hardware models and control system algorithms have previously been developed by Boeing-SVS for various tracking and pointing systems. These simulations, however, had always used images with featureless or random backgrounds and simple target geometries. With the requirement to engage tactical ground targets in the presence of cluttered backgrounds, a new type of scene generation tool was required to fully evaluate system performance in this challenging environment. To answer this need, Irma was integrated into the existing suite of Boeing-SVS simulation tools, allowing scene generation capabilities with unprecedented realism. Irma is a US Air Force research tool used for high-resolution rendering and prediction of target and background signatures. The MATLAB/Simulink-based simulation achieves closed-loop tracking by running track algorithms on the Irma-generated images, processing the track errors through optical control algorithms, and moving simulated electro-optical elements. The geometry of these elements determines the sensor orientation with respect to the Irma database containing the three-dimensional background and target models. This orientation is dynamically passed to Irma through a Simulink S-function to generate the next image. This integrated simulation provides a test-bed for development and evaluation of tracking and control algorithms against representative images including complex background environments and realistic targets calibrated using field measurements.

EUV focus sensor: design and modeling

NASA Astrophysics Data System (ADS)

Goldberg, Kenneth A.; Teyssier, Maureen E.; Liddle, J. Alexander

2005-05-01

We describe performance modeling and design optimization of a prototype EUV focus sensor (FS) designed for use with existing 0.3-NA EUV projection-lithography tools. At 0.3-NA and 13.5-nm wavelength, the depth of focus shrinks to 150 nm increasing the importance of high-sensitivity focal-plane detection tools. The FS is a free-standing Ni grating structure that works in concert with a simple mask pattern of regular lines and spaces at constant pitch. The FS pitch matches that of the image-plane aerial-image intensity: it transmits the light with high efficiency when the grating is aligned with the aerial image laterally and longitudinally. Using a single-element photodetector, to detect the transmitted flux, the FS is scanned laterally and longitudinally so the plane of peak aerial-image contrast can be found. The design under consideration has a fixed image-plane pitch of 80-nm, with aperture widths of 12-40-nm (1-3 wave-lengths), and aspect ratios of 2-8. TEMPEST-3D is used to model the light transmission. Careful attention is paid to the annular, partially coherent, unpolarized illumination and to the annular pupil of the Micro-Exposure Tool (MET) optics for which the FS is designed. The system design balances the opposing needs of high sensitivity and high throughput opti-mizing the signal-to-noise ratio in the measured intensity contrast.

EUV Focus Sensor: Design and Modeling

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

Goldberg, Kenneth A.; Teyssier, Maureen E.; Liddle, J. Alexander

We describe performance modeling and design optimization of a prototype EUV focus sensor (FS) designed for use with existing 0.3-NA EUV projection-lithography tools. At 0.3-NA and 13.5-nm wavelength, the depth of focus shrinks to 150 nm increasing the importance of high-sensitivity focal-plane detection tools. The FS is a free-standing Ni grating structure that works in concert with a simple mask pattern of regular lines and spaces at constant pitch. The FS pitch matches that of the image-plane aerial-image intensity: it transmits the light with high efficiency when the grating is aligned with the aerial image laterally and longitudinally. Using amore » single-element photodetector, to detect the transmitted flux, the FS is scanned laterally and longitudinally so the plane of peak aerial-image contrast can be found. The design under consideration has a fixed image-plane pitch of 80-nm, with aperture widths of 12-40-nm (1-3 wavelengths), and aspect ratios of 2-8. TEMPEST-3D is used to model the light transmission. Careful attention is paid to the annular, partially coherent, unpolarized illumination and to the annular pupil of the Micro-Exposure Tool (MET) optics for which the FS is designed. The system design balances the opposing needs of high sensitivity and high throughput optimizing the signal-to-noise ratio in the measured intensity contrast.« less

RGD-conjugated silica-coated gold nanorods on the surface of carbon nanotubes for targeted photoacoustic imaging of gastric cancer

NASA Astrophysics Data System (ADS)

Wang, Can; Bao, Chenchen; Liang, Shujing; Fu, Hualin; Wang, Kan; Deng, Min; Liao, Qiande; Cui, Daxiang

2014-05-01

Herein, we reported for the first time that RGD-conjugated silica-coated gold nanorods on the surface of multiwalled carbon nanotubes were successfully used for targeted photoacoustic imaging of in vivo gastric cancer cells. A simple strategy was used to attach covalently silica-coated gold nanorods (sGNRs) onto the surface of multiwalled carbon nanotubes (MWNTs) to fabricate a hybrid nanostructure. The cross-linked reaction occurred through the combination of carboxyl groups on the MWNTs and the amino group on the surface of sGNRs modified with a silane coupling agent. RGD peptides were conjugated with the sGNR/MWNT nanostructure; resultant RGD-conjugated sGNR/MWNT probes were investigated for their influences on viability of MGC803 and GES-1 cells. The nude mice models loaded with gastric cancer cells were prepared, the RGD-conjugated sGNR/MWNT probes were injected into gastric cancer-bearing nude mice models via the tail vein, and the nude mice were observed by an optoacoustic imaging system. Results showed that RGD-conjugated sGNR/MWNT probes showed good water solubility and low cellular toxicity, could target in vivo gastric cancer cells, and obtained strong photoacoustic imaging in the nude model. RGD-conjugated sGNR/MWNT probes will own great potential in applications such as targeted photoacoustic imaging and photothermal therapy in the near future.

Hypercat - Hypercube of AGN tori

NASA Astrophysics Data System (ADS)

Nikutta, Robert; Lopez-Rodriguez, Enrique; Ichikawa, Kohei; Levenson, Nancy A.; Packham, Christopher C.

2018-06-01

AGN unification and observations hold that a dusty torus obscures the central accretion engine along some lines of sight. SEDs of dust tori have been modeled for a long time, but resolved emission morphologies have not been studied in much detail, because resolved observations are only possible recently (VLTI,ALMA) and in the near future (TMT,ELT,GMT). Some observations challenge a simple torus model, because in several objects most of MIR emission appears to emanate from polar regions high above the equatorial plane, i.e. not where the dust supposedly resides.We introduce our software framework and hypercube of AGN tori (Hypercat) made with CLUMPY (www.clumpy.org), a large set of images (6 model parameters + wavelength) to facilitate studies of emission and dust morphologies. We make use of Hypercat to study the morphological properties of the emission and dust distributions as function of model parameters. We find that a simple clumpy torus can indeed produce 10-micron emission patterns extended in polar directions, with extension ratios compatible with those found in observations. We are able to constrain the range of parameters that produce such morphologies.

Quantitative image analysis of immunohistochemical stains using a CMYK color model

PubMed Central

Pham, Nhu-An; Morrison, Andrew; Schwock, Joerg; Aviel-Ronen, Sarit; Iakovlev, Vladimir; Tsao, Ming-Sound; Ho, James; Hedley, David W

2007-01-01

Background Computer image analysis techniques have decreased effects of observer biases, and increased the sensitivity and the throughput of immunohistochemistry (IHC) as a tissue-based procedure for the evaluation of diseases. Methods We adapted a Cyan/Magenta/Yellow/Key (CMYK) model for automated computer image analysis to quantify IHC stains in hematoxylin counterstained histological sections. Results The spectral characteristics of the chromogens AEC, DAB and NovaRed as well as the counterstain hematoxylin were first determined using CMYK, Red/Green/Blue (RGB), normalized RGB and Hue/Saturation/Lightness (HSL) color models. The contrast of chromogen intensities on a 0–255 scale (24-bit image file) as well as compared to the hematoxylin counterstain was greatest using the Yellow channel of a CMYK color model, suggesting an improved sensitivity for IHC evaluation compared to other color models. An increase in activated STAT3 levels due to growth factor stimulation, quantified using the Yellow channel image analysis was associated with an increase detected by Western blotting. Two clinical image data sets were used to compare the Yellow channel automated method with observer-dependent methods. First, a quantification of DAB-labeled carbonic anhydrase IX hypoxia marker in 414 sections obtained from 138 biopsies of cervical carcinoma showed strong association between Yellow channel and positive color selection results. Second, a linear relationship was also demonstrated between Yellow intensity and visual scoring for NovaRed-labeled epidermal growth factor receptor in 256 non-small cell lung cancer biopsies. Conclusion The Yellow channel image analysis method based on a CMYK color model is independent of observer biases for threshold and positive color selection, applicable to different chromogens, tolerant of hematoxylin, sensitive to small changes in IHC intensity and is applicable to simple automation procedures. These characteristics are advantageous for both basic as well as clinical research in an unbiased, reproducible and high throughput evaluation of IHC intensity. PMID:17326824

On the Forward Scattering of Microwave Breast Imaging

PubMed Central

Lui, Hoi-Shun; Fhager, Andreas; Persson, Mikael

2012-01-01

Microwave imaging for breast cancer detection has been of significant interest for the last two decades. Recent studies focus on solving the imaging problem using an inverse scattering approach. Efforts have mainly been focused on the development of the inverse scattering algorithms, experimental setup, antenna design and clinical trials. However, the success of microwave breast imaging also heavily relies on the quality of the forward data such that the tumor inside the breast volume is well illuminated. In this work, a numerical study of the forward scattering data is conducted. The scattering behavior of simple breast models under different polarization states and aspect angles of illumination are considered. Numerical results have demonstrated that better data contrast could be obtained when the breast volume is illuminated using cross-polarized components in linear polarization basis or the copolarized components in the circular polarization basis. PMID:22611371

Scattered wave imaging of the oceanic plate in Cascadia

PubMed Central

Rychert, Catherine A.; Harmon, Nicholas; Tharimena, Saikiran

2018-01-01

Fifty years after plate tectonic theory was developed, the defining mechanism of the plate is still widely debated. The relatively short, simple history of young ocean lithosphere makes it an ideal place to determine the property that defines a plate, yet the remoteness and harshness of the seafloor have made precise imaging challenging. We use S-to-P receiver functions to image discontinuities beneath newly formed lithosphere at the Juan de Fuca and Gorda Ridges. We image a strong negative discontinuity at the base of the plate increasing from 20 to 45 km depth beneath the 0- to 10-million-year-old seafloor and a positive discontinuity at the onset of melting at 90 to 130 km depth. Comparison with geodynamic models and experimental constraints indicates that the observed discontinuities cannot easily be reconciled with subsolidus mechanisms. Instead, partial melt may be required, which would decrease mantle viscosity and define the young oceanic plate. PMID:29457132

Feature extraction from multiple data sources using genetic programming

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Brumby, Steven P.; Pope, Paul A.; Eads, Damian R.; Esch-Mosher, Diana M.; Galassi, Mark C.; Harvey, Neal R.; McCulloch, Hersey D.; Perkins, Simon J.; Porter, Reid B.; Theiler, James P.; Young, Aaron C.; Bloch, Jeffrey J.; David, Nancy A.

2002-08-01

Feature extraction from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. We use the GENetic Imagery Exploitation (GENIE) software for this purpose, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniques to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land cover features including towns, wildfire burnscars, and forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.

Recognition of Equations Using a Two-Dimensional Stochastic Context-Free Grammar

NASA Astrophysics Data System (ADS)

Chou, Philip A.

1989-11-01

We propose using two-dimensional stochastic context-free grammars for image recognition, in a manner analogous to using hidden Markov models for speech recognition. The value of the approach is demonstrated in a system that recognizes printed, noisy equations. The system uses a two-dimensional probabilistic version of the Cocke-Younger-Kasami parsing algorithm to find the most likely parse of the observed image, and then traverses the corresponding parse tree in accordance with translation formats associated with each production rule, to produce eqn I troff commands for the imaged equation. In addition, it uses two-dimensional versions of the Inside/Outside and Baum re-estimation algorithms for learning the parameters of the grammar from a training set of examples. Parsing the image of a simple noisy equation currently takes about one second of cpu time on an Alliant FX/80.

Monocular correspondence detection for symmetrical objects by template matching

NASA Astrophysics Data System (ADS)

Vilmar, G.; Besslich, Philipp W., Jr.

1990-09-01

We describe a possibility to reconstruct 3-D information from a single view of an 3-D bilateral symmetric object. The symmetry assumption allows us to obtain a " second view" from a different viewpoint by a simple reflection of the monocular image. Therefore we have to solve the correspondence problem in a special case where known feature-based or area-based binocular approaches fail. In principle our approach is based on a frequency domain template matching of the features on the epipolar lines. During a training period our system " learns" the assignment of correspondence models to image features. The object shape is interpolated when no template matches to the image features. This fact is an important advantage of this methodology because no " real world" image holds the symmetry assumption perfectly. To simplify the training process we used single views on human faces (e. g. passport photos) but our system is trainable on any other kind of objects.

a Method for the Seamlines Network Automatic Selection Based on Building Vector

NASA Astrophysics Data System (ADS)

Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

2018-04-01

In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

The CASTLES Imaging Survey of Gravitational Lenses

NASA Astrophysics Data System (ADS)

Peng, C. Y.; Falco, E. E.; Lehar, J.; Impey, C. D.; Kochanek, C. S.; McLeod, B. A.; Rix, H.-W.

1997-12-01

The CASTLES survey (Cfa-Arizona-(H)ST-Lens-Survey) is imaging most known small-separation gravitational lenses (or lens candidates), using the NICMOS camera (mostly H-band) and the WFPC2 (V and I band) on HST. To date nearly half of the IR imaging survey has been completed. The main goals are: (1) to search for lens galaxies where none have been directly detected so far; (2) obtain photometric redshift estimates (VIH) for the lenses where no spectroscopic redshifts exist; (3) study and model the lens galaxies in detail, in part to study the mass distribution within them, in part to identify ``simple" systems that may permit accurate time delay estimates for H_0; (3) measure the M/L evolution of the sample of lens galaxies with look-back time (to z ~ 1); (4) determine directly which fraction of sources are lensed by ellipticals vs. spirals. We will present the survey specifications and the images obtained so far.

Narrow-field imaging of the lunar sodium exosphere

NASA Technical Reports Server (NTRS)

Stern, S. Alan; Flynn, Brian C.

1995-01-01

We present the first results of a new technique for imaging the lunar Na atmosphere. The technique employs high resolution, a narrow bandpass, and specific observing geometry to suppress scattered light and image lunar atmospheric Na I emission down to approximately 50 km altitude. Analysis of four latitudinally dispersed images shows that the lunar Na atmosphere exhibits intersting latitudinal and radial dependencies. Application of a simple Maxwellian collisionless exosphere model indicates that: (1) at least two thermal populations are required to adequately fit the soldium's radial intensity behavior, and (2) the fractional abundances and temperatures of the two components vary systematically with latitude. We conclude that both cold (barometric) and hot (suprathermal) Na may coexist in the lunar atmosphere, either as distinct components or as elements of a continuum of populations ranging in temperature from the local surface temperature up to or exceeding escape energies.

A gravitational lens candidate discovered with the Hubble Space Telescope

NASA Technical Reports Server (NTRS)

Maoz, Dan; Bahcall, John N.; Schneider, Donald P.; Doxsey, Rodger; Bahcall, Neta A.; Filippenko, Alexei V.; Goss, W. M.; Lahav, Ofer; Yanny, Brian

1992-01-01

Evidence is reported for gravitational lensing of the high-redshift (z = 3.8) quasar 1208 + 101, observed as part of the Snapshot survey with the HST Planetary Camera. An HST V image taken on gyroscopes resolves the quasar into three point-source components, with the two fainter images having separations of 0.1 and 0.5 arcsec from the central bright component. A radio observation of the quasar with the VLA at 2 cm shows that, like most quasars of this redhsift, 1208 + 101 is radio quiet. Based on positional information alone, the probability that the observed optical components are chance superpositions of Galactic stars is small, but not negligible. Analysis of a combined ground-based spectrum of all three components, using the relative brightnesses of the HST image, supports the lensing hypothesis. If all the components are lensed images of the quasar, the observed configuration cannot be reproduced by simple lens models.

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

Szymanski, J. J.; Brumby, Steven P.; Pope, P. A.

Feature extration from imagery is an important and long-standing problem in remote sensing. In this paper, we report on work using genetic programming to perform feature extraction simultaneously from multispectral and digital elevation model (DEM) data. The tool used is the GENetic Imagery Exploitation (GENIE) software, which produces image-processing software that inherently combines spatial and spectral processing. GENIE is particularly useful in exploratory studies of imagery, such as one often does in combining data from multiple sources. The user trains the software by painting the feature of interest with a simple graphical user interface. GENIE then uses genetic programming techniquesmore » to produce an image-processing pipeline. Here, we demonstrate evolution of image processing algorithms that extract a range of land-cover features including towns, grasslands, wild fire burn scars, and several types of forest. We use imagery from the DOE/NNSA Multispectral Thermal Imager (MTI) spacecraft, fused with USGS 1:24000 scale DEM data.« less

A new approach towards image based virtual 3D city modeling by using close range photogrammetry

NASA Astrophysics Data System (ADS)

Singh, S. P.; Jain, K.; Mandla, V. R.

2014-05-01

3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing day to day for various engineering and non-engineering applications. Generally three main image based approaches are using for virtual 3D city models generation. In first approach, researchers used Sketch based modeling, second method is Procedural grammar based modeling and third approach is Close range photogrammetry based modeling. Literature study shows that till date, there is no complete solution available to create complete 3D city model by using images. These image based methods also have limitations This paper gives a new approach towards image based virtual 3D city modeling by using close range photogrammetry. This approach is divided into three sections. First, data acquisition process, second is 3D data processing, and third is data combination process. In data acquisition process, a multi-camera setup developed and used for video recording of an area. Image frames created from video data. Minimum required and suitable video image frame selected for 3D processing. In second section, based on close range photogrammetric principles and computer vision techniques, 3D model of area created. In third section, this 3D model exported to adding and merging of other pieces of large area. Scaling and alignment of 3D model was done. After applying the texturing and rendering on this model, a final photo-realistic textured 3D model created. This 3D model transferred into walk-through model or in movie form. Most of the processing steps are automatic. So this method is cost effective and less laborious. Accuracy of this model is good. For this research work, study area is the campus of department of civil engineering, Indian Institute of Technology, Roorkee. This campus acts as a prototype for city. Aerial photography is restricted in many country and high resolution satellite images are costly. In this study, proposed method is based on only simple video recording of area. Thus this proposed method is suitable for 3D city modeling. Photo-realistic, scalable, geo-referenced virtual 3D city model is useful for various kinds of applications such as for planning in navigation, tourism, disasters management, transportations, municipality, urban and environmental managements, real-estate industry. Thus this study will provide a good roadmap for geomatics community to create photo-realistic virtual 3D city model by using close range photogrammetry.

Fluorescence imaging of angiogenesis in green fluorescent protein-expressing tumors

NASA Astrophysics Data System (ADS)

Yang, Meng; Baranov, Eugene; Jiang, Ping; Li, Xiao-Ming; Wang, Jin W.; Li, Lingna; Yagi, Shigeo; Moossa, A. R.; Hoffman, Robert M.

2002-05-01

The development of therapeutics for the control of tumor angiogenesis requires a simple, reliable in vivo assay for tumor-induced vascularization. For this purpose, we have adapted the orthotopic implantation model of angiogenesis by using human and rodent tumors genetically tagged with Aequorea victoria green fluorescent protein (GFP) for grafting into nude mice. Genetically-fluorescent tumors can be readily imaged in vivo. The non-luminous induced capillaries are clearly visible against the bright tumor fluorescence examined either intravitally or by whole-body luminance in real time. Fluorescence shadowing replaces the laborious histological techniques for determining blood vessel density. High-level GFP-expressing tumor cell lines made it possible to acquire the high-resolution real-time fluorescent optical images of angiogenesis in both primary tumors and their metastatic lesions in various human and rodent tumor models by means of a light-based imaging system. Intravital images of angiogenesis onset and development were acquired and quantified from a GFP- expressing orthotopically-growing human prostate tumor over a 19-day period. Whole-body optical imaging visualized vessel density increasing linearly over a 20-week period in orthotopically-growing, GFP-expressing human breast tumor MDA-MB-435. Vessels in an orthotopically-growing GFP- expressing Lewis lung carcinoma tumor were visualized through the chest wall via a reversible skin flap. These clinically-relevant angiogenesis mouse models can be used for real-time in vivo evaluation of agents inhibiting or promoting tumor angiogenesis in physiological micro- environments.

Quantitative, depth-resolved determination of particle motion using multi-exposure, spatial frequency domain laser speckle imaging.

PubMed

Rice, Tyler B; Kwan, Elliott; Hayakawa, Carole K; Durkin, Anthony J; Choi, Bernard; Tromberg, Bruce J

2013-01-01

Laser Speckle Imaging (LSI) is a simple, noninvasive technique for rapid imaging of particle motion in scattering media such as biological tissue. LSI is generally used to derive a qualitative index of relative blood flow due to unknown impact from several variables that affect speckle contrast. These variables may include optical absorption and scattering coefficients, multi-layer dynamics including static, non-ergodic regions, and systematic effects such as laser coherence length. In order to account for these effects and move toward quantitative, depth-resolved LSI, we have developed a method that combines Monte Carlo modeling, multi-exposure speckle imaging (MESI), spatial frequency domain imaging (SFDI), and careful instrument calibration. Monte Carlo models were used to generate total and layer-specific fractional momentum transfer distributions. This information was used to predict speckle contrast as a function of exposure time, spatial frequency, layer thickness, and layer dynamics. To verify with experimental data, controlled phantom experiments with characteristic tissue optical properties were performed using a structured light speckle imaging system. Three main geometries were explored: 1) diffusive dynamic layer beneath a static layer, 2) static layer beneath a diffuse dynamic layer, and 3) directed flow (tube) submerged in a dynamic scattering layer. Data fits were performed using the Monte Carlo model, which accurately reconstructed the type of particle flow (diffusive or directed) in each layer, the layer thickness, and absolute flow speeds to within 15% or better.

Off-Angle Iris Correction Methods

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

Santos-Villalobos, Hector J; Thompson, Joseph T; Karakaya, Mahmut

In many real world iris recognition systems obtaining consistent frontal images is problematic do to inexperienced or uncooperative users, untrained operators, or distracting environments. As a result many collected images are unusable by modern iris matchers. In this chapter we present four methods for correcting off-angle iris images to appear frontal which makes them compatible with existing iris matchers. The methods include an affine correction, a retraced model of the human eye, measured displacements, and a genetic algorithm optimized correction. The affine correction represents a simple way to create an iris image that appears frontal but it does not accountmore » for refractive distortions of the cornea. The other method account for refraction. The retraced model simulates the optical properties of the cornea. The other two methods are data driven. The first uses optical flow to measure the displacements of the iris texture when compared to frontal images of the same subject. The second uses a genetic algorithm to learn a mapping that optimizes the Hamming Distance scores between off-angle and frontal images. In this paper we hypothesize that the biological model presented in our earlier work does not adequately account for all variations in eye anatomy and therefore the two data-driven approaches should yield better performance. Results are presented using the commercial VeriEye matcher that show that the genetic algorithm method clearly improves over prior work and makes iris recognition possible up to 50 degrees off-angle.« less

Quantification of video-taped images in microcirculation research using inexpensive imaging software (Adobe Photoshop).

PubMed

Brunner, J; Krummenauer, F; Lehr, H A

2000-04-01

Study end-points in microcirculation research are usually video-taped images rather than numeric computer print-outs. Analysis of these video-taped images for the quantification of microcirculatory parameters usually requires computer-based image analysis systems. Most software programs for image analysis are custom-made, expensive, and limited in their applicability to selected parameters and study end-points. We demonstrate herein that an inexpensive, commercially available computer software (Adobe Photoshop), run on a Macintosh G3 computer with inbuilt graphic capture board provides versatile, easy to use tools for the quantification of digitized video images. Using images obtained by intravital fluorescence microscopy from the pre- and postischemic muscle microcirculation in the skinfold chamber model in hamsters, Photoshop allows simple and rapid quantification (i) of microvessel diameters, (ii) of the functional capillary density and (iii) of postischemic leakage of FITC-labeled high molecular weight dextran from postcapillary venules. We present evidence of the technical accuracy of the software tools and of a high degree of interobserver reliability. Inexpensive commercially available imaging programs (i.e., Adobe Photoshop) provide versatile tools for image analysis with a wide range of potential applications in microcirculation research.

Extremely simple holographic projection of color images

NASA Astrophysics Data System (ADS)

Makowski, Michal; Ducin, Izabela; Kakarenko, Karol; Suszek, Jaroslaw; Kolodziejczyk, Andrzej; Sypek, Maciej

2012-03-01

A very simple scheme of holographic projection is presented with some experimental results showing good quality image projection without any imaging lens. This technique can be regarded as an alternative to classic projection methods. It is based on the reconstruction real images from three phase iterated Fourier holograms. The illumination is performed with three laser beams of primary colors. A divergent wavefront geometry is used to achieve an increased throw angle of the projection, compared to plane wave illumination. Light fibers are used as light guidance in order to keep the setup as simple as possible and to provide point-like sources of high quality divergent wave-fronts at optimized position against the light modulator. Absorbing spectral filters are implemented to multiplex three holograms on a single phase-only spatial light modulator. Hence color mixing occurs without any time-division methods, which cause rainbow effects and color flicker. The zero diffractive order with divergent illumination is practically invisible and speckle field is effectively suppressed with phase optimization and time averaging techniques. The main advantages of the proposed concept are: a very simple and highly miniaturizable configuration; lack of lens; a single LCoS (Liquid Crystal on Silicon) modulator; a strong resistance to imperfections and obstructions of the spatial light modulator like dead pixels, dust, mud, fingerprints etc.; simple calculations based on Fast Fourier Transform (FFT) easily processed in real time mode with GPU (Graphic Programming).

Simple, inexpensive technique for high-quality smartphone fundus photography in human and animal eyes.

PubMed

Haddock, Luis J; Kim, David Y; Mukai, Shizuo

2013-01-01

Purpose. We describe in detail a relatively simple technique of fundus photography in human and rabbit eyes using a smartphone, an inexpensive app for the smartphone, and instruments that are readily available in an ophthalmic practice. Methods. Fundus images were captured with a smartphone and a 20D lens with or without a Koeppe lens. By using the coaxial light source of the phone, this system works as an indirect ophthalmoscope that creates a digital image of the fundus. The application whose software allows for independent control of focus, exposure, and light intensity during video filming was used. With this app, we recorded high-definition videos of the fundus and subsequently extracted high-quality, still images from the video clip. Results. The described technique of smartphone fundus photography was able to capture excellent high-quality fundus images in both children under anesthesia and in awake adults. Excellent images were acquired with the 20D lens alone in the clinic, and the addition of the Koeppe lens in the operating room resulted in the best quality images. Successful photodocumentation of rabbit fundus was achieved in control and experimental eyes. Conclusion. The currently described system was able to take consistently high-quality fundus photographs in patients and in animals using readily available instruments that are portable with simple power sources. It is relatively simple to master, is relatively inexpensive, and can take advantage of the expanding mobile-telephone networks for telemedicine.

Reconstruction of measurable three-dimensional point cloud model based on large-scene archaeological excavation sites

NASA Astrophysics Data System (ADS)

Zhang, Chun-Sen; Zhang, Meng-Meng; Zhang, Wei-Xing

2017-01-01

This paper outlines a low-cost, user-friendly photogrammetric technique with nonmetric cameras to obtain excavation site digital sequence images, based on photogrammetry and computer vision. Digital camera calibration, automatic aerial triangulation, image feature extraction, image sequence matching, and dense digital differential rectification are used, combined with a certain number of global control points of the excavation site, to reconstruct the high precision of measured three-dimensional (3-D) models. Using the acrobatic figurines in the Qin Shi Huang mausoleum excavation as an example, our method solves the problems of little base-to-height ratio, high inclination, unstable altitudes, and significant ground elevation changes affecting image matching. Compared to 3-D laser scanning, the 3-D color point cloud obtained by this method can maintain the same visual result and has advantages of low project cost, simple data processing, and high accuracy. Structure-from-motion (SfM) is often used to reconstruct 3-D models of large scenes and has lower accuracy if it is a reconstructed 3-D model of a small scene at close range. Results indicate that this method quickly achieves 3-D reconstruction of large archaeological sites and produces heritage site distribution of orthophotos providing a scientific basis for accurate location of cultural relics, archaeological excavations, investigation, and site protection planning. This proposed method has a comprehensive application value.

Creating an Optimal 3D Printed Model for Temporal Bone Dissection Training.

PubMed

Takahashi, Kuniyuki; Morita, Yuka; Ohshima, Shinsuke; Izumi, Shuji; Kubota, Yamato; Yamamoto, Yutaka; Takahashi, Sugata; Horii, Arata

2017-07-01

Making a 3-dimensional (3D) temporal bone model is simple using a plaster powder bed and an inkjet printer. However, it is difficult to reproduce air-containing spaces and precise middle ear structures. The objective of this study was to overcome these problems and create a temporal bone model that would be useful both as a training tool and for preoperative simulation. Drainage holes were made to remove excess materials from air-containing spaces, ossicle ligaments were manually changed to bony structures, and small and/or soft tissue structures were colored differently while designing the 3D models. The outcomes were evaluated by 3 procedures: macroscopic and endoscopic inspection of the model, comparison of computed tomography (CT) images of the model to the original CT, and assessment of tactile sensation and reproducibility by 20 surgeons performing surgery on the model. Macroscopic and endoscopic inspection, CT images, and assessment by surgeons were in agreement in terms of reproducibility of model structures. Most structures could be reproduced, but the stapes, tympanic sinus, and mastoid air cells were unsatisfactory. Perioperative tactile sensation of the model was excellent. Although this model still does not embody perfect reproducibility, it proved sufficiently practical for use in surgical training.

Laser speckle imaging to improve clinical outcomes for patients with trigeminal neuralgia undergoing radiofrequency thermocoagulation.

PubMed

Ringkamp, Matthias; Wooten, Matthew; Carson, Benjamin S; Lim, Michael; Hartke, Timothy; Guarnieri, Michael

2016-02-01

Percutaneous treatments for trigeminal neuralgia are safe, simple, and effective for achieving good pain control. Procedural risks could be minimized by using noninvasive imaging techniques to improve the placement of the radiofrequency thermocoagulation probe into the trigeminal ganglion. Positioning of a probe is crucial to maximize pain relief and to minimize unwanted side effects, such as denervation in unaffected areas. This investigation examined the use of laser speckle imaging during probe placement in an animal model. This preclinical safety study used nonhuman primates, Macaca nemestrina (pigtail monkeys), to examine whether real-time imaging of blood flow in the face during the positioning of a coagulation probe could monitor the location and guide the positioning of the probe within the trigeminal ganglion. Data from 6 experiments in 3 pigtail monkeys support the hypothesis that laser imaging is safe and improves the accuracy of probe placement. Noninvasive laser speckle imaging can be performed safely in nonhuman primates. Because improved probe placement may reduce morbidity associated with percutaneous rhizotomies, efficacy trials of laser speckle imaging should be conducted in humans.

Circular motion geometry using minimal data.

PubMed

Jiang, Guang; Quan, Long; Tsui, Hung-Tat

2004-06-01

Circular motion or single axis motion is widely used in computer vision and graphics for 3D model acquisition. This paper describes a new and simple method for recovering the geometry of uncalibrated circular motion from a minimal set of only two points in four images. This problem has been previously solved using nonminimal data either by computing the fundamental matrix and trifocal tensor in three images or by fitting conics to tracked points in five or more images. It is first established that two sets of tracked points in different images under circular motion for two distinct space points are related by a homography. Then, we compute a plane homography from a minimal two points in four images. After that, we show that the unique pair of complex conjugate eigenvectors of this homography are the image of the circular points of the parallel planes of the circular motion. Subsequently, all other motion and structure parameters are computed from this homography in a straighforward manner. The experiments on real image sequences demonstrate the simplicity, accuracy, and robustness of the new method.

Enhancing in vivo tumor boundary delineation with structured illumination fluorescence molecular imaging and spatial gradient mapping

NASA Astrophysics Data System (ADS)

Sun, Jessica; Miller, Jessica P.; Hathi, Deep; Zhou, Haiying; Achilefu, Samuel; Shokeen, Monica; Akers, Walter J.

2016-08-01

Fluorescence imaging, in combination with tumor-avid near-infrared (NIR) fluorescent molecular probes, provides high specificity and sensitivity for cancer detection in preclinical animal models, and more recently, assistance during oncologic surgery. However, conventional camera-based fluorescence imaging techniques are heavily surface-weighted such that surface reflection from skin or other nontumor tissue and nonspecific fluorescence signals dominate, obscuring true cancer-specific signals and blurring tumor boundaries. To address this challenge, we applied structured illumination fluorescence molecular imaging (SIFMI) in live animals for automated subtraction of nonspecific surface signals to better delineate accumulation of an NIR fluorescent probe targeting α4β1 integrin in mice bearing subcutaneous plasma cell xenografts. SIFMI demonstrated a fivefold improvement in tumor-to-background contrast when compared with other full-field fluorescence imaging methods and required significantly reduced scanning time compared with diffuse optical spectroscopy imaging. Furthermore, the spatial gradient mapping enhanced highlighting of tumor boundaries. Through the relatively simple hardware and software modifications described, SIFMI can be integrated with clinical fluorescence imaging systems, enhancing intraoperative tumor boundary delineation from the uninvolved tissue.

Point spread functions and deconvolution of ultrasonic images.

PubMed

Dalitz, Christoph; Pohle-Fröhlich, Regina; Michalk, Thorsten

2015-03-01

This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formulation of the imaging process, and an analytic formula for the PSF of planar transducers is derived. For this analytic expression, different numerical and analytic approximation schemes for evaluating the PSF are presented. By comparing simulated images with measured C-scan images, we demonstrate that the assumptions of LST in combination with our formula for the PSF are a good model for the pulse-echo imaging process. To reconstruct the object from a C-scan image, we compare different deconvolution schemes: the Wiener filter, the ForWaRD algorithm, and the Richardson-Lucy algorithm. The best results are obtained with the Richardson-Lucy algorithm with total variation regularization. For distances greater or equal twice the near field distance, our experiments show that the numerically computed PSF can be replaced with a simple closed analytic term based on a far field approximation.

Two Magnets and a Ball Bearing: A Simple Demonstration of the Methods of Images.

ERIC Educational Resources Information Center

Poon, W. C. K.

2003-01-01

Investigates the behavior of a bar magnet with a steel ball bearing on one pole as it approaches another bar magnet. Maps the problem onto electrostatics and explains observations based on the behavior of point charges near an isolated, uncharged sphere. Offers a simple demonstration of the method of images in electrostatics. (Author/NB)

Simulation and analysis of light scattering by multilamellar bodies present in the human eye

PubMed Central

Méndez-Aguilar, Emilia M.; Kelly-Pérez, Ismael; Berriel-Valdos, L. R.; Delgado-Atencio, José A.

2017-01-01

A modified computational model of the human eye was used to obtain and compare different probability density functions, radial profiles of light pattern distributions, and images of the point spread function formed in the human retina under the presence of different kinds of particles inside crystalline lenses suffering from cataracts. Specifically, this work uses simple particles without shells and multilamellar bodies (MLBs) with shells. The emergence of such particles alters the formation of images on the retina. Moreover, the MLBs change over time, which affects properties such as the refractive index of their shell. Hence, this work not only simulates the presence of such particles but also evaluates the incidence of particle parameters such as particle diameter, particle thickness, and shell refractive index, which are set based on reported experimental values. In addition, two wavelengths (400 nm and 700 nm) are used for light passing through the different layers of the computational model. The effects of these parameters on light scattering are analyzed using the simulation results. Further, in these results, the effects of light scattering on image formation can be seen when single particles, early-stage MLBs, or mature MLBs are incorporated in the model. Finally, it is found that particle diameter has the greatest impact on image formation. PMID:28663924

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.

Simulation and analysis of light scattering by multilamellar bodies present in the human eye.

PubMed

Méndez-Aguilar, Emilia M; Kelly-Pérez, Ismael; Berriel-Valdos, L R; Delgado-Atencio, José A

2017-06-01

A modified computational model of the human eye was used to obtain and compare different probability density functions, radial profiles of light pattern distributions, and images of the point spread function formed in the human retina under the presence of different kinds of particles inside crystalline lenses suffering from cataracts. Specifically, this work uses simple particles without shells and multilamellar bodies (MLBs) with shells. The emergence of such particles alters the formation of images on the retina. Moreover, the MLBs change over time, which affects properties such as the refractive index of their shell. Hence, this work not only simulates the presence of such particles but also evaluates the incidence of particle parameters such as particle diameter, particle thickness, and shell refractive index, which are set based on reported experimental values. In addition, two wavelengths (400 nm and 700 nm) are used for light passing through the different layers of the computational model. The effects of these parameters on light scattering are analyzed using the simulation results. Further, in these results, the effects of light scattering on image formation can be seen when single particles, early-stage MLBs, or mature MLBs are incorporated in the model. Finally, it is found that particle diameter has the greatest impact on image formation.

A multi-scale Lattice Boltzmann model for simulating solute transport in 3D X-ray micro-tomography images of aggregated porous materials

NASA Astrophysics Data System (ADS)

Zhang, Xiaoxian; Crawford, John W.; Flavel, Richard J.; Young, Iain M.

2016-10-01

The Lattice Boltzmann (LB) model and X-ray computed tomography (CT) have been increasingly used in combination over the past decade to simulate water flow and chemical transport at pore scale in porous materials. Because of its limitation in resolution and the hierarchical structure of most natural soils, the X-ray CT tomography can only identify pores that are greater than its resolution and treats other pores as solid. As a result, the so-called solid phase in X-ray images may in reality be a grey phase, containing substantial connected pores capable of conducing fluids and solute. Although modified LB models have been developed to simulate fluid flow in such media, models for solute transport are relatively limited. In this paper, we propose a LB model for simulating solute transport in binary soil images containing permeable solid phase. The model is based on the single-relaxation time approach and uses a modified partial bounce-back method to describe the resistance caused by the permeable solid phase to chemical transport. We derive the relationship between the diffusion coefficient and the parameter introduced in the partial bounce-back method, and test the model against analytical solution for movement of a pulse of tracer. We also validate it against classical finite volume method for solute diffusion in a simple 2D image, and then apply the model to a soil image acquired using X-ray tomography at resolution of 30 μm in attempts to analyse how the ability of the solid phase to diffuse solute at micron-scale affects the behaviour of the solute at macro-scale after a volumetric average. Based on the simulated results, we discuss briefly the danger in interpreting experimental results using the continuum model without fully understanding the pore-scale processes, as well as the potential of using pore-scale modelling and tomography to help improve the continuum models.

Building a 2.5D Digital Elevation Model from 2D Imagery

NASA Technical Reports Server (NTRS)

Padgett, Curtis W.; Ansar, Adnan I.; Brennan, Shane; Cheng, Yang; Clouse, Daniel S.; Almeida, Eduardo

2013-01-01

When projecting imagery into a georeferenced coordinate frame, one needs to have some model of the geographical region that is being projected to. This model can sometimes be a simple geometrical curve, such as an ellipse or even a plane. However, to obtain accurate projections, one needs to have a more sophisticated model that encodes the undulations in the terrain including things like mountains, valleys, and even manmade structures. The product that is often used for this purpose is a Digital Elevation Model (DEM). The technology presented here generates a high-quality DEM from a collection of 2D images taken from multiple viewpoints, plus pose data for each of the images and a camera model for the sensor. The technology assumes that the images are all of the same region of the environment. The pose data for each image is used as an initial estimate of the geometric relationship between the images, but the pose data is often noisy and not of sufficient quality to build a high-quality DEM. Therefore, the source imagery is passed through a feature-tracking algorithm and multi-plane-homography algorithm, which refine the geometric transforms between images. The images and their refined poses are then passed to a stereo algorithm, which generates dense 3D data for each image in the sequence. The 3D data from each image is then placed into a consistent coordinate frame and passed to a routine that divides the coordinate frame into a number of cells. The 3D points that fall into each cell are collected, and basic statistics are applied to determine the elevation of that cell. The result of this step is a DEM that is in an arbitrary coordinate frame. This DEM is then filtered and smoothed in order to remove small artifacts. The final step in the algorithm is to take the initial DEM and rotate and translate it to be in the world coordinate frame [such as UTM (Universal Transverse Mercator), MGRS (Military Grid Reference System), or geodetic] such that it can be saved in a standard DEM format and used for projection.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography)

PubMed Central

Siegel, Nisan; Storrie, Brian; Bruce, Marc

2016-01-01

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called “CINCH”. An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution. PMID:26839443

Fast iterative image reconstruction using sparse matrix factorization with GPU acceleration

NASA Astrophysics Data System (ADS)

Zhou, Jian; Qi, Jinyi

2011-03-01

Statistically based iterative approaches for image reconstruction have gained much attention in medical imaging. An accurate system matrix that defines the mapping from the image space to the data space is the key to high-resolution image reconstruction. However, an accurate system matrix is often associated with high computational cost and huge storage requirement. Here we present a method to address this problem by using sparse matrix factorization and parallel computing on a graphic processing unit (GPU).We factor the accurate system matrix into three sparse matrices: a sinogram blurring matrix, a geometric projection matrix, and an image blurring matrix. The sinogram blurring matrix models the detector response. The geometric projection matrix is based on a simple line integral model. The image blurring matrix is to compensate for the line-of-response (LOR) degradation due to the simplified geometric projection matrix. The geometric projection matrix is precomputed, while the sinogram and image blurring matrices are estimated by minimizing the difference between the factored system matrix and the original system matrix. The resulting factored system matrix has much less number of nonzero elements than the original system matrix and thus substantially reduces the storage and computation cost. The smaller size also allows an efficient implement of the forward and back projectors on GPUs, which have limited amount of memory. Our simulation studies show that the proposed method can dramatically reduce the computation cost of high-resolution iterative image reconstruction. The proposed technique is applicable to image reconstruction for different imaging modalities, including x-ray CT, PET, and SPECT.

Improvements in Modeling the Collimated Jets of Comet 19P/Borrelly from the Stereo Images of the Deep Space 1 Flyby

NASA Astrophysics Data System (ADS)

Melville, Kenneth J.; Farnham, T.; Hoban, S.

2010-10-01

On September 22, 2001, the spacecraft Deep Space 1 (DS1), which was primarily designed for testing advanced technologies in space, preformed an extended mission flyby of the comet 19P/Borrelly. This encounter provided scientists with the best images taken of a comet. These images from the DS1 Miniature Integrated Camera and Spectrometer (MICAS) instrument show features of comet Borrelly's surface; collimated dust jets escaping the nucleus, and the coma of gas and dust that surrounds the nucleus. Properties of the jet, such as rate and angle of expansion have been measured accurately due to the jet's geometric structure and position on the rotation axis of the comet. These measurements have been taken for several points along the spacecrafts approach, flyby, and from additional McDonald ground based observatory images. A model of the jet with similar geometry has been constructed in order to reproduce the observational data found in the flyby images. Other proposed models are tested as well. Once these models has been adjusted to replicate the data, they can be used to investigate the collimation mechanism below the comets surface producing the jet. Comet 19P/Borrelly is the idea test for this model due to the simple structure of the jet, as well as the wide variety of angles and observation times. Using information from this model, scientists may be able to make new assumptions on the composition and physical structure of other comets. This research was supported by the NASA Planetary Data System: Small Bodies Node, and College Student Investigator Program at UMBC Goddard Earth Sciences & Technology Center.

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Super-Resolution Image Reconstruction Applied to Medical Ultrasound

NASA Astrophysics Data System (ADS)

Ellis, Michael

Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in vivo images of a human testicle. In all instances, the methods presented here outperform conventional image reconstruction methods by a significant margin. As TONE and its variants are general image reconstruction techniques, the theories and research presented here have the potential to significantly improve not only ultrasound's clinical utility, but that of other imaging modalities as well.

Salient in space, salient in time: Fixation probability predicts fixation duration during natural scene viewing.

PubMed

Einhäuser, Wolfgang; Nuthmann, Antje

2016-09-01

During natural scene viewing, humans typically attend and fixate selected locations for about 200-400 ms. Two variables characterize such "overt" attention: the probability of a location being fixated, and the fixation's duration. Both variables have been widely researched, but little is known about their relation. We use a two-step approach to investigate the relation between fixation probability and duration. In the first step, we use a large corpus of fixation data. We demonstrate that fixation probability (empirical salience) predicts fixation duration across different observers and tasks. Linear mixed-effects modeling shows that this relation is explained neither by joint dependencies on simple image features (luminance, contrast, edge density) nor by spatial biases (central bias). In the second step, we experimentally manipulate some of these features. We find that fixation probability from the corpus data still predicts fixation duration for this new set of experimental data. This holds even if stimuli are deprived of low-level images features, as long as higher level scene structure remains intact. Together, this shows a robust relation between fixation duration and probability, which does not depend on simple image features. Moreover, the study exemplifies the combination of empirical research on a large corpus of data with targeted experimental manipulations.

Computation of fluid flow and pore-space properties estimation on micro-CT images of rock samples

NASA Astrophysics Data System (ADS)

Starnoni, M.; Pokrajac, D.; Neilson, J. E.

2017-09-01

Accurate determination of the petrophysical properties of rocks, namely REV, mean pore and grain size and absolute permeability, is essential for a broad range of engineering applications. Here, the petrophysical properties of rocks are calculated using an integrated approach comprising image processing, statistical correlation and numerical simulations. The Stokes equations of creeping flow for incompressible fluids are solved using the Finite-Volume SIMPLE algorithm. Simulations are then carried out on three-dimensional digital images obtained from micro-CT scanning of two rock formations: one sandstone and one carbonate. Permeability is predicted from the computed flow field using Darcy's law. It is shown that REV, REA and mean pore and grain size are effectively estimated using the two-point spatial correlation function. Homogeneity and anisotropy are also evaluated using the same statistical tools. A comparison of different absolute permeability estimates is also presented, revealing a good agreement between the numerical value and the experimentally determined one for the carbonate sample, but a large discrepancy for the sandstone. Finally, a new convergence criterion for the SIMPLE algorithm, and more generally for the family of pressure-correction methods, is presented. This criterion is based on satisfaction of bulk momentum balance, which makes it particularly useful for pore-scale modelling of reservoir rocks.

A Simple Noise Correction Scheme for Diffusional Kurtosis Imaging

PubMed Central

Glenn, G. Russell; Tabesh, Ali; Jensen, Jens H.

2014-01-01

Purpose Diffusional kurtosis imaging (DKI) is sensitive to the effects of signal noise due to strong diffusion weightings and higher order modeling of the diffusion weighted signal. A simple noise correction scheme is proposed to remove the majority of the noise bias in the estimated diffusional kurtosis. Methods Weighted linear least squares (WLLS) fitting together with a voxel-wise, subtraction-based noise correction from multiple, independent acquisitions are employed to reduce noise bias in DKI data. The method is validated in phantom experiments and demonstrated for in vivo human brain for DKI-derived parameter estimates. Results As long as the signal-to-noise ratio (SNR) for the most heavily diffusion weighted images is greater than 2.1, errors in phantom diffusional kurtosis estimates are found to be less than 5 percent with noise correction, but as high as 44 percent for uncorrected estimates. In human brain, noise correction is also shown to improve diffusional kurtosis estimates derived from measurements made with low SNR. Conclusion The proposed correction technique removes the majority of noise bias from diffusional kurtosis estimates in noisy phantom data and is applicable to DKI of human brain. Features of the method include computational simplicity and ease of integration into standard WLLS DKI post-processing algorithms. PMID:25172990

Super-global distortion correction for a rotational C-arm x-ray image intensifier.

PubMed

Liu, R R; Rudin, S; Bednarek, D R

1999-09-01

Image intensifier (II) distortion changes as a function of C-arm rotation angle because of changes in the orientation of the II with the earth's or other stray magnetic fields. For cone-beam computed tomography (CT), distortion correction for all angles is essential. The new super-global distortion correction consists of a model to continuously correct II distortion not only at each location in the image but for every rotational angle of the C arm. Calibration bead images were acquired with a standard C arm in 9 in. II mode. The super-global (SG) model is obtained from the single-plane global correction of the selected calibration images with given sampling angle interval. The fifth-order single-plane global corrections yielded a residual rms error of 0.20 pixels, while the SG model yielded a rms error of 0.21 pixels, a negligibly small difference. We evaluated the accuracy dependence of the SG model on various factors, such as the single-plane global fitting order, SG order, and angular sampling interval. We found that a good SG model can be obtained using a sixth-order SG polynomial fit based on the fifth-order single-plane global correction, and that a 10 degrees sampling interval was sufficient. Thus, the SG model saves processing resources and storage space. The residual errors from the mechanical errors of the x-ray system were also investigated, and found comparable with the SG residual error. Additionally, a single-plane global correction was done in the cylindrical coordinate system, and physical information about pincushion distortion and S distortion were observed and analyzed; however, this method is not recommended due to a lack of calculational efficiency. In conclusion, the SG model provides an accurate, fast, and simple correction for rotational C-arm images, which may be used for cone-beam CT.

Ganalyzer: A tool for automatic galaxy image analysis

NASA Astrophysics Data System (ADS)

Shamir, Lior

2011-05-01

Ganalyzer is a model-based tool that automatically analyzes and classifies galaxy images. Ganalyzer works by separating the galaxy pixels from the background pixels, finding the center and radius of the galaxy, generating the radial intensity plot, and then computing the slopes of the peaks detected in the radial intensity plot to measure the spirality of the galaxy and determine its morphological class. Unlike algorithms that are based on machine learning, Ganalyzer is based on measuring the spirality of the galaxy, a task that is difficult to perform manually, and in many cases can provide a more accurate analysis compared to manual observation. Ganalyzer is simple to use, and can be easily embedded into other image analysis applications. Another advantage is its speed, which allows it to analyze ~10,000,000 galaxy images in five days using a standard modern desktop computer. These capabilities can make Ganalyzer a useful tool in analyzing large datasets of galaxy images collected by autonomous sky surveys such as SDSS, LSST or DES.

Inviscid Limit for Damped and Driven Incompressible Navier-Stokes Equations in mathbb R^2

NASA Astrophysics Data System (ADS)

Ramanah, D.; Raghunath, S.; Mee, D. J.; Rösgen, T.; Jacobs, P. A.

2007-08-01

Experiments to demonstrate the use of the background-oriented schlieren (BOS) technique in hypersonic impulse facilities are reported. BOS uses a simple optical set-up consisting of a structured background pattern, an electronic camera with a high shutter speed and a high intensity light source. The visualization technique is demonstrated in a small reflected shock tunnel with a Mach 4 conical nozzle, nozzle supply pressure of 2.2 MPa and nozzle supply enthalpy of 1.8 MJ/kg. A 20° sharp circular cone and a model of the MUSES-C re-entry body were tested. Images captured were processed using PIV-style image analysis to visualize variations in the density field. The shock angle on the cone measured from the BOS images agreed with theoretical calculations to within 0.5°. Shock standoff distances could be measured from the BOS image for the re-entry body. Preliminary experiments are also reported in higher enthalpy facilities where flow luminosity can interfere with imaging of the background pattern.

Diffusion processes in tumors: A nuclear medicine approach

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

Amaya, Helman, E-mail: haamayae@unal.edu.co

The number of counts used in nuclear medicine imaging techniques, only provides physical information about the desintegration of the nucleus present in the the radiotracer molecules that were uptaken in a particular anatomical region, but that information is not a real metabolic information. For this reason a mathematical method was used to find a correlation between number of counts and {sup 18}F-FDG mass concentration. This correlation allows a better interpretation of the results obtained in the study of diffusive processes in an agar phantom, and based on it, an image from the PETCETIX DICOM sample image set from OsiriX-viewer softwaremore » was processed. PET-CT gradient magnitude and Laplacian images could show direct information on diffusive processes for radiopharmaceuticals that enter into the cells by simple diffusion. In the case of the radiopharmaceutical {sup 18}F-FDG is necessary to include pharmacokinetic models, to make a correct interpretation of the gradient magnitude and Laplacian of counts images.« less

A self-synchronized high speed computational ghost imaging system: A leap towards dynamic capturing

NASA Astrophysics Data System (ADS)

Suo, Jinli; Bian, Liheng; Xiao, Yudong; Wang, Yongjin; Zhang, Lei; Dai, Qionghai

2015-11-01

High quality computational ghost imaging needs to acquire a large number of correlated measurements between the to-be-imaged scene and different reference patterns, thus ultra-high speed data acquisition is of crucial importance in real applications. To raise the acquisition efficiency, this paper reports a high speed computational ghost imaging system using a 20 kHz spatial light modulator together with a 2 MHz photodiode. Technically, the synchronization between such high frequency illumination and bucket detector needs nanosecond trigger precision, so the development of synchronization module is quite challenging. To handle this problem, we propose a simple and effective computational self-synchronization scheme by building a general mathematical model and introducing a high precision synchronization technique. The resulted efficiency is around 14 times faster than state-of-the-arts, and takes an important step towards ghost imaging of dynamic scenes. Besides, the proposed scheme is a general approach with high flexibility for readily incorporating other illuminators and detectors.

Visualization of aging-associated chromatin alterations with an engineered TALE system

PubMed Central

Ren, Ruotong; Deng, Liping; Xue, Yanhong; Suzuki, Keiichiro; Zhang, Weiqi; Yu, Yang; Wu, Jun; Sun, Liang; Gong, Xiaojun; Luan, Huiqin; Yang, Fan; Ju, Zhenyu; Ren, Xiaoqing; Wang, Si; Tang, Hong; Geng, Lingling; Zhang, Weizhou; Li, Jian; Qiao, Jie; Xu, Tao; Qu, Jing; Liu, Guang-Hui

2017-01-01

Visualization of specific genomic loci in live cells is a prerequisite for the investigation of dynamic changes in chromatin architecture during diverse biological processes, such as cellular aging. However, current precision genomic imaging methods are hampered by the lack of fluorescent probes with high specificity and signal-to-noise contrast. We find that conventional transcription activator-like effectors (TALEs) tend to form protein aggregates, thereby compromising their performance in imaging applications. Through screening, we found that fusing thioredoxin with TALEs prevented aggregate formation, unlocking the full power of TALE-based genomic imaging. Using thioredoxin-fused TALEs (TTALEs), we achieved high-quality imaging at various genomic loci and observed aging-associated (epi) genomic alterations at telomeres and centromeres in human and mouse premature aging models. Importantly, we identified attrition of ribosomal DNA repeats as a molecular marker for human aging. Our study establishes a simple and robust imaging method for precisely monitoring chromatin dynamics in vitro and in vivo. PMID:28139645

Magnetic Doppler imaging of Ap stars

NASA Astrophysics Data System (ADS)

Silvester, J.; Wade, G. A.; Kochukhov, O.; Landstreet, J. D.; Bagnulo, S.

2008-04-01

Historically, the magnetic field geometries of the chemically peculiar Ap stars were modelled in the context of a simple dipole field. However, with the acquisition of increasingly sophisticated diagnostic data, it has become clear that the large-scale field topologies exhibit important departures from this simple model. Recently, new high-resolution circular and linear polarisation spectroscopy has even hinted at the presence of strong, small-scale field structures, which were completely unexpected based on earlier modelling. This project investigates the detailed structure of these strong fossil magnetic fields, in particular the large-scale field geometry, as well as small scale magnetic structures, by mapping the magnetic and chemical surface structure of a selected sample of Ap stars. These maps will be used to investigate the relationship between the local field vector and local surface chemistry, looking for the influence the field may have on the various chemical transport mechanisms (i.e., diffusion, convection and mass loss). This will lead to better constraints on the origin and evolution, as well as refining the magnetic field model for Ap stars. Mapping will be performed using high resolution and signal-to-noise ratio time-series of spectra in both circular and linear polarisation obtained using the new-generation ESPaDOnS (CFHT, Mauna Kea, Hawaii) and NARVAL spectropolarimeters (Pic du Midi Observatory). With these data we will perform tomographic inversion of Doppler-broadened Stokes IQUV Zeeman profiles of a large variety of spectral lines using the INVERS10 magnetic Doppler imaging code, simultaneously recovering the detailed surface maps of the vector magnetic field and chemical abundances.

A 4D global respiratory motion model of the thorax based on CT images: A proof of concept.

PubMed

Fayad, Hadi; Gilles, Marlene; Pan, Tinsu; Visvikis, Dimitris

2018-05-17

Respiratory motion reduces the sensitivity and specificity of medical images especially in the thoracic and abdominal areas. It may affect applications such as cancer diagnostic imaging and/or radiation therapy (RT). Solutions to this issue include modeling of the respiratory motion in order to optimize both diagnostic and therapeutic protocols. Personalized motion modeling required patient-specific four-dimensional (4D) imaging which in the case of 4D computed tomography (4D CT) acquisition is associated with an increased dose. The goal of this work was to develop a global respiratory motion model capable of relating external patient surface motion to internal structure motion without the need for a patient-specific 4D CT acquisition. The proposed global model is based on principal component analysis and can be adjusted to a given patient anatomy using only one or two static CT images in conjunction with a respiratory synchronized patient external surface motion. It is based on the relation between the internal motion described using deformation fields obtained by registering 4D CT images and patient surface maps obtained either from optical imaging devices or extracted from CT image-based patient skin segmentation. 4D CT images of six patients were used to generate the global motion model which was validated by adapting it on four different patients having skin segmented surfaces and two other patients having time of flight camera acquired surfaces. The reproducibility of the proposed model was also assessed on two patients with two 4D CT series acquired within 2 weeks of each other. Profile comparison shows the efficacy of the global respiratory motion model and an improvement while using two CT images in order to adapt the model. This was confirmed by the correlation coefficient with a mean correlation of 0.9 and 0.95 while using one or two CT images respectively and when comparing acquired to model generated 4D CT images. For the four patients with segmented surfaces, expert validation indicates an error of 2.35 ± 0.26 mm compared to 6.07 ± 0.76 mm when using a simple interpolation between full inspiration (FI) and full expiration (FE) CT only; i.e., without specific modeling of the respiratory motion. For the two patients with acquired surfaces, this error was of 2.48 ± 0.18 mm. In terms of reproducibility, model error changes of 0.12 and 0.17 mm were measured for the two patients concerned. The framework for the derivation of a global respiratory motion model was developed. A single or two static CT images and associated patient surface motion, as a surrogate measure, are only needed to personalize the model. This model accuracy and reproducibility were assessed by comparing acquired vs model generated 4D CT images. Future work will consist of assessing extensively the proposed model for radiotherapy applications. © 2018 American Association of Physicists in Medicine.

Macroscopic fluorescence imaging: a novel technique to monitor retention and distribution of injected microspheres in an experimental model of ischemic heart failure.

PubMed

Martens, Andreas; Rojas, Sebastian V; Baraki, Hassina; Rathert, Christian; Schecker, Natalie; Hernandez, Sara Rojas; Schwanke, Kristin; Zweigerdt, Robert; Martin, Ulrich; Saito, Shunsuke; Haverich, Axel; Kutschka, Ingo

2014-01-01

The limited effectiveness of cardiac cell therapy has generated concern regarding its clinical relevance. Experimental studies show that cell retention and engraftment are low after injection into ischemic myocardium, which may restrict therapy effectiveness significantly. Surgical aspects and mechanical loss are suspected to be the main culprits behind this phenomenon. As current techniques of monitoring intramyocardial injections are complex and time-consuming, the aim of the study was to develop a fast and simple model to study cardiac retention and distribution following intramyocardial injections. For this purpose, our main hypothesis was that macroscopic fluorescence imaging could adequately serve as a detection method for intramyocardial injections. A total of 20 mice underwent ligation of the left anterior descending artery (LAD) for myocardial infarction. Fluorescent microspheres with cellular dimensions were used as cell surrogates. Particles (5 × 10(5)) were injected into the infarcted area of explanted resting hearts (Ex vivo myocardial injetions EVMI, n = 10) and in vivo into beating hearts (In vivo myocardial injections IVMI, n = 10). Microsphere quantification was performed by fluorescence imaging of explanted organs. Measurements were repeated after a reduction to homogenate dilutions. Cardiac microsphere retention was 2.78 × 10(5) ± 0.31 × 10(5) in the EVMI group. In the IVMI group, cardiac retention of microspheres was significantly lower (0.74 × 10(5) ± 0.18 × 10(5); p<0.05). Direct fluorescence imaging revealed venous drainage through the coronary sinus, resulting in a microsphere accumulation in the left (0.90 × 10(5) ± 0.20 × 10(5)) and the right (1.07 × 10(5) ± 0.17 × 10(5)) lung. Processing to homogenates involved further particle loss (p<0.05) in both groups. We developed a fast and simple direct fluorescence imaging method for biodistribution analysis which enabled the quantification of fluorescent microspheres after intramyocardial delivery using macroscopic fluorescence imaging. This new technique showed massive early particle loss and venous drainage into the right atrium leading to substantial accumulation of graft particles in both lungs.

Equation of State of the Two-Dimensional Hubbard Model

NASA Astrophysics Data System (ADS)

Cocchi, Eugenio; Miller, Luke A.; Drewes, Jan H.; Koschorreck, Marco; Pertot, Daniel; Brennecke, Ferdinand; Köhl, Michael

2016-04-01

The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0 ≲U /t ≲20 and temperatures, down to kBT /t =0.63 (2 ) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches.

MCAT to XCAT: The Evolution of 4-D Computerized Phantoms for Imaging Research

PubMed Central

Paul Segars, W.; Tsui, Benjamin M. W.

2012-01-01

Recent work in the development of computerized phantoms has focused on the creation of ideal “hybrid” models that seek to combine the realism of a patient-based voxelized phantom with the flexibility of a mathematical or stylized phantom. We have been leading the development of such computerized phantoms for use in medical imaging research. This paper will summarize our developments dating from the original four-dimensional (4-D) Mathematical Cardiac-Torso (MCAT) phantom, a stylized model based on geometric primitives, to the current 4-D extended Cardiac-Torso (XCAT) and Mouse Whole-Body (MOBY) phantoms, hybrid models of the human and laboratory mouse based on state-of-the-art computer graphics techniques. This paper illustrates the evolution of computerized phantoms toward more accurate models of anatomy and physiology. This evolution was catalyzed through the introduction of nonuniform rational b-spline (NURBS) and subdivision (SD) surfaces, tools widely used in computer graphics, as modeling primitives to define a more ideal hybrid phantom. With NURBS and SD surfaces as a basis, we progressed from a simple geometrically based model of the male torso (MCAT) containing only a handful of structures to detailed, whole-body models of the male and female (XCAT) anatomies (at different ages from newborn to adult), each containing more than 9000 structures. The techniques we applied for modeling the human body were similarly used in the creation of the 4-D MOBY phantom, a whole-body model for the mouse designed for small animal imaging research. From our work, we have found the NURBS and SD surface modeling techniques to be an efficient and flexible way to describe the anatomy and physiology for realistic phantoms. Based on imaging data, the surfaces can accurately model the complex organs and structures in the body, providing a level of realism comparable to that of a voxelized phantom. In addition, they are very flexible. Like stylized models, they can easily be manipulated to model anatomical variations and patient motion. With the vast improvement in realism, the phantoms developed in our lab can be combined with accurate models of the imaging process (SPECT, PET, CT, magnetic resonance imaging, and ultrasound) to generate simulated imaging data close to that from actual human or animal subjects. As such, they can provide vital tools to generate predictive imaging data from many different subjects under various scanning parameters from which to quantitatively evaluate and improve imaging devices and techniques. From the MCAT to XCAT, we will demonstrate how NURBS and SD surface modeling have resulted in a major evolutionary advance in the development of computerized phantoms for imaging research. PMID:26472880

3D reconstruction of SEM images by use of optical photogrammetry software.

PubMed

Eulitz, Mona; Reiss, Gebhard

2015-08-01

Reconstruction of the three-dimensional (3D) surface of an object to be examined is widely used for structure analysis in science and many biological questions require information about their true 3D structure. For Scanning Electron Microscopy (SEM) there has been no efficient non-destructive solution for reconstruction of the surface morphology to date. The well-known method of recording stereo pair images generates a 3D stereoscope reconstruction of a section, but not of the complete sample surface. We present a simple and non-destructive method of 3D surface reconstruction from SEM samples based on the principles of optical close range photogrammetry. In optical close range photogrammetry a series of overlapping photos is used to generate a 3D model of the surface of an object. We adapted this method to the special SEM requirements. Instead of moving a detector around the object, the object itself was rotated. A series of overlapping photos was stitched and converted into a 3D model using the software commonly used for optical photogrammetry. A rabbit kidney glomerulus was used to demonstrate the workflow of this adaption. The reconstruction produced a realistic and high-resolution 3D mesh model of the glomerular surface. The study showed that SEM micrographs are suitable for 3D reconstruction by optical photogrammetry. This new approach is a simple and useful method of 3D surface reconstruction and suitable for various applications in research and teaching. Copyright © 2015 Elsevier Inc. All rights reserved.

Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems

NASA Astrophysics Data System (ADS)

Xu, Jingjiang; Song, Shaozhen; Li, Yuandong; Wang, Ruikang K.

2018-01-01

Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  <  ~40 mrad. We also conduct a series of in vivo vascular imaging in animal models and human retina to verify the findings from the MC model through assessing the OCTA performance metrics of vessel connectivity, image SNR and contrast-to-noise ratio. We show that for all the metrics assessed, the complex-based algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

Complex-based OCT angiography algorithm recovers microvascular information better than amplitude- or phase-based algorithms in phase-stable systems.

PubMed

Xu, Jingjiang; Song, Shaozhen; Li, Yuandong; Wang, Ruikang K

2017-12-19

Optical coherence tomography angiography (OCTA) is increasingly becoming a popular inspection tool for biomedical imaging applications. By exploring the amplitude, phase and complex information available in OCT signals, numerous algorithms have been proposed that contrast functional vessel networks within microcirculatory tissue beds. However, it is not clear which algorithm delivers optimal imaging performance. Here, we investigate systematically how amplitude and phase information have an impact on the OCTA imaging performance, to establish the relationship of amplitude and phase stability with OCT signal-to-noise ratio (SNR), time interval and particle dynamics. With either repeated A-scan or repeated B-scan imaging protocols, the amplitude noise increases with the increase of OCT SNR; however, the phase noise does the opposite, i.e. it increases with the decrease of OCT SNR. Coupled with experimental measurements, we utilize a simple Monte Carlo (MC) model to simulate the performance of amplitude-, phase- and complex-based algorithms for OCTA imaging, the results of which suggest that complex-based algorithms deliver the best performance when the phase noise is  <  ~40 mrad. We also conduct a series of in vivo vascular imaging in animal models and human retina to verify the findings from the MC model through assessing the OCTA performance metrics of vessel connectivity, image SNR and contrast-to-noise ratio. We show that for all the metrics assessed, the complex-based algorithm delivers better performance than either the amplitude- or phase-based algorithms for both the repeated A-scan and the B-scan imaging protocols, which agrees well with the conclusion drawn from the MC simulations.

An Automatic Procedure for Combining Digital Images and Laser Scanner Data

NASA Astrophysics Data System (ADS)

Moussa, W.; Abdel-Wahab, M.; Fritsch, D.

2012-07-01

Besides improving both the geometry and the visual quality of the model, the integration of close-range photogrammetry and terrestrial laser scanning techniques directs at filling gaps in laser scanner point clouds to avoid modeling errors, reconstructing more details in higher resolution and recovering simple structures with less geometric details. Thus, within this paper a flexible approach for the automatic combination of digital images and laser scanner data is presented. Our approach comprises two methods for data fusion. The first method starts by a marker-free registration of digital images based on a point-based environment model (PEM) of a scene which stores the 3D laser scanner point clouds associated with intensity and RGB values. The PEM allows the extraction of accurate control information for the direct computation of absolute camera orientations with redundant information by means of accurate space resection methods. In order to use the computed relations between the digital images and the laser scanner data, an extended Helmert (seven-parameter) transformation is introduced and its parameters are estimated. Precedent to that, in the second method, the local relative orientation parameters of the camera images are calculated by means of an optimized Structure and Motion (SaM) reconstruction method. Then, using the determined transformation parameters results in having absolute oriented images in relation to the laser scanner data. With the resulting absolute orientations we have employed robust dense image reconstruction algorithms to create oriented dense image point clouds, which are automatically combined with the laser scanner data to form a complete detailed representation of a scene. Examples of different data sets are shown and experimental results demonstrate the effectiveness of the presented procedures.

Real-space mapping of the strongly coupled plasmons of nanoparticle dimers.

PubMed

Kim, Deok-Soo; Heo, Jinhwa; Ahn, Sung-Hyun; Han, Sang Woo; Yun, Wan Soo; Kim, Zee Hwan

2009-10-01

We carried out the near-field optical imaging of isolated and dimerized gold nanocubes to directly investigate the strong coupling between two adjacent nanoparticles. The high-resolution (approximately 10 nm) local field maps (intensities and phases) of self-assembled nanocube dimers reveal antisymmetric plasmon modes that are starkly different from a simple superposition of two monomeric dipole plasmons, which is fully reproduced by the electrodynamics simulations. The result decisively proves that, for the closely spaced pair of nanoparticles (interparticle distance/particle size approximately 0.04), the strong Coulombic attraction between the charges at the interparticle gap dominates over the intraparticle charge oscillations, resulting in a hybridized dimer plasmon mode that is qualitatively different from those expected from a simple dipole-dipole coupling model.

The Wernicke area: Modern evidence and a reinterpretation.

PubMed

Binder, Jeffrey R

2015-12-15

The term "Wernicke's area" is most often used as an anatomical label for the gyri forming the lower posterior left sylvian fissure. Although traditionally this region was held to support language comprehension, modern imaging and neuropsychological studies converge on the conclusion that this region plays a much larger role in speech production. This evidence is briefly reviewed, and a simple schematic model of posterior cortical language processing is described. © 2015 American Academy of Neurology.

Experiments on automatic classification of tissue malignancy in the field of digital pathology

NASA Astrophysics Data System (ADS)

Pereira, J.; Barata, R.; Furtado, Pedro

2017-06-01

Automated analysis of histological images helps diagnose and further classify breast cancer. Totally automated approaches can be used to pinpoint images for further analysis by the medical doctor. But tissue images are especially challenging for either manual or automated approaches, due to mixed patterns and textures, where malignant regions are sometimes difficult to detect unless they are in very advanced stages. Some of the major challenges are related to irregular and very diffuse patterns, as well as difficulty to define winning features and classifier models. Although it is also hard to segment correctly into regions, due to the diffuse nature, it is still crucial to take low-level features over individualized regions instead of the whole image, and to select those with the best outcomes. In this paper we report on our experiments building a region classifier with a simple subspace division and a feature selection model that improves results over image-wide and/or limited feature sets. Experimental results show modest accuracy for a set of classifiers applied over the whole image, while the conjunction of image division, per-region low-level extraction of features and selection of features, together with the use of a neural network classifier achieved the best levels of accuracy for the dataset and settings we used in the experiments. Future work involves deep learning techniques, adding structures semantics and embedding the approach as a tumor finding helper in a practical Medical Imaging Application.

The role of extra-foveal processing in 3D imaging

NASA Astrophysics Data System (ADS)

Eckstein, Miguel P.; Lago, Miguel A.; Abbey, Craig K.

2017-03-01

The field of medical image quality has relied on the assumption that metrics of image quality for simple visual detection tasks are a reliable proxy for the more clinically realistic visual search tasks. Rank order of signal detectability across conditions often generalizes from detection to search tasks. Here, we argue that search in 3D images represents a paradigm shift in medical imaging: radiologists typically cannot exhaustively scrutinize all regions of interest with the high acuity fovea requiring detection of signals with extra-foveal areas (visual periphery) of the human retina. We hypothesize that extra-foveal processing can alter the detectability of certain types of signals in medical images with important implications for search in 3D medical images. We compare visual search of two different types of signals in 2D vs. 3D images. We show that a small microcalcification-like signal is more highly detectable than a larger mass-like signal in 2D search, but its detectability largely decreases (relative to the larger signal) in the 3D search task. Utilizing measurements of observer detectability as a function retinal eccentricity and observer eye fixations we can predict the pattern of results in the 2D and 3D search studies. Our findings: 1) suggest that observer performance findings with 2D search might not always generalize to 3D search; 2) motivate the development of a new family of model observers that take into account the inhomogeneous visual processing across the retina (foveated model observers).

Instrument performance enhancement and modification through an extended instrument paradigm

NASA Astrophysics Data System (ADS)

Mahan, Stephen Lee

An extended instrument paradigm is proposed, developed and shown in various applications. The CBM (Chin, Blass, Mahan) method is an extension to the linear systems model of observing systems. In the most obvious and practical application of image enhancement of an instrument characterized by a time-invariant instrumental response function, CBM can be used to enhance images or spectra through a simple convolution application of the CBM filter for a resolution improvement of as much as a factor of two. The CBM method can be used in many applications. We discuss several within this work including imaging through turbulent atmospheres, or what we've called Adaptive Imaging. Adaptive Imaging provides an alternative approach for the investigator desiring results similar to those obtainable with adaptive optics, however on a minimal budget. The CBM method is also used in a backprojected filtered image reconstruction method for Positron Emission Tomography. In addition, we can use information theoretic methods to aid in the determination of model instrumental response function parameters for images having an unknown origin. Another application presented herein involves the use of the CBM method for the determination of the continuum level of a Fourier transform spectrometer observation of ethylene, which provides a means for obtaining reliable intensity measurements in an automated manner. We also present the application of CBM to hyperspectral image data of the comet Shoemaker-Levy 9 impact with Jupiter taken with an acousto-optical tunable filter equipped CCD camera to an adaptive optics telescope.

Decoding natural images from evoked brain activities using encoding models with invertible mapping.

PubMed

Li, Chao; Xu, Junhai; Liu, Baolin

2018-05-21

Recent studies have built encoding models in the early visual cortex, and reliable mappings have been made between the low-level visual features of stimuli and brain activities. However, these mappings are irreversible, so that the features cannot be directly decoded. To solve this problem, we designed a sparse framework-based encoding model that predicted brain activities from a complete feature representation. Moreover, according to the distribution and activation rules of neurons in the primary visual cortex (V1), three key transformations were introduced into the basic feature to improve the model performance. In this setting, the mapping was simple enough that it could be inverted using a closed-form formula. Using this mapping, we designed a hybrid identification method based on the support vector machine (SVM), and tested it on a published functional magnetic resonance imaging (fMRI) dataset. The experiments confirmed the rationality of our encoding model, and the identification accuracies for 2 subjects increased from 92% and 72% to 98% and 92% with the chance level only 0.8%. Copyright © 2018 Elsevier Ltd. All rights reserved.

Improving Consensus Scoring of Crowdsourced Data Using the Rasch Model: Development and Refinement of a Diagnostic Instrument.

PubMed

Brady, Christopher John; Mudie, Lucy Iluka; Wang, Xueyang; Guallar, Eliseo; Friedman, David Steven

2017-06-20

Diabetic retinopathy (DR) is a leading cause of vision loss in working age individuals worldwide. While screening is effective and cost effective, it remains underutilized, and novel methods are needed to increase detection of DR. This clinical validation study compared diagnostic gradings of retinal fundus photographs provided by volunteers on the Amazon Mechanical Turk (AMT) crowdsourcing marketplace with expert-provided gold-standard grading and explored whether determination of the consensus of crowdsourced classifications could be improved beyond a simple majority vote (MV) using regression methods. The aim of our study was to determine whether regression methods could be used to improve the consensus grading of data collected by crowdsourcing. A total of 1200 retinal images of individuals with diabetes mellitus from the Messidor public dataset were posted to AMT. Eligible crowdsourcing workers had at least 500 previously approved tasks with an approval rating of 99% across their prior submitted work. A total of 10 workers were recruited to classify each image as normal or abnormal. If half or more workers judged the image to be abnormal, the MV consensus grade was recorded as abnormal. Rasch analysis was then used to calculate worker ability scores in a random 50% training set, which were then used as weights in a regression model in the remaining 50% test set to determine if a more accurate consensus could be devised. Outcomes of interest were the percent correctly classified images, sensitivity, specificity, and area under the receiver operating characteristic (AUROC) for the consensus grade as compared with the expert grading provided with the dataset. Using MV grading, the consensus was correct in 75.5% of images (906/1200), with 75.5% sensitivity, 75.5% specificity, and an AUROC of 0.75 (95% CI 0.73-0.78). A logistic regression model using Rasch-weighted individual scores generated an AUROC of 0.91 (95% CI 0.88-0.93) compared with 0.89 (95% CI 0.86-92) for a model using unweighted scores (chi-square P value<.001). Setting a diagnostic cut-point to optimize sensitivity at 90%, 77.5% (465/600) were graded correctly, with 90.3% sensitivity, 68.5% specificity, and an AUROC of 0.79 (95% CI 0.76-0.83). Crowdsourced interpretations of retinal images provide rapid and accurate results as compared with a gold-standard grading. Creating a logistic regression model using Rasch analysis to weight crowdsourced classifications by worker ability improves accuracy of aggregated grades as compared with simple majority vote. ©Christopher John Brady, Lucy Iluka Mudie, Xueyang Wang, Eliseo Guallar, David Steven Friedman. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.06.2017.

Green light may improve diagnostic accuracy of nailfold capillaroscopy with a simple digital videomicroscope.

PubMed

Weekenstroo, Harm H A; Cornelissen, Bart M W; Bernelot Moens, Hein J

2015-06-01

Nailfold capillaroscopy is a non-invasive and safe technique for the analysis of microangiopathologies. Imaging quality of widely used simple videomicroscopes is poor. The use of green illumination instead of the commonly used white light may improve contrast. The aim of the study was to compare the effect of green illumination with white illumination, regarding capillary density, the number of microangiopathologies, and sensitivity and specificity for systemic sclerosis. Five rheumatologists have evaluated 80 images; 40 images acquired with green light, and 40 images acquired with white light. A larger number of microangiopathologies were found in images acquired with green light than in images acquired with white light. This results in slightly higher sensitivity with green light in comparison with white light, without reducing the specificity. These findings suggest that green instead of white illumination may facilitate evaluation of capillaroscopic images obtained with a low-cost digital videomicroscope.

Toward Model Building for Visual Aesthetic Perception

PubMed Central

Lughofer, Edwin; Zeng, Xianyi

2017-01-01

Several models of visual aesthetic perception have been proposed in recent years. Such models have drawn on investigations into the neural underpinnings of visual aesthetics, utilizing neurophysiological techniques and brain imaging techniques including functional magnetic resonance imaging, magnetoencephalography, and electroencephalography. The neural mechanisms underlying the aesthetic perception of the visual arts have been explained from the perspectives of neuropsychology, brain and cognitive science, informatics, and statistics. Although corresponding models have been constructed, the majority of these models contain elements that are difficult to be simulated or quantified using simple mathematical functions. In this review, we discuss the hypotheses, conceptions, and structures of six typical models for human aesthetic appreciation in the visual domain: the neuropsychological, information processing, mirror, quartet, and two hierarchical feed-forward layered models. Additionally, the neural foundation of aesthetic perception, appreciation, or judgement for each model is summarized. The development of a unified framework for the neurobiological mechanisms underlying the aesthetic perception of visual art and the validation of this framework via mathematical simulation is an interesting challenge in neuroaesthetics research. This review aims to provide information regarding the most promising proposals for bridging the gap between visual information processing and brain activity involved in aesthetic appreciation. PMID:29270194

Image-Based Airborne Sensors: A Combined Approach for Spectral Signatures Classification through Deterministic Simulated Annealing

PubMed Central

Guijarro, María; Pajares, Gonzalo; Herrera, P. Javier

2009-01-01

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented towards the combination of simple classifiers. In this paper we propose a combined strategy based on the Deterministic Simulated Annealing (DSA) framework. The simple classifiers used are the well tested supervised parametric Bayesian estimator and the Fuzzy Clustering. The DSA is an optimization approach, which minimizes an energy function. The main contribution of DSA is its ability to avoid local minima during the optimization process thanks to the annealing scheme. It outperforms simple classifiers used for the combination and some combined strategies, including a scheme based on the fuzzy cognitive maps and an optimization approach based on the Hopfield neural network paradigm. PMID:22399989

Single-particle cryo-EM-Improved ab initio 3D reconstruction with SIMPLE/PRIME.

PubMed

Reboul, Cyril F; Eager, Michael; Elmlund, Dominika; Elmlund, Hans

2018-01-01

Cryogenic electron microscopy (cryo-EM) and single-particle analysis now enables the determination of high-resolution structures of macromolecular assemblies that have resisted X-ray crystallography and other approaches. We developed the SIMPLE open-source image-processing suite for analysing cryo-EM images of single-particles. A core component of SIMPLE is the probabilistic PRIME algorithm for identifying clusters of images in 2D and determine relative orientations of single-particle projections in 3D. Here, we extend our previous work on PRIME and introduce new stochastic optimization algorithms that improve the robustness of the approach. Our refined method for identification of homogeneous subsets of images in accurate register substantially improves the resolution of the cluster centers and of the ab initio 3D reconstructions derived from them. We now obtain maps with a resolution better than 10 Å by exclusively processing cluster centers. Excellent parallel code performance on over-the-counter laptops and CPU workstations is demonstrated. © 2017 The Protein Society.

Detection of fastener loosening in simple lap joint based on ultrasonic wavefield imaging

NASA Astrophysics Data System (ADS)

Gooda Sahib, M. I.; Leong, S. J.; Chia, C. C.; Mustapha, F.

2017-12-01

Joints in aero-mechanical structures are critical elements that ensure the structural integrity but they are prone to damages. Inspection of such joints that have no prior baseline data is really challenging but it can be possibly done using the Ultrasonic Propagation Imager (UPI). The feasibility of applying UPI for detection of loosened fastener is investigated in this study. A simple lap joint specimen made by connecting two pieces of 2.5mm thick SAE304 stainless steel plates using five M6 screws and nuts has been used in this study. All fasteners are tightened to 10Nm but one of them is completely loosened to simulate the damage. The wavefield data is processed into ultrasonic wavefield propagation video and a series of spectral amplitude images. The spectral images showed noticeable amplitude difference at the loosened fastener, hence confirmed the feasibility of using UPI for structural joints inspection. A simple contrast maximization method is also introduced to improve the result.

Imaging with hypertelescopes: a simple modal approach

NASA Astrophysics Data System (ADS)

Aime, C.

2008-05-01

Aims: We give a simple analysis of imaging with hypertelescopes, a technique proposed by Labeyrie to produce snapshot images using arrays of telescopes. The approach is modal: we describe the transformations induced by the densification onto a sinusoidal decomposition of the focal image instead of the usual point spread function approach. Methods: We first express the image formed at the focus of a diluted array of apertures as the product R_0(α) X_F(α) of the diffraction pattern of the elementary apertures R_0(α) by the object-dependent interference term X_F(α) between all apertures. The interference term, which can be written in the form of a Fourier Series for an extremely diluted array, produces replications of the object, which makes observing the image difficult. We express the focal image after the densification using the approach of Tallon and Tallon-Bosc. Results: The result is very simple for an extremely diluted array. We show that the focal image in a periscopic densification of the array can be written as R_0(α) X_F(α/γ), where γ is the factor of densification. There is a dilatation of the interference term while the diffraction term is unchanged. After de-zooming, the image can be written as γ2 X_F(α)R_0(γ α), an expression which clearly indicates that the final image corresponds to the center of the Fizeau image intensified by γ2. The imaging limitations of hypertelescopes are therefore those of the original configuration. The effect of the suppression of image replications is illustrated in a numerical simulation for a fully redundant configuration and a non-redundant one.

[Digital processing and evaluation of ultrasound images].

PubMed

Borchers, J; Klews, P M

1993-10-01

With the help of workstations and PCs, on-site image processing has become possible. If the images are not available in digital form the video signal has to be A/D converted. In the case of colour images the colour channels R (red), G (green) and B (blue) have to be digitized separately. "Truecolour" imaging calls for an 8 bit resolution per channel, leading to 24 bits per pixel. Out of a pool of 2(24) possible values only the relevant 128 gray values and 64 shades of red and blue respectively needed for a colour-coded ultrasound image have to be isolated. Digital images can be changed and evaluated with the help of readily available image evaluation programmes. It is mandatory that during image manipulation the gray scale and colour pixels and LUTs (Look-Up-Table) must be worked on separately. Using relatively simple LUT manipulations astonishing image improvements are possible. Application of simple mathematical operations can lead to completely new clinical results. For example, by subtracting two consecutive colour flow images in time and special LUT operations, local acceleration of blood flow can be visualized (Colour Acceleration Imaging).

SVGenes: a library for rendering genomic features in scalable vector graphic format.

PubMed

Etherington, Graham J; MacLean, Daniel

2013-08-01

Drawing genomic features in attractive and informative ways is a key task in visualization of genomics data. Scalable Vector Graphics (SVG) format is a modern and flexible open standard that provides advanced features including modular graphic design, advanced web interactivity and animation within a suitable client. SVGs do not suffer from loss of image quality on re-scaling and provide the ability to edit individual elements of a graphic on the whole object level independent of the whole image. These features make SVG a potentially useful format for the preparation of publication quality figures including genomic objects such as genes or sequencing coverage and for web applications that require rich user-interaction with the graphical elements. SVGenes is a Ruby-language library that uses SVG primitives to render typical genomic glyphs through a simple and flexible Ruby interface. The library implements a simple Page object that spaces and contains horizontal Track objects that in turn style, colour and positions features within them. Tracks are the level at which visual information is supplied providing the full styling capability of the SVG standard. Genomic entities like genes, transcripts and histograms are modelled in Glyph objects that are attached to a track and take advantage of SVG primitives to render the genomic features in a track as any of a selection of defined glyphs. The feature model within SVGenes is simple but flexible and not dependent on particular existing gene feature formats meaning graphics for any existing datasets can easily be created without need for conversion. The library is provided as a Ruby Gem from https://rubygems.org/gems/bio-svgenes under the MIT license, and open source code is available at https://github.com/danmaclean/bioruby-svgenes also under the MIT License. dan.maclean@tsl.ac.uk.

Image-Based Models for Specularity Propagation in Diminished Reality.

PubMed

Said, Souheil Hadj; Tamaazousti, Mohamed; Bartoli, Adrien

2018-07-01

The aim of Diminished Reality (DR) is to remove a target object in a live video stream seamlessly. In our approach, the area of the target object is replaced with new texture that blends with the rest of the image. The result is then propagated to the next frames of the video. One of the important stages of this technique is to update the target region with respect to the illumination change. This is a complex and recurrent problem when the viewpoint changes. We show that the state-of-the-art in DR fails in solving this problem, even under simple scenarios. We then use local illumination models to address this problem. According to these models, the variation in illumination only affects the specular component of the image. In the context of DR, the problem is therefore solved by propagating the specularities in the target area. We list a set of structural properties of specularities which we incorporate in two new models for specularity propagation. Our first model includes the same property as the previous approaches, which is the smoothness of illumination variation, but has a different estimation method based on the Thin-Plate Spline. Our second model incorporates more properties of the specularity's shape on planar surfaces. Experimental results on synthetic and real data show that our strategy substantially improves the rendering quality compared to the state-of-the-art in DR.

Theory of reflectivity blurring in seismic depth imaging

NASA Astrophysics Data System (ADS)

Thomson, C. J.; Kitchenside, P. W.; Fletcher, R. P.

2016-05-01

A subsurface extended image gather obtained during controlled-source depth imaging yields a blurred kernel of an interface reflection operator. This reflectivity kernel or reflection function is comprised of the interface plane-wave reflection coefficients and so, in principle, the gather contains amplitude versus offset or angle information. We present a modelling theory for extended image gathers that accounts for variable illumination and blurring, under the assumption of a good migration-velocity model. The method involves forward modelling as well as migration or back propagation so as to define a receiver-side blurring function, which contains the effects of the detector array for a given shot. Composition with the modelled incident wave and summation over shots then yields an overall blurring function that relates the reflectivity to the extended image gather obtained from field data. The spatial evolution or instability of blurring functions is a key concept and there is generally not just spatial blurring in the apparent reflectivity, but also slowness or angle blurring. Gridded blurring functions can be estimated with, for example, a reverse-time migration modelling engine. A calibration step is required to account for ad hoc band limitedness in the modelling and the method also exploits blurring-function reciprocity. To demonstrate the concepts, we show numerical examples of various quantities using the well-known SIGSBEE test model and a simple salt-body overburden model, both for 2-D. The moderately strong slowness/angle blurring in the latter model suggests that the effect on amplitude versus offset or angle analysis should be considered in more realistic structures. Although the description and examples are for 2-D, the extension to 3-D is conceptually straightforward. The computational cost of overall blurring functions implies their targeted use for the foreseeable future, for example, in reservoir characterization. The description is for scalar waves, but the extension to elasticity is foreseeable and we emphasize the separation of the overburden and survey-geometry blurring effects from the nature of the target scatterer.

Spatiotemporal models for the simulation of infrared backgrounds

NASA Astrophysics Data System (ADS)

Wilkes, Don M.; Cadzow, James A.; Peters, R. Alan, II; Li, Xingkang

1992-09-01

It is highly desirable for designers of automatic target recognizers (ATRs) to be able to test their algorithms on targets superimposed on a wide variety of background imagery. Background imagery in the infrared spectrum is expensive to gather from real sources, consequently, there is a need for accurate models for producing synthetic IR background imagery. We have developed a model for such imagery that will do the following: Given a real, infrared background image, generate another image, distinctly different from the one given, that has the same general visual characteristics as well as the first and second-order statistics of the original image. The proposed model consists of a finite impulse response (FIR) kernel convolved with an excitation function, and histogram modification applied to the final solution. A procedure for deriving the FIR kernel using a signal enhancement algorithm has been developed, and the histogram modification step is a simple memoryless nonlinear mapping that imposes the first order statistics of the original image onto the synthetic one, thus the overall model is a linear system cascaded with a memoryless nonlinearity. It has been found that the excitation function relates to the placement of features in the image, the FIR kernel controls the sharpness of the edges and the global spectrum of the image, and the histogram controls the basic coloration of the image. A drawback to this method of simulating IR backgrounds is that a database of actual background images must be collected in order to produce accurate FIR and histogram models. If this database must include images of all types of backgrounds obtained at all times of the day and all times of the year, the size of the database would be prohibitive. In this paper we propose improvements to the model described above that enable time-dependent modeling of the IR background. This approach can greatly reduce the number of actual IR backgrounds that are required to produce a sufficiently accurate mathematical model for synthesizing a similar IR background for different times of the day. Original and synthetic IR backgrounds will be presented. Previous research in simulating IR backgrounds was performed by Strenzwilk, et al., Botkin, et al., and Rapp. The most recent work of Strenzwilk, et al. was based on the use of one-dimensional ARMA models for synthesizing the images. Their results were able to retain the global statistical and spectral behavior of the original image, but the synthetic image was not visually very similar to the original. The research presented in this paper is the result of an attempt to improve upon their results, and represents a significant improvement in quality over previously obtained results.

Enhanced resolution imaging of ultrathin ZnO layers on Ag(111) by multiple hydrogen molecules in a scanning tunneling microscope junction

NASA Astrophysics Data System (ADS)

Liu, Shuyi; Shiotari, Akitoshi; Baugh, Delroy; Wolf, Martin; Kumagai, Takashi

2018-05-01

Molecular hydrogen in a scanning tunneling microscope (STM) junction has been found to enhance the lateral spatial resolution of the STM imaging, referred to as scanning tunneling hydrogen microscopy (STHM). Here we report atomic resolution imaging of 2- and 3-monolayer (ML) thick ZnO layers epitaxially grown on Ag(111) using STHM. The enhanced resolution can be obtained at a relatively large tip to surface distance and resolves a more defective structure exhibiting dislocation defects for 3-ML-thick ZnO than for 2 ML. In order to elucidate the enhanced imaging mechanism, the electric and mechanical properties of the hydrogen molecular junction (HMJ) are investigated by a combination of STM and atomic force microscopy. It is found that the HMJ shows multiple kinklike features in the tip to surface distance dependence of the conductance and frequency shift curves, which are absent in a hydrogen-free junction. Based on a simple modeling, we propose that the junction contains several hydrogen molecules and sequential squeezing of the molecules out of the junction results in the kinklike features in the conductance and frequency shift curves. The model also qualitatively reproduces the enhanced resolution image of the ZnO films.

Automatic optimal filament segmentation with sub-pixel accuracy using generalized linear models and B-spline level-sets.

PubMed

Xiao, Xun; Geyer, Veikko F; Bowne-Anderson, Hugo; Howard, Jonathon; Sbalzarini, Ivo F

2016-08-01

Biological filaments, such as actin filaments, microtubules, and cilia, are often imaged using different light-microscopy techniques. Reconstructing the filament curve from the acquired images constitutes the filament segmentation problem. Since filaments have lower dimensionality than the image itself, there is an inherent trade-off between tracing the filament with sub-pixel accuracy and avoiding noise artifacts. Here, we present a globally optimal filament segmentation method based on B-spline vector level-sets and a generalized linear model for the pixel intensity statistics. We show that the resulting optimization problem is convex and can hence be solved with global optimality. We introduce a simple and efficient algorithm to compute such optimal filament segmentations, and provide an open-source implementation as an ImageJ/Fiji plugin. We further derive an information-theoretic lower bound on the filament segmentation error, quantifying how well an algorithm could possibly do given the information in the image. We show that our algorithm asymptotically reaches this bound in the spline coefficients. We validate our method in comprehensive benchmarks, compare with other methods, and show applications from fluorescence, phase-contrast, and dark-field microscopy. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Beyond the Sparsity-Based Target Detector: A Hybrid Sparsity and Statistics Based Detector for Hyperspectral Images.

PubMed

Du, Bo; Zhang, Yuxiang; Zhang, Liangpei; Tao, Dacheng

2016-08-18

Hyperspectral images provide great potential for target detection, however, new challenges are also introduced for hyperspectral target detection, resulting that hyperspectral target detection should be treated as a new problem and modeled differently. Many classical detectors are proposed based on the linear mixing model and the sparsity model. However, the former type of model cannot deal well with spectral variability in limited endmembers, and the latter type of model usually treats the target detection as a simple classification problem and pays less attention to the low target probability. In this case, can we find an efficient way to utilize both the high-dimension features behind hyperspectral images and the limited target information to extract small targets? This paper proposes a novel sparsitybased detector named the hybrid sparsity and statistics detector (HSSD) for target detection in hyperspectral imagery, which can effectively deal with the above two problems. The proposed algorithm designs a hypothesis-specific dictionary based on the prior hypotheses for the test pixel, which can avoid the imbalanced number of training samples for a class-specific dictionary. Then, a purification process is employed for the background training samples in order to construct an effective competition between the two hypotheses. Next, a sparse representation based binary hypothesis model merged with additive Gaussian noise is proposed to represent the image. Finally, a generalized likelihood ratio test is performed to obtain a more robust detection decision than the reconstruction residual based detection methods. Extensive experimental results with three hyperspectral datasets confirm that the proposed HSSD algorithm clearly outperforms the stateof- the-art target detectors.

High-fidelity meshes from tissue samples for diffusion MRI simulations.

PubMed

Panagiotaki, Eleftheria; Hall, Matt G; Zhang, Hui; Siow, Bernard; Lythgoe, Mark F; Alexander, Daniel C

2010-01-01

This paper presents a method for constructing detailed geometric models of tissue microstructure for synthesizing realistic diffusion MRI data. We construct three-dimensional mesh models from confocal microscopy image stacks using the marching cubes algorithm. Random-walk simulations within the resulting meshes provide synthetic diffusion MRI measurements. Experiments optimise simulation parameters and complexity of the meshes to achieve accuracy and reproducibility while minimizing computation time. Finally we assess the quality of the synthesized data from the mesh models by comparison with scanner data as well as synthetic data from simple geometric models and simplified meshes that vary only in two dimensions. The results support the extra complexity of the three-dimensional mesh compared to simpler models although sensitivity to the mesh resolution is quite robust.

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

Rodigas, Timothy J.; Hinz, Philip M.; Malhotra, Renu, E-mail: rodigas@as.arizona.edu

Planets can affect debris disk structure by creating gaps, sharp edges, warps, and other potentially observable signatures. However, there is currently no simple way for observers to deduce a disk-shepherding planet's properties from the observed features of the disk. Here we present a single equation that relates a shepherding planet's maximum mass to the debris ring's observed width in scattered light, along with a procedure to estimate the planet's eccentricity and minimum semimajor axis. We accomplish this by performing dynamical N-body simulations of model systems containing a star, a single planet, and an exterior disk of parent bodies and dustmore » grains to determine the resulting debris disk properties over a wide range of input parameters. We find that the relationship between planet mass and debris disk width is linear, with increasing planet mass producing broader debris rings. We apply our methods to five imaged debris rings to constrain the putative planet masses and orbits in each system. Observers can use our empirically derived equation as a guide for future direct imaging searches for planets in debris disk systems. In the fortuitous case of an imaged planet orbiting interior to an imaged disk, the planet's maximum mass can be estimated independent of atmospheric models.« less

Psychophysical experiments on the PicHunter image retrieval system

NASA Astrophysics Data System (ADS)

Papathomas, Thomas V.; Cox, Ingemar J.; Yianilos, Peter N.; Miller, Matt L.; Minka, Thomas P.; Conway, Tiffany E.; Ghosn, Joumana

2001-01-01

Psychophysical experiments were conducted on PicHunter, a content-based image retrieval (CBIR) experimental prototype with the following properties: (1) Based on a model of how users respond, it uses Bayes's rule to predict what target users want, given their actions. (2) It possesses an extremely simple user interface. (3) It employs an entropy- based scheme to improve convergence. (4) It introduces a paradigm for assessing the performance of CBIR systems. Experiments 1-3 studied human judgment of image similarity to obtain data for the model. Experiment 4 studied the importance of using: (a) semantic information, (b) memory of earlier input, and (c) relative and absolute judgments of similarity. Experiment 5 tested an approach that we propose for comparing performances of CBIR systems objectively. Finally, experiment 6 evaluated the most informative display-updating scheme that is based on entropy minimization, and confirmed earlier simulation results. These experiments represent one of the first attempts to quantify CBIR performance based on psychophysical studies, and they provide valuable data for improving CBIR algorithms. Even though they were designed with PicHunter in mind, their results can be applied to any CBIR system and, more generally, to any system that involves judgment of image similarity by humans.

Natural image statistics mediate brightness 'filling in'.

PubMed

Dakin, Steven C; Bex, Peter J

2003-11-22

Although the human visual system can accurately estimate the reflectance (or lightness) of surfaces under enormous variations in illumination, two equiluminant grey regions can be induced to appear quite different simply by placing a light-dark luminance transition between them. This illusion, the Craik-Cornsweet-O'Brien (CCOB) effect, has been taken as evidence for a low-level 'filling-in' mechanism subserving lightness perception. Here, we present evidence that the mechanism responsible for the CCOB effect operates not via propagation of a neural signal across space but by amplification of the low spatial frequency (SF) structure of the image. We develop a simple computational model that relies on the statistics of natural scenes actively to reconstruct the image that is most likely to have caused an observed series of responses across SF channels. This principle is tested psychophysically by deriving classification images (CIs) for subjects' discrimination of the contrast polarity of CCOB stimuli masked with noise. CIs resemble 'filled-in' stimuli; i.e. observers rely on portions of the stimuli that contain no information per se but that correspond closely to the reported perceptual completion. As predicted by the model, the filling-in process is contingent on the presence of appropriate low SF structure.

Development of an EMC3-EIRENE Synthetic Imaging Diagnostic

NASA Astrophysics Data System (ADS)

Meyer, William; Allen, Steve; Samuell, Cameron; Lore, Jeremy

2017-10-01

2D and 3D flow measurements are critical for validating numerical codes such as EMC3-EIRENE. Toroidal symmetry assumptions preclude tomographic reconstruction of 3D flows from single camera views. In addition, the resolution of the grids utilized in numerical code models can easily surpass the resolution of physical camera diagnostic geometries. For these reasons we have developed a Synthetic Imaging Diagnostic capability for forward projection comparisons of EMC3-EIRENE model solutions with the line integrated images from the Doppler Coherence Imaging diagnostic on DIII-D. The forward projection matrix is 2.8 Mpixel by 6.4 Mcells for the non-axisymmetric case we present. For flow comparisons, both simple line integral, and field aligned component matrices must be calculated. The calculation of these matrices is a massive embarrassingly parallel problem and performed with a custom dispatcher that allows processing platforms to join mid-problem as they become available, or drop out if resources are needed for higher priority tasks. The matrices are handled using standard sparse matrix techniques. Prepared by LLNL under Contract DE-AC52-07NA27344. This material is based upon work supported by the U.S. DOE, Office of Science, Office of Fusion Energy Sciences. LLNL-ABS-734800.

High-speed 3D imaging of cellular activity in the brain using axially-extended beams and light sheets.

PubMed

Hillman, Elizabeth Mc; Voleti, Venkatakaushik; Patel, Kripa; Li, Wenze; Yu, Hang; Perez-Campos, Citlali; Benezra, Sam E; Bruno, Randy M; Galwaduge, Pubudu T

2018-06-01

As optical reporters and modulators of cellular activity have become increasingly sophisticated, the amount that can be learned about the brain via high-speed cellular imaging has increased dramatically. However, despite fervent innovation, point-scanning microscopy is facing a fundamental limit in achievable 3D imaging speeds and fields of view. A range of alternative approaches are emerging, some of which are moving away from point-scanning to use axially-extended beams or sheets of light, for example swept confocally aligned planar excitation (SCAPE) microscopy. These methods are proving effective for high-speed volumetric imaging of the nervous system of small organisms such as Drosophila (fruit fly) and D. Rerio (Zebrafish), and are showing promise for imaging activity in the living mammalian brain using both single and two-photon excitation. This article describes these approaches and presents a simple model that demonstrates key advantages of axially-extended illumination over point-scanning strategies for high-speed volumetric imaging, including longer integration times per voxel, improved photon efficiency and reduced photodamage. Copyright © 2018 Elsevier Ltd. All rights reserved.

Linear prediction data extrapolation superresolution radar imaging

NASA Astrophysics Data System (ADS)

Zhu, Zhaoda; Ye, Zhenru; Wu, Xiaoqing

1993-05-01

Range resolution and cross-range resolution of range-doppler imaging radars are related to the effective bandwidth of transmitted signal and the angle through which the object rotates relatively to the radar line of sight (RLOS) during the coherent processing time, respectively. In this paper, linear prediction data extrapolation discrete Fourier transform (LPDEDFT) superresolution imaging method is investigated for the purpose of surpassing the limitation imposed by the conventional FFT range-doppler processing and improving the resolution capability of range-doppler imaging radar. The LPDEDFT superresolution imaging method, which is conceptually simple, consists of extrapolating observed data beyond the observation windows by means of linear prediction, and then performing the conventional IDFT of the extrapolated data. The live data of a metalized scale model B-52 aircraft mounted on a rotating platform in a microwave anechoic chamber and a flying Boeing-727 aircraft were processed. It is concluded that, compared to the conventional Fourier method, either higher resolution for the same effective bandwidth of transmitted signals and total rotation angle of the object or equal-quality images from smaller bandwidth and total angle may be obtained by LPDEDFT.

An insect-inspired model for visual binding II: functional analysis and visual attention.

PubMed

Northcutt, Brandon D; Higgins, Charles M

2017-04-01

We have developed a neural network model capable of performing visual binding inspired by neuronal circuitry in the optic glomeruli of flies: a brain area that lies just downstream of the optic lobes where early visual processing is performed. This visual binding model is able to detect objects in dynamic image sequences and bind together their respective characteristic visual features-such as color, motion, and orientation-by taking advantage of their common temporal fluctuations. Visual binding is represented in the form of an inhibitory weight matrix which learns over time which features originate from a given visual object. In the present work, we show that information represented implicitly in this weight matrix can be used to explicitly count the number of objects present in the visual image, to enumerate their specific visual characteristics, and even to create an enhanced image in which one particular object is emphasized over others, thus implementing a simple form of visual attention. Further, we present a detailed analysis which reveals the function and theoretical limitations of the visual binding network and in this context describe a novel network learning rule which is optimized for visual binding.

"Tools For Analysis and Visualization of Large Time- Varying CFD Data Sets"

NASA Technical Reports Server (NTRS)

Wilhelms, Jane; vanGelder, Allen

1999-01-01

During the four years of this grant (including the one year extension), we have explored many aspects of the visualization of large CFD (Computational Fluid Dynamics) datasets. These have included new direct volume rendering approaches, hierarchical methods, volume decimation, error metrics, parallelization, hardware texture mapping, and methods for analyzing and comparing images. First, we implemented an extremely general direct volume rendering approach that can be used to render rectilinear, curvilinear, or tetrahedral grids, including overlapping multiple zone grids, and time-varying grids. Next, we developed techniques for associating the sample data with a k-d tree, a simple hierarchial data model to approximate samples in the regions covered by each node of the tree, and an error metric for the accuracy of the model. We also explored a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH (Association for Computing Machinery Special Interest Group on Computer Graphics) '96. In our initial implementation, we automatically image the volume from 32 approximately evenly distributed positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation.

A simple solution for model comparison in bold imaging: the special case of reward prediction error and reward outcomes.

PubMed

Erdeniz, Burak; Rohe, Tim; Done, John; Seidler, Rachael D

2013-01-01

Conventional neuroimaging techniques provide information about condition-related changes of the BOLD (blood-oxygen-level dependent) signal, indicating only where and when the underlying cognitive processes occur. Recently, with the help of a new approach called "model-based" functional neuroimaging (fMRI), researchers are able to visualize changes in the internal variables of a time varying learning process, such as the reward prediction error or the predicted reward value of a conditional stimulus. However, despite being extremely beneficial to the imaging community in understanding the neural correlates of decision variables, a model-based approach to brain imaging data is also methodologically challenging due to the multicollinearity problem in statistical analysis. There are multiple sources of multicollinearity in functional neuroimaging including investigations of closely related variables and/or experimental designs that do not account for this. The source of multicollinearity discussed in this paper occurs due to correlation between different subjective variables that are calculated very close in time. Here, we review methodological approaches to analyzing such data by discussing the special case of separating the reward prediction error signal from reward outcomes.

A mechanistic compartmental model for total antibody uptake in tumors.

PubMed

Thurber, Greg M; Dane Wittrup, K

2012-12-07

Antibodies are under development to treat a variety of cancers, such as lymphomas, colon, and breast cancer. A major limitation to greater efficacy for this class of drugs is poor distribution in vivo. Localization of antibodies occurs slowly, often in insufficient therapeutic amounts, and distributes heterogeneously throughout the tumor. While the microdistribution around individual vessels is important for many therapies, the total amount of antibody localized in the tumor is paramount for many applications such as imaging, determining the therapeutic index with antibody drug conjugates, and dosing in radioimmunotherapy. With imaging and pretargeted therapeutic strategies, the time course of uptake is critical in determining when to take an image or deliver a secondary reagent. We present here a simple mechanistic model of antibody uptake and retention that captures the major rates that determine the time course of antibody concentration within a tumor including dose, affinity, plasma clearance, target expression, internalization, permeability, and vascularization. Since many of the parameters are known or can be estimated in vitro, this model can approximate the time course of antibody concentration in tumors to aid in experimental design, data interpretation, and strategies to improve localization. Copyright © 2012 Elsevier Ltd. All rights reserved.

A mechanistic compartmental model for total antibody uptake in tumors

PubMed Central

Thurber, Greg M.; Dane Wittrup, K.

2012-01-01

Antibodies are under development to treat a variety of cancers, such as lymphomas, colon, and breast cancer. A major limitation to greater efficacy for this class of drugs is poor distribution in vivo. Localization of antibodies occurs slowly, often in insufficient therapeutic amounts, and distributes heterogeneously throughout the tumor. While the microdistribution around individual vessels is important for many therapies, the total amount of antibody localized in the tumor is paramount for many applications such as imaging, determining the therapeutic index with antibody drug conjugates, and dosing in radioimmunotherapy. With imaging and pretargeted therapeutic strategies, the time course of uptake is critical in determining when to take an image or deliver a secondary reagent. We present here a simple mechanistic model of antibody uptake and retention that captures the major rates that determine the time course of antibody concentration within a tumor including dose, affinity, plasma clearance, target expression, internalization, permeability, and vascularization. Since many of the parameters are known or can be estimated in vitro, this model can approximate the time course of antibody concentration in tumors to aid in experimental design, data interpretation, and strategies to improve localization. PMID:22974563

Time-series MODIS image-based retrieval and distribution analysis of total suspended matter concentrations in Lake Taihu (China).

PubMed

Zhang, Yuchao; Lin, Shan; Liu, Jianping; Qian, Xin; Ge, Yi

2010-09-01

Although there has been considerable effort to use remotely sensed images to provide synoptic maps of total suspended matter (TSM), there are limited studies on universal TSM retrieval models. In this paper, we have developed a TSM retrieval model for Lake Taihu using TSM concentrations measured in situ and a time series of quasi-synchronous MODIS 250 m images from 2005. After simple geometric and atmospheric correction, we found a significant relationship (R = 0.8736, N = 166) between in situ measured TSM concentrations and MODIS band normalization difference of band 3 and band 1. From this, we retrieved TSM concentrations in eight regions of Lake Taihu in 2007 and analyzed the characteristic distribution and variation of TSM. Synoptic maps of model-estimated TSM of 2007 showed clear geographical and seasonal variations. TSM in Central Lake and Southern Lakeshore were consistently higher than in other regions, while TSM in East Taihu was generally the lowest among the regions throughout the year. Furthermore, a wide range of TSM concentrations appeared from winter to summer. TSM in winter could be several times that in summer.

Intensity correction for multichannel hyperpolarized 13C imaging of the heart.

PubMed

Dominguez-Viqueira, William; Geraghty, Benjamin J; Lau, Justin Y C; Robb, Fraser J; Chen, Albert P; Cunningham, Charles H

2016-02-01

Develop and test an analytic correction method to correct the signal intensity variation caused by the inhomogeneous reception profile of an eight-channel phased array for hyperpolarized (13) C imaging. Fiducial markers visible in anatomical images were attached to the individual coils to provide three dimensional localization of the receive hardware with respect to the image frame of reference. The coil locations and dimensions were used to numerically model the reception profile using the Biot-Savart Law. The accuracy of the coil sensitivity estimation was validated with images derived from a homogenous (13) C phantom. Numerical coil sensitivity estimates were used to perform intensity correction of in vivo hyperpolarized (13) C cardiac images in pigs. In comparison to the conventional sum-of-squares reconstruction, improved signal uniformity was observed in the corrected images. The analytical intensity correction scheme was shown to improve the uniformity of multichannel image reconstruction in hyperpolarized [1-(13) C]pyruvate and (13) C-bicarbonate cardiac MRI. The method is independent of the pulse sequence used for (13) C data acquisition, simple to implement and does not require additional scan time, making it an attractive technique for multichannel hyperpolarized (13) C MRI. © 2015 Wiley Periodicals, Inc.