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Sample records for functional image analysis

  1. 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.

  2. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis.

    PubMed

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

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  3. Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis

    PubMed Central

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

    2015-01-01

    Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the prediction of clinical outcomes and the characterization of disease progression. But in the meantime, the growing data dimensions pose great methodological and computational challenges for the representation and selection of features in image cluster analysis. To address these challenges, we first extend the functional principal component analysis (FPCA) from one dimension to two dimensions to fully capture the space variation of image the signals. The image signals contain a large number of redundant features which provide no additional information for clustering analysis. The widely used methods for removing the irrelevant features are sparse clustering algorithms using a lasso-type penalty to select the features. However, the accuracy of clustering using a lasso-type penalty depends on the selection of the penalty parameters and the threshold value. In practice, they are difficult to determine. Recently, randomized algorithms have received a great deal of attentions in big data analysis. This paper presents a randomized algorithm for accurate feature selection in image clustering analysis. The proposed method is applied to both the liver and kidney cancer histology image data from the TCGA database. The results demonstrate that the randomized feature selection method coupled with functional principal component analysis substantially outperforms the current sparse clustering algorithms in image cluster analysis. PMID:26196383

  4. 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.

  5. Region of interest based analysis of functional imaging data.

    PubMed

    Nieto-Castanon, Alfonso; Ghosh, Satrajit S; Tourville, Jason A; Guenther, Frank H

    2003-08-01

    fMRI analysis techniques are presented that test functional hypotheses at the region of interest (ROI) level. An SPM-compatible Matlab toolbox has been developed that allows the creation of subject-specific ROI masks based on anatomical markers and the testing of functional hypotheses on the regional response using multivariate time-series analysis techniques. The combined application of subject-specific ROI definition and region-level functional analysis is shown to appropriately compensate for intersubject anatomical variability, offering finer localization and increased sensitivity to task-related effects than standard techniques based on whole-brain normalization and voxel or cluster-level functional analysis, while providing a more direct link between discrete brain region hypotheses and the statistical analyses used to test them.

  6. 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.

  7. Analysis of mitochondrial dynamics and functions using imaging approaches

    PubMed Central

    Mitra, Kasturi; Lippincott-Schwartz, Jennifer

    2010-01-01

    Mitochondria are organelles that have been primarily known as the ‘power house of the cell’. However, recent advances in the field have revealed that mitochondria are also involved in many other cellular activities like lipid modifications, redox balance, calcium balance and even control cell death. These multifunctional organelles are motile and highly dynamic in shapes and forms; the dynamism is brought about by the mitochondria's ability to undergo fission and fusion with each other. Therefore it is very important to be able to image mitochondrial shape changes to relate to the variety of cellular functions these organelles have to accomplish. The protocols mentioned here will enable researchers to perform steady state and time lapse imaging of mitochondria in live cells by using confocal microscopy. High resolution 3D imaging of mitochondria will not only be helpful in understanding mitochondrial structure in detail but also could be used to analyze their structural relationships with other organelles in the cell. FRAP (fluorescence recovery after photobleaching) studies can be performed to understand mitochondrial dynamics or dynamics of any mitochondrial molecule within the organelle. Microirradiation assay can be performed to study functional continuity between mitochondria. Protocol for measuring mitochondrial potential has also been included in this chapter. In conclusion, the protocols described here will aid the understanding of mitochondrial structure-function relationship. PMID:20235105

  8. Texture functions in image analysis: A computationally efficient solution

    NASA Technical Reports Server (NTRS)

    Cox, S. C.; Rose, J. F.

    1983-01-01

    A computationally efficient means for calculating texture measurements from digital images by use of the co-occurrence technique is presented. The calculation of the statistical descriptors of image texture and a solution that circumvents the need for calculating and storing a co-occurrence matrix are discussed. The results show that existing efficient algorithms for calculating sums, sums of squares, and cross products can be used to compute complex co-occurrence relationships directly from the digital image input.

  9. Image Registration for Quantitative Analysis of Kidney Function using MRI

    NASA Astrophysics Data System (ADS)

    Sance, Rosario; Ledesma-Carbayo, María J.; Lundervold, Arvid; Santos, Andrés

    2006-10-01

    The aim of the present study is to analyze the possibilities of registration algorithms to compensate respiratory motion and deformation in abdominal DCE-MRI 3D temporary series. The final objective is that from registered data, appropriate intensity curves of local renal activity along the time could be represented for each kidney voxel. Assuming a relation between the voxel intensity and the contrast media concentration, this non-invasive renographic method could be used to evaluate the local renal function, and to calculate typical renal parameters like glomerular filtration rate.

  10. 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.

  11. 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.

  12. 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

  13. 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).

  14. Independent Component Analysis Involving Autocorrelated Sources With an Application to Functional Magnetic Resonance Imaging

    PubMed Central

    Lee, Seonjoo; Shen, Haipeng; Truong, Young; Lewis, Mechelle; Huang, Xuemei

    2016-01-01

    Independent component analysis (ICA) is an effective data-driven method for blind source separation. It has been successfully applied to separate source signals of interest from their mixtures. Most existing ICA procedures are carried out by relying solely on the estimation of the marginal density functions, either parametrically or nonparametrically. In many applications, correlation structures within each source also play an important role besides the marginal distributions. One important example is functional magnetic resonance imaging (fMRI) analysis where the brain-function-related signals are temporally correlated. In this article, we consider a novel approach to ICA that fully exploits the correlation structures within the source signals. Specifically, we propose to estimate the spectral density functions of the source signals instead of their marginal density functions. This is made possible by virtue of the intrinsic relationship between the (unobserved) sources and the (observed) mixed signals. Our methodology is described and implemented using spectral density functions from frequently used time series models such as autoregressive moving average (ARMA) processes. The time series parameters and the mixing matrix are estimated via maximizing the Whittle likelihood function. We illustrate the performance of the proposed method through extensive simulation studies and a real fMRI application. The numerical results indicate that our approach outperforms several popular methods including the most widely used fastICA algorithm. This article has supplementary material online. PMID:27524847

  15. A novel image analysis method based on Bayesian segmentation for event-related functional MRI

    NASA Astrophysics Data System (ADS)

    Huang, Lejian; Comer, Mary L.; Talavage, Thomas M.

    2008-02-01

    This paper presents the application of the expectation-maximization/maximization of the posterior marginals (EM/MPM) algorithm to signal detection for functional MRI (fMRI). On basis of assumptions for fMRI 3-D image data, a novel analysis method is proposed and applied to synthetic data and human brain data. Synthetic data analysis is conducted using two statistical noise models (white and autoregressive of order 1) and, for low contrast-to-noise ratio (CNR) data, reveals better sensitivity and specificity for the new method than for the traditional General Linear Model (GLM) approach. When applied to human brain data, functional activation regions are found to be consistent with those obtained using the GLM approach.

  16. The neuronal correlates of intranasal trigeminal function-an ALE meta-analysis of human functional brain imaging data.

    PubMed

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

    2010-03-01

    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 (CO(2)), 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 CO(2) 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.

  17. 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

  18. Functional Brain Imaging

    PubMed Central

    2006-01-01

    Executive Summary Objective The objective of this analysis is to review a spectrum of functional brain imaging technologies to identify whether there are any imaging modalities that are more effective than others for various brain pathology conditions. This evidence-based analysis reviews magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) for the diagnosis or surgical management of the following conditions: Alzheimer’s disease (AD), brain tumours, epilepsy, multiple sclerosis (MS), and Parkinson’s disease (PD). Clinical Need: Target Population and Condition Alzheimer’s disease is a progressive, degenerative, neurologic condition characterized by cognitive impairment and memory loss. The Canadian Study on Health and Aging estimated that there will be 97,000 incident cases (about 60,000 women) of dementia (including AD) in Canada in 2006. In Ontario, there will be an estimated 950 new cases and 580 deaths due to brain cancer in 2006. Treatments for brain tumours include surgery and radiation therapy. However, one of the limitations of radiation therapy is that it damages tissue though necrosis and scarring. Computed tomography (CT) and magnetic resonance imaging (MRI) may not distinguish between radiation effects and resistant tissue, creating a potential role for functional brain imaging. Epilepsy is a chronic disorder that provokes repetitive seizures. In Ontario, the rate of epilepsy is estimated to be 5 cases per 1,000 people. Most people with epilepsy are effectively managed with drug therapy; but about 50% do not respond to drug therapy. Surgical resection of the seizure foci may be considered in these patients, and functional brain imaging may play a role in localizing the seizure foci. Multiple sclerosis is a progressive, inflammatory, demyelinating disease of the central nervous system (CNS). The cause of MS is unknown; however, it is thought to be

  19. 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…

  20. Rostral and caudal prefrontal contribution to creativity: a meta-analysis of functional imaging data

    PubMed Central

    Gonen-Yaacovi, Gil; de Souza, Leonardo Cruz; Levy, Richard; Urbanski, Marika; Josse, Goulven; Volle, Emmanuelle

    2013-01-01

    Creativity is of central importance for human civilization, yet its neurocognitive bases are poorly understood. The aim of the present study was to integrate existing functional imaging data by using the meta-analysis approach. We reviewed 34 functional imaging studies that reported activation foci during tasks assumed to engage creative thinking in healthy adults. A coordinate-based meta-analysis using Activation Likelihood Estimation (ALE) first showed a set of predominantly left-hemispheric regions shared by the various creativity tasks examined. These regions included the caudal lateral prefrontal cortex (PFC), the medial and lateral rostral PFC, and the inferior parietal and posterior temporal cortices. Further analyses showed that tasks involving the combination of remote information (combination tasks) activated more anterior areas of the lateral PFC than tasks involving the free generation of unusual responses (unusual generation tasks), although both types of tasks shared caudal prefrontal areas. In addition, verbal and non-verbal tasks involved the same regions in the left caudal prefrontal, temporal, and parietal areas, but also distinct domain-oriented areas. Taken together, these findings suggest that several frontal and parieto-temporal regions may support cognitive processes shared by diverse creativity tasks, and that some regions may be specialized for distinct types of processes. In particular, the lateral PFC appeared to be organized along a rostro-caudal axis, with rostral regions involved in combining ideas creatively and more posterior regions involved in freely generating novel ideas. PMID:23966927

  1. Analysis of abdominal wounds made by surgical trocars using functional luminal imaging probe (FLIP) technology.

    PubMed

    McMahon, Barry P; O'Donovan, Deidre; Liao, Donghua; Zhao, Jingbo; Schiretz, Rich; Heninrich, Russell; Gregersen, Hans

    2008-09-01

    The aim was to use a novel functional luminal imaging probe for evaluation of wound defects and tissue damage resulting from the use of trocars. Following general anesthesia of 4 adult pigs, 6 different trocars were randomly inserted at preselected locations in the porcine abdominal wall. The functional luminal imaging probe was used to profile the trocar holes during bag distension from 8 axial cross-sectional area measurements. The cross-sectional areas and pressure in the bag were recorded and exported to Matlab for analysis and data display. Geometric profiles were generated, and the minimum cross-sectional area and hole length (abdominal wall thickness) were used as endpoints. Successful distensions were made in all cases. The slope of the contours increased away from the narrowest point of the hole. The slope increased more rapidly toward the inner abdominal wall than toward the outer wall. The slope of the linear trend lines for the cross-sectional area-pressure relation represents the compliance at the narrowest point in the wall. The hole length (abdominal wall thickness) could be obtained at different cross-sectional area cutoff points. A cutoff point of 300 mm(2) gave good results when compared to the length of the hole measured after the tissue was excised. This technique represents a new and straightforward way to evaluate the effects of trocars on the abdominal wall. It may also prove useful in comparing techniques and technology from different manufacturers. PMID:18757380

  2. 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.

  3. 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.

  4. Functions of images

    NASA Astrophysics Data System (ADS)

    Lehtonen, Juha; Andriyashin, Alexey; Parkkinen, Jussi; Leisti, Tuomas; Nyman, Göte

    2006-10-01

    The visual quality of images is outward in image presentation, compression and analysis. Depending on the use, the quality of images may give more information or more experiences to the viewer. However, the relations between mathematical and human methods for grouping the images are not obvious. For example, different humans think differently and so, they make the grouping differently. However, there may be some connections between image mathematical features and human selections. Here we try to find such relations that could give more possibilities for developing the actual quality of images for different purposes. In this study, we present some methods and preliminary results that are based on psychological tests to humans, MPEG-7 based features of the images and face detection methods. We also show some notes and questions belonging to this problem and plans for the future research.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Functional atlas of emotional faces processing: a voxel-based meta-analysis of 105 functional magnetic resonance imaging studies

    PubMed Central

    Fusar-Poli, Paolo; Placentino, Anna; Carletti, Francesco; Landi, Paola; Allen, Paul; Surguladze, Simon; Benedetti, Francesco; Abbamonte, Marta; Gasparotti, Roberto; Barale, Francesco; Perez, Jorge; McGuire, Philip; Politi, Pierluigi

    2009-01-01

    Background Most of our social interactions involve perception of emotional information from the faces of other people. Furthermore, such emotional processes are thought to be aberrant in a range of clinical disorders, including psychosis and depression. However, the exact neurofunctional maps underlying emotional facial processing are not well defined. Methods Two independent researchers conducted separate comprehensive PubMed (1990 to May 2008) searches to find all functional magnetic resonance imaging (fMRI) studies using a variant of the emotional faces paradigm in healthy participants. The search terms were: “fMRI AND happy faces,” “fMRI AND sad faces,” “fMRI AND fearful faces,” “fMRI AND angry faces,” “fMRI AND disgusted faces” and “fMRI AND neutral faces.” We extracted spatial coordinates and inserted them in an electronic database. We performed activation likelihood estimation analysis for voxel-based meta-analyses. Results Of the originally identified studies, 105 met our inclusion criteria. The overall database consisted of 1785 brain coordinates that yielded an overall sample of 1600 healthy participants. Quantitative voxel-based meta-analysis of brain activation provided neurofunctional maps for 1) main effect of human faces; 2) main effect of emotional valence; and 3) modulatory effect of age, sex, explicit versus implicit processing and magnetic field strength. Processing of emotional faces was associated with increased activation in a number of visual, limbic, temporoparietal and prefrontal areas; the putamen; and the cerebellum. Happy, fearful and sad faces specifically activated the amygdala, whereas angry or disgusted faces had no effect on this brain region. Furthermore, amygdala sensitivity was greater for fearful than for happy or sad faces. Insular activation was selectively reported during processing of disgusted and angry faces. However, insular sensitivity was greater for disgusted than for angry faces. Conversely

  10. 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.

  11. Unbiased group-wise image registration: applications in brain fiber tract atlas construction and functional connectivity analysis.

    PubMed

    Geng, Xiujuan; Gu, Hong; Shin, Wanyong; Ross, Thomas J; Yang, Yihong

    2011-10-01

    We propose an unbiased implicit-reference group-wise (IRG) image registration method and demonstrate its applications in the construction of a brain white matter fiber tract atlas and the analysis of resting-state functional MRI (fMRI) connectivity. Most image registration techniques pair-wise align images to a selected reference image and group analyses are performed in the reference space, which may produce bias. The proposed method jointly estimates transformations, with an elastic deformation model, registering all images to an implicit reference corresponding to the group average. The unbiased registration is applied to build a fiber tract atlas by registering a group of diffusion tensor images. Compared to reference-based registration, the IRG registration improves the fiber track overlap within the group. After applying the method in the fMRI connectivity analysis, results suggest a general improvement in functional connectivity maps at a group level in terms of larger cluster size and higher average t-scores.

  12. 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.

  13. 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

  14. A review of heart chamber segmentation for structural and functional analysis using cardiac magnetic resonance imaging.

    PubMed

    Peng, Peng; Lekadir, Karim; Gooya, Ali; Shao, Ling; Petersen, Steffen E; Frangi, Alejandro F

    2016-04-01

    Cardiovascular magnetic resonance (CMR) has become a key imaging modality in clinical cardiology practice due to its unique capabilities for non-invasive imaging of the cardiac chambers and great vessels. A wide range of CMR sequences have been developed to assess various aspects of cardiac structure and function, and significant advances have also been made in terms of imaging quality and acquisition times. A lot of research has been dedicated to the development of global and regional quantitative CMR indices that help the distinction between health and pathology. The goal of this review paper is to discuss the structural and functional CMR indices that have been proposed thus far for clinical assessment of the cardiac chambers. We include indices definitions, the requirements for the calculations, exemplar applications in cardiovascular diseases, and the corresponding normal ranges. Furthermore, we review the most recent state-of-the art techniques for the automatic segmentation of the cardiac boundaries, which are necessary for the calculation of the CMR indices. Finally, we provide a detailed discussion of the existing literature and of the future challenges that need to be addressed to enable a more robust and comprehensive assessment of the cardiac chambers in clinical practice.

  15. Direct Characterization of Arterial Input Functions by Fluorescence Imaging of Exposed Carotid Artery to Facilitate Kinetic Analysis

    PubMed Central

    Elliott, Jonathan T.; Tichauer, Kenneth M.; Samkoe, Kimberley S.; Gunn, Jason R.; Sexton, Kristian J.; Pogue, Brian W.

    2014-01-01

    Purpose With the goal of facilitating tracer kinetic analysis in small-animal planar fluorescence imaging, an experimental method for characterizing tracer arterial input functions is presented. The proposed method involves exposing the common carotid arteries by surgical dissection, which can then be imaged directly during tracer injection and clearance. Procedures Arterial concentration curves of IRDye-700DX-carboxylate, IRDye-800CW-EGF, and IRDye-800CW conjugated to anti-EGFR Affibody are recovered from athymic female mice (n=12) by directly imaging exposed vessels. Images were acquired with two imaging protocols: a slow-kinetics approach (temporal resolution=45 s) to recover the arterial curves from two tracers simultaneously, and a fast-kinetics approach (temporal resolution=500 ms) to characterize the first-pass peak of a single tracer. Arterial input functions obtained by the carotid imaging technique, as well as plasma curves measured by blood sampling were fit with a biexponential pharmacokinetic model. Results Pharmacological fast- and slow-phase rate constants recovered with the proposed method were 0.37±0.26 and 0.007±0.001 min−1, respectively, for the IRDye700DX-C. For the IRDye800CW-EGF, the rate constants were 0.11±0.13 and 0.003±0.002 min−1. These rate constants did not differ significantly from those calculated previously by blood sampling, as determined by an F test; however, the between-subject variability was four times lower for arterial curves recovered using the proposed technique, compared with blood sampling. Conclusions The proposed technique enables the direct characterization of arterial input functions for kinetic analysis. As this method requires no additional instrumentation, it is immediately deployable in commercially available planar fluorescence imaging systems. PMID:24420443

  16. Object detection and classification using image moment functions in the applied to video and imagery analysis

    NASA Astrophysics Data System (ADS)

    Mise, Olegs; Bento, Stephen

    2013-05-01

    This paper proposes an object detection algorithm and a framework based on a combination of Normalized Central Moment Invariant (NCMI) and Normalized Geometric Radial Moment (NGRM). The developed framework allows detecting objects with offline pre-loaded signatures and/or using the tracker data in order to create an online object signature representation. The framework has been successfully applied to the target detection and has demonstrated its performance on real video and imagery scenes. In order to overcome the implementation constraints of the low-powered hardware, the developed framework uses a combination of image moment functions and utilizes a multi-layer neural network. The developed framework has been shown to be robust to false alarms on non-target objects. In addition, optimization for fast calculation of the image moments descriptors is discussed. This paper presents an overview of the developed framework and demonstrates its performance on real video and imagery scenes.

  17. Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network

    PubMed Central

    Morgan, Victoria L.; Mishra, Arabinda; Newton, Allen T.; Gore, John C.; Ding, Zhaohua

    2009-01-01

    Background The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing interest in characterizing the relationship between these measures in the distributed neural networks of the brain. In this study, we attempted an integration of structural and functional analyses of the human language circuits, including Wernicke's (WA), Broca's (BA) and supplementary motor area (SMA), using a combination of blood oxygen level dependent (BOLD) and diffusion tensor MRI. Methodology/Principal Findings Functional connectivity was measured by low frequency inter-regional correlations of BOLD MRI signals acquired in a resting steady-state, and structural connectivity was measured by using adaptive fiber tracking with diffusion tensor MRI data. The results showed that different language pathways exhibited different structural and functional connectivity, indicating varying levels of inter-dependence in processing across regions. Along the path between BA and SMA, the fibers tracked generally formed a single bundle and the mean radius of the bundle was positively correlated with functional connectivity. However, fractional anisotropy was found not to be correlated with functional connectivity along paths connecting either BA and SMA or BA and WA. Conclusions/Significance These findings suggest that structure-function relations in the human language circuits may involve a number of confounding factors that need to be addressed. Nevertheless, the insights gained from this work offers a useful guidance for continued studies that may provide a non-invasive means to evaluate brain network integrity in vivo for use in diagnosing and determining disease progression and recovery. PMID:19684850

  18. 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.

  19. Optimizing the design and analysis of clinical functional magnetic resonance imaging research studies.

    PubMed

    Carter, Cameron S; Heckers, Stephan; Nichols, Thomas; Pine, Daniel S; Strother, Stephen

    2008-11-15

    With the widespread availability of functional magnetic resonance imaging (fMRI), there has been rapid progress in identifying neural correlates of cognition and emotion in the human brain. In conjunction with basic research studies, fMRI has been increasingly applied in clinical disorders, making it a central research tool in human psychopathology, psychopharmacology, and genetics. In the present article, we discuss a number of conceptual and methodological challenges that confront the implementation of fMRI in clinical and translational research, and we offer a set of recommendations intended to enhance the interpretability and reproducibility of results in clinical fMRI.

  20. Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software

    PubMed Central

    Kamentsky, Lee; Jones, Thouis R.; Fraser, Adam; Bray, Mark-Anthony; Logan, David J.; Madden, Katherine L.; Ljosa, Vebjorn; Rueden, Curtis; Eliceiri, Kevin W.; Carpenter, Anne E.

    2011-01-01

    Summary: There is a strong and growing need in the biology research community for accurate, automated image analysis. Here, we describe CellProfiler 2.0, which has been engineered to meet the needs of its growing user base. It is more robust and user friendly, with new algorithms and features to facilitate high-throughput work. ImageJ plugins can now be run within a CellProfiler pipeline. Availability and Implementation: CellProfiler 2.0 is free and open source, available at http://www.cellprofiler.org under the GPL v. 2 license. It is available as a packaged application for Macintosh OS X and Microsoft Windows and can be compiled for Linux. Contact: anne@broadinstitute.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21349861

  1. Automatic detection of local arterial input functions through Independent Component Analysis on Dynamic Contrast enhanced Magnetic Resonance Imaging.

    PubMed

    Narvaez, Mario; Ruiz-Espana, Silvia; Arana, Estanislao; Moratal, David

    2015-08-01

    Arterial Input Function (AIF) is obtained from perfusion studies as a basic parameter for the calculus of hemodynamic variables used as surrogate markers of the vascular status of tissues. However, at present, its identification is made manually leading to high subjectivity, low repeatability and considerable time consumption. We propose an alternative method to automatically identify local AIF in perfusion images using Independent Component Analysis. PMID:26737244

  2. 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.

  3. 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. PMID:27432660

  4. 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.

  5. 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.

  6. 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.

  7. Basic image analysis and manipulation in ImageJ.

    PubMed

    Hartig, Sean M

    2013-01-01

    Image analysis methods have been developed to provide quantitative assessment of microscopy data. In this unit, basic aspects of image analysis are outlined, including software installation, data import, image processing functions, and analytical tools that can be used to extract information from microscopy data using ImageJ. Step-by-step protocols for analyzing objects in a fluorescence image and extracting information from two-color tissue images collected by bright-field microscopy are included.

  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. A comparison of analysis of variance and correlation methods for investigating cognitive development with functional magnetic resonance imaging.

    PubMed

    Fair, Damien A; Brown, Timothy T; Petersen, Steven E; Schlaggar, Bradley L

    2006-01-01

    Statistical approaches used in functional magnetic resonance imaging (fMRI) to study cognitive development are varied and evolving. Two approaches have generally been used. These are between-group end-point analysis of variance (ANOVA) and age-related regression. Differences in these 2 approaches could produce different results when applied to a single data set. Event-related fMRI data from a group of typically developing participants (n = 95; age range = 7-35 years) performing controlled lexical processing tasks were analyzed using both methods. Results from the 2 approaches showed significant overlap, but also noteworthy differences. The results suggest that for regions showing age-related changes, correlation was relatively more sensitive to more linear changes whereas ANOVA was relatively more sensitive to less-linear changes. These findings suggest that full characterization of developmental dynamics will require converging methodologies.

  11. Neural correlates of viewing paintings: evidence from a quantitative meta-analysis of functional magnetic resonance imaging data.

    PubMed

    Vartanian, Oshin; Skov, Martin

    2014-06-01

    Many studies involving functional magnetic resonance imaging (fMRI) have exposed participants to paintings under varying task demands. To isolate neural systems that are activated reliably across fMRI studies in response to viewing paintings regardless of variation in task demands, a quantitative meta-analysis of fifteen experiments using the activation likelihood estimation (ALE) method was conducted. As predicted, viewing paintings was correlated with activation in a distributed system including the occipital lobes, temporal lobe structures in the ventral stream involved in object (fusiform gyrus) and scene (parahippocampal gyrus) perception, and the anterior insula-a key structure in experience of emotion. In addition, we also observed activation in the posterior cingulate cortex bilaterally-part of the brain's default network. These results suggest that viewing paintings engages not only systems involved in visual representation and object recognition, but also structures underlying emotions and internalized cognitions.

  12. Image based performance analysis of thermal imagers

    NASA Astrophysics Data System (ADS)

    Wegner, D.; Repasi, E.

    2016-05-01

    Due to advances in technology, modern thermal imagers resemble sophisticated image processing systems in functionality. Advanced signal and image processing tools enclosed into the camera body extend the basic image capturing capability of thermal cameras. This happens in order to enhance the display presentation of the captured scene or specific scene details. Usually, the implemented methods are proprietary company expertise, distributed without extensive documentation. This makes the comparison of thermal imagers especially from different companies a difficult task (or at least a very time consuming/expensive task - e.g. requiring the execution of a field trial and/or an observer trial). For example, a thermal camera equipped with turbulence mitigation capability stands for such a closed system. The Fraunhofer IOSB has started to build up a system for testing thermal imagers by image based methods in the lab environment. This will extend our capability of measuring the classical IR-system parameters (e.g. MTF, MTDP, etc.) in the lab. The system is set up around the IR- scene projector, which is necessary for the thermal display (projection) of an image sequence for the IR-camera under test. The same set of thermal test sequences might be presented to every unit under test. For turbulence mitigation tests, this could be e.g. the same turbulence sequence. During system tests, gradual variation of input parameters (e. g. thermal contrast) can be applied. First ideas of test scenes selection and how to assembly an imaging suite (a set of image sequences) for the analysis of imaging thermal systems containing such black boxes in the image forming path is discussed.

  13. 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.

  14. Molecular and Functional Imaging of Internet Addiction

    PubMed Central

    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. PMID:25879023

  15. 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.

  16. Phase transfer function of digital imaging systems

    NASA Astrophysics Data System (ADS)

    Bhakta, Vikrant R.

    For the past several decades, optical engineering has relied heavily on Fourier analysis of linear systems as a valuable aid in realizing numerous imaging applications. Today, spatial frequency analysis via the optical transfer function (OTF) remains an integral tool for the design, characterization and testing of incoherent imaging systems. The magnitude of the complex OTF is known as the modulation transfer function (MTF) and its phase is given by the phase transfer function (PTF). The MTF represents the contrast reduction at each spatial frequency; whereas, the PTF represents the spatial shift of these frequencies. While the MTF has been used extensively to characterize imaging systems, the PTF has long been ignored because it was thought to have an insignificant presence and to be difficult to understand and measure. Through theoretical analysis and experimental demonstrations, this work addresses all of these issues and shows that the PTF is a valuable tool for modern-day digital imaging systems. The effects of optical aberrations on the PTF of an imaging system in the absence of aliasing have been analyzed in detail. However, for the digital imaging systems, the effect of aliasing on the overall system behavior becomes an important consideration. To this end, the effects of aliasing on the PTF of the sampled imaging system are described and its key properties are derived. The role of PTF as an essential metric in today's imaging systems necessitates practical PTF measurement techniques. Two, easy-to-implement, image-based methods for PTF measurement are described and experimentally validated. These measurement methods and the insights gained from the theoretical analysis are leveraged for several applications spanning diverse fields such as optical system characterization, computational imaging, and image processing.

  17. Integrating cell biology, image analysis, and computational mechanical modeling to analyze the contributions of cellulose and xyloglucan to stomatal function.

    PubMed

    Rui, Yue; Yi, Hojae; Kandemir, Baris; Wang, James Z; Puri, Virendra M; Anderson, Charles T

    2016-06-01

    Cell walls are likely to be essential determinants of the amazing strength and flexibility of the guard cells that surround each stomatal pore in plants, but surprisingly little is known about cell wall composition, organization, and dynamics in guard cells. Recent analyses of cell wall organization and stomatal function in the guard cells of Arabidopsis thaliana mutants with defects in cellulose and xyloglucan have allowed for the development of new hypotheses about the relative contributions of these components to guard cell function. Advanced image analysis methods can allow for the automated detection of key structures, such as microtubules (MTs) and Cellulose Synthesis Complexes (CSCs), in guard cells, to help determine their contributions to stomatal function. A major challenge in the mechanical modeling of dynamic biological structures, such as guard cell walls, is to connect nanoscale features (e.g., wall polymers and their molecular interactions) with cell-scale mechanics; this challenge can be addressed by applying multiscale computational modeling that spans multiple spatial scales and physical attributes for cell walls.

  18. Integrating cell biology, image analysis, and computational mechanical modeling to analyze the contributions of cellulose and xyloglucan to stomatal function.

    PubMed

    Rui, Yue; Yi, Hojae; Kandemir, Baris; Wang, James Z; Puri, Virendra M; Anderson, Charles T

    2016-06-01

    Cell walls are likely to be essential determinants of the amazing strength and flexibility of the guard cells that surround each stomatal pore in plants, but surprisingly little is known about cell wall composition, organization, and dynamics in guard cells. Recent analyses of cell wall organization and stomatal function in the guard cells of Arabidopsis thaliana mutants with defects in cellulose and xyloglucan have allowed for the development of new hypotheses about the relative contributions of these components to guard cell function. Advanced image analysis methods can allow for the automated detection of key structures, such as microtubules (MTs) and Cellulose Synthesis Complexes (CSCs), in guard cells, to help determine their contributions to stomatal function. A major challenge in the mechanical modeling of dynamic biological structures, such as guard cell walls, is to connect nanoscale features (e.g., wall polymers and their molecular interactions) with cell-scale mechanics; this challenge can be addressed by applying multiscale computational modeling that spans multiple spatial scales and physical attributes for cell walls. PMID:27220916

  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. Analysis of WASp function during the wound inflammatory response--live-imaging studies in zebrafish larvae.

    PubMed

    Cvejic, Ana; Hall, Chris; Bak-Maier, Magdalena; Flores, Maria Vega; Crosier, Phil; Redd, Michael J; Martin, Paul

    2008-10-01

    Wiskott-Aldrich syndrome protein (WASp) is haematopoietically restricted, and is the causative protein underlying a severe human disorder that can lead to death due to immunodeficiency and haemorrhaging. Much is known about the biochemistry of WASp and the migratory capacity of WASp-defective cells in vitro, but in vivo studies of immune-cell behaviour are more challenging. Using the translucency of zebrafish larvae, we live-imaged the effects of morpholino knockdown of WASp1 (also known as Was) on leukocyte migration in response to a wound. In embryos at 22 hours post-fertilisation, primitive macrophages were impaired in their migration towards laser wounds. Once a circulatory system had developed, at 3 days post-fertilisation, we observed significantly reduced recruitment of neutrophils and macrophages to ventral fin wounds. Cell-tracking studies indicated that fewer leukocytes leave the vessels adjacent to a wound and those that do exhibit impaired navigational capacity. Their cell morphology appears unaltered but their choice of leading-edge pseudopodia is more frequently incorrect, leading to impaired chemotaxis. We also identified two zebrafish mutants in WASp1 by TILLING, one of which was in the WIP-binding domain that is the hotspot for human lesions, and mutants exhibited the same deficiencies in wound inflammation and thrombus formation as WASp1 morphants.

  1. Analysis of WASp function during the wound inflammatory response--live-imaging studies in zebrafish larvae.

    PubMed

    Cvejic, Ana; Hall, Chris; Bak-Maier, Magdalena; Flores, Maria Vega; Crosier, Phil; Redd, Michael J; Martin, Paul

    2008-10-01

    Wiskott-Aldrich syndrome protein (WASp) is haematopoietically restricted, and is the causative protein underlying a severe human disorder that can lead to death due to immunodeficiency and haemorrhaging. Much is known about the biochemistry of WASp and the migratory capacity of WASp-defective cells in vitro, but in vivo studies of immune-cell behaviour are more challenging. Using the translucency of zebrafish larvae, we live-imaged the effects of morpholino knockdown of WASp1 (also known as Was) on leukocyte migration in response to a wound. In embryos at 22 hours post-fertilisation, primitive macrophages were impaired in their migration towards laser wounds. Once a circulatory system had developed, at 3 days post-fertilisation, we observed significantly reduced recruitment of neutrophils and macrophages to ventral fin wounds. Cell-tracking studies indicated that fewer leukocytes leave the vessels adjacent to a wound and those that do exhibit impaired navigational capacity. Their cell morphology appears unaltered but their choice of leading-edge pseudopodia is more frequently incorrect, leading to impaired chemotaxis. We also identified two zebrafish mutants in WASp1 by TILLING, one of which was in the WIP-binding domain that is the hotspot for human lesions, and mutants exhibited the same deficiencies in wound inflammation and thrombus formation as WASp1 morphants. PMID:18782862

  2. Magnetic Resonance Imaging Analysis of Dyssynchrony and Myocardial Scar Predicts Function Class Improvement following Cardiac Resynchronization Therapy

    PubMed Central

    Bilchick, Kenneth C.; Dimaano, Veronica; Wu, Katherine C.; Helm, Robert H.; Weiss, Robert G.; Lima, Joao A.; Berger, Ronald D.; Tomaselli, Gordon F.; Bluemke, David A.; Halperin, Henry R.; Abraham, Theodore; Kass, David A.; Lardo, Albert C.

    2009-01-01

    STRUCTURED ABSTRACT Objective We tested a circumferential mechanical dyssynchrony index (circumferential uniformity ratio estimate, or CURE; 0–1, 1=synchrony) derived from magnetic resonance myocardial tagging (MR-MT) for predicting clinical function class improvement following cardiac resynchronization therapy (CRT). Background There remains a significant nonresponse rate to CRT, with recent data questioning the reproducibility of standard echocardiography-based dyssynchrony metrics. MR-MT provides high quality mechanical activation data throughout the heart, and delayed enhancement magnetic resonance imaging (DEMRI) offers precise characterization of myocardial scar and scar distribution. Methods MR-MT was performed in patients with cardiomyopathy, divided into: 1) a CRT-HF cohort (n=20) with mean (SD) LVEF 0.23 (0.057) in order to evaluate the clinical use of MR-MT and DEMRI prior to CRT; and 2) a multimodality cohort (n=27) with mean (SD) LVEF 0.20 (0.066) in order to compare MR-MT and tissue Doppler imaging (TDI) assessments of mechanical dyssynchrony. MR-MT was also performed in 9 healthy control subjects. Results MR-MT showed that control subjects had highly synchronous contraction (mean [SD] CURE 0.96 [0.01]) while TDI septal-lateral delay indicated dyssynchrony in 44% of normal controls. Using a cutoff of <0.75 for CURE based on ROC analysis (AUC 0.889), 56% of patients tested positive for mechanical dyssynchrony, and the MR-MT CURE predicted improved function class in CRT-HF patients with 90% accuracy (PPV 87%; NPV 100%). Adding DEMRI (% total scar<15%) data improved accuracy further to 95% (PPV 93%; NPV 100%). The correlation between CURE and QRSd was modest in all cardiomyopathy subjects (r=0.58, p<0.001), and somewhat less in the CRT-HF group (r=0.40, p=0.08). The multimodality cohort showed a 30% discordance rate between CURE and TDI septal-lateral delay. Conclusions MR-MT assessment of circumferential mechanical dyssynchrony predicts improvement in

  3. 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.

  4. 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

  5. Oncological image analysis.

    PubMed

    Brady, Sir Michael; Highnam, Ralph; Irving, Benjamin; Schnabel, Julia A

    2016-10-01

    Cancer is one of the world's major healthcare challenges and, as such, an important application of medical image analysis. After a brief introduction to cancer, we summarise some of the major developments in oncological image analysis over the past 20 years, but concentrating those in the authors' laboratories, and then outline opportunities and challenges for the next decade.

  6. Reading in the brain of children and adults: a meta-analysis of 40 functional magnetic resonance imaging studies.

    PubMed

    Martin, Anna; Schurz, Matthias; Kronbichler, Martin; Richlan, Fabio

    2015-05-01

    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.

  7. Functional analysis of the rabbit temporomandibular joint using dynamic biplane imaging.

    PubMed

    Henderson, Sarah E; Desai, Riddhi; Tashman, Scott; Almarza, Alejandro J

    2014-04-11

    The dynamic function of the rabbit temporomandibular joint (TMJ) was analyzed through non-invasive, three-dimensional skeletal kinematics, providing essential knowledge for understanding normal joint motion. The objective of this study was to evaluate and determine repeatable measurements of rabbit TMJ kinematics. Maximal distances, as well as paths were traced and analyzed for the incisors and for the condyle-fossa relationship. From one rabbit to another, the rotations and translations of both the incisors and the condyle relative to the fossa contained multiple clear, repeatable patterns. The slope of the superior/inferior incisor distance with respect to the rotation about the transverse axis was repeatable to 0.14 mm/deg and the right/left incisor distance with respect to the rotation about the vertical axis was repeatable to 0.03 mm/deg. The slope of the superior/inferior condylar translation with respect to the rotational movement about the transverse axis showed a consistent relationship to within 0.05 mm/deg. The maximal translations of the incisors and condyles were also consistent within and between rabbits. With an understanding of the normal mechanics of the TMJ, kinematics can be used to compare and understand TMJ injury and degeneration models.

  8. Functional analysis of the rabbit temporomandibular joint using dynamic biplane imaging.

    PubMed

    Henderson, Sarah E; Desai, Riddhi; Tashman, Scott; Almarza, Alejandro J

    2014-04-11

    The dynamic function of the rabbit temporomandibular joint (TMJ) was analyzed through non-invasive, three-dimensional skeletal kinematics, providing essential knowledge for understanding normal joint motion. The objective of this study was to evaluate and determine repeatable measurements of rabbit TMJ kinematics. Maximal distances, as well as paths were traced and analyzed for the incisors and for the condyle-fossa relationship. From one rabbit to another, the rotations and translations of both the incisors and the condyle relative to the fossa contained multiple clear, repeatable patterns. The slope of the superior/inferior incisor distance with respect to the rotation about the transverse axis was repeatable to 0.14 mm/deg and the right/left incisor distance with respect to the rotation about the vertical axis was repeatable to 0.03 mm/deg. The slope of the superior/inferior condylar translation with respect to the rotational movement about the transverse axis showed a consistent relationship to within 0.05 mm/deg. The maximal translations of the incisors and condyles were also consistent within and between rabbits. With an understanding of the normal mechanics of the TMJ, kinematics can be used to compare and understand TMJ injury and degeneration models. PMID:24594064

  9. Functional Analysis of the Rabbit Temporomandibular Joint Using Dynamic Biplane Imaging

    PubMed Central

    Henderson, Sarah E.; Desai, Riddhi; Tashman, Scott; Almarza, Alejandro J.

    2014-01-01

    The dynamic function of the rabbit temporomandibular joint (TMJ) was analyzed through non-invasive three-dimensional skeletal kinematics, providing essential knowledge for understanding normal joint motion. The objective of this study was to evaluate and determine repeatable measurements of rabbit TMJ kinematics. Maximal distances, as well as paths were traced and analyzed for the incisors and for the condyle-fossa relationship. From one rabbit to another, the rotations and translations of both the incisors and the condyle relative to the fossa contained multiple clear, repeatable patterns. The slope of the superior/inferior incisor distance with respect to the rotation about the transverse axis was repeatable to 0.14 mm/degree and the right/left incisor distance with respect to the rotation about the vertical axis was repeatable to 0.03 mm/degree. The slope of the superior/inferior condylar translation with respect to the rotational movement about the transverse axis showed a consistent relationship to within 0.05 mm/degree. The maximal translations of the incisors and condyles were also consistent within and between rabbits. With an understanding of the normal mechanics of the TMJ, kinematics can be used to compare and understand TMJ injury and degeneration models. PMID:24594064

  10. Time series analysis in the time domain and resampling methods for studies of functional magnetic resonance brain imaging.

    PubMed

    Locascio, J J; Jennings, P J; Moore, C I; Corkin, S

    1997-01-01

    Although functional magnetic resonance imaging (fMRI) methods yield rich temporal and spatial data for even a single subject, universally accepted data analysis techniques have not been developed that use all the potential information from fMRI of the brain. Specifically, temporal correlations and confounds are a problem in assessing change within pixels. Spatial correlations across pixels are a problem in determining regions of activation and in correcting for multiple significance tests. We propose methods that address these issues in the analysis of task-related changes in mean signal intensity for individual subjects. Our approach to temporally based problems within pixels is to employ a model based on autoregressive-moving average (ARMA or "Box-Jenkins") time series methods, which we call CARMA (Contrasts and ARMA). To adjust for performing multiple significance tests across pixels, taking into account between-pixel correlations, we propose adjustment of P values with "resampling methods." Our objective is to produce two- or three-dimensional brain maps that provide, at each pixel in the map, an estimated P value with absolute meaning. That is, each P value approximates the probability of having obtained by chance the observed signal effect at that pixel, given that the null hypothesis is true. Simulated and real data examples are provided. PMID:20408214

  11. 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.

  12. Functional morphology analysis of the left anterior descending coronary artery in EBCT images.

    PubMed

    Kakadiaris, Ioannis A; Santamaría-Pang, Alberto; Pednekar, Amol

    2010-08-01

    In this paper, we present a physics-based deformable model framework for morphological and motion analysis of the left anterior descending (LAD) coronary artery. The proposed model is designed to capture the complex motion that the LAD undergoes during the cardiac cycle. The key idea is to define a local coordinate system for the heart and to parameterize both the shape and motion of the LAD in a single framework. The shape of the LAD is modeled as a parametric generalized cylinder, and the motion during the heart cycle is modeled as a composite of three components, which are as follows: 1) longitudinal deformation, 2) radial displacement, and 3) angular displacement over the cardiac cycle. The proposed framework for the LAD shape-motion estimation is generic, since it does not assume any particular tubular shape. Results obtained for four human subjects using electron beam computed tomography data are in agreement with LAD shape-motion deformations reported in the literature. PMID:20176530

  13. 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. PMID:27012301

  14. Functional imaging for regenerative medicine.

    PubMed

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

    2016-01-01

    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

  15. 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.

  16. 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

  17. Functional imaging in Huntington's disease.

    PubMed

    Paulsen, Jane S

    2009-04-01

    Huntington's disease (HD) is a genetic brain disease characterized by loss of capacity in movement control, cognition, and emotional regulation over a period of about 30 years. Since it is well established that clinical impairments and brain atrophy can be detected decades prior to receiving a clinical diagnosis, functional neuroimaging efforts have gained momentum in HD research. In most brain disorders, there is accumulating evidence that the clinical manifestations of disease do not simply depend on the extent of tissue loss, but represent a complex balance among neuronal dysfunction, tissue repair, and circuitry reorganization. Based upon this premise, functional neuroimaging modalities may be more sensitive to the earliest changes in HD than are structural imaging approaches. For this review, PET and fMRI studies conducted in HD samples were summarized. Strengths and limitations of the utilization of functional imaging in HD are discussed and recommendations are offered to facilitate future research endeavors.

  18. Dynamic imaging of brain function

    PubMed Central

    Hyder, Fahmeed

    2013-01-01

    In recent years, there have been unprecedented methodological advances in the dynamic imaging of brain activities. Electrophysiological, optical, and magnetic resonance methods now allow mapping of functional activation (or deactivation) by measurement of neuronal activity (e.g., membrane potential, ion flux, neurotransmitter flux), energy metabolism (e.g., glucose consumption, oxygen consumption, creatine kinase flux), and functional hyperemia (e.g., blood oxygenation, blood flow, blood volume). Properties of the glutamatergic synapse are used as a model to reveal activities at the nerve terminal and their associated changes in energy demand and blood flow. This approach reveals that each method measures different tissue- and/or cell-specific components with specified spatiotemporal resolution. While advantages and disadvantages of different methods are apparent and often used to supersede one another in terms of specificity and/or sensitivity, no particular technique is the optimal dynamic brain imaging method because each method is unique in some respect. Because the demand for energy substrates is a fundamental requirement for function, energy-based methods may allow quantitative dynamic imaging in vivo. However there are exclusive neurobiological insights gained by combining some of these different dynamic imaging techniques. PMID:18839085

  19. The role of the right hemisphere in metaphor comprehension: a meta-analysis of functional magnetic resonance imaging studies.

    PubMed

    Yang, Jie

    2014-01-01

    The role of the right hemisphere (RH) in metaphor comprehension is still controversial. Numerous neuroimaging studies have found that conventionality, sentential context, and task demand can influence the involvement of the RH in metaphor processing. The current meta-analysis used foci from 17 original functional magnetic resonance imaging studies to identify what factors modulate the involvement of the RH in metaphor processing. Activation likelihood estimation was used for quantification. We focused on the contrast of metaphorical meaning processing versus literal meaning processing and calculated the meta-analysis effects when (1) metaphorical meaning is conventional, (2) metaphorical meaning is novel, (3) metaphorical and literal meaning are presented in words, (4) metaphorical and literal meaning are presented in sentential context, (5) task is valence judgment, and (6) task is semantic relatedness judgment. The results indicated that the RH only showed significant effects in metaphor processing when the metaphorical meaning is novel, when metaphorical meaning is presented in sentential context, and when the task is semantic relatedness judgment. The effects were located in right fronto-temporal regions, including inferior frontal gyrus, middle frontal gyrus, insula, superior temporal gyrus, and middle temporal gyrus. These results suggest that conventionality, contextual complexity, and task demand can modulate the effect of figurativeness and influence the involvement of RH in metaphor comprehension. The main role of the RH in metaphor processing is related with activating broad semantic fields and integrating concepts that may have distant semantic relations, and hence provide support for the view that the RH is responsible for processing coarse semantic information in language comprehension.

  20. Reducing Inter-subject Anatomical Variation: Effect of Normalization Method on Sensitivity of Functional Magnetic Resonance Imaging Data Analysis in Auditory Cortex and the Superior Temporal Region

    PubMed Central

    Tahmasebi, Amir M.; Abolmaesumi, Purang; Zheng, Zane Z.; Munhall, Kevin G.; Johnsrude, Ingrid S.

    2009-01-01

    Conventional group analysis of functional MRI (fMRI) data usually involves spatial alignment of anatomy across participants by registering every brain image to an anatomical reference image. Due to the high degree of inter-subject anatomical variability, a low-resolution average anatomical model is typically used as the target template, and/or smoothing kernels are applied to the fMRI data to increase the overlap among subjects’ image data. However, such smoothing can make it difficult to resolve small regions such as subregions of auditory cortex when anatomical morphology varies among subjects. Here, we use data from an auditory fMRI study to show that using a high-dimensional registration technique (HAMMER) results in an enhanced functional signal-to-noise ratio (fSNR) for functional data analysis within auditory regions, with more localized activation patterns. The technique is validated against DARTEL, a high-dimensional diffeomorphic registration, as well as against commonly used low-dimensional normalization techniques such as the techniques provided with SPM2 (cosine basis functions) and SPM5 (unified segmentation) software packages. We also systematically examine how spatial resolution of the template image and spatial smoothing of the functional data affect the results. Only the high-dimensional technique (HAMMER) appears to be able to capitalize on the excellent anatomical resolution of a single-subject reference template, and, as expected, smoothing increased fSNR, but at the cost of spatial resolution. In general, results demonstrate significant improvement in fSNR using HAMMER compared to analysis after normalization using DARTEL, or conventional normalization such as cosine basis function and unified segmentation in SPM, with more precisely localized activation foci, at least for activation in the region of auditory cortex. PMID:19481162

  1. 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.

  2. 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.

  3. Image Analysis of Foods.

    PubMed

    Russ, John C

    2015-09-01

    The structure of foods, both natural and processed ones, is controlled by many variables ranging from biology to chemistry and mechanical forces. The structure also controls many of the properties of the food, including consumer acceptance, taste, mouthfeel, appearance, and so on, and nutrition. Imaging provides an important tool for measuring the structure of foods. This includes 2-dimensional (2D) images of surfaces and sections, for example, viewed in a microscope, as well as 3-dimensional (3D) images of internal structure as may be produced by confocal microscopy, or computed tomography and magnetic resonance imaging. The use of images also guides robotics for harvesting and sorting. Processing of images may be needed to calibrate colors, reduce noise, enhance detail, and delineate structure and dimensions. Measurement of structural information such as volume fraction and internal surface areas, as well as the analysis of object size, location, and shape in both 2- and 3-dimensional images is illustrated and described, with primary references and examples from a wide range of applications. PMID:26270611

  4. 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.

  5. Functional imaging in Tourette's syndrome.

    PubMed

    Adams, J R; Troiano, A R; Calne, D B

    2004-10-01

    The cause or causes of Tourette's syndrome (TS) remain unknown. Functional imaging studies have evaluated several implicated neurotransmitter systems and focused predominantly on the frequency or severity of tics. The results have been inconclusive and frequently contradictory with little light shed on pathogenetic mechanisms. However, metabolic derangements have been demonstrated within regions of the basal ganglia, limbic system and sensori-motor cortex and are in keeping with the concept of TS as both a motor and behavioral disorder. TS has long been regarded an involuntary movement disorder. However, many patients have stated that without the premonitory sensation, there would be no tics. For this reason, it has been suggested that the premonitory urge may be considered the involuntary component of TS and the performance of the tic merely a voluntary response. Future studies are needed to differentiate functional changes relating to urge from those associated with the performance of tics and tic suppression.

  6. Quantification of global left ventricular function: comparison of multidetector computed tomography and magnetic resonance imaging. a meta-analysis and review of the current literature.

    PubMed

    van der Vleuten, P A; Willems, T P; Götte, M J W; Tio, R A; Greuter, M J W; Zijlstra, F; Oudkerk, M

    2006-12-01

    Cardiac morbidity and mortality are closely related to cardiac volumes and global left ventricular (LV) function, expressed as left ventricular ejection fraction. Accurate assessment of these parameters is required for the prediction of prognosis in individual patients as well as in entire cohorts. The current standard of reference for left ventricular function is analysis by short-axis magnetic resonance imaging. In recent years, major extensive technological improvements have been achieved in computed tomography. The most marked development has been the introduction of the multidetector CT (MDCT), which has significantly improved temporal and spatial resolutions. In order to assess the current status of MDCT for analysis of LV function, the current available literature on this subject was reviewed. The data presented in this review indicate that the global left ventricular functional parameters measured by contemporary multi-detector row systems combined with adequate reconstruction algorithms and post-processing tools show a narrow diagnostic window and are interchangeable with those obtained by MRI.

  7. 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. PMID:16894996

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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

  13. Global lithospheric imaging using teleseismic receiver functions

    NASA Astrophysics Data System (ADS)

    Rondenay, S.; Spieker, K.; Halpaap, F.; Farestveit, M.; Sawade, L.; Zijerveld, L.

    2015-12-01

    Project GLImER (Global Lithospheric Imagining using Earthquake Recordings) aims to conduct a global survey of lithospheric interfaces using converted teleseismic body waves. Data from permanent and temporary seismic networks worldwide will be processed automatically to produce global maps of key interfaces (Moho, intra-lithospheric interfaces, lithosphere-asthenosphere boundary). In this presentation, we discuss the challenges associated with automating the analysis of converted waves and the potential of the resulting data products to be used in novel imaging approaches. With regards to automation, we address in particular the search for an optimal deconvolution method in receiver function analysis. To do so, we carry out a systematic comparison of various commonly used deconvolution methods and find that all methods produce equally robust receiver functions provided that a suitable regularization parameter is found. We further note that a suitable regularization can be found objectively for most approaches, thus challenging the belief that only time-domain deconvolution is a viable option for receiver function automation. With regards to imaging applications, we investigate how the resulting global database of receiver functions will be amenable to existing processing approaches as well as new approaches adapted from seismic exploration, including industry-based interpretation tools.

  14. 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.

  15. Feasibility of functional imaging for brachytherapy

    PubMed Central

    2009-01-01

    This review summarizes the current understanding of the feasibility of functional imaging for brachytherapy. In following subsections the role of ultrasound, power doppler imaging, positron emission tomography, magnetic resonance imaging, dynamic dose calculation and targeted brachytherapy is analyzed. The combination of functional imaging with the new tools for intraoperative dose calculation and optimization opens new and exciting times in brachytherapy. New optimized protocols are needed and should be tested in controlled trials, to demonstrate an advantage of such a new paradigm.

  16. 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.

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

    PubMed

    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

  18. 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

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

    PubMed Central

    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. PMID:25165444

  20. Structured Functional Principal Component Analysis

    PubMed Central

    Shou, Haochang; Zipunnikov, Vadim; Crainiceanu, Ciprian M.; Greven, Sonja

    2015-01-01

    Summary Motivated by modern observational studies, we introduce a class of functional models that expand nested and crossed designs. These models account for the natural inheritance of the correlation structures from sampling designs in studies where the fundamental unit is a function or image. Inference is based on functional quadratics and their relationship with the underlying covariance structure of the latent processes. A computationally fast and scalable estimation procedure is developed for high-dimensional data. Methods are used in applications including high-frequency accelerometer data for daily activity, pitch linguistic data for phonetic analysis, and EEG data for studying electrical brain activity during sleep. PMID:25327216

  1. Characteristic functionals in imaging and image-quality assessment: tutorial.

    PubMed

    Clarkson, Eric; Barrett, Harrison H

    2016-08-01

    Characteristic functionals are one of the main analytical tools used to quantify the statistical properties of random fields and generalized random fields. The viewpoint taken here is that a random field is the correct model for the ensemble of objects being imaged by a given imaging system. In modern digital imaging systems, random fields are not used to model the reconstructed images themselves since these are necessarily finite dimensional. After a brief introduction to the general theory of characteristic functionals, many examples relevant to imaging applications are presented. The propagation of characteristic functionals through both a binned and list-mode imaging system is also discussed. Methods for using characteristic functionals and image data to estimate population parameters and classify populations of objects are given. These methods are based on maximum likelihood and maximum a posteriori techniques in spaces generated by sampling the relevant characteristic functionals through the imaging operator. It is also shown how to calculate a Fisher information matrix in this space. These estimators and classifiers, and the Fisher information matrix, can then be used for image quality assessment of imaging systems.

  2. 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.

  3. Functional optical imaging at the microscopic level

    PubMed Central

    Salazar Vázquez, Beatriz Y.; Hightower, Ciel Makena; Sapuppo, Francesca; Tartakovsky, Daniel M.; Intaglietta, Marcos

    2010-01-01

    Functional microscopic imaging of in vivo tissues aims at characterizing parameters at the level of the unitary cellular components under normal conditions, in the presence of blood flow, to understand and monitor phenomena that lead to maintaining homeostatic balance. Of principal interest are the setting of shear stress on the endothelium; formation of the plasma layer, where the balance between nitric oxide production and scavenging is established; and formation of the oxygen gradients that determine the distribution of oxygen from blood into the tissue. Optical techniques that enable the analysis of functional microvascular processes are the measurement of blood vessel dimensions by image shearing, the photometric analysis of the extent of the plasma layer, the dual-slit methodology for measuring blood flow velocity, and the direct measurement of oxygen concentration in blood and tissue. Each of these technologies includes the development of paired, related mathematical approaches that enable characterizing the transport properties of the blood tissue system. While the technology has been successful in analyzing the living tissue in experimental conditions, deployment to clinical settings remains an elusive goal, due to the difficulty of obtaining optical access to the depth of the tissue. PMID:20210428

  4. 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.…

  5. A 3D image analysis tool for SPECT imaging

    NASA Astrophysics Data System (ADS)

    Kontos, Despina; Wang, Qiang; Megalooikonomou, Vasileios; Maurer, Alan H.; Knight, Linda C.; Kantor, Steve; Fisher, Robert S.; Simonian, Hrair P.; Parkman, Henry P.

    2005-04-01

    We have developed semi-automated and fully-automated tools for the analysis of 3D single-photon emission computed tomography (SPECT) images. The focus is on the efficient boundary delineation of complex 3D structures that enables accurate measurement of their structural and physiologic properties. We employ intensity based thresholding algorithms for interactive and semi-automated analysis. We also explore fuzzy-connectedness concepts for fully automating the segmentation process. We apply the proposed tools to SPECT image data capturing variation of gastric accommodation and emptying. These image analysis tools were developed within the framework of a noninvasive scintigraphic test to measure simultaneously both gastric emptying and gastric volume after ingestion of a solid or a liquid meal. The clinical focus of the particular analysis was to probe associations between gastric accommodation/emptying and functional dyspepsia. Employing the proposed tools, we outline effectively the complex three dimensional gastric boundaries shown in the 3D SPECT images. We also perform accurate volume calculations in order to quantitatively assess the gastric mass variation. This analysis was performed both with the semi-automated and fully-automated tools. The results were validated against manual segmentation performed by a human expert. We believe that the development of an automated segmentation tool for SPECT imaging of the gastric volume variability will allow for other new applications of SPECT imaging where there is a need to evaluate complex organ function or tumor masses.

  6. 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. PMID:27503078

  7. 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.

  8. 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…

  9. Uncooled thermal imaging and image analysis

    NASA Astrophysics Data System (ADS)

    Wang, Shiyun; Chang, Benkang; Yu, Chunyu; Zhang, Junju; Sun, Lianjun

    2006-09-01

    Thermal imager can transfer difference of temperature to difference of electric signal level, so can be application to medical treatment such as estimation of blood flow speed and vessel 1ocation [1], assess pain [2] and so on. With the technology of un-cooled focal plane array (UFPA) is grown up more and more, some simple medical function can be completed with un-cooled thermal imager, for example, quick warning for fever heat with SARS. It is required that performance of imaging is stabilization and spatial and temperature resolution is high enough. In all performance parameters, noise equivalent temperature difference (NETD) is often used as the criterion of universal performance. 320 x 240 α-Si micro-bolometer UFPA has been applied widely presently for its steady performance and sensitive responsibility. In this paper, NETD of UFPA and the relation between NETD and temperature are researched. several vital parameters that can affect NETD are listed and an universal formula is presented. Last, the images from the kind of thermal imager are analyzed based on the purpose of detection persons with fever heat. An applied thermal image intensification method is introduced.

  10. Conflict Processing in the Rat Brain: Behavioral Analysis and Functional μPET Imaging Using [18F]Fluorodeoxyglucose

    PubMed Central

    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 [18F]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. PMID:22363272

  11. 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.

  12. 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

  13. 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.

  14. Functional imaging as an indicator of diagnostic information in cardiac magnetic-resonance images

    NASA Astrophysics Data System (ADS)

    Klingler, Joseph W.; Andrews, Lee T.; Begeman, Michael S.; Zeiss, Jacob; Leighton, Richard F.

    1990-08-01

    Magnetic Resonance (MR) images of the human heart provide three dimensional geometric information about the location of cardiac structures throughout the cardiac cycle. Analysis of this four dimensional data set allows detection of abnormal cardiac function related to the presence of coronary artery disease. To assist in this analysis, quantitative measurements of cardiac performance are made from the MR data including ejection fractions, regional wall motion and myocardial wall thickening. Analysis of cardiac performance provided by quantitative analysis of MR data can be aided by computer graphics presentation techniques. Two and three dimensional functional images are computed to indicate regions of abnormality based on the previous methods. The two dimensional images are created using color graphics overlays on the original MR image to represent performance. Polygon surface modeling techniques are used to represent data which is three dimensional, such as blood pool volumes. The surface of these images are color encoded by regional ejection fraction, wall motion or wall thickening. A functional image sequence is constructed at each phase of the cardiac cycle and displayed as a movie loop for review by the physician. Selection of a region on the functional image allows visual interpretation of the original MR images, graphical plots of cardiac function and tabular results. Color encoding is based on absolute measurements and comparison to standard normal templates of cardiac performance.

  15. 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.

  16. Functional imaging of the musculoskeletal system.

    PubMed

    Griffith, James F

    2015-06-01

    Functional imaging, which provides information of how tissues function rather than structural information, is well established in neuro- and cardiac imaging. Many musculoskeletal structures, such as ligaments, fascia and mineralized bone, have by definition a mainly structural role and clearly don't have the same functional capacity as the brain, heart, liver or kidney. The main functionally responsive musculoskeletal tissues are the bone marrow, muscle and nerve and, as such, magnetic resonance (MR) functional imaging has primarily addressed these areas. Proton or phosphorus spectroscopy, other fat quantification techniques, perfusion imaging, BOLD imaging, diffusion and diffusion tensor imaging (DTI) are the main functional techniques applied. The application of these techniques in the musculoskeletal system has mainly been research orientated where they have already greatly enhanced our understanding of marrow physiology, muscle physiology and neural function. Going forwards, they will have a greater clinical impact helping to bridge the disconnect often seen between structural appearances and clinical symptoms, allowing a greater understanding of disease processes and earlier recognition of disease, improving prognostic prediction and optimizing the monitoring of treatment effect. PMID:26029633

  17. 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.

  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. 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

  20. An analysis of whole body tracer kinetics in dynamic PET studies with application to image-based blood input function extraction.

    PubMed

    Huang, Jian; O'Sullivan, Finbarr

    2014-05-01

    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.

  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. Myocardial motion and function assessment using 4D images

    NASA Astrophysics Data System (ADS)

    Shi, Peng-Cheng; Robinson, Glynn P.; Duncan, James S.

    1994-09-01

    This paper describes efforts aimed at more objectively and accurately quantifying the local, regional and global function of the left ventricle (LV) of the heart from 4D image data. Using our shape-based image analysis methods, point-wise myocardial motion vector fields between successive image frames through the entire cardiac cycle will be computed. Quantitative LV motion, thickening, and strain measurements will then be established from the point correspondence maps. In the paper, we will also briefly describe an in vivo experimental model which uses implanted imaging-opaque markers to validate the results of our image analysis methods. Finally, initial experimental results using image sequences from two different modalities will be presented.

  3. 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.

  4. 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.

  5. 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

  6. The influence of motor expertise on the brain activity of motor task performance: A meta-analysis of functional magnetic resonance imaging studies.

    PubMed

    Yang, Jie

    2015-06-01

    Previous research has investigated the influence of long-term motor training on the brain activity of motor processes, but the findings are inconsistent. To clarify how acquiring motor expertise induces cortical reorganization during motor task performance, the current study conducted a quantitative meta-analysis on 26 functional magnetic resonance imaging (fMRI) studies that investigate motor task performance in people with long-term motor training experience (e.g., athletes, musicians, and dancers) and control participants. Meta-analysis of the brain activation in motor experts and novices showed similar effects in the bilateral frontal and parietal regions. The meta-analysis on the contrast between motor experts and novices indicated that experts showed stronger effects in the left inferior parietal lobule (BA 40) than did novices in motor execution and prediction tasks. In motor observation tasks, experts showed stronger effects in the left inferior frontal gyrus (BA 9) and left precentral gyrus (BA 6) than novices. On the contrary, novices had stronger effects in the right motor areas and basal ganglia as compared with motor experts. These results indicate that motor experts have effect increases in brain areas involved in action planning and action comprehension, and suggest that intensive motor training might elaborate the motor representation related to the task performance.

  7. 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.

  8. Modeling of functional brain imaging data

    NASA Astrophysics Data System (ADS)

    Horwitz, Barry

    1999-03-01

    The richness and complexity of data sets obtained from functional neuroimaging studies of human cognitive behavior, using techniques such as positron emission tomography and functional magnetic resonance imaging, have until recently not been exploited by computational neural modeling methods. In this article, following a brief introduction to functional neuroimaging methodology, two neural modeling approaches for use with functional brain imaging data are described. One, which uses structural equation modeling, examines the effective functional connections between various brain regions during specific cognitive tasks. The second employs large-scale neural modeling to relate functional neuroimaging signals in multiple, interconnected brain regions to the underlying neurobiological time-varying activities in each region. These two modeling procedures are illustrated using a visual processing paradigm.

  9. 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

  10. 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.

  11. Image sharpness function based on edge feature

    NASA Astrophysics Data System (ADS)

    Jun, Ni

    2009-11-01

    Autofocus technique has been widely used in optical tracking and measure system, but it has problem that when the autofocus device should to work. So, no-reference image sharpness assessment has become an important issue. A new Sharpness Function that can estimate current frame image be in focus or not is proposed in this paper. According to current image whether in focus or not and choose the time of auto focus automatism. The algorithm measures object typical edge and edge direction, and then get image local kurtosis information to determine the degree of image sharpness. It firstly select several grads points cross the edge line, secondly calculates edge sharpness value and get the cure of the kurtosis, according the measure precision of optical-equipment, a threshold value will be set beforehand. If edge kurtosis value is more than threshold, it can conclude current frame image is in focus. Otherwise, it is out of focus. If image is out of focus, optics system then takes autofocus program. This algorithm test several thousands of digital images captured from optical tracking and measure system. The results show high correlation with subjective sharpness assessment for s images of sky object.

  12. 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.

  13. 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.

  14. Malware analysis using visualized image matrices.

    PubMed

    Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

    2014-01-01

    This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively. PMID:25133202

  15. Malware Analysis Using Visualized Image Matrices

    PubMed Central

    Im, Eul Gyu

    2014-01-01

    This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively. PMID:25133202

  16. Malware analysis using visualized image matrices.

    PubMed

    Han, KyoungSoo; Kang, BooJoong; Im, Eul Gyu

    2014-01-01

    This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. The proposed method generates RGB-colored pixels on image matrices using the opcode sequences extracted from malware samples and calculates the similarities for the image matrices. Particularly, our proposed methods are available for packed malware samples by applying them to the execution traces extracted through dynamic analysis. When the images are generated, we can reduce the overheads by extracting the opcode sequences only from the blocks that include the instructions related to staple behaviors such as functions and application programming interface (API) calls. In addition, we propose a technique that generates a representative image for each malware family in order to reduce the number of comparisons for the classification of unknown samples and the colored pixel information in the image matrices is used to calculate the similarities between the images. Our experimental results show that the image matrices of malware can effectively be used to classify malware families both statically and dynamically with accuracy of 0.9896 and 0.9732, respectively.

  17. Image Analysis in Surgical Pathology.

    PubMed

    Lloyd, Mark C; Monaco, James P; Bui, Marilyn M

    2016-06-01

    Digitization of glass slides of surgical pathology samples facilitates a number of value-added capabilities beyond what a pathologist could previously do with a microscope. Image analysis is one of the most fundamental opportunities to leverage the advantages that digital pathology provides. The ability to quantify aspects of a digital image is an extraordinary opportunity to collect data with exquisite accuracy and reliability. In this review, we describe the history of image analysis in pathology and the present state of technology processes as well as examples of research and clinical use. PMID:27241112

  18. Design Criteria For Networked Image Analysis System

    NASA Astrophysics Data System (ADS)

    Reader, Cliff; Nitteberg, Alan

    1982-01-01

    Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

  19. Image Chain Analysis For Digital Image Rectification System

    NASA Astrophysics Data System (ADS)

    Arguello, Roger J.

    1981-07-01

    An image chain analysis, utilizing a comprehensive computer program, has been gen-erated for the key elements of a digital image rectification system. System block dia-grams and analyses for three system configurations employing film scanner input have been formulated with a parametric specification of pertinent element modulation transfer functions and input film scene spectra. The major elements of the system for this analy-sis include a high-resolution, high-speed charge-coupled device film scanner, three candidate digital resampling option algorithms (i.e., nearest neighbor, bilinear inter-polation and cubic convolution methods), and two candidate printer reconstructor implemen-tations (solid-state light-emitting diode printer and laser beam recorder). Suitable metrics for the digital rectification system, incorporating the effects of interpolation and resolution error, were established, and the image chain analysis program was used to perform a quantitative comparison of the three resampling options with the two candi-date printer reconstructor implementations. The nearest neighbor digital resampling function is found to be a good compromise choice when cascaded with either a light-emit-ting diode printer or laser beam recorder. The resulting composite intensity point spread functions, including resampling, and both types of reconstruction are bilinear and quadratic, respectively.

  20. 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.

  1. Independent component analysis applied to pharmacological magnetic resonance imaging (phMRI): new insights into the functional networks underlying panic attacks as induced by CCK-4.

    PubMed

    Dieler, A C; Sämann, P G; Leicht, G; Eser, D; Kirsch, V; Baghai, T C; Karch, S; Schüle, C; Pogarell, O; Czisch, M; Rupprecht, R; Mulert, C

    2008-01-01

    Pharmacological magnetic resonance imaging (phMRI) is a method to study effects of psychopharmacological agents on neural activation. Changes of the blood oxygen level dependent (BOLD), the basis of functional MRI (fMRI), are typically obtained at relatively high sampling frequencies. This has more recently been exploited in the field of fMRI by applying independent component analysis (ICA), an explorative data analysis method decomposing activation into distinct neural networks. While already successfully used to investigate resting network and task-induced activity, its use in phMRI is new. Further extension of this method to tensorial probabilistic ICA (tensor PICA) allows to group similar brain activation across the anatomical, temporal, subject or session domain. This approach is useful for pharmacological experiments when no pharmacokinetic model exists. We exemplify this method using data from a placebo-controlled cholecystokinine-4 (CCK-4) injection experiment performed on 16 neuropsychiatrically and medically healthy males (age 25.6 +/- 4.2 years). Tensor PICA identified strong increases in activity in 12 networks. Comparison with results gained from the standard approach (voxelwise regression analysis) revealed good reproduction of areas previously associated with CCK-4 action, such as the anterior cingulate, orbitofrontal cortex, cerebellum, temporolateral, left parietal and insular areas, striatum, and precuneus. Several other components such as the dorsal anterior cingulate and medial prefrontal cortex were identified, suggesting higher sensitivity of the method. Exploration of the time courses of each activated network revealed differences, that might be lost when a fixed time course is modeled, e. g. neuronal responses to an acoustic warning signal prior to injection. Comparison of placebo and CCK-4 runs further showed that a proportion of networks are newly elicited by CCK-4 whereas other components are significantly active in the placebo conditions

  2. 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.

  3. 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

  4. Functional lumen imaging of the gastrointestinal tract.

    PubMed

    Lottrup, Christian; Gregersen, Hans; Liao, Donghua; Fynne, Lotte; Frøkjær, Jens Brøndum; Krogh, Klaus; Regan, Julie; Kunwald, Peter; McMahon, Barry P

    2015-10-01

    This nonsystematic review aims to describe recent developments in the use of functional lumen imaging in the gastrointestinal tract stimulated by the introduction of the functional lumen imaging probe. When ingested food in liquid and solid form is transported along the gastrointestinal tract, sphincters provide an important role in the flow and control of these contents. Inadequate function of sphincters is the basis of many gastrointestinal diseases. Despite this, traditional methods of sphincter diagnosis and measurement such as fluoroscopy, manometry, and the barostat are limited in what they can tell us. It has long been thought that measurement of sphincter function through resistance to distension is a better approach, now more commonly known as distensibility testing. The functional lumen imaging probe is the first medical measurement device that purports in a practical way to provide geometric profiling and measurement of distensibility in sphincters. With use of impedance planimetry, an axial series of cross-sectional areas and pressure in a catheter-mounted allantoid bag are used for the calculation of distensibility parameters. The technique has been trialed in many valvular areas of the gastrointestinal tract, including the upper esophageal sphincter, the esophagogastric junction, and the anorectal region. It has shown potential in the biomechanical assessment of sphincter function and characterization of swallowing disorders, gastroesophageal reflux disease, eosinophilic esophagitis, achalasia, and fecal incontinence. From this early work, the functional lumen imaging technique has the potential to contribute to a better and more physiological understanding of narrowing regions in the gastrointestinal tract in general and sphincters in particular. PMID:25980822

  5. 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…

  6. Automatic analysis of macroarrays images.

    PubMed

    Caridade, C R; Marcal, A S; Mendonca, T; Albuquerque, P; Mendes, M V; Tavares, F

    2010-01-01

    The analysis of dot blot (macroarray) images is currently based on the human identification of positive/negative dots, which is a subjective and time consuming process. This paper presents a system for the automatic analysis of dot blot images, using a pre-defined grid of markers, including a number of ON and OFF controls. The geometric deformations of the input image are corrected, and the individual markers detected, both tasks fully automatically. Based on a previous training stage, the probability for each marker to be ON is established. This information is provided together with quality parameters for training, noise and classification, allowing for a fully automatic evaluation of a dot blot image. PMID:21097139

  7. 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. PMID:11051496

  8. 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.

  9. 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.

  10. Analysis of autostereoscopic three-dimensional images using multiview wavelets.

    PubMed

    Saveljev, Vladimir; Palchikova, Irina

    2016-08-10

    We propose that multiview wavelets can be used in processing multiview images. The reference functions for the synthesis/analysis of multiview images are described. The synthesized binary images were observed experimentally as three-dimensional visual images. The symmetric multiview B-spline wavelets are proposed. The locations recognized in the continuous wavelet transform correspond to the layout of the test objects. The proposed wavelets can be applied to the multiview, integral, and plenoptic images. PMID:27534470

  11. 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…

  12. Functional imaging in freely moving animals.

    PubMed

    Kerr, Jason N D; Nimmerjahn, Axel

    2012-02-01

    Uncovering the relationships between animal behavior and cellular activity in the brain has been one of the key aims of neuroscience research for decades, and still remains so. Electrophysiological approaches have enabled sparse sampling from electrically excitable cells in freely moving animals that has led to the identification of important phenomena such as place, grid and head-direction cells. Optical imaging in combination with newly developed labeling approaches now allows minimally invasive and comprehensive sampling from dense networks of electrically and chemically excitable cells such as neurons and glia during self-determined behavior. To achieve this two main imaging avenues have been followed: Optical recordings in head-restrained, mobile animals and miniature microscope-bearing freely moving animals. Here we review progress made toward functional cellular imaging in freely moving rodents, focusing on developments over the past few years. We discuss related challenges and biological applications.

  13. 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.

  14. Functional magnetic resonance imaging using RASER

    PubMed Central

    Goerke, Ute; Garwood, Michael; Ugurbil, Kamil

    2010-01-01

    Although functional imaging of neuronal activity by magnetic resonance imaging (fMRI) has become the primary methodology employed in studying the brain, significant portions of the brain are inaccessible by this methodology due to its sensitivity to macroscopic magnetic field inhomogeneities induced near air filled cavities in the head. In this paper, we demonstrate that this sensitivity is eliminated by a novel pulse sequence, RASER (rapid acquisition by sequential excitation and refocusing) (Chamberlain et al., 2007), that can generate functional maps. This is accomplished because RASER acquired signals are purely and perfectly T2 weighted, without any T2*-effects that are inherent in the other image acquisition schemes employed to date. T2-weighted fMRI sequences are also more specific to the site of neuronal activity at ultrahigh magnetic fields than T2*-variations since they are dominated by signal components originating from the tissue in the capillary bed. The RASER based fMRI response is quantified; it is shown to have inherently less noisy time series and to provide fMRI in brain regions, such as the orbitofrontal cortex, which are challenging to image with conventional techniques. PMID:20699123

  15. Functional plasticity before the cradle: a review of neural functional imaging in the human fetus.

    PubMed

    Anderson, Amy L; Thomason, Moriah E

    2013-11-01

    The organization of the brain is highly plastic in fetal life. Establishment of healthy neural functional systems during the fetal period is essential to normal growth and development. Across the last several decades, remarkable progress has been made in understanding the development of human fetal functional brain systems. This is largely due to advances in imaging methodologies. Fetal neuroimaging began in the 1950-1970's with fetal electroencephalography (EEG) applied during labor. Later, in the 1980's, magnetoencephalography (MEG) emerged as an effective approach for investigating fetal brain function. Most recently, functional magnetic resonance imaging (fMRI) has arisen as an additional powerful approach for examining fetal brain function. This review will discuss major developmental findings from fetal imaging studies such as the maturation of prenatal sensory system functions, functional hemispheric asymmetry, and sensory-driven neurodevelopment. We describe how with improved imaging and analysis techniques, functional imaging of the fetus has the potential to assess the earliest point of neural maturation and provide insight into the patterning and sequence of normal and abnormal brain development.

  16. 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.

  17. Electroencephalographic imaging of higher brain function.

    PubMed Central

    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. PMID:10466140

  18. Millisecond single-molecule localization microscopy combined with convolution analysis and automated image segmentation to determine protein concentrations in complexly structured, functional cells, one cell at a time.

    PubMed

    Wollman, Adam J M; Leake, Mark C

    2015-01-01

    We present a single-molecule tool called the CoPro (concentration of proteins) method that uses millisecond imaging with convolution analysis, automated image segmentation and super-resolution localization microscopy to generate robust estimates for protein concentration in different compartments of single living cells, validated using realistic simulations of complex multiple compartment cell types. We demonstrate its utility experimentally on model Escherichia coli bacteria and Saccharomyces cerevisiae budding yeast cells, and use it to address the biological question of how signals are transduced in cells. Cells in all domains of life dynamically sense their environment through signal transduction mechanisms, many involving gene regulation. The glucose sensing mechanism of S. cerevisiae is a model system for studying gene regulatory signal transduction. It uses the multi-copy expression inhibitor of the GAL gene family, Mig1, to repress unwanted genes in the presence of elevated extracellular glucose concentrations. We fluorescently labelled Mig1 molecules with green fluorescent protein (GFP) via chromosomal integration at physiological expression levels in living S. cerevisiae cells, in addition to the RNA polymerase protein Nrd1 with the fluorescent protein reporter mCherry. Using CoPro we make quantitative estimates of Mig1 and Nrd1 protein concentrations in the cytoplasm and nucleus compartments on a cell-by-cell basis under physiological conditions. These estimates indicate a ∼4-fold shift towards higher values in the concentration of diffusive Mig1 in the nucleus if the external glucose concentration is raised, whereas equivalent levels in the cytoplasm shift to smaller values with a relative change an order of magnitude smaller. This compares with Nrd1 which is not involved directly in glucose sensing, and which is almost exclusively localized in the nucleus under high and low external glucose levels. CoPro facilitates time-resolved quantification of

  19. Functional Doppler optical coherence tomography for cortical blood flow imaging

    NASA Astrophysics Data System (ADS)

    Yu, Lingfeng; Liu, Gangjun; Nguyen, Elaine; Choi, Bernard; Chen, Zhongping

    2010-02-01

    Optical methods have been widely used in basic neuroscience research to study the cerebral blood flow dynamics in order to overcome the low spatial resolution associated with magnetic resonance imaging and positron emission tomography. Although laser Doppler imaging and laser speckle imaging can map out en face cortical hemodynamics and columns, depth resolution is not available. Two-photon microscopy has been used for mapping cortical activity. However, flow measurement requires fluorescent dye injection, which can be problematic. The noninvasive and high resolution tomographic capabilities of optical coherence tomography make it a promising technique for mapping depth resolved cortical blood flow. Here, we present a functional Doppler optical coherence tomography (OCT) imaging modality for quantitative evaluation of cortical blood flow in a mouse model. Fast, repeated, Doppler OCT scans across a vessel of interest were performed to record flow dynamic information with a high temporal resolution of the cardiac cycles. Spectral Doppler analysis of continuous Doppler images demonstrates how the velocity components and longitudinally projected flow-volume-rate change over time, thereby providing complementary temporal flow information to the spatially distributed flow information of Doppler OCT. The proposed functional Doppler OCT imaging modality can be used to diagnose vessel stenosis/blockage or monitor blood flow changes due to pharmacological agents/neuronal activities. Non-invasive in-vivo mice experiments were performed to verify the capabilities of function Doppler OCT.

  20. 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.

  1. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox

    PubMed Central

    Lacerda, Luis Miguel; Ferreira, Hugo Alexandre

    2015-01-01

    Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity. Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19–73 years old) with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also. Results. It was observed both a high inter-hemispheric symmetry

  2. Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox.

    PubMed

    Ribeiro, Andre Santos; Lacerda, Luis Miguel; Ferreira, Hugo Alexandre

    2015-01-01

    Aim. In recent years, connectivity studies using neuroimaging data have increased the understanding of the organization of large-scale structural and functional brain networks. However, data analysis is time consuming as rigorous procedures must be assured, from structuring data and pre-processing to modality specific data procedures. Until now, no single toolbox was able to perform such investigations on truly multimodal image data from beginning to end, including the combination of different connectivity analyses. Thus, we have developed the Multimodal Imaging Brain Connectivity Analysis (MIBCA) toolbox with the goal of diminishing time waste in data processing and to allow an innovative and comprehensive approach to brain connectivity. Materials and Methods. The MIBCA toolbox is a fully automated all-in-one connectivity toolbox that offers pre-processing, connectivity and graph theoretical analyses of multimodal image data such as diffusion-weighted imaging, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). It was developed in MATLAB environment and pipelines well-known neuroimaging softwares such as Freesurfer, SPM, FSL, and Diffusion Toolkit. It further implements routines for the construction of structural, functional and effective or combined connectivity matrices, as well as, routines for the extraction and calculation of imaging and graph-theory metrics, the latter using also functions from the Brain Connectivity Toolbox. Finally, the toolbox performs group statistical analysis and enables data visualization in the form of matrices, 3D brain graphs and connectograms. In this paper the MIBCA toolbox is presented by illustrating its capabilities using multimodal image data from a group of 35 healthy subjects (19-73 years old) with volumetric T1-weighted, diffusion tensor imaging, and resting state fMRI data, and 10 subjets with 18F-Altanserin PET data also. Results. It was observed both a high inter-hemispheric symmetry and

  3. Symmetric subspace learning for image analysis.

    PubMed

    Papachristou, Konstantinos; Tefas, Anastasios; Pitas, Ioannis

    2014-12-01

    Subspace learning (SL) is one of the most useful tools for image analysis and recognition. A large number of such techniques have been proposed utilizing a priori knowledge about the data. In this paper, new subspace learning techniques are presented that use symmetry constraints in their objective functions. The rational behind this idea is to exploit the a priori knowledge that geometrical symmetry appears in several types of data, such as images, objects, faces, and so on. Experiments on artificial, facial expression recognition, face recognition, and object categorization databases highlight the superiority and the robustness of the proposed techniques, in comparison with standard SL techniques.

  4. Imaging control functions of optical scanners

    NASA Astrophysics Data System (ADS)

    Nishinaga, Hisashi; Hirayama, Toru; Fujii, Daiyu; Yamamoto, Hajime; Irihama, Hiroshi; Ogata, Taro; Koizumi, Yukio; Suzuki, Kenta; Fujishima, Yohei; Matsuyama, Tomoyuki; Kawaguchi, Ryoichi

    2014-03-01

    For future printing based on multiple patterning and directed self-assembly, critical dimension and overlay requirements become tighter for immersion lithography. Thermal impact of exposure to both the projection lens and reticle expansion becomes the dominant factor for high volume production. A new procedure to tune the thermal control function is needed to maintain the tool conditions to obtain high productivity and accuracy. Additionally, new functions of both hardware and software are used to improve the imaging performance even during exposure with high-dose conditions. In this paper, we describe the procedure to tune the thermal control parameters which indicate the response of projection lens aberration and reticle expansion separately. As new functionalities to control the thermal lens aberration, wavefront-based lens control software and reticle bending hardware are introduced. By applying these functions, thermal focus control can be improved drastically. Further, the capability of prediction of reticle expansion is discussed, including experimental data from overlay exposure and aerial image sensor results.

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. Seven topics in functional magnetic resonance imaging.

    PubMed

    Bandettini, Peter A

    2009-09-01

    Functional MRI (fMRI) is a non-invasive brain imaging methodology that started in 1991 and allows human brain activation to be imaged at high resolution within only a few minutes. Because it has extremely high sensitivity, is relatively easy to implement, and can be performed on most standard clinical MRI scanners. It continues to grow at an explosive rate throughout the world. Over the years, at any given time, fMRI has been defined by only a handful of major topics that have been the focus of researchers using and developing the methodology. In this review, I attempt to take a snapshot of the field of fMRI as it is in mid-2009 by discussing the seven topics that I feel are most on the minds of fMRI researchers. The topics are, in no particular order or grouping: (1) Clinical impact, (2) Utilization of individual functional maps, (3) fMRI signal interpretation, (4) Pattern effect mapping and decoding, (5) Endogenous oscillations, (6) MRI technology, and (7) Alternative functional contrast mechanisms. Most of these topics are highly interdependent, each advancing as the others advance. While most fMRI involves applications towards clinical or neuroscience questions, all applications are fundamentally dependent on advances in basic methodology as well as advances in our understanding of the relationship between neuronal activity and fMRI signal changes. This review neglects almost completely an in-depth discussion of applications. Rather the discussions are on the methods and interpretation.

  10. SEVEN TOPICS IN FUNCTIONAL MAGNETIC RESONANCE IMAGING

    PubMed Central

    BANDETTINI, PETER A.

    2010-01-01

    Functional MRI (fMRI) is a non-invasive brain imaging methodology that started in 1991 and allows human brain activation to be imaged at high resolution within only a few minutes. Because it has extremely high sensitivity, is relatively easy to implement, and can be performed on most standard clinical MRI scanners. It continues to grow at an explosive rate throughout the world. Over the years, at any given time, fMRI has been defined by only a handful of major topics that have been the focus of researchers using and developing the methodology. In this review, I attempt to take a snapshot of the field of fMRI as it is in mid-2009 by discussing the seven topics that I feel are most on the minds of fMRI researchers. The topics are, in no particular order or grouping: (1) Clinical impact, (2) Utilization of individual functional maps, (3) fMRI signal interpretation, (4) Pattern effect mapping and decoding, (5) Endogenous oscillations, (6) MRI technology, and (7) Alternative functional contrast mechanisms. Most of these topics are highly interdependent, each advancing as the others advance. While most fMRI involves applications towards clinical or neuroscience questions, all applications are fundamentally dependent on advances in basic methodology as well as advances in our understanding of the relationship between neuronal activity and fMRI signal changes. This review neglects almost completely an in-depth discussion of applications. Rather the discussions are on the methods and interpretation. PMID:19938211

  11. 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

  12. Target identification by image analysis.

    PubMed

    Fetz, V; Prochnow, H; Brönstrup, M; Sasse, F

    2016-05-01

    Covering: 1997 to the end of 2015Each biologically active compound induces phenotypic changes in target cells that are characteristic for its mode of action. These phenotypic alterations can be directly observed under the microscope or made visible by labelling structural elements or selected proteins of the cells with dyes. A comparison of the cellular phenotype induced by a compound of interest with the phenotypes of reference compounds with known cellular targets allows predicting its mode of action. While this approach has been successfully applied to the characterization of natural products based on a visual inspection of images, recent studies used automated microscopy and analysis software to increase speed and to reduce subjective interpretation. In this review, we give a general outline of the workflow for manual and automated image analysis, and we highlight natural products whose bacterial and eucaryotic targets could be identified through such approaches. PMID:26777141

  13. Program functionality and information analysis

    SciTech Connect

    Woods, T.W.; Shipler, D.B.

    1992-04-01

    The Office of Civilian Radioactive Waste Management (OCRWM) is executing a plan for improvement of the United States Nuclear Waste Management Program. As part of the plan, OCRWM is performing a systems engineering analysis of both the physical system, i.e., the Nuclear Waste Management System (NWMS), and the programmatic functions that must be accomplished to bring the physical system into being. The functional analysis effort is being performed by two separate teams working in parallel, one of which addresses the physical system functions and the other the programmatic functions. This paper presents information on the analysis of the programmatic functions.

  14. 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.

  15. Intravital multiphoton microscopy for imaging hepatobiliary function

    NASA Astrophysics Data System (ADS)

    Li, Feng-Chieh; Sun, Tzu-Lin; Lee, Hsuan-Shu; Yang, Shu-Mei; Dong, Chen-Yuan

    2007-07-01

    Liver is the chemical factory in body responsible for important functions such as metabolism and detoxification. When liver can not be regenerated in time to amend damages that has occurred, failure of hepatic functions can result. Traditionally, the study of liver pathology has depended on histological techniques, but such methods are limited to ex-vivo observation. In order to study hepatic metabolism in vivo, we have designed a hepatic imaging chamber made of biocompatible titanium alloy (6V4Al-Ti, ELI grade). In combination with multiphoton and second harmonic generation microscopy, our approach allows the intravital observation of hepatic intravital activities to be achieved. Processes such as hepatic metabolism and disease progression can be studied using this methodology.

  16. Ultrasonic image analysis for beef tenderness

    NASA Astrophysics Data System (ADS)

    Park, Bosoon; Thane, Brian R.; Whittaker, A. D.

    1993-05-01

    Objective measurement of meat tenderness has been a topic of concern for palatability evaluation. In this study, a real-time ultrasonic B-mode imaging method was used for measuring beef palatability attributes such as juiciness, muscle fiber tenderness, connective tissue amount, overall tenderness, flavor intensity, and percent total collagen noninvasively. A temporal averaging image enhancement method was used for image analysis. Ultrasonic image intensity, fractal dimension, attenuation, and statistical gray-tone spatial-dependence matrix image texture measurement were analyzed. The contrast of the textural feature was the most correlated parameter with palatability attributes. The longitudinal scanning method was better for juiciness, muscle fiber tenderness, flavor intensity, and percent soluble collagen, whereas, the cross-sectional method was better for connective tissue, overall tenderness. The multivariate linear regression models were developed as a function of textural features and image intensity parameters. The determinant coefficients of regression models were for juiciness (R2 equals .97), for percent total collagen (R2 equals .88), for flavor intensity (R2 equals .75), for muscle fiber tenderness (R2 equals .55), and for overall tenderness (R2 equals .49), respectively.

  17. Imaging Functional Nucleic Acid Delivery to Skin.

    PubMed

    Kaspar, Roger L; Hickerson, Robyn P; González-González, Emilio; Flores, Manuel A; Speaker, Tycho P; Rogers, Faye A; Milstone, Leonard M; Contag, Christopher H

    2016-01-01

    Monogenic skin diseases arise from well-defined single gene mutations, and in some cases a single point mutation. As the target cells are superficial, these diseases are ideally suited for treatment by nucleic acid-based therapies as well as monitoring through a variety of noninvasive imaging technologies. Despite the accessibility of the skin, there remain formidable barriers for functional delivery of nucleic acids to the target cells within the dermis and epidermis. These barriers include the stratum corneum and the layered structure of the skin, as well as more locally, the cellular, endosomal and nuclear membranes. A wide range of technologies for traversing these barriers has been described and moderate success has been reported for several approaches. The lessons learned from these studies include the need for combinations of approaches to facilitate nucleic acid delivery across these skin barriers and then functional delivery across the cellular and nuclear membranes for expression (e.g., reporter genes, DNA oligonucleotides or shRNA) or into the cytoplasm for regulation (e.g., siRNA, miRNA, antisense oligos). The tools for topical delivery that have been evaluated include chemical, physical and electrical methods, and the development and testing of each of these approaches has been greatly enabled by imaging tools. These techniques allow delivery and real time monitoring of reporter genes, therapeutic nucleic acids and also triplex nucleic acids for gene editing. Optical imaging is comprised of a number of modalities based on properties of light-tissue interaction (e.g., scattering, autofluorescence, and reflectance), the interaction of light with specific molecules (e.g., absorbtion, fluorescence), or enzymatic reactions that produce light (bioluminescence). Optical imaging technologies operate over a range of scales from macroscopic to microscopic and if necessary, nanoscopic, and thus can be used to assess nucleic acid delivery to organs, regions, cells

  18. Imaging Functional Nucleic Acid Delivery to Skin.

    PubMed

    Kaspar, Roger L; Hickerson, Robyn P; González-González, Emilio; Flores, Manuel A; Speaker, Tycho P; Rogers, Faye A; Milstone, Leonard M; Contag, Christopher H

    2016-01-01

    Monogenic skin diseases arise from well-defined single gene mutations, and in some cases a single point mutation. As the target cells are superficial, these diseases are ideally suited for treatment by nucleic acid-based therapies as well as monitoring through a variety of noninvasive imaging technologies. Despite the accessibility of the skin, there remain formidable barriers for functional delivery of nucleic acids to the target cells within the dermis and epidermis. These barriers include the stratum corneum and the layered structure of the skin, as well as more locally, the cellular, endosomal and nuclear membranes. A wide range of technologies for traversing these barriers has been described and moderate success has been reported for several approaches. The lessons learned from these studies include the need for combinations of approaches to facilitate nucleic acid delivery across these skin barriers and then functional delivery across the cellular and nuclear membranes for expression (e.g., reporter genes, DNA oligonucleotides or shRNA) or into the cytoplasm for regulation (e.g., siRNA, miRNA, antisense oligos). The tools for topical delivery that have been evaluated include chemical, physical and electrical methods, and the development and testing of each of these approaches has been greatly enabled by imaging tools. These techniques allow delivery and real time monitoring of reporter genes, therapeutic nucleic acids and also triplex nucleic acids for gene editing. Optical imaging is comprised of a number of modalities based on properties of light-tissue interaction (e.g., scattering, autofluorescence, and reflectance), the interaction of light with specific molecules (e.g., absorbtion, fluorescence), or enzymatic reactions that produce light (bioluminescence). Optical imaging technologies operate over a range of scales from macroscopic to microscopic and if necessary, nanoscopic, and thus can be used to assess nucleic acid delivery to organs, regions, cells

  19. 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.

  20. Functional Nanoscale Imaging of Synaptic Vesicle Cycling with Superfast Fixation.

    PubMed

    Schikorski, Thomas

    2016-01-01

    Functional imaging is the measurement of structural changes during an ongoing physiological process over time. In many cases, functional imaging has been implemented by tracking a fluorescent signal in live imaging sessions. Electron microscopy, however, excludes live imaging which has hampered functional imaging approaches on the ultrastructural level. This barrier was broken with the introduction of superfast fixation. Superfast fixation is capable of stopping and fixing membrane traffic at sufficient speed to capture a physiological process at a distinct functional state. Applying superfast fixation at sequential time points allows tracking of membrane traffic in a step-by-step fashion.This technique has been applied to track labeled endocytic vesicles at central synapses as they pass through the synaptic vesicle cycle. At synapses, neurotransmitter is released from synaptic vesicles (SVs) via fast activity-dependent exocytosis. Exocytosis is coupled to fast endocytosis that retrieves SVs components from the plasma membrane shortly after release. Fluorescent FM dyes that bind to the outer leaflet of the plasma membrane enter the endocytic vesicle during membrane retrieval and remain trapped in endocytic vesicles have been widely used to study SV exo-endocytic cycling in live imaging sessions. FM dyes can also be photoconverted into an electron-dense diaminobenzidine polymer which allows the investigation of SV cycling in the electron microscope. The combination of FM labeling with superfast fixation made it possible to track the fine structure of endocytic vesicles at 1 s intervals. Because this combination is not specialized to SV cycling, many other cellular processes can be studied. Furthermore, the technique is easy to set up and cost effective.This chapter describes activity-dependent FM dye labeling of SVs in cultured hippocampal neurons, superfast microwave-assisted fixation, photoconversion of the fluorescent endocytic vesicles, and the analysis of

  1. 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.

  2. 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,…

  3. 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.

  4. 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. PMID:27182830

  5. 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

  6. 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

    Corona-Villalobos, Celia P; 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

    2015-09-01

    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

  7. 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.

  8. Scalable histopathological image analysis via active learning.

    PubMed

    Zhu, Yan; Zhang, Shaoting; Liu, Wei; Metaxas, Dimitris N

    2014-01-01

    Training an effective and scalable system for medical image analysis usually requires a large amount of labeled data, which incurs a tremendous annotation burden for pathologists. Recent progress in active learning can alleviate this issue, leading to a great reduction on the labeling cost without sacrificing the predicting accuracy too much. However, most existing active learning methods disregard the "structured information" that may exist in medical images (e.g., data from individual patients), and make a simplifying assumption that unlabeled data is independently and identically distributed. Both may not be suitable for real-world medical images. In this paper, we propose a novel batch-mode active learning method which explores and leverages such structured information in annotations of medical images to enforce diversity among the selected data, therefore maximizing the information gain. We formulate the active learning problem as an adaptive submodular function maximization problem subject to a partition matroid constraint, and further present an efficient greedy algorithm to achieve a good solution with a theoretically proven bound. We demonstrate the efficacy of our algorithm on thousands of histopathological images of breast microscopic tissues. PMID:25320821

  9. 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.

  10. Forthergillian Lecture. Imaging human brain function.

    PubMed

    Frackowiak, R S

    The non-invasive brain scanning techniques introduced a quarter of a century ago have become crucial for diagnosis in clinical neurology. They have also been used to investigate brain function and have provided information about normal activity and pathogenesis. They have been used to investigate functional specialization in the brain and how specialized areas communicate to generate complex integrated functions such as speech, memory, the emotions and so on. The phenomenon of brain plasticity is poorly understood and yet clinical neurologists are aware, from everyday observations, that spontaneous recovery from brain lesions is common. An improved understanding of the mechanisms of recovery may generate new therapeutic strategies and indicate ways of modulating mechanisms that promote plastic compensation for loss of function. The main methods used to investigate these issues are positron emission tomography and magnetic resonance imaging (M.R.I.). M.R.I. is also used to map brain structure. The techniques of functional brain mapping and computational morphometrics depend on high performance scanners and a validated set of analytic statistical procedures that generate reproducible data and meaningful inferences from brain scanning data. The motor system presents a good paradigm to illustrate advances made by scanning towards an understanding of plasticity at the level of brain areas. The normal motor system is organized in a nested hierarchy. Recovery from paralysis caused by internal capsule strokes involves functional reorganization manifesting itself as changed patterns of activity in the component brain areas of the normal motor system. The pattern of plastic modification depends in part on patterns of residual or disturbed connectivity after brain injury. Therapeutic manipulations in patients with Parkinson's disease using deep brain stimulation, dopaminergic agents or fetal mesencephalic transplantation provide a means to examine mechanisms underpinning

  11. Statistical analysis of biophoton image

    NASA Astrophysics Data System (ADS)

    Wang, Susheng

    1998-08-01

    A photon count image system has been developed to obtain the ultra-weak bioluminescence image. The photon images of some plant, animal and human hand have been detected. The biophoton image is different from usual image. In this paper three characteristics of biophoton image are analyzed. On the basis of these characteristics the detected probability and detected limit of photon count image system, detected limit of biophoton image have been discussed. These researches provide scientific basis for experiments design and photon image processing.

  12. Computer analysis of mammography phantom images (CAMPI)

    NASA Astrophysics Data System (ADS)

    Chakraborty, Dev P.

    1997-05-01

    Computer analysis of mammography phantom images (CAMPI) is a method for objective and precise measurements of phantom image quality in mammography. This investigation applied CAMPI methodology to the Fischer Mammotest Stereotactic Digital Biopsy machine. Images of an American College of Radiology phantom centered on the largest two microcalcification groups were obtained on this machine under a variety of x-ray conditions. Analyses of the images revealed that the precise behavior of the CAMPI measures could be understood from basic imaging physics principles. We conclude that CAMPI is sensitive to subtle image quality changes and can perform accurate evaluations of images, especially of directly acquired digital images.

  13. 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.

  14. Theoretical Analysis of Radiographic Images by Nonstationary Poisson Processes

    NASA Astrophysics Data System (ADS)

    Tanaka, Kazuo; Yamada, Isao; Uchida, Suguru

    1980-12-01

    This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples of the one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process.

  15. IMAGE ANALYSIS ALGORITHMS FOR DUAL MODE IMAGING SYSTEMS

    SciTech Connect

    Robinson, Sean M.; Jarman, Kenneth D.; Miller, Erin A.; Misner, Alex C.; Myjak, Mitchell J.; Pitts, W. Karl; Seifert, Allen; Seifert, Carolyn E.; Woodring, Mitchell L.

    2010-06-11

    The level of detail discernable in imaging techniques has generally excluded them from consideration as verification tools in inspection regimes where information barriers are mandatory. However, if a balance can be struck between sufficient information barriers and feature extraction to verify or identify objects of interest, imaging may significantly advance verification efforts. This paper describes the development of combined active (conventional) radiography and passive (auto) radiography techniques for imaging sensitive items assuming that comparison images cannot be furnished. Three image analysis algorithms are presented, each of which reduces full image information to non-sensitive feature information and ultimately is intended to provide only a yes/no response verifying features present in the image. These algorithms are evaluated on both their technical performance in image analysis and their application with or without an explicitly constructed information barrier. The first algorithm reduces images to non-invertible pixel intensity histograms, retaining only summary information about the image that can be used in template comparisons. This one-way transform is sufficient to discriminate between different image structures (in terms of area and density) without revealing unnecessary specificity. The second algorithm estimates the attenuation cross-section of objects of known shape based on transition characteristics around the edge of the object’s image. The third algorithm compares the radiography image with the passive image to discriminate dense, radioactive material from point sources or inactive dense material. By comparing two images and reporting only a single statistic from the combination thereof, this algorithm can operate entirely behind an information barrier stage. Together with knowledge of the radiography system, the use of these algorithms in combination can be used to improve verification capability to inspection regimes and improve

  16. 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

  17. 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.

  18. Functional Magnetic Resonance Imaging for Imaging Neural Activity in the Human Brain: The Annual Progress

    PubMed Central

    Chen, Shengyong; Li, Xiaoli

    2012-01-01

    Functional magnetic resonance imaging (fMRI) is recently developed and applied to measure the hemodynamic response related to neural activity. The fMRI can not only noninvasively record brain signals without risks of ionising radiation inherent in other scanning methods, such as CT or PET scans, but also record signal from all regions of the brain, unlike EEG/MEG which are biased towards the cortical surface. This paper introduces the fundamental principles and summarizes the research progress of the last year for imaging neural activity in the human brain. Aims of functional analysis of neural activity from fMRI include biological findings, functional connectivity, vision and hearing research, emotional research, neurosurgical planning, pain management, and many others. Besides formulations and basic processing methods, models and strategies of processing technology are introduced, including general linear model, nonlinear model, generative model, spatial pattern analysis, statistical analysis, correlation analysis, and multimodal combination. This paper provides readers the most recent representative contributions in the area. PMID:22319550

  19. Functional magnetic resonance imaging for imaging neural activity in the human brain: the annual progress.

    PubMed

    Chen, Shengyong; Li, Xiaoli

    2012-01-01

    Functional magnetic resonance imaging (fMRI) is recently developed and applied to measure the hemodynamic response related to neural activity. The fMRI can not only noninvasively record brain signals without risks of ionising radiation inherent in other scanning methods, such as CT or PET scans, but also record signal from all regions of the brain, unlike EEG/MEG which are biased towards the cortical surface. This paper introduces the fundamental principles and summarizes the research progress of the last year for imaging neural activity in the human brain. Aims of functional analysis of neural activity from fMRI include biological findings, functional connectivity, vision and hearing research, emotional research, neurosurgical planning, pain management, and many others. Besides formulations and basic processing methods, models and strategies of processing technology are introduced, including general linear model, nonlinear model, generative model, spatial pattern analysis, statistical analysis, correlation analysis, and multimodal combination. This paper provides readers the most recent representative contributions in the area.

  20. 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.

  1. Functional Calcium Imaging in Developing Cortical Networks

    PubMed Central

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

    2011-01-01

    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

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics.

    PubMed

    Niessen, Wiro J

    2016-10-01

    MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role. PMID:27344937

  7. MR brain image analysis in dementia: From quantitative imaging biomarkers to ageing brain models and imaging genetics.

    PubMed

    Niessen, Wiro J

    2016-10-01

    MR brain image analysis has constantly been a hot topic research area in medical image analysis over the past two decades. In this article, it is discussed how the field developed from the construction of tools for automatic quantification of brain morphology, function, connectivity and pathology, to creating models of the ageing brain in normal ageing and disease, and tools for integrated analysis of imaging and genetic data. The current and future role of the field in improved understanding of the development of neurodegenerative disease is discussed, and its potential for aiding in early and differential diagnosis and prognosis of different types of dementia. For the latter, the use of reference imaging data and reference models derived from large clinical and population imaging studies, and the application of machine learning techniques on these reference data, are expected to play a key role.

  8. Image registration with uncertainty analysis

    DOEpatents

    Simonson, Katherine M.

    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.

  9. 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.

  10. Millimeter-wave sensor image analysis

    NASA Technical Reports Server (NTRS)

    Wilson, William J.; Suess, Helmut

    1989-01-01

    Images of an airborne, scanning, radiometer operating at a frequency of 98 GHz, have been analyzed. The mm-wave images were obtained in 1985/1986 using the JPL mm-wave imaging sensor. The goal of this study was to enhance the information content of these images and make their interpretation easier for human analysis. In this paper, a visual interpretative approach was used for information extraction from the images. This included application of nonlinear transform techniques for noise reduction and for color, contrast and edge enhancement. Results of the techniques on selected mm-wave images are presented.

  11. Derivation of various transfer functions of ideal or aberrated imaging systems from the three-dimensional transfer function.

    PubMed

    Braat, Joseph J M; Janssen, Augustus J E M

    2015-06-01

    The three-dimensional frequency transfer function for optical imaging systems was introduced by Frieden in the 1960s. The analysis of this function and its partly back-transformed functions (two-dimensional and one-dimensional optical transfer functions) in the case of an ideal or aberrated imaging system has received relatively little attention in the literature. Regarding ideal imaging systems with an incoherently illuminated object volume, we present analytic expressions for the classical two-dimensional x-y-transfer function in a defocused plane, for the axial z-transfer function in the presence of defocusing and for the x-z-transfer function in the presence of a lateral shift δy with respect to the imaged pattern in the x-z-plane. For an aberrated imaging system we use the common expansion of the aberrated pupil function with the aid of Zernike polynomials. It is shown that the line integral appearing in Frieden's three-dimensional transfer function can be evaluated for aberrated systems using a relationship established first by Cormack between the line integral of a Zernike polynomial over a full chord of the unit disk and a Chebyshev polynomial of the second kind. Some new developments in the theory of Zernike polynomials from the last decade allow us to present explicit expressions for the line integral in the case of a weakly aberrated imaging system. We outline a similar, but more complicated, analytic scheme for the case of severely aberrated systems.

  12. Quantitative analysis of digital microscope images.

    PubMed

    Wolf, David E; Samarasekera, Champika; Swedlow, Jason R

    2013-01-01

    This chapter discusses quantitative analysis of digital microscope images and presents several exercises to provide examples to explain the concept. This chapter also presents the basic concepts in quantitative analysis for imaging, but these concepts rest on a well-established foundation of signal theory and quantitative data analysis. This chapter presents several examples for understanding the imaging process as a transformation from sample to image and the limits and considerations of quantitative analysis. This chapter introduces to the concept of digitally correcting the images and also focuses on some of the more critical types of data transformation and some of the frequently encountered issues in quantization. Image processing represents a form of data processing. There are many examples of data processing such as fitting the data to a theoretical curve. In all these cases, it is critical that care is taken during all steps of transformation, processing, and quantization.

  13. Quantitative analysis of digital microscope images.

    PubMed

    Wolf, David E; Samarasekera, Champika; Swedlow, Jason R

    2013-01-01

    This chapter discusses quantitative analysis of digital microscope images and presents several exercises to provide examples to explain the concept. This chapter also presents the basic concepts in quantitative analysis for imaging, but these concepts rest on a well-established foundation of signal theory and quantitative data analysis. This chapter presents several examples for understanding the imaging process as a transformation from sample to image and the limits and considerations of quantitative analysis. This chapter introduces to the concept of digitally correcting the images and also focuses on some of the more critical types of data transformation and some of the frequently encountered issues in quantization. Image processing represents a form of data processing. There are many examples of data processing such as fitting the data to a theoretical curve. In all these cases, it is critical that care is taken during all steps of transformation, processing, and quantization. PMID:23931513

  14. Multiscale Analysis of Solar Image Data

    NASA Astrophysics Data System (ADS)

    Young, C. A.; Myers, D. C.

    2001-12-01

    It is often said that the blessing and curse of solar physics is that there is too much data. Solar missions such as Yohkoh, SOHO and TRACE have shown us the Sun with amazing clarity but have also cursed us with an increased amount of higher complexity data than previous missions. We have improved our view of the Sun yet we have not improved our analysis techniques. The standard techniques used for analysis of solar images generally consist of observing the evolution of features in a sequence of byte scaled images or a sequence of byte scaled difference images. The determination of features and structures in the images are done qualitatively by the observer. There is little quantitative and objective analysis done with these images. Many advances in image processing techniques have occured in the past decade. Many of these methods are possibly suited for solar image analysis. Multiscale/Multiresolution methods are perhaps the most promising. These methods have been used to formulate the human ability to view and comprehend phenomena on different scales. So these techniques could be used to quantitify the imaging processing done by the observers eyes and brains. In this work we present a preliminary analysis of multiscale techniques applied to solar image data. Specifically, we explore the use of the 2-d wavelet transform and related transforms with EIT, LASCO and TRACE images. This work was supported by NASA contract NAS5-00220.

  15. 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

  16. Bayesian spatiotemporal inference in functional magnetic resonance imaging.

    PubMed

    Gössl, C; Auer, D P; Fahrmeir, L

    2001-06-01

    Mapping of the human brain by means of functional magnetic resonance imaging (fMRI) is an emerging field in cognitive and clinical neuroscience. Current techniques to detect activated areas of the brain mostly proceed in two steps. First, conventional methods of correlation, regression, and time series analysis are used to assess activation by a separate, pixelwise comparison of the fMRI signal time courses to the reference function of a presented stimulus. Spatial aspects caused by correlations between neighboring pixels are considered in a separate second step, if at all. The aim of this article is to present hierarchical Bayesian approaches that allow one to simultaneously incorporate temporal and spatial dependencies between pixels directly in the model formulation. For reasons of computational feasibility, models have to be comparatively parsimonious, without oversimplifying. We introduce parametric and semiparametric spatial and spatiotemporal models that proved appropriate and illustrate their performance applied to visual fMRI data.

  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. 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.

  19. 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.

  20. Image Reconstruction Using Analysis Model Prior.

    PubMed

    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

  1. 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

  2. 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.

  3. 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

  4. 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

  5. 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.

  6. 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. PMID:27141917

  7. 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.

  8. 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

  9. [2-dimensional echocardiographic analysis of the volume and function of the right ventricle in the apical and subcostal 4 chamber image].

    PubMed

    Jacksch, R; Karsch, K R; Niethammer, J; Seipel, L

    1986-09-01

    To determine the diagnostic accuracy of two-dimensional echocardiography in the evaluation of RV dimensions and function, biplane angiography of the right ventricle and 2-D echo was performed in 60 consecutive patients and analyzed by two independent investigators. In 42 of 60 patients (group A) the RV could be visualized in the rotated apical 4 chamber view and in 18 patients in the subcostal 4 chamber view with good quality, which made it possible to define the right ventricular endocardium in the real-time proceeding. In 20 of these 42 patients the RV could be registered in the apical 4 chamber view with complete definition of the endocardium also in the stop frame (group B). Quantitative analysis was performed in the end-diastolic and end-systolic stop frame, using the area-length method. The correlation of echocardiography and angiography for the end-diastolic volumes was poor in group A (r = 0.62) and superior in group B (r = 0.73). The correlation coefficient for end-systolic volumes was r = 0.70 in group A and r = 0.92 in group B. End-diastolic and end-systolic volumes were systematically underestimated by echocardiography. RV ejection fraction did not correlate between both methods. The subcostal 4 chamber view was not sufficient in determining RV volumes and function. The results demonstrate that the right ventricle can be visualized in 70% of patients with sufficient quality. RV dimensions and volumes can be determined with high accuracy in these patients. PMID:3788262

  10. 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. PMID:27606187

  11. 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.

  12. What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging.

    PubMed

    Ugurbil, Kamil

    2016-10-01

    When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a 'golden technique' that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. PMID:27574313

  13. What is feasible with imaging human brain function and connectivity using functional magnetic resonance imaging.

    PubMed

    Ugurbil, Kamil

    2016-10-01

    When we consider all of the methods we employ to detect brain function, from electrophysiology to optical techniques to functional magnetic resonance imaging (fMRI), we do not really have a 'golden technique' that meets all of the needs for studying the brain. We have methods, each of which has significant limitations but provide often complimentary information. Clearly, there are many questions that need to be answered about fMRI, which unlike other methods, allows us to study the human brain. However, there are also extraordinary accomplishments or demonstration of the feasibility of reaching new and previously unexpected scales of function in the human brain. This article reviews some of the work we have pursued, often with extensive collaborations with other co-workers, towards understanding the underlying mechanisms of the methodology, defining its limitations, and developing solutions to advance it. No doubt, our knowledge of human brain function has vastly expanded since the introduction of fMRI. However, methods and instrumentation in this dynamic field have evolved to a state that discoveries about the human brain based on fMRI principles, together with information garnered at a much finer spatial and temporal scale through other methods, are poised to significantly accelerate in the next decade.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

  14. Quantitative image analysis of synovial tissue.

    PubMed

    van der Hall, Pascal O; Kraan, Maarten C; Tak, Paul Peter

    2007-01-01

    Quantitative image analysis is a form of imaging that includes microscopic histological quantification, video microscopy, image analysis, and image processing. Hallmarks are the generation of reliable, reproducible, and efficient measurements via strict calibration and step-by-step control of the acquisition, storage and evaluation of images with dedicated hardware and software. Major advantages of quantitative image analysis over traditional techniques include sophisticated calibration systems, interaction, speed, and control of inter- and intraobserver variation. This results in a well controlled environment, which is essential for quality control and reproducibility, and helps to optimize sensitivity and specificity. To achieve this, an optimal quantitative image analysis system combines solid software engineering with easy interactivity with the operator. Moreover, the system also needs to be as transparent as possible in generating the data because a "black box design" will deliver uncontrollable results. In addition to these more general aspects, specifically for the analysis of synovial tissue the necessity of interactivity is highlighted by the added value of identification and quantification of information as present in areas such as the intimal lining layer, blood vessels, and lymphocyte aggregates. Speed is another important aspect of digital cytometry. Currently, rapidly increasing numbers of samples, together with accumulation of a variety of markers and detection techniques has made the use of traditional analysis techniques such as manual quantification and semi-quantitative analysis unpractical. It can be anticipated that the development of even more powerful computer systems with sophisticated software will further facilitate reliable analysis at high speed.

  15. Partial iterated function system-based fractal image coding

    NASA Astrophysics Data System (ADS)

    Wang, Zhou; Yu, Ying Lin

    1996-06-01

    A recent trend in computer graphics and image processing has been to use iterated function system (IFS) to generate and describe images. Barnsley et al. presented the conception of fractal image compression and Jacquin was the first to propose a fully automatic gray scale still image coding algorithm. This paper introduces a generalization of basic IFS, leading to a conception of partial iterated function system (PIFS). A PIFS operator is contractive under certain conditions and when it is applied to generate an image, only part of it is actually iteratedly applied. PIFS provides us a flexible way to combine fractal coding with other image coding techniques and many specific algorithms can be derived from it. On the basis of PIFS, we implement a partial fractal block coding (PFBC) algorithm and compare it with basic IFS based fractal block coding algorithm. Experimental results show that coding efficiency is improved and computation time is reduced while image fidelity does not degrade very much.

  16. 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.

  17. 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.

  18. 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. PMID:24114106

  19. Fidelity Analysis of Sampled Imaging Systems

    NASA Technical Reports Server (NTRS)

    Park, Stephen K.; Rahman, Zia-ur

    1999-01-01

    Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image

  20. Quantitative Functional Morphology by Imaging Flow Cytometry.

    PubMed

    Vorobjev, Ivan A; Barteneva, Natasha S

    2016-01-01

    This chapter describes advantages and limitations of imaging flow cytometry (IFC) based on Imagestream instrumentation using a hybrid approach of morphometric measurement and quantitation of multiparametric fluorescent intensities' distribution in cells and particles. Brief comparison is given of IFC with conventional flow cytometry and fluorescent microscopy. Some future directions of the IFC technology are described and discussed. PMID:27460234

  1. Image based physiological monitoring of cardiac function

    NASA Astrophysics Data System (ADS)

    Maier, Corinna S.; Bock, Michael; Semmler, Wolfhard; Lorenz, Christine H.

    2008-03-01

    A new framework for image based physiological cardiac monitoring is proposed based on repeated imaging of critical slice locations in an interventional MRI environment. The aim of this work is to provide a method of detecting pathological changes in the left ventricular (LV) myocardial wall motion where the standard ECG methods are not possible due to distortions by the magnetic field. First MRI LV short axis images are acquired for different phases of the cardiac cycle over RR intervals. Then LV contours are detected based on an established segmentation algorithm. The contour's Fourier Descriptors are calculated to classify myocardial wall into two classes: contracted or not contracted. The classifier is trained during an initial observation period before a pathological change might occur during an intervention. A contour rejected by the classifier using the unconditional, predictive probability of the contour's observation vector as confidence measure is interpreted as a probably pathologic change in the LV myocardial wall motion. To evaluate the performance of the classifier a simple model is introduced for simulating the contours of a pathological, ischemic, LV myocardial wall. The overall performance of the classifier on 516 samples based on healthy volunteer images and 3096 simulated ischemic samples yielded a mean classification error for supervised training of 5.7% and for unsupervised training of 8.7%.

  2. Quantitative Functional Morphology by Imaging Flow Cytometry.

    PubMed

    Vorobjev, Ivan A; Barteneva, Natasha S

    2016-01-01

    This chapter describes advantages and limitations of imaging flow cytometry (IFC) based on Imagestream instrumentation using a hybrid approach of morphometric measurement and quantitation of multiparametric fluorescent intensities' distribution in cells and particles. Brief comparison is given of IFC with conventional flow cytometry and fluorescent microscopy. Some future directions of the IFC technology are described and discussed.

  3. 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

  4. Automatic analysis of a skull fracture based on image content

    NASA Astrophysics Data System (ADS)

    Shao, Hong; Zhao, Hong

    2003-09-01

    Automatic analysis based on image content is a hotspot with bright future of medical image diagnosis technology research. Analysis of the fracture of skull can help doctors diagnose. In this paper, a new approach is proposed to automatically detect the fracture of skull based on CT image content. First region growing method, whose seeds and growing rules are chosen by k-means clustering dynamically, is applied for image automatic segmentation. The segmented region boundary is found by boundary tracing. Then the shape of the boundary is analyzed, and the circularity measure is taken as description parameter. At last the rules for computer automatic diagnosis of the fracture of the skull are reasoned by entropy function. This method is used to analyze the images from the third ventricles below layer to cerebral cortex top layer. Experimental result shows that the recognition rate is 100% for the 100 images, which are chosen from medical image database randomly and are not included in the training examples. This method integrates color and shape feature, and isn't affected by image size and position. This research achieves high recognition rate and sets a basis for automatic analysis of brain image.

  5. 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

  6. [Functional magnetic resonance imaging of psychopharmacological brain effects: an update].

    PubMed

    Braus, D F; Brassen, S; Weimer, E; Tost, H

    2003-02-01

    Functional magnetic resonance imaging (fMRI) is well established for the examination of functional activity in the living brain. The method permits the development of functional activation maps during perceptual, cognitive and emotional efforts with a high temporal and spatial resolution. As of late there has been growing interest in using this technique to investigate regionally specific brain activity following the administration of drugs such as nicotine, cocaine, lorazepam, scopolamine, antipsychotics or antidepressants. Studies in experimental animals investigate signal changes associated with the administration of psychopharmacological substances in different brain areas using a high magnetising field (> 4 Tesla). FMRI-studies in healthy human volunteers and psychiatric patients focus on cerebral activity following acute drug administration (single challenge) and on adaptive effects of the CNS due to long- term medication. Their results provide insights into brain physiology and neuropharmacological mechanisms which are in turn relevant for preclinical pharmacological studies, responder analyses and for the investigation of pathogenetic models in psychiatric diseases. However, with these new opportunities, additional methodological considerations and limitations emerge. Besides the need of controlling motion artefacts, the influence of interfering psychological variables, an exact specification of the experimental design, a standardised analysis for data adjustment and technical limitations have to be considered. This article provides an overview of the underlying model of brain function, present applications, future possibilities and methodological limitations of fMRI for the understanding of human psychopharmacology. PMID:12579470

  7. On the response function separability of hyperspectral imaging systems

    NASA Astrophysics Data System (ADS)

    Jemec, Jurij; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran

    2015-05-01

    Hyperspectral imaging systems effectively collect information across the spectral and two spatial dimensions by employing three main components: the front lens, the light-diffraction element and a camera. Imperfections in these components introduce spectral and spatial dependent distortions in the recorded hyperspectral image. These can be characterized by a 3D response function that is subsequently used to remove distortions and enhance the resolution of the recorded images by deconvolution. The majority of existing characterization methods assume spatial and spectral separability of the 3D response function. In this way, the complex problem of 3D response function characterization is reduced to independent characterizations of the three orthogonal response function components. However, if the 3D response function is non-separable, such characterization can lead to poor response function estimates, and hence inaccurate and distorted results of the subsequent deconvolution-based calibration and image enhancement. In this paper, we evaluate the influence of the spatial response function non-separability on the results of the calibration by deconvolution. For this purpose, a novel procedure for direct measurement of the 2D spatial response function is proposed along with a quantitative measure of the spatial response function non-separability. The quality of deconvolved images is assessed in terms of full width at half maximum (FWHM) and step edge overshoot magnitude observed in the deconvolved images of slanted edges, images of biological slides, and 1951 USAF resolution test chart. Results show that there are cases, when nonseparability of the system response function is significant and should be considered by the deconvolution-based calibration and image enhancement methods.

  8. NIH Image to ImageJ: 25 years of image analysis.

    PubMed

    Schneider, Caroline A; Rasband, Wayne S; Eliceiri, Kevin W

    2012-07-01

    For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.

  9. Factor Analysis of the Image Correlation Matrix.

    ERIC Educational Resources Information Center

    Kaiser, Henry F.; Cerny, Barbara A.

    1979-01-01

    Whether to factor the image correlation matrix or to use a new model with an alpha factor analysis of it is mentioned, with particular reference to the determinacy problem. It is pointed out that the distribution of the images is sensibly multivariate normal, making for "better" factor analyses. (Author/CTM)

  10. 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.

  11. An Imaging And Graphics Workstation For Image Sequence Analysis

    NASA Astrophysics Data System (ADS)

    Mostafavi, Hassan

    1990-01-01

    This paper describes an application-specific engineering workstation designed and developed to analyze imagery sequences from a variety of sources. The system combines the software and hardware environment of the modern graphic-oriented workstations with the digital image acquisition, processing and display techniques. The objective is to achieve automation and high throughput for many data reduction tasks involving metric studies of image sequences. The applications of such an automated data reduction tool include analysis of the trajectory and attitude of aircraft, missile, stores and other flying objects in various flight regimes including launch and separation as well as regular flight maneuvers. The workstation can also be used in an on-line or off-line mode to study three-dimensional motion of aircraft models in simulated flight conditions such as wind tunnels. The system's key features are: 1) Acquisition and storage of image sequences by digitizing real-time video or frames from a film strip; 2) computer-controlled movie loop playback, slow motion and freeze frame display combined with digital image sharpening, noise reduction, contrast enhancement and interactive image magnification; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored image sequence; 4) automatic and manual field-of-view and spatial calibration; 5) image sequence data base generation and management, including the measurement data products; 6) off-line analysis software for trajectory plotting and statistical analysis; 7) model-based estimation and tracking of object attitude angles; and 8) interface to a variety of video players and film transport sub-systems.

  12. 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. PMID:25805449

  13. Image Analysis of DNA Fiber and Nucleus in Plants.

    PubMed

    Ohmido, Nobuko; Wako, Toshiyuki; Kato, Seiji; Fukui, Kiichi

    2016-01-01

    Advances in cytology have led to the application of a wide range of visualization methods in plant genome studies. Image analysis methods are indispensable tools where morphology, density, and color play important roles in the biological systems. Visualization and image analysis methods are useful techniques in the analyses of the detailed structure and function of extended DNA fibers (EDFs) and interphase nuclei. The EDF is the highest in the spatial resolving power to reveal genome structure and it can be used for physical mapping, especially for closely located genes and tandemly repeated sequences. One the other hand, analyzing nuclear DNA and proteins would reveal nuclear structure and functions. In this chapter, we describe the image analysis protocol for quantitatively analyzing different types of plant genome, EDFs and interphase nuclei. PMID:27557694

  14. 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

  15. A Robust Actin Filaments Image Analysis Framework.

    PubMed

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

    2016-08-01

    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 grown in

  16. A unified approach to image focus and defocus analysis

    NASA Astrophysics Data System (ADS)

    Liu, Yen-Fu

    1998-09-01

    Recovering the three-dimensional (3D) information lost due to the projection of a 3D scene onto a two- dimensional (2D) image plane is an important research area in computer vision. In this thesis we present a new approach to reconstruct a highly accurate 3D shape and focused image of an object from a sequence of noisy defocused images. This new approach-Unified Focus and Defocus Analysis (UFDA)-unifies two approaches- Image Focus Analysis (IFA) and Image Defocus Analysis (IDA)-which have been treated separately in the research literature so far. UFDA is based on modeling the sensing of defocused images in a camera system. The concept of a ``Three-Dimensional Point Spread Function'' (3D PSF) in the (x, y, d) space is introduced, where x and y are the image spatial coordinates and d is a parameter representing the level of defocus. The importance of the choice of this parameterization is that it facilitates the derivation of a 3D convolution equation for image formation under certain weak conditions. The problem of 3D shape and focused image reconstruction is formulated as an optimization problem where the difference (mean- square error) between the observed image data and the estimated image data is minimized by an optimization approach. The estimated image data is obtained from the image sensing model and the current best known solutions to the 3D shape and focused image. Depending on the number of images in the sequence, an initial estimation of the solution can be obtained through IFA or IDA methods. Three optimization techniques have been applied to UFDA-a classical gradient descent approach, a local search method and a regularization technique. Based on these techniques, an efficient computational algorithm has been developed to use a variable number of images. A parallel implementation of UFDA on the Parallel Virtual Machine (PVM) is also investigated. One of the most computationally intensive parts of the UFDA approach is the estimation of image data that

  17. Ethical issues of brain functional imaging: reading your mind.

    PubMed

    Karanasiou, Irene S; Biniaris, Christos G; Marsh, Andrew J

    2008-01-01

    Neuroimaging practice and research are overviewed in this paper through an ethics lens. The main ethical implications in biomedical research concerning functional brain imaging are discussed with the focus on issues related to imaging of personal information and privacy. Specific norms and guidelines will be eventually formed in the future under the umbrella of the new discipline of Neuroethics.

  18. 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.

  19. 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. PMID:21943171

  20. 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.

  1. Hemodynamic responses to functional activation accessed by optical imaging

    NASA Astrophysics Data System (ADS)

    Ni, Songlin; Li, Pengcheng; Yang, Yuanyuan; Lv, Xiaohua; Luo, Qingming

    2006-01-01

    A multi-wavelength light-emitting diode (LED) and laser diode (LD) based optical imaging system was developed to visualize the changes in cerebral blood flow, oxygenation following functional activation simultaneously in rodent cortex. The 2-D blood flow image was accessed by laser speckle contrast imaging, and the spectroscopic imaging of intrinsic signal was used for the calculation of oxyhemoglobin (HbO), deoxyhemoglobin (Hb) and total hemoglobin (HbT) concentration. The combination of spectroscopic imaging and laser speckle contrast imaging provides the capability to simultaneously investigate the spatial and temporal blood flow and hemoglobin concentration changes with high resolution, which may lead to a better understanding of the coupling between neuronal activation and vascular responses. The optical imaging system been built is compact and convenient to investigators. And it is reliable to acquire raw data. In present study, the hemodynamic responses to cortical spreading depression (CSD) in parietal cortex of ~-chloralose/urethan anesthetized rats were demonstrated.

  2. Magnetic resonance imaging in the evaluation of cognitive function.

    PubMed

    Bigler, Erin D

    2014-10-01

    Image quality of magnetic resonance imaging (MRI) scans of the brain currently approximate gross anatomy as would be viewed at autopsy. During the first decade of the 21st Century incredible advances in image processing and quantification have occurred permitting more refined methods for studying brain-behavior-cognitive functioning. The current presentation overviews the current status of MRI methods for routine clinical assessment of brain pathology, how these techniques identify neuropathology and how pathological findings are quantified. Diffusion tensor imaging (DTI), functional MRI (fMRI), and resting state fMRI are all reviewed, emphasizing how these techniques permit an examination of brain function and connectivity. General regional relationships of brain function associated with cognitive control will be highlighted.

  3. Beyond BOLD: optimizing functional imaging in stroke populations.

    PubMed

    Veldsman, Michele; Cumming, Toby; Brodtmann, Amy

    2015-04-01

    Blood oxygenation level-dependent (BOLD) signal changes are often assumed to directly reflect neural activity changes. Yet the real relationship is indirect, reliant on numerous assumptions, and subject to several sources of noise. Deviations from the core assumptions of BOLD contrast functional magnetic resonance imaging (fMRI), and their implications, have been well characterized in healthy populations, but are frequently neglected in stroke populations. In addition to conspicuous local structural and vascular changes after stroke, there are many less obvious challenges in the imaging of stroke populations. Perilesional ischemic changes, remodeling in regions distant to lesion sites, and diffuse perfusion changes all complicate interpretation of BOLD signal changes in standard fMRI protocols. Most stroke patients are also older than the young populations on which assumptions of neurovascular coupling and the typical analysis pipelines are based. We present a review of the evidence to show that the basic assumption of neurovascular coupling on which BOLD-fMRI relies does not capture the complex changes arising from stroke, both pathological and recovery related. As a result, estimating neural activity using the canonical hemodynamic response function is inappropriate in a number of contexts. We review methods designed to better estimate neural activity in stroke populations. One promising alternative to event-related fMRI is a resting-state-derived functional connectivity approach. Resting-state fMRI is well suited to stroke populations because it makes no performance demands on patients and is capable of revealing network-based pathology beyond the lesion site.

  4. 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.

  5. 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. PMID:24845620

  6. 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

  7. 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.

  8. 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.

  9. 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…

  10. Principal component analysis of scintimammographic images.

    PubMed

    Bonifazzi, Claudio; Cinti, Maria Nerina; Vincentis, Giuseppe De; Finos, Livio; Muzzioli, Valerio; Betti, Margherita; Nico, Lanconelli; Tartari, Agostino; Pani, Roberto

    2006-01-01

    The recent development of new gamma imagers based on scintillation array with high spatial resolution, has strongly improved the possibility of detecting sub-centimeter cancer in Scintimammography. However, Compton scattering contamination remains the main drawback since it limits the sensitivity of tumor detection. Principal component image analysis (PCA), recently introduced in scintimam nographic imaging, is a data reduction technique able to represent the radiation emitted from chest, breast healthy and damaged tissues as separated images. From these images a Scintimammography can be obtained where the Compton contamination is "removed". In the present paper we compared the PCA reconstructed images with the conventional scintimammographic images resulting from the photopeak (Ph) energy window. Data coming from a clinical trial were used. For both kinds of images the tumor presence was quantified by evaluating the t-student statistics for independent sample as a measure of the signal-to-noise ratio (SNR). Since the absence of Compton scattering, the PCA reconstructed images shows a better noise suppression and allows a more reliable diagnostics in comparison with the images obtained by the photopeak energy window, reducing the trend in producing false positive. PMID:17646004

  11. Optical multipolar spread functions of an aplanatic imaging system

    NASA Astrophysics Data System (ADS)

    Rouxel, Jérémy R.; Toury, Timothée

    2016-07-01

    The electromagnetic field near the focus of a perfect imaging system is calculated for different multipolar sources that play an important role in the radiation of nanostructures. Those multipoles are the exact and extended multipoles occurring in electrodynamics. The theory of diffraction of vector waves is reviewed rigorously for a dipolar radiation and applied to the imaging of multipolar sources. Different geometries are considered in order to connect with experiments and the multipolar spread functions are given in a ready-to-use format up to the octupolar order, in the general case and in the paraxial approximation. Defocus imaging is finally considered to provide a first step toward multipolar imaging.

  12. 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.

  13. 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. PMID:27142698

  14. Image analysis in comparative genomic hybridization

    SciTech Connect

    Lundsteen, C.; Maahr, J.; Christensen, B.

    1995-01-01

    Comparative genomic hybridization (CGH) is a new technique by which genomic imbalances can be detected by combining in situ suppression hybridization of whole genomic DNA and image analysis. We have developed software for rapid, quantitative CGH image analysis by a modification and extension of the standard software used for routine karyotyping of G-banded metaphase spreads in the Magiscan chromosome analysis system. The DAPI-counterstained metaphase spread is karyotyped interactively. Corrections for image shifts between the DAPI, FITC, and TRITC images are done manually by moving the three images relative to each other. The fluorescence background is subtracted. A mean filter is applied to smooth the FITC and TRITC images before the fluorescence ratio between the individual FITC and TRITC-stained chromosomes is computed pixel by pixel inside the area of the chromosomes determined by the DAPI boundaries. Fluorescence intensity ratio profiles are generated, and peaks and valleys indicating possible gains and losses of test DNA are marked if they exceed ratios below 0.75 and above 1.25. By combining the analysis of several metaphase spreads, consistent findings of gains and losses in all or almost all spreads indicate chromosomal imbalance. Chromosomal imbalances are detected either by visual inspection of fluorescence ratio (FR) profiles or by a statistical approach that compares FR measurements of the individual case with measurements of normal chromosomes. The complete analysis of one metaphase can be carried out in approximately 10 minutes. 8 refs., 7 figs., 1 tab.

  15. 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

  16. 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.

  17. Concept of functional imaging of memory decline in Alzheimer's disease.

    PubMed

    Drzezga, Alexander

    2008-04-01

    Functional imaging methods such as Positron Emission Tomography (PET) and functional Magnetic Resonance Imaging (fMRI) have contributed inestimably to the understanding of physiological cognitive processes in the brain in the recent decades. These techniques for the first time allowed the in vivo assessment of different features of brain function in the living human subject. It was therefore obvious to apply these methods to evaluate pathomechanisms of cognitive dysfunction in disorders such as Alzheimer's disease (AD) as well. One of the most dominant symptoms of AD is the impairment of memory. In this context, the term "memory" represents a simplification and summarizes a set of complex cognitive functions associated with encoding and retrieval of different types of information. A number of imaging studies assessed the functional changes of neuronal activity in the brain at rest and also during performance of cognitive work, with regard to specific characteristics of memory decline in AD. In the current article, basic principles of common functional imaging procedures will be explained and it will be discussed how they can be reasonably applied for the assessment of memory decline in AD. Furthermore, it will be illustrated how these imaging procedures have been employed to improve early and specific diagnosis of the disease, to understand specific pathomechanisms of memory dysfunction and associated compensatory mechanisms, and to draw reverse conclusions on physiological function of memory.

  18. 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.

  19. Image-based modeling of lung structure and function

    PubMed Central

    Tawhai, Merryn H.; Lin, Ching-Long

    2010-01-01

    Current state-of-the-art in image-based modeling allows derivation of patient-specific models of the lung, lobes, airways, and pulmonary vascular trees. The application of traditional engineering analyses of fluid and structural mechanics to image-based subject-specific models has the potential to provide new insight into structure-function relationships in the individual via functional interpretation that complements imaging and experimental studies. Three major issues that are encountered in studies of air flow through the bronchial airways are the representation of airway geometry, the imposition of physiological boundary conditions, and the treatment of turbulence. Here we review some efforts to resolve each of these issues, with particular focus on image-based models that have been developed to simulate air flow from the mouth to the terminal bronchiole, and subjected to physiologically meaningful boundary conditions via image registration and soft tissue mechanics models. PMID:21105146

  20. Functional magnetic resonance imaging in neurology.

    PubMed

    Auer, Tibor; Schwarcz, Attila; Horváth, Réka A; Barsi, Péter; Janszky, József

    2008-01-30

    The present contribution discusses the clinical use of functional MRI (fMRI) and its role in the most common neurological diseases. FMRI was found a reliable and reproducible examination tool resulting in a wide distribution of fMRI methods in presurgical evaluation of epilepsy in determining the relationship of eloquent areas and the epileptic focus. Preliminary data suggest that fMRI using memory paradigms can predict the postoperative memory decline in epilepsy surgery by determining whether a reorganization of memory functions took place. Speech-activated fMRI became the most used tool in determining hemispheric dominance. Visual and sensory-motor cortex can also be routinely investigated by fMRI which helps in decision on epilepsy surgery. FMRI combined with EEG is a new diagnostic tool in epilepsy and sleep disorders. FMRI can identify the penumbra after stroke and can provide an additional information on metabolic state of the threatened brain tissue. FMRI has a predictive role in post-stroke recovery. In relapsing-remitting MS an adaptive reorganization can be demonstrated by fMRI affecting the visual, motor, and memory systems, despite preserved functional performance. Much more extensive reorganization can be demonstrated in secondary progressive MS. These findings suggest that the different stages of MS are related to different stages of the reorganization and MS becomes progressive when there is no more reserve capacity in the brain for reorganization. FMRI offers the capability of detecting early functional hemodynamic alterations in Alzheimer's disease before morphological changes. FMRI can be a valuable tool to test and monitor treatment efficacy in AD. FMRI can also provide information about the mechanisms of different therapeutic approaches in Parkinson disorder including drug treatment and deep brain stimulation.

  1. Occupational Functionality: A Concept Analysis.

    PubMed

    Combs, Bryan; Heaton, Karen

    2016-08-01

    Occupational health nursing has evolved since the late 19th century and, with the inclusion of advanced practice nursing, has become essential to the health and safety of workers. A key component of the knowledge required of advanced practice occupational health nurses is an understanding of what it means for workers to be fit for duty The definition or concept of being fit for duty varies depending on the point-of-view of the health care provider. Health care providers across all professions must have a consistent understanding of what it means to be fit for duty Literature shows that professions and specialties that often collaborate have varying ideas about what it means to be fit for duty These differences highlight the need for a consistent concept that can be used across professions, is holistic, and incorporates other concepts critical to all points of view. To better understand fit for duty, a concept analysis, using the Walker and Avant framework, focused on the concept of occupational functionality (OF). Occupational functionality is best defined as the qualities of being suited to serve an occupational purpose efficiently and effectively within the physical, occupational, environmental, and psychological demands of a unique work setting. This concept analysis offers an initial step in understanding fit for duty and gives health care providers a concept that can be used across disciplines. PMID:27462030

  2. 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…

  3. Functional Magnetic Resonance Imaging in Acute Kidney Injury: Present Status

    PubMed Central

    Zhou, Hai Ying; Chen, Tian Wu; Zhang, Xiao Ming

    2016-01-01

    Acute kidney injury (AKI) is a common complication of hospitalization that is characterized by a sudden loss of renal excretory function and associated with the subsequent development of chronic kidney disease, poor prognosis, and increased mortality. Although the pathophysiology of renal functional impairment in the setting of AKI remains poorly understood, previous studies have identified changes in renal hemodynamics, perfusion, and oxygenation as key factors in the development and progression of AKI. The early assessment of these changes remains a challenge. Many established approaches are not applicable to humans because of their invasiveness. Functional renal magnetic resonance (MR) imaging offers an alternative assessment tool that could be used to evaluate renal morphology and function noninvasively and simultaneously. Thus, the purpose of this review is to illustrate the principle, application, and role of the techniques of functional renal MR imaging, including blood oxygen level-dependent imaging, arterial spin labeling, and diffusion-weighted MR imaging, in the management of AKI. The use of gadolinium in MR imaging may exacerbate renal impairment and cause nephrogenic systemic fibrosis. Therefore, dynamic contrast-enhanced MR imaging will not be discussed in this paper. PMID:26925411

  4. 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.

  5. A Wave Equation Migration Method for Receiver Function Imaging

    NASA Astrophysics Data System (ADS)

    Chen, L.; Wen, L.; Zheng, T.

    2004-12-01

    A wave equation based poststack depth migration method is proposed to image the crustal and upper mantle structures using teleseismic receiver functions. By utilizing a frequency-wavenumber domain one-way phase-screen propagator for wavefield extrapolation in the migration scheme, the common conversion point (CCP) stacked receiver functions are backward propagated to construct the subsurface structural images. Synthetic experiments demonstrate the validity of the migration method for a variety of laterally heterogeneous models. The migrated images show considerable improvement over the CCP images in recovering the structural features. The phase-screen propagator migration method proves to be particularly useful for imaging complex structures and deep discontinuities overlain by strong shallow anomalies, because of its capability of handling lateral velocity variations. Influences of several factors on the image quality of the poststack migration are further investigated, including inter-station spacing, noise level of the data, velocity model used in migration, and earthquake distribution (incident direction of source fields). Theoretical derivation and numerical results suggest that both the CCP stacking and the poststack migration of receiver functions need to be designed in a target-oriented way for reliable and efficient imaging, and special consideration on earthquake distribution is particularly required in designing seismic experiments if structures of large dips are present. The proposed wav equation migration scheme is applied to image the Earth's internal structures using a number of dense field data sets collected at many seismic arrays in Asia. The constructed images reveal several interesting subsurface structures of the study regions and synthetic tests indicate that those subsurface features are well resolved by the seismic data. Significant improvements of the image quality demonstrate the great potential and flexibility of the proposed migration

  6. Repeated-Measures Analysis of Image Data

    NASA Technical Reports Server (NTRS)

    Newton, H. J.

    1983-01-01

    It is suggested that using a modified analysis of variance procedure on data sampled systematically from a rectangular array of image data can provide a measure of homogeneity of means over that array in single directions and how variation in perpendicular directions interact. The modification of analysis of variance required to account for spatial correlation is described theoretically and numerically on simulated data.

  7. 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.

  8. A computational framework for exploratory data analysis in biomedical imaging

    NASA Astrophysics Data System (ADS)

    Wismueller, Axel

    2009-02-01

    Purpose: To develop, test, and evaluate a novel unsupervised machine learning method for the analysis of multidimensional biomedical imaging data. Methods: The Exploration Machine (XOM) is introduced as a method for computing low-dimensional representations of high-dimensional observations. XOM systematically inverts functional and structural components of topology-preserving mappings. Thus, it can contribute to both structure-preserving visualization and data clustering. We applied XOM to the analysis of microarray imaging data of gene expression profiles in Saccharomyces cerevisiae, and to model-free analysis of functional brain MRI data by unsupervised clustering. For both applications, we performed quantitative comparisons to results obtained by established algorithms. Results: Genome data: Absolute (relative) Sammon error values were 2.21 Â. 103 (1.00) for XOM, 2.45 Â. 103 (1.11) for Sammon's mapping, 2.77 Â. 103 (1.25) for Locally Linear Embedding (LLE), 2.82 Â. 103 (1.28) for PCA, 3.36 Â. 103 (1.52) for Isomap, and 10.19 Â. 103(4.61) for Self-Organizing Map (SOM). - Functional MRI data: Areas under ROC curves for detection of task-related brain activation were 0.984 +/- 0.03 for XOM, 0.983 +/- 0.02 for Minimal-Free-Energy VQ, and 0.979 +/- 0.02 for SOM. Conclusion: We introduce the Exploration Machine as a novel machine learning method for the analysis of multidimensional biomedical imaging data. XOM can be successfully applied to microarray gene expression analysis and to clustering of functional brain MR image time-series. By simultaneously contributing to dimensionality reduction and data clustering, XOM is a useful novel method for data analysis in biomedical imaging.

  9. Hybrid µCT-FMT imaging and image analysis

    PubMed Central

    Zafarnia, Sara; Babler, Anne; Jahnen-Dechent, Willi; Lammers, Twan; Lederle, Wiltrud; Kiessling, Fabian

    2015-01-01

    Fluorescence-mediated tomography (FMT) enables longitudinal and quantitative determination of the fluorescence distribution in vivo and can be used to assess the biodistribution of novel probes and to assess disease progression using established molecular probes or reporter genes. The combination with an anatomical modality, e.g., micro computed tomography (µCT), is beneficial for image analysis and for fluorescence reconstruction. We describe a protocol for multimodal µCT-FMT imaging including the image processing steps necessary to extract quantitative measurements. After preparing the mice and performing the imaging, the multimodal data sets are registered. Subsequently, an improved fluorescence reconstruction is performed, which takes into account the shape of the mouse. For quantitative analysis, organ segmentations are generated based on the anatomical data using our interactive segmentation tool. Finally, the biodistribution curves are generated using a batch-processing feature. We show the applicability of the method by assessing the biodistribution of a well-known probe that binds to bones and joints. PMID:26066033

  10. Some problems for representations of brain organization based on activation in functional imaging.

    PubMed

    Sidtis, John J

    2007-08-01

    Functional brain imaging has overshadowed traditional lesion studies in becoming the dominant approach to the study of brain-behavior relationships. The proponents of functional imaging studies frequently argue that this approach provides an advantage over lesion studies by observing normal brain activity in vivo without the disruptive effects of brain damage. However, the enthusiastic onslaught of brain images, frequently presented as veridical representations of mental function, has sometimes overwhelmed some basic facts about brain organization repeatedly observed over more than a century. In particular, the lateralization of speech and language to the left cerebral hemisphere in over 90% of the right-handed population does not appear to have been taken as a serious constraint in the interpretation of imaging results in studies of these functions. This paper reviews a number of areas in which standard activation assumptions yield results that are at odds with clinical experience. The activation approach will be contrasted with a performance-based analysis of functional image data, which, at least in the case of speech production, yields results in better agreement with lesion data. Functional imaging represents enormous opportunities for understanding brain-behavior relationships, but at the present level of understanding of what is being represented in such images, it is premature to adhere to a single approach based on the strong but questionable assumptions inherent in most activation studies. PMID:16938343

  11. Functional oesophago-gastric junction imaging

    PubMed Central

    McMahon, Barry P; Drewes, Asbjørn Mohr; Gregersen, Hans

    2006-01-01

    Despite its role in disease there is still no definitive method to assess oesophago-gastric junction competence (OGJ). Traditionally the OGJ has been assessed using manometry with lower oesophageal sphincter pressure as the indicator. More recently this has been shown not to be a very reliable marker of sphincter function and competence against reflux. Disorders such as gastro-oesophageal reflux disease and to a lesser extend achalasia still effects a significant number of patients. This review looks at using a new technique known as impedance planimetry to profile the geometry and pressure in the OGJ during distension of a bag. The data gathered can be reconstructed into a dynamic representation of OGJ action. This has been shown to provide a useful representation of the OGJ and to show changes to the competence of the OGJ in terms of compliance and distensibility as a result of endoluminal therapy. PMID:16718804

  12. 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. PMID:24114100

  13. Functional magnetic resonance imaging (FMRI) and expert testimony.

    PubMed

    Kulich, Ronald; Maciewicz, Raymond; Scrivani, Steven J

    2009-03-01

    Medical experts frequently use imaging studies to illustrate points in their court testimony. This article reviews how these studies impact the credibility of expert testimony with judges and juries. The apparent "objective" evidence provided by such imaging studies can lend strong credence to a judge's or jury's appraisal of medical expert's testimony. However, as the court usually has no specialized scientific expertise, the use of complex images as part of courtroom testimony also has the potential to mislead or at least inappropriately bias the weight given to expert evidence. Recent advances in brain imaging may profoundly impact forensic expert testimony. Functional magnetic resonance imaging and other physiologic imaging techniques currently allow visualization of the activation pattern of brain regions associated with a wide variety of cognitive and behavioral tasks, and more recently, pain. While functional imaging technology has a valuable role in brain research and clinical investigation, it is important to emphasize that the use of imaging studies in forensic matters requires a careful scientific foundation and a rigorous legal assessment. PMID:19254335

  14. 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. PMID:26828757

  15. 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

  16. 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.

  17. 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. PMID:11407959

  18. Interpretable functional principal component analysis.

    PubMed

    Lin, Zhenhua; Wang, Liangliang; Cao, Jiguo

    2016-09-01

    Functional principal component analysis (FPCA) is a popular approach to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs). The intervals where the values of FPCs are significant are interpreted as where sample curves have major variations. However, these intervals are often hard for naïve users to identify, because of the vague definition of "significant values". In this article, we develop a novel penalty-based method to derive FPCs that are only nonzero precisely in the intervals where the values of FPCs are significant, whence the derived FPCs possess better interpretability than the FPCs derived from existing methods. To compute the proposed FPCs, we devise an efficient algorithm based on projection deflation techniques. We show that the proposed interpretable FPCs are strongly consistent and asymptotically normal under mild conditions. Simulation studies confirm that with a competitive performance in explaining variations of sample curves, the proposed FPCs are more interpretable than the traditional counterparts. This advantage is demonstrated by analyzing two real datasets, namely, electroencephalography data and Canadian weather data.

  19. Data analysis for GOPEX image frames

    NASA Technical Reports Server (NTRS)

    Levine, B. M.; Shaik, K. S.; Yan, T.-Y.

    1993-01-01

    The data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between 9-16 Dec. 1992 is described. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mexico. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public release images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a daily basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. Processing steps are described and the theories are compared with the experimental results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimental planning to geometrically locate pulse positions with greater certainty.

  20. Cancer detection by quantitative fluorescence image analysis.

    PubMed

    Parry, W L; Hemstreet, G P

    1988-02-01

    Quantitative fluorescence image analysis is a rapidly evolving biophysical cytochemical technology with the potential for multiple clinical and basic research applications. We report the application of this technique for bladder cancer detection and discuss its potential usefulness as an adjunct to methods used currently by urologists for the diagnosis and management of bladder cancer. Quantitative fluorescence image analysis is a cytological method that incorporates 2 diagnostic techniques, quantitation of nuclear deoxyribonucleic acid and morphometric analysis, in a single semiautomated system to facilitate the identification of rare events, that is individual cancer cells. When compared to routine cytopathology for detection of bladder cancer in symptomatic patients, quantitative fluorescence image analysis demonstrated greater sensitivity (76 versus 33 per cent) for the detection of low grade transitional cell carcinoma. The specificity of quantitative fluorescence image analysis in a small control group was 94 per cent and with the manual method for quantitation of absolute nuclear fluorescence intensity in the screening of high risk asymptomatic subjects the specificity was 96.7 per cent. The more familiar flow cytometry is another fluorescence technique for measurement of nuclear deoxyribonucleic acid. However, rather than identifying individual cancer cells, flow cytometry identifies cellular pattern distributions, that is the ratio of normal to abnormal cells. Numerous studies by others have shown that flow cytometry is a sensitive method to monitor patients with diagnosed urological disease. Based upon results in separate quantitative fluorescence image analysis and flow cytometry studies, it appears that these 2 fluorescence techniques may be complementary tools for urological screening, diagnosis and management, and that they also may be useful separately or in combination to elucidate the oncogenic process, determine the biological potential of tumors

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

    PubMed

    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.

  2. Advanced automated char image analysis techniques

    SciTech Connect

    Tao Wu; Edward Lester; Michael Cloke

    2006-05-15

    Char morphology is an important characteristic when attempting to understand coal behavior and coal burnout. In this study, an augmented algorithm has been proposed to identify char types using image analysis. On the basis of a series of image processing steps, a char image is singled out from the whole image, which then allows the important major features of the char particle to be measured, including size, porosity, and wall thickness. The techniques for automated char image analysis have been tested against char images taken from ICCP Char Atlas as well as actual char particles derived from pyrolyzed char samples. Thirty different chars were prepared in a drop tube furnace operating at 1300{sup o}C, 1% oxygen, and 100 ms from 15 different world coals sieved into two size fractions (53-75 and 106-125 {mu}m). The results from this automated technique are comparable with those from manual analysis, and the additional detail from the automated sytem has potential use in applications such as combustion modeling systems. Obtaining highly detailed char information with automated methods has traditionally been hampered by the difficulty of automatic recognition of individual char particles. 20 refs., 10 figs., 3 tabs.

  3. 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

  4. 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…

  5. A pairwise image analysis with sparse decomposition

    NASA Astrophysics Data System (ADS)

    Boucher, A.; Cloppet, F.; Vincent, N.

    2013-02-01

    This paper aims to detect the evolution between two images representing the same scene. The evolution detection problem has many practical applications, especially in medical images. Indeed, the concept of a patient "file" implies the joint analysis of different acquisitions taken at different times, and the detection of significant modifications. The research presented in this paper is carried out within the application context of the development of computer assisted diagnosis (CAD) applied to mammograms. It is performed on already registered pair of images. As the registration is never perfect, we must develop a comparison method sufficiently adapted to detect real small differences between comparable tissues. In many applications, the assessment of similarity used during the registration step is also used for the interpretation step that yields to prompt suspicious regions. In our case registration is assumed to match the spatial coordinates of similar anatomical elements. In this paper, in order to process the medical images at tissue level, the image representation is based on elementary patterns, therefore seeking patterns, not pixels. Besides, as the studied images have low entropy, the decomposed signal is expressed in a parsimonious way. Parsimonious representations are known to help extract the significant structures of a signal, and generate a compact version of the data. This change of representation should allow us to compare the studied images in a short time, thanks to the low weight of the images thus represented, while maintaining a good representativeness. The good precision of our results show the approach efficiency.

  6. Current Status of Functional Imaging in Eating Disorders

    PubMed Central

    Frank, Guido K.W.; Kaye, Walter H.

    2013-01-01

    Eating Disorders are complex psychiatric problems that involve biologic and psychological factors. Brain imaging studies provide insights how functionally connected brain networks may contribute to disturbed eating behavior, resulting in food refusal and altered body weight, but also body preoccupations and heightened anxiety. In this article we review the current state of brain imaging in eating disorders, and how such techniques may help identify pathways that could be important in the treatment of those often detrimental disorders. PMID:22532388

  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. )

    1992-01-01

    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.

  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.

    1992-09-01

    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.

  9. Automated eXpert Spectral Image Analysis

    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 limtedmore » 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

  10. 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.

  11. 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.

  12. Challenges of functional imaging research of pain in children

    PubMed Central

    Sava, Simona; Lebel, Alyssa A; Leslie, David S; Drosos, Athena; Berde, Charles; Becerra, Lino; Borsook, David

    2009-01-01

    Functional imaging has revolutionized the neurosciences. In the pain field it has dramatically altered our understanding of how the brain undergoes significant functional, anatomical and chemical changes in patients with chronic pain. However, most studies have been performed in adults. Because functional imaging is non-invasive and can be performed in awake individuals, applications in children have become more prevalent, but only recently in the pain field. Measures of changes in the brains of children have important implications in understanding neural plasticity in response to acute and chronic pain in the developing brain. Such findings may have implications for treatments in children affected by chronic pain and provide novel insights into chronic pain syndromes in adults. In this review we summarize this potential and discuss specific concerns related to the imaging of pain in children. PMID:19531255

  13. Functional requirements for a central research imaging data repository.

    PubMed

    Franke, Thomas; Gruetz, Romanus; Dickmann, Frank

    2013-01-01

    The current situation at many university medical centers regarding the management of biomedical research imaging data leaves much to be desired. In contrast to the recommendations of the German Research Foundation (DFG) and the German Council of Sciences and Humanities regarding the professional management of research data, there are commonly many individual data pools for research data in each institute and the management remains the responsibility of the researcher. A possible solution for this situation would be to install local central repositories for biomedical research imaging data. In this paper, we developed a scenario based on abstracted use-cases for institutional research undertakings as well as collaborative biomedical research projects and analyzed the functional requirements that a local repository would have to fulfill. We determined eight generic categories of functional requirements, which can be viewed as a basic guideline for the minimum functionality of a central repository for biomedical research imaging data.

  14. 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.

  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. 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.

  17. Applications Of Binary Image Analysis Techniques

    NASA Astrophysics Data System (ADS)

    Tropf, H.; Enderle, E.; Kammerer, H. P.

    1983-10-01

    After discussing the conditions where binary image analysis techniques can be used, three new applications of the fast binary image analysis system S.A.M. (Sensorsystem for Automation and Measurement) are reported: (1) The human view direction is measured at TV frame rate while the subject's head is free movable. (2) Industrial parts hanging on a moving conveyor are classified prior to spray painting by robot. (3) In automotive wheel assembly, the eccentricity of the wheel is minimized by turning the tyre relative to the rim in order to balance the eccentricity of the components.

  18. Microscopical image analysis: problems and approaches.

    PubMed

    Bradbury, S

    1979-03-01

    This article reviews some of the problems which have been encountered in the application of automatic image analysis to problems in biology. Some of the questions involved in the actual formulation of such a problem for this approach are considered as well as the difficulties in the analysis due to lack of specific constrast in the image and to its complexity. Various practical methods which have been successful in overcoming these problems are outlined, and the question of the desirability of an opto-manual or semi-automatic system as opposed to a fully automatic version is considered.

  19. 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.

  20. 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…

  1. Noninvasive functional cardiac electrical source imaging: combining MRI and ECG mapping for imaging electrical function

    NASA Astrophysics Data System (ADS)

    Tilg, Bernhard; Modre, Robert; Fischer, Gerald; Hanser, Friedrich; Messnarz, Bernd; Schocke, Michael F. H.; Kremser, Christian; Roithinger, Franz

    2002-04-01

    Inverse electrocardiography has been developing for several years. By coupling electrocardiographic mapping and 3D+time anatomical data, the electrical excitation sequence can be imaged completely noninvasively in the human heart. In this study, a bidomain theory based surface heart model activation time imaging approach was applied to single beat data of atrial and ventricular depolarization. For sinus and paced rhythms, the sites of early activation and the areas with late activation were estimated with sufficient accuracy. In particular for focal arrhythmias, this model-based imaging approach might allow the guidance and evaluation of antiarrhythmic interventions, for instance, in case of catheter ablation or drug therapy.

  2. SIMA: Python software for analysis of dynamic fluorescence imaging data

    PubMed Central

    Kaifosh, Patrick; Zaremba, Jeffrey D.; Danielson, Nathan B.; Losonczy, Attila

    2014-01-01

    Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs), and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI) for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at http://www.losonczylab.org/sima/. PMID:25295002

  3. SIMA: Python software for analysis of dynamic fluorescence imaging data.

    PubMed

    Kaifosh, Patrick; Zaremba, Jeffrey D; Danielson, Nathan B; Losonczy, Attila

    2014-01-01

    Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs), and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI) for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at http://www.losonczylab.org/sima/.

  4. Analysis of an interferometric Stokes imaging polarimeter

    NASA Astrophysics Data System (ADS)

    Murali, Sukumar

    Estimation of Stokes vector components from an interferometric fringe encoded image is a novel way of measuring the State Of Polarization (SOP) distribution across a scene. Imaging polarimeters employing interferometric techniques encode SOP in- formation across a scene in a single image in the form of intensity fringes. The lack of moving parts and use of a single image eliminates the problems of conventional polarimetry - vibration, spurious signal generation due to artifacts, beam wander, and need for registration routines. However, interferometric polarimeters are limited by narrow bandpass and short exposure time operations which decrease the Signal to Noise Ratio (SNR) defined as the ratio of the mean photon count to the standard deviation in the detected image. A simulation environment for designing an Interferometric Stokes Imaging polarimeter (ISIP) and a detector with noise effects is created and presented. Users of this environment are capable of imaging an object with defined SOP through an ISIP onto a detector producing a digitized image output. The simulation also includes bandpass imaging capabilities, control of detector noise, and object brightness levels. The Stokes images are estimated from a fringe encoded image of a scene by means of a reconstructor algorithm. A spatial domain methodology involving the idea of a unit cell and slide approach is applied to the reconstructor model developed using Mueller calculus. The validation of this methodology and effectiveness compared to a discrete approach is demonstrated with suitable examples. The pixel size required to sample the fringes and minimum unit cell size required for reconstruction are investigated using condition numbers. The importance of the PSF of fore-optics (telescope) used in imaging the object is investigated and analyzed using a point source imaging example and a Nyquist criteria is presented. Reconstruction of fringe modulated images in the presence of noise involves choosing an

  5. 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.

  6. 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

  7. 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.

  8. Image distortion analysis using polynomial series expansion.

    PubMed

    Baggenstoss, Paul M

    2004-11-01

    In this paper, we derive a technique for analysis of local distortions which affect data in real-world applications. In the paper, we focus on image data, specifically handwritten characters. Given a reference image and a distorted copy of it, the method is able to efficiently determine the rotations, translations, scaling, and any other distortions that have been applied. Because the method is robust, it is also able to estimate distortions for two unrelated images, thus determining the distortions that would be required to cause the two images to resemble each other. The approach is based on a polynomial series expansion using matrix powers of linear transformation matrices. The technique has applications in pattern recognition in the presence of distortions. PMID:15521492

  9. Principal Components Analysis In Medical Imaging

    NASA Astrophysics Data System (ADS)

    Weaver, J. B.; Huddleston, A. L.

    1986-06-01

    Principal components analysis, PCA, is basically a data reduction technique. PCA has been used in several problems in diagnostic radiology: processing radioisotope brain scans (Ref.1), automatic alignment of radionuclide images (Ref. 2), processing MRI images (Ref. 3,4), analyzing first-pass cardiac studies (Ref. 5) correcting for attenuation in bone mineral measurements (Ref. 6) and in dual energy x-ray imaging (Ref. 6,7). This paper will progress as follows; a brief introduction to the mathematics of PCA will be followed by two brief examples of how PCA has been used in the literature. Finally my own experience with PCA in dual-energy x-ray imaging will be given.

  10. 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. PMID:27277901

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. PIXE analysis and imaging of papyrus documents

    NASA Astrophysics Data System (ADS)

    Lövestam, N. E. Göran; Swietlicki, Erik

    1990-01-01

    The analysis of antique papyrus documents using an external milliprobe is described. Missing characters of text in the documents were made visible by means of PIXE analysis and X-ray imaging of the areas studied. The contrast between the papyrus and the ink was further increased when the information contained in all the elements was taken into account simultaneously using a multivariate technique (partial least-squares regression).

  16. Functional Analysis of Transcription Factors in Arabidopsis

    PubMed Central

    Mitsuda, Nobutaka; Ohme-Takagi, Masaru

    2009-01-01

    Transcription factors (TFs) regulate the expression of genes at the transcriptional level. Modification of TF activity dynamically alters the transcriptome, which leads to metabolic and phenotypic changes. Thus, functional analysis of TFs using ‘omics-based’ methodologies is one of the most important areas of the post-genome era. In this mini-review, we present an overview of Arabidopsis TFs and introduce strategies for the functional analysis of plant TFs, which include both traditional and recently developed technologies. These strategies can be assigned to five categories: bioinformatic analysis; analysis of molecular function; expression analysis; phenotype analysis; and network analysis for the description of entire transcriptional regulatory networks. PMID:19478073

  17. Visualization of Parameter Space for Image Analysis

    PubMed Central

    Pretorius, A. Johannes; Bray, Mark-Anthony P.; Carpenter, Anne E.; Ruddle, Roy A.

    2013-01-01

    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. PMID:22034361

  18. 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.

  19. 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…

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Functional DNA Nanomaterials for Sensing and Imaging in Living Cells

    PubMed Central

    Torabi, Seyed-Fakhreddin; Lu, Yi

    2014-01-01

    Recent developments in integrating high selectivity of functional DNA, such as DNAzyme and aptamers, with efficient DNA delivery into cells by gold nanoparticles or superior near-infrared optical properties of upconversion nanoparticles are reviewed. Their applications in sensing and imaging small organic metabolites, toxins, metal ions, pH, DNA, RNA, proteins, and pathogens are summarized. The advantages and future directions of these functional DNA materials are discussed. PMID:24468446

  6. 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.

  7. 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.

  8. Single photon emission computed tomography of the heart: a functional image

    SciTech Connect

    Itti, R.; Casset, D.; Philippe, L.; Brochier, M.

    1987-01-01

    Images of radioactive tracer uptake are mainly functional images since the tracer distribution may directly be related to the regional variations in function, such as myocardial perfusion in the case of thallium-201 single photon tomography. Combination of pictures obtained in different physiological conditions (stress-rest, for instance) enhance the functional aspects of these studies. For gated cardiac blood pool images, on the contrary, labelling of the circulating blood pool using technetium-99m provides morphological pictures of the heart chambers and function can only be derived from the dynamic analysis of the image sequence recorded at the successive phases of the cardiac cycle. The technique of thick slice tomography preserves the relationship between count rates and local volumes of radioactive blood. Parametric imaging therefore applies to tomography as well as to plane projections. In the simplest case reconstruction of the extreme phases of the heart beat, end-diastole and end-systole may be sufficient. But to achieve more sophisticated functional analysis such as Fourier phase mapping, reconstruction of the whole cardiac cycle is necessary.

  9. 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

  10. 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.

  11. 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…

  12. Coherence imaging by use of a Newton rings sampling function.

    PubMed

    Podoleanu, A G; Dobre, G M; Webb, D J; Jackson, D A

    1996-11-01

    We show that, with suitable optics in the arm of a Michelson interferometer, orthogonal galvo-scanning mirrors build a sampling function in the form of Newton rings when the two interferometer arms are matched. Using a low-coherence source, one can obtain transversal depth-resolved images. A fast display procedure using a storage oscilloscope was devised based on this method.

  13. Frequency domain analysis of knock images

    NASA Astrophysics Data System (ADS)

    Qi, Yunliang; He, Xin; Wang, Zhi; Wang, Jianxin

    2014-12-01

    High speed imaging-based knock analysis has mainly focused on time domain information, e.g. the spark triggered flame speed, the time when end gas auto-ignition occurs and the end gas flame speed after auto-ignition. This study presents a frequency domain analysis on the knock images recorded using a high speed camera with direct photography in a rapid compression machine (RCM). To clearly visualize the pressure wave oscillation in the combustion chamber, the images were high-pass-filtered to extract the luminosity oscillation. The luminosity spectrum was then obtained by applying fast Fourier transform (FFT) to three basic colour components (red, green and blue) of the high-pass-filtered images. Compared to the pressure spectrum, the luminosity spectra better identify the resonant modes of pressure wave oscillation. More importantly, the resonant mode shapes can be clearly visualized by reconstructing the images based on the amplitudes of luminosity spectra at the corresponding resonant frequencies, which agree well with the analytical solutions for mode shapes of gas vibration in a cylindrical cavity.

  14. 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.

  15. 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

  16. Real-time microstructural and functional imaging and image processing in optical coherence tomography

    NASA Astrophysics Data System (ADS)

    Westphal, Volker

    Optical Coherence Tomography (OCT) is a noninvasive optical imaging technique that allows high-resolution cross-sectional imaging of tissue microstructure, achieving a spatial resolution of about 10 mum. OCT is similar to B-mode ultrasound (US) except that it uses infrared light instead of ultrasound. In contrast to US, no coupling gel is needed, simplifying the image acquisition. Furthermore, the fiber optic implementation of OCT is compatible with endoscopes. In recent years, the transition from slow imaging, bench-top systems to real-time clinical systems has been under way. This has lead to a variety of applications, namely in ophthalmology, gastroenterology, dermatology and cardiology. First, this dissertation will demonstrate that OCT is capable of imaging and differentiating clinically relevant tissue structures in the gastrointestinal tract. A careful in vitro correlation study between endoscopic OCT images and corresponding histological slides was performed. Besides structural imaging, OCT systems were further developed for functional imaging, as for example to visualize blood flow. Previously, imaging flow in small vessels in real-time was not possible. For this research, a new processing scheme similar to real-time Doppler in US was introduced. It was implemented in dedicated hardware to allow real-time acquisition and overlayed display of blood flow in vivo. A sensitivity of 0.5mm/s was achieved. Optical coherence microscopy (OCM) is a variation of OCT, improving the resolution even further to a few micrometers. Advances made in the OCT scan engine for the Doppler setup enabled real-time imaging in vivo with OCM. In order to generate geometrical correct images for all the previous applications in real-time, extensive image processing algorithms were developed. Algorithms for correction of distortions due to non-telecentric scanning, nonlinear scan mirror movements, and refraction were developed and demonstrated. This has led to interesting new

  17. Cerebellum and speech perception: a functional magnetic resonance imaging study.

    PubMed

    Mathiak, Klaus; Hertrich, Ingo; Grodd, Wolfgang; Ackermann, Hermann

    2002-08-15

    A variety of data indicate that the cerebellum participates in perceptual tasks requiring the precise representation of temporal information. Access to the word form of a lexical item requires, among other functions, the processing of durational parameters of verbal utterances. Therefore, cerebellar dysfunctions must be expected to impair word recognition. In order to specify the topography of the assumed cerebellar speech perception mechanism, a functional magnetic resonance imaging study was performed using the German lexical items "Boden" ([bodn], Engl. "floor") and "Boten" ([botn], "messengers") as test materials. The contrast in sound structure of these two lexical items can be signaled either by the length of the wordmedial pause (closure time, CLT; an exclusively temporal measure) or by the aspiration noise of wordmedial "d" or "t" (voice onset time, VOT; an intrasegmental cue). A previous study found bilateral cerebellar disorders to compromise word recognition based on CLT whereas the encoding of VOT remained unimpaired. In the present study, two series of "Boden - Boten" utterances were resynthesized, systematically varying either in CLT or VOT. Subjects had to identify both words "Boden" and "Boten" by analysis of either the durational parameter CLT or the VOT aspiration segment. In a subtraction design, CLT categorization as compared to VOT identification (CLT - VOT) yielded a significant hemodynamic response of the right cerebellar hemisphere (neocerebellum Crus I) and the frontal lobe (anterior to Broca's area). The reversed contrast ( VOT - CLT) resulted in a single activation cluster located at the level of the supratemporal plane of the dominant hemisphere. These findings provide first evidence for a distinct contribution of the right cerebellar hemisphere to speech perception in terms of encoding of durational parameters of verbal utterances. Verbal working memory tasks, lexical response selection, and auditory imagery of word strings have been

  18. Semiautomated ROI analysis in dynamic MR studies. Part I: Image analysis tools for automatic correction of organ displacements.

    PubMed

    Gerig, G; Kikinis, R; Kuoni, W; von Schulthess, G K; Kübler, O

    1991-01-01

    The most important problem in the analysis of time sequences is the compensation for artifactual motion. Owing to motion, medical images of the abdominal region do not represent organs with fixed configuration. Analysis of organ function with dynamic contrast medium studies using regions of interest (ROIs) is thus not readily accomplished. Images of the organ of interest need to be registered and corrected prior to a detailed local analysis. We have developed an image analysis scheme that allows the automatic detection of the organ contours, the extraction of the motion parameters per frame, and the registration of images. The complete procedure requires only minimal user interaction and results in a readjusted image sequence, where organs of interest remain fixed. Both a visual analysis of the dynamic behavior of functional properties and a quantitative statistical analysis of signal intensity versus time within local ROIs are considerably facilitated using the corrected series.

  19. 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.

  20. 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.

  1. Autonomous Image Analysis for Future Mars Missions

    NASA Technical Reports Server (NTRS)

    Gulick, V. C.; Morris, R. L.; Ruzon, M. A.; Bandari, E.; Roush, T. L.

    1999-01-01

    To explore high priority landing sites and to prepare for eventual human exploration, future Mars missions will involve rovers capable of traversing tens of kilometers. However, the current process by which scientists interact with a rover does not scale to such distances. Specifically, numerous command cycles are required to complete even simple tasks, such as, pointing the spectrometer at a variety of nearby rocks. In addition, the time required by scientists to interpret image data before new commands can be given and the limited amount of data that can be downlinked during a given command cycle constrain rover mobility and achievement of science goals. Experience with rover tests on Earth supports these concerns. As a result, traverses to science sites as identified in orbital images would require numerous science command cycles over a period of many weeks, months or even years, perhaps exceeding rover design life and other constraints. Autonomous onboard science analysis can address these problems in two ways. First, it will allow the rover to preferentially transmit "interesting" images, defined as those likely to have higher science content. Second, the rover will be able to anticipate future commands. For example, a rover might autonomously acquire and return spectra of "interesting" rocks along with a high-resolution image of those rocks in addition to returning the context images in which they were detected. Such approaches, coupled with appropriate navigational software, help to address both the data volume and command cycle bottlenecks that limit both rover mobility and science yield. We are developing fast, autonomous algorithms to enable such intelligent on-board decision making by spacecraft. Autonomous algorithms developed to date have the ability to identify rocks and layers in a scene, locate the horizon, and compress multi-spectral image data. We are currently investigating the possibility of reconstructing a 3D surface from a sequence of images

  2. Functional Neuro-Imaging and Post-Traumatic Olfactory Impairment

    PubMed Central

    Roberts, Richard J.; Sheehan, William; Thurber, Steven; Roberts, Mary Ann

    2010-01-01

    Objective: To evaluate via a research literature survey the anterior neurological significance of decreased olfactory functioning following traumatic brain injuries. Materials and Methods: A computer literature review was performed to locate all functional neuro-imaging studies on patients with post-traumatic anosmia and other olfactory deficits. Results: A convergence of findings from nine functional neuro-imaging studies indicating evidence for reduced metabolic activity at rest or relative hypo-perfusion during olfactory activations. Hypo-activation of the prefrontal regions was apparent in all nine post-traumatic samples, with three samples yielding evidence of reduced activity in the temporal regions as well. Conclusions: The practical ramifications include the reasonable hypothesis that a total anosmic head trauma patient likely has frontal lobe involvement. PMID:21716782

  3. Voxel-Wise Functional Connectomics Using Arterial Spin Labeling Functional Magnetic Resonance Imaging: The Role of Denoising.

    PubMed

    Liang, Xiaoyun; Connelly, Alan; Calamante, Fernando

    2015-11-01

    The objective of this study was to investigate voxel-wise functional connectomics using arterial spin labeling (ASL) functional magnetic resonance imaging (fMRI). Since ASL signal has an intrinsically low signal-to-noise ratio (SNR), the role of denoising is evaluated; in particular, a novel denoising method, dual-tree complex wavelet transform (DT-CWT) combined with the nonlocal means (NLM) algorithm is implemented and evaluated. Simulations were conducted to evaluate the performance of the proposed method in denoising images and in detecting functional networks from noisy data (including the accuracy and sensitivity of detection). In addition, denoising was applied to in vivo ASL datasets, followed by network analysis using graph theoretical approaches. Efficiencies cost was used to evaluate the performance of denoising in detecting functional networks from in vivo ASL fMRI data. Simulations showed that denoising is effective in detecting voxel-wise functional networks from low SNR data and/or from data with small total number of time points. The capability of denoised voxel-wise functional connectivity analysis was also demonstrated with in vivo data. We concluded that denoising is important for voxel-wise functional connectivity using ASL fMRI and that the proposed DT-CWT-NLM method should be a useful ASL preprocessing step.

  4. Measurement and analysis of image sensors

    NASA Astrophysics Data System (ADS)

    Vitek, Stanislav

    2005-06-01

    For astronomical applications is necessary to have high precision in sensing and processing the image data. In this time are used the large CCD sensors from the various reasons. For the replacement of CCD sensors with CMOS sensing devices is important to know transfer characteristics of used CCD sensors. In the special applications like the robotic telescopes (fully automatic, without human interactions) seems to be good using of specially designed smart sensors, which have integrated more functions and have more features than CCDs.

  5. Morphological analysis of infrared images for waterjets

    NASA Astrophysics Data System (ADS)

    Gong, Yuxin; Long, Aifang

    2013-03-01

    High-speed waterjet has been widely used in industries and been investigated as a model of free shearing turbulence. This paper presents an investigation involving the flow visualization of high speed water jet, the noise reduction of the raw thermogram using a high-pass morphological filter ? and a median filter; the image enhancement using white top-hat filter; and the image segmentation using the multiple thresholding method. The image processing results by the designed morphological filters, ? - top-hat, were proved being ideal for further quantitative and in-depth analysis and can be used as a new morphological filter bank that may be of general implications for the analogous work

  6. Image sequence analysis workstation for multipoint motion analysis

    NASA Astrophysics Data System (ADS)

    Mostafavi, Hassan

    1990-08-01

    This paper describes an application-specific engineering workstation designed and developed to analyze motion of objects from video sequences. The system combines the software and hardware environment of a modem graphic-oriented workstation with the digital image acquisition, processing and display techniques. In addition to automation and Increase In throughput of data reduction tasks, the objective of the system Is to provide less invasive methods of measurement by offering the ability to track objects that are more complex than reflective markers. Grey level Image processing and spatial/temporal adaptation of the processing parameters is used for location and tracking of more complex features of objects under uncontrolled lighting and background conditions. The applications of such an automated and noninvasive measurement tool include analysis of the trajectory and attitude of rigid bodies such as human limbs, robots, aircraft in flight, etc. The system's key features are: 1) Acquisition and storage of Image sequences by digitizing and storing real-time video; 2) computer-controlled movie loop playback, freeze frame display, and digital Image enhancement; 3) multiple leading edge tracking in addition to object centroids at up to 60 fields per second from both live input video or a stored Image sequence; 4) model-based estimation and tracking of the six degrees of freedom of a rigid body: 5) field-of-view and spatial calibration: 6) Image sequence and measurement data base management; and 7) offline analysis software for trajectory plotting and statistical analysis.

  7. Operant-contingency-based preparation of children for functional magnetic resonance imaging.

    PubMed

    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.

  8. A method for functional magnetic resonance imaging of olfaction.

    PubMed

    Sobel, N; Prabhakaran, V; Desmond, J E; Glover, G H; Sullivan, E V; Gabrieli, J D

    1997-12-30

    A method for generating olfactory stimuli for humans within a functional magnetic resonance imaging (fMRI) experimental design is described. The system incorporates a nasal-mask in which the change from odorant to no-odorant conditions occurs in less than 500 ms and is not accompanied by visual, auditory, tactile, or thermal cues. The mask provides an ordorant-free environment following prolonged ordorant presence. Specific imaging parameters that are conducive to the study of the human olfactory system are described. In a pilot study performed using these methods, the specific patterns of activation observed converged with published experimental and clinical findings. PMID:9497007

  9. Vectorial point spread function and optical transfer function in oblique plane imaging.

    PubMed

    Kim, Jeongmin; Li, Tongcang; Wang, Yuan; Zhang, Xiang

    2014-05-01

    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.

  10. Atmospheric Imaging Assembly Multithermal Loop Analysis: First Results

    NASA Astrophysics Data System (ADS)

    Schmelz, J. T.; Kimble, J. A.; Jenkins, B. S.; Worley, B. T.; Anderson, D. J.; Pathak, S.; Saar, S. H.

    2010-12-01

    The Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory has state-of-the-art spatial resolution and shows the most detailed images of coronal loops ever observed. The series of coronal filters peak at different temperatures, which span the range of active regions. These features represent a significant improvement over earlier coronal imagers and make AIA ideal for multithermal analysis. Here, we targeted a 171 Å coronal loop in AR 11092 observed by AIA on 2010 August 3. Isothermal analysis using the 171-to-193 ratio gave a temperature of log T ≈ 6.1, similar to the results of Extreme ultraviolet Imaging Spectrograph (EIT) and TRACE. Differential emission measure analysis, however, showed that the plasma was multithermal, not isothermal, with the bulk of the emission measure at log T > 6.1. The result from the isothermal analysis, which is the average of the true plasma distribution weighted by the instrument response functions, appears to be deceptively low. These results have potentially serious implications: EIT and TRACE results, which use the same isothermal method, show substantially smaller temperature gradients than predicted by standard models for loops in hydrodynamic equilibrium and have been used as strong evidence in support of footpoint heating models. These implications may have to be re-examined in the wake of new results from AIA.

  11. 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)

  12. 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.

  13. 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.

  14. 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.

  15. Dopaminergic action beyond its effects on motor function: imaging studies.

    PubMed

    Brooks, David J

    2006-08-01

    Along with motor programming, it is now thought that tonic release of dopamine in the striatum acts to focus and filter non-motor activities such as working memory, implicit learning, decision making, and planning. Additionally, thresholds to painful stimuli may well be dopamine dependant. Phasic (burst) release of dopamine in the basal ganglia and frontal areas is thought to play a role in alerting organisms to novel and potentially rewarding stimuli and in mediating contextual learning. Dopamine release also drives a craving for stimuli and facilitates their enjoyment. Functional imaging can help elucidate the role of dopamine in mediating non-motor activities. The integrity of dopamine terminal function can be measured with PET and SPECT in vivo in health and Parkinson's disease (PD) and this can be correlated with performance of executive tasks. In addition, these imaging modalities allow dopamine release in response to stimuli (both rewarding and unrewarding) to be detected, as reflected by changes in D2 receptor availability to radioligands. Finally, the functional effects of dopamine deficiency and its replacement can be monitored by studying patterns of brain activation, as evidenced by regional blood flow changes. In this review, some of the insights that imaging has given us concerning the role of dopamine in non-motor functions is presented.

  16. Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration.

    PubMed

    de Bruin, P W; Kaptein, B L; Stoel, B C; Reiber, J H C; Rozing, P M; Valstar, E R

    2008-01-01

    Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: |mu |< 0.083 mm for translations and |mu| < 0.023 degrees for rotations. The precision sigma in x-, y-, and z-direction was 0.090, 0.077, and 0.220 mm for translations and 0.155 degrees , 0.243 degrees , and 0.074 degrees for rotations. Our results show that the accuracy and precision of in vitro IBRSA, performed under ideal laboratory conditions, are lower than in vitro standard RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications.

  17. Quantitative image analysis of celiac disease

    PubMed Central

    Ciaccio, Edward J; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

    2015-01-01

    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. PMID:25759524

  18. Quantitative image analysis of celiac disease.

    PubMed

    Ciaccio, Edward J; Bhagat, Govind; Lewis, Suzanne K; Green, Peter H

    2015-03-01

    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.

  19. Characterisation of mycelial morphology using image analysis.

    PubMed

    Paul, G C; Thomas, C R

    1998-01-01

    Image analysis is now well established in quantifying and characterising microorganisms from fermentation samples. In filamentous fermentations it has become an invaluable tool for characterising complex mycelial morphologies, although it is not yet used extensively in industry. Recent method developments include characterisation of spore germination from the inoculum stage and of the subsequent dispersed and pellet forms. Further methods include characterising vacuolation and simple structural differentiation of mycelia, also from submerged cultures. Image analysis can provide better understanding of the development of mycelial morphology, of the physiological states of the microorganisms in the fermenter, and of their interactions with the fermentation conditions. This understanding should lead to improved design and operation of mycelial fermentations. PMID:9468800

  20. 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

  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. Longitudinal, multimodal functional imaging of microvascular response to photothermal therapy

    PubMed Central

    Bui, Albert K.; Teves, Kathleen M.; Indrawan, Elmer; Jia, Wangcun; Choi, Bernard

    2012-01-01

    Although studies have shown that photothermal therapy can coagulate selectively abnormal vasculature, the ability of this method to achieve consistent, complete removal of the vasculature is questionable. We present the use of multimodal, wide-field functional imaging to study, in greater detail, the biological response to selective laser injury. Specifically, a single-platform instrument capable of coregistered fluorescence imaging and laser speckle imaging was utilized to monitor vascular endothelial growth factor gene expression and blood flow, respectively, in a transgenic rodent model. Collectively, the longitudinal, in vivo data collected with our instrument suggest that the biological response to selective laser injury involves early-stage redistribution of blood flow, followed by increased vascular endothelial growth factor promoter activity to stimulate pro-angiogenic events. PMID:20890338

  3. 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.

  4. ISLE (Image and Signal LISP Environment): A functional language interface for signal and image processing

    SciTech Connect

    Azevedo, S.G.; Fitch, J.P.

    1987-10-21

    Conventional software interfaces that use imperative computer commands or menu interactions are often restrictive environments when used for researching new algorithms or analyzing processed experimental data. We found this to be true with current signal-processing software (SIG). As an alternative, ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal LISP Environment (ISLE) is an example of an interpreted functional language interface based on common LISP. Advantages of ISLE include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligence (AI) software. 10 refs.

  5. ISLE (Image and Signal Lisp Environment): A functional language interface for signal and image processing

    SciTech Connect

    Azevedo, S.G.; Fitch, J.P.

    1987-05-01

    Conventional software interfaces which utilize imperative computer commands or menu interactions are often restrictive environments when used for researching new algorithms or analyzing processed experimental data. We found this to be true with current signal processing software (SIG). Existing ''functional language'' interfaces provide features such as command nesting for a more natural interaction with the data. The Image and Signal Lisp Environment (ISLE) will be discussed as an example of an interpreted functional language interface based on Common LISP. Additional benefits include multidimensional and multiple data-type independence through dispatching functions, dynamic loading of new functions, and connections to artificial intelligence software.

  6. Common tasks in microscopic and ultrastructural image analysis using ImageJ.

    PubMed

    Papadopulos, Francesca; Spinelli, Matthew; Valente, Sabrina; Foroni, Laura; Orrico, Catia; Alviano, Francesco; Pasquinelli, Gianandrea

    2007-01-01

    Cooperation between research communities and software-development teams has led to the creation of novel software. The purpose of this paper is to show an alternative work method based on the usage of ImageJ (http://rsb.info.nih.gov/ij/), which can be effectively employed in solving common microscopic and ultrastructural image analysis tasks. As an open-source software, ImageJ provides the possibility to work in a free-development/sharing world. Its very "friendly" graphical user interface helps users to manage and edit biomedical images. The on-line material such as handbooks, wikis, and plugins leads users through various functions, giving clues about potential new applications. ImageJ is not only a morphometric analysis software, it is sufficiently flexible to be adapted to the numerous requirements tasked in the laboratories as routine as well as research demands. Examples include area measurements on selectively stained tissue components, cell count and area measurements at single cell level, immunohistochemical antigen quantification, and immunoelectron microscopy gold particle count.

  7. Image analysis of blood platelets adhesion.

    PubMed

    Krízová, P; Rysavá, J; Vanícková, M; Cieslar, P; Dyr, J E

    2003-01-01

    Adhesion of blood platelets is one of the major events in haemostatic and thrombotic processes. We studied adhesion of blood platelets on fibrinogen and fibrin dimer sorbed on solid support material (glass, polystyrene). Adhesion was carried on under static and dynamic conditions and measured as percentage of the surface covered with platelets. Within a range of platelet counts in normal and in thrombocytopenic blood we observed a very significant decrease in platelet adhesion on fibrin dimer with bounded active thrombin with decreasing platelet count. Our results show the imperative use of platelet poor blood preparations as control samples in experiments with thrombocytopenic blood. Experiments carried on adhesive surfaces sorbed on polystyrene showed lower relative inaccuracy than on glass. Markedly different behaviour of platelets adhered on the same adhesive surface, which differed only in support material (glass or polystyrene) suggest that adhesion and mainly spreading of platelets depends on physical quality of the surface. While on polystyrene there were no significant differences between fibrin dimer and fibrinogen, adhesion measured on glass support material markedly differed between fibrin dimer and fibrinogen. We compared two methods of thresholding in image analysis of adhered platelets. Results obtained by image analysis of spreaded platelets showed higher relative inaccuracy than results obtained by image analysis of platelets centres and aggregates.

  8. Functional transcranial brain imaging by optical-resolution photoacoustic microscopy

    NASA Astrophysics Data System (ADS)

    Hu, Song; Maslov, Konstantin; Tsytsarev, Vassiliy; Wang, Lihong V.

    2009-07-01

    Optical-resolution photoacoustic microscopy (OR-PAM) is applied to functional brain imaging in living mice. A near-diffraction-limited bright-field optical illumination is employed to achieve micrometer lateral resolution, and a dual-wavelength measurement is utilized to extract the blood oxygenation information. The variation in hemoglobin oxygen saturation (sO2) along vascular branching has been imaged in a precapillary arteriolar tree and a postcapillary venular tree, respectively. To the best of our knowledge, this is the first report on in vivo volumetric imaging of brain microvascular morphology and oxygenation down to single capillaries through intact mouse skulls. It is anticipated that: (i) chronic imaging enabled by this minimally invasive procedure will advance the study of cortical plasticity and neurological diseases; (ii) revealing the neuroactivity-dependent changes in hemoglobin concentration and oxygenation will facilitate the understanding of neurovascular coupling at the capillary level; and (iii) combining functional OR-PAM and high-resolution blood flowmetry will have the potential to explore cellular pathways of brain energy metabolism.

  9. 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.

  10. Vestibular function and temporal bone imaging in DFNB1.

    PubMed

    Oonk, A M M; Beynon, A J; Peters, T A; Kunst, H P M; Admiraal, R J C; Kremer, H; Verbist, B; Pennings, R J E

    2015-09-01

    DFNB1 is the most prevalent type of hereditary hearing impairment known nowadays and the audiometric phenotype is very heterogeneous. There is, however, no consensus in literature on vestibular and imaging characteristics. Vestibular function and imaging results of 44 DFNB1 patients were evaluated in this retrospective study. All patients displayed a response during rotational velocity step testing. In 65% of the cases, the caloric results were within normal range bilaterally. The video head impulse test was normal in all patients. In 34.4% of the CT scans one or more temporal bone anomalies were found. The various anomalies found, were present in small numbers and none seemed convincingly linked to a specific DFNB1genotype. The group of DFNB1 patients presented here is the largest thus far evaluated for their vestibular function. From this study, it can be assumed that DFNB1 is not associated with vestibular dysfunction or specific temporal bone anomalies. PMID:26188104

  11. Widespread functional and molecular imaging in drug development.

    PubMed

    Ashton, Edward A

    2007-11-01

    The numbers of both large- and small-molecule drug candidates have increased substantially over the past decade, while overall and late-stage failure rates have hovered around 80 and 50% respectively. The corresponding rise in research and development expenditures relative to numbers of approved drugs has made it increasingly apparent that new methods are needed to assess potential efficacy in the earliest stages of drug development. It is generally not possible to power early-phase trials sufficiently to demonstrate efficacy using clinical end points. However, functional imaging techniques can often provide both the sensitivity to treatment effects and high reproducibility necessary to obtain statistically supportable evidence of treatment effect, even in relatively small Phase I trials. This article examines both the benefits and potential pitfalls associated with the inclusion of functional and molecular imaging in the drug development process.

  12. Pulmonary functional magnetic resonance imaging for paediatric lung disease.

    PubMed

    Kirby, Miranda; Coxson, Harvey O; Parraga, Grace

    2013-09-01

    A better understanding of the anatomic structure and physiological function of the lung is fundamental to understanding the pathogenesis of pulmonary disease and how to design and deliver better treatments and measure response to intervention. Magnetic resonance imaging (MRI) with the hyperpolarised noble gases helium-3 ((3)He) and xenon-129 ((129)Xe) provides both structural and functional pulmonary measurements, and because it does not require the use of x-rays or other ionising radiation, offers the potential for intensive serial and longitudinal studies in paediatric patients. These facts are particularly important in the evaluation of chronic lung diseases such as asthma and cystic fibrosis- both of which can be considered paediatric respiratory diseases with unmet therapy needs. This review discusses MRI-based imaging methods with a focus on hyperpolarised gas MRI. We also discuss the strengths and limitations as well as the future work required for clinical translation towards paediatric respiratory disease. PMID:23522599

  13. Functional Imaging in Diagnostic of Orthopedic Implant-Associated Infections

    PubMed Central

    Potapova, Inga

    2013-01-01

    Surgeries’ sterile conditions and perioperative antibiotic therapies decrease implant associated infections rates significantly. However, up to 10% of orthopedic devices still fail due to infections. An implant infection generates a high socio-economic burden. An early diagnosis of an infection would significantly improve patients’ outcomes. There are numerous clinical tests to diagnose infections. The “Gold Standard” is a microbiological culture, which requires an invasive sampling and lasts up to several weeks. None of the existing tests in clinics alone is sufficient for a conclusive diagnosis of an infection. Meanwhile, there are functional imaging modalities, which hold the promise of a non-invasive, quick, and specific infection diagnostic. This review focuses on orthopedic implant-associated infections, their pathogenicity, diagnosis and functional imaging. PMID:26824928

  14. EEG and functional ultrasound imaging in mobile rats

    PubMed Central

    Sieu, Lim-Anna; Bergel, Antoine; Tiran, Elodie; Deffieux, Thomas; Pernot, Mathieu; Gennisson, Jean-Luc; Tanter, Mickaël; Cohen, Ivan

    2015-01-01

    We developed an integrated experimental framework which extends the brain exploration capabilities of functional ultrasound imaging to awake/mobile animals. In addition to hemodynamic data, this method further allows parallel access to EEG recordings of neuronal activity. This approach is illustrated with two proofs of concept: first, a behavioral study, concerning theta rhythm activation in a maze running task and, second, a disease-related study concerning spontaneous epileptic seizures. PMID:26237228

  15. 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.

  16. Application Of Digital Image Processing To Acoustic Ambiguity Functions

    NASA Astrophysics Data System (ADS)

    Sharkey, J. Brian

    1983-03-01

    The passive acoustic ambiguity function is a measure of the cross-spectrum in a Doppler-shift and time-delay space that arises when two or more passive receivers are used to monitor a moving acoustic source. Detection of a signal source in the presence of noise has been treated in the past from a communications-theory point of view, with considerable effort devoted to establishing a threshold to which the maximum value of the function is compared. That approach disregards ambiguity function topography information which in practice is manually used to interpret source characteristics and source kinematics. Because of the two-dimensional representation of the ambiguity function, digital image processing techniques can be easily applied for the purposes of topography enhancement and characterization. This work presents an overview of techniques previously reported as well as more current research being conducted to improve detection performance and automate topography characterization.

  17. 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.

  18. 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…

  19. Reticle defect sizing of optical proximity correction defects using SEM imaging and image analysis techniques

    NASA Astrophysics Data System (ADS)

    Zurbrick, Larry S.; Wang, Lantian; Konicek, Paul; Laird, Ellen R.

    2000-07-01

    Sizing of programmed defects on optical proximity correction (OPC) feature sis addressed using high resolution scanning electron microscope (SEM) images and image analysis techniques. A comparison and analysis of different sizing methods is made. This paper addresses the issues of OPC defect definition and discusses the experimental measurement results obtained by SEM in combination with image analysis techniques.

  20. Multispectral laser imaging for advanced food analysis

    NASA Astrophysics Data System (ADS)

    Senni, L.; Burrascano, P.; Ricci, M.

    2016-07-01

    A hardware-software apparatus for food inspection capable of realizing multispectral NIR laser imaging at four different wavelengths is herein discussed. The system was designed to operate in a through-transmission configuration to detect the presence of unwanted foreign bodies inside samples, whether packed or unpacked. A modified Lock-In technique was employed to counterbalance the significant signal intensity attenuation due to transmission across the sample and to extract the multispectral information more efficiently. The NIR laser wavelengths used to acquire the multispectral images can be varied to deal with different materials and to focus on specific aspects. In the present work the wavelengths were selected after a preliminary analysis to enhance the image contrast between foreign bodies and food in the sample, thus identifying the location and nature of the defects. Experimental results obtained from several specimens, with and without packaging, are presented and the multispectral image processing as well as the achievable spatial resolution of the system are discussed.

  1. 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.

  2. 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. PMID:23343236

  3. Imaging Phenotype of Occupational Endotoxin-Related Lung Function Decline

    PubMed Central

    Lai, Peggy S.; Hang, Jing-qing; Zhang, Feng-ying; Sun, J.; Zheng, Bu-Yong; Su, Li; Washko, George R.; Christiani, David C.

    2016-01-01

    accelerated lung function decline. Citation: Lai PS, Hang J, Zhang F, Sun J, Zheng BY, Su L, Washko GR, Christiani DC. 2016. Imaging phenotype of occupational endotoxin-related lung function decline. Environ Health Perspect 124:1436–1442; http://dx.doi.org/10.1289/EHP195 PMID:27138294

  4. 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.

    2016-09-01

    The covariance of ground-based Lucky Images (COELI) is a robust and easy-to-use algorithm that allows us to detect faint companions surrounding a host star. In this paper we analyze 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.

  5. PAMS photo image retrieval prototype alternatives analysis

    SciTech Connect

    Conner, M.L.

    1996-04-30

    Photography and Audiovisual Services uses a system called the Photography and Audiovisual Management System (PAMS) to perform order entry and billing services. The PAMS system utilizes Revelation Technologies database management software, AREV. Work is currently in progress to link the PAMS AREV system to a Microsoft SQL Server database engine to provide photograph indexing and query capabilities. The link between AREV and SQLServer will use a technique called ``bonding.`` This photograph imaging subsystem will interface to the PAMS system and handle the image capture and retrieval portions of the project. The intent of this alternatives analysis is to examine the software and hardware alternatives available to meet the requirements for this project, and identify a cost-effective solution.

  6. [Imaging Mass Spectrometry in Histopathologic Analysis].

    PubMed

    Yamazaki, Fumiyoshi; Seto, Mitsutoshi

    2015-04-01

    Matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry (IMS) enables visualization of the distribution of a range of biomolecules by integrating biochemical information from mass spectrometry with positional information from microscopy. IMS identifies a target molecule. In addition, IMS enables global analysis of biomolecules containing unknown molecules by detecting the ratio of the molecular weight to electric charge without any target, which makes it possible to identify novel molecules. IMS generates data on the distribution of lipids and small molecules in tissues, which is difficult to visualize with either conventional counter-staining or immunohistochemistry. In this review, we firstly introduce the principle of imaging mass spectrometry and recent advances in the sample preparation method. Secondly, we present findings regarding biological samples, especially pathological ones. Finally, we discuss the limitations and problems of the IMS technique and clinical application, such as in drug development. PMID:26536781

  7. 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.

  8. Methodological challenges and solutions in auditory functional magnetic resonance imaging.

    PubMed

    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

  9. AFM imaging of functionalized double-walled carbon nanotubes.

    PubMed

    Lamprecht, C; Danzberger, J; Lukanov, P; Tîlmaciu, C-M; Galibert, A-M; Soula, B; Flahaut, E; Gruber, H J; Hinterdorfer, P; Ebner, A; Kienberger, F

    2009-07-01

    We present a comparative study of several non-covalent approaches to disperse, debundle and non-covalently functionalize double-walled carbon nanotubes (DWNTs). We investigated the ability of bovine serum albumin (BSA), phospholipids grafted onto amine-terminated polyethylene glycol (PL-PEG(2000)-NH(2)), as well as a combination thereof, to coat purified DWNTs. Topographical imaging with the atomic force microscope (AFM) was used to assess the coating of individual DWNTs and the degree of debundling and dispersion. Topographical images showed that functionalized DWNTs are better separated and less aggregated than pristine DWNTs and that the different coating methods differ in their abilities to successfully debundle and disperse DWNTs. Height profiles indicated an increase in the diameter of DWNTs depending on the functionalization method and revealed adsorption of single molecules onto the nanotubes. Biofunctionalization of the DWNT surface was achieved by coating DWNTs with biotinylated BSA, providing for biospecific binding of streptavidin in a simple incubation step. Finally, biotin-BSA-functionalized DWNTs were immobilized on an avidin layer via the specific avidin-biotin interaction. PMID:19375857

  10. Multivariate Analysis of Functional Metagenomes

    PubMed Central

    Dinsdale, Elizabeth A.; Edwards, Robert A.; Bailey, Barbara A.; Tuba, Imre; Akhter, Sajia; McNair, Katelyn; Schmieder, Robert; Apkarian, Naneh; Creek, Michelle; Guan, Eric; Hernandez, Mayra; Isaacs, Katherine; Peterson, Chris; Regh, Todd; Ponomarenko, Vadim

    2013-01-01

    Metagenomics is a primary tool for the description of microbial and viral communities. The sheer magnitude of the data generated in each metagenome makes identifying key differences in the function and taxonomy between communities difficult to elucidate. Here we discuss the application of seven different data mining and statistical analyses by comparing and contrasting the metabolic functions of 212 microbial metagenomes within and between 10 environments. Not all approaches are appropriate for all questions, and researchers should decide which approach addresses their questions. This work demonstrated the use of each approach: for example, random forests provided a robust and enlightening description of both the clustering of metagenomes and the metabolic processes that were important in separating microbial communities from different environments. All analyses identified that the presence of phage genes within the microbial community was a predictor of whether the microbial community was host-associated or free-living. Several analyses identified the subtle differences that occur with environments, such as those seen in different regions of the marine environment. PMID:23579547

  11. 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

  12. 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.

  13. 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.

  14. Can selective arterial clamping with fluorescence imaging preserve kidney function during robotic partial nephrectomy?

    PubMed Central

    McClintock, Tyler R.; Bjurlin, Marc A.; Wysock, James S.; Borofsky, Michael S.; Marien, Tracy P.; Okoro, Chinonyerem; Stifelman, Michael D.

    2015-01-01

    Objectives To compare renal functional outcomes in robotic partial nephrectomy (RPN) with selective arterial clamping guided by near infrared fluorescence (NIRF) imaging to a matched cohort of patients who underwent RPN without selective arterial clamping and NIRF imaging. Methods From April 2011 to December 2012, NIRF imaging-enhanced RPN with selective clamping was utilized in 42 cases. Functional outcomes of successful cases were compared with a cohort of patients, matched by tumor size, preoperative eGFR, functional kidney status, age, sex, body mass index, and American Society of Anesthesiologists score, who underwent RPN without selective clamping and NIRF imaging. Results In matched-pair analysis, selective clamping with NIRF was associated with superior kidney function at discharge, as demonstrated by postoperative eGFR (78.2 vs 68.5 ml/min per 1.73m2; P=0.04), absolute reduction of eGFR (−2.5 vs −14.0 ml/min per 1.73m2; P<0.01) and percent change in eGFR (−1.9% vs −16.8%, P<0.01). Similar trends were noted at three month follow up but these differences became non-significant (P[eGFR]=0.07], P[absolute reduction of eGFR]=0.10, and P[percent change in eGFR]=0.07). In the selective clamping group, a total of four perioperative complications occurred in three patients, all of which were Clavien I-III. Conclusion Utilization of NIRF imaging was associated with improved short-term renal functional outcomes when compared to RPN without selective arterial clamping and NIRF imaging. With this effect attenuated at later follow-up, randomized prospective studies and long-term assessment of kidney-specific functional outcomes are needed to further assess the benefits of this technology. PMID:24909960

  15. Imaging of the Functional and Dysfunctional Visual System

    PubMed Central

    DeYoe, Edgar A.; Ulmer, John L.; Mueller, Wade M.; Sabsevitz, David S.; Reitsma, Danielle C.; Pillai, Jay J.

    2015-01-01

    Functional magnetic resonance imaging (fMRI) is used clinically to map the visual cortex before brain surgery or other invasive treatments to achieve an optimal balance between therapeutic effect and the avoidance of postoperative vision deficits. Clinically optimized stimuli, analyses, and displays permit identification of cortical subregions supporting high-acuity central vision that are critical for reading and other essential visual functions. A novel data display permits instant appreciation of the functional relationship between the pattern of fMRI brain activation and the pattern of vision loss and preservation within the patient's field of view. Neurovascular uncoupling and its detection in the visual cortex are key issues for the interpretation of fMRI results in patients with existing brain pathology. PMID:26233858

  16. 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.

  17. Quantitative imaging of lymphatic function with liposomal indocyanine green.

    PubMed

    Proulx, Steven T; Luciani, Paola; Derzsi, Stefanie; Rinderknecht, Matthias; Mumprecht, Viviane; Leroux, Jean-Christophe; Detmar, Michael

    2010-09-15

    Lymphatic vessels play a major role in cancer progression and in postsurgical lymphedema, and several new therapeutic approaches targeting lymphatics are currently being developed. Thus, there is a critical need for quantitative imaging methods to measure lymphatic flow. Indocyanine green (ICG) has been used for optical imaging of the lymphatic system, but it is unstable in solution and may rapidly enter venous capillaries after local injection. We developed a novel liposomal formulation of ICG (LP-ICG), resulting in vastly improved stability in solution and an increased fluorescence signal with a shift toward longer wavelength absorption and emission. When injected intradermally to mice, LP-ICG was specifically taken up by lymphatic vessels and allowed improved visualization of deep lymph nodes. In a genetic mouse model of lymphatic dysfunction, injection of LP-ICG showed no enhancement of draining lymph nodes and slower clearance from the injection site. In mice bearing B16 luciferase-expressing melanomas expressing vascular endothelial growth factor-C (VEGF-C), sequential near-IR imaging of intradermally injected LP-ICG enabled quantification of lymphatic flow. Increased flow through draining lymph nodes was observed in mice bearing VEGF-C-expressing tumors without metastases, whereas a decreased flow pattern was seen in mice with a higher lymph node tumor burden. This new method will likely facilitate quantitative studies of lymphatic function in preclinical investigations and may also have potential for imaging of lymphedema or improved sentinel lymph detection in cancer. PMID:20823159

  18. 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

  19. Functional magnetic resonance imaging at 0.2 Tesla.

    PubMed

    Stroman, P W; Malisza, K L; Onu, M

    2003-10-01

    Functional magnetic resonance imaging of healthy human volunteers was carried out at 0.2 T, using proton-density weighted (TE = 24 ms) spin-echo imaging, in order to eliminate any contribution from the blood oxygenation-level dependent (BOLD) effect. The purpose of the study was to verify the existence of a proton-density change contribution to spin-echo functional magnetic resonance imaging (fMRI) data. Results demonstrated signal intensity changes in motor and sensory areas of the brain during performance of a motor task and cold sensory stimulation of the hand, with signal changes ranging from 1.7 to 2.3%. These values are consistent with 1.9% signal changes observed previously under similar conditions at 3 T. These findings confirm the proton-density change contribution to spin-echo fMRI data and support the theory of signal enhancement by extravascular water protons (SEEP) as a non-BOLD fMRI contrast mechanism. This study also demonstrates that fMRI based on the SEEP contrast mechanism can be carried out at low fields where the BOLD effect is expected to be negligible.

  20. 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 with cirrhosis, and one patient with acute fulminant non-A, non-B hepatitis. Technetium-99m NGA liver imaging provided anatomic information of diagnostic quality comparable to that obtained with other routine imaging modalities, including computed tomography, angiography, ultrasound, and (Tc)sulfur colloid scintigraphy. Kinetic modeling of dynamic (Tc)NGA data produced estimates of standardized hepatic blood flow, Q (hepatic blood flow divided by total blood volume), and hepatic binding protein concentration, (HBP). Significant rank correlation was obtained between (HBP) estimates and CTC scores. This correlation supports the hypothesis that (HBP) is a measure of functional hepatocyte mass. The combination of decreased Q and markedly reduced (HBP) may have prognostic significance; all three patients with this combination died of hepatic failure within 6 wk of imaging.

  1. 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.

  2. Bone feature analysis using image processing techniques.

    PubMed

    Liu, Z Q; Austin, T; Thomas, C D; Clement, J G

    1996-01-01

    In order to establish the correlation between bone structure and age, and information about age-related bone changes, it is necessary to study microstructural features of human bone. Traditionally, in bone biology and forensic science, the analysis if bone cross-sections has been carried out manually. Such a process is known to be slow, inefficient and prone to human error. Consequently, the results obtained so far have been unreliable. In this paper we present a new approach to quantitative analysis of cross-sections of human bones using digital image processing techniques. We demonstrate that such a system is able to extract various bone features consistently and is capable of providing more reliable data and statistics for bones. Consequently, we will be able to correlate features of bone microstructure with age and possibly also with age related bone diseases such as osteoporosis. The development of knowledge-based computer vision-systems for automated bone image analysis can now be considered feasible.

  3. A textural approach based on Gabor functions for texture edge detection in ultrasound images.

    PubMed

    Chen, C M; Lu, H H; Han, K C

    2001-04-01

    Edge detection is an important, but difficult, step in quantitative ultrasound (US) image analysis. In this paper, we present a new textural approach for detecting a class of edges in US images; namely, the texture edges with a weak regional mean gray-level difference (RMGD) between adjacent regions. The proposed approach comprises a vision model-based texture edge detector using Gabor functions and a new texture-enhancement scheme. The experimental results on the synthetic edge images have shown that the performances of the four tested textural and nontextural edge detectors are about 20%-95% worse than that of the proposed approach. Moreover, the texture enhancement may improve the performance of the proposed texture edge detector by as much as 40%. The experiments on 20 clinical US images have shown that the proposed approach can find reasonable edges for real objects of interest with the performance of 0.4 +/- 0.08 in terms of the Pratt's figure.

  4. Imaging Approaches in Functional Assessment of Implantable Myogenic Biomaterials and Engineered Muscle Tissue

    PubMed Central

    Gargiulo, Paolo

    2015-01-01

    The fields of tissue engineering and regenerative medicine utilize implantable biomaterials and engineered tissues to regenerate damaged cells or replace lost tissues. There are distinct challenges in all facets of this research, but functional assessments and monitoring of such complex environments as muscle tissues present the current strategic priority. Many extant methods for addressing these questions result in the destruction or alteration of tissues or cell populations under investigation. Modern advances in non-invasive imaging modalities present opportunities to rethink some of the anachronistic methods, however, their standard employment may not be optimal when considering advancements in myology. New image analysis protocols and/or combinations of established modalities need to be addressed. This review focuses on efficacies and limitations of available imaging modalities to the functional assessment of implantable myogenic biomaterials and engineered muscle tissues. PMID:26913149

  5. In-vivo imaging of the photoreceptor mosaic in retinal dystrophies and correlations with visual function

    SciTech Connect

    Choi, S; Doble, N; Hardy, J; Jones, S; Keltner, J; Olivier, S; Werner, J S

    2005-10-26

    To relate in-vivo microscopic retinal changes to visual function assessed with clinical tests in patients with various forms of retinal dystrophies. The UC Davis Adaptive Optics (AO) Fundus Camera was used to acquire in-vivo retinal images at the cellular level. Visual function tests, consisting of visual field analysis, multifocal electroretinography (mfERG), contrast sensitivity and color vision measures, were performed on all subjects. Five patients with different forms of retinal dystrophies and three control subjects were recruited. Cone densities were quantified for all retinal images. In all images of diseased retinas, there were extensive areas of dark space between groups of photoreceptors, where no cone photoreceptors were evident. These irregular features were not seen in healthy retinas, but were characteristic features in fundi with retinal dystrophies. There was a correlation between functional vision loss and the extent to which the irregularities occurred in retinal images. Cone densities were found to decrease with an associated decrease in retinal function. AO fundus photography is a reliable technique for assessing and quantifying the changes in the photoreceptor layer as disease progresses. Furthermore, this technique can be useful in cases where visual function tests give borderline or ambiguous results, as it allows visualization of individual photoreceptors.

  6. Functional Imaging of Working Memory and Peripheral Endothelial Function in Middle-Aged Adults

    ERIC Educational Resources Information Center

    Gonzales, Mitzi M.; Tarumi, Takashi; Tanaka, Hirofumi; Sugawara, Jun; Swann-Sternberg, Tali; Goudarzi, Katayoon; Haley, Andreana P.

    2010-01-01

    The current study examined the relationship between a prognostic indicator of vascular health, flow-mediated dilation (FMD), and working memory-related brain activation in healthy middle-aged adults. Forty-two participants underwent functional magnetic resonance imaging while completing a 2-Back working memory task. Brachial artery…

  7. Semi-automated porosity identification from thin section images using image analysis and intelligent discriminant classifiers

    NASA Astrophysics Data System (ADS)

    Ghiasi-Freez, Javad; Soleimanpour, Iman; Kadkhodaie-Ilkhchi, Ali; Ziaii, Mansur; Sedighi, Mahdi; Hatampour, Amir

    2012-08-01

    Identification of different types of porosity within a reservoir rock is a functional parameter for reservoir characterization since various pore types play different roles in fluid transport and also, the pore spaces determine the fluid storage capacity of the reservoir. The present paper introduces a model for semi-automatic identification of porosity types within thin section images. To get this goal, a pattern recognition algorithm is followed. Firstly, six geometrical shape parameters of sixteen largest pores of each image are extracted using image analysis techniques. The extracted parameters and their corresponding pore types of 294 pores are used for training two intelligent discriminant classifiers, namely linear and quadratic discriminant analysis. The trained classifiers take the geometrical features of the pores to identify the type and percentage of five types of porosity, including interparticle, intraparticle, oomoldic, biomoldic, and vuggy in each image. The accuracy of classifiers is determined from two standpoints. Firstly, the predicted and measured percentages of each type of porosity are compared with each other. The results indicate reliable performance for predicting percentage of each type of porosity. In the second step, the precisions of classifiers for categorizing the pore spaces are analyzed. The classifiers also took a high acceptance score when used for individual recognition of pore spaces. The proposed methodology is a further promising application for petroleum geologists allowing statistical study of pore types in a rapid and accurate way.

  8. 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.

  9. 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

  10. 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

  11. AUTO: A computer program for the determination of the two-dimensional autocorrelation function of digital images

    NASA Astrophysics Data System (ADS)

    Pfleiderer, S.; Ball, D. G. A.; Bailey, R. C.

    1993-07-01

    The two-dimensional (2-D) autocorrelation function (ACF) of an image statistically characterizes the spatial pattern within that image and presents a powerful tool for fabric analysis. It determines shape preferred orientation, degree of alignment, and distribution anisotropy of image objects. We present here a fast, user-friendly, MS-DOS based computer program, AUTO, to calculate the 2-D ACF of a digital monochrome image. AUTO displays an image on the screen and allows selection of a portion of the image for autocorrelation. Rapid calculation of ACF values is achieved by using a fast Fourier transform (FFT) routine according to the convolution theorem. The spatial distribution of ACF values is contoured for quantitative analysis of fabric anisotropy. Applications of this technique include the determination of grain or pore fabric of geological specimens, strain analysis, and the interpretation of petrophysical properties.

  12. Soil Surface Roughness through Image Analysis

    NASA Astrophysics Data System (ADS)

    Tarquis, A. M.; Saa-Requejo, A.; Valencia, J. L.; Moratiel, R.; Paz-Gonzalez, A.; Agro-Environmental Modeling

    2011-12-01

    Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on several factors being one of them surface micro-topography, usually quantified trough soil surface roughness (SSR). SSR greatly affects surface sealing and runoff generation, yet little information is available about the effect of roughness on the spatial distribution of runoff and on flow concentration. The methods commonly used to measure SSR involve measuring point elevation using a pin roughness meter or laser, both of which are labor intensive and expensive. Lately a simple and inexpensive technique based on percentage of shadow in soil surface image has been developed to determine SSR in the field in order to obtain measurement for wide spread application. One of the first steps in this technique is image de-noising and thresholding to estimate the percentage of black pixels in the studied area. In this work, a series of soil surface images have been analyzed applying several de-noising wavelet analysis and thresholding algorithms to study the variation in percentage of shadows and the shadows size distribution. Funding provided by Spanish Ministerio de Ciencia e Innovación (MICINN) through project no. AGL2010- 21501/AGR and by Xunta de Galicia through project no INCITE08PXIB1621 are greatly appreciated.

  13. Monotonic correlation analysis of image quality measures for image fusion

    NASA Astrophysics Data System (ADS)

    Kaplan, Lance M.; Burks, Stephen D.; Moore, Richard K.; Nguyen, Quang

    2008-04-01

    The next generation of night vision goggles will fuse image intensified and long wave infra-red to create a hybrid image that will enable soldiers to better interpret their surroundings during nighttime missions. Paramount to the development of such goggles is the exploitation of image quality (IQ) measures to automatically determine the best image fusion algorithm for a particular task. This work introduces a novel monotonic correlation coefficient to investigate how well possible IQ features correlate to actual human performance, which is measured by a perception study. The paper will demonstrate how monotonic correlation can identify worthy features that could be overlooked by traditional correlation values.

  14. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.

    PubMed

    Yan, Chao-Gan; Wang, Xin-Di; Zuo, Xi-Nian; Zang, Yu-Feng

    2016-07-01

    Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies. PMID:27075850

  15. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging.

    PubMed

    Yan, Chao-Gan; Wang, Xin-Di; Zuo, Xi-Nian; Zang, Yu-Feng

    2016-07-01

    Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.

  16. In-orbit commissioning of SPOT5 image compression function

    NASA Astrophysics Data System (ADS)

    Moury, Gilles A.; Latry, Christophe

    2003-11-01

    CNES has launched in May 2002 a new high resolution (2.5m) and large swath (2 x 60km) optical remote sensing satellite: SPOT5. To achieve a high image acquisition capacity with this system, a large on-board mass memory (100 Gbits) together with a 3:1 real-time compression are being used. The quasi-lossless and fixed output rate requirements put on the on-board image compression resulted in the development of a custom algorithm. This algorithm is based on: a DCT decorrelator, a scalar quantizer, an entropy coder and a rate regulator. It has been extensively tested before launch both in terms of quantitative performances and in terms of visual performances. The objectives of the on-orbit validation of the SPOT5 image compression function were the following: (1) Perform an image quality assessment in worst case conditions for the compression. In particular, the THR mode (2.5 m resolution) is potentially sensitive to compression noise and was therefore thoroughly checked for any compression artefacts. Compression noise characteristics were taken into account in the denoising stage of the ground processing for improved performances; (2) Verify the adequacy of the compression parameters with regard to the in-flight characteristics of the instruments (MTF, radiometric spreading, ...); (3) Technological checkout of the compression unit on board the satellite. This paper will present an overview of SPOT5 mission, the methods used for on-orbit validation of the compression and, finally, all the validation results together with the lessons learned throughout this development. On-board image compression for future CNES remote sensing missions will be addressed as a conclusion.

  17. Functional recognition imaging using artificial neural networks: applications to rapid cellular identification via broadband electromechanical response.

    PubMed

    Nikiforov, M P; Reukov, V V; Thompson, G L; Vertegel, A A; Guo, S; Kalinin, S V; Jesse, S

    2009-10-01

    Functional recognition imaging in scanning probe microscopy (SPM) using artificial neural network identification is demonstrated. This approach utilizes statistical analysis of complex SPM responses at a single spatial location to identify the target behavior, which is reminiscent of associative thinking in the human brain, obviating the need for analytical models. We demonstrate, as an example of recognition imaging, rapid identification of cellular organisms using the difference in electromechanical activity over a broad frequency range. Single-pixel identification of model Micrococcus lysodeikticus and Pseudomonas fluorescens bacteria is achieved, demonstrating the viability of the method.

  18. Functional Recognition Imaging Using Artificial Neural Networks: Applications to Rapid Cellular Identification by Broadband Electromechanical Response

    PubMed Central

    Nikiforov, M.P.; Reukov, V.V.; Thompson, G.L.; Vertegel, A.A.; Guo, S.; Jesse, S.; Kalinin, S.V.

    2010-01-01

    Functional recognition imaging in Scanning Probe Microscopy (SPM) using artificial neural network identification is demonstrated. This approach utilizes statistical analysis of complex SPM responses to identify the target behavior, reminiscent of associative thinking in the human brain and obviating the need for analytical models. As an example of recognition imaging, we demonstrate rapid identification of cellular organisms using difference in electromechanical activity in a broad frequency range. Single-pixel identification of model Micrococcus lysodeikticus and Pseudomonas fluorescens bacteria is achieved, demonstrating the viability of the method. PMID:19752493

  19. Implantable imaging device for brain functional imaging system using flavoprotein fluorescence

    NASA Astrophysics Data System (ADS)

    Sunaga, Yoshinori; Yamaura, Hiroshi; Haruta, Makito; Yamaguchi, Takahiro; Motoyama, Mayumi; Ohta, Yasumi; Takehara, Hiroaki; Noda, Toshihiko; Sasagawa, Kiyotaka; Tokuda, Takashi; Yoshimura, Yumiko; Ohta, Jun

    2016-03-01

    The autofluorescence of mitochondrial flavoprotein is very useful for functional brain imaging because the fluorescence intensity of flavoprotein changes as per neural activities. In this study, we developed an implantable imaging device for green fluorescence imaging and detected fluorescence changes of flavoprotein associated with visual stimulation using the device. We examined the device performance using anesthetized mice. We set the device on the visual cortex and measured fluorescence changes of flavoprotein in response to visual stimulation. A full-field sinusoidal grating with a vertical orientation was used for applying to activate the visual cortex. We successfully observed visually evoked fluorescence changes in the mouse visual cortex using our implantable device. This result suggests that we can observe the fluorescence changes of flavoprotein associated with visual stimulation in a freely moving mouse by using this technology.

  20. FUNCTIONAL ANALYSIS AND TREATMENT OF COPROPHAGIA

    PubMed Central

    Ing, Anna D; Roane, Henry S; Veenstra, Rebecca A

    2011-01-01

    In the current investigation, functional analysis results suggested that coprophagia, the ingestion of fecal matter, was maintained by automatic reinforcement. Providing noncontingent access to alternative stimuli decreased coprophagia, and the intervention was generalized to two settings. PMID:21541128

  1. Pathway-Based Functional Analysis of Metagenomes

    NASA Astrophysics Data System (ADS)

    Bercovici, Sivan; Sharon, Itai; Pinter, Ron Y.; Shlomi, Tomer

    Metagenomic data enables the study of microbes and viruses through their DNA as retrieved directly from the environment in which they live. Functional analysis of metagenomes explores the abundance of gene families, pathways, and systems, rather than their taxonomy. Through such analysis researchers are able to identify those functional capabilities most important to organisms in the examined environment. Recently, a statistical framework for the functional analysis of metagenomes was described that focuses on gene families. Here we describe two pathway level computational models for functional analysis that take into account important, yet unaddressed issues such as pathway size, gene length and overlap in gene content among pathways. We test our models over carefully designed simulated data and propose novel approaches for performance evaluation. Our models significantly improve over current approach with respect to pathway ranking and the computations of relative abundance of pathways in environments.

  2. Wavelet Analysis of Space Solar Telescope Images

    NASA Astrophysics Data System (ADS)

    Zhu, Xi-An; Jin, Sheng-Zhen; Wang, Jing-Yu; Ning, Shu-Nian

    2003-12-01

    The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.

  3. Difference Image Analysis of Galactic Microlensing. I. Data Analysis

    SciTech Connect

    Alcock, C.; Allsman, R. A.; Alves, D.; Axelrod, T. S.; Becker, A. C.; Bennett, D. P.; Cook, K. H.; Drake, A. J.; Freeman, K. C.; Griest, K.

    1999-08-20

    This is a preliminary report on the application of Difference Image Analysis (DIA) to Galactic bulge images. The aim of this analysis is to increase the sensitivity to the detection of gravitational microlensing. We discuss how the DIA technique simplifies the process of discovering microlensing events by detecting only objects that have variable flux. We illustrate how the DIA technique is not limited to detection of so-called ''pixel lensing'' events but can also be used to improve photometry for classical microlensing events by removing the effects of blending. We will present a method whereby DIA can be used to reveal the true unblended colors, positions, and light curves of microlensing events. We discuss the need for a technique to obtain the accurate microlensing timescales from blended sources and present a possible solution to this problem using the existing Hubble Space Telescope color-magnitude diagrams of the Galactic bulge and LMC. The use of such a solution with both classical and pixel microlensing searches is discussed. We show that one of the major causes of systematic noise in DIA is differential refraction. A technique for removing this systematic by effectively registering images to a common air mass is presented. Improvements to commonly used image differencing techniques are discussed. (c) 1999 The American Astronomical Society.

  4. Patient-adaptive lesion metabolism analysis by dynamic PET images.

    PubMed

    Gao, Fei; Liu, Huafeng; Shi, Pengcheng

    2012-01-01

    Dynamic PET imaging provides important spatial-temporal information for metabolism analysis of organs and tissues, and generates a great reference for clinical diagnosis and pharmacokinetic analysis. Due to poor statistical properties of the measurement data in low count dynamic PET acquisition and disturbances from surrounding tissues, identifying small lesions inside the human body is still a challenging issue. The uncertainties in estimating the arterial input function will also limit the accuracy and reliability of the metabolism analysis of lesions. Furthermore, the sizes of the patients and the motions during PET acquisition will yield mismatch against general purpose reconstruction system matrix, this will also affect the quantitative accuracy of metabolism analyses of lesions. In this paper, we present a dynamic PET metabolism analysis framework by defining a patient adaptive system matrix to improve the lesion metabolism analysis. Both patient size information and potential small lesions are incorporated by simulations of phantoms of different sizes and individual point source responses. The new framework improves the quantitative accuracy of lesion metabolism analysis, and makes the lesion identification more precisely. The requirement of accurate input functions is also reduced. Experiments are conducted on Monte Carlo simulated data set for quantitative analysis and validation, and on real patient scans for assessment of clinical potential. PMID:23286175

  5. Functional magnetic resonance imaging in medicine and physiology

    SciTech Connect

    Moonen, C.T.W.; van Zijl, P.C.M.; Frank, J.A.; Bihan, D.L.; Becker, E.D. )

    1990-10-05

    Magnetic resonance imaging (MRI) is a well-established diagnostic tool that provides detailed information about macroscopic structure and anatomy. Recent advances in MRI allow the noninvasive spatial evaluation of various biophysical and biochemical processes in living systems. Specifically, the motion of water can be measured in processes such as vascular flow, capillary flow, diffusion, and exchange. In addition, the concentrations of various metabolites can be determined for the assessment of regional regulation of metabolism. Examples are given that demonstrate the use of functional MRI for clinical and research purposes. This development adds a new dimension to the application of magnetic resonance to medicine and physiology.

  6. PEG functionalized luminescent lipid particles for cellular imaging

    NASA Astrophysics Data System (ADS)

    Rana, Suman; Barick, K. C.; Shetake, Neena G.; Verma, Gunjan; Aswal, V. K.; Panicker, Lata; Pandey, B. N.; Hassan, P. A.

    2016-08-01

    We report here the synthesis, characterization and cellular uptake of luminescent micelle-like particles with phospholipid core and non-ionic PEG based surfactant polysorbate 80 shell. The adsorption of polysorbate 80 at the interface of lipid containing microemulsion droplets and its solidification upon removal of solvent leads to anchoring of PEG chain to the lipid particles. Hydrophobic partitioning of luminescent molecules, sodium 3-hydroxynaphthalene-2-carboxylic acid to the phospholipid core offers additional functionality to these particles. Thus, the cooperative assembly of lipid, non-ionic amphiphile and organic luminescent probe leads to the formation of multifunctional biocompatible particles which are useful for simultaneous imaging and therapy.

  7. The economics of functional magnetic resonance imaging: clinical and research.

    PubMed

    Yousem, David M

    2014-11-01

    It is difficult to justify maintaining a clinical functional magnetic resonance imaging (fMRI) program based solely on revenue generation. The use of fMRI is, therefore, based mostly in patient care considerations, leading to better outcomes. The high costs of the top-of-the-line equipment, hardware, and software needed for state-of-the-art fMRI and the time commitment by multiple professionals are not adequately reimbursed at a representative rate by current payor schemes for the Current Procedure Terminology codes assigned.

  8. Controlled therapy by imaging of functional structures of intact liver

    NASA Astrophysics Data System (ADS)

    Wang, W.; Zhuang, Feng Y.; Ruan, G.; Kakihana, Yasuyuki; Krug, A.; Kessler, Manfred D.

    2000-04-01

    Ligustrazine, a Chinese herb medicine has been used to treat the diseases of cardiovascular and cerebral vascular diseases in China by Chinese traditional physicians or many years. Recently, results showed that ligustrazine is a powerful hepatic vasodilator. It can greatly change the blood supply of the tissues. Due to micro-optical tissue sensor developed recently it became possible to image functional structures of tissue on the level of intact blood capillaries. In our experiment we used the Oxyscan in order to study the effect of Ligustrazine on the oxygen supply of rat liver.

  9. Radar image sequence analysis of inhomogeneous water surfaces

    NASA Astrophysics Data System (ADS)

    Seemann, Joerg; Senet, Christian M.; Dankert, Heiko; Hatten, Helge; Ziemer, Friedwart

    1999-10-01

    The radar backscatter from the ocean surface, called sea clutter, is modulated by the surface wave field. A method was developed to estimate the near-surface current, the water depth and calibrated surface wave spectra from nautical radar image sequences. The algorithm is based on the three- dimensional Fast Fourier Transformation (FFT) of the spatio- temporal sea clutter pattern in the wavenumber-frequency domain. The dispersion relation is used to define a filter to separate the spectral signal of the imaged waves from the background noise component caused by speckle noise. The signal-to-noise ratio (SNR) contains information about the significant wave height. The method has been proved to be reliable for the analysis of homogeneous water surfaces in offshore installations. Radar images are inhomogeneous because of the dependency of the image transfer function (ITF) on the azimuth angle between the wave propagation and the antenna viewing direction. The inhomogeneity of radar imaging is analyzed using image sequences of a homogeneous deep-water surface sampled by a ship-borne radar. Changing water depths in shallow-water regions induce horizontal gradients of the tidal current. Wave refraction occurs due to the spatial variability of the current and water depth. These areas cannot be investigated with the standard method. A new method, based on local wavenumber estimation with the multiple-signal classification (MUSIC) algorithm, is outlined. The MUSIC algorithm provides superior wavenumber resolution on local spatial scales. First results, retrieved from a radar image sequence taken from an installation at a coastal site, are presented.

  10. Functional imaging of single synapses in brain slices.

    PubMed

    Oertner, Thomas G

    2002-11-01

    The strength of synaptic connections in the brain is not fixed, but can be modulated by numerous mechanisms. Traditionally, electrophysiology has been used to characterize connections between neurons. Electrophysiology typically reports the activity of populations of synapses, while most mechanisms of plasticity are thought to operate at the level of single synapses. Recently, two-photon laser scanning microscopy has enabled us to perform optical quantal analysis of individual synapses in intact brain tissue. Here we introduce the basic principle of the two-photon microscope and discuss its main differences compared to the confocal microscope. Using calcium imaging in dendritic spines as an example, we explain the advantages of simultaneous dual-dye imaging for quantitative calcium measurements and address two common problems, dye saturation and background fluorescence subtraction.

  11. Advances in functional magnetic resonance imaging: technology and clinical applications.

    PubMed

    Dickerson, Bradford C

    2007-07-01

    Functional MRI (fMRI) is a valuable method for use by clinical investigators to study task-related brain activation in patients with neurological or neuropsychiatric illness. Despite the relative infancy of the field, the rapid adoption of this functional neuroimaging technology has resulted from, among other factors, its ready availability, its relatively high spatial and temporal resolution, and its safety as a noninvasive imaging tool that enables multiple repeated scans over the course of a longitudinal study, and thus may lend itself well as a measure in clinical drug trials. Investigators have used fMRI to identify abnormal functional brain activity during task performance in a variety of patient populations, including those with neurodegenerative, demyelinating, cerebrovascular, and other neurological disorders that highlight the potential utility of fMRI in both basic and clinical spheres of research. In addition, fMRI studies reveal processes related to neuroplasticity, including compensatory hyperactivation, which may be a universally-occurring, adaptive neural response to insult. Functional MRI is being used to study the modulatory effects of genetic risk factors for neurological disease on brain activation; it is being applied to differential diagnosis, as a predictive biomarker of disease course, and as a means to identify neural correlates of neurotherapeutic interventions. Technological advances are rapidly occurring that should provide new applications for fMRI, including improved spatial resolution, which promises to reveal novel insights into the function of fine-scale neural circuitry of the human brain in health and disease.

  12. Functional principal components analysis of workload capacity functions

    PubMed Central

    Burns, Devin M.; Houpt, Joseph W.; Townsend, James T.; Endres, Michael J.

    2013-01-01

    Workload capacity, an important concept in many areas of psychology, describes processing efficiency across changes in workload. The capacity coefficient is a function across time that provides a useful measure of this construct. Until now, most analyses of the capacity coefficient have focused on the magnitude of this function, and often only in terms of a qualitative comparison (greater than or less than one). This work explains how a functional extension of principal components analysis can capture the time-extended information of these functional data, using a small number of scalar values chosen to emphasize the variance between participants and conditions. This approach provides many possibilities for a more fine-grained study of differences in workload capacity across tasks and individuals. PMID:23475829

  13. Functional analysis and intervention for breath holding.

    PubMed

    Kern, L; Mauk, J E; Marder, T J; Mace, F C

    1995-01-01

    We conducted a functional analysis of breath-holding episodes in a 7-year-old girl with severe mental retardation and Cornelia-de-Lange syndrome. The results showed that breath holding served an operant function, primarily to gain access to attention. The intervention, consisting of extinction, scheduled attention, and use of a picture card communication system, resulted in decreased breath holding.

  14. Structural and functional imaging correlates for age-related changes in the brain.

    PubMed

    Tumeh, Paul C; Alavi, Abass; Houseni, Mohamed; Greenfield, Antje; Chryssikos, Timothy; Newberg, Andrew; Torigian, Drew A; Moonis, Gul

    2007-03-01

    In recent years, investigators have made significant progress in documenting brain structure and function as it relates to aging by using positron emission tomography, conventional magnetic resonance (MR) imaging, advanced MR techniques, and functional MR imaging. This review summarizes the latest advances in understanding physiologic maturation and aging as detected by these neuroimaging modalities. We also present our experience with MR volumetric and positron emission tomography analysis in separate cohorts of healthy subjects in the pediatric and adult age groups respectively. Our results are consistent with previous studies and include the following: total brain volume was found to increase with age (up to 20 years of age). Whole brain metabolism and frontal lobe metabolism both decrease significantly with age (38% and 42%, respectively), whereas cerebellar metabolism does not show a significant decline with age. Defining normal alterations in brain function and structure allows early detection of disorders such as Alzheimer's and Parkinson's diseases, which are commonly associated with normal aging. PMID:17289456

  15. The Emergence of NMDA Receptor Metabotropic Function: Insights from Imaging.

    PubMed

    Dore, Kim; Aow, Jonathan; Malinow, Roberto

    2016-01-01

    The NMDA receptor (R) participates in many important physiological and pathological processes. For example, its activation is required for both long-term potentiation (LTP) and long-term depression (LTD) of synaptic transmission, cellular models of learning and memory. Furthermore, it may play a role in the actions of amyloid-beta on synapses as well as in the signaling leading to cell death following stroke. Until recently, these processes were thought to be mediated by ion-flux through the receptor. Using a combination of imaging and electrophysiological approaches, ion-flux independent functions of the NMDAR were recently examined. In this review, we will discuss the role of metabotropic NMDAR function in LTD and synaptic dysfunction. PMID:27516738

  16. Band Excitation in Scanning Probe Microscopy: Recognition and Functional Imaging

    SciTech Connect

    Jesse, Stephen; Vasudevan, Dr. Rama; Collins, Liam; Strelcov, Evgheni; Okatan, Mahmut B; Belianinov, Alex; Baddorf, Arthur P; Proksch, Roger; Kalinin, Sergei V

    2014-01-01

    Field confinement at the junction between a biased scanning probe microscope s (SPM) tip and solid surface enables local probing of various bias-induced transformations such as polarization switching, ionic motion, or electrochemical reactions to name a few. The nanoscale size of the biased region is smaller or comparable to features like grain boundaries and dislocations, potentially allows for the study of kinetics and thermodynamics at the level of a single defect. In contrast to classical statistically averaged approaches, this allows one to link structure to functionality and deterministically decipher associated mesoscopic and atomistic mechanisms. Furthermore, this type of information can serve as a fingerprint of local material functionality, allowing for local recognition imaging. Here, current progress in multidimensional SPM techniques based on band-excitation time and voltage spectroscopies is illustrated, including discussions on data acquisition, dimensionality reduction, and visualization along with future challenges and opportunities for the field.

  17. The Emergence of NMDA Receptor Metabotropic Function: Insights from Imaging

    PubMed Central

    Dore, Kim; Aow, Jonathan; Malinow, Roberto

    2016-01-01

    The NMDA receptor (R) participates in many important physiological and pathological processes. For example, its activation is required for both long-term potentiation (LTP) and long-term depression (LTD) of synaptic transmission, cellular models of learning and memory. Furthermore, it may play a role in the actions of amyloid-beta on synapses as well as in the signaling leading to cell death following stroke. Until recently, these processes were thought to be mediated by ion-flux through the receptor. Using a combination of imaging and electrophysiological approaches, ion-flux independent functions of the NMDAR were recently examined. In this review, we will discuss the role of metabotropic NMDAR function in LTD and synaptic dysfunction. PMID:27516738

  18. Functional imaging with Turbo-CASL: transit time and multislice imaging considerations.

    PubMed

    Lee, Gregory R; Hernandez-Garcia, Luis; Noll, Douglas C

    2007-04-01

    The optimal use of turbo continuous arterial spin labeling (Turbo-CASL) for functional imaging in the presence of activation-induced transit time (TT) changes was investigated. Functional imaging of a bilateral finger-tapping task showed improved sensitivity for Turbo-CASL as compared to traditional CASL techniques for four of six subjects when scanned at an appropriate repetition time (TR). Both experimental and simulation results suggest that for optimal functional sensitivity with Turbo-CASL, the pulse TR should be set to a value that is 100-200 ms less than the resting-state TT. Simulations were also run to demonstrate the differences in TT sensitivity of different slices within a multislice acquisition, and the signal loss that is expected as the number of slices is increased. Despite the lower baseline ASL signal provided by the Turbo-CASL acquisition, one can achieve equal or improved functional sensitivity due in part to the signal enhancement that accompanies the decrease in TT upon activation. Turbo-CASL is thus a promising technique for functional ASL at higher temporal resolution.

  19. Voltage imaging to understand connections and functions of neuronal circuits.

    PubMed

    Antic, Srdjan D; Empson, Ruth M; Knöpfel, Thomas

    2016-07-01

    Understanding of the cellular mechanisms underlying brain functions such as cognition and emotions requires monitoring of membrane voltage at the cellular, circuit, and system levels. Seminal voltage-sensitive dye and calcium-sensitive dye imaging studies have demonstrated parallel detection of electrical activity across populations of interconnected neurons in a variety of preparations. A game-changing advance made in recent years has been the conceptualization and development of optogenetic tools, including genetically encoded indicators of voltage (GEVIs) or calcium (GECIs) and genetically encoded light-gated ion channels (actuators, e.g., channelrhodopsin2). Compared with low-molecular-weight calcium and voltage indicators (dyes), the optogenetic imaging approaches are 1) cell type specific, 2) less invasive, 3) able to relate activity and anatomy, and 4) facilitate long-term recordings of individual cells' activities over weeks, thereby allowing direct monitoring of the emergence of learned behaviors and underlying circuit mechanisms. We highlight the potential of novel approaches based on GEVIs and compare those to calcium imaging approaches. We also discuss how novel approaches based on GEVIs (and GECIs) coupled with genetically encoded actuators will promote progress in our knowledge of brain circuits and systems. PMID:27075539

  20. Extended depth of field imaging for high speed object analysis

    NASA Technical Reports Server (NTRS)

    Ortyn, William (Inventor); Basiji, David (Inventor); Frost, Keith (Inventor); Liang, Luchuan (Inventor); Bauer, Richard (Inventor); Hall, Brian (Inventor); Perry, David (Inventor)

    2011-01-01

    A high speed, high-resolution flow imaging system is modified to achieve extended depth of field imaging. An optical distortion element is introduced into the flow imaging system. Light from an object, such as a cell, is distorted by the distortion element, such that a point spread function (PSF) of the imaging system is invariant across an extended depth of field. The distorted light is spectrally dispersed, and the dispersed light is used to simultaneously generate a plurality of images. The images are detected, and image processing is used to enhance the detected images by compensating for the distortion, to achieve extended depth of field images of the object. The post image processing preferably involves de-convolution, and requires knowledge of the PSF of the imaging system, as modified by the optical distortion element.

  1. Developmental imaging genetics: linking dopamine function to adolescent behavior.

    PubMed

    Padmanabhan, Aarthi; Luna, Beatriz

    2014-08-01

    Adolescence is a period of development characterized by numerous neurobiological changes that significantly influence behavior and brain function. Adolescence is of particular interest due to the alarming statistics indicating that mortality rates increase two to three-fold during this time compared to childhood, due largely to a peak in risk-taking behaviors resulting from increased impulsivity and sensation seeking. Furthermore, there exists large unexplained variability in these behaviors that are in part mediated by biological factors. Recent advances in molecular genetics and functional neuroimaging have provided a unique and exciting opportunity to non-invasively study the influence of genetic factors on brain function in humans. While genes do not code for specific behaviors, they do determine the structure and function of proteins that are essential to the neuronal processes that underlie behavior. Therefore, studying the interaction of genotype with measures of brain function over development could shed light on critical time points when biologically mediated individual differences in complex behaviors emerge. Here we review animal and human literature examining the neurobiological basis of adolescent development related to dopamine neurotransmission. Dopamine is of critical importance because of (1) its role in cognitive and affective behaviors, (2) its role in the pathogenesis of major psychopathology, and (3) the protracted development of dopamine signaling pathways over adolescence. We will then focus on current research examining the role of dopamine-related genes on brain function. We propose the use of imaging genetics to examine the influence of genetically mediated dopamine variability on brain function during adolescence, keeping in mind the limitations of this approach. PMID:24139694

  2. Developmental imaging genetics: linking dopamine function to adolescent behavior

    PubMed Central

    Padmanabhan, Aarthi; Luna, Beatriz

    2014-01-01

    Adolescence is a period of development characterized by numerous neurobiological changes that significantly influence behavior and brain function. Adolescence is of particular interest due to the alarming statistics indicating that mortality rates increase two to three-fold during this time compared to childhood, due largely to a peak in risk-taking behaviors resulting from increased impulsivity and sensation seeking. Furthermore, there exists large unexplained variability in these behaviors that are in part mediated by biological factors. Recent advances in molecular genetics and functional neuroimaging have provided a unique and exciting opportunity to noninvasively study the influence of genetic factors on brain function in humans. While genes do not code for specific behaviors, they do determine the structure and function of proteins that are essential to the neuronal processes that underlie behavior. Therefore, studying the interaction of genotype with measures of brain function over development could shed light on critical time points when biologically mediated individual differences in complex behaviors emerge. Here we review animal and human literature examining the neurobiological basis of adolescent development related to dopamine neurotransmission. Dopamine is of critical importance because of (1) its role in cognitive and affective behaviors, (2) its role in the pathogenesis of major psychopathology, and (3) the protracted development of dopamine signaling pathways over adolescence. We will then focus on current research examining the role of dopamine-related genes on brain function. We propose the use of imaging genetics to examine the influence of genetically mediated dopamine variability on brain function during adolescence, keeping in mind the limitations of this approach. PMID:24139694

  3. Multifractal analysis of dynamic infrared imaging of breast cancer

    NASA Astrophysics Data System (ADS)

    Gerasimova, E.; Audit, B.; Roux, S. G.; Khalil, A.; Argoul, F.; Naimark, O.; Arneodo, A.

    2013-12-01

    The wavelet transform modulus maxima (WTMM) method was used in a multifractal analysis of skin breast temperature time-series recorded using dynamic infrared (IR) thermography. Multifractal scaling was found for healthy breasts as the signature of a continuous change in the shape of the probability density function (pdf) of temperature fluctuations across time scales from \\sim0.3 to 3 s. In contrast, temperature time-series from breasts with malignant tumors showed homogeneous monofractal temperature fluctuations statistics. These results highlight dynamic IR imaging as a very valuable non-invasive technique for preliminary screening in asymptomatic women to identify those with risk of breast cancer.

  4. Functional imaging of the human placenta with magnetic resonance.

    PubMed

    Siauve, Nathalie; Chalouhi, Gihad E; Deloison, Benjamin; Alison, Marianne; Clement, Olivier; Ville, Yves; Salomon, Laurent J

    2015-10-01

    Abnormal placentation is responsible for most failures in pregnancy; however, an understanding of placental functions remains largely concealed from noninvasive, in vivo investigations. Magnetic resonance imaging (MRI) is safe in pregnancy for magnetic fields of up to 3 Tesla and is being used increasingly to improve the accuracy of prenatal imaging. Functional MRI (fMRI) of the placenta has not yet been validated in a clinical setting, and most data are derived from animal studies. FMRI could be used to further explore placental functions that are related to vascularization, oxygenation, and metabolism in human pregnancies by the use of various enhancement processes. Dynamic contrast-enhanced MRI is best able to quantify placental perfusion, permeability, and blood volume fractions. However, the transplacental passage of Gadolinium-based contrast agents represents a significant safety concern for this procedure in humans. There are alternative contrast agents that may be safer in pregnancy or that do not cross the placenta. Arterial spin labeling MRI relies on magnetically labeled water to quantify the blood flows within the placenta. A disadvantage of this technique is a poorer signal-to-noise ratio. Based on arterial spin labeling, placental perfusion in normal pregnancy is 176 ± 91 mL × min(-1) × 100 g(-1) and decreases in cases with intrauterine growth restriction. Blood oxygen level-dependent and oxygen-enhanced MRIs do not assess perfusion but measure the response of the placenta to changes in oxygen levels with the use of hemoglobin as an endogenous contrast agent. Diffusion-weighted imaging and intravoxel incoherent motion MRI do not require exogenous contrast agents, instead they use the movement of water molecules within tissues. The apparent diffusion coefficient and perfusion fraction are significantly lower in placentas of growth-restricted fetuses when compared with normal pregnancies. Magnetic resonance spectroscopy has the ability to extract

  5. Functional imaging of the human placenta with magnetic resonance.

    PubMed

    Siauve, Nathalie; Chalouhi, Gihad E; Deloison, Benjamin; Alison, Marianne; Clement, Olivier; Ville, Yves; Salomon, Laurent J

    2015-10-01

    Abnormal placentation is responsible for most failures in pregnancy; however, an understanding of placental functions remains largely concealed from noninvasive, in vivo investigations. Magnetic resonance imaging (MRI) is safe in pregnancy for magnetic fields of up to 3 Tesla and is being used increasingly to improve the accuracy of prenatal imaging. Functional MRI (fMRI) of the placenta has not yet been validated in a clinical setting, and most data are derived from animal studies. FMRI could be used to further explore placental functions that are related to vascularization, oxygenation, and metabolism in human pregnancies by the use of various enhancement processes. Dynamic contrast-enhanced MRI is best able to quantify placental perfusion, permeability, and blood volume fractions. However, the transplacental passage of Gadolinium-based contrast agents represents a significant safety concern for this procedure in humans. There are alternative contrast agents that may be safer in pregnancy or that do not cross the placenta. Arterial spin labeling MRI relies on magnetically labeled water to quantify the blood flows within the placenta. A disadvantage of this technique is a poorer signal-to-noise ratio. Based on arterial spin labeling, placental perfusion in normal pregnancy is 176 ± 91 mL × min(-1) × 100 g(-1) and decreases in cases with intrauterine growth restriction. Blood oxygen level-dependent and oxygen-enhanced MRIs do not assess perfusion but measure the response of the placenta to changes in oxygen levels with the use of hemoglobin as an endogenous contrast agent. Diffusion-weighted imaging and intravoxel incoherent motion MRI do not require exogenous contrast agents, instead they use the movement of water molecules within tissues. The apparent diffusion coefficient and perfusion fraction are significantly lower in placentas of growth-restricted fetuses when compared with normal pregnancies. Magnetic resonance spectroscopy has the ability to extract

  6. The physics of functional magnetic resonance imaging (fMRI)

    NASA Astrophysics Data System (ADS)

    Buxton, Richard B.

    2013-09-01

    Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology.

  7. The physics of functional magnetic resonance imaging (fMRI)

    PubMed Central

    Buxton, Richard B

    2015-01-01

    Functional magnetic resonance imaging (fMRI) is a methodology for detecting dynamic patterns of activity in the working human brain. Although the initial discoveries that led to fMRI are only about 20 years old, this new field has revolutionized the study of brain function. The ability to detect changes in brain activity has a biophysical basis in the magnetic properties of deoxyhemoglobin, and a physiological basis in the way blood flow increases more than oxygen metabolism when local neural activity increases. These effects translate to a subtle increase in the local magnetic resonance signal, the blood oxygenation level dependent (BOLD) effect, when neural activity increases. With current techniques, this pattern of activation can be measured with resolution approaching 1 mm3 spatially and 1 s temporally. This review focuses on the physical basis of the BOLD effect, the imaging methods used to measure it, the possible origins of the physiological effects that produce a mismatch of blood flow and oxygen metabolism during neural activation, and the mathematical models that have been developed to understand the measured signals. An overarching theme is the growing field of quantitative fMRI, in which other MRI methods are combined with BOLD methods and analyzed within a theoretical modeling framework to derive quantitative estimates of oxygen metabolism and other physiological variables. That goal is the current challenge for fMRI: to move fMRI from a mapping tool to a quantitative probe of brain physiology. PMID:24006360

  8. Body image and its relationship with sexual function and marital adjustment in infertile women

    PubMed Central

    Karamidehkordi, Akram; Roudsari, Robab Latifnejad

    2014-01-01

    Background: Body image is related to cognitive, emotional, and physical aspects of women's life. Therefore, it is expected to have an important role in women's sexual health and marital adjustment too. This issue seems to be salient in infertile women who suffer from psychological consequences of infertility. This study was conducted to investigate the relationship of body image with sexual function and marital adjustment in infertile women in 2011 in Mashhad, Iran. Materials and Methods: This correlational study was performed on 130 infertile women who referred to Montaserieh Infertility Research Centre in Mashhad, Iran. Subjects were selected using convenient sampling method. To collect data, valid and reliable questionnaires including demographic and infertility-related data tool, modified Younesi Body Image Questionnaire, Rosen Female Sexual Function Index (FSFI), and Spanier Dyadic Adjustment Scale (DAS) were used. Data analysis was performed by SPSS software using Student's t-test, correlation, analysis of variance (ANOVA), and Tukey post-hoc test. Results: The mean scores of body image, sexual function, and marital adjustment in women were 308.1 ± 45.8, 27.23 ± 3.80, and 113.8 ± 19.73, respectively. There was a direct correlation between overall body image and subscales of sexual function including sexual arousal (P = 0.003), sexual desire (P = 0.024), vaginal moisture (P = 0.001), orgasm (P < 0.001), sexual satisfaction (P < 0.001), and dyspareunia (P = 0.007). A direct correlation was also observed between overall body image and subscales of marital adjustment including agreement and consent (P < 0.001), satisfaction with life (P < 0.001), continuity of life (P = 0.007), and expressing emotions within the family environment (P < 0.001). Conclusions: Improved sexual function and marital adjustment in cases with higher body image provides evidence that one of the solutions to reduce sexual dysfunction and marital dispute in infertile women could be

  9. Vector processing enhancements for real-time image analysis.

    SciTech Connect

    Shoaf, S.; APS Engineering Support Division

    2008-01-01

    A real-time image analysis system was developed for beam imaging diagnostics. An Apple Power Mac G5 with an Active Silicon LFG frame grabber was used to capture video images that were processed and analyzed. Software routines were created to utilize vector-processing hardware to reduce the time to process images as compared to conventional methods. These improvements allow for more advanced image processing diagnostics to be performed in real time.

  10. Longitudinal functional magnetic resonance imaging in animal models.

    PubMed

    Silva, Afonso C; Liu, Junjie V; Hirano, Yoshiyuki; Leoni, Renata F; Merkle, Hellmut; Mackel, Julie B; Zhang, Xian Feng; Nascimento, George C; Stefanovic, Bojana

    2011-01-01

    Functional magnetic resonance imaging (fMRI) has had an essential role in furthering our understanding of brain physiology and function. fMRI techniques are nowadays widely applied in neuroscience research, as well as in translational and clinical studies. The use of animal models in fMRI studies has been fundamental in helping elucidate the mechanisms of cerebral blood-flow regulation, and in the exploration of basic neuroscience questions, such as the mechanisms of perception, behavior, and cognition. Because animals are inherently non-compliant, most fMRI performed to date have required the use of anesthesia, which interferes with brain function and compromises interpretability and applicability of results to our understanding of human brain function. An alternative approach that eliminates the need for anesthesia involves training the animal to tolerate physical restraint during the data acquisition. In the present chapter, we review these two different approaches to obtaining fMRI data from animal models, with a specific focus on the acquisition of longitudinal data from the same subjects.

  11. Relations among Functional Systems in Behavior Analysis

    PubMed Central

    Thompson, Travis

    2007-01-01

    This paper proposes that an organism's integrated repertoire of operant behavior has the status of a biological system, similar to other biological systems, like the nervous, cardiovascular, or immune systems. Evidence from a number of sources indicates that the distinctions between biological and behavioral events is often misleading, engendering counterproductive explanatory controversy. A good deal of what is viewed as biological (often thought to be inaccessible or hypothetical) can become publicly measurable variables using currently available and developing technologies. Moreover, such endogenous variables can serve as establishing operations, discriminative stimuli, conjoint mediating events, and maintaining consequences within a functional analysis of behavior and need not lead to reductionistic explanation. I suggest that explanatory misunderstandings often arise from conflating different levels of analysis and that behavior analysis can extend its reach by identifying variables operating within a functional analysis that also serve functions in other biological systems. PMID:17575907

  12. Architectural principles for the design of wide band image analysis systems

    SciTech Connect

    Bruning, U.; Giloi, W.K.; Liedtke, C.E.

    1983-01-01

    To match an image-analysis system appropriately to the multistage nature of image analysis, the system should have: (1) an overall system architecture made up of several dedicated SIMD coprocessors connected through a bottleneck-free, high-speed communication structure; (2) data-structure types in hardware; and (3) a conventional computer for executing operating-system functions and application programs. Coprocessors may exist specifically for local image processing, FFT, list processing, and vector processing in general. All functions must be transparent to the user. The architectural principles of such a system and the policies and mechanisms for its realization are exemplified. 4 references.

  13. Multi-Scale Fractal Analysis of Image Texture and Pattern

    NASA Technical Reports Server (NTRS)

    Emerson, Charles W.

    1998-01-01

    Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and

  14. An optimal point spread function subtraction algorithm for high-contrast imaging: a demonstration with angular differential imaging

    SciTech Connect

    Lafreniere, D; Marois, C; Doyon, R; Artigau, E; Nadeau, D

    2006-09-19

    Direct imaging of exoplanets is limited by bright quasi-static speckles in the point spread function (PSF) of the central star. This limitation can be reduced by subtraction of reference PSF images. We have developed an algorithm to construct an optimal reference PSF image from an arbitrary set of reference images. This image is built as a linear combination of all available images and is optimized independently inside multiple subsections of the image to ensure that the absolute minimum residual noise is achieved within each subsection. The algorithm developed is completely general and can be used with many high contrast imaging observing strategies, such as angular differential imaging (ADI), roll subtraction, spectral differential imaging, reference star observations, etc. The performance of the algorithm is demonstrated for ADI data. It is shown that for this type of data the new algorithm provides a gain in sensitivity by up 22 to a factor 3 at small separation over the algorithm previously used.

  15. Thermal image analysis for detecting facemask leakage

    NASA Astrophysics Data System (ADS)

    Dowdall, Jonathan B.; Pavlidis, Ioannis T.; Levine, James

    2005-03-01

    Due to the modern advent of near ubiquitous accessibility to rapid international transportation the epidemiologic trends of highly communicable diseases can be devastating. With the recent emergence of diseases matching this pattern, such as Severe Acute Respiratory Syndrome (SARS), an area of overt concern has been the transmission of infection through respiratory droplets. Approved facemasks are typically effective physical barriers for preventing the spread of viruses through droplets, but breaches in a mask"s integrity can lead to an elevated risk of exposure and subsequent infection. Quality control mechanisms in place during the manufacturing process insure that masks are defect free when leaving the factory, but there remains little to detect damage caused by transportation or during usage. A system that could monitor masks in real-time while they were in use would facilitate a more secure environment for treatment and screening. To fulfill this necessity, we have devised a touchless method to detect mask breaches in real-time by utilizing the emissive properties of the mask in the thermal infrared spectrum. Specifically, we use a specialized thermal imaging system to detect minute air leakage in masks based on the principles of heat transfer and thermodynamics. The advantage of this passive modality is that thermal imaging does not require contact with the subject and can provide instant visualization and analysis. These capabilities can prove invaluable for protecting personnel in scenarios with elevated levels of transmission risk such as hospital clinics, border check points, and airports.

  16. Computer-aided pulmonary image analysis in small animal models

    PubMed Central

    Xu, Ziyue; Bagci, Ulas; Mansoor, Awais; Kramer-Marek, Gabriela; Luna, Brian; Kubler, Andre; Dey, Bappaditya; Foster, Brent; Papadakis, Georgios Z.; Camp, Jeremy V.; Jonsson, Colleen B.; Bishai, William R.; Jain, Sanjay; Udupa, Jayaram K.; Mollura, Daniel J.

    2015-01-01

    Purpose: To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models. Methods: The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors’ system estimates an expected lung volume by utilizing a regression function between total lung capacity and approximated rib cage volume. A significant difference between the expected lung volume and the initial lung segmentation indicates the presence of severe pathology, and invokes a machine learning based abnormal imaging pattern detection system next. The final stage of the proposed framework is the automatic extraction of airway tree for which new affinity relationships within the fuzzy connectedness image segmentation framework are proposed by combining Hessian and gray-scale morphological reconstruction filters. Results: 133 CT scans were collected from four different studies encompassing a wide spectrum of pulmonary abnormalities pertaining to two commonly used small animal models (ferret and rabbit). Sensitivity and specificity were greater than 90% for pathological lung segmentation (average dice similarity coefficient > 0.9). While qualitative visual assessments of airway tree extraction were performed by the participating expert radiologists, for quantitative evaluation the authors validated the proposed airway extraction method by using publicly available EXACT’09 data set. Conclusions: The authors developed a comprehensive computer-aided pulmonary image analysis framework for preclinical research applications. The proposed framework consists of automatic pathological lung segmentation and accurate airway tree extraction. The framework has high sensitivity and specificity; therefore, it can contribute advances in preclinical research in pulmonary diseases. PMID:26133591

  17. Computer-aided pulmonary image analysis in small animal models

    SciTech Connect

    Xu, Ziyue; Mansoor, Awais; Mollura, Daniel J.; Bagci, Ulas; Kramer-Marek, Gabriela; Luna, Brian; Kubler, Andre; Dey, Bappaditya; Jain, Sanjay; Foster, Brent; Papadakis, Georgios Z.; Camp, Jeremy V.; Jonsson, Colleen B.; Bishai, William R.; Udupa, Jayaram K.

    2015-07-15

    Purpose: To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models. Methods: The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors’ system estimates an expected lung volume by utilizing a regression function between total lung capacity and approximated rib cage volume. A significant difference between the expected lung volume and the initial lung segmentation indicates the presence of severe pathology, and invokes a machine learning based abnormal imaging pattern detection system next. The final stage of the proposed framework is the automatic extraction of airway tree for which new affinity relationships within the fuzzy connectedness image segmentation framework are proposed by combining Hessian and gray-scale morphological reconstruction filters. Results: 133 CT scans were collected from four different studies encompassing a wide spectrum of pulmonary abnormalities pertaining to two commonly used small animal models (ferret and rabbit). Sensitivity and specificity were greater than 90% for pathological lung segmentation (average dice similarity coefficient > 0.9). While qualitative visual assessments of airway tree extraction were performed by the participating expert radiologists, for quantitative evaluation the authors validated the proposed airway extraction method by using publicly available EXACT’09 data set. Conclusions: The authors developed a comprehensive computer-aided pulmonary image analysis framework for preclinical research applications. The proposed framework consists of automatic pathological lung segmentation and accurate airway tree extraction. The framework has high sensitivity and specificity; therefore, it can contribute advances in preclinical research in pulmonary diseases.

  18. Roentgen stereophotogrammetric analysis using computer-based image-analysis.

    PubMed

    Ostgaard, S E; Gottlieb, L; Toksvig-Larsen, S; Lebech, A; Talbot, A; Lund, B

    1997-09-01

    The two-dimensional position of markers in radiographs for Roentgen Stereophotogrammetric Analysis (RSA) is usually determined using a measuring table. The purpose of this study was to evaluate the reproducibility and the accuracy of a new RSA system using digitized radiographs and image-processing algorithms to determine the marker position in the radiographs. Four double-RSA examinations of a phantom and 18 RSA examinations from six patients included in different RSA-studies of knee prostheses were used to test the reproducibility and the accuracy of the system. The radiographs were scanned at 600 dpi resolution and 256 gray levels. The center of each of the tantalum-markers in the radiographs was calculated by the computer program from the contour of the marker with the use of an edge-detection software algorithm after the marker was identified on a PC monitor. The study showed that computer-based image analysis can be used in RSA-examinations. The advantages of using image-processing software in RSA are that the marker positions are determined in an objective manner, and that there is no need for a systematic manual identification of all the markers on the radiograph before the actual measurement.

  19. Some selected quantitative methods of thermal image analysis in Matlab.

    PubMed

    Koprowski, Robert

    2016-05-01

    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image. PMID:26556680

  20. Some selected quantitative methods of thermal image analysis in Matlab.

    PubMed

    Koprowski, Robert

    2016-05-01

    The paper presents a new algorithm based on some selected automatic quantitative methods for analysing thermal images. It shows the practical implementation of these image analysis methods in Matlab. It enables to perform fully automated and reproducible measurements of selected parameters in thermal images. The paper also shows two examples of the use of the proposed image analysis methods for the area of ​​the skin of a human foot and face. The full source code of the developed application is also provided as an attachment. The main window of the program during dynamic analysis of the foot thermal image.

  1. Image analysis by integration of disparate information

    NASA Technical Reports Server (NTRS)

    Lemoigne, Jacqueline

    1993-01-01

    Image analysis often starts with some preliminary segmentation which provides a representation of the scene needed for further interpretation. Segmentation can be performed in several ways, which are categorized as pixel based, edge-based, and region-based. Each of these approaches are affected differently by various factors, and the final result may be improved by integrating several or all of these methods, thus taking advantage of their complementary nature. In this paper, we propose an approach that integrates pixel-based and edge-based results by utilizing an iterative relaxation technique. This approach has been implemented on a massively parallel computer and tested on some remotely sensed imagery from the Landsat-Thematic Mapper (TM) sensor.

  2. Multiparametric Image Analysis of Lung Branching Morphogenesis

    PubMed Central

    Schnatwinkel, Carsten; Niswander, Lee

    2013-01-01

    BACKGROUND Lung branching morphogenesis is a fundamental developmental process, yet the cellular dynamics that occur during lung development and the molecular mechanisms underlying recent postulated branching modes are poorly understood. RESULTS Here, we implemented a time-lapse video microscopy method to study the cellular behavior and molecular mechanisms of planar bifurcation and domain branching in lung explant- and organotypic cultures. Our analysis revealed morphologically distinct stages that are shaped at least in part by a combination of localized and orientated cell divisions and by local mechanical forces. We also identified myosin light-chain kinase as an important regulator of bud bifurcation, but not domain branching in lung explants. CONCLUSION This live imaging approach provides a method to study cellular behavior during lung branching morphogenesis and suggests the importance of a mechanism primarily based on oriented cell proliferation and mechanical forces in forming and shaping the developing lung airways. PMID:23483685

  3. Decoding post-stroke motor function from structural brain imaging.

    PubMed

    Rondina, Jane M; Filippone, Maurizio; Girolami, Mark; Ward, Nick S

    2016-01-01

    Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine learning in structural imaging to investigate diseases that involve brain injury presents an additional challenge, especially in conditions like stroke, due to the high variability across patients regarding characteristics of the lesions. Extracting data from anatomical images in a way that translates brain damage information into features to be used as input to learning algorithms is still an open question. One of the most common approaches to capture regional information from brain injury is to obtain the lesion load per region (i.e. the proportion of voxels in anatomical structures that are considered to be damaged). However, no systematic evaluation has yet been performed to compare this approach with using patterns of voxels (i.e. considering each voxel as a single feature). In this paper we compared both approaches applying Gaussian Process Regression to decode motor scores in 50 chronic stroke patients based solely on data derived from structural MRI. For both approaches we compared different ways to delimit anatomical areas: regions of interest from an anatomical atlas, the corticospinal tract, a mask obtained from fMRI analysis with a motor task in healthy controls and regions selected using lesion-symptom mapping. Our analysis showed that extracting features through patterns of voxels that represent lesion probability produced better results than quantifying the lesion load per region. In particular, from the different ways to delimit anatomical areas compared, the best performance was obtained with a combination of a range of cortical and subcortical motor areas as well as the corticospinal tract. These results will inform the appropriate methodology for predicting long term motor outcomes from early post

  4. Functional-mixed effects models for candidate genetic mapping in imaging genetic studies.

    PubMed

    Lin, Ja-An; Zhu, Hongtu; Mihye, Ahn; Sun, Wei; Ibrahim, Joseph G

    2014-12-01

    The aim of this paper is to develop a functional-mixed effects modeling (FMEM) framework for the joint analysis of high-dimensional imaging data in a large number of locations (called voxels) of a three-dimensional volume with a set of genetic markers and clinical covariates. Our FMEM is extremely useful for efficiently carrying out the candidate gene approaches in imaging genetic studies. FMEM consists of two novel components including a mixed effects model for modeling nonlinear genetic effects on imaging phenotypes by introducing the genetic random effects at each voxel and a jumping surface model for modeling the variance components of the genetic random effects and fixed effects as piecewise smooth functions of the voxels. Moreover, FMEM naturally accommodates the correlation structure of the genetic markers at each voxel, while the jumping surface model explicitly incorporates the intrinsically spatial smoothness of the imaging data. We propose a novel two-stage adaptive smoothing procedure to spatially estimate the piecewise smooth functions, particularly the irregular functional genetic variance components, while preserving their edges among different piecewise-smooth regions. We develop weighted likelihood ratio tests and derive their exact approximations to test the effect of the genetic markers across voxels. Simulation studies show that FMEM significantly outperforms voxel-wise approaches in terms of higher sensitivity and specificity to identify regions of interest for carrying out candidate genetic mapping in imaging genetic studies. Finally, FMEM is used to identify brain regions affected by three candidate genes including CR1, CD2AP, and PICALM, thereby hoping to shed light on the pathological interactions between these candidate genes and brain structure and function.

  5. Delineating potential epileptogenic areas utilizing resting functional magnetic resonance imaging (fMRI) in epilepsy patients.

    PubMed

    Pizarro, Ricardo; Nair, Veena; Meier, Timothy; Holdsworth, Ryan; Tunnell, Evelyn; Rutecki, Paul; Sillay, Karl; Meyerand, Mary E; Prabhakaran, Vivek

    2016-08-01

    Seizure localization includes neuroimaging like electroencephalogram, and magnetic resonance imaging (MRI) with limited ability to characterize the epileptogenic network. Temporal clustering analysis (TCA) characterizes epileptogenic network congruent with interictal epileptiform discharges by clustering together voxels with transient signals. We generated epileptogenic areas for 12 of 13 epilepsy patients with TCA, congruent with different areas of seizure onset. Resting functional MRI (fMRI) scans are noninvasive, and can be acquired quickly, in patients with different levels of severity and function. Analyzing resting fMRI data using TCA is quick and can complement clinical methods to characterize the epileptogenic network. PMID:27362339

  6. DynaMod: dynamic functional modularity analysis

    PubMed Central

    Sun, Choong-Hyun; Hwang, Taeho; Oh, Kimin; Yi, Gwan-Su

    2010-01-01

    A comprehensive analysis of enriched functional categories in differentially expressed genes is important to extract the underlying biological processes of genome-wide expression profiles. Moreover, identification of the network of significant functional modules in these dynamic processes is an interesting challenge. This study introduces DynaMod, a web-based application that identifies significant functional modules reflecting the change of modularity and differential expressions that are correlated with gene expression profiles under different conditions. DynaMod allows the inspection of a wide variety of functional modules such as the biological pathways, transcriptional factor–target gene groups, microRNA–target gene groups, protein complexes and hub networks involved in protein interactome. The statistical significance of dynamic functional modularity is scored based on Z-statistics from the average of mutual information (MI) changes of involved gene pairs under different conditions. Significantly correlated gene pairs among the functional modules are used to generate a correlated network of functional categories. In addition to these main goals, this scoring strategy supports better performance to detect significant genes in microarray analyses, as the scores of correlated genes show the superior characteristics of the significance analysis compared with those of individual genes. DynaMod also offers cross-comparison between different analysis outputs. DynaMod is freely accessible at http://piech.kaist.ac.kr/dynamod. PMID:20460468

  7. The Road to FUNCTIONAL IMAGING and ULTRAHIGH FIELDS

    PubMed Central

    Uğurbil, Kâmil

    2012-01-01

    The Center for Magnetic Resonance (CMRR) at the University of Minnesota was one of laboratories where the work that simultaneously and independently introduced functional magnetic resonance imaging (fMRI) of human brain activity was carried out. However, unlike other laboratories pursuing fMRI at the time, our work was performed at 4 Tesla magnetic field and coincided with the effort to push human magnetic resonance imaging to field strength significantly beyond 1.5 Tesla which was the high-end standard of the time. The human fMRI experiments performed in CMRR were planned between two colleagues who had known each other and had worked together previously in Bell Laboratories, namely Seiji Ogawa and myself, immediately after the Blood Oxygenation Level Dependent (BOLD) contrast was developed by Seiji. We were waiting for our first human system, a 4 Tesla system, to arrive in order to attempt at imaging brain activity in the human brain and these were the first experiments we performed on the 4 Tesla instrument in CMRR when it became marginally operational. This was a prelude to a subsequent systematic push we initiated for exploiting higher magnetic fields to improve the accuracy and sensitivity of fMRI maps, first going to 9.4 Tesla for animal model studies and subsequently developing a 7 Tesla human system for the first time. Steady improvements in high field instrumentation and ever expanding armamentarium of image acquisition and engineering solutions to challenges posed by ultrahigh fields has brought fMRI to submillimeter resolution in the whole brain at 7 Tesla, the scale necessary to reach cortical columns and laminar differentiation in the whole brain. The solutions that emerged in response to technological challenges posed by 7 Tesla also propagated and continues to propagate to lower field clinical systems, a major advantage of the ultrahigh fields effort that is underappreciated. Further improvements at 7T are inevitable. Further translation of these

  8. Automated Imaging and Analysis of the Hemagglutination Inhibition Assay.

    PubMed

    Nguyen, Michael; Fries, Katherine; Khoury, Rawia; Zheng, Lingyi; Hu, Branda; Hildreth, Stephen W; Parkhill, Robert; Warren, William

    2016-04-01

    The hemagglutination inhibition (HAI) assay quantifies the level of strain-specific influenza virus antibody present in serum and is the standard by which influenza vaccine immunogenicity is measured. The HAI assay endpoint requires real-time monitoring of rapidly evolving red blood cell (RBC) patterns for signs of agglutination at a rate of potentially thousands of patterns per day to meet the throughput needs for clinical testing. This analysis is typically performed manually through visual inspection by highly trained individuals. However, concordant HAI results across different labs are challenging to demonstrate due to analyst bias and variability in analysis methods. To address these issues, we have developed a bench-top, standalone, high-throughput imaging solution that automatically determines the agglutination states of up to 9600 HAI assay wells per hour and assigns HAI titers to 400 samples in a single unattended 30-min run. Images of the tilted plates are acquired as a function of time and analyzed using algorithms that were developed through comprehensive examination of manual classifications. Concordance testing of the imaging system with eight different influenza antigens demonstrates 100% agreement between automated and manual titer determination with a percent difference of ≤3.4% for all cases.

  9. High resolution ultraviolet imaging spectrometer for latent image analysis.

    PubMed

    Lyu, Hang; Liao, Ningfang; Li, Hongsong; Wu, Wenmin

    2016-03-21

    In this work, we present a close-range ultraviolet imaging spectrometer with high spatial resolution, and reasonably high spectral resolution. As the transmissive optical components cause chromatic aberration in the ultraviolet (UV) spectral range, an all-reflective imaging scheme is introduced to promote the image quality. The proposed instrument consists of an oscillating mirror, a Cassegrain objective, a Michelson structure, an Offner relay, and a UV enhanced CCD. The finished spectrometer has a spatial resolution of 29.30μm on the target plane; the spectral scope covers both near and middle UV band; and can obtain approximately 100 wavelength samples over the range of 240~370nm. The control computer coordinates all the components of the instrument and enables capturing a series of images, which can be reconstructed into an interferogram datacube. The datacube can be converted into a spectrum datacube, which contains spectral information of each pixel with many wavelength samples. A spectral calibration is carried out by using a high pressure mercury discharge lamp. A test run demonstrated that this interferometric configuration can obtain high resolution spectrum datacube. The pattern recognition algorithm is introduced to analyze the datacube and distinguish the latent traces from the base materials. This design is particularly good at identifying the latent traces in the application field of forensic imaging.

  10. An ion beam analysis software based on ImageJ

    NASA Astrophysics Data System (ADS)

    Udalagama, C.; Chen, X.; Bettiol, A. A.; Watt, F.

    2013-07-01

    The suit of techniques (RBS, STIM, ERDS, PIXE, IL, IF,…) available in ion beam analysis yields a variety of rich information. Typically, after the initial challenge of acquiring data we are then faced with the task of having to extract relevant information or to present the data in a format with the greatest impact. This process sometimes requires developing new software tools. When faced with such situations the usual practice at the Centre for Ion Beam Applications (CIBA) in Singapore has been to use our computational expertise to develop ad hoc software tools as and when we need them. It then became apparent that the whole ion beam community can benefit from such tools; specifically from a common software toolset that can be developed and maintained by everyone with freedom to use and allowance to modify. In addition to the benefits of readymade tools and sharing the onus of development, this also opens up the possibility for collaborators to access and analyse ion beam data without having to depend on an ion beam lab. This has the virtue of making the ion beam techniques more accessible to a broader scientific community. We have identified ImageJ as an appropriate software base to develop such a common toolset. In addition to being in the public domain and been setup for collaborative tool development, ImageJ is accompanied by hundreds of modules (plugins) that allow great breadth in analysis. The present work is the first step towards integrating ion beam analysis into ImageJ. Some of the features of the current version of the ImageJ ‘ion beam' plugin are: (1) reading list mode or event-by-event files, (2) energy gates/sorts, (3) sort stacks, (4) colour function, (5) real time map updating, (6) real time colour updating and (7) median & average map creation.

  11. Image Analysis and Length Estimation of Biomolecules Using AFM

    PubMed Central

    Sundstrom, Andrew; Cirrone, Silvio; Paxia, Salvatore; Hsueh, Carlin; Kjolby, Rachel; Gimzewski, James K.; Reed, Jason; Mishra, Bud

    2014-01-01

    There are many examples of problems in pattern analysis for which it is often possible to obtain systematic characterizations, if in addition a small number of useful features or parameters of the image are known a priori or can be estimated reasonably well. Often, the relevant features of a particular pattern analysis problem are easy to enumerate, as when statistical structures of the patterns are well understood from the knowledge of the domain. We study a problem from molecular image analysis, where such a domain-dependent understanding may be lacking to some degree and the features must be inferred via machine-learning techniques. In this paper, we propose a rigorous, fully automated technique for this problem. We are motivated by an application of atomic force microscopy (AFM) image processing needed to solve a central problem in molecular biology, aimed at obtaining the complete transcription profile of a single cell, a snapshot that shows which genes are being expressed and to what degree. Reed et al. (“Single molecule transcription profiling with AFM,” Nanotechnology, vol. 18, no. 4, 2007) showed that the transcription profiling problem reduces to making high-precision measurements of biomolecule backbone lengths, correct to within 20–25 bp (6–7.5 nm). Here, we present an image processing and length estimation pipeline using AFM that comes close to achieving these measurement tolerances. In particular, we develop a biased length estimator on trained coefficients of a simple linear regression model, biweighted by a Beaton–Tukey function, whose feature universe is constrained by James–Stein shrinkage to avoid overfitting. In terms of extensibility and addressing the model selection problem, this formulation subsumes the models we studied. PMID:22759526

  12. Imaging samples in silica aerogel using an experimental point spread function.

    PubMed

    White, Amanda J; Ebel, Denton S

    2015-02-01

    Light microscopy is a powerful tool that allows for many types of samples to be examined in a rapid, easy, and nondestructive manner. Subsequent image analysis, however, is compromised by distortion of signal by instrument optics. Deconvolution of images prior to analysis allows for the recovery of lost information by procedures that utilize either a theoretically or experimentally calculated point spread function (PSF). Using a laser scanning confocal microscope (LSCM), we have imaged whole impact tracks of comet particles captured in silica aerogel, a low density, porous SiO2 solid, by the NASA Stardust mission. In order to understand the dynamical interactions between the particles and the aerogel, precise grain location and track volume measurement are required. We report a method for measuring an experimental PSF suitable for three-dimensional deconvolution of imaged particles in aerogel. Using fluorescent beads manufactured into Stardust flight-grade aerogel, we have applied a deconvolution technique standard in the biological sciences to confocal images of whole Stardust tracks. The incorporation of an experimentally measured PSF allows for better quantitative measurements of the size and location of single grains in aerogel and more accurate measurements of track morphology.

  13. Imaging samples in silica aerogel using an experimental point spread function.

    PubMed

    White, Amanda J; Ebel, Denton S

    2015-02-01

    Light microscopy is a powerful tool that allows for many types of samples to be examined in a rapid, easy, and nondestructive manner. Subsequent image analysis, however, is compromised by distortion of signal by instrument optics. Deconvolution of images prior to analysis allows for the recovery of lost information by procedures that utilize either a theoretically or experimentally calculated point spread function (PSF). Using a laser scanning confocal microscope (LSCM), we have imaged whole impact tracks of comet particles captured in silica aerogel, a low density, porous SiO2 solid, by the NASA Stardust mission. In order to understand the dynamical interactions between the particles and the aerogel, precise grain location and track volume measurement are required. We report a method for measuring an experimental PSF suitable for three-dimensional deconvolution of imaged particles in aerogel. Using fluorescent beads manufactured into Stardust flight-grade aerogel, we have applied a deconvolution technique standard in the biological sciences to confocal images of whole Stardust tracks. The incorporation of an experimentally measured PSF allows for better quantitative measurements of the size and location of single grains in aerogel and more accurate measurements of track morphology. PMID:25517515

  14. Functional imaging of glucose-evoked rat islet activities using transient intrinsic optical signals

    NASA Astrophysics Data System (ADS)

    Yao, Xin-Cheng; Cui, Wan-Xing; Li, Yi-Chao; Zhang, Wei; Lu, Rong-Wen; Thompson, Anthony; Amthor, Franklin; Wang, Xu-Jing

    2012-05-01

    We demonstrate intrinsic optical signal (IOS) imaging of intact rat islet, which consists of many endocrine cells working together. A near-infrared digital microscope was employed for optical monitoring of islet activities evoked by glucose stimulation. Dynamic NIR images revealed transient IOS responses in the islet activated by low-dose (2.75 mM) and high-dose (5.5 mM) glucose stimuli. Comparative experiments and quantitative analysis indicated that both glucose metabolism and calcium/insulin dynamics might contribute to the observed IOS responses. Further investigation of the IOS imaging technology may provide a high resolution method for ex vivo functional examination of the islet, which is important for advanced study of diabetes associated islet dysfunctions and for improved quality control of donor islets for transplantation.

  15. Functional magnetic resonance imaging of autism spectrum disorders

    PubMed Central

    Dichter, Gabriel S.

    2012-01-01

    This review presents an overview of functional magnetic resonance imaging findings in autism spectrum disorders (ASDs), Although there is considerable heterogeneity with respect to results across studies, common themes have emerged, including: (i) hypoactivation in nodes of the “social brain” during social processing tasks, including regions within the prefrontal cortex, the posterior superior temporal sulcus, the amygdala, and the fusiform gyrus; (ii) aberrant frontostriatal activation during cognitive control tasks relevant to restricted and repetitive behaviors and interests, including regions within the dorsal prefrontal cortex and the basal ganglia; (iii) differential lateralization and activation of language processing and production regions during communication tasks; (iv) anomalous mesolimbic responses to social and nonsocial rewards; (v) task-based long-range functional hypoconnectivity and short-range hyper-connectivity; and (vi) decreased anterior-posterior functional connectivity during resting states. These findings provide mechanistic accounts of ASD pathophysiology and suggest directions for future research aimed at elucidating etiologic models and developing rationally derived and targeted treatments. PMID:23226956

  16. Functional magnetic resonance imaging of autism spectrum disorders.

    PubMed

    Dichter, Gabriel S

    2012-09-01

    This review presents an overview of functional magnetic resonance imaging findings in autism spectrum disorders (ASDS), although there is considerable heterogeneity with respect to results across studies, common themes have emerged, including: (i) hypoactivation in nodes of the "social brain" during social processing tasks, including regions within the prefrontal cortex, the posterior superior temporal sulcus, the amygdala, and the fusiform gyrus; (ii) aberrant frontostriatal activation during cognitive control tasks relevant to restricted and repetitive behaviors and interests, including regions within the dorsal prefrontal cortex and the basal ganglia; (iii) differential lateralization and activation of language processing and production regions during communication tasks; (iv) anomalous mesolimbic responses to social and nonsocial rewards; (v) task-based long-range functional hypoconnectivity and short-range hyper-connectivity; and (vi) decreased anterior-posterior functional connectivity during resting states. These findings provide mechanistic accounts of ASD pathophysiology and suggest directions for future research aimed at elucidating etiologic models and developing rationally derived and targeted treatments.

  17. Functional magnetic resonance imaging in chronic ischaemic stroke.

    PubMed

    Lake, Evelyn M R; Bazzigaluppi, Paolo; Stefanovic, Bojana

    2016-10-01

    Ischaemic stroke is the leading cause of adult disability worldwide. Effective rehabilitation is hindered by uncertainty surrounding the underlying mechanisms that govern long-term ischaemic injury progression. Despite its potential as a sensitive non-invasive in vivo marker of brain function that may aid in the development of new treatments, blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has found limited application in the clinical research on chronic stage stroke progression. Stroke affects each of the physiological parameters underlying the BOLD contrast, markedly complicating the interpretation of BOLD fMRI data. This review summarizes current progress on application of BOLD fMRI in the chronic stage of ischaemic injury progression and discusses means by which more information may be gained from such BOLD fMRI measurements. Concomitant measurements of vascular reactivity, neuronal activity and metabolism in preclinical models of stroke are reviewed along with illustrative examples of post-ischaemic evolution in neuronal, glial and vascular function. The realization of the BOLD fMRI potential to propel stroke research is predicated on the carefully designed preclinical research establishing an ischaemia-specific quantitative model of BOLD signal contrast to provide the framework for interpretation of fMRI findings in clinical populations.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'.

  18. Imaging emotional brain functions: conceptual and methodological issues.

    PubMed

    Peper, Martin

    2006-06-01

    This article reviews the psychophysiological and brain imaging literature on emotional brain function from a methodological point of view. The difficulties in defining, operationalising and measuring emotional activation and, in particular, aversive learning will be considered. Emotion is a response of the organism during an episode of major significance and involves physiological activation, motivational, perceptual, evaluative and learning processes, motor expression, action tendencies and monitoring/subjective feelings. Despite the advances in assessing the physiological correlates of emotional perception and learning processes, a critical appraisal shows that functional neuroimaging approaches encounter methodological difficulties regarding measurement precision (e.g., response scaling and reproducibility) and validity (e.g., response specificity, generalisation to other paradigms, subjects or settings). Since emotional processes are not only the result of localised but also of widely distributed activation, a more representative model of assessment is needed that systematically relates the hierarchy of high- and low-level emotion constructs with the corresponding patterns of activity and functional connectivity of the brain.

  19. Functional magnetic resonance imaging in chronic ischaemic stroke.

    PubMed

    Lake, Evelyn M R; Bazzigaluppi, Paolo; Stefanovic, Bojana

    2016-10-01

    Ischaemic stroke is the leading cause of adult disability worldwide. Effective rehabilitation is hindered by uncertainty surrounding the underlying mechanisms that govern long-term ischaemic injury progression. Despite its potential as a sensitive non-invasive in vivo marker of brain function that may aid in the development of new treatments, blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) has found limited application in the clinical research on chronic stage stroke progression. Stroke affects each of the physiological parameters underlying the BOLD contrast, markedly complicating the interpretation of BOLD fMRI data. This review summarizes current progress on application of BOLD fMRI in the chronic stage of ischaemic injury progression and discusses means by which more information may be gained from such BOLD fMRI measurements. Concomitant measurements of vascular reactivity, neuronal activity and metabolism in preclinical models of stroke are reviewed along with illustrative examples of post-ischaemic evolution in neuronal, glial and vascular function. The realization of the BOLD fMRI potential to propel stroke research is predicated on the carefully designed preclinical research establishing an ischaemia-specific quantitative model of BOLD signal contrast to provide the framework for interpretation of fMRI findings in clinical populations.This article is part of the themed issue 'Interpreting BOLD: a dialogue between cognitive and cellular neuroscience'. PMID:27574307

  20. Imaging biomarkers in multiple Sclerosis: From image analysis to population imaging.

    PubMed

    Barillot, Christian; Edan, Gilles; Commowick, Olivier

    2016-10-01

    The production of imaging data in medicine increases more rapidly than the capacity of computing models to extract information from it. The grand challenges of better understanding the brain, offering better care for neurological disorders, and stimulating new drug design will not be achieved without significant advances in computational neuroscience. The road to success is to develop a new, generic, computational methodology and to confront and validate this methodology on relevant diseases with adapted computational infrastructures. This new concept sustains the need to build new research paradigms to better understand the natural history of the pathology at the early phase; to better aggregate data that will provide the most complete representation of the pathology in order to better correlate imaging with other relevant features such as clinical, biological or genetic data. In this context, one of the major challenges of neuroimaging in clinical neurosciences is to detect quantitative signs of pathological evolution as early as possible to prevent disease progression, evaluate therapeutic protocols or even better understand and model the natural history of a given neurological pathology. Many diseases encompass brain alterations often not visible on conventional MRI sequences, especially in normal appearing brain tissues (NABT). MRI has often a low specificity for differentiating between possible pathological changes which could help in discriminating between the different pathological stages or grades. The objective of medical image analysis procedures is to define new quantitative neuroimaging biomarkers to track the evolution of the pathology at different levels. This paper illustrates this issue in one acute neuro-inflammatory pathology: Multiple Sclerosis (MS). It exhibits the current medical image analysis approaches and explains how this field of research will evolve in the next decade to integrate larger scale of information at the temporal, cellular