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Sample records for functional image analysis

  1. Hyperspectral image classification using functional data analysis.

    PubMed

    Li, Hong; Xiao, Guangrun; Xia, Tian; Tang, Y Y; Li, Luoqing

    2014-09-01

    The large number of spectral bands acquired by hyperspectral imaging sensors allows us to better distinguish many subtle objects and materials. Unlike other classical hyperspectral image classification methods in the multivariate analysis framework, in this paper, a novel method using functional data analysis (FDA) for accurate classification of hyperspectral images has been proposed. The central idea of FDA is to treat multivariate data as continuous functions. From this perspective, the spectral curve of each pixel in the hyperspectral images is naturally viewed as a function. This can be beneficial for making full use of the abundant spectral information. The relevance between adjacent pixel elements in the hyperspectral images can also be utilized reasonably. Functional principal component analysis is applied to solve the classification problem of these functions. Experimental results on three hyperspectral images show that the proposed method can achieve higher classification accuracies in comparison to some state-of-the-art hyperspectral image classification methods.

  2. Functional data analysis in brain imaging studies.

    PubMed

    Tian, Tian Siva

    2010-01-01

    Functional data analysis (FDA) considers the continuity of the curves or functions, and is a topic of increasing interest in the statistics community. FDA is commonly applied to time-series and spatial-series studies. The development of functional brain imaging techniques in recent years made it possible to study the relationship between brain and mind over time. Consequently, an enormous amount of functional data is collected and needs to be analyzed. Functional techniques designed for these data are in strong demand. This paper discusses three statistically challenging problems utilizing FDA techniques in functional brain imaging analysis. These problems are dimension reduction (or feature extraction), spatial classification in functional magnetic resonance imaging studies, and the inverse problem in magneto-encephalography studies. The application of FDA to these issues is relatively new but has been shown to be considerably effective. Future efforts can further explore the potential of FDA in functional brain imaging studies.

  3. Technical considerations for functional magnetic resonance imaging analysis.

    PubMed

    Conklin, Chris J; Faro, Scott H; Mohamed, Feroze B

    2014-11-01

    Clinical application of functional magnetic resonance imaging (fMRI) based on blood oxygenation level-dependent (BOLD) effect has increased over the past decade because of its ability to map regional blood flow in response to brain stimulation. This mapping is primarily achieved by exploiting the BOLD effect precipitated by changes in the magnetic properties of hemoglobin. BOLD fMRI has utility in neurosurgical planning and mapping neuronal functional connectivity. Conventional echo planar imaging techniques are used to acquire stimulus-driven fMR imaging BOLD data. This article highlights technical aspects of fMRI data analysis to make it more accessible in clinical settings.

  4. Functional imaging of auditory scene analysis.

    PubMed

    Gutschalk, Alexander; Dykstra, Andrew R

    2014-01-01

    Our auditory system is constantly faced with the task of decomposing the complex mixture of sound arriving at the ears into perceptually independent streams constituting accurate representations of individual sound sources. This decomposition, termed auditory scene analysis, is critical for both survival and communication, and is thought to underlie both speech and music perception. The neural underpinnings of auditory scene analysis have been studied utilizing invasive experiments with animal models as well as non-invasive (MEG, EEG, and fMRI) and invasive (intracranial EEG) studies conducted with human listeners. The present article reviews human neurophysiological research investigating the neural basis of auditory scene analysis, with emphasis on two classical paradigms termed streaming and informational masking. Other paradigms - such as the continuity illusion, mistuned harmonics, and multi-speaker environments - are briefly addressed thereafter. We conclude by discussing the emerging evidence for the role of auditory cortex in remapping incoming acoustic signals into a perceptual representation of auditory streams, which are then available for selective attention and further conscious processing. This article is part of a Special Issue entitled Human Auditory Neuroimaging.

  5. Sensitivity analysis of near-infrared functional lymphatic imaging

    PubMed Central

    Weiler, Michael; Kassis, Timothy

    2012-01-01

    Abstract. Near-infrared imaging of lymphatic drainage of injected indocyanine green (ICG) has emerged as a new technology for clinical imaging of lymphatic architecture and quantification of vessel function, yet the imaging capabilities of this approach have yet to be quantitatively characterized. We seek to quantify its capabilities as a diagnostic tool for lymphatic disease. Imaging is performed in a tissue phantom for sensitivity analysis and in hairless rats for in vivo testing. To demonstrate the efficacy of this imaging approach to quantifying immediate functional changes in lymphatics, we investigate the effects of a topically applied nitric oxide (NO) donor glyceryl trinitrate ointment. Premixing ICG with albumin induces greater fluorescence intensity, with the ideal concentration being 150  μg/mL ICG and 60  g/L albumin. ICG fluorescence can be detected at a concentration of 150  μg/mL as deep as 6 mm with our system, but spatial resolution deteriorates below 3 mm, skewing measurements of vessel geometry. NO treatment slows lymphatic transport, which is reflected in increased transport time, reduced packet frequency, reduced packet velocity, and reduced effective contraction length. NIR imaging may be an alternative to invasive procedures measuring lymphatic function in vivo in real time. PMID:22734775

  6. Sensitivity analysis of near-infrared functional lymphatic imaging

    NASA Astrophysics Data System (ADS)

    Weiler, Michael; Kassis, Timothy; Dixon, J. Brandon

    2012-06-01

    Near-infrared imaging of lymphatic drainage of injected indocyanine green (ICG) has emerged as a new technology for clinical imaging of lymphatic architecture and quantification of vessel function, yet the imaging capabilities of this approach have yet to be quantitatively characterized. We seek to quantify its capabilities as a diagnostic tool for lymphatic disease. Imaging is performed in a tissue phantom for sensitivity analysis and in hairless rats for in vivo testing. To demonstrate the efficacy of this imaging approach to quantifying immediate functional changes in lymphatics, we investigate the effects of a topically applied nitric oxide (NO) donor glyceryl trinitrate ointment. Premixing ICG with albumin induces greater fluorescence intensity, with the ideal concentration being 150 μg/mL ICG and 60 g/L albumin. ICG fluorescence can be detected at a concentration of 150 μg/mL as deep as 6 mm with our system, but spatial resolution deteriorates below 3 mm, skewing measurements of vessel geometry. NO treatment slows lymphatic transport, which is reflected in increased transport time, reduced packet frequency, reduced packet velocity, and reduced effective contraction length. NIR imaging may be an alternative to invasive procedures measuring lymphatic function in vivo in real time.

  7. Statistical analysis of dynamic sequences for functional imaging

    NASA Astrophysics Data System (ADS)

    Kao, Chien-Min; Chen, Chin-Tu; Wernick, Miles N.

    2000-04-01

    Factor analysis of medical image sequences (FAMIS), in which one concerns the problem of simultaneous identification of homogeneous regions (factor images) and the characteristic temporal variations (factors) inside these regions from a temporal sequence of images by statistical analysis, is one of the major challenges in medical imaging. In this research, we contribute to this important area of research by proposing a two-step approach. First, we study the use of the noise- adjusted principal component (NAPC) analysis developed by Lee et. al. for identifying the characteristic temporal variations in dynamic scans acquired by PET and MRI. NAPC allows us to effectively reject data noise and substantially reduce data dimension based on signal-to-noise ratio consideration. Subsequently, a simple spatial analysis based on the criteria of minimum spatial overlapping and non-negativity of the factor images is applied for extraction of the factors and factor images. In our simulation study, our preliminary results indicate that the proposed approach can accurately identify the factor images. However, the factors are not completely separated.

  8. Meta-analysis of functional brain imaging in specific phobia.

    PubMed

    Ipser, Jonathan C; Singh, Leesha; Stein, Dan J

    2013-07-01

    Although specific phobia is a prevalent anxiety disorder, evidence regarding its underlying functional neuroanatomy is inconsistent. A meta-analysis was undertaken to identify brain regions that were consistently responsive to phobic stimuli, and to characterize changes in brain activation following cognitive behavioral therapy (CBT). We searched the PubMed, SCOPUS and PsycINFO databases to identify positron emission tomography and functional magnetic resonance imaging studies comparing brain activation in specific phobia patients and healthy controls. Two raters independently extracted study data from all the eligible studies, and pooled coordinates from these studies using activation likelihood estimation, a quantitative meta-analytic technique. Resulting statistical parametric maps were compared between patients and healthy controls, in response to phobic versus fear-evoking stimuli, and before and after therapy. Thirteen studies were included, comprising 327 participants. Regions that were consistently activated in response to phobic stimuli included the left insula, amygdala, and globus pallidus. Compared to healthy controls, phobic subjects had increased activation in response to phobic stimuli in the left amygdala/globus pallidus, left insula, right thalamus (pulvinar), and cerebellum. Following exposure-based therapy widespread deactivation was observed in the right frontal cortex, limbic cortex, basal ganglia and cerebellum, with increased activation detected in the thalamus. Exposure to phobia-specific stimuli elicits brain activation that is consistent with current understandings of the neuroanatomy of fear conditioning and extinction. There is evidence that the effects of CBT in specific phobia may be mediated through the same underlying neurocircuitry.

  9. Analysis of nulling phase functions suitable to image plane coronagraphy

    NASA Astrophysics Data System (ADS)

    Hénault, François; Carlotti, Alexis; Vérinaud, Christophe

    2016-07-01

    Coronagraphy is a very efficient technique for identifying and characterizing extra-solar planets orbiting in the habitable zone of their parent star, especially in a space environment. An important family of coronagraphs is actually based on phase plates located at an intermediate image plane of the optical system, and spreading the starlight outside the "Lyot" exit pupil plane of the instrument. In this commutation we present a set of candidate phase functions generating a central null at the Lyot plane, and study how it propagates to the image plane of the coronagraph. These functions include linear azimuthal phase ramps (the well-known optical vortex), azimuthally cosine-modulated phase profiles, and circular phase gratings. Nnumerical simulations of the expected null depth, inner working angle, sensitivity to pointing errors, effect of central obscuration located at the pupil or image planes, and effective throughput including image mask and Lyot stop transmissions are presented and discussed. The preliminary conclusion is that azimuthal cosine functions appear as an interesting alternative to the classical optical vortex of integer topological charge.

  10. Sensitivity analysis of near-infrared functional lymphatic imaging

    NASA Astrophysics Data System (ADS)

    Weiler, Michael; Kassis, Timothy; Dixon, J. Brandon

    2012-03-01

    Background - Near-infrared (NIR) imaging of lymphatic drainage of injected indocyanine green (ICG) has emerged as a new technology for clinical imaging of lymphatic architecture and quantification of vessel function, offering better spatial and temporal resolution than competing imaging modalities. While NIR lymphatic imaging has begun to be reported in the literature, the technology is still in its infancy and its imaging capabilities have yet to be quantitatively characterized. The objective of this study, therefore, was to characterize the parameters of NIR lymphatic imaging to quantify its capabilities as a diagnostic tool for evaluating lymphatic disease. Methods - An NIR imaging system was developed using a laser diode for excitation, ICG as a fluorescent agent, and a CCD camera to detect emission. A tissue phantom with mock lymphatic vessels of known depths and diameters was used as an alternative to in vivo lymphatic vessels due to the greater degree of control with the phantom. Results and Conclusions - When dissolved in an albumin physiological salt solution (APSS) to mimic interstitial fluid, ICG experiences shifts in the excitation/emission wavelengths such that it is maximally excited at 805nm and produces peak fluorescence at 840nm. Premixing ICG with albumin induces greater fluorescence intensity, with the ideal concentration being: 900μM (60g/L) albumin and 193.5μM (150μg/mL) ICG. ICG fluorescence can be detected as deep as 6mm, but spatial resolution deteriorates severely below 3mm, thus skewing vessel geometry measurements. ICG packet travel, a common measure of lymphatic transport, can be detected as deep as 5mm.

  11. Time-frequency analysis of functional optical mammographic images

    NASA Astrophysics Data System (ADS)

    Barbour, Randall L.; Graber, Harry L.; Schmitz, Christoph H.; Tarantini, Frank; Khoury, Georges; Naar, David J.; Panetta, Thomas F.; Lewis, Theophilus; Pei, Yaling

    2003-07-01

    We have introduced working technology that provides for time-series imaging of the hemoglobin signal in large tissue structures. In this study we have explored our ability to detect aberrant time-frequency responses of breast vasculature for subjects with Stage II breast cancer at rest and in response to simple provocations. The hypothesis being explored is that time-series imaging will be sensitive to the known structural and functional malformations of the tumor vasculature. Mammographic studies were conducted using an adjustable hemisheric measuring head containing 21 source and 21 detector locations (441 source-detector pairs). Simultaneous dual-wavelength studies were performed at 760 and 830 nm at a framing rate of ~2.7 Hz. Optical measures were performed on women lying prone with the breast hanging in a pendant position. Two class of measures were performed: (1) 20- minute baseline measure wherein the subject was at rest; (2) provocation studies wherein the subject was asked to perform some simple breathing maneuvers. Collected data were analyzed to identify the time-frequency structure and central tendencies of the detector responses and those of the image time series. Imaging data were generated using the Normalized Difference Method (Pei et al., Appl. Opt. 40, 5755-5769, 2001). Results obtained clearly document three classes of anomalies when compared to the normal contralateral breast. 1) Breast tumors exhibit altered oxygen supply/demand imbalance in response to an oxidative challenge (breath hold). 2) The vasomotor response of the tumor vasculature is mainly depressed and exhibits an altered modulation. 3) The affected area of the breast wherein the altered vasomotor signature is seen extends well beyond the limits of the tumor itself.

  12. Automated microscopy and image analysis for androgen receptor function.

    PubMed

    Hartig, Sean M; Newberg, Justin Y; Bolt, Michael J; Szafran, Adam T; Marcelli, Marco; Mancini, Michael A

    2011-01-01

    Systems-level approaches have emerged that rely on analytical, microscopy-based technology for the discovery of novel drug targets and the mechanisms driving AR signaling, transcriptional activity, and ligand independence. Single cell behavior can be quantified by high-throughput microscopy methods through analysis of endogenous protein levels and localization or creation of biosensor cell lines that can simultaneously detect both acute and latent responses to known and unknown androgenic stimuli. The cell imaging and analytical protocols can be automated to discover agonist/antagonist response windows for nuclear translocation, reporter gene activity, nuclear export, and subnuclear transcription events, facilitating access to a multiplex model system that is inherently unavailable through classic biochemical approaches. In this chapter, we highlight the key steps needed for developing, conducting, and analyzing high-throughput screens to identify effectors of AR signaling.

  13. Multiple functional linear model for association analysis of RNA-seq with imaging

    PubMed Central

    Jiang, Junhai; Lin, Nan; Guo, Shicheng; Chen, Jinyun; Xiong, Momiao

    2015-01-01

    Emerging integrative analysis of genomic and anatomical imaging data which has not been well developed, provides invaluable information for the holistic discovery of the genomic structure of disease and has the potential to open a new avenue for discovering novel disease susceptibility genes which cannot be identified if they are analyzed separately. A key issue to the success of imaging and genomic data analysis is how to reduce their dimensions. Most previous methods for imaging information extraction and RNA-seq data reduction do not explore imaging spatial information and often ignore gene expression variation at the genomic positional level. To overcome these limitations, we extend functional principle component analysis from one dimension to two dimensions (2DFPCA) for representing imaging data and develop a multiple functional linear model (MFLM) in which functional principal scores of images are taken as multiple quantitative traits and RNA-seq profile across a gene is taken as a function predictor for assessing the association of gene expression with images. The developed method has been applied to image and RNA-seq data of ovarian cancer and kidney renal clear cell carcinoma (KIRC) studies. We identified 24 and 84 genes whose expressions were associated with imaging variations in ovarian cancer and KIRC studies, respectively. Our results showed that many significantly associated genes with images were not differentially expressed, but revealed their morphological and metabolic functions. The results also demonstrated that the peaks of the estimated regression coefficient function in the MFLM often allowed the discovery of splicing sites and multiple isoforms of gene expressions. PMID:26753102

  14. Spatial independent component analysis of functional brain optical imaging

    NASA Astrophysics Data System (ADS)

    Li, Yong; Li, Pengcheng; Liu, Yadong; Luo, Weihua; Hu, Dewen; Luo, Qingming

    2003-12-01

    This paper introduces the algorithm and the basic theory of Independent Component Analysis (ICA), and discusses how to choose the proper ICA model of the data by the characteristics of the underlying signals to be estimated. The Spatial ICA (SICA) is applied to model and analysis of the data in the experiment when the signals and noises are spatially dependent. The data acquired from the intrinsic optical signals which are caused by electricity stimulation to sciatic nerve of rat are analyzed by SICA. In the result, the active-related component of the signals and its time course can be separate, and the signals of heartbeat and respiration also can be separated.

  15. Analysis of a 3-D system function measured for magnetic particle imaging.

    PubMed

    Rahmer, Jürgen; Weizenecker, Jürgen; Gleich, Bernhard; Borgert, Jörn

    2012-06-01

    Magnetic particle imaging (MPI) is a new tomographic imaging approach that can quantitatively map magnetic nanoparticle distributions in vivo. It is capable of volumetric real-time imaging at particle concentrations low enough to enable clinical applications. For image reconstruction in 3-D MPI, a system function (SF) is used, which describes the relation between the acquired MPI signal and the spatial origin of the signal. The SF depends on the instrumental configuration, the applied field sequence, and the magnetic particle characteristics. Its properties reflect the quality of the spatial encoding process. This work presents a detailed analysis of a measured SF to give experimental evidence that 3-D MPI encodes information using a set of 3-D spatial patterns or basis functions that is stored in the SF. This resembles filling 3-D k-space in magnetic resonance imaging, but is faster since all information is gathered simultaneously over a broad acquisition bandwidth. A frequency domain analysis shows that the finest structures that can be encoded with the presented SF are as small as 0.6 mm. SF simulations are performed to demonstrate that larger particle cores extend the set of basis functions towards higher resolution and that the experimentally observed spatial patterns require the existence of particles with core sizes of about 30 nm in the calibration sample. A simple formula is presented that qualitatively describes the basis functions to be expected at a certain frequency.

  16. Quantitative assessment of p-glycoprotein expression and function using confocal image analysis.

    PubMed

    Hamrang, Zahra; Arthanari, Yamini; Clarke, David; Pluen, Alain

    2014-10-01

    P-glycoprotein is implicated in clinical drug resistance; thus, rapid quantitative analysis of its expression and activity is of paramout importance to the design and success of novel therapeutics. The scope for the application of quantitative imaging and image analysis tools in this field is reported here at "proof of concept" level. P-glycoprotein expression was utilized as a model for quantitative immunofluorescence and subsequent spatial intensity distribution analysis (SpIDA). Following expression studies, p-glycoprotein inhibition as a function of verapamil concentration was assessed in two cell lines using live cell imaging of intracellular Calcein retention and a routine monolayer fluorescence assay. Intercellular and sub-cellular distributions in the expression of the p-glycoprotein transporter between parent and MDR1-transfected Madin-Derby Canine Kidney cell lines were examined. We have demonstrated that quantitative imaging can provide dose-response parameters while permitting direct microscopic analysis of intracellular fluorophore distributions in live and fixed samples. Analysis with SpIDA offers the ability to detect heterogeniety in the distribution of labeled species, and in conjunction with live cell imaging and immunofluorescence staining may be applied to the determination of pharmacological parameters or analysis of biopsies providing a rapid prognostic tool.

  17. Anatomical-Functional Correlative Analysis Of The Human Brain Using Three Dimensional Imaging Systems

    NASA Astrophysics Data System (ADS)

    Evans, Alan C.; Marrett, Sean; Collins, D. L.; Peters, Terence M.

    1989-05-01

    Quantitative interpretation of functional images (PET or SPECT) is hampered by poor spatial resolution, low counting statistics and, for many tracers, low contrast between different brain structures of interest. Further, normal tracer distributions can be severely distorted by such gross pathologies as stroke, tumor and dementia. Hence, the complementary anatomical information provided by CT or MRI is essential for accurate and reproducible regional analysis of functional data. We have developed methods for the three-dimensional integration and simultaneous display of image volumes from MRI and PET. PET data was collected from an older Therascan 3-slice scanner with 12 mm resolution and a 15-slice Scanditronix PC-2048 system having 5-6 mm resolution in each dimension. MRI data was obtained from a Philips 1.5 Tesla Gyroscan scanner. The image volumes were loaded into a PIXAR 3-D image computer for simultaneous display. A general algorithm for finding the optimal transformation between two ensembles of equivalent points was implemented and investigated through simulation studies. Using a locally-developed 3-D image/graphics analysis package, equivalent points in the two image volumes were identified, either manually or via an adjustable computerized volume-of-interest (VOI) atlas. The MRI data were then re-sampled along planes parallel to the PET planes and the two volumes overlaid using opacity-weighted composition. Arbitrary oblique planes through the two volumes were obtained in interactive sessions.

  18. Magnetic induction tomography: evaluation of the point spread function and analysis of resolution and image distortion.

    PubMed

    Merwa, Robert; Scharfetter, Hermann

    2007-07-01

    Magnetic induction tomography (MIT) is a low-resolution imaging modality used for reconstructing the changes of the passive electrical properties in a target object. For an imaging system, it is very important to give forecasts about the image quality. Both the maximum resolution and the correctness of the location of the inhomogeneities are of major interest. Furthermore, the smallest object which can be detected for a certain noise level is a criterion for the diagnostic value of an image. The properties of an MIT image are dependent on the position inside the object, the conductivity distribution and of course on the location and the number of excitation coils and receiving coils. Quantitative statements cannot be made in general but it is feasible to predict the image quality for a selected problem. For electrical impedance tomography (EIT), the theoretical limits of image quality have been studied carefully and a comprehensive analysis for MIT is necessary. Thus, a simplified analysis on resolution, dimensions and location of an inhomogeneity was carried out by means of an evaluation of the point spread function (PSF). In analogy to EIT the PSF depends strongly on the location, showing the broadest distribution in the centre of the object. Increasing the amount of regularization according to increasing measurement noise, the PSF broadens and its centre is shifted towards the borders of the object. The resolution is indirectly proportional to the width of the PSF and increases when moving from the centre towards the border of the object and decreases with increasing noise.

  19. Quantitative analysis of scanning tunneling microscopy images of mixed-ligand-functionalized nanoparticles.

    PubMed

    Biscarini, Fabio; Ong, Quy Khac; Albonetti, Cristiano; Liscio, Fabiola; Longobardi, Maria; Mali, Kunal S; Ciesielski, Artur; Reguera, Javier; Renner, Christoph; De Feyter, Steven; Samorì, Paolo; Stellacci, Francesco

    2013-11-12

    Ligand-protected gold nanoparticles exhibit large local curvatures, features rapidly varying over small scales, and chemical heterogeneity. Their imaging by scanning tunneling microscopy (STM) can, in principle, provide direct information on the architecture of their ligand shell, yet STM images require laborious analysis and are challenging to interpret. Here, we report a straightforward, robust, and rigorous method for the quantitative analysis of the multiscale features contained in STM images of samples consisting of functionalized Au nanoparticles deposited onto Au/mica. The method relies on the analysis of the topographical power spectral density (PSD) and allows us to extract the characteristic length scales of the features exhibited by nanoparticles in STM images. For the mixed-ligand-protected Au nanoparticles analyzed here, the characteristic length scale is 1.2 ± 0.1 nm, whereas for the homoligand Au NPs this scale is 0.75 ± 0.05 nm. These length scales represent spatial correlations independent of scanning parameters, and hence the features in the PSD can be ascribed to a fingerprint of the STM contrast of ligand-protected nanoparticles. PSD spectra from images recorded at different laboratories using different microscopes and operators can be overlapped across most of the frequency range, proving that the features in the STM images of nanoparticles can be compared and reproduced.

  20. A framework for the analysis and evaluation of optical imaging systems with arbitrary response functions

    NASA Astrophysics Data System (ADS)

    Wang, Zhipeng

    The scientific applications and engineering aspects of multispectral and hyperspectral imaging systems have been studied extensively. The traditional geometric spectral imaging system model is specifically developed aiming at spectral sensors with spectrally non-overlapping bands. Spectral imaging systems with overlapping bands also exist. For example, the quantum-dot infrared photodetectors (QDIPs) for midwave- and longwave-infrared (IR) imaging systems exhibit highly overlapping spectral responses tunable through the bias voltages applied. This makes it possible to build spectrally tunable imaging system in IR range based on single QDIP. Furthermore, the QDIP based system can be operated as being adaptive to scenes. Other optical imaging systems like the human eye and some polarimetric sensing systems also have overlapping bands. To analyze such sensors, a functional analysis-based framework is provided in this dissertation. The framework starts from the mathematical description of the interaction between sensor and the radiation from scene reaching it. A geometric model of the spectral imaging process is provided based on the framework. The spectral response functions and the scene spectra are considered as vectors inside an 1-dimensional spectral space. The spectral imaging process is abstracted to represent a projection of scene spectrum onto sensor. The projected spectrum, which is the least-square error reconstruction of the scene vectors, contains the useful information for image processing. Spectral sensors with arbitrary spectral response functions are can be analyzed with this model. The framework leads directly to an image pre-processing algorithm to remove the data correlation between bands. Further discussion shows that this model can also serve the purpose of sensor evaluation, and thus facilitates comparison between different sensors. The spectral shapes and the Signal-to-Noise Ratios (SNR) of different bands are seen to influence the sensor

  1. Improved factor analysis of dynamic PET images to estimate arterial input function and tissue curves

    NASA Astrophysics Data System (ADS)

    Boutchko, Rostyslav; Mitra, Debasis; Pan, Hui; Jagust, William; Gullberg, Grant T.

    2015-03-01

    Factor analysis of dynamic structures (FADS) is a methodology of extracting time-activity curves (TACs) for corresponding different tissue types from noisy dynamic images. The challenges of FADS include long computation time and sensitivity to the initial guess, resulting in convergence to local minima far from the true solution. We propose a method of accelerating and stabilizing FADS application to sequences of dynamic PET images by adding preliminary cluster analysis of the time activity curves for individual voxels. We treat the temporal variation of individual voxel concentrations as a set of time-series and use a partial clustering analysis to identify the types of voxel TACs that are most functionally distinct from each other. These TACs provide a good initial guess for the temporal factors for subsequent FADS processing. Applying this approach to a set of single slices of dynamic 11C-PIB images of the brain allows identification of the arterial input function and two different tissue TACs that are likely to correspond to the specific and non-specific tracer binding-tissue types. These results enable us to perform direct classification of tissues based on their pharmacokinetic properties in dynamic PET without relying on a compartment-based kinetic model, without identification of the reference region, or without using any external methods of estimating the arterial input function, as needed in some techniques.

  2. Correlation of sensorimotor activation with functional magnetic resonance imaging and magnetoencephalography in presurgical functional imaging: a spatial analysis.

    PubMed

    Kober, H; Nimsky, C; Möller, M; Hastreiter, P; Fahlbusch, R; Ganslandt, O

    2001-11-01

    In this study we investigated the spatial heterotopy of MEG and fMRI localizations after sensory and motor stimulation tasks. Both methods are frequently used to study the topology of the primary and secondary motor cortex, as well as a tool for presurgical brain mapping. fMRI was performed with a 1.5T MR system, using echo-planar imaging with a motor and a sensory task. Somatosensory and motor evoked fields were recorded with a biomagnetometer. fMRI activation was determined with a cross-correlation analysis. MEG source localization was performed with a single equivalent current dipole model and a current density localization approach. Distances between MEG and fMRI activation sites were measured within the same anatomical 3-D-MR image set. The central region could be identified by MEG and fMRI in 33 of 34 cases. However, MEG and fMRI localization results showed significantly different activation sites for the motor and sensory task with a distance of 10 and 15 mm, respectively. This reflects the different neurophysiological mechanisms: direct neuronal current flow (MEG) and secondary changes in cerebral blood flow and oxygenation level of activated versus non activated brain structures (fMRI). The result of our study has clinical implications when MEG and fMRI localizations are used for pre- and intraoperative brain mapping. Although both modalities are useful for the estimation of the motor cortex, a single modality may err in the exact topographical labeling of the motor cortex. In some unclear cases a combination of both methods should be used in order to avoid neurological deficits.

  3. A study on quantifying COPD severity by combining pulmonary function tests and CT image analysis

    NASA Astrophysics Data System (ADS)

    Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

    2011-03-01

    This paper describes a novel method that can evaluate chronic obstructive pulmonary disease (COPD) severity by combining measurements of pulmonary function tests and measurements obtained from CT image analysis. There is no cure for COPD. However, with regular medical care and consistent patient compliance with treatments and lifestyle changes, the symptoms of COPD can be minimized and progression of the disease can be slowed. Therefore, many diagnosis methods based on CT image analysis have been proposed for quantifying COPD. Most of diagnosis methods for COPD extract the lesions as low-attenuation areas (LAA) by thresholding and evaluate the COPD severity by calculating the LAA in the lung (LAA%). However, COPD is usually the result of a combination of two conditions, emphysema and chronic obstructive bronchitis. Therefore, the previous methods based on only LAA% do not work well. The proposed method utilizes both of information including the measurements of pulmonary function tests and the results of the chest CT image analysis to evaluate the COPD severity. In this paper, we utilize a multi-class AdaBoost to combine both of information and classify the COPD severity into five stages automatically. The experimental results revealed that the accuracy rate of the proposed method was 88.9% (resubstitution scheme) and 64.4% (leave-one-out scheme).

  4. Imaging the Crustal and Subducted Slab Structure Beneath Puerto Rico Using Receiver Function Analysis

    NASA Astrophysics Data System (ADS)

    Vanacore, E. A.; Lopez, A. M.; Huerfano Moreno, V. A.

    2015-12-01

    The determination of earthquake locations are dependent on the velocity model selected. Consequently, the refinement and updating of the velocity models used at the local and regional network level is a critical component for network efficiency through location accuracy. With the expansion of broadband instruments within the Puerto Rico -Virgin Islands region, updating the velocity model is a current long term goal of the Puerto Rico Seismic Network (PRSN). As a first step to this long term goal, receiver functions of ~20 broadband stations with data between 2010 and 2015 were calculated using iterative time domain deconvolution. The receiver function analysis not only provides insight into the crustal velocity structure but also leads to a better understanding of the region's larger tectonic structure. Preliminary results of the receiver function analysis exhibit evidence of a "slab signal"; the receiver function backazimuth sweeps for some stations particularly on the northern side of the island contain a strong P to S conversion at approximately 7 seconds which likely corresponds to the top of the slab beneath Puerto Rico. This strong slab signal implies that simple 1-D analyses of the data (e.g. H-K stacking) may lead to misleading results. To further understand the crustal structure of PRVI, we employ a 3D common-conversion-point analysis. This analysis yields a Moho beneath the island between 32-42km and a possible southward dipping slab structure between 60-80km depth. Further analysis is needed to determine the 2D or 3D velocity structure of Puerto Rico and the surrounding environs such as waveform modeling. Given the current geometry of the available array, detailed imaging of the slab and mantle wedge beneath Puerto Rico is limited. PRSN is currently seeking to install denser temporary networks to improve local imaging that will help understand the nature of the crust, mantle wedge and slab structure beneath the island as well as the structure's influence

  5. Surface-based functional magnetic resonance imaging analysis of partial brain echo planar imaging data at 1.5 T.

    PubMed

    Jo, Hang Joon; Lee, Jong-Min; Kim, Jae-Hun; Choi, Chi-Hoon; Kang, Do-Hyung; Kwon, Jun Soo; Kim, Sun I

    2009-06-01

    Surface-based functional magnetic resonance imaging (fMRI) analysis is more sensitive and accurate than volume-based analysis for detecting neural activation. However, these advantages are less important in practical fMRI experiments with commonly used 1.5-T magnetic resonance devices because of the resolution gap between the echo planar imaging data and the cortical surface models. We expected high-resolution segmented partial brain echo planar imaging (EPI) data to overcome this problem, and the activation patterns of the high-resolution data could be different from the low-resolution data. For the practical applications of surface-based fMRI analysis using segmented EPI techniques, the effects of some important factors (e.g., activation patterns, registration and local distortions) should be intensively evaluated because the results of surface-based fMRI analyses could be influenced by them. In this study, we demonstrated the difference between activations detected from low-resolution EPI data, which were covering whole brain, and high-resolution segmented EPI data covering partial brain by volume- and surface-based analysis methods. First, we compared the activation maps of low- and high-resolution EPI datasets detected by volume- and surface-based analyses, with the spatial patterns of activation clusters, and analyzed the distributions of activations in occipital lobes. We also analyzed the high-resolution EPI data covering motor areas and fusiform gyri of human brain, and presented the differences of activations detected by volume- and surface-based methods.

  6. Source analysis of stimulus-preceding negativity constrained by functional magnetic resonance imaging.

    PubMed

    Kotani, Yasunori; Ohgami, Yoshimi; Ishiwata, Takayuki; Arai, Jun-Ichirou; Kiryu, Shigeru; Inoue, Yusuke

    2015-10-01

    The stimulus-preceding negativity (SPN) is an event-related potential (ERP) reflecting anticipation. The anterior insular cortex is assumed to be one of the physiological sources of the SPN. However, the precise neural substrates of the SPN have yet to be confirmed. We therefore performed separate functional magnetic resonance imaging (fMRI) and ERP studies using the same time estimation task, followed by fMRI-constrained ERP source analysis. Dipole locations were determined by the fMRI results, while the time courses of dipole activities were modeled by the ERP data. Analysis revealed that the right anterior insula was significantly activated before delivery of the feedback stimulus, whereas the left anterior insula was not, and that the SPN mainly arose from four groups of brain regions related to, respectively: (1) the salience network, (2) reward expectation, (3) perceptual anticipation, and (4) arousal. The results suggest that the SPN pertains to multiple brain functions with complex interactions.

  7. Surface-based analysis methods for high-resolution functional magnetic resonance imaging

    PubMed Central

    Khan, Rez; Zhang, Qin; Darayan, Shayan; Dhandapani, Sankari; Katyal, Sucharit; Greene, Clint; Bajaj, Chandra; Ress, David

    2011-01-01

    Functional magnetic resonance imaging (fMRI) has become a popular technique for studies of human brain activity. Typically, fMRI is performed with >3-mm sampling, so that the imaging data can be regarded as two-dimensional samples that average through the 1.5—4-mm thickness of cerebral cortex. The increasing use of higher spatial resolutions, <1.5-mm sampling, complicates the analysis of fMRI, as one must now consider activity variations within the depth of the brain tissue. We present a set of surface-based methods to exploit the use of high-resolution fMRI for depth analysis. These methods utilize white-matter segmentations coupled with deformable-surface algorithms to create a smooth surface representation at the gray-white interface and pial membrane. These surfaces provide vertex positions and normals for depth calculations, enabling averaging schemes that can increase contrast-to-noise ratio, as well as permitting the direct analysis of depth profiles of functional activity in the human brain. PMID:22125419

  8. The neuronal correlates of intranasal trigeminal function – An ALE meta-analysis of human functional brain imaging data

    PubMed Central

    Albrecht, Jessica; Kopietz, Rainer; Frasnelli, Johannes; Wiesmann, Martin; Hummel, Thomas; Lundström, Johan N.

    2009-01-01

    Almost every odor we encounter in daily life has the capacity to produce a trigeminal sensation. Surprisingly, few functional imaging studies exploring human neuronal correlates of intranasal trigeminal function exist, and results are to some degree inconsistent. We utilized activation likelihood estimation (ALE), a quantitative voxel-based meta-analysis tool, to analyze functional imaging data (fMRI/PET) following intranasal trigeminal stimulation with carbon dioxide (CO2), a stimulus known to exclusively activate the trigeminal system. Meta-analysis tools are able to identify activations common across studies, thereby enabling activation mapping with higher certainty. Activation foci of nine studies utilizing trigeminal stimulation were included in the meta-analysis. We found significant ALE scores, thus indicating consistent activation across studies, in the brainstem, ventrolateral posterior thalamic nucleus, anterior cingulate cortex, insula, precentral gyrus, as well as in primary and secondary somatosensory cortices – a network known for the processing of intranasal nociceptive stimuli. Significant ALE values were also observed in the piriform cortex, insula, and the orbitofrontal cortex, areas known to process chemosensory stimuli, and in association cortices. Additionally, the trigeminal ALE statistics were directly compared with ALE statistics originating from olfactory stimulation, demonstrating considerable overlap in activation. In conclusion, the results of this meta-analysis map the human neuronal correlates of intranasal trigeminal stimulation with high statistical certainty and demonstrate that the cortical areas recruited during the processing of intranasal CO2 stimuli include those outside traditional trigeminal areas. Moreover, through illustrations of the considerable overlap between brain areas that process trigeminal and olfactory information; these results demonstrate the interconnectivity of flavor processing. PMID:19913573

  9. Functional Magnetic Resonance Imaging

    ERIC Educational Resources Information Center

    Voos, Avery; Pelphrey, Kevin

    2013-01-01

    Functional magnetic resonance imaging (fMRI), with its excellent spatial resolution and ability to visualize networks of neuroanatomical structures involved in complex information processing, has become the dominant technique for the study of brain function and its development. The accessibility of in-vivo pediatric brain-imaging techniques…

  10. Fuzzy membership functions for analysis of high-resolution CT images of diffuse pulmonary diseases.

    PubMed

    Almeida, Eliana; Rangayyan, Rangaraj M; Azevedo-Marques, Paulo M

    2015-08-01

    We propose the use of fuzzy membership functions to analyze images of diffuse pulmonary diseases (DPDs) based on fractal and texture features. The features were extracted from preprocessed regions of interest (ROIs) selected from high-resolution computed tomography images. The ROIs represent five different patterns of DPDs and normal lung tissue. A Gaussian mixture model (GMM) was constructed for each feature, with six Gaussians modeling the six patterns. Feature selection was performed and the GMMs of the five significant features were used. From the GMMs, fuzzy membership functions were obtained by a probability-possibility transformation and further statistical analysis was performed. An average classification accuracy of 63.5% was obtained for the six classes. For four of the six classes, the classification accuracy was superior to 65%, and the best classification accuracy was 75.5% for one class. The use of fuzzy membership functions to assist in pattern classification is an alternative to deterministic approaches to explore strategies for medical diagnosis.

  11. "More is different" in functional magnetic resonance imaging: a review of recent data analysis techniques.

    PubMed

    Lohmann, Gabriele; Stelzer, Johannes; Neumann, Jane; Ay, Nihat; Turner, Robert

    2013-01-01

    Two aspects play a key role in recently developed strategies for functional magnetic resonance imaging (fMRI) data analysis: first, it is now recognized that the human brain is a complex adaptive system and exhibits the hallmarks of complexity such as emergence of patterns arising out of a multitude of interactions between its many constituents. Second, the field of fMRI has evolved into a data-intensive, big data endeavor with large databases and masses of data being shared around the world. At the same time, ultra-high field MRI scanners are now available producing data at previously unobtainable quality and quantity. Both aspects have led to shifts in the way in which we view fMRI data. Here, we review recent developments in fMRI data analysis methodology that resulted from these shifts in paradigm.

  12. Frequency Clustering Analysis for Resting State Functional Magnetic Resonance Imaging Based on Hilbert-Huang Transform

    PubMed Central

    Wu, Xia; Wu, Tong; Liu, Chenghua; Wen, Xiaotong; Yao, Li

    2017-01-01

    Objective: Exploring resting-state functional networks using functional magnetic resonance imaging (fMRI) is a hot topic in the field of brain functions. Previous studies suggested that the frequency dependence between blood oxygen level dependent (BOLD) signals may convey meaningful information regarding interactions between brain regions. Methods: In this article, we introduced a novel frequency clustering analysis method based on Hilbert-Huang Transform (HHT) and a label-replacement procedure. First, the time series from multiple predefined regions of interest (ROIs) were extracted. Second, each time series was decomposed into several intrinsic mode functions (IMFs) by using HHT. Third, the improved k-means clustering method using a label-replacement method was applied to the data of each subject to classify the ROIs into different classes. Results: Two independent resting-state fMRI dataset of healthy subjects were analyzed to test the efficacy of method. The results show almost identical clusters when applied to different runs of a dataset or to different datasets, indicating a stable performance of our framework. Conclusions and Significance: Our framework provided a novel measure for functional segregation of the brain according to time-frequency characteristics of resting state BOLD activities. PMID:28261074

  13. SACICA: a sparse approximation coefficient-based ICA model for functional magnetic resonance imaging data analysis.

    PubMed

    Wang, Nizhuan; Zeng, Weiming; Chen, Lei

    2013-05-30

    Independent component analysis (ICA) has been widely used in functional magnetic resonance imaging (fMRI) data to evaluate the functional connectivity, which assumes that the sources of functional networks are statistically independent. Recently, many researchers have demonstrated that sparsity is an effective assumption for fMRI signal separation. In this research, we present a sparse approximation coefficient-based ICA (SACICA) model to analyse fMRI data, which is a promising combination model of sparse features and an ICA technique. The SACICA method consists of three procedures. The wavelet packet decomposition procedure, which decomposes the fMRI data into wavelet tree nodes with different degrees of sparsity, is first. Then, the sparse approximation coefficients set formation procedure, in which an effective Lp norm is proposed to measure the sparse degree of the distinct wavelet tree nodes, is second. The ICA decomposition and reconstruction procedure, which utilises the sparse approximation coefficients set of the fMRI data, is last. The hybrid data experimental results demonstrated that the SACICA method exhibited the stronger spatial source reconstruction ability with respect to the unsmoothed fMRI data and better detection sensitivity of the functional signal on the smoothed fMRI data than the FastICA method. Furthermore, task-related experiments also revealed that SACICA was not only effective in discovering the functional networks but also exhibited a better detection sensitivity of the visual-related functional signal. In addition, the SACICA combined with Fast-FENICA proposed by Wang et al. (2012) was demonstrated to conduct the group analysis effectively on the resting-state data set.

  14. Image watermarking based on the space/spatial-frequency analysis and Hermite functions expansion

    NASA Astrophysics Data System (ADS)

    Stanković, Srdjan; Orović, Irena; Chabert, Marie; Mobasseri, Bijan

    2013-01-01

    An image watermarking scheme that combines Hermite functions expansion and space/spatial-frequency analysis is proposed. In the first step, the Hermite functions expansion is employed to select busy regions for watermark embedding. In the second step, the space/spatial-frequency representation and Hermite functions expansion are combined to design the imperceptible watermark, using the host local frequency content. The Hermite expansion has been done by using the fast Hermite projection method. Recursive realization of Hermite functions significantly speeds up the algorithms for regions selection and watermark design. The watermark detection is performed within the space/spatial-frequency domain. The detection performance is increased due to the high information redundancy in that domain in comparison with the space or frequency domains, respectively. The performance of the proposed procedure has been tested experimentally for different watermark strengths, i.e., for different values of the peak signal-to-noise ratio (PSNR). The proposed approach provides high detection performance even for high PSNR values. It offers a good compromise between detection performance (including the robustness to a wide variety of common attacks) and imperceptibility.

  15. Principal and independent component analysis of concomitant functional near infrared spectroscopy and magnetic resonance imaging data

    NASA Astrophysics Data System (ADS)

    Schelkanova, Irina; Toronov, Vladislav

    2011-07-01

    Although near infrared spectroscopy (NIRS) is now widely used both in emerging clinical techniques and in cognitive neuroscience, the development of the apparatuses and signal processing methods for these applications is still a hot research topic. The main unresolved problem in functional NIRS is the separation of functional signals from the contaminations by systemic and local physiological fluctuations. This problem was approached by using various signal processing methods, including blind signal separation techniques. In particular, principal component analysis (PCA) and independent component analysis (ICA) were applied to the data acquired at the same wavelength and at multiple sites on the human or animal heads during functional activation. These signal processing procedures resulted in a number of principal or independent components that could be attributed to functional activity but their physiological meaning remained unknown. On the other hand, the best physiological specificity is provided by broadband NIRS. Also, a comparison with functional magnetic resonance imaging (fMRI) allows determining the spatial origin of fNIRS signals. In this study we applied PCA and ICA to broadband NIRS data to distill the components correlating with the breath hold activation paradigm and compared them with the simultaneously acquired fMRI signals. Breath holding was used because it generates blood carbon dioxide (CO2) which increases the blood-oxygen-level-dependent (BOLD) signal as CO2 acts as a cerebral vasodilator. Vasodilation causes increased cerebral blood flow which washes deoxyhaemoglobin out of the cerebral capillary bed thus increasing both the cerebral blood volume and oxygenation. Although the original signals were quite diverse, we found very few different components which corresponded to fMRI signals at different locations in the brain and to different physiological chromophores.

  16. A robust independent component analysis (ICA) model for functional magnetic resonance imaging (fMRI) data

    NASA Astrophysics Data System (ADS)

    Ao, Jingqi; Mitra, Sunanda; Liu, Zheng; Nutter, Brian

    2011-03-01

    The coupling of carefully designed experiments with proper analysis of functional magnetic resonance imaging (fMRI) data provides us with a powerful as well as noninvasive tool to help us understand cognitive processes associated with specific brain regions and hence could be used to detect abnormalities induced by a diseased state. The hypothesisdriven General Linear Model (GLM) and the data-driven Independent Component Analysis (ICA) model are the two most commonly used models for fMRI data analysis. A hybrid ICA-GLM model combines the two models to take advantages of benefits from both models to achieve more accurate mapping of the stimulus-induced activated brain regions. We propose a modified hybrid ICA-GLM model with probabilistic ICA that includes a noise model. In this modified hybrid model, a probabilistic principle component analysis (PPCA)-based component number estimation is used in the ICA stage to extract the intrinsic number of original time courses. In addition, frequency matching is introduced into the time course selection stage, along with temporal correlation, F-test based model fitting estimation, and time course combination, to produce a more accurate design matrix for GLM. A standard fMRI dataset is used to compare the results of applying GLM and the proposed hybrid ICA-GLM in generating activation maps.

  17. Correlation analysis between pulmonary function test parameters and CT image parameters of emphysema

    NASA Astrophysics Data System (ADS)

    Liu, Cheng-Pei; Li, Chia-Chen; Yu, Chong-Jen; Chang, Yeun-Chung; Wang, Cheng-Yi; Yu, Wen-Kuang; Chen, Chung-Ming

    2016-03-01

    Conventionally, diagnosis and severity classification of Chronic Obstructive Pulmonary Disease (COPD) are usually based on the pulmonary function tests (PFTs). To reduce the need of PFT for the diagnosis of COPD, this paper proposes a correlation model between the lung CT images and the crucial index of the PFT, FEV1/FVC, a severity index of COPD distinguishing a normal subject from a COPD patient. A new lung CT image index, Mirage Index (MI), has been developed to describe the severity of COPD primarily with emphysema disease. Unlike conventional Pixel Index (PI) which takes into account all voxels with HU values less than -950, the proposed approach modeled these voxels by different sizes of bullae balls and defines MI as a weighted sum of the percentages of the bullae balls of different size classes and locations in a lung. For evaluation of the efficacy of the proposed model, 45 emphysema subjects of different severity were involved in this study. In comparison with the conventional index, PI, the correlation between MI and FEV1/FVC is -0.75+/-0.08, which substantially outperforms the correlation between PI and FEV1/FVC, i.e., -0.63+/-0.11. Moreover, we have shown that the emphysematous lesion areas constituted by small bullae balls are basically irrelevant to FEV1/FVC. The statistical analysis and special case study results show that MI can offer better assessment in different analyses.

  18. Live imaging of muscles in Drosophila metamorphosis: Towards high-throughput gene identification and function analysis.

    PubMed

    Puah, Wee Choo; Wasser, Martin

    2016-03-01

    Time-lapse microscopy in developmental biology is an emerging tool for functional genomics. Phenotypic effects of gene perturbations can be studied non-invasively at multiple time points in chronological order. During metamorphosis of Drosophila melanogaster, time-lapse microscopy using fluorescent reporters allows visualization of alternative fates of larval muscles, which are a model for the study of genes related to muscle wasting. While doomed muscles enter hormone-induced programmed cell death, a smaller population of persistent muscles survives to adulthood and undergoes morphological remodeling that involves atrophy in early, and hypertrophy in late pupation. We developed a method that combines in vivo imaging, targeted gene perturbation and image analysis to identify and characterize genes involved in muscle development. Macrozoom microscopy helps to screen for interesting muscle phenotypes, while confocal microscopy in multiple locations over 4-5 days produces time-lapse images that are used to quantify changes in cell morphology. Performing a similar investigation using fixed pupal tissues would be too time-consuming and therefore impractical. We describe three applications of our pipeline. First, we show how quantitative microscopy can track and measure morphological changes of muscle throughout metamorphosis and analyze genes involved in atrophy. Second, our assay can help to identify genes that either promote or prevent histolysis of abdominal muscles. Third, we apply our approach to test new fluorescent proteins as live markers for muscle development. We describe mKO2 tagged Cysteine proteinase 1 (Cp1) and Troponin-I (TnI) as examples of proteins showing developmental changes in subcellular localization. Finally, we discuss strategies to improve throughput of our pipeline to permit genome-wide screens in the future.

  19. Imaging basal ganglia function

    PubMed Central

    BROOKS, DAVID J.

    2000-01-01

    In this review, the value of functional imaging for providing insight into the role of the basal ganglia in motor control is reviewed. Brain activation findings in normal subjects and Parkinson's disease patients are examined and evidence supporting the existence for functionally independent distributed basal ganglia-frontal loops is presented. It is argued that the basal ganglia probably act to focus and filter cortical output, optimising the running of motor programs. PMID:10923986

  20. Preserved pontine glucose metabolism in Alzheimer disease: A reference region for functional brain image (PET) analysis

    SciTech Connect

    Minoshima, Satoshi; Frey, K.A.; Foster, N.L.; Kuhl, D.W.

    1995-07-01

    Our goal was to examine regional preservation of energy metabolism in Alzheimer disease (AD) and to evaluate effects of PET data normalization to reference regions. Regional metabolic rates in the pons, thalamus, putamen, sensorimotor cortex, visual cortex, and cerebellum (reference regions) were determined stereotaxically and examined in 37 patients with probable AD and 22 normal controls based on quantitative {sup 18}FDG-PET measurements. Following normalization of metabolic rates of the parietotemporal association cortex and whole brain to each reference region, distinctions of the two groups were assessed. The pons showed the best preservation of glucose metabolism in AD. Other reference regions showed relatively preserved metabolism compared with the parietotemporal association cortex and whole brain, but had significant metabolic reduction. Data normalization to the pons not only enhanced statistical significance of metabolic reduction in the parietotemporal association cortex, but also preserved the presence of global cerebral metabolic reduction indicated in analysis of the quantitative data. Energy metabolism in the pons in probable AD is well preserved. The pons is a reliable reference for data normalization and will enhance diagnostic accuracy and efficiency of quantitative and nonquantitative functional brain imaging. 39 refs., 2 figs., 3 tabs.

  1. Development of a Multi-Centre Clinical Trial Data Archiving and Analysis Platform for Functional Imaging

    NASA Astrophysics Data System (ADS)

    Driscoll, Brandon; Jaffray, David; Coolens, Catherine

    2014-03-01

    Purpose: To provide clinicians & researchers participating in multi-centre clinical trials with a central repository for large volume dynamic imaging data as well as a set of tools for providing end-to-end testing and image analysis standards of practice. Methods: There are three main pieces to the data archiving and analysis system; the PACS server, the data analysis computer(s) and the high-speed networks that connect them. Each clinical trial is anonymized using a customizable anonymizer and is stored on a PACS only accessible by AE title access control. The remote analysis station consists of a single virtual machine per trial running on a powerful PC supporting multiple simultaneous instances. Imaging data management and analysis is performed within ClearCanvas Workstation® using custom designed plug-ins for kinetic modelling (The DCE-Tool®), quality assurance (The DCE-QA Tool) and RECIST. Results: A framework has been set up currently serving seven clinical trials spanning five hospitals with three more trials to be added over the next six months. After initial rapid image transfer (+ 2 MB/s), all data analysis is done server side making it robust and rapid. This has provided the ability to perform computationally expensive operations such as voxel-wise kinetic modelling on very large data archives (+20 GB/50k images/patient) remotely with minimal end-user hardware. Conclusions: This system is currently in its proof of concept stage but has been used successfully to send and analyze data from remote hospitals. Next steps will involve scaling up the system with a more powerful PACS and multiple high powered analysis machines as well as adding real-time review capabilities.

  2. Robust analysis of event-related functional magnetic resonance imaging data using independent component analysis

    NASA Astrophysics Data System (ADS)

    Kadah, Yasser M.

    2002-04-01

    We propose a technique that enables robust use of blind source separation techniques in fMRI data analysis. The fMRI temporal signal is modeled as the summation of the true activation signal, a physiological baseline fluctuation component, and a random noise component. A preprocessing denoising is used to reduce the dimensionality of the random noise component in this mixture before applying the principal/independent component analysis (PCA/ICA) methods. The set of denoised time courses from a localized region are utilized to capture the region-specific activation patterns. We show a significant improvement in the convergence properties of the ICA iteration when the denoised time courses are used. We also demonstrate the advantage of using ICA over PCA to separate components due to physiological signals from those corresponding to actual activation. Moreover, we propose the use of ICA to analyze the magnitude of the Fourier domain of the time courses. This allows ICA to group signals with similar patterns and different delays together, which makes the iteration even more efficient. The proposed technique is verified using computer simulations as well as actual data from a healthy human volunteer. The results confirm the robustness of the new strategy and demonstrate its value for clinical use.

  3. Prefrontal Structural and Functional Brain Imaging findings in Antisocial, Violent, and Psychopathic Individuals: A Meta-Analysis

    PubMed Central

    Yang, Yaling; Raine, Adrian

    2009-01-01

    Brain imaging studies suggest that antisocial and violent behavior is associated with structural and functional deficits in the prefrontal cortex, but there is heterogeneity in findings and it is unclear whether findings apply to psychopaths, non-violent offenders, community-based samples, and studies employing psychiatric controls. A meta-analysis was conducted on 43 structural and functional imaging studies and results show significantly reduced prefrontal structure and function in antisocial individuals. Effect sizes were significant for both structural and functional studies. With minor exceptions, no statistically significant moderating effects of sample characteristics and methodological variables were observed. Findings were localized to the right orbitofrontal cortex, right anterior cingulate cortex, and left dorsolateral prefrontal cortex. Findings confirm the replicability of prefrontal structural and functional impairments in antisocial populations and highlight the involvement of orbitofrontal, dorsolateral frontal, and anterior cingulate cortex in antisocial behavior. PMID:19833485

  4. Analysis of potassium and calcium imaging to assay the function of opioid receptors.

    PubMed

    Spahn, Viola; Nockemann, Dinah; Machelska, Halina

    2015-01-01

    As the activation of opioid receptors leads to the modulation of potassium and calcium channels, the ion imaging represents an attractive method to analyze the function of the receptors. Here, we describe the imaging of potassium using the FluxOR™ potassium ion channel assay, and of calcium using Fura-2 acetoxymethyl ester. Specifically, we (1) characterize the activation of the G-protein-coupled inwardly rectifying potassium 2 channel by agonists of μ- and δ-opioid receptors with the aid of the FluxOR™ assay in cultured mouse dorsal root ganglion neurons, and (2) describe calcium imaging protocols to measure capsaicin-induced transient receptor potential vanilloid 1 channel activity during opioid withdrawal in transfected human embryonic kidney 293 cells.

  5. A conditional Granger causality model approach for group analysis in functional magnetic resonance imaging.

    PubMed

    Zhou, Zhenyu; Wang, Xunheng; Klahr, Nelson J; Liu, Wei; Arias, Diana; Liu, Hongzhi; von Deneen, Karen M; Wen, Ying; Lu, Zuhong; Xu, Dongrong; Liu, Yijun

    2011-04-01

    Granger causality model (GCM) derived from multivariate vector autoregressive models of data has been employed to identify effective connectivity in the human brain with functional magnetic resonance imaging (fMRI) and to reveal complex temporal and spatial dynamics underlying a variety of cognitive processes. In the most recent fMRI effective connectivity measures, pair-wise GCM has commonly been applied based on single-voxel values or average values from special brain areas at the group level. Although a few novel conditional GCM methods have been proposed to quantify the connections between brain areas, our study is the first to propose a viable standardized approach for group analysis of fMRI data with GCM. To compare the effectiveness of our approach with traditional pair-wise GCM models, we applied a well-established conditional GCM to preselected time series of brain regions resulting from general linear model (GLM) and group spatial kernel independent component analysis of an fMRI data set in the temporal domain. Data sets consisting of one task-related and one resting-state fMRI were used to investigate connections among brain areas with the conditional GCM method. With the GLM-detected brain activation regions in the emotion-related cortex during the block design paradigm, the conditional GCM method was proposed to study the causality of the habituation between the left amygdala and pregenual cingulate cortex during emotion processing. For the resting-state data set, it is possible to calculate not only the effective connectivity between networks but also the heterogeneity within a single network. Our results have further shown a particular interacting pattern of default mode network that can be characterized as both afferent and efferent influences on the medial prefrontal cortex and posterior cingulate cortex. These results suggest that the conditional GCM approach based on a linear multivariate vector autoregressive model can achieve greater accuracy

  6. Analysis and measurement of the modulation transfer function of harmonic shear wave induced phase encoding imaging.

    PubMed

    McAleavey, Stephen A

    2014-05-01

    Shear wave induced phase encoding (SWIPE) imaging generates ultrasound backscatter images of tissue-like elastic materials by using traveling shear waves to encode the lateral position of the scatters in the phase of the received echo. In contrast to conventional ultrasound B-scan imaging, SWIPE offers the potential advantages of image formation without beam focusing or steering from a single transducer element, lateral resolution independent of aperture size, and the potential to achieve relatively high lateral resolution with low frequency ultrasound. Here a Fourier series description of the phase modulated echo signal is developed, demonstrating that echo harmonics at multiples of the shear wave frequency reveal target k-space data at identical multiples of the shear wavenumber. Modulation transfer functions of SWIPE imaging systems are calculated for maximum shear wave acceleration and maximum shear constraints, and compared with a conventionally focused aperture. The relative signal-to-noise ratio of the SWIPE method versus a conventionally focused aperture is found through these calculations. Reconstructions of wire targets in a gelatin phantom using 1 and 3.5 MHz ultrasound and a cylindrical shear wave source are presented, generated from the fundamental and second harmonic of the shear wave modulation frequency, demonstrating weak dependence of lateral resolution with ultrasound frequency.

  7. Four-dimensional functional analysis of left and right ventricles using MR images and active appearance models

    NASA Astrophysics Data System (ADS)

    Zhang, Honghai; Thomas, Matthew T.; Walker, Nicholas E.; Stolpen, Alan H.; Wahle, Andreas; Scholz, Thomas D.; Sonka, Milan

    2007-03-01

    Conventional analysis of cardiac ventricular function from magnetic resonance images is typically relying on short axis image information only. Usually, two cardiac phases of the cardiac cycle are analyzed- the end-diastole and end-systole. Unfortunately, the short axis ventricular coverage is incomplete and inconsistent due to the lack of image information about the ventricular apex and base. In routine clinical images, this information is only available in long axis image planes. Additionally, the standard ventricular function indices such as ejection fraction are only based on a limited temporal information and therefore do not fully describe the four-dimensional (4D, 3D+time) nature of the heart's motion. We report a novel approach in which the long and short axis image data are fused to correct for respiratory motion and form a spatio-temporal 4D data sequence with cubic voxels. To automatically segment left and right cardiac ventricles, a 4D active appearance model was built. Applying the method to cardiac segmentation of tetralogy of Fallot (TOF) and normal hearts, our method achieved mostly subvoxel signed surface positioning errors of 0.2+/-1.1 voxels for normal left ventricle, 0.6+/-1.5 voxels for normal right ventricle, 0.5+/-2.1 voxels for TOF left ventricle, and 1.3+/-2.6 voxels for TOF right ventricle. Using the computer segmentation results, the cardiac shape and motion indices and volume-time curves were derived as novel indices describing the ventricular function in 4D.

  8. Retinal Imaging and Image Analysis

    PubMed Central

    Abràmoff, Michael D.; Garvin, Mona K.; Sonka, Milan

    2011-01-01

    Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships. PMID:21743764

  9. Unsupervised learning toward brain imaging data analysis: cigarette craving and resistance related neuronal activations from functional magnetic resonance imaging data analysis

    NASA Astrophysics Data System (ADS)

    Kim, Dong-Youl; Lee, Jong-Hwan

    2014-05-01

    A data-driven unsupervised learning such as an independent component analysis was gainfully applied to bloodoxygenation- level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data compared to a model-based general linear model (GLM). This is due to an ability of this unsupervised learning method to extract a meaningful neuronal activity from BOLD signal that is a mixture of confounding non-neuronal artifacts such as head motions and physiological artifacts as well as neuronal signals. In this study, we support this claim by identifying neuronal underpinnings of cigarette craving and cigarette resistance. The fMRI data were acquired from heavy cigarette smokers (n = 14) while they alternatively watched images with and without cigarette smoking. During acquisition of two fMRI runs, they were asked to crave when they watched cigarette smoking images or to resist the urge to smoke. Data driven approaches of group independent component analysis (GICA) method based on temporal concatenation (TC) and TCGICA with an extension of iterative dual-regression (TC-GICA-iDR) were applied to the data. From the results, cigarette craving and cigarette resistance related neuronal activations were identified in the visual area and superior frontal areas, respectively with a greater statistical significance from the TC-GICA-iDR method than the TC-GICA method. On the other hand, the neuronal activity levels in many of these regions were not statistically different from the GLM method between the cigarette craving and cigarette resistance due to potentially aberrant BOLD signals.

  10. Pain and functional imaging.

    PubMed Central

    Ingvar, M

    1999-01-01

    Functional neuroimaging has fundamentally changed our knowledge about the cerebral representation of pain. For the first time it has been possible to delineate the functional anatomy of different aspects of pain in the medial and lateral pain systems in the brain. The rapid developments in imaging methods over the past years have led to a consensus in the description of the central pain responses between different studies and also to a definition of a central pain matrix with specialized subfunctions in man. In the near future we will see studies where a systems perspective allows for a better understanding of the regulatory mechanisms in the higher-order frontal and parietal cortices. Also, pending the development of experimental paradigms, the functional anatomy of the emotional aspects of pain will become better known. PMID:10466155

  11. Two-way principal component analysis for matrix-variate data, with an application to functional magnetic resonance imaging data.

    PubMed

    Huang, Lei; Reiss, Philip T; Xiao, Luo; Zipunnikov, Vadim; Lindquist, Martin A; Crainiceanu, Ciprian M

    2016-08-29

    SummaryMany modern neuroimaging studies acquire large spatial images of the brain observed sequentially over time. Such data are often stored in the forms of matrices. To model these matrix-variate data we introduce a class of separable processes using explicit latent process modeling. To account for the size and two-way structure of the data, we extend principal component analysis to achieve dimensionality reduction at the individual level. We introduce necessary identifiability conditions for each model and develop scalable estimation procedures. The method is motivated by and applied to a functional magnetic resonance imaging study designed to analyze the relationship between pain and brain activity.

  12. Introducing anisotropic Minkowski functionals and quantitative anisotropy measures for local structure analysis in biomedical imaging

    NASA Astrophysics Data System (ADS)

    Wismüller, Axel; De, Titas; Lochmüller, Eva; Eckstein, Felix; Nagarajan, Mahesh B.

    2013-03-01

    The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications.

  13. Radial distribution function imaging by STEM diffraction: Phase mapping and analysis of heterogeneous nanostructured glasses.

    PubMed

    Mu, Xiaoke; Wang, Di; Feng, Tao; Kübel, Christian

    2016-09-01

    Characterizing heterogeneous nanostructured amorphous materials is a challenging topic, because of difficulty to solve disordered atomic arrangement in nanometer scale. We developed a new transmission electron microscopy (TEM) method to enable phase analysis and mapping of heterogeneous amorphous structures. That is to combine scanning TEM (STEM) diffraction mapping, radial distribution function (RDF) analysis, and hyperspectral analysis. This method was applied to an amorphous zirconium oxide and zirconium iron multilayer system, and showed extreme sensitivity to small atomic packing variations. This approach helps to understand local structure variations in glassy composite materials and provides new insights to correlate structure and properties of glasses.

  14. A functional analysis of deception detection of a mock crime using infrared thermal imaging and the Concealed Information Test

    PubMed Central

    Park, Kevin K.; Suk, Hye Won; Hwang, Heungsun; Lee, Jang-Han

    2013-01-01

    The purpose of this study was to utilize thermal imaging and the Concealed Information Test to detect deception in participants who committed a mock crime. A functional analysis using a functional ANOVA and a functional discriminant analysis was conducted to decrease the variation in the physiological data collected through the thermal imaging camera. Participants chose between a non-crime mission (Innocent Condition: IC), or a mock crime (Guilty Condition: GC) of stealing a wallet in a computer lab. Temperature in the periorbital region of the face was measured while questioning participants regarding mock crime details. Results revealed that the GC showed significantly higher temperatures when responding to crime relevant items compared to irrelevant items, while the IC did not. The functional ANOVA supported the initial results that facial temperatures of the GC elevated when responding to crime relevant items, demonstrating an interaction between group (guilty/innocent) and relevance (relevant/irrelevant). The functional discriminant analysis revealed that answering crime relevant items can be used to discriminate guilty from innocent participants. These results suggest that measuring facial temperatures in the periorbital region while conducting the Concealed Information Test is able to differentiate the GC from the IC. PMID:23470924

  15. A functional analysis of deception detection of a mock crime using infrared thermal imaging and the Concealed Information Test.

    PubMed

    Park, Kevin K; Suk, Hye Won; Hwang, Heungsun; Lee, Jang-Han

    2013-01-01

    The purpose of this study was to utilize thermal imaging and the Concealed Information Test to detect deception in participants who committed a mock crime. A functional analysis using a functional ANOVA and a functional discriminant analysis was conducted to decrease the variation in the physiological data collected through the thermal imaging camera. Participants chose between a non-crime mission (Innocent Condition: IC), or a mock crime (Guilty Condition: GC) of stealing a wallet in a computer lab. Temperature in the periorbital region of the face was measured while questioning participants regarding mock crime details. Results revealed that the GC showed significantly higher temperatures when responding to crime relevant items compared to irrelevant items, while the IC did not. The functional ANOVA supported the initial results that facial temperatures of the GC elevated when responding to crime relevant items, demonstrating an interaction between group (guilty/innocent) and relevance (relevant/irrelevant). The functional discriminant analysis revealed that answering crime relevant items can be used to discriminate guilty from innocent participants. These results suggest that measuring facial temperatures in the periorbital region while conducting the Concealed Information Test is able to differentiate the GC from the IC.

  16. Evidence for correlations between distant intentionality and brain function in recipients: a functional magnetic resonance imaging analysis.

    PubMed

    Achterberg, Jeanne; Cooke, Karin; Richards, Todd; Standish, Leanna J; Kozak, Leila; Lake, James

    2005-12-01

    This study, using functional magnetic resonance imaging (fMRI) technology, demonstrated that distant intentionality (DI), defined as sending thoughts at a distance, is correlated with an activation of certain brain functions in the recipients. Eleven healers who espoused some form for connecting or healing at a distance were recruited from the island of Hawaii. Each healer selected a person with whom they felt a special connection as a recipient for DI. The recipient was placed in the MRI scanner and isolated from all forms of sensory contact from the healer. The healers sent forms of DI that related to their own healing practices at random 2-minute intervals that were unknown to the recipient. Significant differences between experimental (send) and control (no send) procedures were found (p = 0.000127). Areas activated during the experimental procedures included the anterior and middle cingulate area, precuneus, and frontal area. It was concluded that instructions to a healer to make an intentional connection with a sensory isolated person can be correlated to changes in brain function of that individual.

  17. Functional magnetic resonance imaging.

    PubMed

    Buchbinder, Bradley R

    2016-01-01

    Functional magnetic resonance imaging (fMRI) maps the spatiotemporal distribution of neural activity in the brain under varying cognitive conditions. Since its inception in 1991, blood oxygen level-dependent (BOLD) fMRI has rapidly become a vital methodology in basic and applied neuroscience research. In the clinical realm, it has become an established tool for presurgical functional brain mapping. This chapter has three principal aims. First, we review key physiologic, biophysical, and methodologic principles that underlie BOLD fMRI, regardless of its particular area of application. These principles inform a nuanced interpretation of the BOLD fMRI signal, along with its neurophysiologic significance and pitfalls. Second, we illustrate the clinical application of task-based fMRI to presurgical motor, language, and memory mapping in patients with lesions near eloquent brain areas. Integration of BOLD fMRI and diffusion tensor white-matter tractography provides a road map for presurgical planning and intraoperative navigation that helps to maximize the extent of lesion resection while minimizing the risk of postoperative neurologic deficits. Finally, we highlight several basic principles of resting-state fMRI and its emerging translational clinical applications. Resting-state fMRI represents an important paradigm shift, focusing attention on functional connectivity within intrinsic cognitive networks.

  18. Functionalized Nanolipobubbles Embedded Within a Nanocomposite Hydrogel: a Molecular Bio-imaging and Biomechanical Analysis of the System.

    PubMed

    Mufamadi, Maluta S; Choonara, Yahya E; Kumar, Pradeep; du Toit, Lisa C; Modi, Girish; Naidoo, Dinesh; Iyuke, Sunny E; Pillay, Viness

    2016-05-17

    The purpose of this study was to explore the use of molecular bio-imaging systems and biomechanical dynamics to elucidate the fate of a nanocomposite hydrogel system prepared by merging FITC-labeled nanolipobubbles within a cross-linked hydrogel network. The nanocomposite hydrogel system was characterized by size distribution analysis and zeta potential as well as shears thinning behavior, elastic modulus (G'), viscous loss moduli (G"), TEM, and FTIR. In addition, molecular bio-imaging via Vevo ultrasound and Cell-viZio techniques evaluated the stability and distribution of the nanolipobubbles within the cross-linked hydrogel. FITC-labeled and functionalized nanolipobubbles had particle sizes between 135 and 158 nm (PdI = 0.129 and 0.190) and a zeta potential of -34 mV. TEM and ultrasound imaging revealed the uniformity and dimensional stability of the functionalized nanolipobubbles pre- and post-embedment into the cross-linked hydrogel. Biomechanical characterization of the hydrogel by shear thinning behavior was governed by the polymer concentration and the cross-linker, glutaraldehyde. Ultrasound analysis and Cell-viZio bio-imaging were highly suitable to visualize the fluorescent image-guided nanolipobubbles and their morphology post-embedment into the hydrogel to form the NanoComposite system. Since the nanocomposite is intended for targeted treatment of neurodegenerative disorders, the distribution of the functionalized nanolipobubbles into PC12 neuronal cells was also ascertained via confocal microscopy. Results demonstrated effective release and localization of the nanolipobubbles within PC12 neuronal cells. The molecular structure of the synthetic surface peptide remained intact for an extended period to ensure potency for targeted delivery from the hydrogel ex vivo. These findings provide further insight into the properties of nanocomposite hydrogels for specialized drug delivery.

  19. Fractionating theory of mind: a meta-analysis of functional brain imaging studies.

    PubMed

    Schurz, Matthias; Radua, Joaquim; Aichhorn, Markus; Richlan, Fabio; Perner, Josef

    2014-05-01

    We meta-analyzed imaging studies on theory of mind and formed individual task groups based on stimuli and instructions. Overlap in brain activation between all task groups was found in the mPFC and in the bilateral posterior TPJ. This supports the idea of a core network for theory of mind that is activated whenever we are reasoning about mental states, irrespective of the task- and stimulus-formats (Mar, 2011). In addition, we found a number of task-related activation differences surrounding this core-network. ROI based analyses show that areas in the TPJ, the mPFC, the precuneus, the temporal lobes and the inferior frontal gyri have distinct profiles of task-related activation. Functional accounts of these areas are reviewed and discussed with respect to our findings.

  20. Independent component analysis of localized resting-state functional magnetic resonance imaging reveals specific motor subnetworks.

    PubMed

    Sohn, William Seunghyun; Yoo, Kwangsun; Jeong, Yong

    2012-01-01

    Recent studies have shown that blood oxygen level-dependent low-frequency (<0.1 Hz) fluctuations (LFFs) during a resting-state exhibit a high degree of correlation with other regions that share cognitive function. Initial studies of resting-state network mapping have focused primarily on major networks such as the default mode network, primary motor, somatosensory, visual, and auditory networks. However, more specific or subnetworks, including those associated with specific motor functions, have yet to be properly addressed. We performed independent component analysis (ICA) in a specific target region of the brain, a process we name, "localized ICA." We demonstrated that when ICA is applied to localized fMRI data, it can be used to distinguish resting-state LFFs associated with specific motor functions (e.g., finger tapping, foot movement, or bilateral lip pulsing) in the primary motor cortex. These ICA components generated from localized data can then be used as functional regions of interest to map whole-brain connectivity. In addition, this method can be used to visualize inter-regional connectivity by expanding the localized region and identifying components that show connectivity between the two regions.

  1. Fixation based event-related fmri analysis: using eye fixations as events in functional magnetic resonance imaging to reveal cortical processing during the free exploration of visual images.

    PubMed

    Marsman, Jan Bernard C; Renken, Remco; Velichkovsky, Boris M; Hooymans, Johanna M M; Cornelissen, Frans W

    2012-02-01

    Eye movements, comprising predominantly fixations and saccades, are known to reveal information about perception and cognition, and they provide an explicit measure of attention. Nevertheless, fixations have not been considered as events in the analyses of data obtained during functional magnetic resonance imaging (fMRI) experiments. Most likely, this is due to their brevity and statistical properties. Despite these limitations, we used fixations as events to model brain activation in a free viewing experiment with standard fMRI scanning parameters. First, we found that fixations on different objects in different task contexts resulted in distinct cortical patterns of activation. Second, using multivariate pattern analysis, we showed that the BOLD signal revealed meaningful information about the task context of individual fixations and about the object being inspected during these fixations. We conclude that fixation-based event-related (FIBER) fMRI analysis creates new pathways for studying human brain function by enabling researchers to explore natural viewing behavior.

  2. Fast fluorescent imaging-based Thai jasmine rice identification with polynomial fitting function and neural network analysis.

    PubMed

    Suwansukho, Kajpanya; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

    2014-04-01

    With our single-wavelength spectral-imaging-based Thai jasmine rice identification system, we emphasize here that a combination of an appropriate polynomial fitting function on the determined chain code and a well-trained neural network configuration is highly sufficient in achieving a low false acceptance rate (FAR) and a low false rejection rate (FRR). Experimental demonstration shows promising results in identifying our desired Thai jasmine rice from six unwanted rice varieties with FAR and FRR values of 6.2% and 7.1%, respectively. Additional key performances include a much faster identification time of 30.5 s, chemical-free analysis, robustness, and adaptive learning.

  3. Brain imaging and brain function

    SciTech Connect

    Sokoloff, L.

    1985-01-01

    This book is a survey of the applications of imaging studies of regional cerebral blood flow and metabolism to the investigation of neurological and psychiatric disorders. Contributors review imaging techniques and strategies for measuring regional cerebral blood flow and metabolism, for mapping functional neural systems, and for imaging normal brain functions. They then examine the applications of brain imaging techniques to the study of such neurological and psychiatric disorders as: cerebral ischemia; convulsive disorders; cerebral tumors; Huntington's disease; Alzheimer's disease; depression and other mood disorders. A state-of-the-art report on magnetic resonance imaging of the brain and central nervous system rounds out the book's coverage.

  4. [Therapeutic function of images].

    PubMed

    Aisenson Kogan, A

    1986-03-01

    The aim here searched is to explore the reasons why some systems of psychotherapy choose images as a means for attaining the cure. In one case at least (Roger Desoille's "awake dream"--the production and interpretation of images constitutes the basic procedure. The question arises: which sort of images? It is not dealt here with the oniric ones, but with the consciously created and must be called symbolic images. Almost every image that appears during a therapy session reveals a symbolic nature, but the very concept of symbol is not free from ambiguity some positions originated in different areas of investigation are mentioned, ending with a description of the traits that, according to the writer, bestow a symbolic character to images. These can be sensible ones or linguistic, as they appear in literary productions. Their importance as a factor of the psychotherapeutic change resides in the fact that symbolic images thus created are felt as not real events and at the same time containing subjective meaning. These two traits combine to lessen the anxiety before the confrontation with one's own impulses or feelings and at same time to stimulate towards new ways of behavior, until then desired -perhaps unconsciously- but too frightening to materialize in the real world.

  5. Image Analysis and Modeling

    DTIC Science & Technology

    1976-03-01

    This report summarizes the results of the research program on Image Analysis and Modeling supported by the Defense Advanced Research Projects Agency...The objective is to achieve a better understanding of image structure and to use this knowledge to develop improved image models for use in image ... analysis and processing tasks such as information extraction, image enhancement and restoration, and coding. The ultimate objective of this research is

  6. Brain Imaging Analysis

    PubMed Central

    BOWMAN, F. DUBOIS

    2014-01-01

    The increasing availability of brain imaging technologies has led to intense neuroscientific inquiry into the human brain. Studies often investigate brain function related to emotion, cognition, language, memory, and numerous other externally induced stimuli as well as resting-state brain function. Studies also use brain imaging in an attempt to determine the functional or structural basis for psychiatric or neurological disorders and, with respect to brain function, to further examine the responses of these disorders to treatment. Neuroimaging is a highly interdisciplinary field, and statistics plays a critical role in establishing rigorous methods to extract information and to quantify evidence for formal inferences. Neuroimaging data present numerous challenges for statistical analysis, including the vast amounts of data collected from each individual and the complex temporal and spatial dependence present. We briefly provide background on various types of neuroimaging data and analysis objectives that are commonly targeted in the field. We present a survey of existing methods targeting these objectives and identify particular areas offering opportunities for future statistical contribution. PMID:25309940

  7. 3D imaging of the Corinth rift from a new passive seismic tomography and receiver function analysis

    NASA Astrophysics Data System (ADS)

    Godano, Maxime; Gesret, Alexandrine; Noble, Mark; Lyon-Caen, Hélène; Gautier, Stéphanie; Deschamps, Anne

    2016-04-01

    model and earthquake location. In addition to the tomographic imaging, we perform a preliminary receiver function analysis of teleseismic data recorded by the broadband stations of the CRL network. The RF analysis should provide the interface depths beneath seismometers and increase the imaging resolution of the upper crustal structures provided by the 3D tomography. In this first attempt, we adjust the 1D velocity model that produces a synthetic RF as similar as possible to the observed RF for a subset of data. We compare the identified interfaces with structures imaged by the tomography.

  8. Characterizing nonlinear relationships in functional imaging data using eigenspace maximal information canonical correlation analysis (emiCCA).

    PubMed

    Dong, Li; Zhang, Yangsong; Zhang, Rui; Zhang, Xingxing; Gong, Diankun; Valdes-Sosa, Pedro A; Xu, Peng; Luo, Cheng; Yao, Dezhong

    2015-04-01

    Many important problems in the analysis of neuroimages can be formulated as discovering the relationship between two sets of variables, a task for which linear techniques such as canonical correlation analysis (CCA) have been commonly used. However, to further explore potential nonlinear processes that might co-exist with linear ones in brain function, a more flexible method is required. Here, we propose a new unsupervised and data-driven method, termed the eigenspace maximal information canonical correlation analysis (emiCCA), which is capable of automatically capturing the linear and/or nonlinear relationships between various data sets. A simulation confirmed the superior performance of emiCCA in comparison with linear CCA and kernel CCA (a nonlinear version of CCA). An emiCCA framework for functional magnetic resonance imaging (fMRI) data processing was designed and applied to data from a real motor execution fMRI experiment. This analysis uncovered one linear (in primary motor cortex) and a few nonlinear networks (e.g., in the supplementary motor area, bilateral insula, and cerebellum). This suggests that these various task-related brain areas are part of networks that also contribute to the execution of movements of the hand. These results suggest that emiCCA is a promising technique for exploring various data.

  9. Functional Imaging: CT and MRI

    PubMed Central

    van Beek, Edwin JR; Hoffman, Eric A

    2008-01-01

    Synopsis Numerous imaging techniques permit evaluation of regional pulmonary function. Contrast-enhanced CT methods now allow assessment of vasculature and lung perfusion. Techniques using spirometric controlled MDCT allow for quantification of presence and distribution of parenchymal and airway pathology, Xenon gas can be employed to assess regional ventilation of the lungs and rapid bolus injections of iodinated contrast agent can provide quantitative measure of regional parenchymal perfusion. Advances in magnetic resonance imaging (MRI) of the lung include gadolinium-enhanced perfusion imaging and hyperpolarized helium imaging, which can allow imaging of pulmonary ventilation and .measurement of the size of emphysematous spaces. PMID:18267192

  10. Rostral medial prefrontal dysfunctions and consummatory pleasure in schizophrenia: a meta-analysis of functional imaging studies.

    PubMed

    Yan, Chao; Yang, Tammy; Yu, Qi-Jing; Jin, Zhen; Cheung, Eric F C; Liu, Xun; Chan, Raymond C K

    2015-03-30

    A large number of imaging studies have examined the neural correlates of consummatory pleasure and anticipatory pleasure in schizophrenia, but the brain regions where schizophrenia patients consistently demonstrate dysfunctions remain unclear. We performed a series of meta-analyses on imaging studies to delineate the regions associated with consummatory and anticipatory pleasure dysfunctions in schizophrenia. Nineteen functional magnetic resonance imaging or positron emission tomography studies using whole brain analysis were identified through a literature search (PubMed and EBSCO; January 1990-February 2014). Activation likelihood estimation was performed using the GingerALE software. The clusters identified were obtained after controlling for the false discovery rate at p<0.05 and applying a minimum cluster size of 200 mm(3). It was found that schizophrenia patients exhibited decreased activation mainly in the rostral medial prefrontal cortex (rmPFC), the right parahippocampus/amygala, and other limbic regions (e.g., the subgenual anterior cingulate cortex, the putamen, and the medial globus pallidus) when consummating pleasure. Task instructions (feeling vs. stimuli) were differentially related to medial prefrontal dysfunction in schizophrenia. When patients anticipated pleasure, reduced activation in the left putamen was observed, despite the limited number of studies. Our findings suggest that the medial prefrontal cortex and limbic regions may play an important role in neural dysfunction underlying deficits in consummatory pleasure in schizophrenia.

  11. Independent component analysis for the detection of in vivo intrinsic signals from an optical imager of retinal function

    NASA Astrophysics Data System (ADS)

    Barriga, Eduardo S.; Pattichis, Marios; Abramoff, Michael; T'so, Dan; Kwon, Young; Kardon, Randy; Soliz, Peter

    2007-02-01

    To overcome the difficulty in detection of loss of retinal activity, a functional-Retinal Imaging Device (f-RID) was developed. The device, which is based on a modified fundus camera, seeks to detect changes in optical signals that reflect functional changes in the retina. Measured changes in reflectance in response to the visual stimulus are on the order of 0.1% to 1% of the total reflected intensity level, which makes the functional signal difficult to detect by standard methods because it is masked by other physiological signals and by noise. In this paper, we present a new Independent Component Analysis (ICA) algorithm used to analyze the video sequences from a set of experiments with different patterned stimuli from cats and humans. The ICA algorithm with priors (ICA-P) uses information about the stimulation paradigms to increase the signal detection thresholds when compared to traditional ICA algorithms. The results of the analysis show that we can detect signal levels as low as 0.01% of the total reflected intensity. Also, improvement of up to 30dB in signal detection over traditional ICA algorithms is achieved. The study found that in more than 80% of the in-vivo experiments the patterned stimuli effects on the retina can be detected and extracted.

  12. Image-analysis library

    NASA Technical Reports Server (NTRS)

    1980-01-01

    MATHPAC image-analysis library is collection of general-purpose mathematical and statistical routines and special-purpose data-analysis and pattern-recognition routines for image analysis. MATHPAC library consists of Linear Algebra, Optimization, Statistical-Summary, Densities and Distribution, Regression, and Statistical-Test packages.

  13. Quantitative imaging of lymph function.

    PubMed

    Sharma, Ruchi; Wang, Wei; Rasmussen, John C; Joshi, Amit; Houston, Jessica P; Adams, Kristen E; Cameron, Arlin; Ke, Shi; Kwon, Sunkuk; Mawad, Michel E; Sevick-Muraca, Eva M

    2007-06-01

    Functional lymphatic imaging was demonstrated in the abdomen and anterior hindlimb of anesthetized, intact Yorkshire swine by using near-infrared (NIR) fluorescence imaging following intradermal administration of 100-200 microl of 32 microM indocyanine green (ICG) and 64 microM hyaluronan NIR imaging conjugate to target the lymph vascular endothelial receptor (LYVE)-1 on the lymph endothelium. NIR fluorescence imaging employed illumination of 780 nm excitation light ( approximately 2 mW/cm(2)) and collection of 830 nm fluorescence generated from the imaging agents. Our results show the ability to image the immediate trafficking of ICG from the plexus, through the vessels and lymphangions, and to the superficial mammary, subiliac, and middle iliac lymph nodes, which were located as deep as 3 cm beneath the tissue surface. "Packets" of ICG-transited lymph vessels of 2-16 cm length propelled at frequencies of 0.5-3.3 pulses/min and velocities of 0.23-0.75 cm/s. Lymph propulsion was independent of respiration rate. In the case of the hyaluronan imaging agent, lymph propulsion was absent as the dye progressed immediately through the plexus and stained the lymph vessels and nodes. Lymph imaging required 5.0 and 11.9 microg of ICG and hyaluronan conjugate, respectively. Our results suggest that microgram quantities of NIR optical imaging agents and their conjugates have a potential to image lymph function in patients suffering from lymph-related disorders.

  14. A tool for classifying individuals with chronic back pain: using multivariate pattern analysis with functional magnetic resonance imaging data.

    PubMed

    Callan, Daniel; Mills, Lloyd; Nott, Connie; England, Robert; England, Shaun

    2014-01-01

    Chronic pain is one of the most prevalent health problems in the world today, yet neurological markers, critical to diagnosis of chronic pain, are still largely unknown. The ability to objectively identify individuals with chronic pain using functional magnetic resonance imaging (fMRI) data is important for the advancement of diagnosis, treatment, and theoretical knowledge of brain processes associated with chronic pain. The purpose of our research is to investigate specific neurological markers that could be used to diagnose individuals experiencing chronic pain by using multivariate pattern analysis with fMRI data. We hypothesize that individuals with chronic pain have different patterns of brain activity in response to induced pain. This pattern can be used to classify the presence or absence of chronic pain. The fMRI experiment consisted of alternating 14 seconds of painful electric stimulation (applied to the lower back) with 14 seconds of rest. We analyzed contrast fMRI images in stimulation versus rest in pain-related brain regions to distinguish between the groups of participants: 1) chronic pain and 2) normal controls. We employed supervised machine learning techniques, specifically sparse logistic regression, to train a classifier based on these contrast images using a leave-one-out cross-validation procedure. We correctly classified 92.3% of the chronic pain group (N = 13) and 92.3% of the normal control group (N = 13) by recognizing multivariate patterns of activity in the somatosensory and inferior parietal cortex. This technique demonstrates that differences in the pattern of brain activity to induced pain can be used as a neurological marker to distinguish between individuals with and without chronic pain. Medical, legal and business professionals have recognized the importance of this research topic and of developing objective measures of chronic pain. This method of data analysis was very successful in correctly classifying each of the two

  15. Molecular and functional imaging of internet addiction.

    PubMed

    Zhu, Yunqi; Zhang, Hong; Tian, Mei

    2015-01-01

    Maladaptive use of the Internet results in Internet addiction (IA), which is associated with various negative consequences. Molecular and functional imaging techniques have been increasingly used for analysis of neurobiological changes and neurochemical correlates of IA. This review summarizes molecular and functional imaging findings on neurobiological mechanisms of IA, focusing on magnetic resonance imaging (MRI) and nuclear imaging modalities including positron emission tomography (PET) and single photon emission computed tomography (SPECT). MRI studies demonstrate that structural changes in frontal cortex are associated with functional abnormalities in Internet addicted subjects. Nuclear imaging findings indicate that IA is associated with dysfunction of the brain dopaminergic systems. Abnormal dopamine regulation of the prefrontal cortex (PFC) could underlie the enhanced motivational value and uncontrolled behavior over Internet overuse in addicted subjects. Further investigations are needed to determine specific changes in the Internet addictive brain, as well as their implications for behavior and cognition.

  16. Basics of image analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hyperspectral imaging technology has emerged as a powerful tool for quality and safety inspection of food and agricultural products and in precision agriculture over the past decade. Image analysis is a critical step in implementing hyperspectral imaging technology; it is aimed to improve the qualit...

  17. The prefrontal dysfunction in individuals with Internet gaming disorder: a meta-analysis of functional magnetic resonance imaging studies.

    PubMed

    Meng, Yajing; Deng, Wei; Wang, Huiyao; Guo, Wanjun; Li, Tao

    2015-07-01

    With the advancement in high-resolution magnetic resonance imaging (MRI) technology and automated analysis, studies on functional MRI (fMRI) made it possible to identify the functional activity of brain in vivo in individuals with Internet gaming disorder (IGD), and to explore the underpinning neuroscience basis of IGD. Yet, no available literature has systemically reviewed the fMRI studies of IGD using meta-analyses. This study reviewed 61 candidate articles and finally selected 10 qualified voxel-wise whole-brain analysis studies for performing a comprehensive series of meta-analyses employing effect size signed differential mapping approach. Compared with healthy controls, subjects with IGD showed a significant activation in the bilateral medial frontal gyrus (MFG) and the left cingulate gyrus, as well as the left medial temporal gyrus and fusiform gyrus. Furthermore, the on-line time of IGD subjects was positively correlated with activations in the left MFG and the right cingulated gyrus. These findings implicate the important role of dysfunctional prefrontal lobe in the neuropathological mechanism of IGD. Considering the overlapped role of prefrontal lobe in the reward and self-regulatory system, our results provided supportive evidence for the reclassification of IGD as a behavioural addiction.

  18. Do women really have more bilateral language representation than men? A meta-analysis of functional imaging studies.

    PubMed

    Sommer, Iris E C; Aleman, André; Bouma, Anke; Kahn, René S

    2004-08-01

    Sex differences in cognition are consistently reported, men excelling in most visuospatial tasks and women in certain verbal tasks. It has been hypothesized that these sex differences in cognition results from a more bilateral pattern of language representation in women than in men. This bilateral pattern of language representation in women is thought to interfere with visuospatial functions in the right hemisphere. To test whether language representation is indeed more bilateral in the female than in the male brain, a meta-analysis was performed on studies that assessed language activity with functional imaging in healthy men and women. Effect sizes were weighted for sample size and the meta-analytic method was applied to obtain a combined effect size. Fourteen studies were included, providing data on 377 men and 442 women. Meta-analysis yielded a mean weighted effect d of 0.21 with a 95% confidence interval of -0.05 to 0.48, indicating no significant difference in language lateralization between men and women. This implies that the putative sex difference in language lateralization may be absent at the population level, or may be observed only with some, as yet not defined, language tasks. It is therefore not likely that differences in language lateralization underlie the general sex differences in cognitive performance, and the neuronal basis for these cognitive sex differences remains elusive.

  19. EMOTIONS AND IMAGES IN LANGUAGE--A LEARNING ANALYSIS OF THEIR ACQUISITION AND FUNCTION.

    ERIC Educational Resources Information Center

    STAATS, ARTHUR W.

    THIS ARTICLE PRESENTED THEORETICAL AND EXPERIMENTAL ANALYSES CONCERNING IMPORTANT ASPECTS OF LANGUAGE. IT WAS SUGGESTED THAT A LEARNING THEORY WHICH INEGRATES INSTRUMENTAL AND CLASSICAL CONDITIONING, CUTTING ACROSS THEORETICAL LINES, COULD SERVE AS THE BASIS FOR A COMPREHENSIVE THEORY OF LANGUAGE ACQUISITION AND FUNCTION. THE PAPER ILLUSTRATED THE…

  20. Comparing Analysis Methods in Functional Calcium Imaging of the Insect Brain.

    PubMed

    Balkenius, Anna; Johansson, Anders J; Balkenius, Christian

    2015-01-01

    We investigate four different methods for background estimation in calcium imaging of the insect brain and evaluate their performance on six data sets consisting of data recorded from two sites in two species of moths. The calcium fluorescence decay curve outside the potential response is estimated using either a low-pass filter or constant, linear or polynomial regression, and is subsequently used to calculate the magnitude, latency and duration of the response. The magnitude and variance of the responses that are obtained by the different methods are compared, and, by computing the receiver operating characteristics of a classifier based on response magnitude, we evaluate the ability of each method to detect the stimulus type and conclude that a polynomial approximation of the background gives the overall best result.

  1. Echocardiographic analysis of the left ventricular function in young athletes: a focus on speckle tracking imaging

    PubMed Central

    Charfeddine, Salma; Mallek, Souad; Triki, Faten; Hammami, Rania; Abid, Dorra; Abid, Leila; Kammoun, Samir

    2016-01-01

    Introduction The objectives were to assess the left ventricular (LV) structure and function in regularly trained young athletes, using 2 D conventional echocardiographic (echo) methods and speckle tracking echocardiography (STE). An observational cross-sectional study. Methods Thirty-three footballers and 20 healthy untrained subjects were included in the study. The systolic and diastolic LV functions were evaluated by 2D conventional echo parameters, Doppler method and STE. Results All the found values were within the normal range. The LV End Diastolic Diameter (LVED 37.24±2.08 mm/m2) and the LV Mass index (LVMi 97.93±15.58 g/m2) were significantly higher in young athletes as compared with controls. There was no difference regarding the LV systolic function assessed by conventional echo parameters in the 2 study groups. Regarding the diastolic function, the transmitral inflow velocities ratio was significantly higher in athletes (E/A = 2.10±0.49 versus 1.64±0.26, p< 0.001) but there was no difference in the filling pressure in the 2 groups. The STE demonstrated a different pattern of LV deformation in the different groups. A significant lower LV global longitudinal strain (GLS -20.68±2.05 versus -22.99±2.32 %, p<0.001) and higher radial and circumferential strains have been found in the young athletes as compared with controls. A significant relationship between the GLS values and LVED (r= 0.299, p = 0.03) and LVMi was also reported in athletes. Conclusion While conventional morphological and functional echocardiographic parameters failed to distinguish the adaptations in the athlete’s heart, deformation parameters showed a different pattern of LV mechanics in young footballers versus controls. PMID:28292133

  2. Integral equation analysis and optimization of 2D layered nanolithography masks by complex images Green's function technique in TM polarization.

    PubMed

    Haghtalab, Mohammad; Faraji-Dana, Reza

    2012-05-01

    Analysis and optimization of diffraction effects in nanolithography through multilayered media with a fast and accurate field-theoretical approach is presented. The scattered field through an arbitrary two-dimensional (2D) mask pattern in multilayered media illuminated by a TM-polarized incident wave is determined by using an electric field integral equation formulation. In this formulation the electric field is represented in terms of complex images Green's functions. The method of moments is then employed to solve the resulting integral equation. In this way an accurate and computationally efficient approximate method is achieved. The accuracy of the proposed method is vindicated through comparison with direct numerical integration results. Moreover, the comparison is made between the results obtained by the proposed method and those obtained by the full-wave finite-element method. The ray tracing method is combined with the proposed method to describe the imaging process in the lithography. The simulated annealing algorithm is then employed to solve the inverse problem, i.e., to design an optimized mask pattern to improve the resolution. Two binary mask patterns under normal incident coherent illumination are designed by this method, where it is shown that the subresolution features improve the critical dimension significantly.

  3. Adaptive Denoising Technique for Robust Analysis of Functional Magnetic Resonance Imaging Data

    DTIC Science & Technology

    2007-11-02

    or receive while t fMRI o versatil of epoc method ER-fM to the studies comes intra-su functioADAPTIVE DENOISING TECHNIQUE FOR ROBUST ANALYSIS OF...supported in part by the Center for Advanced Software and Biomedical Engineering Consultations (CASBEC), Cairo University, and IBE Technologies , Egypt

  4. Single-Molecule Imaging and Functional Analysis of Als Adhesins and Mannans during Candida albicans Morphogenesis

    PubMed Central

    Beaussart, Audrey; Alsteens, David; El-Kirat-Chatel, Sofiane; Lipke, Peter N.; Kucharíková, Sona; Van Dijck, Patrick; Dufrêne, Yves F.

    2012-01-01

    Cellular morphogenesis in the fungal pathogen Candida albicans is associated with changes in cell wall composition that play important roles in biofilm formation and immune responses. Yet, how fungal morphogenesis modulates the biophysical properties and interactions of the cell surface molecules is poorly understood, mainly owing to the paucity of high-resolution imaging techniques. Here, we use single-molecule atomic force microscopy to localize and analyze the key components of the surface of living C. albicans cells during morphogenesis. We show that the yeast-to-hypha transition leads to a major increase in the distribution, adhesion, unfolding and extension of Als adhesins and their associated mannans on the cell surface. We also find that morphogenesis dramatically increases cell surface hydrophobicity. These molecular changes are critical for microbe-host interactions, including adhesion, colonization, and biofilm formation. The single-molecule experiments presented here offer promising prospects for understanding how microbial pathogens use cell surface molecules to modulate biofilm and immune interactions. PMID:23145462

  5. 4-D Cardiac MR Image Analysis: Left and Right Ventricular Morphology and Function

    PubMed Central

    Wahle, Andreas; Johnson, Ryan K.; Scholz, Thomas D.; Sonka, Milan

    2010-01-01

    In this study, a combination of active shape model (ASM) and active appearance model (AAM) was used to segment the left and right ventricles of normal and Tetralogy of Fallot (TOF) hearts on 4-D (3-D+time) MR images. For each ventricle, a 4-D model was first used to achieve robust preliminary segmentation on all cardiac phases simultaneously and a 3-D model was then applied to each phase to improve local accuracy while maintaining the overall robustness of the 4-D segmentation. On 25 normal and 25 TOF hearts, in comparison to the expert traced independent standard, our comprehensive performance assessment showed subvoxel segmentation accuracy, high overlap ratios, good ventricular volume correlations, and small percent volume differences. Following 4-D segmentation, novel quantitative shape and motion features were extracted using shape information, volume-time and dV/dt curves, analyzed and used for disease status classification. Automated discrimination between normal/TOF subjects achieved 90%–100% sensitivity and specificity. The features obtained from TOF hearts show higher variability compared to normal subjects, suggesting their potential use as disease progression indicators. The abnormal shape and motion variations of the TOF hearts were accurately captured by both the segmentation and feature characterization. PMID:19709962

  6. Open framework for management and processing of multi-modality and multidimensional imaging data for analysis and modelling muscular function

    NASA Astrophysics Data System (ADS)

    García Juan, David; Delattre, Bénédicte M. A.; Trombella, Sara; Lynch, Sean; Becker, Matthias; Choi, Hon Fai; Ratib, Osman

    2014-03-01

    Musculoskeletal disorders (MSD) are becoming a big healthcare economical burden in developed countries with aging population. Classical methods like biopsy or EMG used in clinical practice for muscle assessment are invasive and not accurately sufficient for measurement of impairments of muscular performance. Non-invasive imaging techniques can nowadays provide effective alternatives for static and dynamic assessment of muscle function. In this paper we present work aimed toward the development of a generic data structure for handling n-dimensional metabolic and anatomical data acquired from hybrid PET/MR scanners. Special static and dynamic protocols were developed for assessment of physical and functional images of individual muscles of the lower limb. In an initial stage of the project a manual segmentation of selected muscles was performed on high-resolution 3D static images and subsequently interpolated to full dynamic set of contours from selected 2D dynamic images across different levels of the leg. This results in a full set of 4D data of lower limb muscles at rest and during exercise. These data can further be extended to a 5D data by adding metabolic data obtained from PET images. Our data structure and corresponding image processing extension allows for better evaluation of large volumes of multidimensional imaging data that are acquired and processed to generate dynamic models of the moving lower limb and its muscular function.

  7. Functional imaging in lung cancer

    PubMed Central

    Harders, S W; Balyasnikowa, S; Fischer, B M

    2014-01-01

    Lung cancer represents an increasingly frequent cancer diagnosis worldwide. An increasing awareness on smoking cessation as an important mean to reduce lung cancer incidence and mortality, an increasing number of therapy options and a steady focus on early diagnosis and adequate staging have resulted in a modestly improved survival. For early diagnosis and precise staging, imaging, especially positron emission tomography combined with CT (PET/CT), plays an important role. Other functional imaging modalities such as dynamic contrast-enhanced CT (DCE-CT) and diffusion-weighted MR imaging (DW-MRI) have demonstrated promising results within this field. The purpose of this review is to provide the reader with a brief and balanced introduction to these three functional imaging modalities and their current or potential application in the care of patients with lung cancer. PMID:24289258

  8. Quantitative Amyloid Imaging Using Image-Derived Arterial Input Function

    PubMed Central

    Su, Yi; Blazey, Tyler M.; Snyder, Abraham Z.; Raichle, Marcus E.; Hornbeck, Russ C.; Aldea, Patricia; Morris, John C.; Benzinger, Tammie L. S.

    2015-01-01

    Amyloid PET imaging is an indispensable tool widely used in the investigation, diagnosis and monitoring of Alzheimer’s disease (AD). Currently, a reference region based approach is used as the mainstream quantification technique for amyloid imaging. This approach assumes the reference region is amyloid free and has the same tracer influx and washout kinetics as the regions of interest. However, this assumption may not always be valid. The goal of this work is to evaluate an amyloid imaging quantification technique that uses arterial region of interest as the reference to avoid potential bias caused by specific binding in the reference region. 21 participants, age 58 and up, underwent Pittsburgh compound B (PiB) PET imaging and MR imaging including a time-of-flight (TOF) MR angiography (MRA) scan and a structural scan. FreeSurfer based regional analysis was performed to quantify PiB PET data. Arterial input function was estimated based on coregistered TOF MRA using a modeling based technique. Regional distribution volume (VT) was calculated using Logan graphical analysis with estimated arterial input function. Kinetic modeling was also performed using the estimated arterial input function as a way to evaluate PiB binding (DVRkinetic) without a reference region. As a comparison, Logan graphical analysis was also performed with cerebellar cortex as reference to obtain DVRREF. Excellent agreement was observed between the two distribution volume ratio measurements (r>0.89, ICC>0.80). The estimated cerebellum VT was in line with literature reported values and the variability of cerebellum VT in the control group was comparable to reported variability using arterial sampling data. This study suggests that image-based arterial input function is a viable approach to quantify amyloid imaging data, without the need of arterial sampling or a reference region. This technique can be a valuable tool for amyloid imaging, particularly in population where reference normalization

  9. Quantitative amyloid imaging using image-derived arterial input function.

    PubMed

    Su, Yi; Blazey, Tyler M; Snyder, Abraham Z; Raichle, Marcus E; Hornbeck, Russ C; Aldea, Patricia; Morris, John C; Benzinger, Tammie L S

    2015-01-01

    Amyloid PET imaging is an indispensable tool widely used in the investigation, diagnosis and monitoring of Alzheimer's disease (AD). Currently, a reference region based approach is used as the mainstream quantification technique for amyloid imaging. This approach assumes the reference region is amyloid free and has the same tracer influx and washout kinetics as the regions of interest. However, this assumption may not always be valid. The goal of this work is to evaluate an amyloid imaging quantification technique that uses arterial region of interest as the reference to avoid potential bias caused by specific binding in the reference region. 21 participants, age 58 and up, underwent Pittsburgh compound B (PiB) PET imaging and MR imaging including a time-of-flight (TOF) MR angiography (MRA) scan and a structural scan. FreeSurfer based regional analysis was performed to quantify PiB PET data. Arterial input function was estimated based on coregistered TOF MRA using a modeling based technique. Regional distribution volume (VT) was calculated using Logan graphical analysis with estimated arterial input function. Kinetic modeling was also performed using the estimated arterial input function as a way to evaluate PiB binding (DVRkinetic) without a reference region. As a comparison, Logan graphical analysis was also performed with cerebellar cortex as reference to obtain DVRREF. Excellent agreement was observed between the two distribution volume ratio measurements (r>0.89, ICC>0.80). The estimated cerebellum VT was in line with literature reported values and the variability of cerebellum VT in the control group was comparable to reported variability using arterial sampling data. This study suggests that image-based arterial input function is a viable approach to quantify amyloid imaging data, without the need of arterial sampling or a reference region. This technique can be a valuable tool for amyloid imaging, particularly in population where reference normalization may

  10. Reading in the brain of children and adults: A meta‐analysis of 40 functional magnetic resonance imaging studies

    PubMed Central

    Martin, Anna; Schurz, Matthias; Kronbichler, Martin

    2015-01-01

    Abstract We used quantitative, coordinate‐based meta‐analysis to objectively synthesize age‐related commonalities and differences in brain activation patterns reported in 40 functional magnetic resonance imaging (fMRI) studies of reading in children and adults. Twenty fMRI studies with adults (age means: 23–34 years) were matched to 20 studies with children (age means: 7–12 years). The separate meta‐analyses of these two sets showed a pattern of reading‐related brain activation common to children and adults in left ventral occipito‐temporal (OT), inferior frontal, and posterior parietal regions. The direct statistical comparison between the two meta‐analytic maps of children and adults revealed higher convergence in studies with children in left superior temporal and bilateral supplementary motor regions. In contrast, higher convergence in studies with adults was identified in bilateral posterior OT/cerebellar and left dorsal precentral regions. The results are discussed in relation to current neuroanatomical models of reading and tentative functional interpretations of reading‐related activation clusters in children and adults are provided. Hum Brain Mapp 36:1963–1981, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.. PMID:25628041

  11. The neural basis of hand gesture comprehension: A meta-analysis of functional magnetic resonance imaging studies.

    PubMed

    Yang, Jie; Andric, Michael; Mathew, Mili M

    2015-10-01

    Gestures play an important role in face-to-face communication and have been increasingly studied via functional magnetic resonance imaging. Although a large amount of data has been provided to describe the neural substrates of gesture comprehension, these findings have never been quantitatively summarized and the conclusion is still unclear. This activation likelihood estimation meta-analysis investigated the brain networks underpinning gesture comprehension while considering the impact of gesture type (co-speech gestures vs. speech-independent gestures) and task demand (implicit vs. explicit) on the brain activation of gesture comprehension. The meta-analysis of 31 papers showed that as hand actions, gestures involve a perceptual-motor network important for action recognition. As meaningful symbols, gestures involve a semantic network for conceptual processing. Finally, during face-to-face interactions, gestures involve a network for social emotive processes. Our finding also indicated that gesture type and task demand influence the involvement of the brain networks during gesture comprehension. The results highlight the complexity of gesture comprehension, and suggest that future research is necessary to clarify the dynamic interactions among these networks.

  12. Imaging and chemical surface analysis of biomolecular functionalization of monolithically integrated on silicon Mach-Zehnder interferometric immunosensors

    NASA Astrophysics Data System (ADS)

    Gajos, Katarzyna; Angelopoulou, Michailia; Petrou, Panagiota; Awsiuk, Kamil; Kakabakos, Sotirios; Haasnoot, Willem; Bernasik, Andrzej; Rysz, Jakub; Marzec, Mateusz M.; Misiakos, Konstantinos; Raptis, Ioannis; Budkowski, Andrzej

    2016-11-01

    Time-of-flight secondary ion mass spectrometry (imaging, micro-analysis) has been employed to evaluate biofunctionalization of the sensing arm areas of Mach-Zehnder interferometers monolithically integrated on silicon chips for the immunochemical (competitive) detection of bovine κ-casein in goat milk. Biosensor surfaces are examined after: modification with (3-aminopropyl)triethoxysilane, application of multiple overlapping spots of κ-casein solutions, blocking with 100-times diluted goat milk, and reaction with monoclonal mouse anti-κ-casein antibodies in blocking solution. The areas spotted with κ-casein solutions of different concentrations are examined and optimum concentration providing homogeneous coverage is determined. Coverage of biosensor surfaces with biomolecules after each of the sequential steps employed in immunodetection is also evaluated with TOF-SIMS, supplemented by Atomic force microscopy and X-ray photoelectron spectroscopy. Uniform molecular distributions are observed on the sensing arm areas after spotting with optimum κ-casein concentration, blocking and immunoreaction. The corresponding biomolecular compositions are determined with a Principal Component Analysis that distinguished between protein amino acids and milk glycerides, as well as between amino acids characteristic for Mabs and κ-casein, respectively. Use of the optimum conditions (κ-casein concentration) for functionalization of chips with arrays of ten Mach-Zehnder interferometers provided on-chips assays with dramatically improved both intra-chip response repeatability and assay detection sensitivity.

  13. Localized connectivity in depression: a meta-analysis of resting state functional imaging studies.

    PubMed

    Iwabuchi, Sarina J; Krishnadas, Rajeev; Li, Chunbo; Auer, Dorothee P; Radua, Joaquim; Palaniyappan, Lena

    2015-04-01

    Resting-state fMRI studies investigating the pathophysiology of depression have identified prominent abnormalities in large-scale brain networks. However, it is unclear if localized dysfunction of specialized brain regions contribute to network-level abnormalities. We employed a meta-analytical procedure and reviewed studies conducted in China investigating changes in regional homogeneity (ReHo), a measure of localized intraregional connectivity, from resting-state fMRI in depression. Exploiting the statistical power gained from pooled analysis, we also investigated the effects of age, gender, illness duration and treatment on ReHo. The medial prefrontal cortex (MPFC) showed the most robust and reliable increase in ReHo in depression, with greater abnormality in medication-free patients with multiple episodes. Brain networks that relate to this region have been identified previously to show aberrant connectivity in depression, and we propose that the localized neuronal inefficiency of MPFC exists alongside wider network level disruptions involving this region.

  14. Flightspeed Integral Image Analysis Toolkit

    NASA Technical Reports Server (NTRS)

    Thompson, David R.

    2009-01-01

    The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

  15. General and specialized brain correlates for analogical reasoning: A meta-analysis of functional imaging studies.

    PubMed

    Hobeika, Lucie; Diard-Detoeuf, Capucine; Garcin, Béatrice; Levy, Richard; Volle, Emmanuelle

    2016-05-01

    Reasoning by analogy allows us to link distinct domains of knowledge and to transfer solutions from one domain to another. Analogical reasoning has been studied using various tasks that have generally required the consideration of the relationships between objects and their integration to infer an analogy schema. However, these tasks varied in terms of the level and the nature of the relationships to consider (e.g., semantic, visuospatial). The aim of this study was to identify the cerebral network involved in analogical reasoning and its specialization based on the domains of information and task specificity. We conducted a coordinate-based meta-analysis of 27 experiments that used analogical reasoning tasks. The left rostrolateral prefrontal cortex was one of the regions most consistently activated across the studies. A comparison between semantic and visuospatial analogy tasks showed both domain-oriented regions in the inferior and middle frontal gyri and a domain-general region, the left rostrolateral prefrontal cortex, which was specialized for analogy tasks. A comparison of visuospatial analogy to matrix problem tasks revealed that these two relational reasoning tasks engage, at least in part, distinct right and left cerebral networks, particularly separate areas within the left rostrolateral prefrontal cortex. These findings highlight several cognitive and cerebral differences between relational reasoning tasks that can allow us to make predictions about the respective roles of distinct brain regions or networks. These results also provide new, testable anatomical hypotheses about reasoning disorders that are induced by brain damage. Hum Brain Mapp 37:1953-1969, 2016. © 2016 Wiley Periodicals, Inc.

  16. Independent component analysis using prior information for signal detection in a functional imaging system of the retina.

    PubMed

    Barriga, E Simon; Pattichis, Marios; Ts'o, Dan; Abramoff, Michael; Kardon, Randy; Kwon, Young; Soliz, Peter

    2011-02-01

    Independent component analysis (ICA) is a statistical technique that estimates a set of sources mixed by an unknown mixing matrix using only a set of observations. For this purpose, the only assumption is that the sources are statistically independent. In many applications, some information about the nature of the unknown signals is available. In this paper we show a method for incorporating prior information about the mixing matrix to increase the levels of detection of responses to visual stimuli. Experimentally, our method matches the performance of known ICA algorithms for high SNR and can greatly improve the performance for low levels of SNR or low levels of signal-to-background ratio (SBR). For the problem of signal extraction, we have achieved detection for signals as small as 0.01% (-40 dB SBR) in hybrid live/synthetic data simulations. In experiments using a functional imager of the retina, measured changes in reflectance in response to visual stimulus are in the order of 0.1-1% of the total pixel intensity value, which makes the functional signal difficult to detect by standard methods. The results of the analysis show that using ICA-P signal levels of 0.1% can be detected. The approach also generalizes the standard Infomax algorithm which can be thought of as a special case of ICA-P when the confidence parameter or a tolerance value is zero. For in vivo animal experiments, we show that signal detection agreement over a range of confidence values parameters can be used to establish reflectance changes in response to the visual stimulus.

  17. Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

    PubMed Central

    Gnyawali, Surya C.; Blum, Kevin; Pal, Durba; Ghatak, Subhadip; Khanna, Savita; Roy, Sashwati; Sen, Chandan K.

    2017-01-01

    Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system. PMID:28106129

  18. Retooling Laser Speckle Contrast Analysis Algorithm to Enhance Non-Invasive High Resolution Laser Speckle Functional Imaging of Cutaneous Microcirculation

    NASA Astrophysics Data System (ADS)

    Gnyawali, Surya C.; Blum, Kevin; Pal, Durba; Ghatak, Subhadip; Khanna, Savita; Roy, Sashwati; Sen, Chandan K.

    2017-01-01

    Cutaneous microvasculopathy complicates wound healing. Functional assessment of gated individual dermal microvessels is therefore of outstanding interest. Functional performance of laser speckle contrast imaging (LSCI) systems is compromised by motion artefacts. To address such weakness, post-processing of stacked images is reported. We report the first post-processing of binary raw data from a high-resolution LSCI camera. Sharp images of low-flowing microvessels were enabled by introducing inverse variance in conjunction with speckle contrast in Matlab-based program code. Extended moving window averaging enhanced signal-to-noise ratio. Functional quantitative study of blood flow kinetics was performed on single gated microvessels using a free hand tool. Based on detection of flow in low-flow microvessels, a new sharp contrast image was derived. Thus, this work presents the first distinct image with quantitative microperfusion data from gated human foot microvasculature. This versatile platform is applicable to study a wide range of tissue systems including fine vascular network in murine brain without craniotomy as well as that in the murine dorsal skin. Importantly, the algorithm reported herein is hardware agnostic and is capable of post-processing binary raw data from any camera source to improve the sensitivity of functional flow data above and beyond standard limits of the optical system.

  19. Functional imaging for regenerative medicine.

    PubMed

    Leahy, Martin; Thompson, Kerry; Zafar, Haroon; Alexandrov, Sergey; Foley, Mark; O'Flatharta, Cathal; Dockery, Peter

    2016-04-19

    In vivo imaging is a platform technology with the power to put function in its natural structural context. With the drive to translate stem cell therapies into pre-clinical and clinical trials, early selection of the right imaging techniques is paramount to success. There are many instances in regenerative medicine where the biological, biochemical, and biomechanical mechanisms behind the proposed function of stem cell therapies can be elucidated by appropriate imaging. Imaging techniques can be divided according to whether labels are used and as to whether the imaging can be done in vivo. In vivo human imaging places additional restrictions on the imaging tools that can be used. Microscopies and nanoscopies, especially those requiring fluorescent markers, have made an extraordinary impact on discovery at the molecular and cellular level, but due to their very limited ability to focus in the scattering tissues encountered for in vivo applications they are largely confined to superficial imaging applications in research laboratories. Nanoscopy, which has tremendous benefits in resolution, is limited to the near-field (e.g. near-field scanning optical microscope (NSNOM)) or to very high light intensity (e.g. stimulated emission depletion (STED)) or to slow stochastic events (photo-activated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM)). In all cases, nanoscopy is limited to very superficial applications. Imaging depth may be increased using multiphoton or coherence gating tricks. Scattering dominates the limitation on imaging depth in most tissues and this can be mitigated by the application of optical clearing techniques that can impose mild (e.g. topical application of glycerol) or severe (e.g. CLARITY) changes to the tissue to be imaged. Progression of therapies through to clinical trials requires some thought as to the imaging and sensing modalities that should be used. Smoother progression is facilitated by the use of

  20. Multisensor Image Analysis System

    DTIC Science & Technology

    1993-04-15

    AD-A263 679 II Uli! 91 Multisensor Image Analysis System Final Report Authors. Dr. G. M. Flachs Dr. Michael Giles Dr. Jay Jordan Dr. Eric...or decision, unless so designated by other documentation. 93-09739 *>ft s n~. now illlllM3lMVf Multisensor Image Analysis System Final...Multisensor Image Analysis System 3. REPORT TYPE AND DATES COVERED FINAL: LQj&tt-Z JZOfVL 5. FUNDING NUMBERS 93 > 6. AUTHOR(S) Drs. Gerald

  1. Functional near-infrared imager

    NASA Astrophysics Data System (ADS)

    Luo, Qingming; Nioka, Shoko; Chance, Britton

    1997-08-01

    We developed a continuous wave (cw) light imaging probe which includes 9 light sources and four pairs detectors (each pair has one 850 nm filtered detector and one 760 nm filtered detector). The light sources are controlled by a computer and the signals from the detectors are converted and processed in the computer. There are 16 measurement sections and total detection area is 9 cm multiplied by 4 cm which can be scanned every 8 seconds. The detector-source uses 2.5 cm spacing. In this study, we present the noise, drift, detectivity and spatial resolution test results of the imager. Changes of oxygenation and blood volume in about 2 cm depth from the surface of brain model can be detected. The temporal resolution is 8 seconds and spatial resolution is about 2 cm. The detectivity of OD changes can reach 0.008. With this cw imaging probe, we measured motor function in motor cortex area, visual function in occipital area, and cognitive activity in frontal forehead area of the human brian when the subjects are stimulated by moving fingers, viewing a flashing light and doing an analogy test, respectively. The experimental results show that the cw imaging probe can be used for functional images of brain activity, base upon changes of oxygenation and blood volume due to the stimulus.

  2. [Presurgical functional magnetic resonance imaging].

    PubMed

    Stippich, C

    2010-02-01

    Functional magnetic resonance imaging (fMRI) is an important and novel neuroimaging modality for patients with brain tumors. By non-invasive measurement, localization and lateralization of brain activiation, most importantly of motor and speech function, fMRI facilitates the selection of the most appropriate and sparing treatment and function-preserving surgery. Prerequisites for the diagnostic use of fMRI are the application of dedicated clinical imaging protocols and standardization of the respective imaging procedures. The combination with diffusion tensor imaging (DTI) also enables tracking and visualization of important fiber bundles such as the pyramidal tract and the arcuate fascicle. These multimodal MR data can be implemented in computer systems for functional neuronavigation or radiation treatment. The practicability, accuracy and reliability of presurgical fMRI have been validated by large numbers of published data. However, fMRI cannot be considered as a fully established modality of diagnostic neuroimaging due to the lack of guidelines of the responsible medical associations as well as the lack of medical certification of important hardware and software components. This article reviews the current research in the field and provides practical information relevant for presurgical fMRI.

  3. Abnormalities of regional brain function in Parkinson’s disease: a meta-analysis of resting state functional magnetic resonance imaging studies

    PubMed Central

    Pan, PingLei; Zhang, Yang; Liu, Yi; Zhang, He; Guan, DeNing; Xu, Yun

    2017-01-01

    There is convincing evidence that abnormalities of regional brain function exist in Parkinson’s disease (PD). However, many resting-state functional magnetic resonance imaging (rs-fMRI) studies using amplitude of low-frequency fluctuations (ALFF) have reported inconsistent results about regional spontaneous neuronal activity in PD. Therefore, we conducted a comprehensive meta-analysis using the Seed-based d Mapping and several complementary analyses. We searched PubMed, Embase, and Web of Science databases for eligible whole-brain rs-fMRI studies that measured ALFF differences between patients with PD and healthy controls published from January 1st, 2000 until June 24, 2016. Eleven studies reporting 14 comparisons, comparing 421 patients and 381 healthy controls, were included. The most consistent and replicable findings in patients with PD compared with healthy controls were identified, including the decreased ALFFs in the bilateral supplementary motor areas, left putamen, left premotor cortex, and left inferior parietal gyrus, and increased ALFFs in the right inferior parietal gyrus. The altered ALFFs in these brain regions are related to motor deficits and compensation in PD, which contribute to understanding its neurobiological underpinnings and could serve as specific regions of interest for further studies. PMID:28079169

  4. A group independent component analysis of covert verb generation in children: a functional magnetic resonance imaging study.

    PubMed

    Karunanayaka, Prasanna; Schmithorst, Vincent J; Vannest, Jennifer; Szaflarski, Jerzy P; Plante, Elena; Holland, Scott K

    2010-05-15

    Semantic language skills are an integral part of early childhood language development. The semantic association between verbs and nouns constitutes an important building block for the construction of sentences. In this large-scale functional magnetic resonance imaging (fMRI) study, involving 336 subjects between the ages of 5 and 18 years, we investigated the neural correlates of covert verb generation in children. Using group independent component analysis (ICA), seven task-related components were identified including the mid-superior temporal gyrus, the most posterior aspect of the superior temporal gyrus, the parahippocampal gyrus, the inferior frontal gyrus, the angular gyrus, and medial aspect of the parietal lobule (precuneus/posterior cingulate). A highly left-lateralized component was found including the medial temporal gyrus, the frontal gyrus, the inferior frontal gyrus, and the angular gyrus. The associated independent component (IC) time courses were analyzed to investigate developmental changes in the neural elements supporting covert verb generation. Observed age effects may either reflect specific local neuroplastic changes in the neural substrates supporting language or a more global transformation of neuroplasticity in the developing brain. The results are analyzed and presented in the framework of two theoretical models for neurocognitive brain development. In this context, group ICA of fMRI data from our large sample of children aged 5-18 years provides strong evidence in support of the regionally weighted model for cognitive neurodevelopment of language networks.

  5. Multispectral Imaging Broadens Cellular Analysis

    NASA Technical Reports Server (NTRS)

    2007-01-01

    Amnis Corporation, a Seattle-based biotechnology company, developed ImageStream to produce sensitive fluorescence images of cells in flow. The company responded to an SBIR solicitation from Ames Research Center, and proposed to evaluate several methods of extending the depth of field for its ImageStream system and implement the best as an upgrade to its commercial products. This would allow users to view whole cells at the same time, rather than just one section of each cell. Through Phase I and II SBIR contracts, Ames provided Amnis the funding the company needed to develop this extended functionality. For NASA, the resulting high-speed image flow cytometry process made its way into Medusa, a life-detection instrument built to collect, store, and analyze sample organisms from erupting hydrothermal vents, and has the potential to benefit space flight health monitoring. On the commercial end, Amnis has implemented the process in ImageStream, combining high-resolution microscopy and flow cytometry in a single instrument, giving researchers the power to conduct quantitative analyses of individual cells and cell populations at the same time, in the same experiment. ImageStream is also built for many other applications, including cell signaling and pathway analysis; classification and characterization of peripheral blood mononuclear cell populations; quantitative morphology; apoptosis (cell death) assays; gene expression analysis; analysis of cell conjugates; molecular distribution; and receptor mapping and distribution.

  6. Functional imaging in chronic migraine.

    PubMed

    Maniyar, Farooq H; Goadsby, Peter J

    2013-05-01

    Chronic migraine is a relatively common disorder in neurological terms that causes very significant disability at a high cost. The precise mechanisms behind the progression of episodic migraine to chronic migraine are not well understood. Functional neuro-imaging works on the basis that neuronal activations are associated with changes in regional cerebral blood flow, and it can help us answer some of these questions. In this review, we discuss important recent studies in chronic migraine or studies relating to increasing frequency of migraine attacks. The findings show that increasing frequency of migraine attacks is associated with changes in key brainstem areas, basal ganglia and various cortical areas involved in pain.

  7. A new method for point-spread function correction using the ellipticity of re-smeared artificial images in weak gravitational lensing shear analysis

    SciTech Connect

    Okura, Yuki; Futamase, Toshifumi E-mail: tof@astr.tohoku.ac.jp

    2014-09-10

    Highly accurate weak lensing analysis is urgently required for planned cosmic shear observations. For this purpose we have eliminated various systematic noises in the measurement. The point-spread function (PSF) effect is one of them. A perturbative approach for correcting the PSF effect on the observed image ellipticities has been previously employed. Here we propose a new non-perturbative approach for PSF correction that avoids the systematic error associated with the perturbative approach. The new method uses an artificial image for measuring shear which has the same ellipticity as the lensed image. This is done by re-smearing the observed galaxy images and observed star images (PSF) with an additional smearing function to obtain the original lensed galaxy images. We tested the new method with simple simulated objects that have Gaussian or Sérsic profiles smeared by a Gaussian PSF with sufficiently large size to neglect pixelization. Under the condition of no pixel noise, it is confirmed that the new method has no systematic error even if the PSF is large and has a high ellipticity.

  8. Analysis of MUSIC-type imaging functional for single, thin electromagnetic inhomogeneity in limited-view inverse scattering problem

    NASA Astrophysics Data System (ADS)

    Ahn, Chi Young; Jeon, Kiwan; Park, Won-Kwang

    2015-06-01

    This study analyzes the well-known MUltiple SIgnal Classification (MUSIC) algorithm to identify unknown support of thin penetrable electromagnetic inhomogeneity from scattered field data collected within the so-called multi-static response matrix in limited-view inverse scattering problems. The mathematical theories of MUSIC are partially discovered, e.g., in the full-view problem, for an unknown target of dielectric contrast or a perfectly conducting crack with the Dirichlet boundary condition (Transverse Magnetic-TM polarization) and so on. Hence, we perform further research to analyze the MUSIC-type imaging functional and to certify some well-known but theoretically unexplained phenomena. For this purpose, we establish a relationship between the MUSIC imaging functional and an infinite series of Bessel functions of integer order of the first kind. This relationship is based on the rigorous asymptotic expansion formula in the existence of a thin inhomogeneity with a smooth supporting curve. Various results of numerical simulation are presented in order to support the identified structure of MUSIC. Although a priori information of the target is needed, we suggest a least condition of range of incident and observation directions to apply MUSIC in the limited-view problem.

  9. Functional brain imaging across development.

    PubMed

    Rubia, Katya

    2013-12-01

    The developmental cognitive neuroscience literature has grown exponentially over the last decade. This paper reviews the functional magnetic resonance imaging (fMRI) literature on brain function development of typically late developing functions of cognitive and motivation control, timing and attention as well as of resting state neural networks. Evidence shows that between childhood and adulthood, concomitant with cognitive maturation, there is progressively increased functional activation in task-relevant lateral and medial frontal, striatal and parieto-temporal brain regions that mediate these higher level control functions. This is accompanied by progressively stronger functional inter-regional connectivity within task-relevant fronto-striatal and fronto-parieto-temporal networks. Negative age associations are observed in earlier developing posterior and limbic regions, suggesting a shift with age from the recruitment of "bottom-up" processing regions towards "top-down" fronto-cortical and fronto-subcortical connections, leading to a more mature, supervised cognition. The resting state fMRI literature further complements this evidence by showing progressively stronger deactivation with age in anti-correlated task-negative resting state networks, which is associated with better task performance. Furthermore, connectivity analyses during the resting state show that with development increasingly stronger long-range connections are being formed, for example, between fronto-parietal and fronto-cerebellar connections, in both task-positive networks and in task-negative default mode networks, together with progressively lesser short-range connections, suggesting progressive functional integration and segregation with age. Overall, evidence suggests that throughout development between childhood and adulthood, there is progressive refinement and integration of both task-positive fronto-cortical and fronto-subcortical activation and task-negative deactivation, leading to

  10. Noninvasive functional brain mapping by change-distribution analysis of averaged PET images of H/sub 2//sup 15/O tissue activity

    SciTech Connect

    Fox, P.T.; Mintun, M.A.

    1989-02-01

    Change-distribution analysis and intersubject averaging of subtracted positron emission tomography (PET) images are new techniques for detecting, localizing, and quantifying state-dependent focal transients in neuronal activity. We previously described their application to cerebral blood flow images (intravenous bolus H/sub 2//sup 15/O, Kety autoradiographic model). We now describe their application to images of H/sub 2//sup 15/O regional tissue activity without conversion to units of blood flow. The sensitivity and specificity of response detection and the accuracy of response localization were virtually identical for the two types of images. Response magnitude expressed in percent change from rest was slightly, but consistently smaller in tissue-activity images. Response magnitude expressed in z-score was the same for the two-image types. Most research and clinical applications of functional brain mapping can employ images of H215O tissue activity (intravenous bolus, 40-sec nondynamic scan) without conversion to units of blood flow. This eliminates arterial blood sampling, thereby simplifying and minimizing the invasivity of the PET procedure.

  11. Support vector analysis of color-Doppler images: a new approach for estimating indices of left ventricular function.

    PubMed

    Rojo-Alvarez, J L; Bermejo, J; Juárez-Caballero, V M; Yotti, R; Cortina, C; García-Fernández, M A; Antoranz, J C

    2006-08-01

    Reliable noninvasive estimators of global left ventricular (LV) chamber function remain unavailable. We have previously demonstrated a potential relationship between color-Doppler M-mode (CDMM) images and two basic indices of LV function: peak-systolic elastance (Emax) and the time-constant of LV relaxation (tau). Thus, we hypothesized that these two indices could be estimated noninvasively by adequate postprocessing of CDMM recordings. A semiparametric regression (SR) version of support vector machine (SVM) is here proposed for building a blind model, capable of analyzing CDMM images automatically, as well as complementary clinical information. Simultaneous invasive and Doppler tracings were obtained in nine mini-pigs in a high-fidelity experimental setup. The model was developed using a test and validation leave-one-out design. Reasonably acceptable prediction accuracy was obtained for both Emax (intraclass correlation coefficient Ric, = 0.81) and tau (Ric, = 0.61). For the first time, a quantitative, noninvasive estimation of cardiovascular indices is addressed by processing Doppler-echocardiography recordings using a learning-from-samples method.

  12. Image analysis library software development

    NASA Technical Reports Server (NTRS)

    Guseman, L. F., Jr.; Bryant, J.

    1977-01-01

    The Image Analysis Library consists of a collection of general purpose mathematical/statistical routines and special purpose data analysis/pattern recognition routines basic to the development of image analysis techniques for support of current and future Earth Resources Programs. Work was done to provide a collection of computer routines and associated documentation which form a part of the Image Analysis Library.

  13. Anatomical and functional imaging in endocrine hypertension

    PubMed Central

    Chaudhary, Vikas; Bano, Shahina

    2012-01-01

    In endocrine hypertension, hormonal excess results in clinically significant hypertension. The functional imaging (such as radionuclide imaging) complements anatomy-based imaging (such as ultrasound, computed tomography, and magnetic resonance imaging) to facilitate diagnostic localization of a lesion causing endocrine hypertension. The aim of this review article is to familiarize general radiologists, endocrinologists, and clinicians with various anatomical and functional imaging techniques used in patients with endocrine hypertension. PMID:23087854

  14. Digital Image Analysis of Cereals

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Image analysis is the extraction of meaningful information from images, mainly digital images by means of digital processing techniques. The field was established in the 1950s and coincides with the advent of computer technology, as image analysis is profoundly reliant on computer processing. As t...

  15. Whole brain high-resolution functional imaging at ultra high magnetic fields: an application to the analysis of resting state networks.

    PubMed

    De Martino, Federico; Esposito, Fabrizio; van de Moortele, Pierre-Francois; Harel, Noam; Formisano, Elia; Goebel, Rainer; Ugurbil, Kamil; Yacoub, Essa

    2011-08-01

    Whole-brain functional magnetic resonance imaging (fMRI) allows measuring brain dynamics at all brain regions simultaneously and is widely used in research and clinical neuroscience to observe both stimulus-related and spontaneous neural activity. Ultrahigh magnetic fields (7T and above) allow functional imaging with high contrast-to-noise ratios and improved spatial resolution and specificity compared to clinical fields (1.5T and 3T). High-resolution 7T fMRI, however, has been mostly limited to partial brain coverage with previous whole-brain applications sacrificing either the spatial or temporal resolution. Here we present whole-brain high-resolution (1, 1.5 and 2mm isotropic voxels) resting state fMRI at 7T, obtained with parallel imaging technology, without sacrificing temporal resolution or brain coverage, over what is typically achieved at 3T with several fold larger voxel volumes. Using Independent Component Analysis we demonstrate that high resolution images acquired at 7T retain enough sensitivity for the reliable extraction of typical resting state brain networks and illustrate the added value of obtaining both single subject and group maps, using cortex based alignment, of the default-mode network (DMN) with high native resolution. By comparing results between multiple resolutions we show that smaller voxels volumes (1 and 1.5mm isotropic) data result in reduced partial volume effects, permitting separations of detailed spatial features within the DMN patterns as well as a better function to anatomy correspondence.

  16. Functional Magnetic Resonance Imaging Methods

    PubMed Central

    Chen, Jingyuan E.; Glover, Gary H.

    2015-01-01

    Since its inception in 1992, Functional Magnetic Resonance Imaging (fMRI) has become an indispensible tool for studying cognition in both the healthy and dysfunctional brain. FMRI monitors changes in the oxygenation of brain tissue resulting from altered metabolism consequent to a task-based evoked neural response or from spontaneous fluctuations in neural activity in the absence of conscious mentation (the “resting state”). Task-based studies have revealed neural correlates of a large number of important cognitive processes, while fMRI studies performed in the resting state have demonstrated brain-wide networks that result from brain regions with synchronized, apparently spontaneous activity. In this article, we review the methods used to acquire and analyze fMRI signals. PMID:26248581

  17. Medical Image Analysis Facility

    NASA Technical Reports Server (NTRS)

    1978-01-01

    To improve the quality of photos sent to Earth by unmanned spacecraft. NASA's Jet Propulsion Laboratory (JPL) developed a computerized image enhancement process that brings out detail not visible in the basic photo. JPL is now applying this technology to biomedical research in its Medical lrnage Analysis Facility, which employs computer enhancement techniques to analyze x-ray films of internal organs, such as the heart and lung. A major objective is study of the effects of I stress on persons with heart disease. In animal tests, computerized image processing is being used to study coronary artery lesions and the degree to which they reduce arterial blood flow when stress is applied. The photos illustrate the enhancement process. The upper picture is an x-ray photo in which the artery (dotted line) is barely discernible; in the post-enhancement photo at right, the whole artery and the lesions along its wall are clearly visible. The Medical lrnage Analysis Facility offers a faster means of studying the effects of complex coronary lesions in humans, and the research now being conducted on animals is expected to have important application to diagnosis and treatment of human coronary disease. Other uses of the facility's image processing capability include analysis of muscle biopsy and pap smear specimens, and study of the microscopic structure of fibroprotein in the human lung. Working with JPL on experiments are NASA's Ames Research Center, the University of Southern California School of Medicine, and Rancho Los Amigos Hospital, Downey, California.

  18. Does pediatric post-traumatic stress disorder alter the brain? Systematic review and meta-analysis of structural and functional magnetic resonance imaging studies.

    PubMed

    Milani, Ana Carolina C; Hoffmann, Elis V; Fossaluza, Victor; Jackowski, Andrea P; Mello, Marcelo F

    2017-03-01

    Several studies have recently demonstrated that the volumes of specific brain regions are reduced in children and adolescents with post-traumatic stress disorder (PTSD) compared with those of healthy controls. Our study investigated the potential association between early traumatic experiences and altered brain regions and functions. We conducted a systematic review of the scientific literature regarding functional magnetic resonance imaging and a meta-analysis of structural magnetic resonance imaging studies that investigated cerebral region volumes in pediatric patients with PTSD. We searched for articles from 2000 to 2014 in the PsycINFO, PubMed, Medline, Lilacs, and ISI (Web of Knowledge) databases. All data regarding the amygdala, hippocampus, corpus callosum, brain, and intracranial volumes that fit the inclusion criteria were extracted and combined in a meta-analysis that assessed differences between groups. The meta-analysis found reduced total corpus callosum areas and reduced total cerebral and intracranial volumes in the patients with PTSD. The total hippocampus (left and right hippocampus) and gray matter volumes of the amygdala and frontal lobe were also reduced, but these differences were not significant. The functional studies revealed differences in brain region activation in response to stimuli in the post-traumatic stress symptoms/PTSD group. Our results confirmed that the pediatric patients with PTSD exhibited structural and functional brain abnormalities and that some of the abnormalities occurred in different brain regions than those observed in adults.

  19. Quantitative histogram analysis of images

    NASA Astrophysics Data System (ADS)

    Holub, Oliver; Ferreira, Sérgio T.

    2006-11-01

    loading of an image No. of bits in a word: 32 No. of processors used: 1 Has the code been vectorized or parallelized?: No No of lines in distributed program, including test data, etc.:138 946 No. of bytes in distributed program, including test data, etc.:15 166 675 Distribution format: tar.gz Nature of physical problem: Quantification of image data (e.g., for discrimination of molecular species in gels or fluorescent molecular probes in cell cultures) requires proprietary or complex software packages, which might not include the relevant statistical parameters or make the analysis of multiple images a tedious procedure for the general user. Method of solution: Tool for conversion of RGB bitmap image into luminance-linear image and extraction of luminance histogram, probability distribution, and statistical parameters (average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of histogram and median of probability distribution) with possible selection of region of interest (ROI) and lower and upper threshold levels. Restrictions on the complexity of the problem: Does not incorporate application-specific functions (e.g., morphometric analysis) Typical running time: Seconds (depending on image size and processor speed) Unusual features of the program: None

  20. Effects of Image Contrast on Functional MRI Image Registration

    PubMed Central

    Gonzalez-Castillo, Javier; Duthie, Kristen N.; Saad, Ziad S.; Chu, Carlton; Bandettini, Peter A.; Luh, Wen-Ming

    2012-01-01

    Lack of tissue contrast and existing inhomogeneous bias fields from multi-channel coils have the potential to degrade the output of registration algorithms; and consequently degrade group analysis and any attempt to accurately localize brain function. Non-invasive ways to improve tissue contrast in fMRI images include the use of low flip angles (FAs) well below the Ernst angle and longer repetition times (TR). Techniques to correct intensity inhomogeneity are also available in most mainstream fMRI data analysis packages; but are not used as part of the pre-processing pipeline in many studies. In this work, we use a combination of real data and simulations to show that simple-to-implement acquisition/pre-processing techniques can significantly improve the outcome of both functional-to-functional and anatomical-to-functional image registrations. We also emphasize the need of tissue contrast on EPI images to be able to appropriately evaluate the quality of the alignment. In particular, we show that the use of low FAs (e.g., θ≤40°), when physiological noise considerations permit such an approach, significantly improves accuracy, consistency and stability of registration for data acquired at relatively short TRs (TR≤2s). Moreover, we also show that the application of bias correction techniques significantly improves alignment both for array-coil data (known to contain high intensity inhomogeneity) as well as birdcage-coil data. Finally, improvements in alignment derived from the use of the first infinite-TR volumes (ITVs) as targets for registration are also demonstrated. For the purpose of quantitatively evaluating the different scenarios, two novel metrics were developed: Mean Voxel Distance (MVD) to evaluate registration consistency, and Deviation of Mean Voxel Distance (dMVD) to evaluate registration stability across successive alignment attempts. PMID:23128074

  1. Analysis of motion tracking in echocardiographic image sequences: influence of system geometry and point-spread function.

    PubMed

    Touil, Basma; Basarab, Adrian; Delachartre, Philippe; Bernard, Olivier; Friboulet, Denis

    2010-03-01

    This paper focuses on motion tracking in echocardiographic ultrasound images. The difficulty of this task is related to the fact that echographic image formation induces decorrelation between the underlying motion of tissue and the observed speckle motion. Since Meunier's seminal work, this phenomenon has been investigated in many simulation studies as part of speckle tracking or optical flow-based motion estimation techniques. Most of these studies modeled image formation using a linear convolution approach, where the system point-spread function (PSF) was spatially invariant and the probe geometry was linear. While these assumptions are valid over a small spatial area, they constitute an oversimplification when a complete image is considered. Indeed, echocardiographic acquisition geometry relies on sectorial probes and the system PSF is not perfectly invariant, even if dynamic focusing is performed. This study investigated the influence of sectorial geometry and spatially varying PSF on speckle tracking. This was done by simulating a typical 64 elements, cardiac probe operating at 3.5 MHz frequency, using the simulation software Field II. This simulation first allowed quantification of the decorrelation induced by the system between two images when simple motion such as translation or incompressible deformation was applied. We then quantified the influence of decorrelation on speckle tracking accuracy using a conventional block matching (BM) algorithm and a bilinear deformable block matching (BDBM) algorithm. In echocardiography, motion estimation is usually performed on reconstructed images where the initial sectorial (i.e., polar) data are interpolated on a cartesian grid. We therefore studied the influence of sectorial acquisition geometry, by performing block matching on cartesian and polar data. Simulation results show that decorrelation is spatially variant and depends on the position of the region where motion takes place relative to the probe. Previous

  2. Pediatric Epilepsy: Neurology, Functional Imaging, and Neurosurgery.

    PubMed

    Mountz, James M; Patterson, Christina M; Tamber, Mandeep S

    2017-03-01

    In this chapter we provide a comprehensive review of the current role that functional imaging can have in the care of the pediatric epilepsy patient from the perspective of the epilepsy neurologist and the epilepsy neurosurgeon. In the neurology section, the diagnosis and classification of epilepsy adapted by the International League Against Epilepsy as well as the etiology and incidence of the disease is presented. The neuroimaging section describes how advanced nuclear medicine imaging methods can be synergized to provide a maximum opportunity to localize an epileptogenic focus. This section described the value of FDG-PET and regional cerebral blood flow SPECT in the identification of an epileptogenic focus. The imaging section also emphasizes the importance on developing a dedicated epilepsy management team, comprised of an epilepsy imaging specialist, epilepsy neurologist and epilepsy neurosurgeon, to provide the maximum benefit to each child with epilepsy. An emphasis is placed on preparation for ictal SPECT injection procedures, including the critical role of an automated injector well as the use of state-of-the-art dedicated nuclear medicine imaging and analysis protocols to correctly localize the epileptogenic focus location. In the final section, surgical options, approaches and expected outcomes for the different classes of epilepsy is presented.

  3. Bridging the Gap: Dynamic Causal Modeling and Granger Causality Analysis of Resting State Functional Magnetic Resonance Imaging.

    PubMed

    Bajaj, Sahil; Adhikari, Bhim M; Friston, Karl J; Dhamala, Mukesh

    2016-09-16

    Granger causality (GC) and dynamic causal modeling (DCM) are the two key approaches used to determine the directed interactions among brain areas. Recent discussions have provided a constructive account of the merits and demerits. GC, on one side, considers dependencies among measured responses, whereas DCM, on the other, models how neuronal activity in one brain area causes dynamics in another. In this study, our objective was to establish construct validity between GC and DCM in the context of resting state functional magnetic resonance imaging (fMRI). We first established the face validity of both approaches using simulated fMRI time series, with endogenous fluctuations in two nodes. Crucially, we tested both unidirectional and bidirectional connections between the two nodes to ensure that both approaches give veridical and consistent results, in terms of model comparison. We then applied both techniques to empirical data and examined their consistency in terms of the (quantitative) in-degree of key nodes of the default mode. Our simulation results suggested a (qualitative) consistency between GC and DCM. Furthermore, by applying nonparametric GC and stochastic DCM to resting-state fMRI data, we confirmed that both GC and DCM infer similar (quantitative) directionality between the posterior cingulate cortex (PCC), the medial prefrontal cortex, the left middle temporal cortex, and the left angular gyrus. These findings suggest that GC and DCM can be used to estimate directed functional and effective connectivity from fMRI measurements in a consistent manner.

  4. Imaging visual function of the human brain

    SciTech Connect

    Marg, E.

    1988-10-01

    Imaging of human brain structure and activity with particular reference to visual function is reviewed along with methods of obtaining the data including computed tomographic (CT) scan, magnetic resonance imaging (MRI), magnetic resonance spectroscopy (MRS), and positron emission tomography (PET). The literature is reviewed and the potential for a new understanding of brain visual function is discussed. PET is reviewed from basic physical principles to the most recent visual brain findings with oxygen-15. It is shown that there is a potential for submillimeter localization of visual functions with sequentially different visual stimuli designed for the temporal separation of the responses. Single photon emission computed tomography (SPECT), a less expensive substitute for PET, is also discussed. MRS is covered from basic physical principles to the current state of the art of in vivo biochemical analysis. Future possible clinical applications are discussed. Improved understanding of the functional neural organization of vision and brain will open a window to maps and circuits of human brain function.119 references.

  5. Subband/Transform MATLAB Functions For Processing Images

    NASA Technical Reports Server (NTRS)

    Glover, D.

    1995-01-01

    SUBTRANS software is package of routines implementing image-data-processing functions for use with MATLAB*(TM) software. Provides capability to transform image data with block transforms and to produce spatial-frequency subbands of transformed data. Functions cascaded to provide further decomposition into more subbands. Also used in image-data-compression systems. For example, transforms used to prepare data for lossy compression. Written for use in MATLAB mathematical-analysis environment.

  6. Interactive Image Analysis System Design,

    DTIC Science & Technology

    1982-12-01

    This report describes a design for an interactive image analysis system (IIAS), which implements terrain data extraction techniques. The design... analysis system. Additionally, the system is fully capable of supporting many generic types of image analysis and data processing, and is modularly...employs commercially available, state of the art minicomputers and image display devices with proven software to achieve a cost effective, reliable image

  7. Parallel Algorithms for Image Analysis.

    DTIC Science & Technology

    1982-06-01

    8217 _ _ _ _ _ _ _ 4. TITLE (aid Subtitle) S. TYPE OF REPORT & PERIOD COVERED PARALLEL ALGORITHMS FOR IMAGE ANALYSIS TECHNICAL 6. PERFORMING O4G. REPORT NUMBER TR-1180...Continue on reverse side it neceesary aid Identlfy by block number) Image processing; image analysis ; parallel processing; cellular computers. 20... IMAGE ANALYSIS TECHNICAL 6. PERFORMING ONG. REPORT NUMBER TR-1180 - 7. AUTHOR(&) S. CONTRACT OR GRANT NUMBER(s) Azriel Rosenfeld AFOSR-77-3271 9

  8. Resting state functional magnetic resonance imaging reveals distinct brain activity in heavy cannabis users – a multi-voxel pattern analysis

    PubMed Central

    Cheng, H; Skosnik, PD; Pruce, BJ; Brumbaugh, MS; Vollmer, JM; Fridberg, DJ; O’Donnell, BF; Hetrick, WP; Newman, SD

    2015-01-01

    Chronic cannabis use can cause cognitive, perceptual and personality alterations, which are believed to be associated with regional brain changes and possible changes in connectivity between functional regions. This study aims to identify the changes from resting state functional magnetic resonance imaging scans. A two-level multi-voxel pattern analysis was proposed to classify male cannabis users from normal controls. The first level analysis works on a voxel basis and identifies clusters for the input of a second level analysis, which works on the functional connectivity between these regions. We found distinct clusters for male cannabis users in the middle frontal gyrus, precentral gyrus, superior frontal gyrus, posterior cingulate cortex, cerebellum and some other regions. Based on the functional connectivity of these clusters, a high overall accuracy rate of 84–88% in classification accuracy was achieved. High correlations were also found between the overall classification accuracy and Barrett Barrett Impulsiveness Scale factor scores of attention and motor. Our result suggests regional differences in the brains of male cannabis users that span from the cerebellum to the prefrontal cortex, which are associated with differences in functional connectivity. PMID:25237118

  9. Persistent Impact of In utero Irradiation on Mouse Brain Structure and Function Characterized by MR Imaging and Behavioral Analysis

    PubMed Central

    Verreet, Tine; Rangarajan, Janaki Raman; Quintens, Roel; Verslegers, Mieke; Lo, Adrian C.; Govaerts, Kristof; Neefs, Mieke; Leysen, Liselotte; Baatout, Sarah; Maes, Frederik; Himmelreich, Uwe; D'Hooge, Rudi; Moons, Lieve; Benotmane, Mohammed A.

    2016-01-01

    Prenatal irradiation is known to perturb brain development. Epidemiological studies revealed that radiation exposure during weeks 8–15 of pregnancy was associated with an increased occurrence of mental disability and microcephaly. Such neurological deficits were reproduced in animal models, in which rodent behavioral testing is an often used tool to evaluate radiation-induced defective brain functionality. However, up to now, animal studies suggested a threshold dose of around 0.30 Gray (Gy) below which no behavioral alterations can be observed, while human studies hinted at late defects after exposure to doses as low as 0.10 Gy. Here, we acutely irradiated pregnant mice at embryonic day 11 with doses ranging from 0.10 to 1.00 Gy. A thorough investigation of the dose-response relationship of altered brain function and architecture following in utero irradiation was achieved using a behavioral test battery and volumetric 3D T2-weighted magnetic resonance imaging (MRI). We found dose-dependent changes in cage activity, social behavior, anxiety-related exploration, and spatio-cognitive performance. Although behavioral alterations in low-dose exposed animals were mild, we did unveil that both emotionality and higher cognitive abilities were affected in mice exposed to ≥0.10 Gy. Microcephaly was apparent from 0.33 Gy onwards and accompanied by deviations in regional brain volumes as compared to controls. Of note, total brain volume and the relative volume of the ventricles, frontal and posterior cerebral cortex, cerebellum, and striatum were most strongly correlated to altered behavioral parameters. Taken together, we present conclusive evidence for persistent low-dose effects after prenatal irradiation in mice and provide a better understanding of the correlation between their brain size and performance in behavioral tests. PMID:27199692

  10. Increasing the reliability of data analysis of functional magnetic resonance imaging by applying a new blockwise permutation method.

    PubMed

    Adolf, Daniela; Weston, Snezhana; Baecke, Sebastian; Luchtmann, Michael; Bernarding, Johannes; Kropf, Siegfried

    2014-01-01

    A recent paper by Eklund et al. (2012) showed that up to 70% false positive results may occur when analyzing functional magnetic resonance imaging (fMRI) data using the statistical parametric mapping (SPM) software, which may mainly be caused by insufficient compensation for the temporal correlation between successive scans. Here, we show that a blockwise permutation method can be an effective alternative to the standard correction method for the correlated residuals in the general linear model, assuming an AR(1)-model as used in SPM for analyzing fMRI data. The blockwise permutation approach including a random shift developed by our group (Adolf et al., 2011) accounts for the temporal correlation structure of the data without having to provide a specific definition of the underlying autocorrelation model. 1465 publicly accessible resting-state data sets were re-analyzed, and the results were compared with those of Eklund et al. (2012). It was found that with the new permutation method the nominal familywise error rate for the detection of activated voxels could be maintained approximately under even the most critical conditions in which Eklund et al. found the largest deviations from the nominal error level. Thus, the method presented here can serve as a tool to ameliorate the quality and reliability of fMRI data analyses.

  11. DIDA - Dynamic Image Disparity Analysis.

    DTIC Science & Technology

    1982-12-31

    Understanding, Dynamic Image Analysis , Disparity Analysis, Optical Flow, Real-Time Processing ___ 20. ABSTRACT (Continue on revere side If necessary aid identify...three aspects of dynamic image analysis must be studied: effectiveness, generality, and efficiency. In addition, efforts must be made to understand the...environment. A better understanding of the need for these Limiting constraints is required. Efficiency is obviously important if dynamic image analysis is

  12. Functional MRI using regularized parallel imaging acquisition.

    PubMed

    Lin, Fa-Hsuan; Huang, Teng-Yi; Chen, Nan-Kuei; Wang, Fu-Nien; Stufflebeam, Steven M; Belliveau, John W; Wald, Lawrence L; Kwong, Kenneth K

    2005-08-01

    Parallel MRI techniques reconstruct full-FOV images from undersampled k-space data by using the uncorrelated information from RF array coil elements. One disadvantage of parallel MRI is that the image signal-to-noise ratio (SNR) is degraded because of the reduced data samples and the spatially correlated nature of multiple RF receivers. Regularization has been proposed to mitigate the SNR loss originating due to the latter reason. Since it is necessary to utilize static prior to regularization, the dynamic contrast-to-noise ratio (CNR) in parallel MRI will be affected. In this paper we investigate the CNR of regularized sensitivity encoding (SENSE) acquisitions. We propose to implement regularized parallel MRI acquisitions in functional MRI (fMRI) experiments by incorporating the prior from combined segmented echo-planar imaging (EPI) acquisition into SENSE reconstructions. We investigated the impact of regularization on the CNR by performing parametric simulations at various BOLD contrasts, acceleration rates, and sizes of the active brain areas. As quantified by receiver operating characteristic (ROC) analysis, the simulations suggest that the detection power of SENSE fMRI can be improved by regularized reconstructions, compared to unregularized reconstructions. Human motor and visual fMRI data acquired at different field strengths and array coils also demonstrate that regularized SENSE improves the detection of functionally active brain regions.

  13. Functional MRI Using Regularized Parallel Imaging Acquisition

    PubMed Central

    Lin, Fa-Hsuan; Huang, Teng-Yi; Chen, Nan-Kuei; Wang, Fu-Nien; Stufflebeam, Steven M.; Belliveau, John W.; Wald, Lawrence L.; Kwong, Kenneth K.

    2013-01-01

    Parallel MRI techniques reconstruct full-FOV images from undersampled k-space data by using the uncorrelated information from RF array coil elements. One disadvantage of parallel MRI is that the image signal-to-noise ratio (SNR) is degraded because of the reduced data samples and the spatially correlated nature of multiple RF receivers. Regularization has been proposed to mitigate the SNR loss originating due to the latter reason. Since it is necessary to utilize static prior to regularization, the dynamic contrast-to-noise ratio (CNR) in parallel MRI will be affected. In this paper we investigate the CNR of regularized sensitivity encoding (SENSE) acquisitions. We propose to implement regularized parallel MRI acquisitions in functional MRI (fMRI) experiments by incorporating the prior from combined segmented echo-planar imaging (EPI) acquisition into SENSE reconstructions. We investigated the impact of regularization on the CNR by performing parametric simulations at various BOLD contrasts, acceleration rates, and sizes of the active brain areas. As quantified by receiver operating characteristic (ROC) analysis, the simulations suggest that the detection power of SENSE fMRI can be improved by regularized reconstructions, compared to unregularized reconstructions. Human motor and visual fMRI data acquired at different field strengths and array coils also demonstrate that regularized SENSE improves the detection of functionally active brain regions. PMID:16032694

  14. On image analysis in fractography (Methodological Notes)

    NASA Astrophysics Data System (ADS)

    Shtremel', M. A.

    2015-10-01

    As other spheres of image analysis, fractography has no universal method for information convolution. An effective characteristic of an image is found by analyzing the essence and origin of every class of objects. As follows from the geometric definition of a fractal curve, its projection onto any straight line covers a certain segment many times; therefore, neither a time series (one-valued function of time) nor an image (one-valued function of plane) can be a fractal. For applications, multidimensional multiscale characteristics of an image are necessary. "Full" wavelet series break the law of conservation of information.

  15. Learning a cost function for microscope image segmentation.

    PubMed

    Nilufar, Sharmin; Perkins, Theodore J

    2014-01-01

    Quantitative analysis of microscopy images is increasingly important in clinical researchers' efforts to unravel the cellular and molecular determinants of disease, and for pathological analysis of tissue samples. Yet, manual segmentation and measurement of cells or other features in images remains the norm in many fields. We report on a new system that aims for robust and accurate semi-automated analysis of microscope images. A user interactively outlines one or more examples of a target object in a training image. We then learn a cost function for detecting more objects of the same type, either in the same or different images. The cost function is incorporated into an active contour model, which can efficiently determine optimal boundaries by dynamic programming. We validate our approach and compare it to some standard alternatives on three different types of microscopic images: light microscopy of blood cells, light microscopy of muscle tissue sections, and electron microscopy cross-sections of axons and their myelin sheaths.

  16. Advances in noninvasive functional imaging of bone.

    PubMed

    Lan, Sheng-Min; Wu, Ya-Na; Wu, Ping-Ching; Sun, Chi-Kuang; Shieh, Dar-Bin; Lin, Ruey-Mo

    2014-02-01

    The demand for functional imaging in clinical medicine is comprehensive. Although the gold standard for the functional imaging of human bones in clinical settings is still radionuclide-based imaging modalities, nonionizing noninvasive imaging technology in small animals has greatly advanced in recent decades, especially the diffuse optical imaging to which Britton Chance made tremendous contributions. The evolution of imaging probes, instruments, and computation has facilitated exploration in the complicated biomedical research field by allowing longitudinal observation of molecular events in live cells and animals. These research-imaging tools are being used for clinical applications in various specialties, such as oncology, neuroscience, and dermatology. The Bone, a deeply located mineralized tissue, presents a challenge for noninvasive functional imaging in humans. Using nanoparticles (NP) with multiple favorable properties as bioimaging probes has provided orthopedics an opportunity to benefit from these noninvasive bone-imaging techniques. This review highlights the historical evolution of radionuclide-based imaging, computed tomography, positron emission tomography, and magnetic resonance imaging, diffuse optics-enabled in vivo technologies, vibrational spectroscopic imaging, and a greater potential for using NPs for biomedical imaging.

  17. Imaging The Flat Slab Beneath The Sierras Pampeanas, Argentina, Using Receiver Function Analysis: Evidence For Overthickened Subducted Oceanic Crust

    NASA Astrophysics Data System (ADS)

    Gans, C.; Beck, S. L.; Zandt, G.; Gilbert, H. J.; Alvarado, P. M.; Linkimer, L.; Porter, R. C.

    2009-12-01

    The western margin of the South American continent between 30°and 32° S is characterized by the flat slab subduction of the ~43 Ma oceanic Nazca plate beneath the continental South American plate. Several arrays of broadband seismic instruments have been deployed in Chile and western Argentina to study this phenomenon (e.g., CHARGE, 2000-2002; SIEMBRA, 2007-2009; ESP, 2008-2010). The low angle subduction has prevented magmatism in the area since the late Miocene due to reduced mantle flow above the subducting slab, and spatially correlates with the formation of both thick-skinned (Sierras Pampeanas) and thin-skinned (Andean Precordillera) thrust belts within the region. In order to better constrain the crust and upper mantle structure in the transition region between flat slab and normal subduction to the south and east, we have calculated receiver functions (RFs) from teleseismic earthquakes. Using our dense SIEMBRA array, combined with the broader CHARGE and ESP arrays, we are able to image in detail the flat slab, which contains a distinct negative arrival (indicative of a low velocity zone) at the top of the flat slab, followed by a strong positive P-to-S conversion. While the exact causes of flat slab subduction continue to be debated, one overriding theme is the necessity of having an overthickened crust in order to increase the buoyancy of the subducting slab. In this region, the hotspot seamount chain of the Juan Fernandez Ridge (JFR) is thought to provide such a mechanism. Kopp et al. (2004), however, did not find overthickened crust in the offshore portion of the JFR, but rather moderately thick oceanic crust. Preliminary results from our receiver functions, compared with synthetic RFs containing either a normal (7 km) or an overthickened (17km) crust, indicate that the oceanic crust at the top of the slab (the low velocity zone) must be at least ~15 km thick. Our results support the idea of an overthickened crust in the subducted flat slab beneath

  18. Functional Magnetic Resonance Imaging and Pediatric Anxiety

    ERIC Educational Resources Information Center

    Pine, Daniel S.; Guyer, Amanda E.; Leibenluft, Ellen; Peterson, Bradley S.; Gerber, Andrew

    2008-01-01

    The use of functional magnetic resonance imaging in investigating pediatric anxiety disorders is studied. Functional magnetic resonance imaging can be utilized in demonstrating parallels between the neural architecture of difference in anxiety of humans and the neural architecture of attention-orienting behavior in nonhuman primates or rodents.…

  19. Functional CT imaging of prostate cancer

    NASA Astrophysics Data System (ADS)

    Henderson, Elizabeth; Milosevic, Michael F.; Haider, Masoom A.; Yeung, Ivan W. T.

    2003-09-01

    The purpose of this paper is to investigate the distribution of blood flow (F), mean capillary transit time (Tc), capillary permeability (PS) and blood volume (vb) in prostate cancer using contrast-enhanced CT. Nine stage T2-T3 prostate cancer patients were enrolled in the study. Following bolus injection of a contrast agent, a time series of CT images of the prostate was acquired. Functional maps showing the distribution of F, Tc, PS and vb within the prostate were generated using a distributed parameter tracer kinetic model, the adiabatic approximation to the tissue homogeneity model. The precision of the maps was assessed using covariance matrix analysis. Finally, maps were compared to the findings of standard clinical investigations. Eight of the functional maps demonstrated regions of increased F, PS and vb, the locations of which were consistent with the results of standard clinical investigations. However, model parameters other than F could only be measured precisely within regions of high F. In conclusion functional CT images of cancer-containing prostate glands demonstrate regions of elevated F, PS and vb. However, caution should be used when applying a complex tracer kinetic model to the study of prostate cancer since not all parameters can be measured precisely in all areas.

  20. Longitudinal Functional Data Analysis.

    PubMed

    Park, So Young; Staicu, Ana-Maria

    We consider dependent functional data that are correlated because of a longitudinal-based design: each subject is observed at repeated times and at each time a functional observation (curve) is recorded. We propose a novel parsimonious modeling framework for repeatedly observed functional observations that allows to extract low dimensional features. The proposed methodology accounts for the longitudinal design, is designed to study the dynamic behavior of the underlying process, allows prediction of full future trajectory, and is computationally fast. Theoretical properties of this framework are studied and numerical investigations confirm excellent behavior in finite samples. The proposed method is motivated by and applied to a diffusion tensor imaging study of multiple sclerosis.

  1. Reflections on ultrasound image analysis.

    PubMed

    Alison Noble, J

    2016-10-01

    Ultrasound (US) image analysis has advanced considerably in twenty years. Progress in ultrasound image analysis has always been fundamental to the advancement of image-guided interventions research due to the real-time acquisition capability of ultrasound and this has remained true over the two decades. But in quantitative ultrasound image analysis - which takes US images and turns them into more meaningful clinical information - thinking has perhaps more fundamentally changed. From roots as a poor cousin to Computed Tomography (CT) and Magnetic Resonance (MR) image analysis, both of which have richer anatomical definition and thus were better suited to the earlier eras of medical image analysis which were dominated by model-based methods, ultrasound image analysis has now entered an exciting new era, assisted by advances in machine learning and the growing clinical and commercial interest in employing low-cost portable ultrasound devices outside traditional hospital-based clinical settings. This short article provides a perspective on this change, and highlights some challenges ahead and potential opportunities in ultrasound image analysis which may both have high impact on healthcare delivery worldwide in the future but may also, perhaps, take the subject further away from CT and MR image analysis research with time.

  2. Spreadsheet-Like Image Analysis

    DTIC Science & Technology

    1992-08-01

    1 " DTIC AD-A254 395 S LECTE D, ° AD-E402 350 Technical Report ARPAD-TR-92002 SPREADSHEET-LIKE IMAGE ANALYSIS Paul Willson August 1992 U.S. ARMY...August 1992 4. TITLE AND SUBTITLE 5. FUNDING NUMBERS SPREADSHEET-LIKE IMAGE ANALYSIS 6. AUTHOR(S) Paul Willson 7. PERFORMING ORGANIZATION NAME(S) AND...14. SUBJECT TERMS 15. NUMBER OF PAGES Image analysis , nondestructive inspection, spreadsheet, Macintosh software, 14 neural network, signal processing

  3. Knowledge-Based Image Analysis.

    DTIC Science & Technology

    1981-04-01

    UNCLASSIF1 ED ETL-025s N IIp ETL-0258 AL Ai01319 S"Knowledge-based image analysis u George C. Stockman Barbara A. Lambird I David Lavine Laveen N. Kanal...extraction, verification, region classification, pattern recognition, image analysis . 3 20. A. CT (Continue on rever.. d. It necessary and Identify by...UNCLgSTFTF n In f SECURITY CLASSIFICATION OF THIS PAGE (When Date Entered) .L1 - I Table of Contents Knowledge Based Image Analysis I Preface

  4. Functional imaging for prostate cancer: therapeutic implications.

    PubMed

    Mari Aparici, Carina; Seo, Youngho

    2012-09-01

    Functional radionuclide imaging modalities, now commonly combined with anatomical imaging modalities computed tomography (CT) or magnetic resonance imaging (single photon emission computed tomography [SPECT]/CT, positron emission tomography [PET]/CT, and PET/magnetic resonance imaging), are promising tools for the management of prostate cancer, particularly for therapeutic implications. Sensitive detection capability of prostate cancer using these imaging modalities is one issue; however, the treatment of prostate cancer using the information that can be obtained from functional radionuclide imaging techniques is another challenging area. There are not many SPECT or PET radiotracers that can cover the full spectrum of the management of prostate cancer from initial detection to staging, prognosis predictor, and all the way to treatment response assessment. However, when used appropriately, the information from functional radionuclide imaging improves, and sometimes significantly changes, the whole course of the cancer management. The limitations of using SPECT and PET radiotracers with regard to therapeutic implications are not so much different from their limitations solely for the task of detecting prostate cancer; however, the specific imaging target and how this target is reliably imaged by SPECT and PET can potentially make significant impact in the treatment of prostate cancer. Finally, although the localized prostate cancer is considered manageable, there is still significant need for improvement in noninvasive imaging of metastatic prostate cancer, in treatment guidance, and in response assessment from functional imaging, including radionuclide-based techniques. In this review article, we present the rationale of using functional radionuclide imaging and the therapeutic implications for each of radionuclide imaging agent that have been studied in human subjects.

  5. Spreadsheet-like image analysis

    NASA Astrophysics Data System (ADS)

    Wilson, Paul

    1992-08-01

    This report describes the design of a new software system being built by the Army to support and augment automated nondestructive inspection (NDI) on-line equipment implemented by the Army for detection of defective manufactured items. The new system recalls and post-processes (off-line) the NDI data sets archived by the on-line equipment for the purpose of verifying the correctness of the inspection analysis paradigms, of developing better analysis paradigms and to gather statistics on the defects of the items inspected. The design of the system is similar to that of a spreadsheet, i.e., an array of cells which may be programmed to contain functions with arguments being data from other cells and whose resultant is the output of that cell's function. Unlike a spreadsheet, the arguments and the resultants of a cell may be a matrix such as a two-dimensional matrix of picture elements (pixels). Functions include matrix mathematics, neural networks and image processing as well as those ordinarily found in spreadsheets. The system employs all of the common environmental supports of the Macintosh computer, which is the hardware platform. The system allows the resultant of a cell to be displayed in any of multiple formats such as a matrix of numbers, text, an image, or a chart. Each cell is a window onto the resultant. Like a spreadsheet if the input value of any cell is changed its effect is cascaded into the resultants of all cells whose functions use that value directly or indirectly. The system encourages the user to play what-of games, as ordinary spreadsheets do.

  6. Clinical applications of functional MR imaging.

    PubMed

    Belyaev, Artem S; Peck, Kyung K; Brennan, Nicole M Petrovich; Holodny, Andrei I

    2013-05-01

    Functional magnetic resonance (fMR) imaging for neurosurgical planning has become the standard of care in centers where it is available. Although paradigms to measure eloquent cortices are not yet standardized, simple tasks elicit reliable maps for planning neurosurgical procedures. A patient-specific paradigm design will refine the usability of fMR imaging for prognostication and recovery of function. Certain pathologic conditions and technical issues limit the interpretation of fMR imaging maps in clinical use and should be considered carefully. However, fMR imaging for neurosurgical planning continues to provide insights into how the brain works and how it responds to pathologic insults.

  7. Analysis of dynamic brain imaging data.

    PubMed Central

    Mitra, P P; Pesaran, B

    1999-01-01

    Modern imaging techniques for probing brain function, including functional magnetic resonance imaging, intrinsic and extrinsic contrast optical imaging, and magnetoencephalography, generate large data sets with complex content. In this paper we develop appropriate techniques for analysis and visualization of such imaging data to separate the signal from the noise and characterize the signal. The techniques developed fall into the general category of multivariate time series analysis, and in particular we extensively use the multitaper framework of spectral analysis. We develop specific protocols for the analysis of fMRI, optical imaging, and MEG data, and illustrate the techniques by applications to real data sets generated by these imaging modalities. In general, the analysis protocols involve two distinct stages: "noise" characterization and suppression, and "signal" characterization and visualization. An important general conclusion of our study is the utility of a frequency-based representation, with short, moving analysis windows to account for nonstationarity in the data. Of particular note are 1) the development of a decomposition technique (space-frequency singular value decomposition) that is shown to be a useful means of characterizing the image data, and 2) the development of an algorithm, based on multitaper methods, for the removal of approximately periodic physiological artifacts arising from cardiac and respiratory sources. PMID:9929474

  8. Spotlight-8 Image Analysis Software

    NASA Technical Reports Server (NTRS)

    Klimek, Robert; Wright, Ted

    2006-01-01

    Spotlight is a cross-platform GUI-based software package designed to perform image analysis on sequences of images generated by combustion and fluid physics experiments run in a microgravity environment. Spotlight can perform analysis on a single image in an interactive mode or perform analysis on a sequence of images in an automated fashion. Image processing operations can be employed to enhance the image before various statistics and measurement operations are performed. An arbitrarily large number of objects can be analyzed simultaneously with independent areas of interest. Spotlight saves results in a text file that can be imported into other programs for graphing or further analysis. Spotlight can be run on Microsoft Windows, Linux, and Apple OS X platforms.

  9. Functional imaging in tumor-associated lymphatics

    NASA Astrophysics Data System (ADS)

    Kwon, Sunkuk; Sevick-Muraca, Eva M.

    2011-03-01

    The lymphatic system plays an important role in cancer cell dissemination; however whether lymphatic drainage pathways and function change during tumor progression and metastasis remains to be elucidated. In this report, we employed a non-invasive, dynamic near-infrared (NIR) fluorescence imaging technique for functional lymphatic imaging. Indocyanine green (ICG) was intradermally injected into tumor-free mice and mice bearing C6/LacZ rat glioma tumors in the tail or hindlimb. Our imaging data showed abnormal lymphatic drainage pathways and reduction/loss of lymphatic contractile function in mice with lymph node (LN) metastasis, indicating that cancer metastasis to the draining LNs is accompanied by transient changes of the lymphatic architectural network and its function. Therefore, functional lymphatic imaging may provide a role in the clinical staging of cancer.

  10. Conflict Processing in the Rat Brain: Behavioral Analysis and Functional μPET Imaging Using [F]Fluorodeoxyglucose.

    PubMed

    Marx, Christine; Lex, Björn; Calaminus, Carsten; Hauber, Wolfgang; Backes, Heiko; Neumaier, Bernd; Mies, Günter; Graf, Rudolf; Endepols, Heike

    2012-01-01

    Conflicts in spatial stimulus-response tasks occur when the task-relevant feature of a stimulus implies a response toward a certain location which does not match the location of stimulus presentation. This conflict leads to increased error rates and longer reaction times, which has been termed Simon effect. A model of dual route processing (automatic and intentional) of stimulus features has been proposed, predicting response conflicts if the two routes are incongruent. Although there is evidence that the prefrontal cortex, notably the anterior cingulate cortex (ACC), plays a crucial role in conflict processing, the neuronal basis of dual route architecture is still unknown. In this study, we pursue a novel approach using positron emission tomography (PET) to identify relevant brain areas in a rat model of an auditory Simon task, a neuropsychological interference task, which is commonly used to study conflict processing in humans. For combination with PET we used the metabolic tracer [(18)F]fluorodeoxyglucose, which accumulates in metabolically active brain cells during the behavioral task. Brain areas involved in conflict processing are supposed to be activated when automatic and intentional route processing lead to different responses (dual route model). Analysis of PET data revealed specific activation patterns for different task settings applicable to the dual route model as established for response conflict processing. The rat motor cortex (M1) may be part of the automatic route or involved in its facilitation, while premotor (M2), prelimbic, and ACC seemed to be essential for inhibiting the incorrect, automatic response, indicating conflict monitoring functions. Our findings and the remarkable similarities to the pattern of activated regions reported during conflict processing in humans demonstrate that our rodent model opens novel opportunities to investigate the anatomical basis of conflict processing and dual route architecture.

  11. Group analysis and the subject factor in functional magnetic resonance imaging: analysis of fifty right-handed healthy subjects in a semantic language task.

    PubMed

    Seghier, Mohamed L; Lazeyras, François; Pegna, Alan J; Annoni, Jean-Marie; Khateb, Asaid

    2008-04-01

    Before considering a given fMRI paradigm as a valid clinical tool, one should first assess the reliability of functional responses across subjects by establishing a normative database and defining a reference activation map that identifies major brain regions involved in the task at hand. However, the definition of such a reference map can be hindered by inter-individual functional variability. In this study, we analysed functional data obtained from 50 healthy subjects during a semantic language task to assess the influence of the number of subjects on the reference map and to characterise inter-individual functional variability. We first compared different group analysis approaches and showed that the extent of the activated network depends not only on the choice of the analysis approach but also on the statistical threshold used and the number of subjects included. This analysis suggested that, while the RFX analysis is suitable to detect confidently true positive activations, the other group approaches are useful for exploratory investigations in small samples. The application of quantitative measures at the voxel and regional levels suggested that while approximately 15-20 subjects were sufficient to reveal reliable and robust left hemisphere activations, >30 subjects were necessary for revealing more variable and weak right hemisphere ones. Finally, to visualise inter-individual variability, we combined two similarity indices that assess the percentages of true positive and false negative voxels in individual activation patterns relative to the group map. We suggest that these measures can be used for the estimation of the degree of 'normality' of functional responses in brain-damaged patients, where this question is often raised, and recommend the use of different quantifications to appreciate accurately the inter-individual functional variability that can be incorporated in group maps.

  12. Functional Extended Redundancy Analysis

    ERIC Educational Resources Information Center

    Hwang, Heungsun; Suk, Hye Won; Lee, Jang-Han; Moskowitz, D. S.; Lim, Jooseop

    2012-01-01

    We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous…

  13. Meta-analysis of functional magnetic resonance imaging studies of timing and cognitive control in schizophrenia and bipolar disorder: Evidence of a primary time deficit.

    PubMed

    Alústiza, Irene; Radua, Joaquim; Pla, Marta; Martin, Raquel; Ortuño, Felipe

    2017-02-03

    Schizophrenia (SZ) and Bipolar Disorder (BD) are associated with deficits in both timing and cognitive control functions. However, the underlying neurological dysfunctions remain poorly understood. The main goal of this study was to identify brain structures activated both by increases in cognitive activity and during timing tasks in patients with SZ and BD relative to controls. We conducted two signed differential mapping (SDM) meta-analyses of functional magnetic resonance imaging studies assessing the brain response to increasing levels of cognitive difficulty: one concerned SZ, and the other BD patients. We conducted a similar SDM meta-analysis on neuroimaging of timing in SZ (no studies in BD could be included). Finally, we carried out a multimodal meta-analysis to identify common brain regions in the findings of the two previous meta-analyses. We found that SZ patients showed hypoactivation in timing-related cortical-subcortical areas. The dysfunction observed during timing partially coincided with deficits for cognitive control functions. We hypothesize that a dysfunctional temporal/cognitive control network underlies the persistent cognitive impairment observed in SZ.

  14. Oncological image analysis: medical and molecular image analysis

    NASA Astrophysics Data System (ADS)

    Brady, Michael

    2007-03-01

    This paper summarises the work we have been doing on joint projects with GE Healthcare on colorectal and liver cancer, and with Siemens Molecular Imaging on dynamic PET. First, we recall the salient facts about cancer and oncological image analysis. Then we introduce some of the work that we have done on analysing clinical MRI images of colorectal and liver cancer, specifically the detection of lymph nodes and segmentation of the circumferential resection margin. In the second part of the paper, we shift attention to the complementary aspect of molecular image analysis, illustrating our approach with some recent work on: tumour acidosis, tumour hypoxia, and multiply drug resistant tumours.

  15. Processing of food, body and emotional stimuli in anorexia nervosa: a systematic review and meta-analysis of functional magnetic resonance imaging studies.

    PubMed

    Zhu, Yikang; Hu, Xiaochen; Wang, Jijun; Chen, Jue; Guo, Qian; Li, Chunbo; Enck, Paul

    2012-11-01

    The characteristics of the cognitive processing of food, body and emotional information in patients with anorexia nervosa (AN) are debatable. We reviewed functional magnetic resonance imaging studies to assess whether there were consistent neural basis and networks in the studies to date. Searching PubMed, Ovid, Web of Science, The Cochrane Library and Google Scholar between January 1980 and May 2012, we identified 17 relevant studies. Activation likelihood estimation was used to perform a quantitative meta-analysis of functional magnetic resonance imaging studies. For both food stimuli and body stimuli, AN patients showed increased hemodynamic response in the emotion-related regions (frontal, caudate, uncus, insula and temporal) and decreased activation in the parietal region. Although no robust brain activation has been found in response to emotional stimuli, emotion-related neural networks are involved in the processing of food and body stimuli among AN. It suggests that negative emotional arousal is related to cognitive processing bias of food and body stimuli in AN.

  16. Incorporating Functional Imaging Information into rpFNA Analysis for Breast Cancer Detection in High Risk Women

    DTIC Science & Technology

    2009-03-01

    Therefore, it has been decided that GEANT4 , a computer modeling and simulation code, should be used to first test different design ideas in a...controlled setting. Installing GEANT4 required a systems update for our computer operating system and downloading supporting software, such as a new C...complier. These tasks have been completed and I am currently learning the GEANT4 software. Task 3: Optimize patient imaging and biopsy protocol

  17. Hyperspectral image analysis. A tutorial.

    PubMed

    Amigo, José Manuel; Babamoradi, Hamid; Elcoroaristizabal, Saioa

    2015-10-08

    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case.

  18. Tutte polynomial in functional magnetic resonance imaging

    NASA Astrophysics Data System (ADS)

    García-Castillón, Marlly V.

    2015-09-01

    Methods of graph theory are applied to the processing of functional magnetic resonance images. Specifically the Tutte polynomial is used to analyze such kind of images. Functional Magnetic Resonance Imaging provide us connectivity networks in the brain which are represented by graphs and the Tutte polynomial will be applied. The problem of computing the Tutte polynomial for a given graph is #P-hard even for planar graphs. For a practical application the maple packages "GraphTheory" and "SpecialGraphs" will be used. We will consider certain diagram which is depicting functional connectivity, specifically between frontal and posterior areas, in autism during an inferential text comprehension task. The Tutte polynomial for the resulting neural networks will be computed and some numerical invariants for such network will be obtained. Our results show that the Tutte polynomial is a powerful tool to analyze and characterize the networks obtained from functional magnetic resonance imaging.

  19. Comparison and combination of scaling index method and Minkowski functionals in the analysis of high resolution magnetic resonance images of the distal radius in vitro

    NASA Astrophysics Data System (ADS)

    Sidorenko, Irina N.; Bauer, Jan; Monetti, Roberto; Mueller, Dirk; Rummeny, Ernst J.; Eckstein, Felix; Raeth, Christoph W.

    2008-03-01

    High resolution magnetic resonance (HRMR) imaging can reveal major characteristics of trabecular bone. The quantification of this trabecular micro architecture can be useful for better understanding the progression of osteoporosis and improve its diagnosis. In the present work we applied the scaling index method (SIM) and Minkowski Functionals (MF) for analysing tomographic images of distal radius specimens in vitro. For both methods, the correlation with the maximum compressive strength (MCS) as determined in a biomechanical test and the diagnostic performance with regard to the spine fracture status were calculated. Both local SIM and global MF methods showed significantly better results compared to bone mineral density measured by quantitative computed tomography. The receiver operating characteristic analysis for differentiating fractured and non-fractured subjects revealed area under the curve (AUC) values of 0.716 for BMD, 0.897 for SIM and 0.911 for MF. The correlation coefficients with MCS were 0.6771 for BMD, 0.843 for SIM and 0.772 for MF. We simulated the effect of perturbations, namely noise effects and intensity variations. Overall, MF method was more sensitive to noise than SIM. A combination of SIM and MF methods could, however, increase AUC values from 0.85 to 0.89 and correlation coefficients from 0.71 to 0.82. In conclusion, local SIM and global MF techniques can successfully be applied for analysing HRMR image data. Since these methods are complementary, their combination offers a new possibility of describing MR images of the trabecular bone, especially noisy ones.

  20. An Analysis of Whole Body Tracer Kinetics in Dynamic PET Studies With Application to Image-Based Blood Input Function Extraction

    PubMed Central

    Huang, Jian; O’Sullivan, Finbarr

    2014-01-01

    In a positron emission tomography (PET) study, the local uptake of the tracer is dependent on vascular delivery and retention. For dynamic studies the measured uptake time-course information can be best interpreted when knowledge of the time-course of tracer in the blood is available. This is certainly true for the most established tracers such as 18F-Fluorodeoxyglucose (FDG) and 15O-Water (H2O). Since direct sampling of blood as part of PET studies is increasingly impractical, there is ongoing interest in image-extraction of blood time-course information. But analysis of PET-measured blood pool signals is complicated because they will typically involve a combination of arterial, venous and tissue information. Thus, a careful appreciation of these components is needed to interpret the available data. To facilitate this process, we propose a novel Markov chain model for representation of the circulation of a tracer atom in the body. The model represents both arterial and venous time-course patterns. Under reasonable conditions equilibration of tracer activity in arterial and venous blood is achieved by the end of the PET study—consistent with empirical measurement. Statistical inference for Markov model parameters is a challenge. A penalized nonlinear least squares process, incorporating a generalized cross-validation score, is proposed. Random effects analysis is used to adaptively specify the structure of the penalty function based on historical samples of directly measured blood data. A collection of arterially sampled data from PET studies with FDG and H2O is used to illustrate the methodology. These data analyses are highly supportive of the overall modeling approach. An adaptation of the model to the problem of extraction of arterial blood signals from imaging data is also developed and promising preliminary results for cerebral and thoracic imaging studies with FDG and H2O are obtained. PMID:24770914

  1. Subband/transform functions for image processing

    NASA Technical Reports Server (NTRS)

    Glover, Daniel

    1993-01-01

    Functions for image data processing written for use with the MATLAB(TM) software package are presented. These functions provide the capability to transform image data with block transformations (such as the Walsh Hadamard) and to produce spatial frequency subbands of the transformed data. Block transforms are equivalent to simple subband systems. The transform coefficients are reordered using a simple permutation to give subbands. The low frequency subband is a low resolution version of the original image, while the higher frequency subbands contain edge information. The transform functions can be cascaded to provide further decomposition into more subbands. If the cascade is applied to all four of the first stage subbands (in the case of a four band decomposition), then a uniform structure of sixteen bands is obtained. If the cascade is applied only to the low frequency subband, an octave structure of seven bands results. Functions for the inverse transforms are also given. These functions can be used for image data compression systems. The transforms do not in themselves produce data compression, but prepare the data for quantization and compression. Sample quantization functions for subbands are also given. A typical compression approach is to subband the image data, quantize it, then use statistical coding (e.g., run-length coding followed by Huffman coding) for compression. Contour plots of image data and subbanded data are shown.

  2. Radiologist and automated image analysis

    NASA Astrophysics Data System (ADS)

    Krupinski, Elizabeth A.

    1999-07-01

    Significant advances are being made in the area of automated medical image analysis. Part of the progress is due to the general advances being made in the types of algorithms used to process images and perform various detection and recognition tasks. A more important reason for this growth in medical image analysis processes, may be due however to a very different reason. The use of computer workstations, digital image acquisition technologies and the use of CRT monitors for display of medical images for primary diagnostic reading is becoming more prevalent in radiology departments around the world. With the advance in computer- based displays, however, has come the realization that displaying images on a CRT monitor is not the same as displaying film on a viewbox. There are perceptual, cognitive and ergonomic issues that must be considered if radiologists are to accept this change in technology and display. The bottom line is that radiologists' performance must be evaluated with these new technologies and image analysis techniques in order to verify that diagnostic performance is at least as good with these new technologies and image analysis procedures as with film-based displays. The goal of this paper is to address some of the perceptual, cognitive and ergonomic issues associated with reading radiographic images from digital displays.

  3. Depth sensitivity analysis of functional near-infrared spectroscopy measurement using three-dimensional Monte Carlo modelling-based magnetic resonance imaging.

    PubMed

    Mansouri, Chemseddine; L'huillier, Jean-Pierre; Kashou, Nasser H; Humeau, Anne

    2010-05-01

    Theoretical analysis of spatial distribution of near-infrared light propagation in head tissues is very important in brain function measurement, since it is impossible to measure the effective optical path length of the detected signal or the effect of optical fibre arrangement on the regions of measurement or its sensitivity. In this study a realistic head model generated from structure data from magnetic resonance imaging (MRI) was introduced into a three-dimensional Monte Carlo code and the sensitivity of functional near-infrared measurement was analysed. The effects of the distance between source and detector, and of the optical properties of the probed tissues, on the sensitivity of the optical measurement to deep layers of the adult head were investigated. The spatial sensitivity profiles of photons in the head, the so-called banana shape, and the partial mean optical path lengths in the skin-scalp and brain tissues were calculated, so that the contribution of different parts of the head to near-infrared spectroscopy signals could be examined. It was shown that the signal detected in brain function measurements was greatly affected by the heterogeneity of the head tissue and its scattering properties, particularly for the shorter interfibre distances.

  4. Functional magnetic resonance imaging studies of language.

    PubMed

    Small, Steven L; Burton, Martha W

    2002-11-01

    Functional neuroimaging of language builds on almost 150 years of study in neurology, psychology, linguistics, anatomy, and physiology. In recent years, there has been an explosion of research using functional imaging technology, especially positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), to understand the relationship between brain mechanisms and language processing. These methods combine high-resolution anatomic images with measures of language-specific brain activity to reveal neural correlates of language processing. This article reviews some of what has been learned about the neuroanatomy of language from these imaging techniques. We first discuss the normal case, organizing the presentation according to the levels of language, encompassing words (lexicon), sound structure (phonemes), and sentences (syntax and semantics). Next, we delve into some unusual language processing circumstances, including second languages and sign languages. Finally, we discuss abnormal language processing, including developmental and acquired dyslexia and aphasia.

  5. Fourier analysis: from cloaking to imaging

    NASA Astrophysics Data System (ADS)

    Wu, Kedi; Cheng, Qiluan; Wang, Guo Ping

    2016-04-01

    Regarding invisibility cloaks as an optical imaging system, we present a Fourier approach to analytically unify both Pendry cloaks and complementary media-based invisibility cloaks into one kind of cloak. By synthesizing different transfer functions, we can construct different devices to realize a series of interesting functions such as hiding objects (events), creating illusions, and performing perfect imaging. In this article, we give a brief review on recent works of applying Fourier approach to analysis invisibility cloaks and optical imaging through scattering layers. We show that, to construct devices to conceal an object, no constructive materials with extreme properties are required, making most, if not all, of the above functions realizable by using naturally occurring materials. As instances, we experimentally verify a method of directionally hiding distant objects and create illusions by using all-dielectric materials, and further demonstrate a non-invasive method of imaging objects completely hidden by scattering layers.

  6. Functional magnetic resonance imaging: imaging techniques and contrast mechanisms.

    PubMed Central

    Howseman, A M; Bowtell, R W

    1999-01-01

    Functional magnetic resonance imaging (fMRI) is a widely used technique for generating images or maps of human brain activity. The applications of the technique are widespread in cognitive neuroscience and it is hoped they will eventually extend into clinical practice. The activation signal measured with fMRI is predicated on indirectly measuring changes in the concentration of deoxyhaemoglobin which arise from an increase in blood oxygenation in the vicinity of neuronal firing. The exact mechanisms of this blood oxygenation level dependent (BOLD) contrast are highly complex. The signal measured is dependent on both the underlying physiological events and the imaging physics. BOLD contrast, although sensitive, is not a quantifiable measure of neuronal activity. A number of different imaging techniques and parameters can be used for fMRI, the choice of which depends on the particular requirements of each functional imaging experiment. The high-speed MRI technique, echo-planar imaging provides the basis for most fMRI experiments. The problems inherent to this method and the ways in which these may be overcome are particularly important in the move towards performing functional studies on higher field MRI systems. Future developments in techniques and hardware are also likely to enhance the measurement of brain activity using MRI. PMID:10466145

  7. Histopathological Image Analysis: A Review

    PubMed Central

    Gurcan, Metin N.; Boucheron, Laura; Can, Ali; Madabhushi, Anant; Rajpoot, Nasir; Yener, Bulent

    2010-01-01

    Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement to the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe. PMID:20671804

  8. Meta-analysis of functional magnetic resonance imaging studies of inhibition and attention in attention-deficit/hyperactivity disorder: exploring task-specific, stimulant medication, and age effects.

    PubMed

    Hart, Heledd; Radua, Joaquim; Nakao, Tomohiro; Mataix-Cols, David; Rubia, Katya

    2013-02-01

    CONTEXT Functional magnetic resonance imaging studies in attention-deficit/hyperactivity disorder (ADHD) revealed fronto-striato-parietal dysfunctions during tasks of inhibition and attention. However, it is unclear whether task-dissociated dysfunctions exist and to what extent they may be influenced by age and by long-term stimulant medication use. OBJECTIVE To conduct a meta-analysis of functional magnetic resonance imaging studies in ADHD during inhibition and attention tasks, exploring age and long-term stimulant medication use effects. DATA SOURCES PubMed, ScienceDirect, Web of Knowledge, Google Scholar, and Scopus databases were searched up to May 2012 for meta-analyses. Meta-regression methods explored age and long-term stimulant medication use effects. STUDY SELECTION Twenty-one data sets were included for inhibition (287 patients with ADHD and 320 control subjects), and 13 data sets were included for attention (171 patients with ADHD and 178 control subjects). DATA EXTRACTION Peak coordinates of clusters of significant group differences, as well as demographic, clinical, and methodological variables, were extracted for each study or were obtained from the authors. DATA SYNTHESIS Patients with ADHD relative to controls showed reduced activation for inhibition in the right inferior frontal cortex, supplementary motor area, and anterior cingulate cortex, as well as striato-thalamic areas, and showed reduced activation for attention in the right dorsolateral prefrontal cortex, posterior basal ganglia, and thalamic and parietal regions. Furthermore, the meta-regression analysis for the attention domain showed that long-term stimulant medication use was associated with more similar right caudate activation relative to controls. Age effects could be analyzed only for the inhibition meta-analysis, showing that the supplementary motor area and basal ganglia were underactivated solely in children with ADHD relative to controls, while the inferior frontal cortex and

  9. Abnormalities of localized connectivity in schizophrenia patients and their unaffected relatives: a meta-analysis of resting-state functional magnetic resonance imaging studies

    PubMed Central

    Xiao, Bo; Wang, Shuai; Liu, Jianbo; Meng, Tiantian; He, Yuqiong; Luo, Xuerong

    2017-01-01

    Objective The localized dysfunction of specialized brain regions in schizophrenia patients and their unaffected relatives has been identified in a large-scale brain network; however, evidence is inconsistent. We aimed to identify abnormalities in the localized connectivity in schizophrenia patients and their relatives by conducting a meta-analysis of regional homogeneity (ReHo) studies. Methods Fourteen studies on resting-state functional magnetic resonance imaging, with 316 schizophrenia patients, 342 healthy controls, and 66 unaffected relatives, were included in the meta-analysis. This analysis was performed using anisotropic effect-size-based signed differential mapping software. Results Schizophrenia patients showed increased ReHo in right superior frontal gyrus and right superior temporal gyrus, as well as decreased ReHo in left fusiform gyrus, left superior temporal gyrus, left postcentral gyrus, and right precentral gyrus. Unaffected relatives showed decreased ReHo in right insula and right superior temporal gyrus. These results remained widely unchanged in both sensitivity and subgroup analyses. Conclusion Schizophrenia patients and their unaffected relatives had extensive abnormal localized connectivity in cerebrum, especially in superior temporal gyrus, which were the potential diagnostic markers and expounded the pathophysiological hypothesis for the disorder. PMID:28243099

  10. Functional minimization problems in image processing

    NASA Astrophysics Data System (ADS)

    Kim, Yunho; Vese, Luminita A.

    2008-02-01

    In this work we wish to recover an unknown image from a blurry version. We solve this inverse problem by energy minimization and regularization. We seek a solution of the form u + v, where u is a function of bounded variation (cartoon component), while v is an oscillatory component (texture), modeled by a Sobolev function with negative degree of differentiability. Experimental results show that this cartoon + texture model better recovers textured details in natural images, by comparison with the more standard models where the unknown is restricted only to the space of functions of bounded variation.

  11. Multimodal Imaging of Dynamic Functional Connectivity

    PubMed Central

    Tagliazucchi, Enzo; Laufs, Helmut

    2015-01-01

    The study of large-scale functional interactions in the human brain with functional magnetic resonance imaging (fMRI) extends almost to the first applications of this technology. Due to historical reasons and preconceptions about the limitations of this brain imaging method, most studies have focused on assessing connectivity over extended periods of time. It is now clear that fMRI can resolve the temporal dynamics of functional connectivity, like other faster imaging techniques such as electroencephalography and magnetoencephalography (albeit on a different temporal scale). However, the indirect nature of fMRI measurements can hinder the interpretability of the results. After briefly summarizing recent advances in the field, we discuss how the simultaneous combination of fMRI with electrophysiological activity measurements can contribute to a better understanding of dynamic functional connectivity in humans both during rest and task, wakefulness, and other brain states. PMID:25762977

  12. Imaging and Functional Analysis of γ-Secretase and Substrate in a Proteolipobead System with an Activity-Based Probe

    PubMed Central

    Gilchrist, M. Lane; Ahn, Kwangwook; Li, Yue-Ming

    2016-01-01

    Investigation of intramembranal protease catalysis demands the generation of intact biomembrane assemblies with structural integrity and lateral mobility. Here, we report the development of a microsphere supported-biomembrane platform enabling characterization of γ-secretase and substrate within proteolipobead assemblies via microscopy and flow cytometry. The active enzyme loading levels were tracked using an activity-based probe, with the biomembranes delineated by carbocyanine lipid reporters. Proteolipobeads formed from HeLa proteoliposomes gave rise to homogeneous distributions of active γ-secretase within supported biomembranes with native-like fluidity. The substrate loading into supported biomembranes was detergent-dependent, as evidenced by even colocalization of substrate and lipid tracers in confocal 3D imaging of individual proteolipobeads. Moreover, the loading level was tunable with bulk substrate concentration. γ-Secretase substrate cleavage and its inhibition within γ-secretase proteolipobeads were observed. This platform offers a means to visualize enzyme and substrate loading, activity, and inhibition in a controllable biomembrane microenvironment. PMID:26699370

  13. Advantages in functional imaging of the brain

    PubMed Central

    Mier, Walter; Mier, Daniela

    2015-01-01

    As neuronal pathologies cause only minor morphological alterations, molecular imaging techniques are a prerequisite for the study of diseases of the brain. The development of molecular probes that specifically bind biochemical markers and the advances of instrumentation have revolutionized the possibilities to gain insight into the human brain organization and beyond this—visualize structure-function and brain-behavior relationships. The review describes the development and current applications of functional brain imaging techniques with a focus on applications in psychiatry. A historical overview of the development of functional imaging is followed by the portrayal of the principles and applications of positron emission tomography (PET) and functional magnetic resonance imaging (fMRI), two key molecular imaging techniques that have revolutionized the ability to image molecular processes in the brain. We conclude that the juxtaposition of PET and fMRI in hybrid PET/MRI scanners enhances the significance of both modalities for research in neurology and psychiatry and might pave the way for a new area of personalized medicine. PMID:26042013

  14. NIFTY (NeuroImaging Functional Toolkit): an interactive program for functional MRI data processing and visualization

    NASA Astrophysics Data System (ADS)

    Arnholt, Jeff C.; Hanson, Dennis P.; Robb, Richard A.

    1995-05-01

    NIFTY (NeuroImaging Functional Toolkit) is a tool designed to perform quantitative analysis and visualization of neurofunctional magnetic resonance image (fMRI) data sets. NIFTY is an OSF/Motif application which utilizes the AVW (a visualization workshop) imaging library developed in our laboratory and includes algorithms for robust image registration, statistical analysis, and mapping of neurofunctional data sets. Anisotropic diffusion routines can be used to enhance the signal-to-noise- ratio of these images. Tools capable of histogram equalization, thresholding, volume rendering, atlas matching, and a large number of other functions can then be used to visualize the data. NIFTY's development will offer a robust and flexible system of essential functions integrated into an interactive, graphically-oriented program, allowing neuroscientists the means by which to process, visualize, and interpret their data.

  15. The Impact of Arterial Input Function Determination Variations on Prostate Dynamic Contrast-Enhanced Magnetic Resonance Imaging Pharmacokinetic Modeling: A Multicenter Data Analysis Challenge

    PubMed Central

    Huang, Wei; Chen, Yiyi; Fedorov, Andriy; Li, Xia; Jajamovich, Guido H.; Malyarenko, Dariya I.; Aryal, Madhava P.; LaViolette, Peter S.; Oborski, Matthew J.; O'Sullivan, Finbarr; Abramson, Richard G.; Jafari-Khouzani, Kourosh; Afzal, Aneela; Tudorica, Alina; Moloney, Brendan; Gupta, Sandeep N.; Besa, Cecilia; Kalpathy-Cramer, Jayashree; Mountz, James M.; Laymon, Charles M.; Muzi, Mark; Schmainda, Kathleen; Cao, Yue; Chenevert, Thomas L.; Taouli, Bachir; Yankeelov, Thomas E.; Fennessy, Fiona; Li, Xin

    2016-01-01

    Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used in tumor detection and therapy response evaluation. Pharmacokinetic analysis of DCE-MRI time-course data allows estimation of quantitative imaging biomarkers such as Ktrans(rate constant for plasma/interstitium contrast reagent (CR) transfer) and ve (extravascular and extracellular volume fraction). However, the use of quantitative DCE-MRI in clinical prostate imaging islimited, with uncertainty in arterial input function (AIF, i.e., the time rate of change of the concentration of CR in the blood plasma) determination being one of the primary reasons. In this multicenter data analysis challenge to assess the effects of variations in AIF quantification on estimation of DCE-MRI parameters, prostate DCE-MRI data acquired at one center from 11 prostate cancer patients were shared among nine centers. Each center used its site-specific method to determine the individual AIF from each data set and submitted the results to the managing center. Along with a literature population averaged AIF, these AIFs and their reference-tissue-adjusted variants were used by the managing center to perform pharmacokinetic analysis of the DCE-MRI data sets using the Tofts model (TM). All other variables including tumor region of interest (ROI) definition and pre-contrast T1 were kept the same to evaluate parameter variations caused by AIF variations only. Considerable pharmacokinetic parameter variations were observed with the within-subject coefficient of variation (wCV) of Ktrans obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in Ktrans than ve and both were reduced when reference-tissue-adjusted AIFs were used. The parameter variations were largely systematic, resulting in nearly unchanged parametric map patterns. The CR intravasation rate constant, kep (= Ktrans/ve), was less sensitive to AIF variation than Ktrans (wCV for unadjusted AIFs: 0.45 for kep vs. 0.74 for Ktrans), suggesting that it

  16. Functional MR Imaging in Chest Malignancies.

    PubMed

    Broncano, Jordi; Luna, Antonio; Sánchez-González, Javier; Alvarez-Kindelan, Antonio; Bhalla, Sanjeev

    2016-02-01

    With recent advances in MR imaging, its application in the thorax has been feasible. The performance of both morphologic and functional techniques in the evaluation of thoracic malignances has improved not only differentiation from benign etiologies but also treatment monitoring based on a multiparametric approach. Several MR imaging-derived parameters have been described as potential biomarkers linked with prognosis and survival. Therefore, an integral approach with a nonradiating and noninvasive technique could be an optimal alternative for evaluating those patients.

  17. Atherosclerosis in Psoriatic Arthritis: A Multiparametric Analysis Using Imaging Technique and Laboratory Markers of Inflammation and Vascular Function.

    PubMed

    Garg, Nidhi; Krishan, Pawan; Syngle, Ashit

    2016-12-01

    Cardiovascular disease is one of the leading causes of death in psoriatic arthritis (PsA). Pathogenesis of accelerated atherosclerosis in PsA remains to be elucidated. Endothelial dysfunction (ED) often precedes manifesting atherosclerosis. This study aims to assess carotid intima-media thickness (CIMT), a marker of atherosclerosis in PsA, in context of markers of inflammation and vascular function. A cross-sectional study was performed in 18 PsA patients who were compared with 18 controls matched for age and sex. Flow-mediated dilatation (FMD) assessed by AngioDefender (Everist Health, Ann Arbor, MI), endothelial progenitor cells (EPCs) quantified by flow cytometry and CIMT measured ultrasonographically. Inflammatory measures included disease activity score of 28 joints count and disease activity index in psoriatic arthritis. We also assayed markers of inflammation, including C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), proinflammatory cytokines (interleukin [IL]-1, IL-6, and tumor necrosis factor [TNF]-α), and endothelial dysfunction, including lipids, intercellular adhesion molecule 1 (ICAM-1), vascular cell adhesion molecule 1 (VCAM-1), and EPCs. CIMT is significantly higher in PsA patients compared with controls (0.062 ± 0.18 vs. 0.045 ± 0.10 cm, p < 0.01) whereas FMD%, EPCs%, and high-density lipoproteins (HDL) cholesterol are significantly reduced in PsA compared with controls (p < 0.05). Compared with controls, PsA patients had significantly increased concentrations of ESR, CRP, TNF-α, IL-6, ICAM-1, and VCAM-1. In PsA, CIMT positively correlated with IL-6 and ICAM-1 and inversely correlated with FMD, HDL, and EPCs (p < 0.05). In PsA, FMD and CIMT were impaired, indicating endothelial dysfunction and accelerated atherosclerosis, respectively. PsA-related inflammatory mechanisms (TNF-α, IL-6) and markers of vascular function (CRP, ICAM-1, and EPCs) may all be involved in the development of vascular disease in Ps

  18. Functionalized gold nanorods for molecular optoacoustic imaging

    NASA Astrophysics Data System (ADS)

    Eghtedari, Mohammad; Oraevsky, Alexander; Conjusteau, Andre; Copland, John A.; Kotov, Nicholas A.; Motamedi, Massoud

    2007-02-01

    The development of gold nanoparticles for molecular optoacoustic imaging is a very promising area of research and development. Enhancement of optoacoustic imaging for molecular detection of tumors requires the engineering of nanoparticles with geometrical and molecular features that can enhance selective targeting of malignant cells while optimizing the sensitivity of optoacoustic detection. In this article, cylindrical gold nanoparticles (i.e. gold nanorods) were fabricated with a plasmon resonance frequency in the near infra-red region of the spectrum, where deep irradiation of tissue is possible using an Alexandrite laser. Gold nanorods (Au-NRs) were functionalized by covalent attachment of Poly(ethylene glycol) to enhance their biocompatibility. These particles were further functionalized with the aim of targeting breast cancer cells using monoclonal antibodies that binds to Her2/neu receptors, which are over expressed on the surface of breast cancer cells. A custom Laser Optoacoustic Imaging System (LOIS) was designed and employed to image nanoparticle-targeted cancer cells in a phantom and PEGylated Au-NRs that were injected subcutaneously into a nude mouse. The results of our experiments show that functionalized Au-NRs with a plasmon resonance frequency at near infra-red region of the spectrum can be detected and imaged in vivo using laser optoacoustic imaging system.

  19. Contrast sensitivity function and image discrimination.

    PubMed

    Peli, E

    2001-02-01

    A previous study tested the validity of simulations of the appearance of a natural image (from different observation distances) generated by using a visual model and contrast sensitivity functions of the individual observers [J. Opt. Soc. Am. A 13, 1131 (1996)]. Deleting image spatial-frequency components that should be undetectable made the simulations indistinguishable from the original images at distances larger than the simulated distance. The simulated observation distance accurately predicted the distance at which the simulated image could be discriminated from the original image. Owing to the 1/f characteristic of natural images' spatial spectra, the individual contrast sensitivity functions (CSF's) used in the simulations of the previous study were actually tested only over a narrow range of retinal spatial frequencies. To test the CSF's over a wide range of frequencies, the same simulations and testing procedure were applied to five contrast versions of the images (10-300%). This provides a stronger test of the model, of the simulations, and specifically of the CSF's used. The relevant CSF for a discrimination task was found to be obtained by using 1-octave Gabor stimuli measured in a contrast detection task. The relevant CSF data had to be measured over a range of observation distances, owing to limitations of the displays.

  20. Functional group analysis

    SciTech Connect

    Smith, W.T. Jr.; Patterson, J.M.

    1986-04-01

    Analytical methods for functional group analysis are reviewed. Literature reviewed is from the period of December 1983 through November 1985 and presents methods for determining the following compounds: acids, acid halides, active hydrogen, alcohols, aldehydes, ketones, amides, amines, amino acids, anhydrides, aromatic hydrocarbons, azo compounds, carbohydrates, chloramines, esters, ethers, halogen compounds, hydrazines, isothiocyanates, nitro compounds, nitroso compounds, organometallic compounds, oxiranes, peroxides, phenols, phosphorus compounds, quinones, silicon compounds, sulfates, sulfonyl chlorides, thioamides, thiols, and thiosemicarbazones. 150 references.

  1. Neural signatures of social conformity: A coordinate-based activation likelihood estimation meta-analysis of functional brain imaging studies.

    PubMed

    Wu, Haiyan; Luo, Yi; Feng, Chunliang

    2016-12-01

    People often align their behaviors with group opinions, known as social conformity. Many neuroscience studies have explored the neuropsychological mechanisms underlying social conformity. Here we employed a coordinate-based meta-analysis on neuroimaging studies of social conformity with the purpose to reveal the convergence of the underlying neural architecture. We identified a convergence of reported activation foci in regions associated with normative decision-making, including ventral striatum (VS), dorsal posterior medial frontal cortex (dorsal pMFC), and anterior insula (AI). Specifically, consistent deactivation of VS and activation of dorsal pMFC and AI are identified when people's responses deviate from group opinions. In addition, the deviation-related responses in dorsal pMFC predict people's conforming behavioral adjustments. These are consistent with current models that disagreement with others might evoke "error" signals, cognitive imbalance, and/or aversive feelings, which are plausibly detected in these brain regions as control signals to facilitate subsequent conforming behaviors. Finally, group opinions result in altered neural correlates of valuation, manifested as stronger responses of VS to stimuli endorsed than disliked by others.

  2. Adolescent body image and psychosocial functioning.

    PubMed

    Davison, Tanya E; McCabe, Marita P

    2006-02-01

    Researchers have highlighted the significance of a poor body image in the development of dysfunctional eating but have systematically investigated few other outcomes. The authors examined the relationships between different aspects of body image and psychosocial functioning. Participants were 245 boys and 173 girls from Grades 8 and 9 (M age = 13.92 years, SD = 0.69 years). Respondents completed measures of physical attractiveness, body satisfaction, body image importance, body image behaviors, appearance comparison, social physique anxiety, self-esteem, depression, anxiety, and same-sex and opposite-sex relations. Whereas girls tended to report a more negative body image than did boys, the relevance of body image to self-esteem was similar for boys and girls. Concern about others' evaluation of their bodies was especially important in understanding low female self-esteem, whereas for boys, ratings of general attractiveness most strongly predicted self-esteem. The authors found a negative body image to be unrelated to symptoms of negative affect but to be strongly associated with poor opposite-sex peer relationships, especially among boys. A negative body image also affected same-sex relations among girls.

  3. Image analysis for DNA sequencing

    NASA Astrophysics Data System (ADS)

    Palaniappan, Kannappan; Huang, Thomas S.

    1991-07-01

    There is a great deal of interest in automating the process of DNA (deoxyribonucleic acid) sequencing to support the analysis of genomic DNA such as the Human and Mouse Genome projects. In one class of gel-based sequencing protocols autoradiograph images are generated in the final step and usually require manual interpretation to reconstruct the DNA sequence represented by the image. The need to handle a large volume of sequence information necessitates automation of the manual autoradiograph reading step through image analysis in order to reduce the length of time required to obtain sequence data and reduce transcription errors. Various adaptive image enhancement, segmentation and alignment methods were applied to autoradiograph images. The methods are adaptive to the local characteristics of the image such as noise, background signal, or presence of edges. Once the two-dimensional data is converted to a set of aligned one-dimensional profiles waveform analysis is used to determine the location of each band which represents one nucleotide in the sequence. Different classification strategies including a rule-based approach are investigated to map the profile signals, augmented with the original two-dimensional image data as necessary, to textual DNA sequence information.

  4. Single particle raster image analysis of diffusion.

    PubMed

    Longfils, M; Schuster, E; Lorén, N; Särkkä, A; Rudemo, M

    2017-04-01

    As a complement to the standard RICS method of analysing Raster Image Correlation Spectroscopy images with estimation of the image correlation function, we introduce the method SPRIA, Single Particle Raster Image Analysis. Here, we start by identifying individual particles and estimate the diffusion coefficient for each particle by a maximum likelihood method. Averaging over the particles gives a diffusion coefficient estimate for the whole image. In examples both with simulated and experimental data, we show that the new method gives accurate estimates. It also gives directly standard error estimates. The method should be possible to extend to study heterogeneous materials and systems of particles with varying diffusion coefficient, as demonstrated in a simple simulation example. A requirement for applying the SPRIA method is that the particle concentration is low enough so that we can identify the individual particles. We also describe a bootstrap method for estimating the standard error of standard RICS.

  5. Errors from Image Analysis

    SciTech Connect

    Wood, William Monford

    2015-02-23

    Presenting a systematic study of the standard analysis of rod-pinch radiographs for obtaining quantitative measurements of areal mass densities, and making suggestions for improving the methodology of obtaining quantitative information from radiographed objects.

  6. Multi-Source Image Analysis.

    DTIC Science & Technology

    1979-12-01

    three sensor systems, but at some test sites only one or two types were utilized. Sensor characteristics were evaluated in relationship to the targets...Multi-source image analysis is an evaluation of remote sensor imagery for military geographic information. The imagery is confined to radar, thermal...heating affect a TIR scanner’s recorded temperature, careful image evaluation can be used to extract valuable military geographic information

  7. A framework for joint image-and-shape analysis

    NASA Astrophysics Data System (ADS)

    Gao, Yi; Tannenbaum, Allen; Bouix, Sylvain

    2014-03-01

    Techniques in medical image analysis are many times used for the comparison or regression on the intensities of images. In general, the domain of the image is a given Cartesian grids. Shape analysis, on the other hand, studies the similarities and differences among spatial objects of arbitrary geometry and topology. Usually, there is no function defined on the domain of shapes. Recently, there has been a growing needs for defining and analyzing functions defined on the shape space, and a coupled analysis on both the shapes and the functions defined on them. Following this direction, in this work we present a coupled analysis for both images and shapes. As a result, the statistically significant discrepancies in both the image intensities as well as on the underlying shapes are detected. The method is applied on both brain images for the schizophrenia and heart images for atrial fibrillation patients.

  8. Functional imaging using the retinal function imager: direct imaging of blood velocity, achieving fluorescein angiography-like images without any contrast agent, qualitative oximetry, and functional metabolic signals.

    PubMed

    Izhaky, David; Nelson, Darin A; Burgansky-Eliash, Zvia; Grinvald, Amiram

    2009-07-01

    The Retinal Function Imager (RFI; Optical Imaging, Rehovot, Israel) is a unique, noninvasive multiparameter functional imaging instrument that directly measures hemodynamic parameters such as retinal blood-flow velocity, oximetric state, and metabolic responses to photic activation. In addition, it allows capillary perfusion mapping without any contrast agent. These parameters of retinal function are degraded by retinal abnormalities. This review delineates the development of these parameters and demonstrates their clinical applicability for noninvasive detection of retinal function in several modalities. The results suggest multiple clinical applications for early diagnosis of retinal diseases and possible critical guidance of their treatment.

  9. The Assessment of Neurological Systems with Functional Imaging

    ERIC Educational Resources Information Center

    Eidelberg, David

    2007-01-01

    In recent years a number of multivariate approaches have been introduced to map neural systems in health and disease. In this review, we focus on spatial covariance methods applied to functional imaging data to identify patterns of regional activity associated with behavior. In the rest state, this form of network analysis can be used to detect…

  10. Multivariate image analysis in biomedicine.

    PubMed

    Nattkemper, Tim W

    2004-10-01

    In recent years, multivariate imaging techniques are developed and applied in biomedical research in an increasing degree. In research projects and in clinical studies as well m-dimensional multivariate images (MVI) are recorded and stored to databases for a subsequent analysis. The complexity of the m-dimensional data and the growing number of high throughput applications call for new strategies for the application of image processing and data mining to support the direct interactive analysis by human experts. This article provides an overview of proposed approaches for MVI analysis in biomedicine. After summarizing the biomedical MVI techniques the two level framework for MVI analysis is illustrated. Following this framework, the state-of-the-art solutions from the fields of image processing and data mining are reviewed and discussed. Motivations for MVI data mining in biology and medicine are characterized, followed by an overview of graphical and auditory approaches for interactive data exploration. The paper concludes with summarizing open problems in MVI analysis and remarks upon the future development of biomedical MVI analysis.

  11. Acoustic noise during functional magnetic resonance imaging.

    PubMed

    Ravicz, M E; Melcher, J R; Kiang, N Y

    2000-10-01

    Functional magnetic resonance imaging (fMRI) enables sites of brain activation to be localized in human subjects. For studies of the auditory system, acoustic noise generated during fMRI can interfere with assessments of this activation by introducing uncontrolled extraneous sounds. As a first step toward reducing the noise during fMRI, this paper describes the temporal and spectral characteristics of the noise present under typical fMRI study conditions for two imagers with different static magnetic field strengths. Peak noise levels were 123 and 138 dB re 20 microPa in a 1.5-tesla (T) and a 3-T imager, respectively. The noise spectrum (calculated over a 10-ms window coinciding with the highest-amplitude noise) showed a prominent maximum at 1 kHz for the 1.5-T imager (115 dB SPL) and at 1.4 kHz for the 3-T imager (131 dB SPL). The frequency content and timing of the most intense noise components indicated that the noise was primarily attributable to the readout gradients in the imaging pulse sequence. The noise persisted above background levels for 300-500 ms after gradient activity ceased, indicating that resonating structures in the imager or noise reverberating in the imager room were also factors. The gradient noise waveform was highly repeatable. In addition, the coolant pump for the imager's permanent magnet and the room air-handling system were sources of ongoing noise lower in both level and frequency than gradient coil noise. Knowledge of the sources and characteristics of the noise enabled the examination of general approaches to noise control that could be applied to reduce the unwanted noise during fMRI sessions.

  12. Analysis of Ventricular Function by Computed Tomography

    PubMed Central

    Rizvi, Asim; Deaño, Roderick C.; Bachman, Daniel P.; Xiong, Guanglei; Min, James K.; Truong, Quynh A.

    2014-01-01

    The assessment of ventricular function, cardiac chamber dimensions and ventricular mass is fundamental for clinical diagnosis, risk assessment, therapeutic decisions, and prognosis in patients with cardiac disease. Although cardiac computed tomography (CT) is a noninvasive imaging technique often used for the assessment of coronary artery disease, it can also be utilized to obtain important data about left and right ventricular function and morphology. In this review, we will discuss the clinical indications for the use of cardiac CT for ventricular analysis, review the evidence on the assessment of ventricular function compared to existing imaging modalities such cardiac MRI and echocardiography, provide a typical cardiac CT protocol for image acquisition and post-processing for ventricular analysis, and provide step-by-step instructions to acquire multiplanar cardiac views for ventricular assessment from the standard axial, coronal, and sagittal planes. Furthermore, both qualitative and quantitative assessments of ventricular function as well as sample reporting are detailed. PMID:25576407

  13. Multilocus Genetic Analysis of Brain Images

    PubMed Central

    Hibar, Derrek P.; Kohannim, Omid; Stein, Jason L.; Chiang, Ming-Chang; Thompson, Paul M.

    2011-01-01

    The quest to identify genes that influence disease is now being extended to find genes that affect biological markers of disease, or endophenotypes. Brain images, in particular, provide exquisitely detailed measures of anatomy, function, and connectivity in the living brain, and have identified characteristic features for many neurological and psychiatric disorders. The emerging field of imaging genomics is discovering important genetic variants associated with brain structure and function, which in turn influence disease risk and fundamental cognitive processes. Statistical approaches for testing genetic associations are not straightforward to apply to brain images because the data in brain images is spatially complex and generally high dimensional. Neuroimaging phenotypes typically include 3D maps across many points in the brain, fiber tracts, shape-based analyses, and connectivity matrices, or networks. These complex data types require new methods for data reduction and joint consideration of the image and the genome. Image-wide, genome-wide searches are now feasible, but they can be greatly empowered by sparse regression or hierarchical clustering methods that isolate promising features, boosting statistical power. Here we review the evolution of statistical approaches to assess genetic influences on the brain. We outline the current state of multivariate statistics in imaging genomics, and future directions, including meta-analysis. We emphasize the power of novel multivariate approaches to discover reliable genetic influences with small effect sizes. PMID:22303368

  14. Optical imaging device of retinal function

    NASA Astrophysics Data System (ADS)

    Kardon, Randy H.; Kwon, Young; Truitt, Paul; Nemeth, Sheila C.; T'so, Dan; Soliz, Peter

    2002-06-01

    An optical imaging device of retina function (OID-RF) has been constructed to record changes in reflected 700-nm light from the fundus caused by retinal activation in response to a visual 535-nm stimulus. The resulting images reveal areas of the retina activated by visual stimulation. This device is a modified fundus camera designed to provide a patterned, moving visual stimulus over a 45-degree field of view to the subject in the green wavelength portion of the visual spectrum while simultaneously imaging the fundus in another, longer wavelength range. Data was collected from 3 normal subjects and recorded for 13 seconds at 4 Hz; 3 seconds were recorded during pre-stimulus baseline, 5 seconds during the stimulus, and 5 seconds post-stimulus. This procedure was repeated several times and, after image registration, the images were averaged to improve signal to noise. The change in reflected intensity from the retina due to the stimulus was then calculated by comparison to the pre-stimulus state. Reflected intensity from areas of stimulated retina began to increase steadily within 1 second after stimulus onset and decayed after stimulus offset. These results indicated that a functional optical signal can be recorded from the human eye.

  15. Dynamic and still microcirculatory image analysis for quantitative microcirculation research

    NASA Astrophysics Data System (ADS)

    Ying, Xiaoyou; Xiu, Rui-juan

    1994-05-01

    Based on analyses of various types of digital microcirculatory image (DMCI), we summed up the image features of DMCI, the digitizing demands for digital microcirculatory imaging, and the basic characteristics of the DMCI processing. A dynamic and still imaging separation processing (DSISP) mode was designed for developing a DMCI workstation and the DMCI processing. Original images in this study were clinical microcirculatory images from human finger nail-bed and conjunctiva microvasculature, and intravital microvascular network images from animal tissue or organs. A series of dynamic and still microcirculatory image analysis functions were developed in this study. The experimental results indicate most of the established analog video image analysis methods for microcirculatory measurement could be realized in a more flexible way based on the DMCI. More information can be rapidly extracted from the quality improved DMCI by employing intelligence digital image analysis methods. The DSISP mode is very suitable for building a DMCI workstation.

  16. Development of contrast-enhanced rodent imaging using functional CT

    NASA Astrophysics Data System (ADS)

    Liang, Yun; Stantz, Keith M.; Krishnamurthi, Ganapathy; Steinmetz, Rosemary; Hutchins, Gary D.

    2003-05-01

    Micro-computed tomography (microCT) is capable of obtaining high-resolution images of skeletal tissues. However its image contrast among soft tissues remains inadequate for tumor detection. High speed functional computed tomography will be needed to image tumors by employing x-ray contrast medium. The functional microCT development will not only facilitate the image contrast enhancement among different tissues but also provide information of tumor physiology. To demonstrate the feasibility of functional CT in mouse imaging, sequential computed tomography is performed in mice after contrast material administration using a high-speed clinical CT scanner. Although the resolution of the clinical scanner is not sufficient to dissolve the anatomic details of rodents, bulky physiological parameters in major organs such as liver, kidney, pancreas, and ovaries (testicular) can be examined. For data analysis, a two-compartmental model is employed and implemented to characterize the tissue physiological parameters (regional blood flow, capillary permeability, and relative compartment volumes.) The measured contrast dynamics in kidneys are fitted with the compartmental model to derive the kidney tissue physiology. The study result suggests that it is feasible to extract mouse tissue physiology using functional CT imaging technology.

  17. Decoding sequential finger movements from preparatory activity in higher-order motor regions: a functional magnetic resonance imaging multi-voxel pattern analysis.

    PubMed

    Nambu, Isao; Hagura, Nobuhiro; Hirose, Satoshi; Wada, Yasuhiro; Kawato, Mitsuo; Naito, Eiichi

    2015-11-01

    Performing a complex sequential finger movement requires the temporally well-ordered organization of individual finger movements. Previous behavioural studies have suggested that the brain prepares a whole sequence of movements as a single set, rather than the movements of individual fingers. However, direct neuroimaging support for this hypothesis is lacking and, assuming it to be true, it remains unclear which brain regions represent the information of a prepared sequence. Here, we measured brain activity with functional magnetic resonance imaging while 14 right-handed healthy participants performed two types of well-learned sequential finger movements with their right hands. Using multi-voxel pattern analysis, we examined whether the types of the forthcoming sequence could be predicted from the preparatory activities of nine regions of interest, which included the motor, somatosensory and posterior parietal regions in each hemisphere, bilateral visual cortices, cerebellum and basal ganglia. We found that, during preparation, the activity of the contralateral motor regions could predict which of the two sequences would be executed. Further detailed analysis revealed that the contralateral dorsal premotor cortex and supplementary motor area were the key areas that contributed to the prediction consistently across participants. These contrasted with results from execution-related brain activity where a performed sequence was successfully predicted from the activities in the broad cortical sensory-motor network, including the bilateral motor, parietal and ipsilateral somatosensory cortices. Our study supports the hypothesis that temporary well-organized sequences of movements are represented as a set in the brain, and that preparatory activity in higher-order motor regions represents information about upcoming motor actions.

  18. Signal and image processing techniques for functional near-infrared imaging of the human brain

    PubMed Central

    Toronov, Vladislav Y.; Zhang, Xiaofeng; Fabiani, Monica; Gratton, Gabriele; Webb, Andrew G.

    2011-01-01

    Near-infrared spectro-imaging (NIRSI) is a quickly developing method for the in-vivo imaging of biological tissues. In particular, it is now extensively employed for imaging the human brain. In this non-invasive technique, the information about the brain is obtained from the analysis of spatial light bundles formed by the photons traveling from light sources to detectors placed on the surface of the head. Most significant problems in the functional brain NIRSI are the separation of the brain information from the physiological noise in non-cerebral tissues, and the localization of functional signals. In this paper we describe signal and image processing techniques we developed in order to measure two types of functional cerebral signals: the hemodynamic responses, and neuronal responses. PMID:21738383

  19. Signal and image processing techniques for functional near-infrared imaging of the human brain

    NASA Astrophysics Data System (ADS)

    Toronov, Vladislav Y.; Zhang, Xiaofeng; Fabiani, Monica; Gratton, Gabriele; Webb, Andrew G.

    2005-03-01

    Near-infrared spectro-imaging (NIRSI) is a quickly developing method for the in-vivo imaging of biological tissues. In particular, it is now extensively employed for imaging the human brain. In this non-invasive technique, the information about the brain is obtained from the analysis of spatial light bundles formed by the photons traveling from light sources to detectors placed on the surface of the head. Most significant problems in the functional brain NIRSI are the separation of the brain information from the physiological noise in non-cerebral tissues, and the localization of functional signals. In this paper we describe signal and image processing techniques we developed in order to measure two types of functional cerebral signals: the hemodynamic responses, and neuronal responses.

  20. Image reconstruction with analytical point spread functions

    NASA Astrophysics Data System (ADS)

    Asensio Ramos, A.; López Ariste, A.

    2010-07-01

    Context. The image degradation produced by atmospheric turbulence and optical aberrations is usually alleviated using post-facto image reconstruction techniques, even when observing with adaptive optics systems. Aims: These techniques rely on the development of the wavefront using Zernike functions and the non-linear optimization of a certain metric. The resulting optimization procedure is computationally heavy. Our aim is to alleviate this computational burden. Methods: We generalize the extended Zernike-Nijboer theory to carry out the analytical integration of the Fresnel integral and present a natural basis set for the development of the point spread function when the wavefront is described using Zernike functions. Results: We present a linear expansion of the point spread function in terms of analytic functions, which, in addition, takes defocusing into account in a natural way. This expansion is used to develop a very fast phase-diversity reconstruction technique, which is demonstrated in terms of some applications. Conclusions: We propose that the linear expansion of the point spread function can be applied to accelerate other reconstruction techniques in use that are based on blind deconvolution.

  1. Electromagnetic inverse applications for functional brain imaging

    SciTech Connect

    Wood, C.C.

    1997-10-01

    This is the final report of a one-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). This project addresses an important mathematical and computational problem in functional brain imaging, namely the electromagnetic {open_quotes}inverse problem.{close_quotes} Electromagnetic brain imaging techniques, magnetoencephalography (MEG) and electroencephalography (EEG), are based on measurements of electrical potentials and magnetic fields at hundreds of locations outside the human head. The inverse problem is the estimation of the locations, magnitudes, and time-sources of electrical currents in the brain from surface measurements. This project extends recent progress on the inverse problem by combining the use of anatomical constraints derived from magnetic resonance imaging (MRI) with Bayesian and other novel algorithmic approaches. The results suggest that we can achieve significant improvements in the accuracy and robustness of inverse solutions by these two approaches.

  2. Functional lung imaging using hyperpolarized gas MRI.

    PubMed

    Fain, Sean B; Korosec, Frank R; Holmes, James H; O'Halloran, Rafael; Sorkness, Ronald L; Grist, Thomas M

    2007-05-01

    The noninvasive assessment of lung function using imaging is increasingly of interest for the study of lung diseases, including chronic obstructive pulmonary disease (COPD) and asthma. Hyperpolarized gas MRI (HP MRI) has demonstrated the ability to detect changes in ventilation, perfusion, and lung microstructure that appear to be associated with both normal lung development and disease progression. The physical characteristics of HP gases and their application to MRI are presented with an emphasis on current applications. Clinical investigations using HP MRI to study asthma, COPD, cystic fibrosis, pediatric chronic lung disease, and lung transplant are reviewed. Recent advances in polarization, pulse sequence development for imaging with Xe-129, and prototype low magnetic field systems dedicated to lung imaging are highlighted as areas of future development for this rapidly evolving technology.

  3. A Unified Mathematical Approach to Image Analysis.

    DTIC Science & Technology

    1987-08-31

    describes four instances of the paradigm in detail. Directions for ongoing and future research are also indicated. Keywords: Image processing; Algorithms; Segmentation; Boundary detection; tomography; Global image analysis .

  4. One-stop-shop stroke imaging with functional CT.

    PubMed

    Tong, Elizabeth; Komlosi, Peter; Wintermark, Max

    2015-12-01

    Advanced imaging techniques have extended beyond traditional anatomic imaging and progressed to dynamic, physiologic and functional imaging. Neuroimaging is no longer a mere diagnostic tool. Multimodal functional CT, comprising of NCCT, PCT and CTA, provides a one-stop-shop for rapid stroke imaging. Integrating those imaging findings with pertinent clinical information can help guide subsequent treatment decisions, medical management and follow-up imaging selection. This review article will briefly discuss the indication and utility of each modality in acute stroke imaging.

  5. Fast Optical Imaging of Human Brain Function

    PubMed Central

    Gratton, Gabriele; Fabiani, Monica

    2010-01-01

    Great advancements in brain imaging during the last few decades have opened a large number of new possibilities for neuroscientists. The most dominant methodologies (electrophysiological and magnetic resonance-based methods) emphasize temporal and spatial information, respectively. However, theorizing about brain function has recently emphasized the importance of rapid (within 100 ms or so) interactions between different elements of complex neuronal networks. Fast optical imaging, and in particular the event-related optical signal (EROS, a technology that has emerged over the last 15 years) may provide descriptions of localized (to sub-cm level) brain activity with a temporal resolution of less than 100 ms. The main limitations of EROS are its limited penetration, which allows us to image cortical structures not deeper than 3 cm from the surface of the head, and its low signal-to-noise ratio. Advantages include the fact that EROS is compatible with most other imaging methods, including electrophysiological, magnetic resonance, and trans-cranial magnetic stimulation techniques, with which can be recorded concurrently. In this paper we present a summary of the research that has been conducted so far on fast optical imaging, including evidence for the possibility of recording neuronal signals with this method, the properties of the signals, and various examples of applications to the study of human cognitive neuroscience. Extant issues, controversies, and possible future developments are also discussed. PMID:20631845

  6. Performance Evaluation of Color Models in the Fusion of Functional and Anatomical Images.

    PubMed

    Ganasala, Padma; Kumar, Vinod; Prasad, A D

    2016-05-01

    Fusion of the functional image with an anatomical image provides additional diagnostic information. It is widely used in diagnosis, treatment planning, and follow-up of oncology. Functional image is a low-resolution pseudo color image representing the uptake of radioactive tracer that gives the important metabolic information. Whereas, anatomical image is a high-resolution gray scale image that gives structural details. Fused image should consist of all the anatomical details without any changes in the functional content. This is achieved through fusion in de-correlated color model and the choice of color model has greater impact on the fusion outcome. In the present work, suitability of different color models for functional and anatomical image fusion is studied. After converting the functional image into de-correlated color model, the achromatic component of functional image is fused with an anatomical image by using proposed nonsubsampled shearlet transform (NSST) based image fusion algorithm to get new achromatic component with all the anatomical details. This new achromatic and original chromatic channels of functional image are converted to RGB format to get fused functional and anatomical image. Fusion is performed in different color models. Different cases of SPECT-MRI images are used for this color model study. Based on visual and quantitative analysis of fused images, the best color model for the stated purpose is determined.

  7. Promise of new imaging technologies for assessing ovarian function

    PubMed Central

    Singh, Jaswant; Adams, Gregg P.; Pierson, Roger A.

    2010-01-01

    Advancements in imaging technologies over the last two decades have ushered a quiet revolution in research approaches to the study of ovarian structure and function. The most significant changes in our understanding of the ovary have resulted from the use of ultrasonography which has enabled sequential analyses in live animals. Computer-assisted image analysis and mathematical modeling of the dynamic changes within the ovary has permitted exciting new avenues of research with readily quantifiable endpoints. Spectral, color-flow and power Doppler imaging now facilitate physiologic interpretations of vascular dynamics over time. Similarly, magnetic resonance imaging (MRI) is emerging as a research tool in ovarian imaging. New technologies, such as three-dimensional ultrasonography and MRI, ultrasound-based biomicroscopy and synchrotron-based techniques each have the potential to enhance our real-time picture of ovarian function to the near-cellular level. Collectively, information available in ultrasonography, MRI, computer-assisted image analysis and mathematical modeling heralds a new era in our understanding of the basic processes of female and male reproduction. PMID:12818654

  8. ALISA: adaptive learning image and signal analysis

    NASA Astrophysics Data System (ADS)

    Bock, Peter

    1999-01-01

    ALISA (Adaptive Learning Image and Signal Analysis) is an adaptive statistical learning engine that may be used to detect and classify the surfaces and boundaries of objects in images. The engine has been designed, implemented, and tested at both the George Washington University and the Research Institute for Applied Knowledge Processing in Ulm, Germany over the last nine years with major funding from Robert Bosch GmbH and Lockheed-Martin Corporation. The design of ALISA was inspired by the multi-path cortical- column architecture and adaptive functions of the mammalian visual cortex.

  9. Characterization of microrod arrays by image analysis

    NASA Astrophysics Data System (ADS)

    Hillebrand, Reinald; Grimm, Silko; Giesa, Reiner; Schmidt, Hans-Werner; Mathwig, Klaus; Gösele, Ulrich; Steinhart, Martin

    2009-04-01

    The uniformity of the properties of array elements was evaluated by statistical analysis of microscopic images of array structures, assuming that the brightness of the array elements correlates quantitatively or qualitatively with a microscopically probed quantity. Derivatives and autocorrelation functions of cumulative frequency distributions of the object brightnesses were used to quantify variations in object properties throughout arrays. Thus, different specimens, the same specimen at different stages of its fabrication or use, and different imaging conditions can be compared systematically. As an example, we analyzed scanning electron micrographs of microrod arrays and calculated the percentage of broken microrods.

  10. A Primer on Functional Analysis

    ERIC Educational Resources Information Center

    Yoman, Jerome

    2008-01-01

    This article presents principles and basic steps for practitioners to complete a functional analysis of client behavior. The emphasis is on application of functional analysis to adult mental health clients. The article includes a detailed flow chart containing all major functional diagnoses and behavioral interventions, with functional assessment…

  11. Electroencephalographic imaging of higher brain function

    NASA Technical Reports Server (NTRS)

    Gevins, A.; Smith, M. E.; McEvoy, L. K.; Leong, H.; Le, J.

    1999-01-01

    High temporal resolution is necessary to resolve the rapidly changing patterns of brain activity that underlie mental function. Electroencephalography (EEG) provides temporal resolution in the millisecond range. However, traditional EEG technology and practice provide insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. Recent advances help to overcome this problem by recording EEGs from more electrodes, by registering EEG data with anatomical images, and by correcting the distortion caused by volume conduction of EEG signals through the skull and scalp. In addition, statistical measurements of sub-second interdependences between EEG time-series recorded from different locations can help to generate hypotheses about the instantaneous functional networks that form between different cortical regions during perception, thought and action. Example applications are presented from studies of language, attention and working memory. Along with its unique ability to monitor brain function as people perform everyday activities in the real world, these advances make modern EEG an invaluable complement to other functional neuroimaging modalities.

  12. Retinal functional imager (RFI): non-invasive functional imaging of the retina.

    PubMed

    Ganekal, S

    2013-01-01

    Retinal functional imager (RFI) is a unique non-invasive functional imaging system with novel capabilities for visualizing the retina. The objective of this review was to show the utility of non-invasive functional imaging in various disorders. Electronic literature search was carried out using the websites www.pubmed.gov and www.google.com. The search words were retinal functional imager and non-invasive retinal imaging used in combination. The articles published or translated into English were studied. The RFI directly measures hemodynamic parameters such as retinal blood-flow velocity, oximetric state, metabolic responses to photic activation and generates capillary perfusion maps (CPM) that provides retinal vasculature detail similar to flourescein angiography. All of these parameters stand in a direct relationship to the function and therefore the health of the retina, and are known to be degraded in the course of retinal diseases. Detecting changes in retinal function aid early diagnosis and treatment as functional changes often precede structural changes in many retinal disorders.

  13. Horizontal Long Axis Imaging Plane for Evaluation of Right Ventricular Function on Cardiac Magnetic Resonance Imaging

    PubMed Central

    Chaturvedi, Abhishek; Whitnah, Joseph; Maki, Jeffrey H; Baran, Timothy; Mitsumori, Lee M

    2016-01-01

    Purpose: The purpose of this study was to evaluate a horizontal long axis (HLA) magnetic resonance imaging (MRI) plane aligned to the long axis of the right ventricular (RV) cavity for functional analysis by comparing the measurement variability and time required for the analysis with that using a short-axis (SAX) image orientation. Materials and Methods: Thirty-four cardiac MRI exams with cine balanced steady-state free precession image stacks in both the SAX and the HLA of the RV (RHLA) were evaluated. Two reviewers independently traced RV endocardial borders on each image of the cine stacks. The time required to complete each set of traces was recorded, and the RV end-diastolic volume, end-systolic volume, and ejection fraction were calculated. Analysis times and RV measurements were compared between the two orientations. Results: Analysis time for each reviewer was significantly shorter for the RHLA stack (reviewer 1 = 6.4 ± 1.8 min, reviewer 2 = 6.0 ± 3.3 min) than for the SAX stack (7.5 ± 2.1 and 6.9 ± 3.6 min, respectively; P < 0.002). Bland–Altman analysis revealed lower mean differences, limits of agreement, and coefficients of variation for RV measurements obtained with the RHLA stack. Conclusions: RV functional analysis using a RHLA stack resulted in shorter analysis times and lower measurement variability than for a SAX stack orientation. PMID:28123842

  14. Machine learning for medical images analysis.

    PubMed

    Criminisi, A

    2016-10-01

    This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods.

  15. [Functional magnetic resonance imaging: physiopathology, techniques and applications].

    PubMed

    Delmaire, C; Krainik, A; Lethuc, V; Reyns, N; Duffau, H; Capelle, L; Lehéricy, S

    2007-03-01

    Brain functional MRI (fMRI) provides an indirect mapping of cerebral activity, based on the detection of local changes in blood flow and oxygenation levels that are associated with neuronal activity (BOLD contrast). fMRI allows noninvasive studies of normal and pathological aspects of the brain's functional organization. It is based on the comparison of two or more cognitive states. Echoplanar imaging is the technique of choice, providing the quickest study of the entire brain. Activation maps are calculated from a statistical analysis of the local signal changes. fMRI has become one of the most widely used functional imaging techniques in neuroscience. In clinical practice, fMRI can identify eloquent areas involved in motor and language functions in surgical patients and can evaluate the risk of postoperative neurological deficit.

  16. A simultaneous multimodal imaging system for tissue functional parameters

    NASA Astrophysics Data System (ADS)

    Ren, Wenqi; Zhang, Zhiwu; Wu, Qiang; Zhang, Shiwu; Xu, Ronald

    2014-02-01

    Simultaneous and quantitative assessment of skin functional characteristics in different modalities will facilitate diagnosis and therapy in many clinical applications such as wound healing. However, many existing clinical practices and multimodal imaging systems are subjective, qualitative, sequential for multimodal data collection, and need co-registration between different modalities. To overcome these limitations, we developed a multimodal imaging system for quantitative, non-invasive, and simultaneous imaging of cutaneous tissue oxygenation and blood perfusion parameters. The imaging system integrated multispectral and laser speckle imaging technologies into one experimental setup. A Labview interface was developed for equipment control, synchronization, and image acquisition. Advanced algorithms based on a wide gap second derivative reflectometry and laser speckle contrast analysis (LASCA) were developed for accurate reconstruction of tissue oxygenation and blood perfusion respectively. Quantitative calibration experiments and a new style of skinsimulating phantom were designed to verify the accuracy and reliability of the imaging system. The experimental results were compared with a Moor tissue oxygenation and perfusion monitor. For In vivo testing, a post-occlusion reactive hyperemia (PORH) procedure in human subject and an ongoing wound healing monitoring experiment using dorsal skinfold chamber models were conducted to validate the usability of our system for dynamic detection of oxygenation and perfusion parameters. In this study, we have not only setup an advanced multimodal imaging system for cutaneous tissue oxygenation and perfusion parameters but also elucidated its potential for wound healing assessment in clinical practice.

  17. Iterative approach of dual regression with a sparse prior enhances the performance of independent component analysis for group functional magnetic resonance imaging (fMRI) data.

    PubMed

    Kim, Yong-Hwan; Kim, Junghoe; Lee, Jong-Hwan

    2012-12-01

    This study proposes an iterative dual-regression (DR) approach with sparse prior regularization to better estimate an individual's neuronal activation using the results of an independent component analysis (ICA) method applied to a temporally concatenated group of functional magnetic resonance imaging (fMRI) data (i.e., Tc-GICA method). An ordinary DR approach estimates the spatial patterns (SPs) of neuronal activation and corresponding time courses (TCs) specific to each individual's fMRI data with two steps involving least-squares (LS) solutions. Our proposed approach employs iterative LS solutions to refine both the individual SPs and TCs with an additional a priori assumption of sparseness in the SPs (i.e., minimally overlapping SPs) based on L(1)-norm minimization. To quantitatively evaluate the performance of this approach, semi-artificial fMRI data were created from resting-state fMRI data with the following considerations: (1) an artificially designed spatial layout of neuronal activation patterns with varying overlap sizes across subjects and (2) a BOLD time series (TS) with variable parameters such as onset time, duration, and maximum BOLD levels. To systematically control the spatial layout variability of neuronal activation patterns across the "subjects" (n=12), the degree of spatial overlap across all subjects was varied from a minimum of 1 voxel (i.e., 0.5-voxel cubic radius) to a maximum of 81 voxels (i.e., 2.5-voxel radius) across the task-related SPs with a size of 100 voxels for both the block-based and event-related task paradigms. In addition, several levels of maximum percentage BOLD intensity (i.e., 0.5, 1.0, 2.0, and 3.0%) were used for each degree of spatial overlap size. From the results, the estimated individual SPs of neuronal activation obtained from the proposed iterative DR approach with a sparse prior showed an enhanced true positive rate and reduced false positive rate compared to the ordinary DR approach. The estimated TCs of the

  18. Image analysis in medical imaging: recent advances in selected examples.

    PubMed

    Dougherty, G

    2010-01-01

    Medical imaging has developed into one of the most important fields within scientific imaging due to the rapid and continuing progress in computerised medical image visualisation and advances in analysis methods and computer-aided diagnosis. Several research applications are selected to illustrate the advances in image analysis algorithms and visualisation. Recent results, including previously unpublished data, are presented to illustrate the challenges and ongoing developments.

  19. Structural and functional brain imaging in schizophrenia.

    PubMed Central

    Cleghorn, J M; Zipursky, R B; List, S J

    1991-01-01

    We present an evaluation of the contribution of structural and functional brain imaging to our understanding of schizophrenia. Methodological influences on the validity of the data generated by these new technologies include problems with measurement and clinical and anatomic heterogeneity. These considerations greatly affect the interpretation of the data generated by these technologies. Work in these fields to date, however, has produced strong evidence which suggests that schizophrenia is a disease which involves abnormalities in the structure and function of many brain areas. Structural brain imaging studies of schizophrenia using computed tomography (CT) and magnetic resonance imaging (MRI) are reviewed and their contribution to current theories of the pathogenesis of schizophrenia are discussed. Positron emission tomography (PET) studies of brain metabolic activity and dopamine receptor binding in schizophrenia are summarized and the critical questions raised by these studies are outlined. Future studies in these fields have the potential to yield critical insights into the pathophysiology of schizophrenia; new directions for studies of schizophrenia using these technologies are identified. PMID:1911736

  20. Live-Animal Imaging of Renal Function by Multiphoton Microscopy

    PubMed Central

    Dunn, Kenneth W.; Sutton, Timothy A.; Sandoval, Ruben M.

    2015-01-01

    Intravital microscopy, microscopy of living animals, is a powerful research technique that combines the resolution and sensitivity found in microscopic studies of cultured cells with the relevance and systemic influences of cells in the context of the intact animal. The power of intravital microscopy has recently been extended with the development of multiphoton fluorescence microscopy systems capable of collecting optical sections from deep within the kidney at subcellular resolution, supporting high-resolution characterizations of the structure and function of glomeruli, tubules, and vasculature in the living kidney. Fluorescent probes are administered to an anesthetized, surgically prepared animal, followed by image acquisition for up to 3 hr. Images are transferred via a high-speed network to specialized computer systems for digital image analysis. This general approach can be used with different combinations of fluorescent probes to evaluate processes such as glomerular permeability, proximal tubule endocytosis, microvascular flow, vascular permeability, mitochondrial function, and cellular apoptosis/necrosis. PMID:23042524

  1. Quantitative multi-image analysis for biomedical Raman spectroscopic imaging.

    PubMed

    Hedegaard, Martin A B; Bergholt, Mads S; Stevens, Molly M

    2016-05-01

    Imaging by Raman spectroscopy enables unparalleled label-free insights into cell and tissue composition at the molecular level. With established approaches limited to single image analysis, there are currently no general guidelines or consensus on how to quantify biochemical components across multiple Raman images. Here, we describe a broadly applicable methodology for the combination of multiple Raman images into a single image for analysis. This is achieved by removing image specific background interference, unfolding the series of Raman images into a single dataset, and normalisation of each Raman spectrum to render comparable Raman images. Multivariate image analysis is finally applied to derive the contributing 'pure' biochemical spectra for relative quantification. We present our methodology using four independently measured Raman images of control cells and four images of cells treated with strontium ions from substituted bioactive glass. We show that the relative biochemical distribution per area of the cells can be quantified. In addition, using k-means clustering, we are able to discriminate between the two cell types over multiple Raman images. This study shows a streamlined quantitative multi-image analysis tool for improving cell/tissue characterisation and opens new avenues in biomedical Raman spectroscopic imaging.

  2. Function Point Analysis Depot

    NASA Technical Reports Server (NTRS)

    Muniz, R.; Martinez, El; Szafran, J.; Dalton, A.

    2011-01-01

    The Function Point Analysis (FPA) Depot is a web application originally designed by one of the NE-C3 branch's engineers, Jamie Szafran, and created specifically for the Software Development team of the Launch Control Systems (LCS) project. The application consists of evaluating the work of each developer to be able to get a real estimate of the hours that is going to be assigned to a specific task of development. The Architect Team had made design change requests for the depot to change the schema of the application's information; that information, changed in the database, needed to be changed in the graphical user interface (GUI) (written in Ruby on Rails (RoR and the web service/server side in Java to match the database changes. These changes were made by two interns from NE-C, Ricardo Muniz from NE-C3, who made all the schema changes for the GUI in RoR and Edwin Martinez, from NE-C2, who made all the changes in the Java side.

  3. Imaging analysis of LDEF craters

    NASA Technical Reports Server (NTRS)

    Radicatidibrozolo, F.; Harris, D. W.; Chakel, J. A.; Fleming, R. H.; Bunch, T. E.

    1991-01-01

    Two small craters in Al from the Long Duration Exposure Facility (LDEF) experiment tray A11E00F (no. 74, 119 micron diameter and no. 31, 158 micron diameter) were analyzed using Auger electron spectroscopy (AES), time-of-flight secondary ion mass spectroscopy (TOF-SIMS), low voltage scanning electron microscopy (LVSEM), and SEM energy dispersive spectroscopy (EDS). High resolution images and sensitive elemental and molecular analysis were obtained with this combined approach. The result of these analyses are presented.

  4. Infrared Imaging System for Studying Brain Function

    NASA Technical Reports Server (NTRS)

    Mintz, Frederick; Mintz, Frederick; Gunapala, Sarath

    2007-01-01

    A proposed special-purpose infrared imaging system would be a compact, portable, less-expensive alternative to functional magnetic resonance imaging (fMRI) systems heretofore used to study brain function. Whereas a typical fMRI system fills a large room, and must be magnetically isolated, this system would fit into a bicycle helmet. The system would include an assembly that would be mounted inside the padding in a modified bicycle helmet or other suitable headgear. The assembly would include newly designed infrared photodetectors and data-acquisition circuits on integrated-circuit chips on low-thermal-conductivity supports in evacuated housings (see figure) arranged in multiple rows and columns that would define image coordinates. Each housing would be spring-loaded against the wearer s head. The chips would be cooled by a small Stirling Engine mounted contiguous to, but thermally isolated from, the portions of the assembly in thermal contact with the wearer s head. Flexible wires or cables for transmitting data from the aforementioned chips would be routed to an integrated, multichannel transmitter and thence through the top of the assembly to a patch antenna on the outside of the helmet. The multiple streams of data from the infrared-detector chips would be sent to a remote site, where they would be processed, by software, into a three-dimensional display of evoked potentials that would represent firing neuronal bundles and thereby indicate locations of neuronal activity associated with mental or physical activity. The 3D images will be analogous to current fMRI images. The data would also be made available, in real-time, for comparison with data in local or internationally accessible relational databases that already exist in universities and research centers. Hence, this system could be used in research on, and for the diagnosis of response from the wearer s brain to physiological, psychological, and environmental changes in real time. The images would also be

  5. Planning applications in image analysis

    NASA Technical Reports Server (NTRS)

    Boddy, Mark; White, Jim; Goldman, Robert; Short, Nick, Jr.

    1994-01-01

    We describe two interim results from an ongoing effort to automate the acquisition, analysis, archiving, and distribution of satellite earth science data. Both results are applications of Artificial Intelligence planning research to the automatic generation of processing steps for image analysis tasks. First, we have constructed a linear conditional planner (CPed), used to generate conditional processing plans. Second, we have extended an existing hierarchical planning system to make use of durations, resources, and deadlines, thus supporting the automatic generation of processing steps in time and resource-constrained environments.

  6. Automated quantitative image analysis of nanoparticle assembly

    NASA Astrophysics Data System (ADS)

    Murthy, Chaitanya R.; Gao, Bo; Tao, Andrea R.; Arya, Gaurav

    2015-05-01

    The ability to characterize higher-order structures formed by nanoparticle (NP) assembly is critical for predicting and engineering the properties of advanced nanocomposite materials. Here we develop a quantitative image analysis software to characterize key structural properties of NP clusters from experimental images of nanocomposites. This analysis can be carried out on images captured at intermittent times during assembly to monitor the time evolution of NP clusters in a highly automated manner. The software outputs averages and distributions in the size, radius of gyration, fractal dimension, backbone length, end-to-end distance, anisotropic ratio, and aspect ratio of NP clusters as a function of time along with bootstrapped error bounds for all calculated properties. The polydispersity in the NP building blocks and biases in the sampling of NP clusters are accounted for through the use of probabilistic weights. This software, named Particle Image Characterization Tool (PICT), has been made publicly available and could be an invaluable resource for researchers studying NP assembly. To demonstrate its practical utility, we used PICT to analyze scanning electron microscopy images taken during the assembly of surface-functionalized metal NPs of differing shapes and sizes within a polymer matrix. PICT is used to characterize and analyze the morphology of NP clusters, providing quantitative information that can be used to elucidate the physical mechanisms governing NP assembly.The ability to characterize higher-order structures formed by nanoparticle (NP) assembly is critical for predicting and engineering the properties of advanced nanocomposite materials. Here we develop a quantitative image analysis software to characterize key structural properties of NP clusters from experimental images of nanocomposites. This analysis can be carried out on images captured at intermittent times during assembly to monitor the time evolution of NP clusters in a highly automated

  7. Functional magnetic resonance imaging and the brain: A brief review

    PubMed Central

    Chow, Maggie S M; Wu, Sharon L; Webb, Sarah E; Gluskin, Katie; Yew, D T

    2017-01-01

    Functional magnetic resonance imaging (fMRI) is employed in many behavior analysis studies, with blood oxygen level dependent- (BOLD-) contrast imaging being the main method used to generate images. The use of BOLD-contrast imaging in fMRI has been refined over the years, for example, the inclusion of a spin echo pulse and increased magnetic strength were shown to produce better recorded images. Taking careful precautions to control variables during measurement, comparisons between different specimen groups can be illustrated by fMRI imaging using both quantitative and qualitative methods. Differences have been observed in comparisons of active and resting, developing and aging, and defective and damaged brains in various studies. However, cognitive studies using fMRI still face a number of challenges in interpretation that can only be overcome by imaging large numbers of samples. Furthermore, fMRI studies of brain cancer, lesions and other brain pathologies of both humans and animals are still to be explored. PMID:28144401

  8. Automated image analysis of uterine cervical images

    NASA Astrophysics Data System (ADS)

    Li, Wenjing; Gu, Jia; Ferris, Daron; Poirson, Allen

    2007-03-01

    Cervical Cancer is the second most common cancer among women worldwide and the leading cause of cancer mortality of women in developing countries. If detected early and treated adequately, cervical cancer can be virtually prevented. Cervical precursor lesions and invasive cancer exhibit certain morphologic features that can be identified during a visual inspection exam. Digital imaging technologies allow us to assist the physician with a Computer-Aided Diagnosis (CAD) system. In colposcopy, epithelium that turns white after application of acetic acid is called acetowhite epithelium. Acetowhite epithelium is one of the major diagnostic features observed in detecting cancer and pre-cancerous regions. Automatic extraction of acetowhite regions from cervical images has been a challenging task due to specular reflection, various illumination conditions, and most importantly, large intra-patient variation. This paper presents a multi-step acetowhite region detection system to analyze the acetowhite lesions in cervical images automatically. First, the system calibrates the color of the cervical images to be independent of screening devices. Second, the anatomy of the uterine cervix is analyzed in terms of cervix region, external os region, columnar region, and squamous region. Third, the squamous region is further analyzed and subregions based on three levels of acetowhite are identified. The extracted acetowhite regions are accompanied by color scores to indicate the different levels of acetowhite. The system has been evaluated by 40 human subjects' data and demonstrates high correlation with experts' annotations.

  9. Functional laser speckle imaging of cerebral blood flow under hypothermia

    NASA Astrophysics Data System (ADS)

    Li, Minheng; Miao, Peng; Zhu, Yisheng; Tong, Shanbao

    2011-08-01

    Hypothermia can unintentionally occur in daily life, e.g., in cardiovascular surgery or applied as therapeutics in the neurosciences critical care unit. So far, the temperature-induced spatiotemporal responses of the neural function have not been fully understood. In this study, we investigated the functional change in cerebral blood flow (CBF), accompanied with neuronal activation, by laser speckle imaging (LSI) during hypothermia. Laser speckle images from Sprague-Dawley rats (n = 8, male) were acquired under normothermia (37°C) and moderate hypothermia (32°C). For each animal, 10 trials of electrical hindpaw stimulation were delivered under both temperatures. Using registered laser speckle contrast analysis and temporal clustering analysis (TCA), we found a delayed response peak and a prolonged response window under hypothermia. Hypothermia also decreased the activation area and the amplitude of the peak CBF. The combination of LSI and TCA is a high-resolution functional imaging method to investigate the spatiotemporal neurovascular coupling in both normal and pathological brain functions.

  10. PIZZARO: Forensic analysis and restoration of image and video data.

    PubMed

    Kamenicky, Jan; Bartos, Michal; Flusser, Jan; Mahdian, Babak; Kotera, Jan; Novozamsky, Adam; Saic, Stanislav; Sroubek, Filip; Sorel, Michal; Zita, Ales; Zitova, Barbara; Sima, Zdenek; Svarc, Petr; Horinek, Jan

    2016-07-01

    This paper introduces a set of methods for image and video forensic analysis. They were designed to help to assess image and video credibility and origin and to restore and increase image quality by diminishing unwanted blur, noise, and other possible artifacts. The motivation came from the best practices used in the criminal investigation utilizing images and/or videos. The determination of the image source, the verification of the image content, and image restoration were identified as the most important issues of which automation can facilitate criminalists work. Novel theoretical results complemented with existing approaches (LCD re-capture detection and denoising) were implemented in the PIZZARO software tool, which consists of the image processing functionality as well as of reporting and archiving functions to ensure the repeatability of image analysis procedures and thus fulfills formal aspects of the image/video analysis work. Comparison of new proposed methods with the state of the art approaches is shown. Real use cases are presented, which illustrate the functionality of the developed methods and demonstrate their applicability in different situations. The use cases as well as the method design were solved in tight cooperation of scientists from the Institute of Criminalistics, National Drug Headquarters of the Criminal Police and Investigation Service of the Police of the Czech Republic, and image processing experts from the Czech Academy of Sciences.

  11. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

    White, Amanda M.; Daly, Don S.; Willse, Alan R.; Protic, Miroslava; Chandler, Darrell P.

    2005-09-01

    The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

  12. Multispectral Image Analysis of Hurricane Gilbert

    DTIC Science & Technology

    1989-05-19

    Classification) Multispectral Image Analysis of Hurrican Gilbert (unclassified) 12. PERSONAL AUTHOR(S) Kleespies, Thomas J. (GL/LYS) 13a. TYPE OF REPORT...cloud top height. component, of tle image in the red channel, and similarly for the green and blue channels. Multispectral Muti.pectral image analysis can...However, there seems to be few references to the human range of vision, the selection as to which mllti.pp.tral image analysis of scenes or

  13. The synthesis and analysis of color images

    NASA Technical Reports Server (NTRS)

    Wandell, B. A.

    1985-01-01

    A method is described for performing the synthesis and analysis of digital color images. The method is based on two principles. First, image data are represented with respect to the separate physical factors, surface reflectance and the spectral power distribution of the ambient light, that give rise to the perceived color of an object. Second, the encoding is made efficient by using a basis expansion for the surface spectral reflectance and spectral power distribution of the ambient light that takes advantage of the high degree of correlation across the visible wavelengths normally found in such functions. Within this framework, the same basic methods can be used to synthesize image data for color display monitors and printed materials, and to analyze image data into estimates of the spectral power distribution and surface spectral reflectances. The method can be applied to a variety of tasks. Examples of applications include the color balancing of color images, and the identification of material surface spectral reflectance when the lighting cannot be completely controlled.

  14. Image analysis from root system pictures

    NASA Astrophysics Data System (ADS)

    Casaroli, D.; Jong van Lier, Q.; Metselaar, K.

    2009-04-01

    Root research has been hampered by a lack of good methods and by the amount of time involved in making measurements. In general the studies from root system are made with either monolith or minirhizotron method which is used as a quantitative tool but requires comparison with conventional destructive methods. This work aimed to analyze roots systems images, obtained from a root atlas book, to different crops in order to find the root length and root length density and correlate them with the literature. Five crops images from Zea mays, Secale cereale, Triticum aestivum, Medicago sativa and Panicum miliaceum were divided in horizontal and vertical layers. Root length distribution was analyzed for horizontal as well as vertical layers. In order to obtain the root length density, a cuboidal volume was supposed to correspond to each part of the image. The results from regression analyses showed root length distributions according to horizontal or vertical layers. It was possible to find the root length distribution for single horizontal layers as a function of vertical layers, and also for single vertical layers as a function of horizontal layers. Regression analysis showed good fits when the root length distributions were grouped in horizontal layers according to the distance from the root center. When root length distributions were grouped according to soil horizons the fits worsened. The resulting root length density estimates were lower than those commonly found in literature, possibly due to (1) the fact that the crop images resulted from single plant situations, while the analyzed field experiments had more than one plant; (2) root overlapping may occur in the field; (3) root experiments, both in the field and image analyses as performed here, are subject to sampling errors; (4) the (hand drawn) images used in this study may have omitted some of the smallest roots.

  15. Nanoparticle Functionalization and Its Potentials for Molecular Imaging

    PubMed Central

    Thiruppathi, Rukmani; Mishra, Sachin; Ganapathy, Mathangi

    2016-01-01

    Functionalization enhances the properties and characteristics of nanoparticles through surface modification, and enables them to play a major role in the field of medicine. In molecular imaging, quality functional images are required with proper differentiation which can be seen with high contrast to obtain viable information. This review article discusses how functionalization enhances molecular imaging and enables multimodal imaging by which images with combination of functions particular to each modality can be obtained. This also explains how nanoparticles interacting at molecular level, when functionalized with molecules can target the cells of interest or substances with high specificity, reducing background signal and allowing simultaneous therapies to be carried out while imaging. Functionalization allows imaging for a prolonged period and enables to track the cells over a period of time. Recent researches and progress in functionalizing the nanoparticles to specifically enhance bioimaging with different modalities and their applications are reviewed in this article. PMID:28331783

  16. Function Analysis and Decomposistion using Function Analysis Systems Technique

    SciTech Connect

    J. R. Wixson

    1999-06-01

    The "Father of Value Analysis", Lawrence D. Miles, was a design engineer for General Electric in Schenectady, New York. Miles developed the concept of function analysis to address difficulties in satisfying the requirements to fill shortages of high demand manufactured parts and electrical components during World War II. His concept of function analysis was further developed in the 1960s by Charles W. Bytheway, a design engineer at Sperry Univac in Salt Lake City, Utah. Charles Bytheway extended Mile's function analysis concepts and introduced the methodology called Function Analysis Systems Techniques (FAST) to the Society of American Value Engineers (SAVE) at their International Convention in 1965 (Bytheway 1965). FAST uses intuitive logic to decompose a high level, or objective function into secondary and lower level functions that are displayed in a logic diagram called a FAST model. Other techniques can then be applied to allocate functions to components, individuals, processes, or other entities that accomplish the functions. FAST is best applied in a team setting and proves to be an effective methodology for functional decomposition, allocation, and alternative development.

  17. Function Analysis and Decomposistion using Function Analysis Systems Technique

    SciTech Connect

    Wixson, James Robert

    1999-06-01

    The "Father of Value Analysis", Lawrence D. Miles, was a design engineer for General Electric in Schenectady, New York. Miles developed the concept of function analysis to address difficulties in satisfying the requirements to fill shortages of high demand manufactured parts and electrical components during World War II. His concept of function analysis was further developed in the 1960s by Charles W. Bytheway, a design engineer at Sperry Univac in Salt Lake City, Utah. Charles Bytheway extended Mile's function analysis concepts and introduced the methodology called Function Analysis Systems Technique (FAST) to the Society of American Value Engineers (SAVE) at their International Convention in 1965 (Bytheway 1965). FAST uses intuitive logic to decompose a high level, or objective function into secondary and lower level functions that are displayed in a logic diagram called a FAST model. Other techniques can then be applied to allocate functions to components, individuals, processes, or other entities that accomplish the functions. FAST is best applied in a team setting and proves to be an effective methodology for functional decomposition, allocation, and alternative development.

  18. Functional Group Analysis.

    ERIC Educational Resources Information Center

    Smith, Walter T., Jr.; Patterson, John M.

    1984-01-01

    Literature on analytical methods related to the functional groups of 17 chemical compounds is reviewed. These compounds include acids, acid azides, alcohols, aldehydes, ketones, amino acids, aromatic hydrocarbons, carbodiimides, carbohydrates, ethers, nitro compounds, nitrosamines, organometallic compounds, peroxides, phenols, silicon compounds,…

  19. Bidimensional measurements of right ventricular function for prediction of survival in patients with pulmonary hypertension: comparison of reproducibility and time of analysis with volumetric cardiac magnetic resonance imaging analysis

    PubMed Central

    Kamel, Ihab R.; Rastegar, Neda; Damico, Rachel; Kolb, Todd M.; Boyce, Danielle M.; Sager, Ala-Eddin S.; Skrok, Jan; Shehata, Monda L.; Vogel-Claussen, Jens; Bluemke, David A.; Girgis, Reda E.; Mathai, Stephen C.; Hassoun, Paul M.; Zimmerman, Stefan L.

    2015-01-01

    Abstract We tested the hypothesis that bidimensional measurements of right ventricular (RV) function obtained by cardiac magnetic resonance imaging (CMR) in patients with pulmonary arterial hypertension (PAH) are faster than volumetric measures and highly reproducible, with comparable ability to predict patient survival. CMR-derived tricuspid annular plane systolic excursion (TAPSE), RV fractional shortening (RVFS), RV fractional area change (RVFAC), standard functional and volumetric measures, and ventricular mass index (VMI) were compared with right heart catheterization data. CMR analysis time was recorded. Receiver operating characteristic curves, Kaplan-Meier, Cox proportional hazard (CPH), and Bland-Altman test were used for analysis. Forty-nine subjects with PAH and 18 control subjects were included. TAPSE, RVFS, RVFAC, RV ejection fraction, and VMI correlated significantly with pulmonary vascular resistance and mean pulmonary artery pressure (all P < 0.05). Patients were followed up for a mean (± standard deviation) of 2.5 ± 1.6 years. Kaplan-Meier curves showed that death was strongly associated with TAPSE <18 mm, RVFS <16.7%, and RVFAC <18.8%. In CPH models with TAPSE as dichotomized at 18 mm, TAPSE was significantly associated with risk of death in both unadjusted and adjusted models (hazard ratio, 4.8; 95% confidence interval, 2.0–11.3; P = 0.005 for TAPSE <18 mm). There was high intra- and interobserver agreement. Bidimensional measurements were faster (1.5 ± 0.3 min) than volumetric measures (25 ± 6 min). In conclusion, TAPSE, RVFS, and RVFAC measures are efficient measures of RV function by CMR that demonstrate significant correlation with invasive measures of PAH severity. In patients with PAH, TAPSE, RVFS, and RVFAC have high intra- and interobserver reproducibility and are more rapidly obtained than volumetric measures. TAPSE <18 mm by CMR was strongly and independently associated with survival in PAH. PMID:26401254

  20. Imaging of the diaphragm: anatomy and function.

    PubMed

    Nason, Laura K; Walker, Christopher M; McNeeley, Michael F; Burivong, Wanaporn; Fligner, Corinne L; Godwin, J David

    2012-01-01

    The diaphragm is the primary muscle of ventilation. Dysfunction of the diaphragm is an underappreciated cause of respiratory difficulties and may be due to a wide variety of entities, including surgery, trauma, tumor, and infection. Diaphragmatic disease usually manifests as elevation at chest radiography. Functional imaging with fluoroscopy (or ultrasonography or magnetic resonance imaging) is a simple and effective method of diagnosing diaphragmatic dysfunction, which can be classified as paralysis, weakness, or eventration. Diaphragmatic paralysis is indicated by absence of orthograde excursion on quiet and deep breathing, with paradoxical motion on sniffing. Diaphragmatic weakness is indicated by reduced or delayed orthograde excursion on deep breathing, with or without paradoxical motion on sniffing. Eventration is congenital thinning of a segment of diaphragmatic muscle and manifests as focal weakness. Treatment of diaphragmatic paralysis depends on the cause of the dysfunction and the severity of the symptoms. Treatment options include plication and phrenic nerve stimulation. Supplemental material available at http://radiographics.rsna.org/lookup/suppl/doi:10.1148/rg.322115127/-/DC1.

  1. Imaging regional renal function parameters using radionuclide tracers

    NASA Astrophysics Data System (ADS)

    Qiao, Yi

    compartment is presented. The blood curve and the radiorenogram are analyzed in great detail and a physiological analysis from the radiorenogram is given. Applications of Kuhn-Tucker multiplier methods are illustrated for the renal compartmental model in the field of nuclear medicine. Conventional kinetic data analysis methods, the maximum likehood method, and the weighted integration method are investigated and used for comparisons. Moreover, the effect of the blood background subtraction is shown by using the gamma camera images in man. Several functional images are calculated and the functional imaging technique is applied for evaluating renal function in man quantitatively and visually and compared with comments from a physician.

  2. Percent area coverage through image analysis

    NASA Astrophysics Data System (ADS)

    Wong, Chung M.; Hong, Sung M.; Liu, De-Ling

    2016-09-01

    The notion of percent area coverage (PAC) has been used to characterize surface cleanliness levels in the spacecraft contamination control community. Due to the lack of detailed particle data, PAC has been conventionally calculated by multiplying the particle surface density in predetermined particle size bins by a set of coefficients per MIL-STD-1246C. In deriving the set of coefficients, the surface particle size distribution is assumed to follow a log-normal relation between particle density and particle size, while the cross-sectional area function is given as a combination of regular geometric shapes. For particles with irregular shapes, the cross-sectional area function cannot describe the true particle area and, therefore, may introduce error in the PAC calculation. Other errors may also be introduced by using the lognormal surface particle size distribution function that highly depends on the environmental cleanliness and cleaning process. In this paper, we present PAC measurements from silicon witness wafers that collected fallouts from a fabric material after vibration testing. PAC calculations were performed through analysis of microscope images and compare them to values derived through the MIL-STD-1246C method. Our results showed that the MIL-STD-1246C method does provide a reasonable upper bound to the PAC values determined through image analysis, in particular for PAC values below 0.1.

  3. Principles and clinical applications of image analysis.

    PubMed

    Kisner, H J

    1988-12-01

    Image processing has traveled to the lunar surface and back, finding its way into the clinical laboratory. Advances in digital computers have improved the technology of image analysis, resulting in a wide variety of medical applications. Offering improvements in turnaround time, standardized systems, increased precision, and walkaway automation, digital image analysis has likely found a permanent home as a diagnostic aid in the interpretation of microscopic as well as macroscopic laboratory images.

  4. FFDM image quality assessment using computerized image texture analysis

    NASA Astrophysics Data System (ADS)

    Berger, Rachelle; Carton, Ann-Katherine; Maidment, Andrew D. A.; Kontos, Despina

    2010-04-01

    Quantitative measures of image quality (IQ) are routinely obtained during the evaluation of imaging systems. These measures, however, do not necessarily correlate with the IQ of the actual clinical images, which can also be affected by factors such as patient positioning. No quantitative method currently exists to evaluate clinical IQ. Therefore, we investigated the potential of using computerized image texture analysis to quantitatively assess IQ. Our hypothesis is that image texture features can be used to assess IQ as a measure of the image signal-to-noise ratio (SNR). To test feasibility, the "Rachel" anthropomorphic breast phantom (Model 169, Gammex RMI) was imaged with a Senographe 2000D FFDM system (GE Healthcare) using 220 unique exposure settings (target/filter, kVs, and mAs combinations). The mAs were varied from 10%-300% of that required for an average glandular dose (AGD) of 1.8 mGy. A 2.5cm2 retroareolar region of interest (ROI) was segmented from each image. The SNR was computed from the ROIs segmented from images linear with dose (i.e., raw images) after flat-field and off-set correction. Image texture features of skewness, coarseness, contrast, energy, homogeneity, and fractal dimension were computed from the Premium ViewTM postprocessed image ROIs. Multiple linear regression demonstrated a strong association between the computed image texture features and SNR (R2=0.92, p<=0.001). When including kV, target and filter as additional predictor variables, a stronger association with SNR was observed (R2=0.95, p<=0.001). The strong associations indicate that computerized image texture analysis can be used to measure image SNR and potentially aid in automating IQ assessment as a component of the clinical workflow. Further work is underway to validate our findings in larger clinical datasets.

  5. Familial Essential Tremor Studied With Functional Magnetic Resonance Imaging

    NASA Astrophysics Data System (ADS)

    Hernandez, A.; Salgado, P.; Gil, A.; Barrios, F. A.

    2003-09-01

    Functional Magnetic Resonance Imaging has become an important analytical tool to study neurodegenerative diseases. We applied the EPI-BOLD functional Magnetic Resonance Imaging technique to acquire functional images of patients with familial essential tremor (FET) disorder and healthy control volunteers, during a motor task activity. Functional and anatomic images were used to produce the brain activation maps of the patients and volunteers. These functional maps of the primary somatosensorial and motor cortexes of patients and control subjects were compared for functional differences per subject. The averaged functional brain images of eight of each case were acquired were, it can be clearly observed the differences in active zones. The results presented in this work show that there are differences in the functional maps during motor task activation between control subjects and FET patients suggesting a cerebral functional reorganization that can be mapped with BOLD-fMRI.

  6. Functional Generalized Structured Component Analysis.

    PubMed

    Suk, Hye Won; Hwang, Heungsun

    2016-12-01

    An extension of Generalized Structured Component Analysis (GSCA), called Functional GSCA, is proposed to analyze functional data that are considered to arise from an underlying smooth curve varying over time or other continua. GSCA has been geared for the analysis of multivariate data. Accordingly, it cannot deal with functional data that often involve different measurement occasions across participants and a large number of measurement occasions that exceed the number of participants. Functional GSCA addresses these issues by integrating GSCA with spline basis function expansions that represent infinite-dimensional curves onto a finite-dimensional space. For parameter estimation, functional GSCA minimizes a penalized least squares criterion by using an alternating penalized least squares estimation algorithm. The usefulness of functional GSCA is illustrated with gait data.

  7. Medical imaging 1995: Physiology and function from multidimensional images

    SciTech Connect

    Hoffman, E.A.

    1995-12-31

    This conference was held February 27--28, 1995 in San Diego, California. The purpose of the conference was to provide a forum for exchange of state-of-the art information on physiologic imaging. This meeting is unique in bringing together the physicists, image processors, workstation developers, experts in image perception, and the experts of picture archiving and display. Individual papers have been processed separately for inclusion in the appropriate data bases.

  8. Image analysis: a consumer's guide.

    PubMed

    Meyer, F

    1983-01-01

    The last years have seen an explosion of systems in image analysis. It is hard for the pathologist or the cytologist to make the right choice of equipment. All machines are stupid, and the only valuable thing is the human work put into it. So make your benefit of the work other people have done for you. Chose a method largely used on many systems and which has proved fertile in many domains and not only for your specific to day's application: Mathematical Morphology, to which are to be added the linear convolutions present on all machines is a strong candidate for becoming such a method. The paper illustrates a working day of an ideal system: research and diagnostic directed work during the working hours, automatic screening of cervical (or other) smears during night.

  9. Functional connectivity of the rodent brain using optical imaging

    NASA Astrophysics Data System (ADS)

    Guevara Codina, Edgar

    The aim of this thesis is to apply functional connectivity in a variety of animal models, using several optical imaging modalities. Even at rest, the brain shows high metabolic activity: the correlation in slow spontaneous fluctuations identifies remotely connected areas of the brain; hence the term "functional connectivity". Ongoing changes in spontaneous activity may provide insight into the neural processing that takes most of the brain metabolic activity, and so may provide a vast source of disease related changes. Brain hemodynamics may be modified during disease and affect resting-state activity. The thesis aims to better understand these changes in functional connectivity due to disease, using functional optical imaging. The optical imaging techniques explored in the first two contributions of this thesis are Optical Imaging of Intrinsic Signals and Laser Speckle Contrast Imaging, together they can estimate the metabolic rate of oxygen consumption, that closely parallels neural activity. They both have adequate spatial and temporal resolution and are well adapted to image the convexity of the mouse cortex. In the last article, a depth-sensitive modality called photoacoustic tomography was used in the newborn rat. Optical coherence tomography and laminar optical tomography were also part of the array of imaging techniques developed and applied in other collaborations. The first article of this work shows the changes in functional connectivity in an acute murine model of epileptiform activity. Homologous correlations are both increased and decreased with a small dependence on seizure duration. These changes suggest a potential decoupling between the hemodynamic parameters in resting-state networks, underlining the importance to investigate epileptic networks with several independent hemodynamic measures. The second study examines a novel murine model of arterial stiffness: the unilateral calcification of the right carotid. Seed-based connectivity analysis

  10. Simple Low Level Features for Image Analysis

    NASA Astrophysics Data System (ADS)

    Falcoz, Paolo

    As human beings, we perceive the world around us mainly through our eyes, and give what we see the status of “reality”; as such we historically tried to create ways of recording this reality so we could augment or extend our memory. From early attempts in photography like the image produced in 1826 by the French inventor Nicéphore Niépce (Figure 2.1) to the latest high definition camcorders, the number of recorded pieces of reality increased exponentially, posing the problem of managing all that information. Most of the raw video material produced today has lost its memory augmentation function, as it will hardly ever be viewed by any human; pervasive CCTVs are an example. They generate an enormous amount of data each day, but there is not enough “human processing power” to view them. Therefore the need for effective automatic image analysis tools is great, and a lot effort has been put in it, both from the academia and the industry. In this chapter, a review of some of the most important image analysis tools are presented.

  11. Naval Signal and Image Analysis Conference Report

    DTIC Science & Technology

    1998-02-26

    Arlington Hilton Hotel in Arlington, Virginia. The meeting was by invitation only and consisted of investigators in the ONR Signal and Image Analysis Program...in signal and image analysis . The conference provided an opportunity for technical interaction between academic researchers and Naval scientists and...plan future directions for the ONR Signal and Image Analysis Program as well as informal recommendations to the Program Officer.

  12. Neuronal correlates of functional magnetic resonance imaging in human temporal cortex

    PubMed Central

    Corina, David P.; Corrigan, Neva; Schoenfield-McNeill, Julie; Poliakov, Andrew; Zamora, Leona; Zanos, Stavros

    2010-01-01

    The relationship between changes in functional magnetic resonance imaging and neuronal activity remains controversial. Data collected during awake neurosurgical procedures for the treatment of epilepsy provided a rare opportunity to examine this relationship in human temporal association cortex. We obtained functional magnetic resonance imaging blood oxygen dependent signals, single neuronal activity and local field potentials from 8 to 300 Hz at 13 temporal cortical sites, from nine subjects, during paired associate learning and control measures. The relation between the functional magnetic resonance imaging signal and the electrophysiologic parameters was assessed in two ways: colocalization between significant changes in these signals on the same paired associate-control comparisons and multiple linear regressions of the electrophysiologic measures on the functional magnetic resonance imaging signal, across all tasks. Significant colocalization was present between increased functional magnetic resonance imaging signals and increased local field potentials power in the 50–250 Hz range. Local field potentials power greater than 100 Hz was also a significant regressor for the functional magnetic resonance imaging signal, establishing this local field potentials frequency range as a neuronal correlate of the functional magnetic resonance imaging signal. There was a trend for a relation between power in some low frequency local field potentials frequencies and the functional magnetic resonance imaging signal, for 8–15 Hz increases in the colocalization analysis and 16–23 Hz in the multiple linear regression analysis. Neither analysis provided evidence for an independent relation to frequency of single neuron activity. PMID:19773355

  13. Analyzing Receptive Fields, Classification Images and Functional Images: Challenges with Opportunities for Synergy

    PubMed Central

    Victor, Jonathan D

    2006-01-01

    In neurophysiology, psychophysics, optical imaging, and functional imaging studies, the investigator seeks a relationship between a high-dimensional variable, such as an image, and a categorical variable, such as the presence or absence of a spike or a behavior. The usual analysis strategy is fundamentally identical across these contexts – it amounts to calculating the average value of the high-dimensional variable for each value of the categorical variable, and comparing these results by subtraction. Though intuitive and straightforward, this procedure may be inaccurate or inefficient, and may overlook important detail. Sophisticated approaches have been developed within these several experimental contexts, but they are rarely applied beyond the context in which they were developed. Recognition of the relationships among these contexts has the potential to accelerate improvements in analytic methods and to increase the information that can be gleaned from experiments. PMID:16306893

  14. Satellite image analysis using neural networks

    NASA Technical Reports Server (NTRS)

    Sheldon, Roger A.

    1990-01-01

    The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

  15. An image analysis system for near-infrared (NIR) fluorescence lymph imaging

    NASA Astrophysics Data System (ADS)

    Zhang, Jingdan; Zhou, Shaohua Kevin; Xiang, Xiaoyan; Rasmussen, John C.; Sevick-Muraca, Eva M.

    2011-03-01

    Quantitative analysis of lymphatic function is crucial for understanding the lymphatic system and diagnosing the associated diseases. Recently, a near-infrared (NIR) fluorescence imaging system is developed for real-time imaging lymphatic propulsion by intradermal injection of microdose of a NIR fluorophore distal to the lymphatics of interest. However, the previous analysis software3, 4 is underdeveloped, requiring extensive time and effort to analyze a NIR image sequence. In this paper, we develop a number of image processing techniques to automate the data analysis workflow, including an object tracking algorithm to stabilize the subject and remove the motion artifacts, an image representation named flow map to characterize lymphatic flow more reliably, and an automatic algorithm to compute lymph velocity and frequency of propulsion. By integrating all these techniques to a system, the analysis workflow significantly reduces the amount of required user interaction and improves the reliability of the measurement.

  16. Imaging the wave functions of adsorbed molecules.

    PubMed

    Lüftner, Daniel; Ules, Thomas; Reinisch, Eva Maria; Koller, Georg; Soubatch, Serguei; Tautz, F Stefan; Ramsey, Michael G; Puschnig, Peter

    2014-01-14

    The basis for a quantum-mechanical description of matter is electron wave functions. For atoms and molecules, their spatial distributions and phases are known as orbitals. Although orbitals are very powerful concepts, experimentally only the electron densities and -energy levels are directly observable. Regardless whether orbitals are observed in real space with scanning probe experiments, or in reciprocal space by photoemission, the phase information of the orbital is lost. Here, we show that the experimental momentum maps of angle-resolved photoemission from molecular orbitals can be transformed to real-space orbitals via an iterative procedure which also retrieves the lost phase information. This is demonstrated with images obtained of a number of orbitals of the molecules pentacene (C22H14) and perylene-3,4,9,10-tetracarboxylic dianhydride (C24H8O6), adsorbed on silver, which are in excellent agreement with ab initio calculations. The procedure requires no a priori knowledge of the orbitals and is shown to be simple and robust.

  17. Microscopy image segmentation tool: Robust image data analysis

    SciTech Connect

    Valmianski, Ilya Monton, Carlos; Schuller, Ivan K.

    2014-03-15

    We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

  18. Microscopy image segmentation tool: robust image data analysis.

    PubMed

    Valmianski, Ilya; Monton, Carlos; Schuller, Ivan K

    2014-03-01

    We present a software package called Microscopy Image Segmentation Tool (MIST). MIST is designed for analysis of microscopy images which contain large collections of small regions of interest (ROIs). Originally developed for analysis of porous anodic alumina scanning electron images, MIST capabilities have been expanded to allow use in a large variety of problems including analysis of biological tissue, inorganic and organic film grain structure, as well as nano- and meso-scopic structures. MIST provides a robust segmentation algorithm for the ROIs, includes many useful analysis capabilities, and is highly flexible allowing incorporation of specialized user developed analysis. We describe the unique advantages MIST has over existing analysis software. In addition, we present a number of diverse applications to scanning electron microscopy, atomic force microscopy, magnetic force microscopy, scanning tunneling microscopy, and fluorescent confocal laser scanning microscopy.

  19. The Relationship Between Body Image and Sexual Function in Middle-Aged Women

    PubMed Central

    Afshari, Poorandokht; Houshyar, Zeinab; Javadifar, Nahid; Pourmotahari, Fatemeh; Jorfi, Maryam

    2016-01-01

    Introduction An individual’s social and marital function, interpersonal relationships, and quality of life may, sometimes be affected by negative body image. This study is aimed at determining the relationship between body image and sexual function in middle-aged women. Methods In this cross-sectional study, 437 middle-aged women, who were referred to various public healthcare centers in Ahvaz, Iran during 2014–2015, were selected. The Female Sexual Function Index (FSFI) and Body Shape Questionnaire (BSQ) were used for data collection. Chi-square, one-way analysis of variance, Spearman’s correlation test, and logistic regression analysis were performed for statistical analysis. Results Approximately 58% of the participants expressed satisfaction with their body image, 35% were mildly dissatisfied, and 7% were moderately dissatisfied with their body image. Body image had a significant negative relationship with sexual satisfaction and sexual function (p=0.005). Furthermore, there was a significant relationship between body image and sexual desire (p=0.022), pain (p=0.001), sexual arousal (p<0.0005), sexual orgasm (p=0.001), and sexual satisfaction (p<0.0005). Conclusion As the results indicated, body image is an important aspect of sexual health. In this study, women with a positive body image had higher sexual function valuation, compared to women with a negative body image. Also, body shape satisfaction was a predictor of sexual function. PMID:28070265

  20. Digital-image processing and image analysis of glacier ice

    USGS Publications Warehouse

    Fitzpatrick, Joan J.

    2013-01-01

    This document provides a methodology for extracting grain statistics from 8-bit color and grayscale images of thin sections of glacier ice—a subset of physical properties measurements typically performed on ice cores. This type of analysis is most commonly used to characterize the evolution of ice-crystal size, shape, and intercrystalline spatial relations within a large body of ice sampled by deep ice-coring projects from which paleoclimate records will be developed. However, such information is equally useful for investigating the stress state and physical responses of ice to stresses within a glacier. The methods of analysis presented here go hand-in-hand with the analysis of ice fabrics (aggregate crystal orientations) and, when combined with fabric analysis, provide a powerful method for investigating the dynamic recrystallization and deformation behaviors of bodies of ice in motion. The procedures described in this document compose a step-by-step handbook for a specific image acquisition and data reduction system built in support of U.S. Geological Survey ice analysis projects, but the general methodology can be used with any combination of image processing and analysis software. The specific approaches in this document use the FoveaPro 4 plug-in toolset to Adobe Photoshop CS5 Extended but it can be carried out equally well, though somewhat less conveniently, with software such as the image processing toolbox in MATLAB, Image-Pro Plus, or ImageJ.

  1. A Hitchhiker's Guide to Functional Magnetic Resonance Imaging

    PubMed Central

    Soares, José M.; Magalhães, Ricardo; Moreira, Pedro S.; Sousa, Alexandre; Ganz, Edward; Sampaio, Adriana; Alves, Victor; Marques, Paulo; Sousa, Nuno

    2016-01-01

    Functional Magnetic Resonance Imaging (fMRI) studies have become increasingly popular both with clinicians and researchers as they are capable of providing unique insights into brain functions. However, multiple technical considerations (ranging from specifics of paradigm design to imaging artifacts, complex protocol definition, and multitude of processing and methods of analysis, as well as intrinsic methodological limitations) must be considered and addressed in order to optimize fMRI analysis and to arrive at the most accurate and grounded interpretation of the data. In practice, the researcher/clinician must choose, from many available options, the most suitable software tool for each stage of the fMRI analysis pipeline. Herein we provide a straightforward guide designed to address, for each of the major stages, the techniques, and tools involved in the process. We have developed this guide both to help those new to the technique to overcome the most critical difficulties in its use, as well as to serve as a resource for the neuroimaging community. PMID:27891073

  2. Image processing software for imaging spectrometry data analysis

    NASA Technical Reports Server (NTRS)

    Mazer, Alan; Martin, Miki; Lee, Meemong; Solomon, Jerry E.

    1988-01-01

    Imaging spectrometers simultaneously collect image data in hundreds of spectral channels, from the near-UV to the IR, and can thereby provide direct surface materials identification by means resembling laboratory reflectance spectroscopy. Attention is presently given to a software system, the Spectral Analysis Manager (SPAM) for the analysis of imaging spectrometer data. SPAM requires only modest computational resources and is composed of one main routine and a set of subroutine libraries. Additions and modifications are relatively easy, and special-purpose algorithms have been incorporated that are tailored to geological applications.

  3. Image processing software for imaging spectrometry data analysis

    NASA Astrophysics Data System (ADS)

    Mazer, Alan; Martin, Miki; Lee, Meemong; Solomon, Jerry E.

    1988-02-01

    Imaging spectrometers simultaneously collect image data in hundreds of spectral channels, from the near-UV to the IR, and can thereby provide direct surface materials identification by means resembling laboratory reflectance spectroscopy. Attention is presently given to a software system, the Spectral Analysis Manager (SPAM) for the analysis of imaging spectrometer data. SPAM requires only modest computational resources and is composed of one main routine and a set of subroutine libraries. Additions and modifications are relatively easy, and special-purpose algorithms have been incorporated that are tailored to geological applications.

  4. Anatomic and functional imaging of tagged molecules in animals

    DOEpatents

    Weisenberger, Andrew G.; Majewski, Stanislaw; Paulus, Michael J.; Gleason, Shaun S.

    2007-04-24

    A novel functional imaging system for use in the imaging of unrestrained and non-anesthetized small animals or other subjects and a method for acquiring such images and further registering them with anatomical X-ray images previously or subsequently acquired. The apparatus comprises a combination of an IR laser profilometry system and gamma, PET and/or SPECT, imaging system, all mounted on a rotating gantry, that permits simultaneous acquisition of positional and orientational information and functional images of an unrestrained subject that are registered, i.e. integrated, using image processing software to produce a functional image of the subject without the use of restraints or anesthesia. The functional image thus obtained can be registered with a previously or subsequently obtained X-ray CT image of the subject. The use of the system described herein permits functional imaging of a subject in an unrestrained/non-anesthetized condition thereby reducing the stress on the subject and eliminating any potential interference with the functional testing that such stress might induce.

  5. Functional infrared imaging in medicine: a quantitative diagnostic approach.

    PubMed

    Merla, A; Romani, G L

    2006-01-01

    The role and the potentialities of high-resolution infrared thermography, combined to bio-heat modelling, have been largely described in the last years in a wide variety of biomedical applications. Quantitative assessment over time of the cutaneous temperature and/or of other biomedical parameters related to the temperature (e.g., cutaneous blood flow, thermal inertia, sympathetic skin response) allows for a better and more complete understanding and description of functional processes involved and/or altered in presence of ailment and interfering with the regular cutaneous thermoregulation. Such an approach to thermal medical imaging requires both new methodologies and tools, like diagnostic paradigms, appropriate software for data analysis and, even, a completely new way to look at data processing. In this paper, some of the studies recently made in our laboratory are presented and described, with the general intent of introducing the reader to these innovative methods to obtain quantitative diagnostic tools based on thermal imaging.

  6. Functional calcium imaging in developing cortical networks.

    PubMed

    Dawitz, Julia; Kroon, Tim; Hjorth, J J Johannes; Meredith, Rhiannon M

    2011-10-22

    A hallmark pattern of activity in developing nervous systems is spontaneous, synchronized network activity. Synchronized activity has been observed in intact spinal cord, brainstem, retina, cortex and dissociated neuronal culture preparations. During periods of spontaneous activity, neurons depolarize to fire single or bursts of action potentials, activating many ion channels. Depolarization activates voltage-gated calcium channels on dendrites and spines that mediate calcium influx. Highly synchronized electrical activity has been measured from local neuronal networks using field electrodes. This technique enables high temporal sampling rates but lower spatial resolution due to integrated read-out of multiple neurons at one electrode. Single cell resolution of neuronal activity is possible using patch-clamp electrophysiology on single neurons to measure firing activity. However, the ability to measure from a network is limited to the number of neurons patched simultaneously, and typically is only one or two neurons. The use of calcium-dependent fluorescent indicator dyes has enabled the measurement of synchronized activity across a network of cells. This technique gives both high spatial resolution and sufficient temporal sampling to record spontaneous activity of the developing network. A key feature of newly-forming cortical and hippocampal networks during pre- and early postnatal development is spontaneous, synchronized neuronal activity (Katz & Shatz, 1996; Khaziphov & Luhmann, 2006). This correlated network activity is believed to be essential for the generation of functional circuits in the developing nervous system (Spitzer, 2006). In both primate and rodent brain, early electrical and calcium network waves are observed pre- and postnatally in vivo and in vitro (Adelsberger et al., 2005; Garaschuk et al., 2000; Lamblin et al., 1999). These early activity patterns, which are known to control several developmental processes including neuronal differentiation

  7. Image registration with uncertainty analysis

    DOEpatents

    Simonson, Katherine M [Cedar Crest, NM

    2011-03-22

    In an image registration method, edges are detected in a first image and a second image. A percentage of edge pixels in a subset of the second image that are also edges in the first image shifted by a translation is calculated. A best registration point is calculated based on a maximum percentage of edges matched. In a predefined search region, all registration points other than the best registration point are identified that are not significantly worse than the best registration point according to a predetermined statistical criterion.

  8. Imaging structural and functional brain networks in temporal lobe epilepsy

    PubMed Central

    Bernhardt, Boris C.; Hong, SeokJun; Bernasconi, Andrea; Bernasconi, Neda

    2013-01-01

    Early imaging studies in temporal lobe epilepsy (TLE) focused on the search for mesial temporal sclerosis, as its surgical removal results in clinically meaningful improvement in about 70% of patients. Nevertheless, a considerable subgroup of patients continues to suffer from post-operative seizures. Although the reasons for surgical failure are not fully understood, electrophysiological and imaging data suggest that anomalies extending beyond the temporal lobe may have negative impact on outcome. This hypothesis has revived the concept of human epilepsy as a disorder of distributed brain networks. Recent methodological advances in non-invasive neuroimaging have led to quantify structural and functional networks in vivo. While structural networks can be inferred from diffusion MRI tractography and inter-regional covariance patterns of structural measures such as cortical thickness, functional connectivity is generally computed based on statistical dependencies of neurophysiological time-series, measured through functional MRI or electroencephalographic techniques. This review considers the application of advanced analytical methods in structural and functional connectivity analyses in TLE. We will specifically highlight findings from graph-theoretical analysis that allow assessing the topological organization of brain networks. These studies have provided compelling evidence that TLE is a system disorder with profound alterations in local and distributed networks. In addition, there is emerging evidence for the utility of network properties as clinical diagnostic markers. Nowadays, a network perspective is considered to be essential to the understanding of the development, progression, and management of epilepsy. PMID:24098281

  9. Common brain areas engaged in false belief reasoning and visual perspective taking: a meta-analysis of functional brain imaging studies

    PubMed Central

    Schurz, Matthias; Aichhorn, Markus; Martin, Anna; Perner, Josef

    2013-01-01

    We performed a quantitative meta-analysis of functional neuroimaging studies to identify brain areas which are commonly engaged in social and visuo-spatial perspective taking. Specifically, we compared brain activation for visual-perspective taking to activation for false belief reasoning, which requires awareness of perspective to understand someone's mistaken belief about the world which contrasts with reality. In support of a previous account by Perner and Leekam (2008), our meta-analytic conjunction analysis found common activation for false belief reasoning and visual perspective taking in the left but not the right dorsal temporo-parietal junction (TPJ). This fits with the idea that the left dorsal TPJ is responsible for representing different perspectives in a domain-general fashion. Moreover, our conjunction analysis found activation in the precuneus and the left middle occipital gyrus close to the putative Extrastriate Body Area (EBA). The precuneus is linked to mental-imagery which may aid in the construction of a different perspective. The EBA may be engaged due to imagined body-transformations when another's viewpoint is adopted. PMID:24198773

  10. In vivo hepatocyte MR imaging using lactose functionalized magnetoliposomes.

    PubMed

    Ketkar-Atre, Ashwini; Struys, Tom; Dresselaers, Tom; Hodenius, Michael; Mannaerts, Inge; Ni, Yicheng; Lambrichts, Ivo; Van Grunsven, Leo A; De Cuyper, Marcel; Himmelreich, Uwe

    2014-01-01

    The aim of this study was to assess a novel lactose functionalized magnetoliposomes (MLs) as an MR contrast agent to target hepatocytes as well as to evaluate the targeting ability of MLs for in vivo applications. In the present work, 17 nm sized iron oxide cores functionalized with anionic MLs bearing lactose moieties were used for targeting the asialoglycoprotein receptor (ASGP-r), which is highly expressed in hepatocytes. Non-functionalized anionic MLs were tested as negative controls. The size distribution of lactose and anionic MLs was determined by transmission electron microscopy (TEM) and dynamic light scattering (DLS). After intravenous administration of both MLs, contrast enhancement in the liver was observed by magnetic resonance imaging (MRI). Label retention was monitored non-invasively by MRI and validated with Prussian blue staining and TEM for up to eight days post MLs administration. Although the MRI signal intensity did not show significant differences between functionalized and non-functionalized particles, iron-specific Prussian blue staining and TEM analysis confirmed the uptake of lactose MLs mainly in hepatocytes. In contrast, non-functionalized anionic MLs were mainly taken up by Kupffer and sinusoidal cells. Target specificity was further confirmed by high-resolution MR imaging of phantoms containing isolated hepatocytes, Kupffer cell (KCs) and hepatic stellate cells (HSCs) fractions. Hypointense signal was observed for hepatocytes isolated from animals which received lactose MLs but not from animals which received anionic MLs. These data demonstrate that galactose-functionalized MLs can be used as a hepatocyte targeting MR contrast agent to potentially aid in the diagnosis of hepatic diseases if the non-specific uptake by KCs is taken into account.

  11. Functional tissue pulsatility imaging of the brain during visual stimulation.

    PubMed

    Kucewicz, John C; Dunmire, Barbrina; Leotta, Daniel F; Panagiotides, Heracles; Paun, Marla; Beach, Kirk W

    2007-05-01

    Functional tissue pulsatility imaging is a new ultrasonic technique being developed to map brain function by measuring changes in tissue pulsatility as a result of changes in blood flow with neuronal activation. The technique is based in principle on plethysmography, an older, nonultrasound technology for measuring expansion of a whole limb or body part as a result of perfusion. Perfused tissue expands by a fraction of a percent early in each cardiac cycle when arterial inflow exceeds venous outflow, and it relaxes later in the cardiac cycle when venous drainage dominates. Tissue pulsatility imaging (TPI) uses tissue Doppler signal processing methods to measure this pulsatile "plethysmographic" signal from hundreds or thousands of sample volumes in an ultrasound image plane. A feasibility study was conducted to determine if TPI could be used to detect regional brain activation during a visual contrast-reversing checkerboard block paradigm study. During a study, ultrasound data were collected transcranially from the occipital lobe as a subject viewed alternating blocks of a reversing checkerboard (stimulus condition) and a static, gray screen (control condition). Multivariate analysis of variance was used to identify sample volumes with significantly different pulsatility waveforms during the control and stimulus blocks. In 7 of 14 studies, consistent regions of activation were detected from tissue around the major vessels perfusing the visual cortex.

  12. Functional anatomy and imaging of the foot.

    PubMed

    Ridola, C; Palma, A

    2001-01-01

    ) suspending the arch from a cable above the level of the bridge. In this manner, we obtain a "functional unit" with two important aims: to support the body weight (static foot), and to serve as a lever to propel the bodies forward in walking and running (dinamic foot). Imaging techniques are able to provide further data on functional anatomy of the foot; in particular, these techniques show the bones structures, ligaments, muscles and tendons, taking part to the arch setting. Routine x-ray examinations precise information about the bone-shape and their relationship. The short and long ligaments, the tendons and the suspending the arch from above are instead successfully valuable using ultrasonography, CT and MR.

  13. Optical imaging of fast, dynamic neurophysiological function.

    SciTech Connect

    Rector, D. M.; Carter, K. M.; Yao, X.; George, J. S.

    2002-01-01

    Fast evoked responses were imaged from rat dorsal medulla and whisker barrel cortex. To investigate the biophysical mechanisms involved, fast optical responses associated with isolated crustacean nerve stimulation were recorded using birefringence and scattered light. Such studies allow optimization of non-invasive imaging techniques being developed for use in humans.

  14. A Mathematical Framework for Image Analysis

    DTIC Science & Technology

    1991-08-01

    The results reported here were derived from the research project ’A Mathematical Framework for Image Analysis ’ supported by the Office of Naval...Research, contract N00014-88-K-0289 to Brown University. A common theme for the work reported is the use of probabilistic methods for problems in image ... analysis and image reconstruction. Five areas of research are described: rigid body recognition using a decision tree/combinatorial approach; nonrigid

  15. Sparse Superpixel Unmixing for Hyperspectral Image Analysis

    NASA Technical Reports Server (NTRS)

    Castano, Rebecca; Thompson, David R.; Gilmore, Martha

    2010-01-01

    Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A superpixel segmentation strategy enables efficient unmixing in an interactive session. The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure). Mineralogical search strategies can be categorized as supervised or unsupervised. Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals.

  16. Image Reconstruction Using Analysis Model Prior

    PubMed Central

    Han, Yu; Du, Huiqian; Lam, Fan; Mei, Wenbo; Fang, Liping

    2016-01-01

    The analysis model has been previously exploited as an alternative to the classical sparse synthesis model for designing image reconstruction methods. Applying a suitable analysis operator on the image of interest yields a cosparse outcome which enables us to reconstruct the image from undersampled data. In this work, we introduce additional prior in the analysis context and theoretically study the uniqueness issues in terms of analysis operators in general position and the specific 2D finite difference operator. We establish bounds on the minimum measurement numbers which are lower than those in cases without using analysis model prior. Based on the idea of iterative cosupport detection (ICD), we develop a novel image reconstruction model and an effective algorithm, achieving significantly better reconstruction performance. Simulation results on synthetic and practical magnetic resonance (MR) images are also shown to illustrate our theoretical claims. PMID:27379171

  17. Ripening of salami: assessment of colour and aspect evolution using image analysis and multivariate image analysis.

    PubMed

    Fongaro, Lorenzo; Alamprese, Cristina; Casiraghi, Ernestina

    2015-03-01

    During ripening of salami, colour changes occur due to oxidation phenomena involving myoglobin. Moreover, shrinkage due to dehydration results in aspect modifications, mainly ascribable to fat aggregation. The aim of this work was the application of image analysis (IA) and multivariate image analysis (MIA) techniques to the study of colour and aspect changes occurring in salami during ripening. IA results showed that red, green, blue, and intensity parameters decreased due to the development of a global darker colour, while Heterogeneity increased due to fat aggregation. By applying MIA, different salami slice areas corresponding to fat and three different degrees of oxidised meat were identified and quantified. It was thus possible to study the trend of these different areas as a function of ripening, making objective an evaluation usually performed by subjective visual inspection.

  18. Image Harvest: an open-source platform for high-throughput plant image processing and analysis

    PubMed Central

    Knecht, Avi C.; Campbell, Malachy T.; Caprez, Adam; Swanson, David R.; Walia, Harkamal

    2016-01-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets. PMID:27141917

  19. Image Harvest: an open-source platform for high-throughput plant image processing and analysis.

    PubMed

    Knecht, Avi C; Campbell, Malachy T; Caprez, Adam; Swanson, David R; Walia, Harkamal

    2016-05-01

    High-throughput plant phenotyping is an effective approach to bridge the genotype-to-phenotype gap in crops. Phenomics experiments typically result in large-scale image datasets, which are not amenable for processing on desktop computers, thus creating a bottleneck in the image-analysis pipeline. Here, we present an open-source, flexible image-analysis framework, called Image Harvest (IH), for processing images originating from high-throughput plant phenotyping platforms. Image Harvest is developed to perform parallel processing on computing grids and provides an integrated feature for metadata extraction from large-scale file organization. Moreover, the integration of IH with the Open Science Grid provides academic researchers with the computational resources required for processing large image datasets at no cost. Image Harvest also offers functionalities to extract digital traits from images to interpret plant architecture-related characteristics. To demonstrate the applications of these digital traits, a rice (Oryza sativa) diversity panel was phenotyped and genome-wide association mapping was performed using digital traits that are used to describe different plant ideotypes. Three major quantitative trait loci were identified on rice chromosomes 4 and 6, which co-localize with quantitative trait loci known to regulate agronomically important traits in rice. Image Harvest is an open-source software for high-throughput image processing that requires a minimal learning curve for plant biologists to analyzephenomics datasets.

  20. Image analysis of dye stained patterns in soils

    NASA Astrophysics Data System (ADS)

    Bogner, Christina; Trancón y Widemann, Baltasar; Lange, Holger

    2013-04-01

    Quality of surface water and groundwater is directly affected by flow processes in the unsaturated zone. In general, it is difficult to measure or model water flow. Indeed, parametrization of hydrological models is problematic and often no unique solution exists. To visualise flow patterns in soils directly dye tracer studies can be done. These experiments provide images of stained soil profiles and their evaluation demands knowledge in hydrology as well as in image analysis and statistics. First, these photographs are converted to binary images classifying the pixels in dye stained and non-stained ones. Then, some feature extraction is necessary to discern relevant hydrological information. In our study we propose to use several index functions to extract different (ideally complementary) features. We associate each image row with a feature vector (i.e. a certain number of image function values) and use these features to cluster the image rows to identify similar image areas. Because images of stained profiles might have different reasonable clusterings, we calculate multiple consensus clusterings. An expert can explore these different solutions and base his/her interpretation of predominant flow mechanisms on quantitative (objective) criteria. The complete workflow from reading-in binary images to final clusterings has been implemented in the free R system, a language and environment for statistical computing. The calculation of image indices is part of our own package Indigo, manipulation of binary images, clustering and visualization of results are done using either build-in facilities in R, additional R packages or the LATEX system.

  1. Histology image analysis for carcinoma detection and grading

    PubMed Central

    He, Lei; Long, L. Rodney; Antani, Sameer; Thoma, George R.

    2012-01-01

    This paper presents an overview of the image analysis techniques in the domain of histopathology, specifically, for the objective of automated carcinoma detection and classification. As in other biomedical imaging areas such as radiology, many computer assisted diagnosis (CAD) systems have been implemented to aid histopathologists and clinicians in cancer diagnosis and research, which have been attempted to significantly reduce the labor and subjectivity of traditional manual intervention with histology images. The task of automated histology image analysis is usually not simple due to the unique characteristics of histology imaging, including the variability in image preparation techniques, clinical interpretation protocols, and the complex structures and very large size of the images themselves. In this paper we discuss those characteristics, provide relevant background information about slide preparation and interpretation, and review the application of digital image processing techniques to the field of histology image analysis. In particular, emphasis is given to state-of-the-art image segmentation methods for feature extraction and disease classification. Four major carcinomas of cervix, prostate, breast, and lung are selected to illustrate the functions and capabilities of existing CAD systems. PMID:22436890

  2. Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

    NASA Technical Reports Server (NTRS)

    Guseman, L. F., Jr.

    1985-01-01

    Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

  3. Dynamic Ultrasound Imaging Applications to Quantify Musculoskeletal Function

    PubMed Central

    Sikdar, Siddhartha; Wei, Qi; Cortes, Nelson

    2014-01-01

    Advances in imaging methods have led to new capability to study muscle and tendon motion in vivo. Direct measurements of muscle and tendon kinematics using imaging may lead to improved understanding of musculoskeletal function. This review presents quantitative ultrasound methods for muscle dynamics that can be used to assess in vivo musculoskeletal function when integrated with other conventional biomechanical measurements. PMID:24949846

  4. Dynamic ultrasound imaging applications to quantify musculoskeletal function.

    PubMed

    Sikdar, Siddhartha; Wei, Qi; Cortes, Nelson

    2014-07-01

    Advances in imaging methods have led to new capability to study muscle and tendon motion in vivo. Direct measurements of muscle and tendon kinematics using imaging may lead to improved understanding of musculoskeletal function. This review presents quantitative ultrasound methods for muscle dynamics that can be used to assess in vivo musculoskeletal function when integrated with other conventional biomechanical measurements.

  5. Stereotactic PET atlas of the human brain: Aid for visual interpretation of functional brain images

    SciTech Connect

    Minoshima, S.; Koeppe, R.A.; Frey, A.; Ishihara, M.; Kuhl, D.E.

    1994-06-01

    In the routine analysis of functional brain images obtained by PET, subjective visual interpretation is often used for anatomic localization. To enhance the accuracy and consistency of the anatomic interpretation, a PET stereotactic atlas and localization approach was designed for functional brain images. The PET atlas was constructed from a high-resolution [{sup 18}F]fluorodeoxyglucose (FDG) image set of a normal volunteer (a 41-yr-ld woman). The image set was reoriented stereotactically, according to the intercommissural (anterior and posterior commissures) line and transformed to the standard stereotactic atlas coordinates. Cerebral structures were annotated on the transaxial planes using a proportional grid system and surface-rendered images. The stereotactic localization technique was applied to image sets from patients with Alzheimer`s disease, and areas of functional alteration were localized visually by referring to the PET atlas. Major brain structures were identified on both transaxial planes and surface-rendered images. In the stereotactic system, anatomic correspondence between the PET atlas and stereotactically reoriented individual image sets of patients with Alzheimer`s disease facilitated both indirect and direct localization of the cerebral structures. Because rapid stereotactic alignment methods for PET images are now available for routine use, the PET atlas will serve as an aid for visual interpretation of functional brain images in the stereotactic system. Widespread application of stereotactic localization may be used in functional brain images, not only in the research setting, but also in routine clinical situations. 41 refs., 3 figs.

  6. The Land Analysis System (LAS) for multispectral image processing

    USGS Publications Warehouse

    Wharton, S. W.; Lu, Y. C.; Quirk, Bruce K.; Oleson, Lyndon R.; Newcomer, J. A.; Irani, Frederick M.

    1988-01-01

    The Land Analysis System (LAS) is an interactive software system available in the public domain for the analysis, display, and management of multispectral and other digital image data. LAS provides over 240 applications functions and utilities, a flexible user interface, complete online and hard-copy documentation, extensive image-data file management, reformatting, conversion utilities, and high-level device independent access to image display hardware. The authors summarize the capabilities of the current release of LAS (version 4.0) and discuss plans for future development. Particular emphasis is given to the issue of system portability and the importance of removing and/or isolating hardware and software dependencies.

  7. The Scientific Image in Behavior Analysis.

    PubMed

    Keenan, Mickey

    2016-05-01

    Throughout the history of science, the scientific image has played a significant role in communication. With recent developments in computing technology, there has been an increase in the kinds of opportunities now available for scientists to communicate in more sophisticated ways. Within behavior analysis, though, we are only just beginning to appreciate the importance of going beyond the printing press to elucidate basic principles of behavior. The aim of this manuscript is to stimulate appreciation of both the role of the scientific image and the opportunities provided by a quick response code (QR code) for enhancing the functionality of the printed page. I discuss the limitations of imagery in behavior analysis ("Introduction"), and I show examples of what can be done with animations and multimedia for teaching philosophical issues that arise when teaching about private events ("Private Events 1 and 2"). Animations are also useful for bypassing ethical issues when showing examples of challenging behavior ("Challenging Behavior"). Each of these topics can be accessed only by scanning the QR code provided. This contingency has been arranged to help the reader embrace this new technology. In so doing, I hope to show its potential for going beyond the limitations of the printing press.

  8. Generating Text from Functional Brain Images

    PubMed Central

    Pereira, Francisco; Detre, Greg; Botvinick, Matthew

    2011-01-01

    Recent work has shown that it is possible to take brain images acquired during viewing of a scene and reconstruct an approximation of the scene from those images. Here we show that it is also possible to generate text about the mental content reflected in brain images. We began with images collected as participants read names of concrete items (e.g., “Apartment’’) while also seeing line drawings of the item named. We built a model of the mental semantic representation of concrete concepts from text data and learned to map aspects of such representation to patterns of activation in the corresponding brain image. In order to validate this mapping, without accessing information about the items viewed for left-out individual brain images, we were able to generate from each one a collection of semantically pertinent words (e.g., “door,” “window” for “Apartment’’). Furthermore, we show that the ability to generate such words allows us to perform a classification task and thus validate our method quantitatively. PMID:21927602

  9. LANDSAT-4 image data quality analysis

    NASA Technical Reports Server (NTRS)

    Anuta, P. E.

    1984-01-01

    Methods were developed for estimating point spread functions from image data. Roads and bridges in dark backgrounds are being examined as well as other smoothing methods for reducing noise in the estimated point spread function. Tomographic techniques were used to estimate two dimensional point spread functions. Reformatting software changes were implemented to handle formats for LANDSAT-5 data.

  10. Description, Recognition and Analysis of Biological Images

    SciTech Connect

    Yu Donggang; Jin, Jesse S.; Luo Suhuai; Pham, Tuan D.; Lai Wei

    2010-01-25

    Description, recognition and analysis biological images plays an important role for human to describe and understand the related biological information. The color images are separated by color reduction. A new and efficient linearization algorithm is introduced based on some criteria of difference chain code. A series of critical points is got based on the linearized lines. The series of curvature angle, linearity, maximum linearity, convexity, concavity and bend angle of linearized lines are calculated from the starting line to the end line along all smoothed contours. The useful method can be used for shape description and recognition. The analysis, decision, classification of the biological images are based on the description of morphological structures, color information and prior knowledge, which are associated each other. The efficiency of the algorithms is described based on two applications. One application is the description, recognition and analysis of color flower images. Another one is related to the dynamic description, recognition and analysis of cell-cycle images.

  11. Structural and Functional Imaging in Parkinsonian Syndromes

    PubMed Central

    Hunt, Christopher H.; Johnson, Geoffrey B.; Morreale, Robert F.; Lowe, Val J.; Peller, Patrick J.

    2014-01-01

    Movement disorders with parkinsonian features are common, and in recent years imaging has assumed a greater role in diagnosis and management. Thus, it is important that radiologists become familiar with the most common imaging patterns of parkinsonism, especially given the significant clinical overlap and diagnostic difficulty associated with these disorders. The authors review the most common magnetic resonance (MR) and molecular imaging patterns of idiopathic Parkinson disease and atypical parkinsonian syndromes. They also discuss the interpretation of clinically available molecular imaging studies, including assessment of cerebral metabolism with 2-[fluorine-18]fluoro-2-deoxy-d-glucose (FDG) positron emission tomography (PET), cortical amyloid deposition with carbon 11 (11C) Pittsburgh compound B and fluorine 18 (18F) florbetapir PET, and dopaminergic activity with iodine 123 (123I) ioflupane single photon emission computed tomography (SPECT). Although no single imaging test is diagnostic, a combination of tests may help narrow the differential diagnosis. Findings at 123I ioflupane SPECT can confirm the loss of dopaminergic neurons in patients with parkinsonism and help distinguish these syndromes from treatable conditions, including essential tremor and drug-induced parkinsonism. FDG PET uptake can demonstrate patterns of neuronal dysfunction that are specific to a particular parkinsonian syndrome. Although MR imaging findings are typically nonspecific in parkinsonian syndromes, classic patterns of T2 signal change can be seen in multiple system atrophy and progressive supranuclear palsy. Finally, positive amyloid-binding PET findings can support the diagnosis of dementia with Lewy bodies. Combined with a thorough clinical evaluation, multimodality imaging information can afford accurate diagnosis, allow selection of appropriate therapy, and provide important prognostic information. ©RSNA, 2014 PMID:25208280

  12. Space station functional relationships analysis

    NASA Technical Reports Server (NTRS)

    Tullis, Thomas S.; Bied, Barbra R.

    1988-01-01

    A systems engineering process is developed to assist Space Station designers to understand the underlying operational system of the facility so that it can be physically arranged and configured to support crew productivity. The study analyzes the operational system proposed for the Space Station in terms of mission functions, crew activities, and functional relationships in order to develop a quantitative model for evaluation of interior layouts, configuration, and traffic analysis for any Station configuration. Development of the model involved identification of crew functions, required support equipment, criteria of assessing functional relationships, and tools for analyzing functional relationship matrices, as well as analyses of crew transition frequency, sequential dependencies, support equipment requirements, potential for noise interference, need for privacy, and overall compatability of functions. The model can be used for analyzing crew functions for the Initial Operating Capability of the Station and for detecting relationships among these functions. Note: This process (FRA) was used during Phase B design studies to test optional layouts of the Space Station habitat module. The process is now being automated as a computer model for use in layout testing of the Space Station laboratory modules during Phase C.

  13. Optical Analysis of Microscope Images

    NASA Astrophysics Data System (ADS)

    Biles, Jonathan R.

    Microscope images were analyzed with coherent and incoherent light using analog optical techniques. These techniques were found to be useful for analyzing large numbers of nonsymbolic, statistical microscope images. In the first part phase coherent transparencies having 20-100 human multiple myeloma nuclei were simultaneously photographed at 100 power magnification using high resolution holographic film developed to high contrast. An optical transform was obtained by focussing the laser onto each nuclear image and allowing the diffracted light to propagate onto a one dimensional photosensor array. This method reduced the data to the position of the first two intensity minima and the intensity of successive maxima. These values were utilized to estimate the four most important cancer detection clues of nuclear size, shape, darkness, and chromatin texture. In the second part, the geometric and holographic methods of phase incoherent optical processing were investigated for pattern recognition of real-time, diffuse microscope images. The theory and implementation of these processors was discussed in view of their mutual problems of dimness, image bias, and detector resolution. The dimness problem was solved by either using a holographic correlator or a speckle free laser microscope. The latter was built using a spinning tilted mirror which caused the speckle to change so quickly that it averaged out during the exposure. To solve the bias problem low image bias templates were generated by four techniques: microphotography of samples, creation of typical shapes by computer graphics editor, transmission holography of photoplates of samples, and by spatially coherent color image bias removal. The first of these templates was used to perform correlations with bacteria images. The aperture bias was successfully removed from the correlation with a video frame subtractor. To overcome the limited detector resolution it is necessary to discover some analog nonlinear intensity

  14. A collaborative biomedical image mining framework: application on the image analysis of microscopic kidney biopsies.

    PubMed

    Goudas, T; Doukas, C; Chatziioannou, A; Maglogiannis, I

    2013-01-01

    The analysis and characterization of biomedical image data is a complex procedure involving several processing phases, like data acquisition, preprocessing, segmentation, feature extraction and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image data set and experiment type. They may thus necessitate advanced image processing and classification knowledge and skills from the side of the biomedical expert. In this work, an application, exploiting web services and applying ontological modeling, is presented, to enable the intelligent creation of image mining workflows. The described tool can be directly integrated to the RapidMiner, Taverna or similar workflow management platforms. A case study dealing with the creation of a sample workflow for the analysis of kidney biopsy microscopy images is presented to demonstrate the functionality of the proposed framework.

  15. Imaging flow cytometry for phytoplankton analysis.

    PubMed

    Dashkova, Veronika; Malashenkov, Dmitry; Poulton, Nicole; Vorobjev, Ivan; Barteneva, Natasha S

    2017-01-01

    This review highlights the concepts and instrumentation of imaging flow cytometry technology and in particular its use for phytoplankton analysis. Imaging flow cytometry, a hybrid technology combining speed and statistical capabilities of flow cytometry with imaging features of microscopy, is rapidly advancing as a cell imaging platform that overcomes many of the limitations of current techniques and contributed significantly to the advancement of phytoplankton analysis in recent years. This review presents the various instrumentation relevant to the field and currently used for assessment of complex phytoplankton communities' composition and abundance, size structure determination, biovolume estimation, detection of harmful algal bloom species, evaluation of viability and metabolic activity and other applications. Also we present our data on viability and metabolic assessment of Aphanizomenon sp. cyanobacteria using Imagestream X Mark II imaging cytometer. Herein, we highlight the immense potential of imaging flow cytometry for microalgal research, but also discuss limitations and future developments.

  16. Digital Image Analysis for DETCHIP® Code Determination

    PubMed Central

    Lyon, Marcus; Wilson, Mark V.; Rouhier, Kerry A.; Symonsbergen, David J.; Bastola, Kiran; Thapa, Ishwor; Holmes, Andrea E.

    2013-01-01

    DETECHIP® is a molecular sensing array used for identification of a large variety of substances. Previous methodology for the analysis of DETECHIP® used human vision to distinguish color changes induced by the presence of the analyte of interest. This paper describes several analysis techniques using digital images of DETECHIP®. Both a digital camera and flatbed desktop photo scanner were used to obtain Jpeg images. Color information within these digital images was obtained through the measurement of red-green-blue (RGB) values using software such as GIMP, Photoshop and ImageJ. Several different techniques were used to evaluate these color changes. It was determined that the flatbed scanner produced in the clearest and more reproducible images. Furthermore, codes obtained using a macro written for use within ImageJ showed improved consistency versus pervious methods. PMID:25267940

  17. Analysis of radar images by means of digital terrain models

    NASA Technical Reports Server (NTRS)

    Domik, G.; Leberl, F.; Kobrick, M.

    1984-01-01

    It is pointed out that the importance of digital terrain models in the processing, analysis, and interpretation of remote sensing data is increasing. In investigations related to the study of radar images, digital terrain models can have a particular significance, because radar reflection is a function of the terrain characteristics. A procedure for the analysis and interpretation of radar images is discussed. The procedure is based on a utilization of computer simulation which makes it possible to produce simulated radar images on the basis of a digital terrain model. The simulated radar images are used for the geometric and radiometric rectification of real radar images. A description of the employed procedures is provided, and the obtained results are discussed, taking into account a test area in Northern California.

  18. Materials characterization through quantitative digital image analysis

    SciTech Connect

    J. Philliber; B. Antoun; B. Somerday; N. Yang

    2000-07-01

    A digital image analysis system has been developed to allow advanced quantitative measurement of microstructural features. This capability is maintained as part of the microscopy facility at Sandia, Livermore. The system records images digitally, eliminating the use of film. Images obtained from other sources may also be imported into the system. Subsequent digital image processing enhances image appearance through the contrast and brightness adjustments. The system measures a variety of user-defined microstructural features--including area fraction, particle size and spatial distributions, grain sizes and orientations of elongated particles. These measurements are made in a semi-automatic mode through the use of macro programs and a computer controlled translation stage. A routine has been developed to create large montages of 50+ separate images. Individual image frames are matched to the nearest pixel to create seamless montages. Results from three different studies are presented to illustrate the capabilities of the system.

  19. Imaging System and Method for Biomedical Analysis

    DTIC Science & Technology

    2013-03-11

    compressive decoding of sparse objects” by A. Coskum et al. 136 Analyst No. 17, pp. 3512–3518, (7 September 2011). Their fluorescent microscopy lensless ...prior art concept is a lensless imaging system proposed in a research paper entitled “ Lensless wide-field fluorescent imaging on a chip using...analysis. [0008] An article published by Sang Jun Moon et al., “Integrating Micro-fluidics and Lensless Imaging for Point-of- Care,” 24 Biosens

  20. Theory of Image Analysis and Recognition.

    DTIC Science & Technology

    1983-01-24

    Narendra Ahuja Image models Ramalingam Chellappa Image models Matti Pietikainen * Texture analysis b David G. Morgenthaler’ 3D digital geometry c Angela Y. Wu...Restoration Parameter Choice A Quantitative Guide," TR-965, October 1980. 70. Matti Pietikainen , "On the Use of Hierarchically Computed ’Mexican Hat...81. Matti Pietikainen and Azriel Rosenfeld, "Image Segmenta- tion by Texture Using Pyramid Node Linking," TR-1008, February 1981. 82. David G. 1

  1. Statistical approaches to human brain mapping by functional magnetic resonance imaging.

    PubMed

    Lange, N

    1996-02-28

    Proper use of functional neuro-imaging through effective experimental design and modern statistical analysis provides new insights in current brain research. This tutorial has two aims: to describe aspects of this technology to applied statisticians and to provide some statistical ideas to neuroscientists unfamiliar with quantitative analytic methods that accommodate randomness. Introductory background material and ample references to current literature on the physics of magnetic resonance imaging, Fourier methods for image reconstruction and measures of image quality are included. Two of the statistical approaches mentioned here are extensions of established methods for longitudinal data analysis to the frequency domain. A recent case study provides real-world instances of approaches, problems and open questions encountered in current functional neuro-imaging research and an introduction to the analysis of spatial time series in this context.

  2. Functional imaging in treatment planning in radiation therapy: a review.

    PubMed

    Perez, Carlos A; Bradley, Jeffrey; Chao, Clifford K S; Grigsby, Perry W; Mutic, Sasa; Malyapa, Robert

    2002-01-01

    The remarkable technical developments obtained in radiation oncology have resulted in an increasing use of image-based treatment planning in radiation therapy for three-dimensional and intensity modulated radiation therapy, stereotactic irradiation and image-guided brachytherapy. There has been increased use of computer-based record and verify systems as well as electronic portal imaging to enhance treatment delivery. From the data presented it is evident that PET scanning and other functional imaging techniques play a major role in the definition of tumor extent and staging of patients with cancer. The recent introduction of a combined CT and PET scanner will substantially simplify image acquisition and treatment planning.

  3. A Meta-analysis on the neural basis of planning: Activation likelihood estimation of functional brain imaging results in the Tower of London task.

    PubMed

    Nitschke, Kai; Köstering, Lena; Finkel, Lisa; Weiller, Cornelius; Kaller, Christoph P

    2017-01-01

    The ability to mentally design and evaluate series of future actions has often been studied in terms of planning abilities, commonly using well-structured laboratory tasks like the Tower of London (ToL). Despite a wealth of studies, findings on the specific localization of planning processes within prefrontal cortex (PFC) and on the hemispheric lateralization are equivocal. Here, we address this issue by integrating evidence from two different sources of data: First, we provide a systematic overview of the existing lesion data on planning in the ToL (10 studies, 211 patients) which does not indicate any evidence for a general lateralization of planning processes in (pre)frontal cortex. Second, we report a quantitative meta-analysis with activation likelihood estimation based on 31 functional neuroimaging datasets on the ToL. Separate meta-analyses of the activation patterns reported for Overall Planning (537 participants) and for Planning Complexity (182 participants) congruently show bilateral contributions of mid-dorsolateral PFC, frontal eye fields, supplementary motor area, precuneus, caudate, anterior insula, and inferior parietal cortex in addition to a left-lateralized involvement of rostrolateral PFC. In contrast to previous attributions of planning-related brain activity to the entire dorsolateral prefrontal cortex (dlPFC) and either its left or right homolog derived from single studies on the ToL, the present meta-analyses stress the pivotal role specifically of the mid-dorsolateral part of PFC (mid-dlPFC), presumably corresponding to Brodmann Areas 46 and 9/46, and strongly argue for a bilateral rather than lateralized involvement of the dlPFC in planning in the ToL. Hum Brain Mapp 38:396-413, 2017. © 2016 Wiley Periodicals, Inc.

  4. The impact of functional imaging on radiation medicine.

    PubMed

    Sharma, Nidhi; Neumann, Donald; Macklis, Roger

    2008-09-15

    Radiation medicine has previously utilized planning methods based primarily on anatomic and volumetric imaging technologies such as CT (Computerized Tomography), ultrasound, and MRI (Magnetic Resonance Imaging). In recent years, it has become apparent that a new dimension of non-invasive imaging studies may hold great promise for expanding the utility and effectiveness of the treatment planning process. Functional imaging such as PET (Positron Emission Tomography) studies and other nuclear medicine based assays are beginning to occupy a larger place in the oncology imaging world. Unlike the previously mentioned anatomic imaging methodologies, functional imaging allows differentiation between metabolically dead and dying cells and those which are actively metabolizing. The ability of functional imaging to reproducibly select viable and active cell populations in a non-invasive manner is now undergoing validation for many types of tumor cells. Many histologic subtypes appear amenable to this approach, with impressive sensitivity and selectivity reported. For clinical radiation medicine, the ability to differentiate between different levels and types of metabolic activity allows the possibility of risk based focal treatments in which the radiation doses and fields are more tightly connected to the perceived risk of recurrence or progression at each location. This review will summarize many of the basic principles involved in the field of functional PET imaging for radiation oncology planning and describe some of the major relevant published data behind this expanding trend.

  5. Digital image processing in cephalometric analysis.

    PubMed

    Jäger, A; Döler, W; Schormann, T

    1989-01-01

    Digital image processing methods were applied to improve the practicability of cephalometric analysis. The individual X-ray film was digitized by the aid of a high resolution microscope-photometer. Digital processing was done using a VAX 8600 computer system. An improvement of the image quality was achieved by means of various digital enhancement and filtering techniques.

  6. Segmentation and learning in the quantitative analysis of microscopy images

    NASA Astrophysics Data System (ADS)

    Ruggiero, Christy; Ross, Amy; Porter, Reid

    2015-02-01

    In material science and bio-medical domains the quantity and quality of microscopy images is rapidly increasing and there is a great need to automatically detect, delineate and quantify particles, grains, cells, neurons and other functional "objects" within these images. These are challenging problems for image processing because of the variability in object appearance that inevitably arises in real world image acquisition and analysis. One of the most promising (and practical) ways to address these challenges is interactive image segmentation. These algorithms are designed to incorporate input from a human operator to tailor the segmentation method to the image at hand. Interactive image segmentation is now a key tool in a wide range of applications in microscopy and elsewhere. Historically, interactive image segmentation algorithms have tailored segmentation on an image-by-image basis, and information derived from operator input is not transferred between images. But recently there has been increasing interest to use machine learning in segmentation to provide interactive tools that accumulate and learn from the operator input over longer periods of time. These new learning algorithms reduce the need for operator input over time, and can potentially provide a more dynamic balance between customization and automation for different applications. This paper reviews the state of the art in this area, provides a unified view of these algorithms, and compares the segmentation performance of various design choices.

  7. EVENT PLANNING USING FUNCTION ANALYSIS

    SciTech Connect

    Lori Braase; Jodi Grgich

    2011-06-01

    Event planning is expensive and resource intensive. Function analysis provides a solid foundation for comprehensive event planning (e.g., workshops, conferences, symposiums, or meetings). It has been used at Idaho National Laboratory (INL) to successfully plan events and capture lessons learned, and played a significant role in the development and implementation of the “INL Guide for Hosting an Event.” Using a guide and a functional approach to planning utilizes resources more efficiently and reduces errors that could be distracting or detrimental to an event. This integrated approach to logistics and program planning – with the primary focus on the participant – gives us the edge.

  8. A functional analysis of crying.

    PubMed

    Bowman, Lynn G; Hardesty, Samantha L; Mendres-Smith, Amber E

    2013-01-01

    Crying has yet to be examined systematically in isolation from other problem behavior, such as aggression or tantrums, during functional analyses (Hanley, Iwata, & McCord, 2003). Identification of variables that may maintain crying is especially important for populations who are susceptible to psychiatric interventions (e.g., individuals who have intellectual disabilities and communication deficits). The current study extended functional analysis methodology to crying with an adolescent boy who had been diagnosed with intellectual disabilities. Results suggested that crying was maintained by caregiver attention delivered in a sympathetic manner.

  9. Machine learning applications in cell image analysis.

    PubMed

    Kan, Andrey

    2017-04-04

    Machine learning (ML) refers to a set of automatic pattern recognition methods that have been successfully applied across various problem domains, including biomedical image analysis. This review focuses on ML applications for image analysis in light microscopy experiments with typical tasks of segmenting and tracking individual cells, and modelling of reconstructed lineage trees. After describing a typical image analysis pipeline and highlighting challenges of automatic analysis (for example, variability in cell morphology, tracking in presence of clutters) this review gives a brief historical outlook of ML, followed by basic concepts and definitions required for understanding examples. This article then presents several example applications at various image processing stages, including the use of supervised learning methods for improving cell segmentation, and the application of active learning for tracking. The review concludes with remarks on parameter setting and future directions.Immunology and Cell Biology advance online publication, 4 April 2017; doi:10.1038/icb.2017.16.

  10. A Robust Actin Filaments Image Analysis Framework

    PubMed Central

    Alioscha-Perez, Mitchel; Benadiba, Carine; Goossens, Katty; Kasas, Sandor; Dietler, Giovanni; Willaert, Ronnie; Sahli, Hichem

    2016-01-01

    The cytoskeleton is a highly dynamical protein network that plays a central role in numerous cellular physiological processes, and is traditionally divided into three components according to its chemical composition, i.e. actin, tubulin and intermediate filament cytoskeletons. Understanding the cytoskeleton dynamics is of prime importance to unveil mechanisms involved in cell adaptation to any stress type. Fluorescence imaging of cytoskeleton structures allows analyzing the impact of mechanical stimulation in the cytoskeleton, but it also imposes additional challenges in the image processing stage, such as the presence of imaging-related artifacts and heavy blurring introduced by (high-throughput) automated scans. However, although there exists a considerable number of image-based analytical tools to address the image processing and analysis, most of them are unfit to cope with the aforementioned challenges. Filamentous structures in images can be considered as a piecewise composition of quasi-straight segments (at least in some finer or coarser scale). Based on this observation, we propose a three-steps actin filaments extraction methodology: (i) first the input image is decomposed into a ‘cartoon’ part corresponding to the filament structures in the image, and a noise/texture part, (ii) on the ‘cartoon’ image, we apply a multi-scale line detector coupled with a (iii) quasi-straight filaments merging algorithm for fiber extraction. The proposed robust actin filaments image analysis framework allows extracting individual filaments in the presence of noise, artifacts and heavy blurring. Moreover, it provides numerous parameters such as filaments orientation, position and length, useful for further analysis. Cell image decomposition is relatively under-exploited in biological images processing, and our study shows the benefits it provides when addressing such tasks. Experimental validation was conducted using publicly available datasets, and in osteoblasts

  11. Retinal image analysis: concepts, applications and potential.

    PubMed

    Patton, Niall; Aslam, Tariq M; MacGillivray, Thomas; Deary, Ian J; Dhillon, Baljean; Eikelboom, Robert H; Yogesan, Kanagasingam; Constable, Ian J

    2006-01-01

    As digital imaging and computing power increasingly develop, so too does the potential to use these technologies in ophthalmology. Image processing, analysis and computer vision techniques are increasing in prominence in all fields of medical science, and are especially pertinent to modern ophthalmology, as it is heavily dependent on visually oriented signs. The retinal microvasculature is unique in that it is the only part of the human circulation that can be directly visualised non-invasively in vivo, readily photographed and subject to digital image analysis. Exciting developments in image processing relevant to ophthalmology over the past 15 years includes the progress being made towards developing automated diagnostic systems for conditions, such as diabetic retinopathy, age-related macular degeneration and retinopathy of prematurity. These diagnostic systems offer the potential to be used in large-scale screening programs, with the potential for significant resource savings, as well as being free from observer bias and fatigue. In addition, quantitative measurements of retinal vascular topography using digital image analysis from retinal photography have been used as research tools to better understand the relationship between the retinal microvasculature and cardiovascular disease. Furthermore, advances in electronic media transmission increase the relevance of using image processing in 'teleophthalmology' as an aid in clinical decision-making, with particular relevance to large rural-based communities. In this review, we outline the principles upon which retinal digital image analysis is based. We discuss current techniques used to automatically detect landmark features of the fundus, such as the optic disc, fovea and blood vessels. We review the use of image analysis in the automated diagnosis of pathology (with particular reference to diabetic retinopathy). We also review its role in defining and performing quantitative measurements of vascular topography

  12. Knowledge-Based Analysis And Understanding Of 3D Medical Images

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.; Juvvadi, Sridhar

    1988-06-01

    The anatomical three-dimensional (3D) medical imaging modalities, such as X-ray CT and MRI, have been well recognized in the diagnostic radiology for several years while the nuclear medicine modalities, such as PET, have just started making a strong impact through functional imaging. Though PET images provide the functional information about the human organs, they are hard to interpret because of the lack of anatomical information. Our objective is to develop a knowledge-based biomedical image analysis system which can interpret the anatomical images (such as CT). The anatomical information thus obtained can then be used in analyzing PET images of the same patient. This will not only help in interpreting PET images but it will also provide a means of studying the correlation between the anatomical and functional imaging. This paper presents the preliminary results of the knowledge based biomedical image analysis system for interpreting CT images of the chest.

  13. Modified Sigmoid Function Based Gray Scale Image Contrast Enhancement Using Particle Swarm Optimization

    NASA Astrophysics Data System (ADS)

    Verma, Harish Kumar; Pal, Sandeep

    2016-06-01

    The main objective of an image enhancement is to improve eminence by maximizing the information content in the test image. Conventional contrast enhancement techniques either often fails to produce reasonable results for a broad variety of low-contrast and high contrast images, or cannot be automatically applied to different images, because they are parameters dependent. Hence this paper introduces a novel hybrid image enhancement approach by taking both the local and global information of an image. In the present work, sigmoid function is being modified on the basis of contrast of the images. The gray image enhancement problem is treated as nonlinear optimization problem with several constraints and solved by particle swarm optimization. The entropy and edge information is included in the objective function as quality measure of an image. The effectiveness of modified sigmoid function based enhancement over conventional methods namely linear contrast stretching, histogram equalization, and adaptive histogram equalization are better revealed by the enhanced images and further validated by statistical analysis of these images.

  14. Edge enhanced morphology for infrared image analysis

    NASA Astrophysics Data System (ADS)

    Bai, Xiangzhi; Liu, Haonan

    2017-01-01

    Edge information is one of the critical information for infrared images. Morphological operators have been widely used for infrared image analysis. However, the edge information in infrared image is weak and the morphological operators could not well utilize the edge information of infrared images. To strengthen the edge information in morphological operators, the edge enhanced morphology is proposed in this paper. Firstly, the edge enhanced dilation and erosion operators are given and analyzed. Secondly, the pseudo operators which are derived from the edge enhanced dilation and erosion operators are defined. Finally, the applications for infrared image analysis are shown to verify the effectiveness of the proposed edge enhanced morphological operators. The proposed edge enhanced morphological operators are useful for the applications related to edge features, which could be extended to wide area of applications.

  15. Image features of spectral correlation function for arrhythmia classification.

    PubMed

    Khalaf, Aya F; Owis, Mohammed I; Yassine, Inas A

    2015-01-01

    Recently, computerized arrhythmia classification tools have been intensively used to aid physicians to recognize different irregular heartbeats. In this paper, we introduce arrhythmia CAD system exploiting cyclostationary signal analysis through estimation of the spectral correlation function for 5 different beat types. Two experiments were performed. Raw spectral correlation data were used as features in the first experiment while the other experiment which dealt with the spectral correlation coefficients as image included extraction of wavelet and shape features followed by fisher score for dimensionality reduction. As for the classification task, Support Vector Machine (SVM) with linear kernel was used for both experiments. The experimental results showed that both proposed approaches are superior compared to several state of the art methods. This approach achieved sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of 99.20%, 99.70%, 98.60%, 99.90% and 97.60% respectively.

  16. Distributed representations in memory: insights from functional brain imaging.

    PubMed

    Rissman, Jesse; Wagner, Anthony D

    2012-01-01

    Forging new memories for facts and events, holding critical details in mind on a moment-to-moment basis, and retrieving knowledge in the service of current goals all depend on a complex interplay between neural ensembles throughout the brain. Over the past decade, researchers have increasingly utilized powerful analytical tools (e.g., multivoxel pattern analysis) to decode the information represented within distributed functional magnetic resonance imaging activity patterns. In this review, we discuss how these methods can sensitively index neural representations of perceptual and semantic content and how leverage on the engagement of distributed representations provides unique insights into distinct aspects of memory-guided behavior. We emphasize that, in addition to characterizing the contents of memories, analyses of distributed patterns shed light on the processes that influence how information is encoded, maintained, or retrieved, and thus inform memory theory. We conclude by highlighting open questions about memory that can be addressed through distributed pattern analyses.

  17. Analysis of imaging quality under the systematic parameters for thermal imaging system

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Jin, Weiqi

    2009-07-01

    The integration of thermal imaging system and radar system could increase the range of target identification as well as strengthen the accuracy and reliability of detection, which is a state-of-the-art and mainstream integrated system to search any invasive target and guard homeland security. When it works, there is, however, one defect existing of what the thermal imaging system would produce affected images which could cause serious consequences when searching and detecting. In this paper, we study and reveal the reason why and how the affected images would occur utilizing the principle of lightwave before establishing mathematical imaging model which could meet the course of ray transmitting. In the further analysis, we give special attentions to the systematic parameters of the model, and analyse in detail all parameters which could possibly affect the imaging process and the function how it does respectively. With comprehensive research, we obtain detailed information about the regulation of diffractive phenomena shaped by these parameters. Analytical results have been convinced through the comparison between experimental images and MATLAB simulated images, while simulated images based on the parameters we revised to judge our expectation have good comparability with images acquired in reality.

  18. GPU accelerated dynamic functional connectivity analysis for functional MRI data.

    PubMed

    Akgün, Devrim; Sakoğlu, Ünal; Esquivel, Johnny; Adinoff, Bryon; Mete, Mutlu

    2015-07-01

    Recent advances in multi-core processors and graphics card based computational technologies have paved the way for an improved and dynamic utilization of parallel computing techniques. Numerous applications have been implemented for the acceleration of computationally-intensive problems in various computational science fields including bioinformatics, in which big data problems are prevalent. In neuroimaging, dynamic functional connectivity (DFC) analysis is a computationally demanding method used to investigate dynamic functional interactions among different brain regions or networks identified with functional magnetic resonance imaging (fMRI) data. In this study, we implemented and analyzed a parallel DFC algorithm based on thread-based and block-based approaches. The thread-based approach was designed to parallelize DFC computations and was implemented in both Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) programming platforms. Another approach developed in this study to better utilize CUDA architecture is the block-based approach, where parallelization involves smaller parts of fMRI time-courses obtained by sliding-windows. Experimental results showed that the proposed parallel design solutions enabled by the GPUs significantly reduce the computation time for DFC analysis. Multicore implementation using OpenMP on 8-core processor provides up to 7.7× speed-up. GPU implementation using CUDA yielded substantial accelerations ranging from 18.5× to 157× speed-up once thread-based and block-based approaches were combined in the analysis. Proposed parallel programming solutions showed that multi-core processor and CUDA-supported GPU implementations accelerated the DFC analyses significantly. Developed algorithms make the DFC analyses more practical for multi-subject studies with more dynamic analyses.

  19. Achromatic synesthesias - a functional magnetic resonance imaging study.

    PubMed

    Melero, H; Ríos-Lago, M; Peña-Melián, A; Álvarez-Linera, J

    2014-09-01

    Grapheme-color synesthetes experience consistent, automatic and idiosyncratic colors associated with specific letters and numbers. Frequently, these specific associations exhibit achromatic synesthetic qualities (e.g. white, black or gray). In this study, we have investigated for the first time the neural basis of achromatic synesthesias, their relationship to chromatic synesthesias and the achromatic congruency effect in order to understand not only synesthetic color but also other components of the synesthetic experience. To achieve this aim, functional magnetic resonance imaging experiments were performed in a group of associator grapheme-color synesthetes and matched controls who were stimulated with real chromatic and achromatic stimuli (Mondrians), and with letters and numbers that elicited different types of grapheme-color synesthesias (i.e. chromatic and achromatic inducers which elicited chromatic but also achromatic synesthesias, as well as congruent and incongruent ones). The information derived from the analysis of Mondrians and chromatic/achromatic synesthesias suggests that real and synesthetic colors/achromaticity do not fully share neural mechanisms. The whole-brain analysis of BOLD signals in response to the complete set of synesthetic inducers revealed that the functional peculiarities of the synesthetic brain are distributed, and reflect different components of the synesthetic experience: a perceptual component, an (attentional) feature binding component, and an emotional component. Additionally, the inclusion of achromatic experiences has provided new evidence in favor of the emotional binding theory, a line of interpretation which constitutes a bridge between grapheme-color synesthesia and other developmental modalities of the phenomenon.

  20. Structure-function relationships of the yeast fatty acid synthase: negative-stain, cryo-electron microscopy, and image analysis studies of the end views of the structure.

    PubMed Central

    Stoops, J K; Kolodziej, S J; Schroeter, J P; Bretaudiere, J P; Wakil, S J

    1992-01-01

    The yeast fatty acid synthase (M(r) = 2.5 x 10(6)) is organized in an alpha 6 beta 6 complex. In these studies, the synthase structure has been examined by negative-stain and cryo-electron microscopy. Side and end views of the structure indicate that the molecule, shaped similar to a prolate ellipsoid, has a high-density band of protein bisecting its major axis. Stained and frozen-hydrated average images of the end views show an excellent concordance and a hexagonal ring having three each alternating egg- and kidney-shaped features with low-protein-density protrusions extending outward from the egg-shaped features. Images also show that the barrel-like structure is not hollow but has a Y-shaped central core, which appears to make contact with the three egg-shaped features. Numerous side views of the structure give good evidence that the beta subunits have an archlike shape. We propose a model for the synthase that has point-group symmetry 32 and six equivalent sites of fatty acid synthesis. The protomeric unit is alpha 2 beta 2. The ends of each of the two archlike beta subunits interact with opposite sides of the two dichotomously arranged disclike alpha subunits. Three such protomeric units form the ring. We propose that the six fatty acid synthesizing centers are composed of two complementary half-alpha subunits and a beta subunit, an arrangement having all the partial activities of the multifunctional enzyme required for fatty acid synthesis. Images PMID:1631160

  1. Imaging Analysis of Collagen Fiber Networks in Cusps of Porcine Aortic Valves: Effect of their Local Distribution and Alignment on Valve Functionality

    PubMed Central

    Mega, Mor; Marom, Gil; Halevi, Rotem; Hamdan, Ashraf; Bluestein, Danny; Haj-Ali, Rami

    2015-01-01

    The cusps of native Aortic Valve (AV) are composed of collagen bundles embedded in soft tissue, creating a heterogenic tissue with asymmetric alignment in each cusp. This study compares native collagen fiber networks (CFNs) with a goal to better understand their influence on stress distribution and valve kinematics. Images of CFNs from five porcine tricuspid AVs are analyzed and fluid-structure interaction models are generated based on them. Although the valves had similar overall kinematics, the CFNs had distinctive influence on local mechanics. The regions with dilute CFN are more prone to damage since they are subjected to higher stress magnitudes. PMID:26406926

  2. Functional analysis of glaucoma data.

    PubMed

    Hosseini-Nasab, Mohammad; Mirzaei K, Zahra

    2014-05-30

    We refer glaucoma to a category of eye disorders often associated with a dangerous buildup of intraocular pressure (IOP), which can damage the eyes' optic nerve that transmits visual information to the brain. Because IOP changes over time, it is a function of time, and it is an advantage that we analyze the phenomenon using functional data analysis. In this paper, we treat the data related to the IOP of 35 patients with right eye glaucoma, collected in Rasul-e-Akram Hospital at Tehran, Iran, over the years 2007–2011. We shall explore the structure of the data in search of the features that describe them, and find the characteristics that give a comprehensible presentation of the structure of the variability in the data.We extract patterns of variation in the data by using a generalization of the smoothed functional principal component analysis to obtain the main factors causing glaucoma and then determine their importance. We also explore the correlation patterns between the IOP of right and left eyes, and then model the left eye IOP of the glaucoma patients at each time on the basis of their right eye IOP in a previous interval of time.We can use the model to predict the values of the former variable by using the latter one in a previous time interval.

  3. INVESTIGATION OF IMAGE ANALYSIS TECHNIQUES.

    DTIC Science & Technology

    The objective of this program was to construct a functional model of the frog retina in order to evaluate its performance with respect to operational...comparison is made between the physiological measurements obtained from frogs and the outputs from the functional model. The features abstracted both by the... frog and the model are the presence and location of edges, moving dark convexities, changing contrast, and dimming. A large number of the parameters of

  4. Construction of realistic images using R-functions

    SciTech Connect

    Shevchenko, A.N.; Tsukanov, I.G.

    1995-09-01

    Realistic images are plane images of three-dimensional bodies in which volume effects are conveyed by illumination. This is how volume is displayed in photographs and paintings. Photographs achieve a realistic volume effect by choosing a certain arrangement, brightness, and number of light sources. Painters choose for their paintings a color palette based entirely on sensory perception. In this paper, we consider the construction of realistic images on a computer display. The shape of the imaged objects is not always known in advance: it may be generated as a result of complex mathematical computations. The geometrical information is described using R-functions.

  5. Molecular, Functional, and Structural Imaging of Major Depressive Disorder.

    PubMed

    Zhang, Kai; Zhu, Yunqi; Zhu, Yuankai; Wu, Shuang; Liu, Hao; Zhang, Wei; Xu, Caiyun; Zhang, Hong; Hayashi, Takuya; Tian, Mei

    2016-06-01

    Major depressive disorder (MDD) is a significant cause of morbidity and mortality worldwide, correlating with genetic susceptibility and environmental risk factors. Molecular, functional, and structural imaging approaches have been increasingly used to detect neurobiological changes, analyze neurochemical correlates, and parse pathophysiological mechanisms underlying MDD. We reviewed recent neuroimaging publications on MDD in terms of molecular, functional, and structural alterations as detected mainly by magnetic resonance imaging (MRI) and positron emission tomography. Altered structure and function of brain regions involved in the cognitive control of affective state have been demonstrated. An abnormal default mode network, as revealed by resting-state functional MRI, is likely associated with aberrant metabolic and serotonergic function revealed by radionuclide imaging. Further multi-modal investigations are essential to clarify the characteristics of the cortical network and serotonergic system associated with behavioral and genetic variations in MDD.

  6. Neurovascular coupling: in vivo optical techniques for functional brain imaging

    PubMed Central

    2013-01-01

    Optical imaging techniques reflect different biochemical processes in the brain, which is closely related with neural activity. Scientists and clinicians employ a variety of optical imaging technologies to visualize and study the relationship between neurons, glial cells and blood vessels. In this paper, we present an overview of the current optical approaches used for the in vivo imaging of neurovascular coupling events in small animal models. These techniques include 2-photon microscopy, laser speckle contrast imaging (LSCI), voltage-sensitive dye imaging (VSDi), functional photoacoustic microscopy (fPAM), functional near-infrared spectroscopy imaging (fNIRS) and multimodal imaging techniques. The basic principles of each technique are described in detail, followed by examples of current applications from cutting-edge studies of cerebral neurovascular coupling functions and metabolic. Moreover, we provide a glimpse of the possible ways in which these techniques might be translated to human studies for clinical investigations of pathophysiology and disease. In vivo optical imaging techniques continue to expand and evolve, allowing us to discover fundamental basis of neurovascular coupling roles in cerebral physiology and pathophysiology. PMID:23631798

  7. Neurovascular coupling: in vivo optical techniques for functional brain imaging.

    PubMed

    Liao, Lun-De; Tsytsarev, Vassiliy; Delgado-Martínez, Ignacio; Li, Meng-Lin; Erzurumlu, Reha; Vipin, Ashwati; Orellana, Josue; Lin, Yan-Ren; Lai, Hsin-Yi; Chen, You-Yin; Thakor, Nitish V

    2013-04-30

    Optical imaging techniques reflect different biochemical processes in the brain, which is closely related with neural activity. Scientists and clinicians employ a variety of optical imaging technologies to visualize and study the relationship between neurons, glial cells and blood vessels. In this paper, we present an overview of the current optical approaches used for the in vivo imaging of neurovascular coupling events in small animal models. These techniques include 2-photon microscopy, laser speckle contrast imaging (LSCI), voltage-sensitive dye imaging (VSDi), functional photoacoustic microscopy (fPAM), functional near-infrared spectroscopy imaging (fNIRS) and multimodal imaging techniques. The basic principles of each technique are described in detail, followed by examples of current applications from cutting-edge studies of cerebral neurovascular coupling functions and metabolic. Moreover, we provide a glimpse of the possible ways in which these techniques might be translated to human studies for clinical investigations of pathophysiology and disease. In vivo optical imaging techniques continue to expand and evolve, allowing us to discover fundamental basis of neurovascular coupling roles in cerebral physiology and pathophysiology.

  8. Students' Images of Two-Variable Functions and Their Graphs

    ERIC Educational Resources Information Center

    Weber, Eric; Thompson, Patrick W.

    2014-01-01

    This paper presents a conceptual analysis for students' images of graphs and their extension to graphs of two-variable functions. We use the conceptual analysis, based on quantitative and covariational reasoning, to construct a hypothetical learning trajectory (HLT) for how students might generalize their understanding of graphs of…

  9. Functional imaging of kinetic parameters from the time dependent linear response function by dynamic scintigraphy

    SciTech Connect

    Stritzke, P.; Knop, J.; Spielmann, R.P.; Montz, R.; Schneider, C.

    1984-01-01

    A new method is proposed to determine the locally differing time dependent linear response function h(r,t) of a radioactive tracer injected into a patients blood pool B(t) by mathematical analysis of a dynamic scintigraphic study A(r,t). Transit times, uptake rates and clearance rates of different tracers are calculated from the linear response function at every matrix point by one computer program. The parameters are presented in functional images on a standard computer display. Thus the whole information from a dynamic study can be condensed within a few images. The integral equation A=h+B +c(r)*B (+ means convolution, c(r)*B(t)=nontarget activity) derived from tracer theory is deconvoluted by mathematical methods, which are unsensitive against noise contamination of the input data. The numerical technique is successfully applied in Iodide-123-Hippuran and Tc-99m-DMSA kidney studies, in Tc-99m-MDP and -DPD bone studies, in Tl-201 myocardial studies and in Iodide-123 thyroid studies. Because the regional blood pool-or nontarget activity is calculated and subtracted, the kinetic parameters are considered to be free from nontarget contributions in all dynamic scintigraphic studies. Examples are demonstrated and the usefulness for clinical application is discussed.

  10. Functional brain imaging in respiratory medicine.

    PubMed

    Pattinson, Kyle

    2015-06-01

    Discordance of clinical symptoms with markers of disease severity remains a conundrum in a variety of respiratory conditions. The breathlessness of chronic lung disease correlates poorly with spirometry, yet is a better predictor of mortality. In chronic cough, symptoms are often evident without clear physical cause. In asthma, the terms 'over perceivers' and 'under perceivers' are common parlance. In all these examples, aberrant brain mechanisms may explain the mismatch between symptoms and pathology. Functional MRI is a non-invasive method of measuring brain function. It has recently become significantly advanced enough to be useful in clinical research and to address these potential mechanisms. This article explains how FMRI works, current understanding from FMRI in breathlessness, cough and asthma and suggests possibilities for future research.

  11. An approach for quantitative image quality analysis for CT

    NASA Astrophysics Data System (ADS)

    Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe

    2016-03-01

    An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.

  12. MRI Image Processing Based on Fractal Analysis

    PubMed

    Marusina, Mariya Y; Mochalina, Alexandra P; Frolova, Ekaterina P; Satikov, Valentin I; Barchuk, Anton A; Kuznetcov, Vladimir I; Gaidukov, Vadim S; Tarakanov, Segrey A

    2017-01-01

    Background: Cancer is one of the most common causes of human mortality, with about 14 million new cases and 8.2 million deaths reported in in 2012. Early diagnosis of cancer through screening allows interventions to reduce mortality. Fractal analysis of medical images may be useful for this purpose. Materials and Methods: In this study, we examined magnetic resonance (MR) images of healthy livers and livers containing metastases from colorectal cancer. The fractal dimension and the Hurst exponent were chosen as diagnostic features for tomographic imaging using Image J software package for image processings FracLac for applied for fractal analysis with a 120x150 pixel area. Calculations of the fractal dimensions of pathological and healthy tissue samples were performed using the box-counting method. Results: In pathological cases (foci formation), the Hurst exponent was less than 0.5 (the region of unstable statistical characteristics). For healthy tissue, the Hurst index is greater than 0.5 (the zone of stable characteristics). Conclusions: The study indicated the possibility of employing fractal rapid analysis for the detection of focal lesions of the liver. The Hurst exponent can be used as an important diagnostic characteristic for analysis of medical images.

  13. Retinal imaging analysis based on vessel detection.

    PubMed

    Jamal, Arshad; Hazim Alkawaz, Mohammed; Rehman, Amjad; Saba, Tanzila

    2017-03-13

    With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection. The RIA assists in the analysis of the retinal images and specialists are served with various options like saving, processing and analyzing retinal images through its advanced interface layout. Additionally, RIA assists in the selection process of vessel segment; processing these vessels by calculating its diameter, standard deviation, length, and displaying detected vessel on the retina. The Agile Unified Process is adopted as the methodology in developing this research. To conclude, Retina Image Analysis might help the optometrist to get better understanding in analyzing the patient's retina. Finally, the Retina Image Analysis procedure is developed using MATLAB (R2011b). Promising results are attained that are comparable in the state of art.

  14. Regional lung function and mechanics using image registration

    NASA Astrophysics Data System (ADS)

    Ding, Kai

    The main function of the respiratory system is gas exchange. Since many disease or injury conditions can cause biomechanical or material property changes that can alter lung function, there is a great interest in measuring regional lung function and mechanics. In this thesis, we present a technique that uses multiple respiratory-gated CT images of the lung acquired at different levels of inflation with both breath-hold static scans and retrospectively reconstructed 4D dynamic scans, along with non-rigid 3D image registration, to make local estimates of lung tissue function and mechanics. We validate our technique using anatomical landmarks and functional Xe-CT estimated specific ventilation. The major contributions of this thesis include: (1) developing the registration derived regional expansion estimation approach in breath-hold static scans and dynamic 4DCT scans, (2) developing a method to quantify lobar sliding from image registration derived displacement field, (3) developing a method for measurement of radiation-induced pulmonary function change following a course of radiation therapy, (4) developing and validating different ventilation measures in 4DCT. The ability of our technique to estimate regional lung mechanics and function as a surrogate of the Xe-CT ventilation imaging for the entire lung from quickly and easily obtained respiratory-gated images, is a significant contribution to functional lung imaging because of the potential increase in resolution, and large reductions in imaging time, radiation, and contrast agent exposure. Our technique may be useful to detect and follow the progression of lung disease such as COPD, may be useful as a planning tool during RT planning, may be useful for tracking the progression of toxicity to nearby normal tissue during RT, and can be used to evaluate the effectiveness of a treatment post-therapy.

  15. Rock fracture image acquisition and analysis

    NASA Astrophysics Data System (ADS)

    Wang, W.; Zongpu, Jia; Chen, Liwan

    2007-12-01

    As a cooperation project between Sweden and China, this paper presents: rock fracture image acquisition and analysis. Rock fracture images are acquired by using UV light illumination and visible optical illumination. To present fracture network reasonable, we set up some models to characterize the network, based on the models, we used Best fit Ferret method to auto-determine fracture zone, then, through skeleton fractures to obtain endpoints, junctions, holes, particles, and branches. Based on the new parameters and a part of common parameters, the fracture network density, porosity, connectivity and complexities can be obtained, and the fracture network is characterized. In the following, we first present a basic consideration and basic parameters for fractures (Primary study of characteristics of rock fractures), then, set up a model for fracture network analysis (Fracture network analysis), consequently to use the model to analyze fracture network with different images (Two dimensional fracture network analysis based on slices), and finally give conclusions and suggestions.

  16. Endoscopic device for functional imaging of the retina

    NASA Astrophysics Data System (ADS)

    Barriga, Simon; Lohani, Sweyta; Martell, Bret; Soliz, Peter; Ts'o, Dan

    2011-03-01

    Non-invasive imaging of retinal function based on the recording of spatially distributed reflectance changes evoked by visual stimuli has to-date been performed primarily using modified commercial fundus cameras. We have constructed a prototype retinal functional imager, using a commercial endoscope (Storz) for the frontend optics, and a low-cost back-end that includes the needed dichroic beam splitter to separate the stimulus path from the imaging path. This device has been tested to demonstrate its performance for the delivery of adequate near infrared (NIR) illumination, intensity of the visual stimulus and reflectance return in the imaging path. The current device was found to be capable of imaging reflectance changes of 0.1%, similar to that observable using the modified commercial fundus camera approach. The visual stimulus (a 505nm spot of 0.5secs) was used with an interrogation illumination of 780nm, and a sequence of imaged captured. At each pixel, the imaged signal was subtracted and normalized by the baseline reflectance, so that the measurement was ΔR/R. The typical retinal activity signal observed had a ΔR/R of 0.3-1.0%. The noise levels were measured when no stimulus was applied and found to vary between +/- 0.05%. Functional imaging has been suggested as a means to provide objective information on retina function that may be a preclinical indicator of ocular diseases, such as age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy. The endoscopic approach promises to yield a significantly more economical retinal functional imaging device that would be clinically important.

  17. Warped functional analysis of variance.

    PubMed

    Gervini, Daniel; Carter, Patrick A

    2014-09-01

    This article presents an Analysis of Variance model for functional data that explicitly incorporates phase variability through a time-warping component, allowing for a unified approach to estimation and inference in presence of amplitude and time variability. The focus is on single-random-factor models but the approach can be easily generalized to more complex ANOVA models. The behavior of the estimators is studied by simulation, and an application to the analysis of growth curves of flour beetles is presented. Although the model assumes a smooth latent process behind the observed trajectories, smootheness of the observed data is not required; the method can be applied to irregular time grids, which are common in longitudinal studies.

  18. Simple method for modulation transfer function determination of digital imaging detectors from edge images

    NASA Astrophysics Data System (ADS)

    Buhr, Egbert; Guenther-Kohfahl, Susanne; Neitzel, Ulrich

    2003-06-01

    A simple variant of the edge method to determine the presampled modulation transfer function (MTF) of digital imaging detectors has been developed that produces sufficiently accurate MTF values for frequencies up to the Nyquist frequency limit of the detector with only a small amount of effort for alignment and computing. An oversampled edge spread function (ESF) is generated from the image of a slanted edge by rearranging the pixel data of N consecutive lines that correspond to a lateral shift of the edge of one pixel. The original data are used for the computational analysis without further data preprocessing. Since the number of lines leading to an edge shift of one pixel is generally a fractional number rather than an integer, a systematic error may be introduced in the MTF obtained. Simulations and theoretical investigations show that for all frequencies up to the Nyquist limit the relative error ΔMTF/MTF is below 1/(2N) and can thus be kept below a given threshold by a suitable choice of N. The method is especially useful for applications where the MTF is needed for frequencies up to the Nyquist frequency limit, like the determination of the detective quantum efficiency (DQE).

  19. Functional Multiple-Set Canonical Correlation Analysis

    ERIC Educational Resources Information Center

    Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

    2012-01-01

    We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

  20. Image analysis tools and emerging algorithms for expression proteomics

    PubMed Central

    English, Jane A.; Lisacek, Frederique; Morris, Jeffrey S.; Yang, Guang-Zhong; Dunn, Michael J.

    2012-01-01

    Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-D Gel Electrophoresis (2-DE) technique of protein separation, and by first covering signal analysis for Mass Spectrometry (MS), we also explain the current image analysis workflow for the emerging high-throughput ‘shotgun’ proteomics platform of Liquid Chromatography coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whilst existing commercial and academic packages and their workflows are described from both a user’s and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS. PMID:21046614

  1. Particle Pollution Estimation Based on Image Analysis

    PubMed Central

    Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

    2016-01-01

    Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction. PMID:26828757

  2. Particle Pollution Estimation Based on Image Analysis.

    PubMed

    Liu, Chenbin; Tsow, Francis; Zou, Yi; Tao, Nongjian

    2016-01-01

    Exposure to fine particles can cause various diseases, and an easily accessible method to monitor the particles can help raise public awareness and reduce harmful exposures. Here we report a method to estimate PM air pollution based on analysis of a large number of outdoor images available for Beijing, Shanghai (China) and Phoenix (US). Six image features were extracted from the images, which were used, together with other relevant data, such as the position of the sun, date, time, geographic information and weather conditions, to predict PM2.5 index. The results demonstrate that the image analysis method provides good prediction of PM2.5 indexes, and different features have different significance levels in the prediction.

  3. Quantitative analysis of qualitative images

    NASA Astrophysics Data System (ADS)

    Hockney, David; Falco, Charles M.

    2005-03-01

    We show optical evidence that demonstrates artists as early as Jan van Eyck and Robert Campin (c1425) used optical projections as aids for producing their paintings. We also have found optical evidence within works by later artists, including Bermejo (c1475), Lotto (c1525), Caravaggio (c1600), de la Tour (c1650), Chardin (c1750) and Ingres (c1825), demonstrating a continuum in the use of optical projections by artists, along with an evolution in the sophistication of that use. However, even for paintings where we have been able to extract unambiguous, quantitative evidence of the direct use of optical projections for producing certain of the features, this does not mean that paintings are effectively photographs. Because the hand and mind of the artist are intimately involved in the creation process, understanding these complex images requires more than can be obtained from only applying the equations of geometrical optics.

  4. On Two-Dimensional ARMA Models for Image Analysis.

    DTIC Science & Technology

    1980-03-24

    2-D ARMA models for image analysis . Particular emphasis is placed on restoration of noisy images using 2-D ARMA models. Computer results are...is concluded that the models are very effective linear models for image analysis . (Author)

  5. Bench to bedside molecular functional imaging in translational cancer medicine: to image or to imagine?

    PubMed

    Mahajan, A; Goh, V; Basu, S; Vaish, R; Weeks, A J; Thakur, M H; Cook, G J

    2015-10-01

    Ongoing research on malignant and normal cell biology has substantially enhanced the understanding of the biology of cancer and carcinogenesis. This has led to the development of methods to image the evolution of cancer, target specific biological molecules, and study the anti-tumour effects of novel therapeutic agents. At the same time, there has been a paradigm shift in the field of oncological imaging from purely structural or functional imaging to combined multimodal structure-function approaches that enable the assessment of malignancy from all aspects (including molecular and functional level) in a single examination. The evolving molecular functional imaging using specific molecular targets (especially with combined positron-emission tomography [PET] computed tomography [CT] using 2- [(18)F]-fluoro-2-deoxy-D-glucose [FDG] and other novel PET tracers) has great potential in translational research, giving specific quantitative information with regard to tumour activity, and has been of pivotal importance in diagnoses and therapy tailoring. Furthermore, molecular functional imaging has taken a key place in the present era of translational cancer research, producing an important tool to study and evolve newer receptor-targeted therapies, gene therapies, and in cancer stem cell research, which could form the basis to translate these agents into clinical practice, popularly termed "theranostics". Targeted molecular imaging needs to be developed in close association with biotechnology, information technology, and basic translational scientists for its best utility. This article reviews the current role of molecular functional imaging as one of the main pillars of translational research.

  6. EANM/ESC guidelines for radionuclide imaging of cardiac function.

    PubMed

    Hesse, B; Lindhardt, T B; Acampa, W; Anagnostopoulos, C; Ballinger, J; Bax, J J; Edenbrandt, L; Flotats, A; Germano, G; Stopar, T Gmeiner; Franken, P; Kelion, A; Kjaer, A; Le Guludec, D; Ljungberg, M; Maenhout, A F; Marcassa, C; Marving, J; McKiddie, F; Schaefer, W M; Stegger, L; Underwood, R

    2008-04-01

    Radionuclide imaging of cardiac function represents a number of well-validated techniques for accurate determination of right (RV) and left ventricular (LV) ejection fraction (EF) and LV volumes. These first European guidelines give recommendations for how and when to use first-pass and equilibrium radionuclide ventriculography, gated myocardial perfusion scintigraphy, gated PET, and studies with non-imaging devices for the evaluation of cardiac function. The items covered are presented in 11 sections: clinical indications, radiopharmaceuticals and dosimetry, study acquisition, RV EF, LV EF, LV volumes, LV regional function, LV diastolic function, reports and image display and reference values from the literature of RVEF, LVEF and LV volumes. If specific recommendations given cannot be based on evidence from original, scientific studies, referral is given to "prevailing or general consensus". The guidelines are designed to assist in the practice of referral to, performance, interpretation and reporting of nuclear cardiology studies for the evaluation of cardiac performance.

  7. VAICo: visual analysis for image comparison.

    PubMed

    Schmidt, Johanna; Gröller, M Eduard; Bruckner, Stefan

    2013-12-01

    Scientists, engineers, and analysts are confronted with ever larger and more complex sets of data, whose analysis poses special challenges. In many situations it is necessary to compare two or more datasets. Hence there is a need for comparative visualization tools to help analyze differences or similarities among datasets. In this paper an approach for comparative visualization for sets of images is presented. Well-established techniques for comparing images frequently place them side-by-side. A major drawback of such approaches is that they do not scale well. Other image comparison methods encode differences in images by abstract parameters like color. In this case information about the underlying image data gets lost. This paper introduces a new method for visualizing differences and similarities in large sets of images which preserves contextual information, but also allows the detailed analysis of subtle variations. Our approach identifies local changes and applies cluster analysis techniques to embed them in a hierarchy. The results of this process are then presented in an interactive web application which allows users to rapidly explore the space of differences and drill-down on particular features. We demonstrate the flexibility of our approach by applying it to multiple distinct domains.

  8. GRETNA: a graph theoretical network analysis toolbox for imaging connectomics

    PubMed Central

    Wang, Jinhui; Wang, Xindi; Xia, Mingrui; Liao, Xuhong; Evans, Alan; He, Yong

    2015-01-01

    Recent studies have suggested that the brain’s structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Windows and UNIX OS) package with a graphical user interface (GUI); (ii) allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii) providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv) allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v) including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI) data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website.1 PMID:26175682

  9. Dual-modality imaging of function and physiology

    NASA Astrophysics Data System (ADS)

    Hasegawa, Bruce H.; Iwata, Koji; Wong, Kenneth H.; Wu, Max C.; Da Silva, Angela; Tang, Hamilton R.; Barber, William C.; Hwang, Andrew B.; Sakdinawat, Anne E.

    2002-04-01

    Dual-modality imaging is a technique where computed tomography or magnetic resonance imaging is combined with positron emission tomography or single-photon computed tomography to acquire structural and functional images with an integrated system. The data are acquired during a single procedure with the patient on a table viewed by both detectors to facilitate correlation between the structural and function images. The resulting data can be useful for localization for more specific diagnosis of disease. In addition, the anatomical information can be used to compensate the correlated radionuclide data for physical perturbations such as photon attenuation, scatter radiation, and partial volume errors. Thus, dual-modality imaging provides a priori information that can be used to improve both the visual quality and the quantitative accuracy of the radionuclide images. Dual-modality imaging systems also are being developed for biological research that involves small animals. The small-animal dual-modality systems offer advantages for measurements that currently are performed invasively using autoradiography and tissue sampling. By acquiring the required data noninvasively, dual-modality imaging has the potential to allow serial studies in a single animal, to perform measurements with fewer animals, and to improve the statistical quality of the data.

  10. Real-time functional near-infrared imager

    NASA Astrophysics Data System (ADS)

    Luo, Qingming; Zeng, Shaoqun; Chance, Britton; Nioka, Shoko

    1998-08-01

    A real time functional Near-InfraRed Imager (fNIRI) was presented in this paper. We developed a continuous wave (cw) light imaging probe which includes 9 light sources and 4 pairs detectors (each pair has one 850 nm filtered detector and one 760 nm filtered detector). There are 16 measurement sections and total detection area is 9 cm X 4 cm. The detector- source uses 2.5 cm spacing. The light sources are controlled by a computer and the signals from the detectors are converted and processed in real time by the computer. The user-friendly software was programmed with Visual C++ language. Relative changes of oxy-Hb, Hb, and total blood concentration in 16 channels and the corresponding images combined by 16 channels could be displayed in real time on computer. With this cw imaging probe, we have measured motor function in motor cortex area, visual function in occipital area, and cognitive activity in frontal forehead area of the human brain when the subjects are stimulated by moving fingers, viewing a flashing light and doing an analogy test, respectively. The experimental results show that the cw imaging probe can be used for functional images of brain activity, based upon changes of oxygenation and blood volume due to the stimulus.

  11. From Image Analysis to Computer Vision: Motives, Methods, and Milestones.

    DTIC Science & Technology

    1998-07-01

    images. Initially, work on digital image analysis dealt with specific classes of images such as text, photomicrographs, nuclear particle tracks, and aerial...photographs; but by the 1960’s, general algorithms and paradigms for image analysis began to be formulated. When the artificial intelligence...scene, but eventually from image sequences obtained by a moving camera; at this stage, image analysis had become scene analysis or computer vision

  12. Selecting an image analysis minicomputer system

    NASA Technical Reports Server (NTRS)

    Danielson, R.

    1981-01-01

    Factors to be weighed when selecting a minicomputer system as the basis for an image analysis computer facility vary depending on whether the user organization procures a new computer or selects an existing facility to serve as an image analysis host. Some conditions not directly related to hardware or software should be considered such as the flexibility of the computer center staff, their encouragement of innovation, and the availability of the host processor to a broad spectrum of potential user organizations. Particular attention must be given to: image analysis software capability; the facilities of a potential host installation; the central processing unit; the operating system and languages; main memory; disk storage; tape drives; hardcopy output; and other peripherals. The operational environment, accessibility; resource limitations; and operational supports are important. Charges made for program execution and data storage must also be examined.

  13. CPD - education and self-assessment: functional imaging in epilepsy.

    PubMed

    Richardson, M P

    2001-03-01

    Functional imaging plays a growing role in the clinical assessment and research investigation of patients with epilepsy. This article reviews the literature on functional MRI (fMRI) investigation of EEG activity, fMRI evaluation of cognitive and motor functions, magnetic resonance spectroscopy (MRS), single photon emission computed tomography (SPECT) and positron emission tomography (PET) in epilepsy. The place of these techniques in clinical evaluation and their contribution to a better neurobiological understanding of epilepsy are discussed.

  14. Ultrasonic imaging characteristics of transplanted kidneys with delayed graft function.

    PubMed

    Liang, W X; Cai, M J; Jiang, L; Xie, Y Q; Yuan, W L; Zhang, H

    2014-08-29

    We investigated the ultrasonic imaging characteristics of transplanted kidneys with delayed graft function (DGF). Ultrasonography was performed in 44 patients after kidney transplantation, and a time-intensity analysis was performed to compare the differences between patients with normal graft function (NGF) and those with DGF. Compared with the NGF group, the DGF group had earlier arrival time, shorter time to peak, and higher arrival intensity and peak intensity (P < 0.05). The variation-of-intensity parameters in different renal cortices increased, whereas the variation-of-time parameter decreased, in those with DGF (P < 0.05). In conclusion, compared with the NGF group, the microcirculation perfusion of transplanted kidneys in the DGF group showed higher perfusion with earlier arrival time, shorter time to peak, and higher arrival intensity and peak intensity. In addition, the intensity variations of contrast agent in different renal cortices from patients with DGF were greater, whereas the variations in perfusion time were smaller than those in patients with NGF.

  15. Automated eXpert Spectral Image Analysis

    SciTech Connect

    Keenan, Michael R.

    2003-11-25

    AXSIA performs automated factor analysis of hyperspectral images. In such images, a complete spectrum is collected an each point in a 1-, 2- or 3- dimensional spatial array. 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 information. Multivariate factor analysis techniques have proven effective for extracting the essential information from high dimensional data sets into a limted number of factors that describe the spectral characteristics and spatial distributions of the pure components comprising the sample. AXSIA provides tools to estimate different types of factor models including Singular Value Decomposition (SVD), Principal Component Analysis (PCA), PCA with factor rotation, and Alternating Least Squares-based Multivariate Curve Resolution (MCR-ALS). As part of the analysis process, AXSIA can automatically estimate the number of pure components that comprise the data and can scale the data to account for Poisson noise. The data analysis methods are fundamentally based on eigenanalysis of the data crossproduct matrix coupled with orthogonal eigenvector rotation and constrained alternating least squares refinement. A novel method for automatically determining the number of significant components, which is based on the eigenvalues of the crossproduct matrix, has also been devised and implemented. The data can be compressed spectrally via PCA and spatially through wavelet transforms, and algorithms have been developed that perform factor analysis in the transform domain while retaining full spatial and spectral resolution in the final result. These latter innovations enable the analysis of larger-than core-memory spectrum-images. AXSIA was designed to perform automated chemical phase analysis of spectrum-images acquired by a variety of chemical imaging techniques. Successful applications include Energy Dispersive X-ray Spectroscopy, X-ray Fluorescence

  16. Objective facial photograph analysis using imaging software.

    PubMed

    Pham, Annette M; Tollefson, Travis T

    2010-05-01

    Facial analysis is an integral part of the surgical planning process. Clinical photography has long been an invaluable tool in the surgeon's practice not only for accurate facial analysis but also for enhancing communication between the patient and surgeon, for evaluating postoperative results, for medicolegal documentation, and for educational and teaching opportunities. From 35-mm slide film to the digital technology of today, clinical photography has benefited greatly from technological advances. With the development of computer imaging software, objective facial analysis becomes easier to perform and less time consuming. Thus, while the original purpose of facial analysis remains the same, the process becomes much more efficient and allows for some objectivity. Although clinical judgment and artistry of technique is never compromised, the ability to perform objective facial photograph analysis using imaging software may become the standard in facial plastic surgery practices in the future.

  17. Four-dimensional analysis of stomatognathic function.

    PubMed

    Terajima, Masahiko; Endo, Mizuki; Aoki, Yoshimitsu; Yuuda, Kyouko; Hayasaki, Haruaki; Goto, Tazuko K; Tokumori, Kenji; Nakasima, Akihiko

    2008-08-01

    Many researchers have attempted to clarify the complex relationships between stomatognathic function and craniofacial morphology. Most studies investigated the trajectories of incisal or condylar points and measured temporomandibular morphology projected onto 2-dimensional radiographic films. Although these methods provided valuable information, their diagnostic capabilities were limited. We introduce a new 4-dimensional (4D) analysis of stomatognathic function that combines the 3-dimensional (3D) computed tomography of the cranium and mandible, dental surface imaging with a noncontact 3D laser scanner, and mandibular movement data recorded with a 6 degrees of freedom jaw-movement analyzer. This method performs dynamic and precise simulations that can analyze and display condyle to fossa distances and occlusal contacts during mandibular function. These comprehensive relationships can be analyzed and displayed not only at intercuspal position, but also at any mandibular position during functional movements. We believe that our 4D analyzing system will be useful for diagnosing temporomandibular disorders of patients with jaw deformities and other malocclusions.

  18. Data analysis tools for imaging infrared technology within the ImageJ environment

    NASA Astrophysics Data System (ADS)

    Rogers, Ryan K.; Edwards, W. Derrik; Waddle, Caleb E.; Dobbins, Christopher L.; Wood, Sam B.

    2013-06-01

    For over 30 years, the U.S. Army Aviation and Missile Research, Development, and Engineering Center (AMRDEC) has specialized in characterizing the performance of infrared (IR) imaging systems in the laboratory and field. In the late 90's, AMRDEC developed the Automated IR Sensor Test Facility (AISTF) which allowed efficient deployment testing of Unmanned Aerial Systems (UAS) payloads. More recently, ImageJ has been used predominately as the image processing environment of choice for analysis of laboratory, field, and simulated data. The strengths of ImageJ are that it is maintained by the U.S. National Institute of Health, it exists in the public domain, and it functions on all major operating systems. Three new tools or "plugins" have been developed at AMRDEC to enhance the accuracy and efficiency of analysis. First, a Noise Equivalent Temperature Difference (NETD) plugin was written to process Signal Transfer Function (SiTF) and 3D noise data. Another plugin was produced that measures the Modulation Transfer Function (MTF) given either an edge or slit target. Lastly, a plugin was developed to measure Focal Plane Array (FPA) defects, classify and bin the customizable defects, and report statistics. This paper will document the capabilities and practical applications of these tools as well as profile their advantages over previous methods of analysis.

  19. Imaging Faults and Shear Zones Using Receiver Functions

    NASA Astrophysics Data System (ADS)

    Schulte-Pelkum, Vera; Mahan, Kevin H.

    2014-11-01

    The geometry of faults at seismogenic depths and their continuation into the ductile zone is of interest for a number of applications ranging from earthquake hazard to modes of lithospheric deformation. Teleseismic passive source imaging of faults and shear zones can be useful particularly where faults are not outlined by local seismicity. Passive seismic signatures of faults may arise from abrupt changes in lithology or foliation orientation in the upper crust, and from mylonitic shear zones at greater depths. Faults and shear zones with less than near-vertical dip lend themselves to detection with teleseismic mode-converted waves (receiver functions) provided that they have either a contrast in isotropic shear velocity ( V s), or a contrast in orientation or strength of anisotropic compressional velocity ( V p). We introduce a detection method for faults and shear zones based on receiver functions. We use synthetic seismograms to demonstrate common features of dipping isotropic interfaces and contrasts in dipping foliation that allows determination of their strike and depth without making further assumptions about the model. We proceed with two applications. We first image a Laramide thrust fault in the western U.S. (the Wind River thrust fault) as a steeply dipping isotropic velocity contrast in the middle crust near the surface trace of the fault; further downdip and across the range, where basin geometry suggests the fault may sole into a subhorizontal shear zone, we identify a candidate shear zone signal from midcrustal depths. The second application is the use of microstructural data from exhumed ductile shear zones in Scotland and in the western Canadian Shield to predict the character of seismic signatures of present-day deep crustal shear zones. Realistic anisotropy in observed shear fabrics generates a signal in receiver functions that is comparable in amplitude to first-order features like the Moho. Observables that can be robustly constrained without

  20. [Imaging evaluation of renal function: principles and limitations].

    PubMed

    Vivier, P-H; Dolores, M; Le Cloirec, J; Beurdeley, M; Liard, A; Elbaz, F; Roset, J-B; Dacher, J-N

    2011-04-01

    The kidney performs multiple functions. Glomerular filtration is the most studied of these functions. In clinical practice, the surgical indication for patients with unilateral uropathy is frequently based on the split renal function as demonstrated by scintigraphy. MRI is not yet validated as a technique but nonetheless offers an interesting non-radiating alternative to achieve both morphological and functional renal evaluation. Recent pulse sequences such as diffusion, arterial spin labeling, and blood oxygenation dependent imaging may also provide additional information. CT and US remain of limited value for the evaluation of renal function.

  1. Imaging P-to-S conversions with multichannel receiver functions

    NASA Astrophysics Data System (ADS)

    Neal, Scott L.; Pavlis, Gary L.

    We present a new methodology in the direct imaging of P-to-S converted phases recorded on broadband seismic arrays. Our approach is based on conventional three-component array processing and receiver function techniques with the key addition of a weighted stack based on an aerial smoothing function. This creates synthetic arrays with a specified aperture whose image points vary continuously across the array. With this approach, it is possible to interpolate data from an array of broadband stations onto an arbitrarily fine grid. We have applied this technique to a single deep event recorded by the Lodore broadband array, located in northern Colorado and southern Wyoming. The resulting images show distinct differences in crustal structure across the array, and also image major upper mantle discontinuities.

  2. Image analysis of neuropsychological test responses

    NASA Astrophysics Data System (ADS)

    Smith, Stephen L.; Hiller, Darren L.

    1996-04-01

    This paper reports recent advances in the development of an automated approach to neuropsychological testing. High performance image analysis algorithms have been developed as part of a convenient and non-invasive computer-based system to provide an objective assessment of patient responses to figure-copying tests. Tests of this type are important in determining the neurological function of patients following stroke through evaluation of their visuo-spatial performance. Many conventional neuropsychological tests suffer from the serious drawback that subjective judgement on the part of the tester is required in the measurement of the patient's response which leads to a qualitative neuropsychological assessment that can be both inconsistent and inaccurate. Results for this automated approach are presented for three clinical populations: patients suffering right hemisphere stroke are compared with adults with no known neurological disorder and a population comprising normal school children of 11 years is presented to demonstrate the sensitivity of the technique. As well as providing a more reliable and consistent diagnosis this technique is sufficiently sensitive to monitor a patient's progress over a period of time and will provide the neuropsychologist with a practical means of evaluating the effectiveness of therapy or medication administered as part of a rehabilitation program.

  3. Dynamic Chest Image Analysis: Evaluation of Model-Based Pulmonary Perfusion Analysis With Pyramid Images

    DTIC Science & Technology

    2007-11-02

    Image Analysis aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the Dynamic Pulmonary Imaging technique 18,5,17,6. We have proposed and evaluated a multiresolutional method with an explicit ventilation model based on pyramid images for ventilation analysis. We have further extended the method for ventilation analysis to pulmonary perfusion. This paper focuses on the clinical evaluation of our method for

  4. On the origin and functions of the term functional analysis.

    PubMed

    Schlinger, Henry D; Normand, Matthew P

    2013-01-01

    In this essay, we note that although Iwata, Dorsey, Slifer, Bauman, and Richman (1982) established the standard framework for conducting functional analyses of problem behavior, the term functional analysis was probably first used in behavior analysis by B. F. Skinner in 1948. We also remind readers that a functional analysis is really an experimental analysis, words that were contained in the title of Skinner's first book, The Behavior of Organisms: An Experimental Analysis (1938). We further describe how Skinner initially applied the concept of functional analysis to an understanding of verbal behavior, and we suggest that the same tactic be applied to the verbal behavior of behavior analysts, in the present case, to the term functional analysis.

  5. Functional imaging of tumor vascular network in small animal models

    NASA Astrophysics Data System (ADS)

    Kalchenko, Vyacheslav; Madar-Balakirski, Noa; Kuznetsov, Yuri; Meglinski, Igor; Harmelin, Alon

    2011-07-01

    In current report we present synchronized in vivo imaging of tumor vascular network and tumor microenvironment obtained by combined use of Dynamic Light Scattering Imaging, Spectrally Enhanced Microscopy, and Fluorescence Intravital Microscopy. Dynamic Light Scattering Imaging is used for functional imaging of the vascular network and blood microcirculation. Spectrally Enhanced Microscopy provides information regarding blood vessel topography. Fluorescence Intravital Microscopy is used for imaging of tumor microvasculature and tumor microenvironment. These well known modalities have been comprehensively validated in the past and are widely used in various bio-medical applications. As shown here, their combined application has great potential for studies of vascular biology. This multi-modal non-invasive diagnostic technique expands our current capacity to investigate blood microcirculation and tumor angiogenesis in vivo, thereby contributing to the development of cancer research and treatment.

  6. Insights into dendritic cell function using advanced imaging modalities.

    PubMed

    Vyas, Jatin M

    2012-11-15

    The application of advanced imaging techniques to fundamental questions in immunology has provided insight into dendritic cell function and has challenged dogma created using static imaging of lymphoid tissue. The history of dendritic cell biology has a storied past and is tightly linked to imaging. The development of imaging techniques that emphasize live cell imaging in situ has provided not only breath-taking movies, but also novel insights into the importance of spatiotemporal relationships between antigen presenting cells and T cells. This review serves to provide a primer on two-photon microscopy, TIRF microscopy, spinning disk confocal microscopy and optical trapping and provides selective examples of insights gained from these tools on dendritic cell biology.

  7. Functional MRI studies of human vision on a clinical imager

    SciTech Connect

    George, J.S.; Lewine, J.D.; Aine, C.J.; van Hulsteyn, D.; Wood, C.C.; Sanders, J.; Maclin, E.; Belliveau, J.W.; Caprihan, A.

    1992-09-01

    During the past decade, Magnetic Resonance Imaging (MRI) has become the method of choice for imaging the anatomy of the human brain. Recently, Belliveau and colleagues have reported the use of echo planar magnetic resonance imaging (EPI) to image patterns of neural activity. Here, we report functional MR imaging in response to visual stimulation without the use of contrast agents, and without the extensive hardware modifications required for EPI. Regions of activity were observed near the expected locations of V1, V2 and possibly V3 and another active region was observed near the parietal-occipital sulcus on the superior surface of the cerebrum. These locations are consistent with sources observed in neuromagnetic studies of the human visual response.

  8. Functional MRI studies of human vision on a clinical imager

    SciTech Connect

    George, J.S.; Lewine, J.D.; Aine, C.J.; van Hulsteyn, D.; Wood, C.C. ); Sanders, J.; Maclin, E. ); Belliveau, J.W. ); Caprihan, A. )

    1992-01-01

    During the past decade, Magnetic Resonance Imaging (MRI) has become the method of choice for imaging the anatomy of the human brain. Recently, Belliveau and colleagues have reported the use of echo planar magnetic resonance imaging (EPI) to image patterns of neural activity. Here, we report functional MR imaging in response to visual stimulation without the use of contrast agents, and without the extensive hardware modifications required for EPI. Regions of activity were observed near the expected locations of V1, V2 and possibly V3 and another active region was observed near the parietal-occipital sulcus on the superior surface of the cerebrum. These locations are consistent with sources observed in neuromagnetic studies of the human visual response.

  9. Emerging concepts in functional and molecular photoacoustic imaging.

    PubMed

    Hu, Song

    2016-08-01

    Providing the specific imaging contrast of optical absorption and excellent spatial scalability across the optical and ultrasonic dimensions, photoacoustic imaging has been rapidly emerging and expanding in the past two decades. In this review, I focus on a few latest advances in this enabling technology that hold the potential to transform in vivo functional and molecular imaging at multiple length scales. Specifically, multi-parametric photoacoustic microscopy enables simultaneous high-resolution mapping of hemoglobin concentration, oxygen saturation and blood flow-opening up the possibility of quantifying the metabolic rate of oxygen at the microscopic level. The pump-probe approach harnesses a variety of photoinduced transient optical absorption as novel contrast mechanisms for high-specificity molecular imaging at depth and as nonlinear excitation strategies for high-resolution volumetric microscopy beyond the conventional limit. Novel magneto-optical and photochromic probes lead to contrast-enhanced molecular photoacoustic imaging through differential detection.

  10. Motion Analysis From Television Images

    NASA Astrophysics Data System (ADS)

    Silberberg, George G.; Keller, Patrick N.

    1982-02-01

    The Department of Defense ranges have relied on photographic instrumentation for gathering data of firings for all types of ordnance. A large inventory of cameras are available on the market that can be used for these tasks. A new set of optical instrumentation is beginning to appear which, in many cases, can directly replace photographic cameras for a great deal of the work being performed now. These are television cameras modified so they can stop motion, see in the dark, perform under hostile environments, and provide real time information. This paper discusses techniques for modifying television cameras so they can be used for motion analysis.

  11. Single remote sensing image scale-up combining modulation transform function compensation

    NASA Astrophysics Data System (ADS)

    Cao, Shixiang; Liu, Wei; Zhou, Nan; He, Hongyan; Jiang, Jie

    2016-01-01

    Remote sensing images usually need scale-up for visualization or representation, using only one original image. According to the performance of detective sensors, a new and more applicable method is proposed here. To enhance the high-frequency components, the modulation transform function compensation (MTFC) part focuses on how to adjust the spatial response before and after launch, under signal-to-noise ratio control. This largely reduces the ring phenomenon from incorrect point spread function guesses. Then a contour stencil prior manages to limit edge artifacts in the upscaled image after MTFC. An iterative backprojection operation with fast convergence is also utilized to bring about intensity and contour consistency. We finally present our analysis based on real images with parallel design for full speed. Compared with existing algorithms, the operator illustrates its potential to keep geometric features and extend the visual and quantitative quality for further analysis.

  12. Enhancing images with Intensity-Dependent Spread functions

    NASA Technical Reports Server (NTRS)

    Reese, Greg

    1992-01-01

    The theory of Intensity-Dependent Spread functions (IDS), a model of the human visual system proposed by Cornsweet (1985), is applied to image enhancement. An artificial image is examined which illustrates the characteristics of IDS processing and shows how the theoretical results translate into visual effects. Examples of realistic scenes that have been enhanced by IDS are presented. The system is shown to be particularly useful for bringing out detail in regions of low-contrast images. IDS can be readily implemented on a parallel computer.

  13. Functional renal imaging: new trends in radiology and nuclear medicine.

    PubMed

    Durand, Emmanuel; Chaumet-Riffaud, Philippe; Grenier, Nicolas

    2011-01-01

    The objective of this work is to compare the characteristics of various techniques for functional renal imaging, with a focus on nuclear medicine and magnetic resonance imaging. Even with low spatial resolution and rather poor signal-to-noise ratio, classical nuclear medicine has the advantage of linearity and good sensitivity. It remains the gold standard technique for renal relative functional assessment. Technetium-99m ((99m)Tc)-labeled diethylenetriamine penta-acetate remains the reference glomerular tracer. Tubular tracers have been improved: (123)I- or (131)I-hippuran, (99m)Tc-MAG3 and, recently, (99m)Tc-nitrilotriacetic acid. However, advancement in molecular imaging has not produced a groundbreaking tracer. Renal magnetic resonance imaging with classical gadolinated tracers probably has potential in this domain but has a lack of linearity and, therefore, its value still needs evaluation. Moreover, the advent of nephrogenic systemic fibrosis has delayed its expansion. Other developments, such as diffusion or blood oxygen level-dependent imaging, may have a role in the future. The other modalities have a limited role in clinical practice for functional renal imaging.

  14. Embedding based on function approximation for large scale image search.

    PubMed

    Do, Thanh-Toan; Cheung, Ngai-Man

    2017-03-23

    The objective of this paper is to design an embedding method that maps local features describing an image (e.g. SIFT) to a higher dimensional representation useful for the image retrieval problem. First, motivated by the relationship between the linear approximation of a nonlinear function in high dimensional space and the stateof- the-art feature representation used in image retrieval, i.e., VLAD, we propose a new approach for the approximation. The embedded vectors resulted by the function approximation process are then aggregated to form a single representation for image retrieval. Second, in order to make the proposed embedding method applicable to large scale problem, we further derive its fast version in which the embedded vectors can be efficiently computed, i.e., in the closed-form. We compare the proposed embedding methods with the state of the art in the context of image search under various settings: when the images are represented by medium length vectors, short vectors, or binary vectors. The experimental results show that the proposed embedding methods outperform existing the state of the art on the standard public image retrieval benchmarks.

  15. Functional imaging of small tissue volumes with diffuse optical tomography

    NASA Astrophysics Data System (ADS)

    Klose, Alexander D.; Hielscher, Andreas H.

    2006-03-01

    Imaging of dynamic changes in blood parameters, functional brain imaging, and tumor imaging are the most advanced application areas of diffuse optical tomography (DOT). When dealing with the image reconstruction problem one is faced with the fact that near-infrared photons, unlike X-rays, are highly scattered when they traverse biological tissue. Image reconstruction schemes are required that model the light propagation inside biological tissue and predict measurements on the tissue surface. By iteratively changing the tissue-parameters until the predictions agree with the real measurements, a spatial distribution of optical properties inside the tissue is found. The optical properties can be related to the tissue oxygenation, inflammation, or to the fluorophore concentration of a biochemical marker. If the model of light propagation is inaccurate, the reconstruction process will lead to an inaccurate result as well. Here, we focus on difficulties that are encountered when DOT is employed for functional imaging of small tissue volumes, for example, in cancer studies involving small animals, or human finger joints for early diagnosis of rheumatoid arthritis. Most of the currently employed image reconstruction methods rely on the diffusion theory that is an approximation to the equation of radiative transfer. But, in the cases of small tissue volumes and tissues that contain low scattering regions diffusion theory has been shown to be of limited applicability Therefore, we employ a light propagation model that is based on the equation of radiative transfer, which promises to overcome the limitations.

  16. Basis Functions in Image Reconstruction From Projections: A Tutorial Introduction

    NASA Astrophysics Data System (ADS)

    Herman, Gabor T.

    2015-11-01

    The series expansion approaches to image reconstruction from projections assume that the object to be reconstructed can be represented as a linear combination of fixed basis functions and the task of the reconstruction algorithm is to estimate the coefficients in such a linear combination based on the measured projection data. It is demonstrated that using spherically symmetric basis functions (blobs), instead of ones based on the more traditional pixels, yields superior reconstructions of medically relevant objects. The demonstration uses simulated computerized tomography projection data of head cross-sections and the series expansion method ART for the reconstruction. In addition to showing the results of one anecdotal example, the relative efficacy of using pixel and blob basis functions in image reconstruction from projections is also evaluated using a statistical hypothesis testing based task oriented comparison methodology. The superiority of the efficacy of blob basis functions over that of pixel basis function is found to be statistically significant.

  17. Medical image analysis with artificial neural networks.

    PubMed

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

    Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging.

  18. Curvelet Based Offline Analysis of SEM Images

    PubMed Central

    Shirazi, Syed Hamad; Haq, Nuhman ul; Hayat, Khizar; Naz, Saeeda; Haque, Ihsan ul

    2014-01-01

    Manual offline analysis, of a scanning electron microscopy (SEM) image, is a time consuming process and requires continuous human intervention and efforts. This paper presents an image processing based method for automated offline analyses of SEM images. To this end, our strategy relies on a two-stage process, viz. texture analysis and quantification. The method involves a preprocessing step, aimed at the noise removal, in order to avoid false edges. For texture analysis, the proposed method employs a state of the art Curvelet transform followed by segmentation through a combination of entropy filtering, thresholding and mathematical morphology (MM). The quantification is carried out by the application of a box-counting algorithm, for fractal dimension (FD) calculations, with the ultimate goal of measuring the parameters, like surface area and perimeter. The perimeter is estimated indirectly by counting the boundary boxes of the filled shapes. The proposed method, when applied to a representative set of SEM images, not only showed better results in image segmentation but also exhibited a good accuracy in the calculation of surface area and perimeter. The proposed method outperforms the well-known Watershed segmentation algorithm. PMID:25089617

  19. Deep Learning in Medical Image Analysis.

    PubMed

    Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

    2017-03-09

    This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement. Expected final online publication date for the Annual Review of Biomedical Engineering Volume 19 is June 4, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

  20. Use of localized performance-based functions for the specification and correction of hybrid imaging systems

    NASA Astrophysics Data System (ADS)

    Lisson, Jerold B.; Mounts, Darryl I.; Fehniger, Michael J.

    1992-08-01

    Localized wavefront performance analysis (LWPA) is a system that allows the full utilization of the system optical transfer function (OTF) for the specification and acceptance of hybrid imaging systems. We show that LWPA dictates the correction of wavefront errors with the greatest impact on critical imaging spatial frequencies. This is accomplished by the generation of an imaging performance map-analogous to a map of the optic pupil error-using a local OTF. The resulting performance map a function of transfer function spatial frequency is directly relatable to the primary viewing condition of the end-user. In addition to optimizing quality for the viewer it will be seen that the system has the potential for an improved matching of the optical and electronic bandpass of the imager and for the development of more realistic acceptance specifications. 1. LOCAL WAVEFRONT PERFORMANCE ANALYSIS The LWPA system generates a local optical quality factor (LOQF) in the form of a map analogous to that used for the presentation and evaluation of wavefront errors. In conjunction with the local phase transfer function (LPTF) it can be used for maximally efficient specification and correction of imaging system pupil errors. The LOQF and LPTF are respectively equivalent to the global modulation transfer function (MTF) and phase transfer function (PTF) parts of the OTF. The LPTF is related to difference of the average of the errors in separated regions of the pupil. Figure

  1. Altered amygdala and hippocampus effective connectivity in mild cognitive impairment patients with depression: a resting-state functional MR imaging study with granger causality analysis.

    PubMed

    Zheng, Li Juan; Yang, Gui Fen; Zhang, Xin Yuan; Wang, Yun Fei; Liu, Ya; Zheng, Gang; Lu, Guang Ming; Zhang, Long Jiang; Han, Ying

    2017-02-15

    Neuroimaging studies have demonstrated that the major depression disorder would increase the risk of dementia in the older with amnestic cognitive impairment. We used granger causality analysis algorithm to explore the amygdala- and hippocampus-based directional connectivity patterns in 12 patients with major depression disorder and amnestic cognitive impairment (mean age: 69.5 ± 10.3 years), 13 amnestic cognitive impairment patients (mean age: 72.7 ± 8.5 years) and 14 healthy controls (mean age: 64.7 ± 7.0 years). Compared with amnestic cognitive impairment patients and control groups respectively, the patients with both major depression disorder and amnestic cognitive impairment displayed increased effective connectivity from the right amygdala to the right lingual and calcarine gyrus, as well as to the bilateral supplementary motor areas. Meanwhile, the patients with both major depression disorder and amnestic cognitive impairment had enhanced effective connectivity from the left superior parietal gyrus, superior and middle occipital gyrus to the left hippocampus, the z values of which was also correlated with the scores of mini-mental state examination and auditory verbal learning test-immediate recall. Our findings indicated that the directional effective connectivity of right amygdala - occipital-parietal lobe - left hippocampus might be the pathway by which major depression disorder inhibited the brain activity in patients with amnestic cognitive impairment.

  2. Functional Analysis and Treatment of Nail Biting

    ERIC Educational Resources Information Center

    Dufrene, Brad A.; Watson, T. Steuart; Kazmerski, Jennifer S.

    2008-01-01

    This study applied functional analysis methodology to nail biting exhibited by a 24-year-old female graduate student. Results from the brief functional analysis indicated variability in nail biting across assessment conditions. Functional analysis data were then used to guide treatment development and implementation. Treatment included a…

  3. Design and implementation of non-linear image processing functions for CMOS image sensor

    NASA Astrophysics Data System (ADS)

    Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

    2012-11-01

    Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

  4. Geometric error analysis for shuttle imaging spectrometer experiment

    NASA Technical Reports Server (NTRS)

    Wang, S. J.; Ih, C. H.

    1984-01-01

    The demand of more powerful tools for remote sensing and management of earth resources steadily increased over the last decade. With the recent advancement of area array detectors, high resolution multichannel imaging spectrometers can be realistically constructed. The error analysis study for the Shuttle Imaging Spectrometer Experiment system is documented for the purpose of providing information for design, tradeoff, and performance prediction. Error sources including the Shuttle attitude determination and control system, instrument pointing and misalignment, disturbances, ephemeris, Earth rotation, etc., were investigated. Geometric error mapping functions were developed, characterized, and illustrated extensively with tables and charts. Selected ground patterns and the corresponding image distortions were generated for direct visual inspection of how the various error sources affect the appearance of the ground object images.

  5. Lung nodules detection in chest radiography: image components analysis

    NASA Astrophysics Data System (ADS)

    Luo, Tao; Mou, Xuanqin; Yang, Ying; Yan, Hao

    2009-02-01

    We aimed to evaluate the effect of different components of chest image on performances of both human observer and channelized Fisher-Hotelling model (CFH) in nodule detection task. Irrelevant and relevant components were separated from clinical chest radiography by employing Principal Component Analysis (PCA) methods. Human observer performance was evaluated in two-alternative forced-choice (2AFC) on original clinical images and anatomical structure only images obtained by PCA methods. Channelized Fisher-Hotelling model with Laguerre-Gauss basis function was evaluated to predict human performance. We show that relevant component is the primary factor influencing on nodule detection in chest radiography. There is obvious difference of detectability between human observer and CFH model for nodule detection in images only containing anatomical structure. CFH model should be used more carefully.

  6. Measuring toothbrush interproximal penetration using image analysis

    NASA Astrophysics Data System (ADS)

    Hayworth, Mark S.; Lyons, Elizabeth K.

    1994-09-01

    An image analysis method of measuring the effectiveness of a toothbrush in reaching the interproximal spaces of teeth is described. Artificial teeth are coated with a stain that approximates real plaque and then brushed with a toothbrush on a brushing machine. The teeth are then removed and turned sideways so that the interproximal surfaces can be imaged. The areas of stain that have been removed within masked regions that define the interproximal regions are measured and reported. These areas correspond to the interproximal areas of the tooth reached by the toothbrush bristles. The image analysis method produces more precise results (10-fold decrease in standard deviation) in a fraction (22%) of the time as compared to our prior visual grading method.

  7. Functional Imaging in OA: Role of Imaging in the Evaluation of Tissue Biomechanics

    PubMed Central

    Neu, Corey P.

    2014-01-01

    Functional imaging refers broadly to the visualization of organ or tissue physiology using medical image modalities. In load-bearing tissues of the body, including articular cartilage lining the bony ends of joints, changes in strain, stress, and material properties occur in osteoarthritis (OA), providing an opportunity to probe tissue function through the progression of the disease. Here, biomechanical measures in cartilage and related joint tissues are discussed as key imaging biomarkers in the evaluation of OA. Emphasis will be placed on the a) potential of radiography, ultrasound, and magnetic resonance imaging to assess early tissue pathomechanics in OA, b) relative utility of kinematic, structural, morphological, and biomechanical measures as functional imaging biomarkers, and c) improved diagnostic specificity through the combination of multiple imaging biomarkers with unique contrasts, including elastography and quantitative assessments of tissue biochemistry. In comparison to other modalities, magnetic resonance imaging provides an extensive range of functional measures at the tissue level, with conventional and emerging techniques available to potentially to assess the spectrum of preclinical to advance OA. PMID:25278049

  8. Probe and object function reconstruction in incoherent stem imaging

    SciTech Connect

    Nellist, P.D.; Pennycook, S.J.

    1996-09-01

    Using the phase-object approximation it is shown how an annular dark- field (ADF) detector in a scanning transmission electron microscope (STEM) leads to an image which can be described by an incoherent model. The point spread function is found to be simply the illuminating probe intensity. An important consequence of this is that there is no phase problem in the imaging process, which allows various image processing methods to be applied directly to the image intensity data. Using an image of a GaAs<110>, the probe intensity profile is reconstructed, confirming the existence of a 1.3 {Angstrom} probe in a 300kV STEM. It is shown that simply deconvolving this reconstructed probe from the image data does not improve its interpretability because the dominant effects of the imaging process arise simply from the restricted resolution of the microscope. However, use of the reconstructed probe in a maximum entropy reconstruction is demonstrated, which allows information beyond the resolution limit to be restored and does allow improved image interpretation.

  9. Unsupervised hyperspectral image analysis using independent component analysis (ICA)

    SciTech Connect

    S. S. Chiang; I. W. Ginsberg

    2000-06-30

    In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed as a random version of the commonly used linear spectral mixture analysis, in which the abundance fractions in a linear mixture model are considered to be unknown independent signal sources. It does not require the full rank of the separating matrix or orthogonality as most ICA methods do. More importantly, the learning algorithm is designed based on the independency of the material abundance vector rather than the independency of the separating matrix generally used to constrain the standard ICA. As a result, the designed learning algorithm is able to converge to non-orthogonal independent components. This is particularly useful in hyperspectral image analysis since many materials extracted from a hyperspectral image may have similar spectral signatures and may not be orthogonal. The AVIRIS experiments have demonstrated that the proposed ICA provides an effective unsupervised technique for hyperspectral image classification.

  10. Digital image analysis of haematopoietic clusters.

    PubMed

    Benzinou, A; Hojeij, Y; Roudot, A-C

    2005-02-01

    Counting and differentiating cell clusters is a tedious task when performed with a light microscope. Moreover, biased counts and interpretation are difficult to avoid because of the difficulties to evaluate the limits between different types of clusters. Presented here, is a computer-based application able to solve these problems. The image analysis system is entirely automatic, from the stage screening, to the statistical analysis of the results of each experimental plate. Good correlations are found with measurements made by a specialised technician.

  11. New developments in paediatric cardiac functional ultrasound imaging.

    PubMed

    de Korte, Chris L; Nillesen, Maartje M; Saris, Anne E C M; Lopata, Richard G P; Thijssen, Johan M; Kapusta, Livia

    2014-07-01

    Ultrasound imaging can be used to estimate the morphology as well as the motion and deformation of tissues. If the interrogated tissue is actively deforming, this deformation is directly related to its function and quantification of this deformation is normally referred as 'strain imaging'. Tissue can also be deformed by applying an internal or external force and the resulting, induced deformation is a function of the mechanical tissue characteristics. In combination with the load applied, these strain maps can be used to estimate or reconstruct the mechanical properties of tissue. This technique was named 'elastography' by Ophir et al. in 1991. Elastography can be used for atherosclerotic plaque characterisation, while the contractility of the heart or skeletal muscles can be assessed with strain imaging. Rather than using the conventional video format (DICOM) image information, radio frequency (RF)-based ultrasound methods enable estimation of the deformation at higher resolution and with higher precision than commercial methods using Doppler (tissue Doppler imaging) or video image data (2D speckle tracking methods). However, the improvement in accuracy is mainly achieved when measuring strain along the ultrasound beam direction, so it has to be considered a 1D technique. Recently, this method has been extended to multiple directions and precision further improved by using spatial compounding of data acquired at multiple beam steered angles. Using similar techniques, the blood velocity and flow can be determined. RF-based techniques are also beneficial for automated segmentation of the ventricular cavities. In this paper, new developments in different techniques of quantifying cardiac function by strain imaging, automated segmentation, and methods of performing blood flow imaging are reviewed and their application in paediatric cardiology is discussed.

  12. COMPUTER ANALYSIS OF PLANAR GAMMA CAMERA IMAGES

    EPA Science Inventory



    COMPUTER ANALYSIS OF PLANAR GAMMA CAMERA IMAGES

    T Martonen1 and J Schroeter2

    1Experimental Toxicology Division, National Health and Environmental Effects Research Laboratory, U.S. EPA, Research Triangle Park, NC 27711 USA and 2Curriculum in Toxicology, Unive...

  13. Scale Free Reduced Rank Image Analysis.

    ERIC Educational Resources Information Center

    Horst, Paul

    In the traditional Guttman-Harris type image analysis, a transformation is applied to the data matrix such that each column of the transformed data matrix is the best least squares estimate of the corresponding column of the data matrix from the remaining columns. The model is scale free. However, it assumes (1) that the correlation matrix is…

  14. Using Image Analysis to Build Reading Comprehension

    ERIC Educational Resources Information Center

    Brown, Sarah Drake; Swope, John

    2010-01-01

    Content area reading remains a primary concern of history educators. In order to better prepare students for encounters with text, the authors propose the use of two image analysis strategies tied with a historical theme to heighten student interest in historical content and provide a basis for improved reading comprehension.

  15. Visualization of parameter space for image analysis.

    PubMed

    Pretorius, A Johannes; Bray, Mark-Anthony P; Carpenter, Anne E; Ruddle, Roy A

    2011-12-01

    Image analysis algorithms are often highly parameterized and much human input is needed to optimize parameter settings. This incurs a time cost of up to several days. We analyze and characterize the conventional parameter optimization process for image analysis and formulate user requirements. With this as input, we propose a change in paradigm by optimizing parameters based on parameter sampling and interactive visual exploration. To save time and reduce memory load, users are only involved in the first step--initialization of sampling--and the last step--visual analysis of output. This helps users to more thoroughly explore the parameter space and produce higher quality results. We describe a custom sampling plug-in we developed for CellProfiler--a popular biomedical image analysis framework. Our main focus is the development of an interactive visualization technique that enables users to analyze the relationships between sampled input parameters and corresponding output. We implemented this in a prototype called Paramorama. It provides users with a visual overview of parameters and their sampled values. User-defined areas of interest are presented in a structured way that includes image-based output and a novel layout algorithm. To find optimal parameter settings, users can tag high- and low-quality results to refine their search. We include two case studies to illustrate the utility of this approach.

  16. ImageJ: Image processing and analysis in Java

    NASA Astrophysics Data System (ADS)

    Rasband, W. S.

    2012-06-01

    ImageJ is a public domain Java image processing program inspired by NIH Image. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.

  17. IMAGE EXPLORER: Astronomical Image Analysis on an HTML5-based Web Application

    NASA Astrophysics Data System (ADS)

    Gopu, A.; Hayashi, S.; Young, M. D.

    2014-05-01

    Large datasets produced by recent astronomical imagers cause the traditional paradigm for basic visual analysis - typically downloading one's entire image dataset and using desktop clients like DS9, Aladin, etc. - to not scale, despite advances in desktop computing power and storage. This paper describes Image Explorer, a web framework that offers several of the basic visualization and analysis functionality commonly provided by tools like DS9, on any HTML5 capable web browser on various platforms. It uses a combination of the modern HTML5 canvas, JavaScript, and several layers of lossless PNG tiles producted from the FITS image data. Astronomers are able to rapidly and simultaneously open up several images on their web-browser, adjust the intensity min/max cutoff or its scaling function, and zoom level, apply color-maps, view position and FITS header information, execute typically used data reduction codes on the corresponding FITS data using the FRIAA framework, and overlay tiles for source catalog objects, etc.

  18. Structural and functional imaging of 3D microfluidic mixers using optical coherence tomography.

    PubMed

    Xi, Chuanwu; Marks, Daniel L; Parikh, Devang S; Raskin, Lutgarde; Boppart, Stephen A

    2004-05-18

    To achieve high mixing efficiency in microfluidic devices, complex designs are often required. Microfluidic devices have been evaluated with light and confocal microscopy, but fluid-flow characteristics at different depths are difficult to separate from the en face images produced. By using optical coherence tomography (OCT), an imaging modality capable of imaging 3D microstructures at micrometer-scale resolutions over millimeter-size scales, we obtained 3D dynamic functional and structural data for three representative microfluidic mixers: a Y channel mixer, a 3D serpentine mixer, and a vortex mixer. In the serpentine mixer, OCT image analysis revealed that the mixing efficiency was linearly dependent on the Reynolds number, whereas it appeared to have exponential dependence when imaged with light microscopy. The visual overlap of fluid flows in light-microscopy images leads to an overestimation of the mixing efficiency, an effect that was eliminated with OCT imaging. Doppler OCT measurements determined velocity profiles at various points in the serpentine mixer. Mixing patterns in the vortex mixer were compared with light-microscopy and OCT image analysis. These results demonstrate that OCT can significantly improve the characterization of 3D microfluidic device structure and function.

  19. Hyperpolarized Xenon-129 Magnetic Resonance Imaging of Functional Lung Microstructure

    NASA Astrophysics Data System (ADS)

    Dregely, Isabel

    Hyperpolarized 129Xe (HXe) is a non-invasive contrast agent for lung magnetic resonance imaging (MRI), which upon inhalation follows the functional pathway of oxygen in the lung by dissolving into lung tissue structures and entering the blood stream. HXe MRI therefore provides unique opportunities for functional lung imaging of gas exchange which occurs from alveolar air spaces across the air-blood boundary into parenchymal tissue. However challenges in acquisition speed and signal-to-noise ratio have limited the development of a HXe imaging biomarker to diagnose lung disease. This thesis addresses these challenges by introducing parallel imaging to HXe MRI. Parallel imaging requires dedicated hardware. This work describes design, implementation, and characterization of a 32-channel phased-array chest receive coil with an integrated asymmetric birdcage transmit coil tuned to the HXe resonance on a 3 Tesla MRI system. Using the newly developed human chest coil, a functional HXe imaging method, multiple exchange time xenon magnetization transfer contrast (MXTC) is implemented. MXTC dynamically encodes HXe gas exchange into the image contrast. This permits two parameters to be derived regionally which are related to gas-exchange functionality by characterizing tissue-to-alveolar-volume ratio and alveolar wall thickness in the lung parenchyma. Initial results in healthy subjects demonstrate the sensitivity of MXTC by quantifying the subtle changes in lung microstructure in response to orientation and lung inflation. Our results in subjects with lung disease show that the MXTC-derived functional tissue density parameter exhibits excellent agreement with established imaging techniques. The newly developed dynamic parameter, which characterizes the alveolar wall, was elevated in subjects with lung disease, most likely indicating parenchymal inflammation. In light of these observations we believe that MXTC has potential as a biomarker for the regional quantification of 1

  20. Analysis of PETT images in psychiatric disorders

    SciTech Connect

    Brodie, J.D.; Gomez-Mont, F.; Volkow, N.D.; Corona, J.F.; Wolf, A.P.; Wolkin, A.; Russell, J.A.G.; Christman, D.; Jaeger, J.

    1983-01-01

    A quantitative method is presented for studying the pattern of metabolic activity in a set of Positron Emission Transaxial Tomography (PETT) images. Using complex Fourier coefficients as a feature vector for each image, cluster, principal components, and discriminant function analyses are used to empirically describe metabolic differences between control subjects and patients with DSM III diagnosis for schizophrenia or endogenous depression. We also present data on the effects of neuroleptic treatment on the local cerebral metabolic rate of glucose utilization (LCMRGI) in a group of chronic schizophrenics using the region of interest approach. 15 references, 4 figures, 3 tables.

  1. Noninvasive structural, functional, and molecular imaging in drug development.

    PubMed

    Rudin, Markus

    2009-06-01

    Modern drug research is mechanism-based and the development of disease modifying therapies involves the identification of molecular key players in the pathological cascade. Today, noninvasive imaging tools enable the visualization and quantitative assessment of the expression of molecular targets, of their interaction with potential ligands, as well as of the functional consequence of this interaction at a molecular (e.g. activation of signaling cascades), cellular, metabolic, physiological, and morphological level in a temporo-spatially resolved manner. The ability to gather such information from the intact organism with all regulatory processes in place renders imaging highly attractive for the biomedical researcher and for the drug developer in particular. Molecular imaging is potentially capable of providing this information. Today, proof-of-principle has been established that imaging is in fact adding value to the drug discovery and development processes. Numerous studies have used structural and functional imaging readouts to document therapy efficacy, mainly during lead optimization. Similarly, major efforts have been devoted to the development and evaluation of imaging biomarkers that might serve as early readouts for therapy response with the potential of being used in the clinical drug evaluation thereby facilitating translational research. In this contribution, we illustrate the role and potential of imaging in modern drug discovery and development with selected examples. Yet, despite its huge potential the impact of imaging on drug discovery has been modest in the past; potential reasons will be discussed. Nevertheless, noninvasive imaging methods are rapidly evolving and it is beyond doubt that their importance for biomedical research will increase.

  2. Good relationships between computational image analysis and radiological physics

    NASA Astrophysics Data System (ADS)

    Arimura, Hidetaka; Kamezawa, Hidemi; Jin, Ze; Nakamoto, Takahiro; Soufi, Mazen

    2015-09-01

    Good relationships between computational image analysis and radiological physics have been constructed for increasing the accuracy of medical diagnostic imaging and radiation therapy in radiological physics. Computational image analysis has been established based on applied mathematics, physics, and engineering. This review paper will introduce how computational image analysis is useful in radiation therapy with respect to radiological physics.

  3. Good relationships between computational image analysis and radiological physics

    SciTech Connect

    Arimura, Hidetaka; Kamezawa, Hidemi; Jin, Ze; Nakamoto, Takahiro; Soufi, Mazen

    2015-09-30

    Good relationships between computational image analysis and radiological physics have been constructed for increasing the accuracy of medical diagnostic imaging and radiation therapy in radiological physics. Computational image analysis has been established based on applied mathematics, physics, and engineering. This review paper will introduce how computational image analysis is useful in radiation therapy with respect to radiological physics.

  4. Image processing and analysis using neural networks for optometry area

    NASA Astrophysics Data System (ADS)

    Netto, Antonio V.; Ferreira de Oliveira, Maria C.

    2002-11-01

    In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

  5. Lateralizing language function with pre-operative functional magnetic resonance imaging in early proficient bilingual patients.

    PubMed

    Połczyńska, Monika M; Japardi, Kevin; Bookheimer, Susan Y

    2017-03-23

    Research on bilinguals with brain lesions is complicated by high patient variability, making it difficult to find well-matched controls. We benefitted from a database of over 700 patients and conducted an analysis of pre-operative functional magnetic resonance imaging data to assess language dominance in 25 early, highly proficient Spanish-English bilinguals, and 25 carefully matched monolingual controls. Our results showed that early bilingualism is associated with greater bilateral hemispheric involvement, and monolingualism is associated with stronger left hemisphere lateralization (p=0.009). The bilinguals showed more pronounced right hemisphere activation (p=0.008). Although language dominance values were concordant in the bilingual group, there were a few (12%) atypical cases with different lateralization patterns in L1 and L2. Finally, we found distinct areas of activity in first and second language within the language network, in addition to regions of convergence. These data underscore the need to map all languages proficiently spoken by surgical candidates.

  6. Functional analysis and treatment of nail biting.

    PubMed

    Dufrene, Brad A; Steuart Watson, T; Kazmerski, Jennifer S

    2008-11-01

    This study applied functional analysis methodology to nail biting exhibited by a 24-year-old female graduate student. Results from the brief functional analysis indicated variability in nail biting across assessment conditions. Functional analysis data were then used to guide treatment development and implementation. Treatment included a simplified habit reversal package that was modified based on results of the functional analysis. Following treatment implementation, nail biting decreased as evidenced by consistent nail growth and participant self-recorded data. Results are discussed in terms of treatment utility of functional analysis methodology for novel populations and response topographies.

  7. Difference image analysis: automatic kernel design using information criteria

    NASA Astrophysics Data System (ADS)

    Bramich, D. M.; Horne, Keith; Alsubai, K. A.; Bachelet, E.; Mislis, D.; Parley, N.

    2016-03-01

    We present a selection of methods for automatically constructing an optimal kernel model for difference image analysis which require very few external parameters to control the kernel design. Each method consists of two components; namely, a kernel design algorithm to generate a set of candidate kernel models, and a model selection criterion to select the simplest kernel model from the candidate models that provides a sufficiently good fit to the target image. We restricted our attention to the case of solving for a spatially invariant convolution kernel composed of delta basis functions, and we considered 19 different kernel solution methods including six employing kernel regularization. We tested these kernel solution methods by performing a comprehensive set of image simulations and investigating how their performance in terms of model error, fit quality, and photometric accuracy depends on the properties of the reference and target images. We find that the irregular kernel design algorithm employing unregularized delta basis functions, combined with either the Akaike or Takeuchi information criterion, is the best kernel solution method in terms of photometric accuracy. Our results are validated by tests performed on two independent sets of real data. Finally, we provide some important recommendations for software implementations of difference image analysis.

  8. Differential Item Functioning Analysis Using Rasch Item Information Functions

    ERIC Educational Resources Information Center

    Wyse, Adam E.; Mapuranga, Raymond

    2009-01-01

    Differential item functioning (DIF) analysis is a statistical technique used for ensuring the equity and fairness of educational assessments. This study formulates a new DIF analysis method using the information similarity index (ISI). ISI compares item information functions when data fits the Rasch model. Through simulations and an international…

  9. Phase transfer function based method to alleviate image artifacts in wavefront coding imaging system

    NASA Astrophysics Data System (ADS)

    Mo, Xutao; Wang, Jinjiang

    2013-09-01

    Wavefront coding technique can extend the depth of filed (DOF) of the incoherent imaging system. Several rectangular separable phase masks (such as cubic type, exponential type, logarithmic type, sinusoidal type, rational type, et al) have been proposed and discussed, because they can extend the DOF up to ten times of the DOF of ordinary imaging system. But according to the research on them, researchers have pointed out that the images are damaged by the artifacts, which usually come from the non-linear phase transfer function (PTF) differences between the PTF used in the image restoration filter and the PTF related to real imaging condition. In order to alleviate the image artifacts in imaging systems with wavefront coding, an optimization model based on the PTF was proposed to make the PTF invariance with the defocus. Thereafter, an image restoration filter based on the average PTF in the designed depth of field was introduced along with the PTF-based optimization. The combination of the optimization and the image restoration proposed can alleviate the artifacts, which was confirmed by the imaging simulation of spoke target. The cubic phase mask (CPM) and exponential phase mask (EPM) were discussed as example.

  10. Automated retinal image analysis over the internet.

    PubMed

    Tsai, Chia-Ling; Madore, Benjamin; Leotta, Matthew J; Sofka, Michal; Yang, Gehua; Majerovics, Anna; Tanenbaum, Howard L; Stewart, Charles V; Roysam, Badrinath

    2008-07-01

    Retinal clinicians and researchers make extensive use of images, and the current emphasis is on digital imaging of the retinal fundus. The goal of this paper is to introduce a system, known as retinal image vessel extraction and registration system, which provides the community of retinal clinicians, researchers, and study directors an integrated suite of advanced digital retinal image analysis tools over the Internet. The capabilities include vasculature tracing and morphometry, joint (simultaneous) montaging of multiple retinal fields, cross-modality registration (color/red-free fundus photographs and fluorescein angiograms), and generation of flicker animations for visualization of changes from longitudinal image sequences. Each capability has been carefully validated in our previous research work. The integrated Internet-based system can enable significant advances in retina-related clinical diagnosis, visualization of the complete fundus at full resolution from multiple low-angle views, analysis of longitudinal changes, research on the retinal vasculature, and objective, quantitative computer-assisted scoring of clinical trials imagery. It could pave the way for future screening services from optometry facilities.

  11. Digital imaging analysis to assess scar phenotype.

    PubMed

    Smith, Brian J; Nidey, Nichole; Miller, Steven F; Moreno Uribe, Lina M; Baum, Christian L; Hamilton, Grant S; Wehby, George L; Dunnwald, Martine

    2014-01-01

    In order to understand the link between the genetic background of patients and wound clinical outcomes, it is critical to have a reliable method to assess the phenotypic characteristics of healed wounds. In this study, we present a novel imaging method that provides reproducible, sensitive, and unbiased assessments of postsurgical scarring. We used this approach to investigate the possibility that genetic variants in orofacial clefting genes are associated with suboptimal healing. Red-green-blue digital images of postsurgical scars of 68 patients, following unilateral cleft lip repair, were captured using the 3dMD imaging system. Morphometric and colorimetric data of repaired regions of the philtrum and upper lip were acquired using ImageJ software, and the unaffected contralateral regions were used as patient-specific controls. Repeatability of the method was high with intraclass correlation coefficient score > 0.8. This method detected a very significant difference in all three colors, and for all patients, between the scarred and the contralateral unaffected philtrum (p ranging from 1.20(-05) to 1.95(-14) ). Physicians' clinical outcome ratings from the same images showed high interobserver variability (overall Pearson coefficient = 0.49) as well as low correlation with digital image analysis results. Finally, we identified genetic variants in TGFB3 and ARHGAP29 associated with suboptimal healing outcome.

  12. Digital imaging analysis to assess scar phenotype

    PubMed Central

    Smith, Brian J.; Nidey, Nichole; Miller, Steven F.; Moreno, Lina M.; Baum, Christian L.; Hamilton, Grant S.; Wehby, George L.; Dunnwald, Martine

    2015-01-01

    In order to understand the link between the genetic background of patients and wound clinical outcomes, it is critical to have a reliable method to assess the phenotypic characteristics of healed wounds. In this study, we present a novel imaging method that provides reproducible, sensitive and unbiased assessments of post-surgical scarring. We used this approach to investigate the possibility that genetic variants in orofacial clefting genes are associated with suboptimal healing. Red-green-blue (RGB) digital images of post-surgical scars of 68 patients, following unilateral cleft lip repair, were captured using the 3dMD image system. Morphometric and colorimetric data of repaired regions of the philtrum and upper lip were acquired using ImageJ software and the unaffected contralateral regions were used as patient-specific controls. Repeatability of the method was high with interclass correlation coefficient score > 0.8. This method detected a very significant difference in all three colors, and for all patients, between the scarred and the contralateral unaffected philtrum (P ranging from 1.20−05 to 1.95−14). Physicians’ clinical outcome ratings from the same images showed high inter-observer variability (overall Pearson coefficient = 0.49) as well as low correlation with digital image analysis results. Finally, we identified genetic variants in TGFB3 and ARHGAP29 associated with suboptimal healing outcome. PMID:24635173

  13. Adaptive sigmoid function bihistogram equalization for image contrast enhancement

    NASA Astrophysics Data System (ADS)

    Arriaga-Garcia, Edgar F.; Sanchez-Yanez, Raul E.; Ruiz-Pinales, Jose; Garcia-Hernandez, Ma. de Guadalupe

    2015-09-01

    Contrast enhancement plays a key role in a wide range of applications including consumer electronic applications, such as video surveillance, digital cameras, and televisions. The main goal of contrast enhancement is to increase the quality of images. However, most state-of-the-art methods induce different types of distortion such as intensity shift, wash-out, noise, intensity burn-out, and intensity saturation. In addition, in consumer electronics, simple and fast methods are required in order to be implemented in real time. A bihistogram equalization method based on adaptive sigmoid functions is proposed. It consists of splitting the image histogram into two parts that are equalized independently by using adaptive sigmoid functions. In order to preserve the mean brightness of the input image, the parameter of the sigmoid functions is chosen to minimize the absolute mean brightness metric. Experiments on the Berkeley database have shown that the proposed method improves the quality of images and preserves their mean brightness. An application to improve the colorfulness of images is also presented.

  14. Ultrasound strain imaging for quantification of tissue function: cardiovascular applications

    NASA Astrophysics Data System (ADS)

    de Korte, Chris L.; Lopata, Richard G. P.; Hansen, Hendrik H. G.

    2013-03-01

    With ultrasound imaging, the motion and deformation of tissue can be measured. Tissue can be deformed by applying a force on it and the resulting deformation is a function of its mechanical properties. Quantification of this resulting tissue deformation to assess the mechanical properties of tissue is called elastography. If the tissue under interrogation is actively deforming, the deformation is directly related to its function and quantification of this deformation is normally referred as `strain imaging'. Elastography can be used for atherosclerotic plaques characterization, while the contractility of the heart or skeletal muscles can be assessed with strain imaging. We developed radio frequency (RF) based ultrasound methods to assess the deformation at higher resolution and with higher accuracy than commercial methods using conventional image data (Tissue Doppler Imaging and 2D speckle tracking methods). However, the improvement in accuracy is mainly achieved when measuring strain along the ultrasound beam direction, so 1D. We further extended this method to multiple directions and further improved precision by using compounding of data acquired at multiple beam steered angles. In arteries, the presence of vulnerable plaques may lead to acute events like stroke and myocardial infarction. Consequently, timely detection of these plaques is of great diagnostic value. Non-invasive ultrasound strain compounding is currently being evaluated as a diagnostic tool to identify the vulnerability of plaques. In the heart, we determined the strain locally and at high resolution resulting in a local assessment in contrary to conventional global functional parameters like cardiac output or shortening fraction.

  15. [Modern methods of functional tomographic brain imaging for brain function reseaching in norm and pathology].

    PubMed

    Kireev, M V; Zakhs, D V; Korotkov, A D; Medvedev, S V

    2013-01-01

    For many years the modern methods of functional tomographic brain imaging (fMRI and PET) were actively used not only for the research of basic brain functions, but also in clinical practice. In present paper we described the basic characteristics of the signal registered with fMRI and PET, the principles of image reconstruction, as well as the methodological requirements, which are necessary to obtain reliable results. The advantages and limitations of modem tomographic methods of the brain functions investigation are discussed. The need of the complex approach use in brain study is emphasized and methods for the study of functional integration of the brain are suggested.

  16. TOPICAL REVIEW: Multimodality imaging of structure and function

    NASA Astrophysics Data System (ADS)

    Townsend, D. W.

    2008-02-01

    Historically, medical devices to image either anatomical structure or functional processes have developed along somewhat independent paths. The recognition that combining images from different modalities can nevertheless offer significant diagnostic advantages gave rise to sophisticated software techniques to coregister structure and function. Recently, alternatives to retrospective software-based fusion have become available through instrumentation that combines two imaging modalities within a single device, an approach that has since been termed hardware fusion. As a result, following their recent introduction into the clinic, combined PET/CT and SPECT/CT devices are now playing an increasingly important role in the diagnosis and staging of human disease. Recently, although limited to the brain, the first clinical MR scanner with a PET insert, a technically-challenging design, has been undergoing evaluation. This review will follow the development of multimodality instrumentation for clinical use from conception to present-day technology and assess the status and future potential for such devices.

  17. Functional magnetic resonance imaging in oncology: state of the art.

    PubMed

    Guimaraes, Marcos Duarte; Schuch, Alice; Hochhegger, Bruno; Gross, Jefferson Luiz; Chojniak, Rubens; Marchiori, Edson

    2014-01-01

    In the investigation of tumors with conventional magnetic resonance imaging, both quantitative characteristics, such as size, edema, necrosis, and presence of metastases, and qualitative characteristics, such as contrast enhancement degree, are taken into consideration. However, changes in cell metabolism and tissue physiology which precede morphological changes cannot be detected by the conventional technique. The development of new magnetic resonance imaging techniques has enabled the functional assessment of the structures in order to obtain information on the different physiological processes of the tumor microenvironment, such as oxygenation levels, cellularity and vascularity. The detailed morphological study in association with the new functional imaging techniques allows for an appropriate approach to cancer patients, including the phases of diagnosis, staging, response evaluation and follow-up, with a positive impact on their quality of life and survival rate.

  18. The role of susceptibility weighted imaging in functional MRI.

    PubMed

    Haacke, E Mark; Ye, Yongquan

    2012-08-15

    The development of functional brain magnetic resonance imaging (fMRI) has been a boon for neuroscientists and radiologists alike. It provides for fundamental information on brain function and better diagnostic tools to study disease. In this paper, we will review some of the early concepts in high resolution gradient echo imaging with a particular emphasis on susceptibility weighted imaging (SWI) and MR angiography (MRA). We begin with the history of our own experience in this area, followed by a discussion of the role of high resolution in studying the vasculature of the brain and how this relates to the BOLD (blood oxygenation level dependent) signal. We introduce the role of SWI and susceptibility mapping (SWIM) in fMRI and close with recommendations for future high resolution experiments.

  19. Functional magnetic resonance imaging in oncology: state of the art*

    PubMed Central

    Guimaraes, Marcos Duarte; Schuch, Alice; Hochhegger, Bruno; Gross, Jefferson Luiz; Chojniak, Rubens; Marchiori, Edson

    2014-01-01

    In the investigation of tumors with conventional magnetic resonance imaging, both quantitative characteristics, such as size, edema, necrosis, and presence of metastases, and qualitative characteristics, such as contrast enhancement degree, are taken into consideration. However, changes in cell metabolism and tissue physiology which precede morphological changes cannot be detected by the conventional technique. The development of new magnetic resonance imaging techniques has enabled the functional assessment of the structures in order to obtain information on the different physiological processes of the tumor microenvironment, such as oxygenation levels, cellularity and vascularity. The detailed morphological study in association with the new functional imaging techniques allows for an appropriate approach to cancer patients, including the phases of diagnosis, staging, response evaluation and follow-up, with a positive impact on their quality of life and survival rate. PMID:25741058

  20. Functional Connectivity Magnetic Resonance Imaging Classification of Autism

    ERIC Educational Resources Information Center

    Anderson, Jeffrey S.; Nielsen, Jared A.; Froehlich, Alyson L.; DuBray, Molly B.; Druzgal, T. Jason; Cariello, Annahir N.; Cooperrider, Jason R.; Zielinski, Brandon A.; Ravichandran, Caitlin; Fletcher, P. Thomas; Alexander, Andrew L.; Bigler, Erin D.; Lange, Nicholas; Lainhart, Janet E.

    2011-01-01

    Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear…

  1. [Functional imaging of pain: from the somatic response to emotions].

    PubMed

    Laurent, Bernard

    2013-01-01

    Functional brain imaging in subjects experiencing pain (real, observed or imagined) has led to considerable progress in our understanding of the role of the brain andpsyche in pain integration and control, as well as some forms of somatoform pain with no anatomical basis. This research is challenging not only the dichotomy between the soma and psyche, but also the concept of psychosomatic pain.

  2. Recent Advances in Morphological Cell Image Analysis

    PubMed Central

    Chen, Shengyong; Zhao, Mingzhu; Wu, Guang; Yao, Chunyan; Zhang, Jianwei

    2012-01-01

    This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed. PMID:22272215

  3. Processing Cones: A Computational Structure for Image Analysis.

    DTIC Science & Technology

    1981-12-01

    image analysis applications, referred to as a processing cone, is described and sample algorithms are presented. A fundamental characteristic of the structure is its hierarchical organization into two-dimensional arrays of decreasing resolution. In this architecture, a protypical function is defined on a local window of data and applied uniformly to all windows in a parallel manner. Three basic modes of processing are supported in the cone: reduction operations (upward processing), horizontal operations (processing at a single level) and projection operations (downward

  4. Intrinsic signal imaging of brain function using a small implantable CMOS imaging device

    NASA Astrophysics Data System (ADS)

    Haruta, Makito; Sunaga, Yoshinori; Yamaguchi, Takahiro; Takehara, Hironari; Noda, Toshihiko; Sasagawa, Kiyotaka; Tokuda, Takashi; Ohta, Jun

    2015-04-01

    A brain functional imaging technique over a long period is important to understand brain functions related to animal behavior. We have developed a small implantable CMOS imaging device for measuring brain activity in freely moving animals. This device is composed of a CMOS image sensor chip and LEDs for illumination. In this study, we demonstrated intrinsic signal imaging of blood flow using the device with a green LED light source at a peak wavelength of 535 nm, which corresponds to one of the absorption spectral peaks of blood cells. Brain activity increases regional blood flow. The device light weight of about 0.02 g makes it possible to stably measure brain activity through blood flow over a long period. The device has successfully measured the intrinsic signal related to sensory stimulation on the primary somatosensory cortex.

  5. Evidential Reasoning in Expert Systems for Image Analysis.

    DTIC Science & Technology

    1985-02-01

    techniques to image analysis (IA). There is growing evidence that these techniques offer significant improvements in image analysis , particularly in the...2) to provide a common framework for analysis, (3) to structure the ER process for major expert-system tasks in image analysis , and (4) to identify...approaches to three important tasks for expert systems in the domain of image analysis . This segment concluded with an assessment of the strengths

  6. Mapping Variation in Vegetation Functioning with Imaging Spectroscopy

    NASA Astrophysics Data System (ADS)

    Townsend, P. A.; Couture, J. J.; Kruger, E. L.; Serbin, S.; Singh, A.

    2015-12-01

    Imaging spectroscopy (otherwise known as hyperspectral remote sensing) offers the potential to characterize the spatial and temporal variation in biophysical and biochemical properties of vegetation that can be costly or logistically difficult to measure comprehensively using traditional methods. A number of recent studies have illustrated the capacity for imaging spectroscopy data, such as from NASA's AVIRIS sensor, to empirically estimate functional traits related to foliar chemistry and physiology (Singh et al. 2015, Serbin et al. 2015). Here, we present analyses that illustrate the implications of those studies to characterize within-field or -stand variability in ecosystem functioning. In agricultural ecosystems, within-field photosynthetic capacity can vary by 30-50%, likely due to within-field variations in water availability and soil fertility. In general, the variability of foliar traits is lower in forests than agriculture, but can still be significant. Finally, we demonstrate that functional trait variability at the stand scale is strongly related to vegetation diversity. These results have two significant implications: 1) reliance on a small number of field samples to broadly estimate functional traits likely underestimates variability in those traits, and 2) if trait estimations from imaging spectroscopy are reliable, such data offer the opportunity to greatly increase the density of measurements we can use to predict ecosystem function.

  7. Hippocampal shape analysis in Alzheimer's disease using functional data analysis.

    PubMed

    Epifanio, Irene; Ventura-Campos, Noelia

    2014-02-28

    The hippocampus is one of the first affected regions in Alzheimer's disease. The left hippocampi of control subjects, patients with mild cognitive impairment and patients with Alzheimer's disease are represented by spherical harmonics. Functional data analysis is used in the hippocampal shape analysis. Functional principal component analysis and functional independent component analysis are defined for multivariate functions with two arguments. A functional linear discriminant function is also defined. Comparisons with other approaches are carried out. Our functional approach gives promising results, especially in shape classification.

  8. Functional imaging and the central control of the bladder.

    PubMed

    Kavia, Rajesh Bharat Chhaganlal; Dasgupta, Ranan; Fowler, Clare Juliet

    2005-12-05

    The central control of the bladder is a complex, multilevel process. Recent advances in functional brain imaging have allowed research into this control in humans. This article reviews the functional imaging studies published to date and discusses the regions of the brain that have been implicated in the central control of continence. Brain regions that have been implicated include the pons (pontine micturition center, PMC), periaqueductal gray (PAG), thalamus, insula, anterior cingulate gyrus, and prefrontal cortices. The PMC and the PAG are thought to be key in the supraspinal control of continence and micturition. Higher centers such as the insula, anterior cingulate gyrus, and prefrontal regions are probably involved in the modulation of this control and cognition of bladder sensations, and in the case of the insula and anterior cingulate, modulation of autonomic function. Further work should aim to examine how the regions interact to achieve urinary continence.

  9. Human brain activity with functional NIR optical imager

    NASA Astrophysics Data System (ADS)

    Luo, Qingming

    2001-08-01

    In this paper we reviewed the applications of functional near infrared optical imager in human brain activity. Optical imaging results of brain activity, including memory for new association, emotional thinking, mental arithmetic, pattern recognition ' where's Waldo?, occipital cortex in visual stimulation, and motor cortex in finger tapping, are demonstrated. It is shown that the NIR optical method opens up new fields of study of the human population, in adults under conditions of simulated or real stress that may have important effects upon functional performance. It makes practical and affordable for large populations the complex technology of measuring brain function. It is portable and low cost. In cognitive tasks subjects could report orally. The temporal resolution could be millisecond or less in theory. NIR method will have good prospects in exploring human brain secret.

  10. BioImage Suite: An integrated medical image analysis suite: An update.

    PubMed

    Papademetris, Xenophon; Jackowski, Marcel P; Rajeevan, Nallakkandi; DiStasio, Marcello; Okuda, Hirohito; Constable, R Todd; Staib, Lawrence H

    2006-01-01

    BioImage Suite is an NIH-supported medical image analysis software suite developed at Yale. It leverages both the Visualization Toolkit (VTK) and the Insight Toolkit (ITK) and it includes many additional algorithms for image analysis especially in the areas of segmentation, registration, diffusion weighted image processing and fMRI analysis. BioImage Suite has a user-friendly user interface developed in the Tcl scripting language. A final beta version is freely available for download.

  11. Using image analysis and ArcGIS® to improve automatic grain boundary detection and quantify geological images

    NASA Astrophysics Data System (ADS)

    DeVasto, Michael A.; Czeck, Dyanna M.; Bhattacharyya, Prajukti

    2012-12-01

    Geological images, such as photos and photomicrographs of rocks, are commonly used as supportive evidence to indicate geological processes. A limiting factor to quantifying images is the digitization process; therefore, image analysis has remained largely qualitative. ArcGIS®, the most widely used Geographic Information System (GIS) available, is capable of an array of functions including building models capable of digitizing images. We expanded upon a previously designed model built using Arc ModelBuilder® to quantify photomicrographs and scanned images of thin sections. In order to enhance grain boundary detection, but limit computer processing and hard drive space, we utilized a preprocessing image analysis technique such that only a single image is used in the digitizing model. Preprocessing allows the model to accurately digitize grain boundaries with fewer images and requires less user intervention by using batch processing in image analysis software and ArcCatalog®. We present case studies for five basic textural analyses using a semi-automated digitized image and quantified in ArcMap®. Grain Size Distributions, Shape Preferred Orientations, Weak phase connections (networking), and Nearest Neighbor statistics are presented in a simplified fashion for further analyses directly obtainable from the automated digitizing method. Finally, we discuss the ramifications for incorporating this method into geological image analyses.

  12. Image analysis for measuring rod network properties

    NASA Astrophysics Data System (ADS)

    Kim, Dongjae; Choi, Jungkyu; Nam, Jaewook

    2015-12-01

    In recent years, metallic nanowires have been attracting significant attention as next-generation flexible transparent conductive films. The performance of films depends on the network structure created by nanowires. Gaining an understanding of their structure, such as connectivity, coverage, and alignment of nanowires, requires the knowledge of individual nanowires inside the microscopic images taken from the film. Although nanowires are flexible up to a certain extent, they are usually depicted as rigid rods in many analysis and computational studies. Herein, we propose a simple and straightforward algorithm based on the filtering in the frequency domain for detecting the rod-shape objects inside binary images. The proposed algorithm uses a specially designed filter in the frequency domain to detect image segments, namely, the connected components aligned in a certain direction. Those components are post-processed to be combined under a given merging rule in a single rod object. In this study, the microscopic properties of the rod networks relevant to the analysis of nanowire networks were measured for investigating the opto-electric performance of transparent conductive films and their alignment distribution, length distribution, and area fraction. To verify and find the optimum parameters for the proposed algorithm, numerical experiments were performed on synthetic images with predefined properties. By selecting proper parameters, the algorithm was used to investigate silver nanowire transparent conductive films fabricated by the dip coating method.

  13. Linear constraint minimum variance beamformer functional magnetic resonance inverse imaging.

    PubMed

    Lin, Fa-Hsuan; Witzel, Thomas; Zeffiro, Thomas A; Belliveau, John W

    2008-11-01

    Accurate estimation of the timing of neural activity is required to fully model the information flow among functionally specialized regions whose joint activity underlies perception, cognition and action. Attempts to detect the fine temporal structure of task-related activity would benefit from functional imaging methods allowing higher sampling rates. Spatial filtering techniques have been used in magnetoencephalography source imaging applications. In this work, we use the linear constraint minimal variance (LCMV) beamformer localization method to reconstruct single-shot volumetric functional magnetic resonance imaging (fMRI) data using signals acquired simultaneously from all channels of a high density radio-frequency (RF) coil array. The LCMV beamformer method generalizes the existing volumetric magnetic resonance inverse imaging (InI) technique, achieving higher detection sensitivity while maintaining whole-brain spatial coverage and 100 ms temporal resolution. In this paper, we begin by introducing the LCMV reconstruction formulation and then quantitatively assess its performance using both simulated and empirical data. To demonstrate the sensitivity and inter-subject reliability of volumetric LCMV InI, we employ an event-related design to probe the spatial and temporal properties of task-related hemodynamic signal modulations in primary visual cortex. Compared to minimum-norm estimate (MNE) reconstructions, LCMV offers better localization accuracy and superior detection sensitivity. Robust results from both single subject and group analyses demonstrate the excellent sensitivity and specificity of volumetric InI in detecting the spatial and temporal structure of task-related brain activity.

  14. Computerized image analysis of digitized infrared images of breasts from a scanning infrared imaging system

    NASA Astrophysics Data System (ADS)

    Head, Jonathan F.; Lipari, Charles A.; Elliot, Robert L.

    1998-10-01

    Infrared imaging of the breasts has been shown to be of value in risk assessment, detection, diagnosis and prognosis of breast cancer. However, infrared imaging has not been widely accepted for a variety of reasons, including the lack of standardization of the subjective visual analysis method. The subjective nature of the standard visual analysis makes it difficult to achieve equivalent results with different equipment and different interpreters of the infrared patterns of the breasts. Therefore, this study was undertaken to develop more objective analysis methods for infrared images of the breasts by creating objective semiquantitative and quantitative analysis of computer assisted image analysis determined mean temperatures of whole breasts and quadrants of the breasts. When using objective quantitative data on whole breasts (comparing differences in means of left and right breasts), semiquantitative data on quadrants of the breast (determining an index by summation of scores for each quadrant), or summation of quantitative data on quadrants of the breasts there was a decrease in the number of abnormal patterns (positives) in patients being screen for breast cancer and an increases in the number of abnormal patterns (true positives) in the breast cancer patients. It is hoped that the decrease in positives in women being screened for breast cancer will translate into a decrease in the false positives but larger numbers of women with longer follow-up will be needed to clarify this. Also a much larger group of breast cancer patients will need to be studied in order to see if there is a true increase in the percentage of breast cancer patients presenting with abnormal infrared images of the breast with these objective image analysis methods.

  15. Vibration signature analysis of AFM images

    SciTech Connect

    Joshi, G.A.; Fu, J.; Pandit, S.M.

    1995-12-31

    Vibration signature analysis has been commonly used for the machine condition monitoring and the control of errors. However, it has been rarely employed for the analysis of the precision instruments such as an atomic force microscope (AFM). In this work, an AFM was used to collect vibration data from a sample positioning stage under different suspension and support conditions. Certain structural characteristics of the sample positioning stage show up as a result of the vibration signature analysis of the surface height images measured using an AFM. It is important to understand these vibration characteristics in order to reduce vibrational uncertainty, improve the damping and structural design, and to eliminate the imaging imperfections. The choice of method applied for vibration analysis may affect the results. Two methods, the data dependent systems (DDS) analysis and the Welch`s periodogram averaging method were investigated for application to this problem. Both techniques provide smooth spectrum plots from the data. Welch`s periodogram provides a coarse resolution as limited by the number of samples and requires a choice of window to be decided subjectively by the user. The DDS analysis provides sharper spectral peaks at a much higher resolution and a much lower noise floor. A decomposition of the signal variance in terms of the frequencies is provided as well. The technique is based on an objective model adequacy criterion.

  16. Pain related inflammation analysis using infrared images

    NASA Astrophysics Data System (ADS)

    Bhowmik, Mrinal Kanti; Bardhan, Shawli; Das, Kakali; Bhattacharjee, Debotosh; Nath, Satyabrata

    2016-05-01

    Medical Infrared Thermography (MIT) offers a potential non-invasive, non-contact and radiation free imaging modality for assessment of abnormal inflammation having pain in the human body. The assessment of inflammation mainly depends on the emission of heat from the skin surface. Arthritis is a disease of joint damage that generates inflammation in one or more anatomical joints of the body. Osteoarthritis (OA) is the most frequent appearing form of arthritis, and rheumatoid arthritis (RA) is the most threatening form of them. In this study, the inflammatory analysis has been performed on the infrared images of patients suffering from RA and OA. For the analysis, a dataset of 30 bilateral knee thermograms has been captured from the patient of RA and OA by following a thermogram acquisition standard. The thermograms are pre-processed, and areas of interest are extracted for further processing. The investigation of the spread of inflammation is performed along with the statistical analysis of the pre-processed thermograms. The objectives of the study include: i) Generation of a novel thermogram acquisition standard for inflammatory pain disease ii) Analysis of the spread of the inflammation related to RA and OA using K-means clustering. iii) First and second order statistical analysis of pre-processed thermograms. The conclusion reflects that, in most of the cases, RA oriented inflammation affects bilateral knees whereas inflammation related to OA present in the unilateral knee. Also due to the spread of inflammation in OA, contralateral asymmetries are detected through the statistical analysis.

  17. Operant-contingency-based preparation of children for functional magnetic resonance imaging.

    PubMed Central

    Slifer, Keith J; Koontz, Kristine L; Cataldo, Michael F

    2002-01-01

    Functional magnetic resonance imaging (fMRI) is used to study brain function during behavioral tasks. The participation of pediatric subjects is problematic because reliable task performance and control of head movement are simultaneously required. Differential reinforcement decreased head motion and improved vigilance task performance in 4 children (2 with behavioral disorders) undergoing simulated fMRI scans. Results show that behavior analysis techniques can improve child cooperation during fMRI procedures. PMID:12102139

  18. Human conjunctival microvasculature assessed with a retinal function imager (RFI)

    PubMed Central

    Jiang, Hong; Ye, Yufeng; DeBuc, Delia Cabrera; Lam, Byron L; Rundek, Tatjana; Tao, Aizhu; Shao, Yilei; Wang, Jianhua

    2012-01-01

    The conjunctival and cerebral vasculatures share similar embryological origins, with similar structural and physiological characteristics. Tracking the conjunctival microvasculature may provide useful information for predicting the onset, progression and prognosis of both systemic and central nervous system (CNS) vascular diseases. The bulbar conjunctival vasculature was imaged using a retinal function imager (RFI, Optical Imaging Ltd, Rehovot, Israel). Hemoglobin in red blood cells was used as an intrinsic motion-contrast agent in the generation of detailed noninvasive capillary-perfusion maps (nCPMs) and the calculation of the blood flow velocity. Five healthy subjects were imaged under normal conditions and again under the stress condition of wearing a contact lens. The retina was also imaged in one eye of one subject for comparison. The nCPMs showed the conjunctival microvasculature in exquisite detail, which appeared as clear as the retinal nCPMs. The blood flow velocities in the temporal conjunctival microvasculature were 0.86 ± 0.08 (mean ± SD, mm/s) for the bare eye and 0.99 ± 0.11 mm/s with contact lens wear. It is feasible to use RFI for imaging the conjunctival vasculature. PMID:23084966

  19. Quantitative image analysis of celiac disease.

    PubMed

    Ciaccio, Edward J; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

    2015-03-07

    We outline the use of quantitative techniques that are currently used for analysis of celiac disease. Image processing techniques can be useful to statistically analyze the pixular data of endoscopic images that is acquired with standard or videocapsule endoscopy. It is shown how current techniques have evolved to become more useful for gastroenterologists who seek to understand celiac disease and to screen for it in suspected patients. New directions for focus in the development of methodology for diagnosis and treatment of this disease are suggested. It is evident that there are yet broad areas where there is potential to expand the use of quantitative techniques for improved analysis in suspected or known celiac disease patients.

  20. Semi-Huber potential function for image segmentation.

    PubMed

    Gutiérrez, Osvaldo; de la Rosa, Ismael; Villa, Jesús; González, Efrén; Escalante, Nivia

    2012-03-12

    In this work, a novel model of Markov Random Field (MRF) is introduced. Such a model is based on a proposed Semi-Huber potential function and it is applied successfully to image segmentation in presence of noise. The main difference with respect to other half-quadratic models that have been taken as a reference is, that the number of parameters to be tuned in the proposed model is smaller and simpler. The idea is then, to choose adequate parameter values heuristically for a good segmentation of the image. In that sense, some experimental results show that the proposed model allows an easier parameter adjustment with reasonable computation times.

  1. Photoacoustic Image Analysis for Cancer Detection and Building a Novel Ultrasound Imaging System

    NASA Astrophysics Data System (ADS)

    Sinha, Saugata

    Photoacoustic (PA) imaging is a rapidly emerging non-invasive soft tissue imaging modality which has the potential to detect tissue abnormality at early stage. Photoacoustic images map the spatially varying optical absorption property of tissue. In multiwavelength photoacoustic imaging, the soft tissue is imaged with different wavelengths, tuned to the absorption peaks of the specific light absorbing tissue constituents or chromophores to obtain images with different contrasts of the same tissue sample. From those images, spatially varying concentration of the chromophores can be recovered. As multiwavelength PA images can provide important physiological information related to function and molecular composition of the tissue, so they can be used for diagnosis of cancer lesions and differentiation of malignant tumors from benign tumors. In this research, a number of parameters have been extracted from multiwavelength 3D PA images of freshly excised human prostate and thyroid specimens, imaged at five different wavelengths. Using marked histology slides as ground truths, region of interests (ROI) corresponding to cancer, benign and normal regions have been identified in the PA images. The extracted parameters belong to different categories namely chromophore concentration, frequency parameters and PA image pixels and they represent different physiological and optical properties of the tissue specimens. Statistical analysis has been performed to test whether the extracted parameters are significantly different between cancer, benign and normal regions. A multidimensional [29 dimensional] feature set, built with the extracted parameters from the 3D PA images, has been divided randomly into training and testing sets. The training set has been used to train support vector machine (SVM) and neural network (NN) classifiers while the performance of the classifiers in differentiating different tissue pathologies have been determined by the testing dataset. Using the NN

  2. Quantitative Analysis Tools and Digital Phantoms for Deformable Image Registration Quality Assurance.

    PubMed

    Kim, Haksoo; Park, Samuel B; Monroe, James I; Traughber, Bryan J; Zheng, Yiran; Lo, Simon S; Yao, Min; Mansur, David; Ellis, Rodney; Machtay, Mitchell; Sohn, Jason W

    2015-08-01

    This article proposes quantitative analysis tools and digital phantoms to quantify intrinsic errors of deformable image registration (DIR) systems and establish quality assurance (QA) procedures for clinical use of DIR systems utilizing local and global error analysis methods with clinically realistic digital image phantoms. Landmark-based image registration verifications are suitable only for images with significant feature points. To address this shortfall, we adapted a deformation vector field (DVF) comparison approach with new analysis techniques to quantify the results. Digital image phantoms are derived from data sets of actual patient images (a reference image set, R, a test image set, T). Image sets from the same patient taken at different times are registered with deformable methods producing a reference DVFref. Applying DVFref to the original reference image deforms T into a new image R'. The data set, R', T, and DVFref, is from a realistic truth set and therefore can be used to analyze any DIR system and expose intrinsic errors by comparing DVFref and DVFtest. For quantitative error analysis, calculating and delineating differences between DVFs, 2 methods were used, (1) a local error analysis tool that displays deformation error magnitudes with color mapping on each image slice and (2) a global error analysis tool that calculates a deformation error histogram, which describes a cumulative probability function of errors for each anatomical structure. Three digital image phantoms were generated from three patients with a head and neck, a lung and a liver cancer. The DIR QA was evaluated using the case with head and neck.

  3. Global Methods for Image Motion Analysis

    DTIC Science & Technology

    1992-10-01

    including the time for reviewing instructions , searching existing data sources, gathering and maintaining the data needed, and completing and reviewing...thanks go to Pankaj who inspired me in research , to Prasad from whom I have learned so much, and to Ronie and Laureen, the memories of whose company...of images to determine egomotion and to extract information from the scene. Research in motion analysis has been focussed on the problems of

  4. Optical coherence tomography imaging based on non-harmonic analysis

    NASA Astrophysics Data System (ADS)

    Cao, Xu; Hirobayashi, Shigeki; Chong, Changho; Morosawa, Atsushi; Totsuka, Koki; Suzuki, Takuya

    2009-11-01

    A new processing technique called Non-Harmonic Analysis (NHA) is proposed for OCT imaging. Conventional Fourier-Domain OCT relies on the FFT calculation which depends on the window function and length. Axial resolution is counter proportional to the frame length of FFT that is limited by the swept range of the swept source in SS-OCT, or the pixel counts of CCD in SD-OCT degraded in FD-OCT. However, NHA process is intrinsically free from this trade-offs; NHA can resolve high frequency without being influenced by window function or frame length of sampled data. In this study, NHA process is explained and applied to OCT imaging and compared with OCT images based on FFT. In order to validate the benefit of NHA in OCT, we carried out OCT imaging based on NHA with the three different sample of onion-skin,human-skin and pig-eye. The results show that NHA process can realize practical image resolution that is equivalent to 100nm swept range only with less than half-reduced wavelength range.

  5. Vectorial point spread function and optical transfer function in oblique plane imaging.

    PubMed

    Kim, Jeongmin; Li, Tongcang; Wang, Yuan; Zhang, Xiang

    2014-05-05

    Oblique plane imaging, using remote focusing with a tilted mirror, enables direct two-dimensional (2D) imaging of any inclined plane of interest in three-dimensional (3D) specimens. It can image real-time dynamics of a living sample that changes rapidly or evolves its structure along arbitrary orientations. It also allows direct observations of any tilted target plane in an object of which orientational information is inaccessible during sample preparation. In this work, we study the optical resolution of this innovative wide-field imaging method. Using the vectorial diffraction theory, we formulate the vectorial point spread function (PSF) of direct oblique plane imaging. The anisotropic lateral resolving power caused by light clipping from the tilted mirror is theoretically analyzed for all oblique angles. We show that the 2D PSF in oblique plane imaging is conceptually different from the inclined 2D slice of the 3D PSF in conventional lateral imaging. Vectorial optical transfer function (OTF) of oblique plane imaging is also calculated by the fast Fourier transform (FFT) method to study effects of oblique angles on frequency responses.

  6. Resting-state functional MR imaging shed insights into the brain of diabetes.

    PubMed

    Wang, Yun Fei; Ji, Xue Man; Lu, Guang Ming; Zhang, Long Jiang

    2016-10-01

    Diabetes mellitus is a common metabolic disease which is associated with increasing risk for multiple cognitive declines. Alterations in brain functional connectivity are believed to be the mechanisms underlying the cognitive function impairments. During the past decade, resting-state functional magnetic resonance imaging (rs-fMRI) has been developed as a major tool to study brain functional connectivity in vivo. This paper briefly reviews the diabetes-associated cognitive impairment, analysis algorithms and clinical applications of rs-fMRI. We also provide future perspectives of rs-fMRI in diabetes.

  7. Functional imaging of the lungs with gas agents.

    PubMed

    Kruger, Stanley J; Nagle, Scott K; Couch, Marcus J; Ohno, Yoshiharu; Albert, Mitchell; Fain, Sean B

    2016-02-01

    This review focuses on the state-of-the-art of the three major classes of gas contrast agents used in magnetic resonance imaging (MRI)-hyperpolarized (HP) gas, molecular oxygen, and fluorinated gas--and their application to clinical pulmonary research. During the past several years there has been accelerated development of pulmonary MRI. This has been driven in part by concerns regarding ionizing radiation using multidetector computed tomography (CT). However, MRI also offers capabilities for fast multispectral and functional imaging using gas agents that are not technically feasible with CT. Recent improvements in gradient performance and radial acquisition methods using ultrashort echo time (UTE) have contributed to advances in these functional pulmonary MRI techniques. The relative strengths and weaknesses of the main functional imaging methods and gas agents are compared and applications to measures of ventilation, diffusion, and gas exchange are presented. Functional lung MRI methods using these gas agents are improving our understanding of a wide range of chronic lung diseases, including chronic obstructive pulmonary disease, asthma, and cystic fibrosis in both adults and children.

  8. Imaging systems based on the encoding of optical coherence functions.

    PubMed

    James, J Christopher; Bennett, Gisele Welch; Rhodes, William T

    2005-09-01

    An imaging scheme is described that is based on the transmission of image-forming information encoded within optical coherence functions. The scheme makes use of dynamic random-valued encoding-decoding masks placed in the input-output planes of any linear optical system. The mask transmittance functions are complex conjugates of each other, as opposed to a similar coherence encoding scheme proposed earlier by two of this paper's authors that used identical masks. [Rhodes and Welch, in Euro-American Workshop on Optoelectronic Information Processing, SPIE Critical Review Series (SPIE, 1999), Vol. CR74, p. 1]. General analyses of the two coherence encoding schemes are performed by using the more general mutual coherence function as opposed to the mutual intensity function used in the earlier scheme. The capabilities and limitations of both encoding schemes are discussed by using simple examples that combine the encoding-decoding masks with free-space propagation, passage through a four-f system, and a single-lens imaging system.

  9. Functional Imaging of Chemically Active Surfaces with Optical Reporter Microbeads

    PubMed Central

    Ahuja, Punkaj; Nair, Sumitha; Narayan, Sreenath; Gratzl, Miklós

    2015-01-01

    We have developed a novel approach to allow for continuous imaging of concentration fields that evolve at surfaces due to release, uptake, and mass transport of molecules, without significant interference of the concentration fields by the chemical imaging itself. The technique utilizes optical “reporter” microbeads immobilized in a thin layer of transparent and inert hydrogel on top of the surface. The hydrogel has minimal density and therefore diffusion in and across it is like in water. Imaging the immobilized microbeads over time provides quantitative concentration measurements at each location where an optical reporter resides. Using image analysis in post-processing these spatially discrete measurements can be transformed into contiguous maps of the dynamic concentration field across the entire surface. If the microbeads are small enough relative to the dimensions of the region of interest and sparsely applied then chemical imaging will not noticeably affect the evolution of concentration fields. In this work colorimetric optode microbeads a few micrometers in diameter were used to image surface concentration distributions on the millimeter scale. PMID:26332766

  10. Tomographic spectral imaging: analysis of localized corrosion.

    SciTech Connect

    Michael, Joseph Richard; Kotula, Paul Gabriel; Keenan, Michael Robert

    2005-02-01

    Microanalysis is typically performed to analyze the near surface of materials. There are many instances where chemical information about the third spatial dimension is essential to the solution of materials analyses. The majority of 3D analyses however focus on limited spectral acquisition and/or analysis. For truly comprehensive 3D chemical characterization, 4D spectral images (a complete spectrum from each volume element of a region of a specimen) are needed. Furthermore, a robust statistical method is needed to extract the maximum amount of chemical information from that extremely large amount of data. In this paper, an example of the acquisition and multivariate statistical analysis of 4D (3-spatial and 1-spectral dimension) x-ray spectral images is described. The method of utilizing a single- or dual-beam FIB (w/o or w/SEM) to get at 3D chemistry has been described by others with respect to secondary-ion mass spectrometry. The basic methodology described in those works has been modified for comprehensive x-ray microanalysis in a dual-beam FIB/SEM (FEI Co. DB-235). In brief, the FIB is used to serially section a site-specific region of a sample and then the electron beam is rastered over the exposed surfaces with x-ray spectral images being acquired at each section. All this is performed without rotating or tilting the specimen between FIB cutting and SEM imaging/x-ray spectral image acquisition. The resultant 4D spectral image is then unfolded (number of volume elements by number of channels) and subjected to the same multivariate curve resolution (MCR) approach that has proven successful for the analysis of lower-dimension x-ray spectral images. The TSI data sets can be in excess of 4Gbytes. This problem has been overcome (for now) and images up to 6Gbytes have been analyzed in this work. The method for analyzing such large spectral images will be described in this presentation. A comprehensive 3D chemical analysis was performed on several corrosion specimens

  11. Multispectral imaging fluorescence microscopy for lymphoid tissue analysis

    NASA Astrophysics Data System (ADS)

    Monici, Monica; Agati, Giovanni; Fusi, Franco; Mazzinghi, Piero; Romano, Salvatore; Pratesi, Riccardo; Alterini, Renato; Bernabei, Pietro A.; Rigacci, Luigi

    1999-01-01

    Multispectral imaging autofluorescence microscopy (MIAM) is used here for the analysis of lymphatic tissues. Lymph node biopsies, from patients with lympthoadenopathy of different origin have been examined. Natural fluorescence (NF) images of 3 micrometers sections were obtained using three filters peaked at 450, 550 and 680 nm with 50 nm bandpass. Monochrome images were combined together in a single RGB image. NF images of lymph node tissue sections show intense blue-green fluorescence of the connective stroma. Normal tissue shows follicles with faintly fluorescent lymphocytes, as expected fro the morphologic and functional characteristics of these cells. Other more fluorescent cells (e.g., plasma cells and macrophages) are evidenced. Intense green fluorescence if localized in the inner wall of the vessels. Tissues coming from patients affected by Hodgkin's lymphoma show spread fluorescence due to connective infiltration and no evidence of follicle organization. Brightly fluorescent large cells, presumably Hodgkin cells, are also observed. These results indicate that MIAM can discriminate between normal and pathological tissues on the basis of their natural fluorescence pattern, and, therefore, represent a potentially useful technique for diagnostic applications. Analysis of the fluorescence spectra of both normal and malignant lymphoid tissues resulted much less discriminatory than MIAM.

  12. Image analysis applied to luminescence microscopy

    NASA Astrophysics Data System (ADS)

    Maire, Eric; Lelievre-Berna, Eddy; Fafeur, Veronique; Vandenbunder, Bernard

    1998-04-01

    We have developed a novel approach to study luminescent light emission during migration of living cells by low-light imaging techniques. The equipment consists in an anti-vibration table with a hole for a direct output under the frame of an inverted microscope. The image is directly captured by an ultra low- light level photon-counting camera equipped with an image intensifier coupled by an optical fiber to a CCD sensor. This installation is dedicated to measure in a dynamic manner the effect of SF/HGF (Scatter Factor/Hepatocyte Growth Factor) both on activation of gene promoter elements and on cell motility. Epithelial cells were stably transfected with promoter elements containing Ets transcription factor-binding sites driving a luciferase reporter gene. Luminescent light emitted by individual cells was measured by image analysis. Images of luminescent spots were acquired with a high aperture objective and time exposure of 10 - 30 min in photon-counting mode. The sensitivity of the camera was adjusted to a high value which required the use of a segmentation algorithm dedicated to eliminate the background noise. Hence, image segmentation and treatments by mathematical morphology were particularly indicated in these experimental conditions. In order to estimate the orientation of cells during their migration, we used a dedicated skeleton algorithm applied to the oblong spots of variable intensities emitted by the cells. Kinetic changes of luminescent sources, distance and speed of migration were recorded and then correlated with cellular morphological changes for each spot. Our results highlight the usefulness of the mathematical morphology to quantify kinetic changes in luminescence microscopy.

  13. Use of imaging to assess normal and adaptive muscle function.

    PubMed

    Segal, Richard L

    2007-06-01

    Physical therapists must be able to determine the activity and passive properties of the musculoskeletal system in order to accurately plan and evaluate therapeutic measures. Discussed in this article are imaging methods that not only allow for the measurement of muscle activity but also allow for the measurement of cellular processes and passive mechanical properties noninvasively and in vivo. The techniques reviewed are T1- and T2-weighted magnetic resonance (MR) imaging, MR spectroscopy, cine-phase-contrast MR imaging, MR elastography, and ultrasonography. At present, many of these approaches are expensive and not readily available in physical therapy clinics but can be found at medical centers. However, there are ways of using these techniques to provide important knowledge about muscle function. This article proposes creative ways in which to use these techniques as evaluative tools.

  14. Structural Image Analysis of the Brain in Neuropsychology Using Magnetic Resonance Imaging (MRI) Techniques.

    PubMed

    Bigler, Erin D

    2015-09-01

    Magnetic resonance imaging (MRI) of the brain provides exceptional image quality for visualization and neuroanatomical classification of brain structure. A variety of image analysis techniques provide both qualitative as well as quantitative methods to relate brain structure with neuropsychological outcome and are reviewed herein. Of particular importance are more automated methods that permit analysis of a broad spectrum of anatomical measures including volume, thickness and shape. The challenge for neuropsychology is which metric to use, for which disorder and the timing of when image analysis methods are applied to assess brain structure and pathology. A basic overview is provided as to the anatomical and pathoanatomical relations of different MRI sequences in assessing normal and abnormal findings. Some interpretive guidelines are offered including factors related to similarity and symmetry of typical brain development along with size-normalcy features of brain anatomy related to function. The review concludes with a detailed example of various quantitative techniques applied to analyzing brain structure for neuropsychological outcome studies in traumatic brain injury.

  15. How to Perform and Interpret Functional Magnetic Resonance Imaging Studies in Functional Gastrointestinal Disorders

    PubMed Central

    Lee, In-Seon; Preissl, Hubert; Enck, Paul

    2017-01-01

    Functional neuroimaging studies have revealed the importance of the role of cognitive and psychological factors and the dysregulation of the brain-gut axis in functional gastrointestinal disorder patients. Although only a small number of neuroimaging studies have been conducted in functional gastrointestinal disorder patients, and despite the fact that the neuroimaging technique requires a high level of knowledge, the technique still has a great deal of potential. The application of functional magnetic resonance imaging (fMRI) technique in functional gastrointestinal disorders should provide novel methods of diagnosing and treating patients. In this review, basic knowledge and technical/practical issues of fMRI will be introduced to clinicians. PMID:28256119

  16. MR imaging and osteoporosis: fractal lacunarity analysis of trabecular bone.

    PubMed

    Zaia, Annamaria; Eleonori, Roberta; Maponi, Pierluigi; Rossi, Roberto; Murri, Roberto

    2006-07-01

    We develop a method of magnetic resonance (MR) image analysis able to provide parameter(s) sensitive to bone microarchitecture changes in aging, and to osteoporosis onset and progression. The method has been built taking into account fractal properties of many anatomic and physiologic structures. Fractal lacunarity analysis has been used to determine relevant parameter(s) to differentiate among three types of trabecular bone structure (healthy young, healthy perimenopausal, and osteoporotic patients) from lumbar vertebra MR images. In particular, we propose to approximate the lacunarity function by a hyperbola model function that depends on three coefficients, alpha, beta, and gamma, and to compute these coefficients as the solution of a least squares problem. This triplet of coefficients provides a model function that better represents the variation of mass density of pixels in the image considered. Clinical application of this preliminary version of our method suggests that one of the three coefficients, beta, may represent a standard for the evaluation of trabecular bone architecture and a potentially useful parametric index for the early diagnosis of osteoporosis.

  17. [Functional imaging of deep brain stimulation in idiopathic Parkinson's disease].

    PubMed

    Hilker, R

    2010-10-01

    Functional brain imaging allows the effects of deep brain stimulation (DBS) on the living human brain to be investigated. In patients with advanced Parkinson's disease (PD), positron emission tomography (PET) studies were undertaken at rest as well as under motor, cognitive or behavioral activation. DBS leads to a reduction of abnormal PD-related network activity in the motor system, which partly correlates with the improvement of motor symptoms. The local increase of energy consumption within the direct target area suggests a predominant excitatory influence of the stimulation current on neuronal tissue. Remote effects of DBS of the subthalamic nucleus (STN) on frontal association cortices indicate an interference of stimulation energy with associative and limbic basal ganglia loops. Taken together, functional brain imaging provides very valuable data for advancement of the DBS technique in PD therapy.

  18. Functionalized Gold Nanorods for Tumor Imaging and Targeted Therapy

    PubMed Central

    Gui, Chen; Cui, Da-xiang

    2012-01-01

    Gold nanorods, as an emerging noble metal nanomaterial with unique properties, have become the new exciting focus of theoretical and experimental studies in the past few years. The structure and function of gold nanorods, especially their biocompatibility, optical property, and photothermal effects, have been attracting more and more attention. Gold nanorods exhibit great potential in applications such as tumor molecular imaging and photothermal therapy. In this article, we review some of the main advances made over the past few years in the application of gold nanorods in surface functionalization, molecular imaging, and photothermal therapy. We also explore other prospective applications and discuss the corresponding concepts, issues, approaches, and challenges, with the aim of stimulating broader interest in gold nanorod-based nanotechnology and improving its practical application. PMID:23691482

  19. Hyperspectral imaging technology for pharmaceutical analysis

    NASA Astrophysics Data System (ADS)

    Hamilton, Sara J.; Lodder, Robert A.

    2002-06-01

    The sensitivity and spatial resolution of hyperspectral imaging instruments are tested in this paper using pharmaceutical applications. The first experiment tested the hypothesis that a near-IR tunable diode-based remote sensing system is capable of monitoring degradation of hard gelatin capsules at a relatively long distance. Spectra from the capsules were used to differentiate among capsules exposed to an atmosphere containing imaging spectrometry of tablets permits the identification and composition of multiple individual tables to be determined simultaneously. A near-IR camera was used to collect thousands of spectra simultaneously from a field of blister-packaged tablets. The number of tablets that a typical near-IR camera can currently analyze simultaneously form a field of blister- packaged tablets. The number of tablets that a typical near- IR camera can currently analyze simultaneously was estimated to be approximately 1300. The bootstrap error-adjusted single-sample technique chemometric-imaging algorithm was used to draw probability-density contour plots that revealed tablet composition. The single-capsule analysis provides an indication of how far apart the sample and instrumentation can be and still maintain adequate S/N, while the multiple- sample imaging experiment gives an indication of how many samples can be analyzed simultaneously while maintaining an adequate S/N and pixel coverage on each sample.

  20. Image analysis of Renaissance copperplate prints

    NASA Astrophysics Data System (ADS)

    Hedges, S. Blair

    2008-02-01

    From the fifteenth to the nineteenth centuries, prints were a common form of visual communication, analogous to photographs. Copperplate prints have many finely engraved black lines which were used to create the illusion of continuous tone. Line densities generally are 100-2000 lines per square centimeter and a print can contain more than a million total engraved lines 20-300 micrometers in width. Because hundreds to thousands of prints were made from a single copperplate over decades, variation among prints can have historical value. The largest variation is plate-related, which is the thinning of lines over successive editions as a result of plate polishing to remove time-accumulated corrosion. Thinning can be quantified with image analysis and used to date undated prints and books containing prints. Print-related variation, such as over-inking of the print, is a smaller but significant source. Image-related variation can introduce bias if images were differentially illuminated or not in focus, but improved imaging technology can limit this variation. The Print Index, the percentage of an area composed of lines, is proposed as a primary measure of variation. Statistical methods also are proposed for comparing and identifying prints in the context of a print database.

  1. [Cap image--a new kind of computer-assisted video image analysis system for dynamic capillary microscopy].

    PubMed

    Klyscz, T; Jünger, M; Jung, F; Zeintl, H

    1997-06-01

    We describe a newly developed multi-function video image analysis system for the computer-aided evaluation of capillaroscopic findings in microcirculation research. The Cap image analysis system comprises an IBM-compatible PC with a Matrox image processing card and real-time video tape digitalization. The video recorder is driven by a personal computer to which it is connected via an RS-232 interface. In contrast to currently available systems, the program presented here makes it possible to select any of several integrated image analysis functions, depending on the quality of the video image. Some examples of the analysis functions available are measurements of erythrocyte flow velocity using the line shift diagram method, the spatial correlation method, and the auto flying spot method. The standard features of the new program include a number of special functions and automatic movement correction. The system thus makes it possible not only to measure numerous morphological parameters such as capillary diameter, length, torquation index and capillary density, but also to perform video densitometric analysis, for example using fluorescent dyes.

  2. Teacher Praise: A Functional Analysis.

    ERIC Educational Resources Information Center

    Brophy, Jere

    1981-01-01

    Teacher praise typically does not function as a reinforcer. Rather, it is reactive to and under the control of student behavior. Its effects must be understood using concepts from attribution and social learning/reinforcement theories. (Author/GK)

  3. Markov Random Fields, Stochastic Quantization and Image Analysis

    DTIC Science & Technology

    1990-01-01

    Markov random fields based on the lattice Z2 have been extensively used in image analysis in a Bayesian framework as a-priori models for the...of Image Analysis can be given some fundamental justification then there is a remarkable connection between Probabilistic Image Analysis , Statistical Mechanics and Lattice-based Euclidean Quantum Field Theory.

  4. Functional Techniques for Data Analysis

    NASA Technical Reports Server (NTRS)

    Tomlinson, John R.

    1997-01-01

    This dissertation develops a new general method of solving Prony's problem. Two special cases of this new method have been developed previously. They are the Matrix Pencil and the Osculatory Interpolation. The dissertation shows that they are instances of a more general solution type which allows a wide ranging class of linear functional to be used in the solution of the problem. This class provides a continuum of functionals which provide new methods that can be used to solve Prony's problem.

  5. Nursing image: an evolutionary concept analysis.

    PubMed

    Rezaei-Adaryani, Morteza; Salsali, Mahvash; Mohammadi, Eesa

    2012-12-01

    A long-term challenge to the nursing profession is the concept of image. In this study, we used the Rodgers' evolutionary concept analysis approach to analyze the concept of nursing image (NI). The aim of this concept analysis was to clarify the attributes, antecedents, consequences, and implications associated with the concept. We performed an integrative internet-based literature review to retrieve English literature published from 1980-2011. Findings showed that NI is a multidimensional, all-inclusive, paradoxical, dynamic, and complex concept. The media, invisibility, clothing style, nurses' behaviors, gender issues, and professional organizations are the most important antecedents of the concept. We found that NI is pivotal in staff recruitment and nursing shortage, resource allocation to nursing, nurses' job performance, workload, burnout and job dissatisfaction, violence against nurses, public trust, and salaries available to nurses. An in-depth understanding of the NI concept would assist nurses to eliminate negative stereotypes and build a more professional image for the nurse and the profession.

  6. Colour atlas of first pass functional imaging of the heart

    SciTech Connect

    Schad, N.; Andrews, E.J.; Fleming, J.W.

    1985-01-01

    This book contains 21 chapters. Some of the titles are: Functional imaging; Fist pass radionuclide studies in evaluation of mitral valve replacement in chronic insufficiency using Bjork-Shiley tilting disc valves; First pass radionuclide studies in evaluation of left and right ventricular function in patients with bioprosthetic mitral valve replacement after 9-11 years; and First pass radionuclide studies in the evaluation of long term (up to about 15 years) follow up of aortic valve replacement using Starr-Edwards ball prosthesis.

  7. Functional magnetic resonance imaging of the brain: a quick review.

    PubMed

    Vaghela, Viratsinh; Kesavadas, Chandrasekharan; Thomas, Bejoy

    2010-01-01

    Ability to non-invasively map the hemodynamic changes occurring focally in areas of brain involved in various motor, sensory and cognitive functions by functional magnetic resonance imaging (fMRI) has revolutionized research in neuroscience in the last two decades. This technique has already gained clinical use especially in pre-surgical evaluation of epilepsy and neurosurgical planning of resection of mass lesions adjacent to eloquent cortex. In this review we attempt to illustrate basic principles and techniques of fMRI, its applications, practical points to consider while performing and evaluating clinical fMRI and its limitations.

  8. Analysis on enhanced depth of field for integral imaging microscope.

    PubMed

    Lim, Young-Tae; Park, Jae-Hyeung; Kwon, Ki-Chul; Kim, Nam

    2012-10-08

    Depth of field of the integral imaging microscope is studied. In the integral imaging microscope, 3-D information is encoded as a form of elemental images Distance between intermediate plane and object point decides the number of elemental image and depth of field of integral imaging microscope. From the analysis, it is found that depth of field of the reconstructed depth plane image by computational integral imaging reconstruction is longer than depth of field of optical microscope. From analyzed relationship, experiment using integral imaging microscopy and conventional microscopy is also performed to confirm enhanced depth of field of integral imaging microscopy.

  9. Resting-state functional MR imaging: a new window to the brain.

    PubMed

    Barkhof, Frederik; Haller, Sven; Rombouts, Serge A R B

    2014-07-01

    Resting-state (RS) functional magnetic resonance (MR) imaging constitutes a novel paradigm that examines spontaneous brain function by using blood oxygen level-dependent contrast in the absence of a task. Spatially distributed networks of temporal synchronization can be detected that can characterize RS networks (RSNs). With a short acquisition time of less than 10 minutes, RS functional MR imaging can be applied in special populations such as children and patients with dementia. Some RSNs are already present in utero, while others mature in childhood. Around 10 major RSNs are consistently found in adults, but their exact spatial extent and strength of coherence are affected by physiologic parameters and drugs. Though the acquisition and analysis methods are still evolving, new disease insights are emerging in a variety of neurologic and psychiatric disorders. The default mode network is affected in Alzheimer disease and various other diseases of cognitive impairment. Alterations in RSNs have been identified in many diseases, in the absence of evident structural modifications, indicating a high sensitivity of the method. Moreover, there is evidence of correlation between RSN alterations and disease progression and severity. However, different diseases often affect the same RSN, illustrating the limited specificity of the findings. This suggests that neurologic and psychiatric diseases are characterized by altered interactions between RSNs and therefore the whole brain should be examined as an integral network (with subnetworks), for example, using graph analysis. A challenge for clinical applications of RS functional MR imaging is the potentially confounding effect of aging, concomitant vascular diseases, or medication on the neurovascular coupling and consequently the functional MR imaging response. Current investigation combines RS functional MR imaging and other methods such as electroencephalography or magnetoencephalography to better understand the vascular

  10. Covariance of lucky images: performance analysis

    NASA Astrophysics Data System (ADS)

    Cagigal, Manuel P.; Valle, Pedro J.; Cagigas, Miguel A.; Villó-Pérez, Isidro; Colodro-Conde, Carlos; Ginski, C.; Mugrauer, M.; Seeliger, M.

    2017-01-01

    The covariance of ground-based lucky images is a robust and easy-to-use algorithm that allows us to detect faint companions surrounding a host star. In this paper, we analyse the relevance of the number of processed frames, the frames' quality, the atmosphere conditions and the detection noise on the companion detectability. This analysis has been carried out using both experimental and computer-simulated imaging data. Although the technique allows us the detection of faint companions, the camera detection noise and the use of a limited number of frames reduce the minimum detectable companion intensity to around 1000 times fainter than that of the host star when placed at an angular distance corresponding to the few first Airy rings. The reachable contrast could be even larger when detecting companions with the assistance of an adaptive optics system.

  11. Uses of software in digital image analysis: a forensic report

    NASA Astrophysics Data System (ADS)

    Sharma, Mukesh; Jha, Shailendra

    2010-02-01

    Forensic image analysis is required an expertise to interpret the content of an image or the image itself in legal matters. Major sub-disciplines of forensic image analysis with law enforcement applications include photo-grammetry, photographic comparison, content analysis and image authentication. It has wide applications in forensic science range from documenting crime scenes to enhancing faint or indistinct patterns such as partial fingerprints. The process of forensic image analysis can involve several different tasks, regardless of the type of image analysis performed. Through this paper authors have tried to explain these tasks, which are described in to three categories: Image Compression, Image Enhancement & Restoration and Measurement Extraction. With the help of examples like signature comparison, counterfeit currency comparison and foot-wear sole impression using the software Canvas and Corel Draw.

  12. Development of an optical imaging platform for functional imaging of small animals using wide-field excitation

    PubMed Central

    Venugopal, Vivek; Chen, Jin; Intes, Xavier

    2010-01-01

    The design and characterization of a time-resolved functional imager using a wide-field excitation scheme for small animal imaging is described. The optimal operation parameters are established based on phantom studies. The performance of the platform for functional imaging and the simultaneous 3D reconstruction of absorption and scattering coefficients is investigated in vitro. PMID:21258454

  13. Machine Learning Interface for Medical Image Analysis.

    PubMed

    Zhang, Yi C; Kagen, Alexander C

    2016-10-11

    TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

  14. Functional MR Imaging of Working Memory in the Human Brain

    PubMed Central

    Ryu, Jae Wook; Byun, Hong Sik; Choi, Dae Seob; Lee, Eun Jeong; Chung, Woo In; Cho, Jae Min; Han, Boo Kyung

    2000-01-01

    Objective In order to investigate the functional brain anatomy associated with verbal and visual working memory, functional magnetic resonance imaging was performed. Materials and Methods In ten normal right handed subjects, functional MR images were obtained using a 1.5-T MR scanner and the EPI BOLD technique. An item recognition task was used for stimulation, and during the activation period of the verbal working memory task, consonant letters were used. During the activation period of the visual working memory task, symbols or diagrams were employed instead of letters. For the post-processing of images, the SPM program was used, with the threshold of significance set at p < .001. We assessed activated brain areas during the two stimulation tasks and compared the activated regions between the two tasks. Results The prefrontal cortex and secondary visual cortex were activated bilaterally by both verbal and visual working memory tasks, and the patterns of activated signals were similar in both tasks. The superior parietal cortex was also activated by both tasks, with lateralization to the left in the verbal task, and bilaterally without lateralization in the visual task. The inferior frontal cortex, inferior parietal cortex and temporal gyrus were activated exclusively by the verbal working memory task, predominantly in the left hemisphere. Conclusion The prefrontal cortex is activated by two stimulation tasks, and this is related to the function of the central executive. The language areas activated by the verbal working memory task may be a function of the phonological loop. Bilateral prefrontal and superior parietal cortices activated by the visual working memory task may be related to the visual maintenance of objects, representing visual working memory. PMID:11752924

  15. A comprehensive neuropsychological mapping battery for functional magnetic resonance imaging.

    PubMed

    Karakas, Sirel; Baran, Zeynel; Ceylan, Arzu Ozkan; Tileylioglu, Emre; Tali, Turgut; Karakas, Hakki Muammer

    2013-11-01

    Existing batteries for FMRI do not precisely meet the criteria for comprehensive mapping of cognitive functions within minimum data acquisition times using standard scanners and head coils. The goal was to develop a battery of neuropsychological paradigms for FMRI that can also be used in other brain imaging techniques and behavioural research. Participants were 61 healthy, young adult volunteers (48 females and 13 males, mean age: 22.25 ± 3.39 years) from the university community. The battery included 8 paradigms for basic (visual, auditory, sensory-motor, emotional arousal) and complex (language, working memory, inhibition/interference control, learning) cognitive functions. Imaging was performed using standard functional imaging capabilities (1.5-T MR scanner, standard head coil). Structural and functional data series were analysed using Brain Voyager QX2.9 and Statistical Parametric Mapping-8. For basic processes, activation centres for individuals were within a distance of 3-11 mm of the group centres of the target regions and for complex cognitive processes, between 7 mm and 15 mm. Based on fixed-effect and random-effects analyses, the distance between the activation centres was 0-4 mm. There was spatial variability between individual cases; however, as shown by the distances between the centres found with fixed-effect and random-effects analyses, the coordinates for individual cases can be used to represent those of the group. The findings show that the neuropsychological brain mapping battery described here can be used in basic science studies that investigate the relationship of the brain to the mind and also as functional localiser in clinical studies for diagnosis, follow-up and pre-surgical mapping.

  16. Functional assessment of transplanted kidneys with magnetic resonance imaging.

    PubMed

    Wang, Yu-Ting; Li, Ying-Chun; Yin, Long-Lin; Pu, Hong; Chen, Jia-Yuan

    2015-10-28

    Kidney transplantation has emerged as the treatment of choice for many patients with end-stage renal disease, which is a significant cause of morbidity and mortality. Given the shortage of clinically available donor kidneys and the significant incidence of allograft dysfunction, a noninvasive and accurate assessment of the allograft renal function is critical for postoperative management. Prompt diagnosis of graft dysfunction facilitates clinical intervention of kidneys with salvageable function. New advances in magnetic resonance imaging (MRI) technology have enabled the calculation of various renal parameters that were previously not feasible to measure noninvasively. Diffusion-weighted imaging provides information on renal diffusion and perfusion simultaneously, with quantification by the apparent diffusion coefficient, the decrease of which reflects renal function impairment. Diffusion-tensor imaging accounts for the directionality of molecular motion and measures fractional anisotropy of the kidneys. Blood oxygen level-dependent MR evaluates intrarenal oxygen bioavailability, generating the parameter of R2* (reflecting the concentration of deoxyhemoglobin). A decrease in R2* could happen during acute rejection. MR nephro-urography/renography demonstrates structural data depicting urinary tract obstructions and functional data regarding the glomerular filtration and blood flow. MR angiography details the transplant vasculature and is particularly suitable for detecting vascular complications, with good correlation with digital subtraction angiography. Other functional MRI technologies, such as arterial spin labeling and MR spectroscopy, are showing additional promise. This review highlights MRI as a comprehensive modality to diagnose a variety of etiologies of graft dysfunction, including prerenal (e.g., renal vasculature), renal (intrinsic causes) and postrenal (e.g., obstruction of the collecting system) etiologies.

  17. Teleseismic receiver function imaging of the Pacific Northwest, United States

    NASA Astrophysics Data System (ADS)

    Eager, Kevin Charles

    The origins of widespread Cenozoic tectonomagmatism in the Pacific Northwest, United States likely involve complex dynamics including subduction of the Juan de Fuca plate and mantle upwelling processes, all of which are reflected in the crust and upper mantle. To provide an improved understanding of these processes, I analyze P-to- S converted phases using the receiver function method to image topographic variations on regional seismic discontinuities in the upper mantle, which provides constraints on mantle thermal structure, and the crust-mantle interface, which provides constraints on crustal thickness and composition. My results confirm complexity in the Juan de Fuca slab structure as found by regional tomographic studies, including limited evidence of the slab penetrating the transition zone between the 410 and 660 km discontinuities. Evidence is inconclusive for a simple mantle plume beneath the central Oregon High Lava Plains, but indicates a regional increase in mantle temperatures stretching to the east. This result implies the inflow of warm material, either from around the southern edge of the Juan de Fuca plate as it descends into the mantle, or from a regional upwelling to the east related to the Yellowstone hotspot. Results for regional crustal structure reveal thin (˜31 km) crust beneath the High Lava Plains relative to surrounding regions that exhibit thicker (35+ km) crust. The thick (≥ 40 km) crust of the Owyhee Plateau has a sharp western boundary and normal Poisson's ratio, a measure of crustal composition. I find a slightly thickened crust and low Poisson's ratio between Steens Mountain and the Owyhee Plateau, consistent with residuum from source magma of the Steens flood basalts. Central and southern Oregon exhibit very high Poisson's ratios and low velocity zones within the crust, suggesting a degree of intracrustal partial melt not seen along the center of the age-progressive High Lava Plains magmatic track, perhaps due to crustal melt

  18. The human parietal operculum. II. Stereotaxic maps and correlation with functional imaging results.

    PubMed

    Eickhoff, Simon B; Amunts, Katrin; Mohlberg, Hartmut; Zilles, Karl

    2006-02-01

    In this study we describe the localization of the cytoarchitectonic subdivisions of the human parietal operculum in stereotaxic space and relate these anatomically defined cortical areas to the location of the functionally defined secondary somatosensory cortex (SII cortex) using a meta-analysis of functional imaging results. The human parietal operculum consists of four distinct cytoarchitectonic areas (OP 1-4) as shown in the preceding publication. The 10 cytoarchitectonically examined brains were 3-D-reconstructed and spatially normalized to the T1-weighted single-subject template of the Montreal Neurological Institute (MNI). A probabilistic map was calculated for each area in this standard stereotaxic space. A cytoarchitectonic summary map of the four cortical areas on the human parietal operculum which combines these probabilistic maps was subsequently computed for the comparison with a meta-analysis of functional locations of SII. The meta-analysis used the results from 57 fMRI and PET studies and allowed the comparison of the functionally defined SII region to the cytoarchitectonic map of the parietal operculum. The functional localization of SII showed a good match to the cytoarchitectonically defined region. Therefore the cytoarchitectonic maps of OP 1-4 of the human parietal operculum can be interpreted as an anatomical correlate of the (functionally defined) human SII region. Our results also suggest that the SII foci reported in functional imaging studies may actually reflect activations in either of its architectonic subregions.

  19. Functional brain imaging in schizophrenia: selected results and methods.

    PubMed

    Brown, Gregory G; Thompson, Wesley K

    2010-01-01

    Functional brain imaging studies of patients with schizophrenia may be grouped into those that assume that the signs and symptoms of schizophrenia are due to disordered circuitry within a critical brain region and studies that assume that the signs and symptoms are due to disordered connections among brain regions. Studies have investigated the disordered functional brain anatomy of both the positive and negative symptoms of schizophrenia. Studies of spontaneous hallucinations find that although hallucinations are associated with abnormal brain activity in primary and secondary sensory areas, disordered brain activation associated with hallucinations is not limited to sensory systems. Disordered activation in non-sensory regions appear to contribute to the emotional strength and valence of hallucinations, to be a factor underlying an inability to distinguish ongoing mental processing from memories, and to reflect the brain's attempt to modulate the intensity of hallucinations and resolve conflicts with other processing demands. Brain activation studies support the view that auditory/verbal hallucinations are associated with an impaired ability of internal speech plans to modulate neural activation in sensory language areas. In early studies, negative symptoms of schizophrenia were hypothesized to be associated with impaired function in frontal brain areas. In support of this hypothesis meta-analytical studies have found that resting blood flow or metabolism in frontal cortex is reduced in schizophrenia, though the magnitude of the effect is only small to moderate. Brain activation studies of working memory (WM) functioning are typically associated with large effect sizes in the frontal cortex, whereas studies of functions other than WM generally reveal smaller effects. Findings from some functional connectivity studies have supported the hypothesis that schizophrenia patients experience impaired functional connections between frontal and temporal cortex, although

  20. Wavelet-based image analysis system for soil texture analysis

    NASA Astrophysics Data System (ADS)

    Sun, Yun; Long, Zhiling; Jang, Ping-Rey; Plodinec, M. John

    2003-05-01

    Soil texture is defined as the relative proportion of clay, silt and sand found in a given soil sample. It is an important physical property of soil that affects such phenomena as plant growth and agricultural fertility. Traditional methods used to determine soil texture are either time consuming (hydrometer), or subjective and experience-demanding (field tactile evaluation). Considering that textural patterns observed at soil surfaces are uniquely associated with soil textures, we propose an innovative approach to soil texture analysis, in which wavelet frames-based features representing texture contents of soil images are extracted and categorized by applying a maximum likelihood criterion. The soil texture analysis system has been tested successfully with an accuracy of 91% in classifying soil samples into one of three general categories of soil textures. In comparison with the common methods, this wavelet-based image analysis approach is convenient, efficient, fast, and objective.

  1. Functional analysis and treatment of diurnal bruxism.

    PubMed

    Lang, Russell; Davenport, Katy; Britt, Courtney; Ninci, Jennifer; Garner, Jennifer; Moore, Melissa

    2013-01-01

    An analogue functional analysis identified attention as a function for a 5-year-old boy's bruxism (teeth grinding). Functional communication training resulted in a reduction of bruxism and an increase in alternative mands for attention. Results were maintained 3 weeks following the intervention.

  2. Functional Analysis and Reduction of Inappropriate Spitting

    ERIC Educational Resources Information Center

    Carter, Stacy L.; Wheeler, John J.

    2007-01-01

    Functional analysis was used to determine the possible function of inappropriate spitting behavior of an adult woman who had been diagnosed with profound mental retardation. Results of an initial descriptive assessment indicated a possible attention function and led to an attention-based intervention, which was deemed ineffective at reducing the…

  3. Methodological challenges and solutions in auditory functional magnetic resonance imaging

    PubMed Central

    Peelle, Jonathan E.

    2014-01-01

    Functional magnetic resonance imaging (fMRI) studies involve substantial acoustic noise. This review covers the difficulties posed by such noise for auditory neuroscience, as well as a number of possible solutions that have emerged. Acoustic noise can affect the processing of auditory stimuli by making them inaudible or unintelligible, and can result in reduced sensitivity to auditory activation in auditory cortex. Equally importantly, acoustic noise may also lead to increased listening effort, meaning that even when auditory stimuli are perceived, neural processing may differ from when the same stimuli are presented in quiet. These and other challenges have motivated a number of approaches for collecting auditory fMRI data. Although using a continuous echoplanar imaging (EPI) sequence provides high quality imaging data, these data may also be contaminated by background acoustic noise. Traditional sparse imaging has the advantage of avoiding acoustic noise during stimulus presentation, but at a cost of reduced temporal resolution. Recently, three classes of techniques have been developed to circumvent these limitations. The first is Interleaved Silent Steady State (ISSS) imaging, a variation of sparse imaging that involves collecting multiple volumes following a silent period while maintaining steady-state longitudinal magnetization. The second involves active noise control to limit the impact of acoustic scanner noise. Finally, novel MRI sequences that reduce the amount of acoustic noise produced during fMRI make the use of continuous scanning a more practical option. Together these advances provide unprecedented opportunities for researchers to collect high-quality data of hemodynamic responses to auditory stimuli using fMRI. PMID:25191218

  4. Atlas of protein expression: image capture, analysis, and design of terabyte image database

    NASA Astrophysics Data System (ADS)

    Wu, Jiahua; Maslen, Gareth; Warford, Anthony; Griffin, Gareth; Xie, Jane; Crowther, Sandra; McCafferty, John

    2006-03-01

    The activity of genes in health and disease are manifested through the proteins which they encode. Ultimately, proteins drive functional processes in cells and tissues and so by measuring individual protein levels, studying modifications and discovering their sites of action we will understand better their function. It is possible to visualize the location of proteins of interest in tissue sections using labeled antibodies which bind to the target protein. This procedure, known as immunohistochemistry (IHC), provides valuable information on the cellular and sub-cellular distribution of proteins in tissue. The project, atlas of protein expression, aims to create a quality, information rich database of protein expression profiles, which is accessible to the world-wide research community. For the long term archival value of the data, the accompanying validated antibody and protein clones will potentially have great research, diagnostic and possibly therapeutic potential. To achieve this we had introduced a number of novel technologies, e.g. express recombinant proteins, select antibodies, stain proteins present in tissue section, and tissue microarray (TMA) image analysis. These are currently being optimized, automated and integrated into a multi-disciplinary production process. We had also created infrastructure for multi-terabyte scale image capture, established an image analysis capability for initial screening and quantization.

  5. In situ nondestructive imaging of functional pigments in Micro-Tom tomato fruits by multi spectral imaging based on Wiener estimation method

    NASA Astrophysics Data System (ADS)

    Nishidate, Izumi; Ooe, Shintaro; Todoroki, Shinsuke; Asamizu, Erika

    2013-05-01

    To evaluate the functional pigments in the tomato fruits nondestructively, we propose a method based on the multispectral diffuse reflectance images estimated by the Wiener estimation for a digital RGB image. Each pixel of the multispectral image is converted to the absorbance spectrum and then analyzed by the multiple regression analysis to visualize the contents of chlorophyll a, lycopene and β-carotene. The result confirms the feasibility of the method for in situ imaging of chlorophyll a, β-carotene and lycopene in the tomato fruits.

  6. Research on automatic human chromosome image analysis

    NASA Astrophysics Data System (ADS)

    Ming, Delie; Tian, Jinwen; Liu, Jian

    2007-11-01

    Human chromosome karyotyping is one of the essential tasks in cytogenetics, especially in genetic syndrome diagnoses. In this thesis, an automatic procedure is introduced for human chromosome image analysis. According to different status of touching and overlapping chromosomes, several segmentation methods are proposed to achieve the best results. Medial axis is extracted by the middle point algorithm. Chromosome band is enhanced by the algorithm based on multiscale B-spline wavelets, extracted by average gray profile, gradient profile and shape profile, and calculated by the WDD (Weighted Density Distribution) descriptors. The multilayer classifier is used in classification. Experiment results demonstrate that the algorithms perform well.

  7. ImageJ-MATLAB: a bidirectional framework for scientific image analysis interoperability.

    PubMed

    Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W

    2016-10-26

    ImageJ-MATLAB is a lightweight Java library facilitating bi-directional interoperability between MATLAB and ImageJ. By defining a standard for translation between matrix and image data structures, researchers are empowered to select the best tool for their image-analysis tasks.

  8. Structural and functional optical coherence tomography imaging of the colon

    NASA Astrophysics Data System (ADS)

    Welge, Weston Anthony

    Colorectal cancer (CRC) remains the second deadliest cancer in the United States, despite steady reduction in mortality rate over the last three decades. Colonoscopy is the gold-standard screening modality with high sensitivity and specificity to mature polyps. However, the miss rate for small (< 5 mm) lesions is estimated to be as high as 26%. Because the five-year survival rate for CRC detected at the local stage is 90%, there is a clear need for a screening procedure that is sensitive to these small lesions. Optical coherence tomography (OCT) has become a major biomedical imaging modality since its invention in 1991. As the optical analog to ultrasound, OCT provides information in both lateral and depth dimensions with resolution < 10 ?m and an imaging depth of about 1.5 mm in scattering tissue. In this dissertation, I describe my efforts to develop new uses of OCT for improved early detection of adenoma in the azoxymethane mouse model of CRC. In recent years, commercial OCT systems have reached imaging speeds sufficiently high for in vivo volumeric imaging while laterally sampling the tissue at the Nyquist limit. First, I describe the design of a miniature endoscope and the integration of this probe with a commercial OCT system. Then I describe the development of two OCT imaging methods, one structural and one functional, that could be used for future work in diagnostic or therapeutic studies. The structural method produces en face images of the colon surface showing the colonic crypts, the first such demonstration of crypt visualization in the mouse. Changes in the crypt pattern are correlated with adenoma and are one of the earliest morphological changes. The functional method uses a Doppler OCT algorithm and image processing to detect the colon microvasculature. This technique can be used for vessel counting and blood flow measurements. Angiogenesis occurs at the beginning of tumorigenesis, and the tumor-originated arterioles are incapable of regular

  9. General comparison of functional imaging in nuclear medicine with other modalities

    SciTech Connect

    Adam, W.E.

    1987-01-01

    New (noninvasive) diagnostic procedures in medicine (ultrasound (US), digital subtraction angiography (DSA), computed tomography (CT), nuclear magnetic resonance (NMR)) create a need for a review of the clinical utility of functional imaging in nuclear medicine. A general approach that is valid for all imaging procedures is not possible. For this reason, an individual assessment for each class of functional imaging is necessary, taking into account the complexity and sophistication of the various imaging procedures. This leads to a hierarchical order: first order functional imaging: imaging of organ motion (heart, lungs, blood); second order functional imaging: imaging of excretory function (kidneys, liver); and third and fourth order functional imaging: imaging of metabolism (except excretory function). First order functional imaging is possible fundamentally, although with limitations in detail, by all modalities. Second order functional imaging is not possible with US. Third and fourth order functional imaging is a privilege of nuclear medicine alone. Up to now, NMR has not proven clinically useful to produce metabolic images in its true sense. First and second order functional imaging of nonradioactive procedures face severe disadvantages, including difficulties in performing stress investigations, which are essential for coronary heart disease, limited capability for true quantitative information (eg, kidney clearance in mL/min), side effects of contrast media and paramagnetic substances, and high costs. 58 references.

  10. Whole-central nervous system functional imaging in larval Drosophila

    PubMed Central

    Lemon, William C.; Pulver, Stefan R.; Höckendorf, Burkhard; McDole, Katie; Branson, Kristin; Freeman, Jeremy; Keller, Philipp J.

    2015-01-01

    Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord. PMID:26263051

  11. Whole-central nervous system functional imaging in larval Drosophila.

    PubMed

    Lemon, William C; Pulver, Stefan R; Höckendorf, Burkhard; McDole, Katie; Branson, Kristin; Freeman, Jeremy; Keller, Philipp J

    2015-08-11

    Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord.

  12. Accuracy of a remote quantitative image analysis in the whole slide images.

    PubMed

    Słodkowska, Janina; Markiewicz, Tomasz; Grala, Bartłomiej; Kozłowski, Wojciech; Papierz, Wielisław; Pleskacz, Katarzyna; Murawski, Piotr

    2011-03-30

    The rationale for choosing a remote quantitative method supporting a diagnostic decision requires some empirical studies and knowledge on scenarios including valid telepathology standards. The tumours of the central nervous system [CNS] are graded on the base of the morphological features and the Ki-67 labelling Index [Ki-67 LI]. Various methods have been applied for Ki-67 LI estimation. Recently we have introduced the Computerized Analysis of Medical Images [CAMI] software for an automated Ki-67 LI counting in the digital images. Aims of our study was to explore the accuracy and reliability of a remote assessment of Ki-67 LI with CAMI software applied to the whole slide images [WSI]. The WSI representing CNS tumours: 18 meningiomas and 10 oligodendrogliomas were stored on the server of the Warsaw University of Technology. The digital copies of entire glass slides were created automatically by the Aperio ScanScope CS with objective 20x or 40x. Aperio's Image Scope software provided functionality for a remote viewing of WSI. The Ki-67 LI assessment was carried on within 2 out of 20 selected fields of view (objective 40x) representing the highest labelling areas in each WSI. The Ki-67 LI counting was performed by 3 various methods: 1) the manual reading in the light microscope - LM, 2) the automated counting with CAMI software on the digital images - DI , and 3) the remote quantitation on the WSIs - as WSI method. The quality of WSIs and technical efficiency of the on-line system were analysed. The comparative statistical analysis was performed for the results obtained by 3 methods of Ki-67 LI counting. The preliminary analysis showed that in 18% of WSI the results of Ki-67 LI differed from those obtained in other 2 methods of counting when the quality of the glass slides was below the standard range. The results of our investigations indicate that the remote automated Ki-67 LI analysis performed with the CAMI algorithm on the whole slide images of meningiomas and

  13. Design and validation of Segment - freely available software for cardiovascular image analysis

    PubMed Central

    2010-01-01

    Background Commercially available software for cardiovascular image analysis often has limited functionality and frequently lacks the careful validation that is required for clinical studies. We have already implemented a cardiovascular image analysis software package and released it as freeware for the research community. However, it was distributed as a stand-alone application and other researchers could not extend it by writing their own custom image analysis algorithms. We believe that the work required to make a clinically applicable prototype can be reduced by making the software extensible, so that researchers can develop their own modules or improvements. Such an initiative might then serve as a bridge between image analysis research and cardiovascular research. The aim of this article is therefore to present the design and validation of a cardiovascular image analysis software package (Segment) and to announce its release in a source code format. Results Segment can be used for image analysis in magnetic resonance imaging (MRI), computed tomography (CT), single photon emission computed tomography (SPECT) and positron emission tomography (PET). Some of its main features include loading of DICOM images from all major scanner vendors, simultaneous display of multiple image stacks and plane intersections, automated segmentation of the left ventricle, quantification of MRI flow, tools for manual and general object segmentation, quantitative regional wall motion analysis, myocardial viability analysis and image fusion tools. Here we present an overview of the validation results and validation procedures for the functionality of the software. We describe a technique to ensure continued accuracy and validity of the software by implementing and using a test script that tests the functionality of the software and validates the output. The software has been made freely available for research purposes in a source code format on the project home page http

  14. Technetium-99m NGA functional hepatic imaging: preliminary clinical experience

    SciTech Connect

    Stadalnik, R.C.; Vera, D.R.; Woodle, E.S.; Trudeau, W.L.; Porter, B.A.; Ward, R.E.; Krohn, K.A.; O'Grady, L.F.

    1985-11-01

    Technetium-99m galactosyl-neoglycoalbumin ( (Tc)NGA) is a radiolabeled ligand to hepatic binding protein, a receptor which resides at the plasma membrane of hepatocytes. This receptor-binding radiopharmaceutical and its kinetic model provide a noninvasive method for the assessment of liver function. Eighteen patients were studied: seven with hepatoma, eight with liver metastases, four wit