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Sample records for functional image analysis

  1. Functional imaging of auditory scene analysis.

    PubMed

    Gutschalk, Alexander; Dykstra, Andrew R

    2014-01-01

    Our auditory system is constantly faced with the task of decomposing the complex mixture of sound arriving at the ears into perceptually independent streams constituting accurate representations of individual sound sources. This decomposition, termed auditory scene analysis, is critical for both survival and communication, and is thought to underlie both speech and music perception. The neural underpinnings of auditory scene analysis have been studied utilizing invasive experiments with animal models as well as non-invasive (MEG, EEG, and fMRI) and invasive (intracranial EEG) studies conducted with human listeners. The present article reviews human neurophysiological research investigating the neural basis of auditory scene analysis, with emphasis on two classical paradigms termed streaming and informational masking. Other paradigms - such as the continuity illusion, mistuned harmonics, and multi-speaker environments - are briefly addressed thereafter. We conclude by discussing the emerging evidence for the role of auditory cortex in remapping incoming acoustic signals into a perceptual representation of auditory streams, which are then available for selective attention and further conscious processing. This article is part of a Special Issue entitled Human Auditory Neuroimaging. PMID:23968821

  2. 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.

  3. Modulation-transfer-function analysis for sampled image systems

    NASA Technical Reports Server (NTRS)

    Park, S. K.; Kaczynski, M.-A.; Schowengerdt, R.

    1984-01-01

    Sampling generally causes the response of a digital imaging system to be locally shift-variant and not directly amenable to Modulation Transfer Function (MTF) analysis. However, this paper demonstrates that a meaningful system response can be calculated by averaging over an ensemble of point-source system inputs to yield an MTF which accounts for the combined effects of image formation, sampling, and image reconstruction. As an illustration, the MTF of the Landsat MSS system is analyzed to reveal an average effective instantaneous field of view which is significantly larger than the commonly accepted value, particularly in the along-track direction where undersampling contributes markedly to an MTF reduction and resultant increase in image blur.

  4. 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.

  5. 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

  6. Time-frequency analysis of functional optical mammographic images

    NASA Astrophysics Data System (ADS)

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

    2003-07-01

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

  7. 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.

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

    PubMed Central

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

    2015-01-01

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

  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. AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA

    PubMed Central

    Morris, Jeffrey S.; Baladandayuthapani, Veerabhadran; Herrick, Richard C.; Sanna, Pietro; Gutstein, Howard

    2011-01-01

    Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method

  11. 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.

  12. [Research of Left Ventricle Function Analysis Using Real-time Cardiac Magnetic Resonance Imaging].

    PubMed

    Yang, Fan; He, Yan; Zhang, Jie; Wu, Yin

    2015-12-01

    Real-time free breathing cardiac cine imaging is a reproducible method with shorter acquisition time and without breath-hold for cardiac magnetic resonance imaging. However, the detection of end-diastole and end-systole frames of real-time free breathing cardiac cine imaging for left ventricle function analysis is commonly completed by visual identification, which is time-consuming and laborious. In order to save processing time, we propose a method for semi-automatic identification of end-diastole and end-systole frames. The method fits respiratory motion signal and acquires the expiration phase, end-diastole and end-systole frames by cross correlation coefficient. The procedure successfully worked on ten healthy volunteers and validated by the analysis of left ventricle function compared to the standard breath-hold steady-state free precession cardiac cine imaging without any significant statistical differences. The results demonstrated that the present method could correctly detect end-diastole and end-systole frames. In the future, this technique may be used for rapid left ventricle function analysis in clinic. PMID:27079101

  13. 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  15. Classification of functional bowel disorders by objective physiological criteria based on endoluminal image analysis.

    PubMed

    Malagelada, Carolina; Drozdzal, Michal; Seguí, Santi; Mendez, Sara; Vitrià, Jordi; Radeva, Petia; Santos, Javier; Accarino, Anna; Malagelada, Juan-R; Azpiroz, Fernando

    2015-09-15

    We have previously developed an original method to evaluate small bowel motor function based on computer vision analysis of endoluminal images obtained by capsule endoscopy. Our aim was to demonstrate intestinal motor abnormalities in patients with functional bowel disorders by endoluminal vision analysis. Patients with functional bowel disorders (n = 205) and healthy subjects (n = 136) ingested the endoscopic capsule (Pillcam-SB2, Given-Imaging) after overnight fast and 45 min after gastric exit of the capsule a liquid meal (300 ml, 1 kcal/ml) was administered. Endoluminal image analysis was performed by computer vision and machine learning techniques to define the normal range and to identify clusters of abnormal function. After training the algorithm, we used 196 patients and 48 healthy subjects, completely naive, as test set. In the test set, 51 patients (26%) were detected outside the normal range (P < 0.001 vs. 3 healthy subjects) and clustered into hypo- and hyperdynamic subgroups compared with healthy subjects. Patients with hypodynamic behavior (n = 38) exhibited less luminal closure sequences (41 ± 2% of the recording time vs. 61 ± 2%; P < 0.001) and more static sequences (38 ± 3 vs. 20 ± 2%; P < 0.001); in contrast, patients with hyperdynamic behavior (n = 13) had an increased proportion of luminal closure sequences (73 ± 4 vs. 61 ± 2%; P = 0.029) and more high-motion sequences (3 ± 1 vs. 0.5 ± 0.1%; P < 0.001). Applying an original methodology, we have developed a novel classification of functional gut disorders based on objective, physiological criteria of small bowel function. PMID:26251472

  16. 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).

  17. Learning partially directed functional networks from meta-analysis imaging data

    PubMed Central

    Neumann, Jane; Fox, Peter T.; Turner, Robert; Lohmann, Gabriele

    2009-01-01

    We propose a new exploratory method for the discovery of partially directed functional networks from fMRI meta-analysis data. The method performs structure learning of Bayesian networks in search of directed probabilistic dependencies between brain regions. Learning is based on the co-activation of brain regions observed across several independent imaging experiments. In a series of simulations, we first demonstrate the reliability of the method. We then present the application of our approach in an extensive meta-analysis including several thousand activation coordinates from more than 500 imaging studies. Results show that our method is able to automatically infer Bayesian networks that capture both directed and undirected probabilistic dependencies between a number of brain regions, including regions that are frequently observed in motor-related and cognitive control tasks. PMID:19815079

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  19. Imaging Taiwan Moho Discontinuity from Receiver Function Inversion, Analysis and Migration

    NASA Astrophysics Data System (ADS)

    Wang, H.; Chen, H.; Zhu, L.; Duan, Y.

    2009-12-01

    We propose an updated Taiwan Moho discontinuity reference model from receiver function inversion, analysis and imaging based on all the available teleseismic data collected from 104 broadband stations. The 104 broadband stations cover two permanent networks from BATS, CWB and temporarily deployed arrays deployed by the TAiwan Integrated GEodynamics Research (TAIGER) project. The effective 1D velocity structure at each station was obtained through inversion. We further determined the spatial depth variation of Moho topography, crustal thickness (H), and Vp/Vs ratios (κ) beneath each broadband station. Using travel-time and waveforms of P-to-S wave conversion and crust reverberation phases, the H-κ stacking analysis provides the first hand information of Moho model. Images of crust-to-lithosphere scale structure profiles across three west-to-east linear receiver arrays were obtained from the CCP (common-conversion-point) stacking of teleseismic records collected from TAIGER project. Additional constraint from two north-to-south profiles along the Central Range and Longitudinal Valley can be derived by combining results from both permanent and portable broadband stations. These five CCP stacked images clearly reveal the Moho discontinuity relief changes. Preliminary results show that the deepest Moho-depth is 40 to 50 km in central Taiwan. The consistent results from velocity estimation, CCP and H-κ stacking marks the thicken crust in central Taiwan due to simultaneous subducting and overriding plates. All images show high impedance contrast that corresponds to sedimentary basins at shallow part of western foothill area.

  20. Imaging Lung Function in Mice Using SPECT/CT and Per-Voxel Analysis

    PubMed Central

    Jobse, Brian N.; Rhem, Rod G.; McCurry, Cory A. J. R.; Wang, Iris Q.; Labiris, N. Renée

    2012-01-01

    Chronic lung disease is a major worldwide health concern but better tools are required to understand the underlying pathologies. Ventilation/perfusion (V/Q) single photon emission computed tomography (SPECT) with per-voxel analysis allows for non-invasive measurement of regional lung function. A clinically adapted V/Q methodology was used in healthy mice to investigate V/Q relationships. Twelve week-old mice were imaged to describe normal lung function while 36 week-old mice were imaged to determine how age affects V/Q. Mice were ventilated with Technegas™ and injected with 99mTc-macroaggregated albumin to trace ventilation and perfusion, respectively. For both processes, SPECT and CT images were acquired, co-registered, and quantitatively analyzed. On a per-voxel basis, ventilation and perfusion were moderately correlated (R = 0.58±0.03) in 12 week old animals and a mean log(V/Q) ratio of −0.07±0.01 and standard deviation of 0.36±0.02 were found, defining the extent of V/Q matching. In contrast, 36 week old animals had significantly increased levels of V/Q mismatching throughout the periphery of the lung. Measures of V/Q were consistent across healthy animals and differences were observed with age demonstrating the capability of this technique in quantifying lung function. Per-voxel analysis and the ability to non-invasively assess lung function will aid in the investigation of chronic lung disease models and drug efficacy studies. PMID:22870297

  1. 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. PMID:19913573

  2. 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

  3. 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

  4. Spread function of acousto-optic filter with high-speed spectral image analysis

    NASA Astrophysics Data System (ADS)

    Zadorin, Anatoly S.; Nemtchenko, Andrei S.

    1998-08-01

    The contradictory requirements are presented to acousto- optic tunable filters (AOF) of spectral image analysis. On the one hand AOF should have high speed. On the other hand it should have good spectral resolution and wide angular aperture. Thus when AOF is fastly tuned with chirp transients, the diffracted wave intensity at different moments of transient process can considerably diverge form its quasistatic level. It means that spread function (SF) depends on the velocity of frequency tuning, i.e., it is described by 2D function with variables - wave length and velocity of frequency tuning. In Cartesian frame this dependence is presented by some surface being dynamic SF (DSF). It characterizes speed and selectivity properties of AOF. In this work DCF mathematical model was constructed and basic properties of spectral image analysis AOF were investigated. It has been established that the greatest distortions of DSF occur if velocity of frequency tuning has exceeded some critical value connected with acousto-optic interaction geometry and aperture sizes of beams. In this case the side lobes of SF will make 'false' maxima which begin to prevail over the basic. In addition under the conditions of phase mismatch DSF loses the symmetry to position of the main maximum. These effects reduce the accuracy of spectral measurements when tuning velocity is high.

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

    PubMed

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

    2013-01-01

    Two aspects play a key role in recently developed strategies for functional magnetic resonance imaging (fMRI) data analysis: first, it is now recognized that the human brain is a complex adaptive system and exhibits the hallmarks of complexity such as emergence of patterns arising out of a multitude of interactions between its many constituents. Second, the field of fMRI has evolved into a data-intensive, big data endeavor with large databases and masses of data being shared around the world. At the same time, ultra-high field MRI scanners are now available producing data at previously unobtainable quality and quantity. Both aspects have led to shifts in the way in which we view fMRI data. Here, we review recent developments in fMRI data analysis methodology that resulted from these shifts in paradigm. PMID:23402339

  6. 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

  7. 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…

  8. 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

  9. Functional imaging and endoscopy

    PubMed Central

    Zhang, Jian-Guo; Liu, Hai-Feng

    2011-01-01

    The emergence of endoscopy for the diagnosis of gastrointestinal diseases and the treatment of gastrointestinal diseases has brought great changes. The mere observation of anatomy with the imaging mode using modern endoscopy has played a significant role in this regard. However, increasing numbers of endoscopies have exposed additional deficiencies and defects such as anatomically similar diseases. Endoscopy can be used to examine lesions that are difficult to identify and diagnose. Early disease detection requires that substantive changes in biological function should be observed, but in the absence of marked morphological changes, endoscopic detection and diagnosis are difficult. Disease detection requires not only anatomic but also functional imaging to achieve a comprehensive interpretation and understanding. Therefore, we must ask if endoscopic examination can be integrated with both anatomic imaging and functional imaging. In recent years, as molecular biology and medical imaging technology have further developed, more functional imaging methods have emerged. This paper is a review of the literature related to endoscopic optical imaging methods in the hopes of initiating integration of functional imaging and anatomical imaging to yield a new and more effective type of endoscopy. PMID:22090783

  10. 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.

  11. The presupplementary area within the language network: a resting state functional magnetic resonance imaging functional connectivity analysis.

    PubMed

    Ter Minassian, Aram; Ricalens, Emmanuel; Nguyen The Tich, Sylvie; Dinomais, Mickaël; Aubé, Christophe; Beydon, Laurent

    2014-08-01

    The presupplementary motor area (pre-SMA) is involved in volitional selection. Despite the lateralization of the language network and different functions for both pre-SMA, few studies have reported the lateralization of pre-SMA activity and very little is known about the possible lateralization of pre-SMA connectivity. Via functional connectivity analysis, we sought to understand how the language network may be connected to other intrinsic connectivity networks (ICNs) through the pre-SMA. We performed a spatial independent component analysis of resting state functional magnetic resonance imaging in 30 volunteers to identify the language network. Subsequently, we applied seed-to-voxel functional connectivity analyses centered on peaks detected in the pre-SMA. Three signal peaks were detected in the pre-SMA. The left rostral pre-SMA intrinsic connectivity network (LR ICN) was left lateralized in contrast to bilateral ICNs associated to right pre-SMA peaks. The LR ICN was anticorrelated with the dorsal attention network and the right caudal pre-SMA ICN (RC ICN) anticorrelated with the default mode network. These two ICNs overlapped minimally. In contrast, the right rostral ICN overlapped the LR ICN. Both right ICNs overlapped in the ventral attention network (vATT). The bilateral connectivity of the right rostral pre-SMA may allow right hemispheric recruitment to process semantic ambiguities. Overlap between the right pre-SMA ICNs in vATT may contribute to internal thought to external environment reorientation. Distinct ICNs connected to areas involved in lexico-syntactic selection and phonology converge in the pre-SMA, which may constitute the resolution space of competing condition-action associations for speech production. PMID:24939724

  12. Image restoration of the open-loop adaptive optics retinal imaging system based on optical transfer function analysis

    NASA Astrophysics Data System (ADS)

    Yu, Lei; Qi, Yue; Li, Dayu; Xia, Mingliang; Xuan, Li

    2013-07-01

    The residual aberrations of the adaptive optics retinal imaging system will decrease the quality of the retinal images. To overcome this obstacle, we found that the optical transfer function (OTF) of the adaptive optics retinal imaging system can be described as the Levy stable distribution. Then a new method is introduced to estimate the OTF of the open-loop adaptive optics system, based on analyzing the residual aberrations of the open-loop adaptive optics system in the residual aberrations measuring mode. At last, the estimated OTF is applied to restore the retinal images of the open-loop adaptive optics retinal imaging system. The contrast and resolution of the restored image is significantly improved with the Laplacian sum (LS) from 0.0785 to 0.1480 and gray mean grads (GMG) from 0.0165 to 0.0306.

  13. Imaging of Cocos Plate Beneath Southern Costa Rica From Receiver Function Analysis

    NASA Astrophysics Data System (ADS)

    Dzierma, Y.; Thorwart, M.; Rabbel, W.

    2007-12-01

    A transect of 19 seismological broadband stations crossing the Talamanca Mountain Range in Southern Costa Rica was operated from March 2005 to April 2007 as a part of the Collaborative Research Center SFB 574 "Volatiles and Fluids in Subduction Zones". The aim of the seismological subproject A2 was to gain insight into the structure of the Central American subduction zone and possible pathways for fluid migration. Previous studies of active seismics and local seismicity suggested to explain the gap of volcanism in the Talamanca range with the lack of a subducting slab. They assumed that the Cocos Ridge underlies the overriding plate at a shallow dip. In contrast, our receiver function analysis of 322 teleseimic earthquakes is able to image the subducting Cocos Plate down to depths of at least 100 km. The dip angle of the slab closer to the trench is outside the network but appears to be shallow, consistent with former studies. Below 40 km, the dip increases to more than 45 deg. This is supported by accurately located seismicity from a tomography study also performed by our group. Crustal structure could also be resolved by the receiver function analysis in agreement with tomography and active seismic investigations. The existence of the subducting slab poses the question why volcanism stopped 4 Ma ago; several possible scenarios are discussed.

  14. 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 4-5days 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. PMID:26431669

  15. Resolution enhancement in active underwater polarization imaging with modulation transfer function analysis.

    PubMed

    Han, Jiefei; Yang, Kecheng; Xia, Min; Sun, Liying; Cheng, Zao; Liu, Hao; Ye, Junwei

    2015-04-10

    Active polarization imaging technology is a convenient and promising method for imaging in a scattering medium such as fog and turbid water. However, few studies have investigated the influence of polarization on the resolution in underwater imaging. This paper reports on the effects of polarization detection on the resolution of underwater imaging by using active polarization imaging technology. An experimental system is designed to determine the influence under various polarization and water conditions. The modulation transfer function is introduced to estimate the resolution variations at different spatial frequencies. Results show that orthogonal detection supplies the best resolution compared with other polarization directions in the turbid water. The performance of the circular polarization method is better than the linear process. However, if the light propagates under low scattering conditions, such as imaging in clean water or at small optical thickness, the resolution enhancement is not sensitive to the polarization angles. PMID:25967316

  16. Analysis of 2-d ultrasound cardiac strain imaging using joint probability density functions.

    PubMed

    Ma, Chi; Varghese, Tomy

    2014-06-01

    Ultrasound frame rates play a key role for accurate cardiac deformation tracking. Insufficient frame rates lead to an increase in signal de-correlation artifacts resulting in erroneous displacement and strain estimation. Joint probability density distributions generated from estimated axial strain and its associated signal-to-noise ratio provide a useful approach to assess the minimum frame rate requirements. Previous reports have demonstrated that bi-modal distributions in the joint probability density indicate inaccurate strain estimation over a cardiac cycle. In this study, we utilize similar analysis to evaluate a 2-D multi-level displacement tracking and strain estimation algorithm for cardiac strain imaging. The effect of different frame rates, final kernel dimensions and a comparison of radio frequency and envelope based processing are evaluated using echo signals derived from a 3-D finite element cardiac model and five healthy volunteers. Cardiac simulation model analysis demonstrates that the minimum frame rates required to obtain accurate joint probability distributions for the signal-to-noise ratio and strain, for a final kernel dimension of 1 λ by 3 A-lines, was around 42 Hz for radio frequency signals. On the other hand, even a frame rate of 250 Hz with envelope signals did not replicate the ideal joint probability distribution. For the volunteer study, clinical data was acquired only at a 34 Hz frame rate, which appears to be sufficient for radio frequency analysis. We also show that an increase in the final kernel dimensions significantly affect the strain probability distribution and joint probability density function generated, with a smaller effect on the variation in the accumulated mean strain estimated over a cardiac cycle. Our results demonstrate that radio frequency frame rates currently achievable on clinical cardiac ultrasound systems are sufficient for accurate analysis of the strain probability distribution, when a multi-level 2-D

  17. 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.

  18. 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.

  19. Prefrontal structural and functional brain imaging findings in antisocial, violent, and psychopathic individuals: a meta-analysis.

    PubMed

    Yang, Yaling; Raine, Adrian

    2009-11-30

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

  20. Characterization of the image-derived carotid artery input function using independent component analysis for the quantitation of [18F] fluorodeoxyglucose positron emission tomography images

    NASA Astrophysics Data System (ADS)

    Chen, K.; Chen, X.; Renaut, R.; Alexander, G. E.; Bandy, D.; Guo, H.; Reiman, E. M.

    2007-12-01

    We previously developed a noninvasive technique for the quantification of fluorodeoxyglucose (FDG) positron emission tomography (PET) images using an image-derived input function obtained from a manually drawn carotid artery region. Here, we investigate the use of independent component analysis (ICA) for more objective identification of the carotid artery and surrounding tissue regions. Using FDG PET data from 22 subjects, ICA was applied to an easily defined cubical region including the carotid artery and neighboring tissue. Carotid artery and tissue time activity curves and three venous samples were used to generate spillover and partial volume-corrected input functions and to calculate the parametric images of the cerebral metabolic rate for glucose (CMRgl). Different from a blood-sampling-free ICA approach, the results from our ICA approach are numerically well matched to those based on the arterial blood sampled input function. In fact, the ICA-derived input functions and CMRgl measurements were not only highly correlated (correlation coefficients >0.99) to, but also highly comparable (regression slopes between 0.92 and 1.09), with those generated using arterial blood sampling. Moreover, the reliability of the ICA-derived input function remained high despite variations in the location and size of the cubical region. The ICA procedure makes it possible to quantify FDG PET images in an objective and reproducible manner. Image-derived input function by ICA for FDG-PET.

  1. 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. PMID:24815265

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

    PubMed Central

    McAleavey, Stephen A.

    2014-01-01

    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. PMID:24815265

  3. Design of an active-passive device for human ankle movement during functional magnetic resonance imaging analysis.

    PubMed

    Belforte, Guido; Eula, Gabriella

    2012-01-01

    Functional magnetic resonance imaging analysis has made major strides in recent years, both because of the development of new scanners and owing to magnetic resonance compatible systems that make it possible to stimulate parts of the human body during analysis. The significant gains in our knowledge of the brain that can thus be achieved justify efforts to construct machines with control circuits suitable for this purpose. This paper presents a magnetic resonance compatible mechatronic device with electropneumatic control that can be used to move one or both feet during functional magnetic resonance imaging analysis of the cerebral motor zones. The system is innovative and original. The results obtained at the end of the investigation were good, and demonstrated that the design is feasible. PMID:22888581

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

    NASA Astrophysics Data System (ADS)

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

    2007-03-01

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

  5. 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.

  6. 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. PMID:26811173

  7. 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

  8. 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.

  9. 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.

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

    PubMed

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

    2016-09-01

    Characterizing heterogeneous nanostructured amorphous materials is a challenging topic, because of difficulty to solve disordered atomic arrangement in nanometer scale. We developed a new transmission electron microscopy (TEM) method to enable phase analysis and mapping of heterogeneous amorphous structures. That is to combine scanning TEM (STEM) diffraction mapping, radial distribution function (RDF) analysis, and hyperspectral analysis. This method was applied to an amorphous zirconium oxide and zirconium iron multilayer system, and showed extreme sensitivity to small atomic packing variations. This approach helps to understand local structure variations in glassy composite materials and provides new insights to correlate structure and properties of glasses. PMID:27236215

  11. 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

  12. 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

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

    PubMed Central

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

    2013-01-01

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

  14. Bioinformatics and functional magnetic resonance imaging in clinical populations: practical aspects of data collection, analysis, interpretation, and management.

    PubMed

    Vincent, Diana J; Hurd, Mark W

    2005-10-15

    In this paper the authors review the issues associated with bioinformatics and functional magnetic resonance (fMR) imaging in the context of neurosurgery. They discuss the practical aspects of data collection, analysis, interpretation, and the management of large data sets, and they consider the challenges involved in the adoption of fMR imaging into clinical neurosurgical practice. Their goal is to provide neurosurgeons and other clinicians with a better understanding of some of the current issues associated with bioinformatics or neuroinformatics and fMR imaging. Thousands to tens of thousands of images are typically acquired during an fMR imaging session. It is essential to follow an activation task paradigm exactly to obtain an accurate representation of cortical activation. These images are then interactively postprocessed offline to produce an activation map, or in some cases a series of maps. The maps may then be viewed and interpreted in consultation with a neurosurgeon and/or other clinicians. After this consultation, long-term archiving of the processed fMR activation maps along with the standard structural MR images is a complex but necessary final step in this process. The fMR modality represents a valuable tool in the neurosurgical planning process that is still in the developmental stages for routine clinical use, but holds exceptional promise for patient care. PMID:16241106

  15. 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

  16. pH-responsive and photostable group IV metal oxide functionalized porous silicon platforms and novel applications of spectroscopic imaging methods for functional and hybrid materials analysis

    NASA Astrophysics Data System (ADS)

    Destino, Joel F.

    This dissertation covers two research topics that center on the spectroscopic characterization of functional materials. First, the performance (i.e. pH stability, photostability, shelf life) of novel photoluminescent group IV metal oxide functionalized porous silicon platforms is discussed. Spectroscopic techniques are used to provide insight into the chemistry of these substrates, and investigate pH-dependent PL response. The second section covers various novel applications of spectroscopic imaging methods. Colocalized Raman and atomic force microscopy and fluorescence imaging results for two- and three-component hybrid antifouling xerogel thin films are presented. Analysis investigates the relationship between surface structure, surface charge, surface pH and chemistry as it relates to antifouling performance. Lastly, practical aspects of tip-enhanced Raman spectroscopy are discussed and preliminary results of WS2 on Au are presented.

  17. Large Sample Group Independent Component Analysis of Functional Magnetic Resonance Imaging Using Anatomical Atlas-Based Reduction and Bootstrapped Clustering

    PubMed Central

    Anderson, Ariana; Bramen, Jennifer; Douglas, Pamela K.; Lenartowicz, Agatha; Cho, Andrew; Culbertson, Chris; Brody, Arthur L.; Yuille, Alan L.; Cohen, Mark S.

    2011-01-01

    Independent component analysis (ICA) is a popular method for the analysis of functional magnetic resonance imaging (fMRI) signals that is capable of revealing connected brain systems of functional significance. To be computationally tractable, estimating the independent components (ICs) inevitably requires one or more dimension reduction steps. Whereas most algorithms perform such reductions in the time domain, the input data are much more extensive in the spatial domain, and there is broad consensus that the brain obeys rules of localization of function into regions that are smaller in number than the number of voxels in a brain image. These functional units apparently reorganize dynamically into networks under different task conditions. Here we develop a new approach to ICA, producing group results by bagging and clustering over hundreds of pooled single-subject ICA results that have been projected to a lower-dimensional subspace. Averages of anatomically based regions are used to compress the single subject-ICA results prior to clustering and resampling via bagging. The computational advantages of this approach make it possible to perform group-level analyses on datasets consisting of hundreds of scan sessions by combining the results of within-subject analysis, while retaining the theoretical advantage of mimicking what is known of the functional organization of the brain. The result is a compact set of spatial activity patterns that are common and stable across scan sessions and across individuals. Such representations may be used in the context of statistical pattern recognition supporting real-time state classification. PMID:22049263

  18. Analysis of the depth of field in hexagonal array integral imaging systems based on modulation transfer function and Strehl ratio.

    PubMed

    Karimzadeh, Ayatollah

    2016-04-10

    Integral imaging is a technique for displaying three-dimensional images using microlens arrays. In this paper, a method for calculating root mean squared wavefront error and modulation transfer function (MTF) of a defocused integral imaging capture system with hexagonal aperture microlens arrays is introduced. Also, maximum allowable depth of field with Century MTF analyzing and Strehl criterion are obtained. PMID:27139873

  19. 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.

  20. 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.

  1. Functional Characterization of Bovine Viral Diarrhea Virus Nonstructural Protein 5A by Reverse Genetic Analysis and Live Cell Imaging

    PubMed Central

    Isken, Olaf; Langerwisch, Ulrike; Schönherr, Robert; Lamp, Benjamin; Schröder, Kristin; Duden, Rainer; Rümenapf, Tillmann H.

    2014-01-01

    Nonstructural protein 5A (NS5A) of bovine viral diarrhea virus (BVDV) is a hydrophilic phosphoprotein with RNA binding activity and a critical component of the viral replicase. In silico analysis suggests that NS5A encompasses three domains interconnected by two low-complexity sequences (LCSs). While domain I harbors two functional determinants, an N-terminal amphipathic helix important for membrane association, and a Zn-binding site essential for RNA replication, the structure and function of the C-terminal half of NS5A are still ill defined. In this study, we introduced a panel of 10 amino acid deletions covering the C-terminal half of NS5A. In the context of a highly efficient monocistronic replicon, deletions in LCS I and the N-terminal part of domain II, as well as in domain III, were tolerated with regard to RNA replication. When introduced into a bicistronic replicon, only deletions in LCS I and the N-terminal part of domain II were tolerated. In the context of the viral full-length genome, these mutations allowed residual virion morphogenesis. Based on these data, a functional monocistronic BVDV replicon coding for an NS5A variant with an insertion of the fluorescent protein mCherry was constructed. Live cell imaging demonstrated that a fraction of NS5A-mCherry localizes to the surface of lipid droplets. Taken together, this study provides novel insights into the functions of BVDV NS5A. Moreover, we established the first pestiviral replicon expressing fluorescent NS5A-mCherry to directly visualize functional viral replication complexes by live cell imaging. PMID:24131714

  2. Modulation transfer function analysis of Kelvin wakes and ambient wave images

    NASA Astrophysics Data System (ADS)

    Lyzenga, D.; Malinas, N.; Burns, J.

    1991-09-01

    Synthetic aperture radar (SAR) images collected during a 1989 surface ship wake experiment are analyzed using a linear imaging model which includes contributions due to velocity bunching, tilt modulation and hydrodynamic modulation as well as azimuth falloff and coherent speckle effects. This model adequately predicts the overall shape of the image spectrum for ambient waves as observed from three different look directions, although there are some discrepancies for range-traveling waves which are attributed to uncertainties in the tilt and hydrodynamic modulation. Inversion of the model to yield estimates of the Kelvin wake and ambient wave heights appears to be successful, although the results are sensitive to the value assumed for the surface decorrelation time.

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

    NASA Astrophysics Data System (ADS)

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

    2007-02-01

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

  4. Functional magnetic resonance imaging during emotion recognition in social anxiety disorder: an activation likelihood meta-analysis

    PubMed Central

    Hattingh, Coenraad J.; Ipser, J.; Tromp, S. A.; Syal, S.; Lochner, C.; Brooks, S. J.; Stein, D. J.

    2012-01-01

    Background: Social anxiety disorder (SAD) is characterized by abnormal fear and anxiety in social situations. Functional magnetic resonance imaging (fMRI) is a brain imaging technique that can be used to demonstrate neural activation to emotionally salient stimuli. However, no attempt has yet been made to statistically collate fMRI studies of brain activation, using the activation likelihood-estimate (ALE) technique, in response to emotion recognition tasks in individuals with SAD. Methods: A systematic search of fMRI studies of neural responses to socially emotive cues in SAD was undertaken. ALE meta-analysis, a voxel-based meta-analytic technique, was used to estimate the most significant activations during emotional recognition. Results: Seven studies were eligible for inclusion in the meta-analysis, constituting a total of 91 subjects with SAD, and 93 healthy controls. The most significant areas of activation during emotional vs. neutral stimuli in individuals with SAD compared to controls were: bilateral amygdala, left medial temporal lobe encompassing the entorhinal cortex, left medial aspect of the inferior temporal lobe encompassing perirhinal cortex and parahippocampus, right anterior cingulate, right globus pallidus, and distal tip of right postcentral gyrus. Conclusion: The results are consistent with neuroanatomic models of the role of the amygdala in fear conditioning, and the importance of the limbic circuitry in mediating anxiety symptoms. PMID:23335892

  5. Statistical image analysis of longitudinal RAVENS images

    PubMed Central

    Lee, Seonjoo; Zipunnikov, Vadim; Reich, Daniel S.; Pham, Dzung L.

    2015-01-01

    Regional analysis of volumes examined in normalized space (RAVENS) are transformation images used in the study of brain morphometry. In this paper, RAVENS images are analyzed using a longitudinal variant of voxel-based morphometry (VBM) and longitudinal functional principal component analysis (LFPCA) for high-dimensional images. We demonstrate that the latter overcomes the limitations of standard longitudinal VBM analyses, which does not separate registration errors from other longitudinal changes and baseline patterns. This is especially important in contexts where longitudinal changes are only a small fraction of the overall observed variability, which is typical in normal aging and many chronic diseases. Our simulation study shows that LFPCA effectively separates registration error from baseline and longitudinal signals of interest by decomposing RAVENS images measured at multiple visits into three components: a subject-specific imaging random intercept that quantifies the cross-sectional variability, a subject-specific imaging slope that quantifies the irreversible changes over multiple visits, and a subject-visit specific imaging deviation. We describe strategies to identify baseline/longitudinal variation and registration errors combined with covariates of interest. Our analysis suggests that specific regional brain atrophy and ventricular enlargement are associated with multiple sclerosis (MS) disease progression. PMID:26539071

  6. 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. PMID:24889021

  7. 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

  8. Image-analysis library

    NASA Technical Reports Server (NTRS)

    1980-01-01

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

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

    PubMed

    Haghtalab, Mohammad; Faraji-Dana, Reza

    2012-05-01

    Analysis and optimization of diffraction effects in nanolithography through multilayered media with a fast and accurate field-theoretical approach is presented. The scattered field through an arbitrary two-dimensional (2D) mask pattern in multilayered media illuminated by a TM-polarized incident wave is determined by using an electric field integral equation formulation. In this formulation the electric field is represented in terms of complex images Green's functions. The method of moments is then employed to solve the resulting integral equation. In this way an accurate and computationally efficient approximate method is achieved. The accuracy of the proposed method is vindicated through comparison with direct numerical integration results. Moreover, the comparison is made between the results obtained by the proposed method and those obtained by the full-wave finite-element method. The ray tracing method is combined with the proposed method to describe the imaging process in the lithography. The simulated annealing algorithm is then employed to solve the inverse problem, i.e., to design an optimized mask pattern to improve the resolution. Two binary mask patterns under normal incident coherent illumination are designed by this method, where it is shown that the subresolution features improve the critical dimension significantly. PMID:22561933

  10. 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

  11. 4-D Cardiac MR Image Analysis: Left and Right Ventricular Morphology and Function

    PubMed Central

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

    2010-01-01

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

  12. Electronic image analysis

    NASA Astrophysics Data System (ADS)

    Gahm, J.; Grosskopf, R.; Jaeger, H.; Trautwein, F.

    1980-12-01

    An electronic system for image analysis was developed on the basis of low and medium cost integrated circuits. The printed circuit boards were designed, using the principles of modern digital electronics and data processing. The system consists of modules for automatic, semiautomatic and visual image analysis. They can be used for microscopical and macroscopical observations. Photographs can be evaluated, too. The automatic version is controlled by software modules adapted to various applications. The result is a system for image analysis suitable for many different measurement problems. The features contained in large image areas can be measured. For automatic routine analysis controlled by processing calculators the necessary software and hardware modules are available.

  13. 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

  14. Basics of image analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. 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.

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

    PubMed Central

    Martin, Anna; Schurz, Matthias; Kronbichler, Martin

    2015-01-01

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

  17. A method of basal forebrain anatomical standardization for functional image analysis.

    PubMed

    Buchsbaum, M S; Fallon, J H; Wei, T C; Guich, S; Spiegel-Cohen, J; Hamilton, M; Tang, C

    1998-12-14

    Functional as well as structural assessment of the basal forebrain has mostly focused on the dorsal caudate and putamen in axial slices where they are easily outlined or their centers located with stereotaxic methods. The more ventral extent of the basal forebrain, where the irregular form and indistinct boundaries of the nucleus accumbens and substantia innominata are difficult to trace and where the brain's ventral surface may contribute partial volume artifacts to measurement, has been less studied. We present a method based on coronal sections, landmarks placed on clearly visible anchor points, and the computational technique of thin-plate spline warping which allows the alignment of groups of individuals to common coordinates for pixel-by-pixel statistical mapping. The reliability of the landmarks across independent raters yields a median absolute difference of 1.3-1.6 mm. The validity of the method is confirmed by variance maps which reveal significant decreases in variance over spindle and bounding box alignment. PMID:10710168

  18. 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

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

    PubMed

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

    2015-10-01

    Gestures play an important role in face-to-face communication and have been increasingly studied via functional magnetic resonance imaging. Although a large amount of data has been provided to describe the neural substrates of gesture comprehension, these findings have never been quantitatively summarized and the conclusion is still unclear. This activation likelihood estimation meta-analysis investigated the brain networks underpinning gesture comprehension while considering the impact of gesture type (co-speech gestures vs. speech-independent gestures) and task demand (implicit vs. explicit) on the brain activation of gesture comprehension. The meta-analysis of 31 papers showed that as hand actions, gestures involve a perceptual-motor network important for action recognition. As meaningful symbols, gestures involve a semantic network for conceptual processing. Finally, during face-to-face interactions, gestures involve a network for social emotive processes. Our finding also indicated that gesture type and task demand influence the involvement of the brain networks during gesture comprehension. The results highlight the complexity of gesture comprehension, and suggest that future research is necessary to clarify the dynamic interactions among these networks. PMID:26271719

  20. 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

  1. Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

    PubMed Central

    Phillips, Jeffrey S.; Greenberg, Adam S.; Pyles, John A.; Pathak, Sudhir K.; Behrmann, Marlene; Schneider, Walter; Tarr, Michael J.

    2012-01-01

    The study of complex computational systems is facilitated by network maps, such as circuit diagrams. Such mapping is particularly informative when studying the brain, as the functional role that a brain area fulfills may be largely defined by its connections to other brain areas. In this report, we describe a novel, non-invasive approach for relating brain structure and function using magnetic resonance imaging (MRI). This approach, a combination of structural imaging of long-range fiber connections and functional imaging data, is illustrated in two distinct cognitive domains, visual attention and face perception. Structural imaging is performed with diffusion-weighted imaging (DWI) and fiber tractography, which track the diffusion of water molecules along white-matter fiber tracts in the brain (Figure 1). By visualizing these fiber tracts, we are able to investigate the long-range connective architecture of the brain. The results compare favorably with one of the most widely-used techniques in DWI, diffusion tensor imaging (DTI). DTI is unable to resolve complex configurations of fiber tracts, limiting its utility for constructing detailed, anatomically-informed models of brain function. In contrast, our analyses reproduce known neuroanatomy with precision and accuracy. This advantage is partly due to data acquisition procedures: while many DTI protocols measure diffusion in a small number of directions (e.g., 6 or 12), we employ a diffusion spectrum imaging (DSI)1, 2 protocol which assesses diffusion in 257 directions and at a range of magnetic gradient strengths. Moreover, DSI data allow us to use more sophisticated methods for reconstructing acquired data. In two experiments (visual attention and face perception), tractography reveals that co-active areas of the human brain are anatomically connected, supporting extant hypotheses that they form functional networks. DWI allows us to create a "circuit diagram" and reproduce it on an individual-subject basis, for

  2. 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

  3. 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

  4. Connectivity Analysis and Feature Classification in Attention Deficit Hyperactivity Disorder Sub-Types: A Task Functional Magnetic Resonance Imaging Study.

    PubMed

    Park, Bo-Yong; Kim, Mansu; Seo, Jongbum; Lee, Jong-Min; Park, Hyunjin

    2016-05-01

    Attention deficit hyperactivity disorder (ADHD) is a pervasive neuropsychiatric disorder. Patients with different ADHD subtypes show different behaviors under different stimuli and thus might require differential approaches to treatment. This study explores connectivity differences between ADHD subtypes and attempts to classify these subtypes based on neuroimaging features. A total of 34 patients (13 ADHD-IA and 21 ADHD-C subtypes) underwent functional magnetic resonance imaging (fMRI) with six task paradigms. Connectivity differences between ADHD subtypes were assessed for the whole brain in each task paradigm. Connectivity measures of the identified regions were used as features for the support vector machine classifier to distinguish between ADHD subtypes. The effectiveness of connectivity measures of the regions were tested by predicting ADHD-related Diagnostic and Statistical Manual of Mental Disorders (DSM) scores. Significant connectivity differences between ADHD subtypes were identified mainly in the frontal, cingulate, and parietal cortices and partially in the temporal, occipital cortices and cerebellum. Classifier accuracy for distinguishing between ADHD subtypes was 91.18 % for both gambling punishment and emotion task paradigms. Linear prediction under the two task paradigms showed significant correlation with DSM hyperactive/impulsive score. Our study identified important brain regions from connectivity analysis based on an fMRI paradigm using gambling punishment and emotion task paradigms. The regions and associated connectivity measures could serve as features to distinguish between ADHD subtypes. PMID:26602102

  5. Where in the brain is nonliteral language? A coordinate-based meta-analysis of functional magnetic resonance imaging studies.

    PubMed

    Rapp, Alexander M; Mutschler, Dorothee E; Erb, Michael

    2012-10-15

    An increasing number of studies have investigated non-literal language, including metaphors, idioms, metonymy, or irony, with functional magnetic resonance imaging (fMRI). However, key questions regarding its neuroanatomy remain controversial. In this work, we used coordinate-based activation-likelihood estimations to merge available fMRI data on non-literal language. A literature search identified 38 fMRI studies on non-literal language (24 metaphor studies, 14 non-salient stimuli studies, 7 idiom studies, 8 irony studies, and 1 metonymy study). Twenty-eight studies with direct comparisons of non-literal and literal studies were included in the main meta-analysis. Sub-analyses for metaphors, idioms, irony, salient metaphors, and non-salient metaphors as well as studies on sentence level were conducted. Studies reported 409 activation foci, of which 129 (32%) were in the right hemisphere. These meta-analyses indicate that a predominantly left lateralised network, including the left and right inferior frontal gyrus; the left, middle, and superior temporal gyrus; and medial prefrontal, superior frontal, cerebellar, parahippocampal, precentral, and inferior parietal regions, is important for non-literal expressions. PMID:22759997

  6. 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

  7. 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

  8. Anmap: Image and data analysis

    NASA Astrophysics Data System (ADS)

    Alexander, Paul; Waldram, Elizabeth; Titterington, David; Rees, Nick

    2014-11-01

    Anmap analyses and processes images and spectral data. Originally written for use in radio astronomy, much of its functionality is applicable to other disciplines; additional algorithms and analysis procedures allow direct use in, for example, NMR imaging and spectroscopy. Anmap emphasizes the analysis of data to extract quantitative results for comparison with theoretical models and/or other experimental data. To achieve this, Anmap provides a wide range of tools for analysis, fitting and modelling (including standard image and data processing algorithms). It also provides a powerful environment for users to develop their own analysis/processing tools either by combining existing algorithms and facilities with the very powerful command (scripting) language or by writing new routines in FORTRAN that integrate seamlessly with the rest of Anmap.

  9. Kinetic analysis in human brain of [11C](R)-rolipram, a positron emission tomographic radioligand to image phosphodiesterase 4: a retest study and use of an image-derived input function

    PubMed Central

    Zanotti-Fregonara, Paolo; Zoghbi, Sami S.; Liow, Jeih-San; Luong, Elise; Boellaard, Ronald; Gladding, Robert L.; Pike, Victor W.; Innis, Robert B.; Fujita, Masahiro

    2010-01-01

    [11C](R)-rolipram provides a measure of the density of phosphodiesterase 4 (PDE4) in brain, an enzyme that metabolizes cAMP. The aims of this study were to perform kinetic modeling of [11C](R)-rolipram in healthy humans using an arterial input function and to replace this arterial input in humans with an image-derived input function. Methods Twelve humans had two injections of [11C](R)-rolipram. An image-derived input function was obtained from the carotid arteries and four blood samples. The samples were used for partial volume correction and for estimating the parent concentration using HPLC analysis. Results An unconstrained two-compartment model and Logan analysis measured distribution volume VT, with good identifiability but with moderately high retest variability (15%). Similar results were obtained using the image input (ratio image/arterial VT = 1.00 ± 0.06). Conclusions Binding of [11C](R)-rolipram to PDE4 can be quantified in human brain using kinetic modeling and an arterial input function. Image input function from carotid arteries provides an equally accurate and reproducible method to quantify PDE4. PMID:21034834

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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

  15. Functional magnetic resonance imaging of the lung.

    PubMed

    Biederer, J; Heussel, C P; Puderbach, M; Wielpuetz, M O

    2014-02-01

    Beyond being a substitute for X-ray, computed tomography, and scintigraphy, magnetic resonance imaging (MRI) inherently combines morphologic and functional information more than any other technology. Lung perfusion: The most established method is first-pass contrast-enhanced imaging with bolus injection of gadolinium chelates and time-resolved gradient-echo (GRE) sequences covering the whole lung (1 volume/s). Images are evaluated visually or semiquantitatively, while absolute quantification remains challenging due to the nonlinear relation of T1-shortening and contrast material concentration. Noncontrast-enhanced perfusion imaging is still experimental, either based on arterial spin labeling or Fourier decomposition. The latter is used to separate high- and low-frequency oscillations of lung signal related to the effects of pulsatile blood flow. Lung ventilation: Using contrast-enhanced first-pass perfusion, lung ventilation deficits are indirectly identified by hypoxic vasoconstriction. More direct but still experimental approaches use either inhalation of pure oxygen, an aerosolized contrast agent, or hyperpolarized noble gases. Fourier decomposition MRI based on the low-frequency lung signal oscillation allows for visualization of ventilation without any contrast agent. Respiratory mechanics: Time-resolved series with high background signal such as GRE or steady-state free precession visualize the movement of chest wall, diaphragm, mediastinum, lung tissue, tracheal wall, and tumor. The assessment of volume changes allows drawing conclusions on regional ventilation. With this arsenal of functional imaging capabilities at high spatial and temporal resolution but without radiation burden, MRI will find its role in regional functional lung analysis and will therefore overcome the sensitivity of global lung function analysis for repeated short-term treatment monitoring. PMID:24481761

  16. Picosecond Imaging Circuit Analysis

    NASA Astrophysics Data System (ADS)

    Kash, Jeffrey A.

    1998-03-01

    With ever-increasing complexity, probing the internal operation of a silicon IC becomes more challenging. Present methods of internal probing are becoming obsolete. We have discovered that a very weak picosecond pulse of light is emitted by each FET in a CMOS circuit whenever the circuit changes logic state. This pulsed emission can be simultaneously imaged and time resolved, using a technique we have named Picosecond Imaging Circuit Analysis (PICA). With a suitable imaging detector, PICA allows time resolved measurement on thousands of devices simultaneously. Computer videos made from measurements on real IC's will be shown. These videos, along with a more quantitative evaluation of the light emission, permit the complete operation of an IC to be measured in a non-invasive way with picosecond time resolution.

  17. 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.

  18. 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

  19. 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.

  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. Structured functional principal component analysis.

    PubMed

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

    2015-03-01

    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

  2. Digital Image Analysis of Cereals

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  3. 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

  4. Radar image analysis utilizing junctive image metamorphosis

    NASA Astrophysics Data System (ADS)

    Krueger, Peter G.; Gouge, Sally B.; Gouge, Jim O.

    1998-09-01

    A feasibility study was initiated to investigate the ability of algorithms developed for medical sonogram image analysis, to be trained for extraction of cartographic information from synthetic aperture radar imagery. BioComputer Research Inc. has applied proprietary `junctive image metamorphosis' algorithms to cancer cell recognition and identification in ultrasound prostate images. These algorithms have been shown to support automatic radar image feature detection and identification. Training set images were used to develop determinants for representative point, line and area features, which were used on test images to identify and localize the features of interest. The software is computationally conservative; operating on a PC platform in real time. The algorithms are robust; having applicability to be trained for feature recognition on any digital imagery, not just those formed from reflected energy, such as sonograms and radar images. Applications include land mass characterization, feature identification, target recognition, and change detection.

  5. Altered sensorimotor activation patterns in idiopathic dystonia—an activation likelihood estimation meta‐analysis of functional brain imaging studies

    PubMed Central

    Herz, Damian M.; Haagensen, Brian N.; Lorentzen, Anne K.; Eickhoff, Simon B.; Siebner, Hartwig R.

    2015-01-01

    Abstract Dystonia is characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements or postures. Functional neuroimaging studies have yielded abnormal task‐related sensorimotor activation in dystonia, but the results appear to be rather variable across studies. Further, study size was usually small including different types of dystonia. Here we performed an activation likelihood estimation (ALE) meta‐analysis of functional neuroimaging studies in patients with primary dystonia to test for convergence of dystonia‐related alterations in task‐related activity across studies. Activation likelihood estimates were based on previously reported regional maxima of task‐related increases or decreases in dystonia patients compared to healthy controls. The meta‐analyses encompassed data from 179 patients with dystonia reported in 18 functional neuroimaging studies using a range of sensorimotor tasks. Patients with dystonia showed bilateral increases in task‐related activation in the parietal operculum and ventral postcentral gyrus as well as right middle temporal gyrus. Decreases in task‐related activation converged in left supplementary motor area and left postcentral gyrus, right superior temporal gyrus and dorsal midbrain. Apart from the midbrain cluster, all between‐group differences in task‐related activity were retrieved in a sub‐analysis including only the 14 studies on patients with focal dystonia. For focal dystonia, an additional cluster of increased sensorimotor activation emerged in the caudal cingulate motor zone. The results show that dystonia is consistently associated with abnormal somatosensory processing in the primary and secondary somatosensory cortex along with abnormal sensorimotor activation of mesial premotor and right lateral temporal cortex. Hum Brain Mapp 37:547–557, 2016. © 2015 Wiley Periodicals, Inc. PMID:26549606

  6. Altered sensorimotor activation patterns in idiopathic dystonia-an activation likelihood estimation meta-analysis of functional brain imaging studies.

    PubMed

    Løkkegaard, Annemette; Herz, Damian M; Haagensen, Brian N; Lorentzen, Anne K; Eickhoff, Simon B; Siebner, Hartwig R

    2016-02-01

    Dystonia is characterized by sustained or intermittent muscle contractions causing abnormal, often repetitive, movements or postures. Functional neuroimaging studies have yielded abnormal task-related sensorimotor activation in dystonia, but the results appear to be rather variable across studies. Further, study size was usually small including different types of dystonia. Here we performed an activation likelihood estimation (ALE) meta-analysis of functional neuroimaging studies in patients with primary dystonia to test for convergence of dystonia-related alterations in task-related activity across studies. Activation likelihood estimates were based on previously reported regional maxima of task-related increases or decreases in dystonia patients compared to healthy controls. The meta-analyses encompassed data from 179 patients with dystonia reported in 18 functional neuroimaging studies using a range of sensorimotor tasks. Patients with dystonia showed bilateral increases in task-related activation in the parietal operculum and ventral postcentral gyrus as well as right middle temporal gyrus. Decreases in task-related activation converged in left supplementary motor area and left postcentral gyrus, right superior temporal gyrus and dorsal midbrain. Apart from the midbrain cluster, all between-group differences in task-related activity were retrieved in a sub-analysis including only the 14 studies on patients with focal dystonia. For focal dystonia, an additional cluster of increased sensorimotor activation emerged in the caudal cingulate motor zone. The results show that dystonia is consistently associated with abnormal somatosensory processing in the primary and secondary somatosensory cortex along with abnormal sensorimotor activation of mesial premotor and right lateral temporal cortex. Hum Brain Mapp 37:547-557, 2016. © 2015 Wiley Periodicals, Inc. PMID:26549606

  7. 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

  8. 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

  9. Working Memory in Unaffected Relatives of Patients With Schizophrenia: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies.

    PubMed

    Zhang, Ruibin; Picchioni, Marco; Allen, Paul; Toulopoulou, Timothea

    2016-07-01

    Working memory deficits, a core cognitive feature of schizophrenia may arise from dysfunction in the frontal and parietal cortices. Numerous studies have also found abnormal neural activation during working memory tasks in patients' unaffected relatives. The aim of this study was to systematically identify and anatomically localize the evidence for those activation differences across all eligible studies. Fifteen functional magnetic resonance imaging (fMRI) manuscripts, containing 16 samples of 289 unaffected relatives of patients with schizophrenia, and 358 healthy controls were identified that met our inclusion criteria: (1) used a working memory task; and (2) reported standard space coordinates. Activation likelihood estimation (ALE) identified convergence across studies. Compared to healthy controls, patients' unaffected relatives showed decreases in neural activation in the right middle frontal gyrus (BA9), as well as right inferior frontal gyrus (BA44). Increased activation was seen in relatives in the right frontopolar (BA10), left inferior parietal lobe (BA40), and thalamus bilaterally. These results suggest that the familial risk of schizophrenia is expressed in changes in neural activation in the unaffected relatives in the cortical-subcortical working memory network that includes, but is not restricted to the middle prefrontal cortex. PMID:26738528

  10. 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

  11. 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.

  12. New Horizons for Imaging Lymphatic Function

    PubMed Central

    Sharma, Ruchi; Wendt, Juliet A.; Rasmussen, John C.; Adams, Kristen E.; Marshall, Milton V.; Sevick-Muraca, Eva M.

    2011-01-01

    In this review, we provide a comprehensive summary of noninvasive imaging modalities used clinically for the diagnosis of lymphatic diseases, new imaging agents for assessing lymphatic architecture and cancer status of lymph nodes, and emerging near-infrared (NIR) fluorescent optical imaging technologies and agents for functional lymphatic imaging. Given the promise of NIR optical imaging, we provide example results of functional lymphatic imaging in mice, swine, and humans, showing the ability of this technology to quantify lymph velocity and frequencies of propulsion resulting from the contractility of lymphatic structures. PMID:18519956

  13. Grid computing in image analysis

    PubMed Central

    2011-01-01

    Diagnostic surgical pathology or tissue–based diagnosis still remains the most reliable and specific diagnostic medical procedure. The development of whole slide scanners permits the creation of virtual slides and to work on so-called virtual microscopes. In addition to interactive work on virtual slides approaches have been reported that introduce automated virtual microscopy, which is composed of several tools focusing on quite different tasks. These include evaluation of image quality and image standardization, analysis of potential useful thresholds for object detection and identification (segmentation), dynamic segmentation procedures, adjustable magnification to optimize feature extraction, and texture analysis including image transformation and evaluation of elementary primitives. Grid technology seems to possess all features to efficiently target and control the specific tasks of image information and detection in order to obtain a detailed and accurate diagnosis. Grid technology is based upon so-called nodes that are linked together and share certain communication rules in using open standards. Their number and functionality can vary according to the needs of a specific user at a given point in time. When implementing automated virtual microscopy with Grid technology, all of the five different Grid functions have to be taken into account, namely 1) computation services, 2) data services, 3) application services, 4) information services, and 5) knowledge services. Although all mandatory tools of automated virtual microscopy can be implemented in a closed or standardized open system, Grid technology offers a new dimension to acquire, detect, classify, and distribute medical image information, and to assure quality in tissue–based diagnosis. PMID:21516880

  14. Imaging the Lithosphere-Asthenosphere Boundary Using Iterative Method of Receiver Function Analysis: A Synthetic Seismogram Approach

    NASA Astrophysics Data System (ADS)

    Maiti, T.; Eaton, D. W. S.; Liu, Q.; Sales de Andrade, E.

    2014-12-01

    Our study is based on the receiver-function (RF) analysis of a hypothetical regional geological model that extends from oceanic to thick cratonic lithosphere. RF techniques are used to study the interior of Earth. Teleseismic P waves are followed by a series of scattered waves, which occur due to P-to-S converted phases. The sequence of these scattered waves on a time series can be represented by receiver function (RF) for the station and may vary with the incidence angle and azimuth of the incoming P-wave. Here we use iterative deconvolution method to study receiver functions, which provides RF estimates with low noise levels. This method is based on least-squares minimization of the difference between the observed horizontal seismogram and a predicted signal generated by the convolution of an iterative spike train with the vertical-component of seismogram. The study is based on a hypothetical model (800x800x400km) on a mesh with 10 km grid spacing that is smoothly embedded within a standard global Earth model. Physical properties of the regional model match with prescribed surface heat-flow and geoid boundary conditions computed using an approach based on thermodynamics, mineral physics, and solid-Earth geophysics. The model also incorporates seismic anisotropy in the mantle beneath the hypothetical continent. A three dimensional model is computed that approximates the mantle flow around the hypothetical continental lithospheric keel. The anisotropy is computed from the flow model and is incorporated to the model. Synthetic seismograms are computed using SPECFEM3D_GLOBE, which provides full wave-equation modelling of seismic wave propagation incorporating material properties such as anisotropy, attenuation and fluid-solid interfaces. To ensure a realistic (non-ideal) azimuthal distribution, the event locations are based on a subset of a ten-year global catalog from 2001 to 2010 within the magnitude range from 6.0 to 7.0.

  15. Functional MRI Using Regularized Parallel Imaging Acquisition

    PubMed Central

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

    2013-01-01

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

  16. Functional Imaging for Prostate Cancer: Therapeutic Implications

    PubMed Central

    Aparici, Carina Mari; Seo, Youngho

    2012-01-01

    Functional radionuclide imaging modalities, now commonly combined with anatomical imaging modalities CT or MRI (SPECT/CT, PET/CT, and PET/MRI) are promising tools for the management of prostate cancer particularly for therapeutic implications. Sensitive detection capability of prostate cancer using these imaging modalities is one issue; however, the treatment of prostate cancer using the information that can be obtained from functional radionuclide imaging techniques is another challenging area. There are not many SPECT or PET radiotracers that can cover the full spectrum of the management of prostate cancer from initial detection, to staging, prognosis predictor, and all the way to treatment response assessment. However, when used appropriately, the information from functional radionuclide imaging improves, and sometimes significantly changes, the whole course of the cancer management. The limitations of using SPECT and PET radiotracers with regards to therapeutic implications are not so much different from their limitations solely for the task of detecting prostate cancer; however, the specific imaging target and how this target is reliably imaged by SPECT and PET can potentially make significant impact in the treatment of prostate cancer. Finally, while the localized prostate cancer is considered manageable, there is still significant need for improvement in noninvasive imaging of metastatic prostate cancer, in treatment guidance, and in response assessment from functional imaging including radionuclide-based techniques. In this review article, we present the rationale of using functional radionuclide imaging and the therapeutic implications for each of radionuclide imaging agent that have been studied in human subjects. PMID:22840598

  17. Estimating variability in functional images using a synthetic resampling approach

    SciTech Connect

    Maitra, R.; O`Sullivan, F.

    1996-12-31

    Functional imaging of biologic parameters like in vivo tissue metabolism is made possible by Positron Emission Tomography (PET). Many techniques, such as mixture analysis, have been suggested for extracting such images from dynamic sequences of reconstructed PET scans. Methods for assessing the variability in these functional images are of scientific interest. The nonlinearity of the methods used in the mixture analysis approach makes analytic formulae for estimating variability intractable. The usual resampling approach is infeasible because of the prohibitive computational effort in simulating a number of sinogram. datasets, applying image reconstruction, and generating parametric images for each replication. Here we introduce an approach that approximates the distribution of the reconstructed PET images by a Gaussian random field and generates synthetic realizations in the imaging domain. This eliminates the reconstruction steps in generating each simulated functional image and is therefore practical. Results of experiments done to evaluate the approach on a model one-dimensional problem are very encouraging. Post-processing of the estimated variances is seen to improve the accuracy of the estimation method. Mixture analysis is used to estimate functional images; however, the suggested approach is general enough to extend to other parametric imaging methods.

  18. Functional magnetic resonance imaging in disorders of consciousness: preliminary results of an innovative analysis of brain connectivity

    PubMed Central

    de Pasquale, Francesco; Caravasso, Chiara Falletta; Péran, Patrice; Catani, Sheila; Tuovinen, Noora; Sabatini, Umberto; Formisano, Rita

    2015-01-01

    Summary The aim of this preliminary study was to present a new approach for connectivity analysis in patients with severe acquired brain injury (ABI) that overcomes some of the difficulties created by anatomical abnormalities due to the brain injury. Using a data-driven approach, resting-state structural MRI (sMRI) and functional MRI (fMRI) data from three severe ABI patients – two with disorders of consciousness (DOC) and one who had recovered consciousness (non-DOC) – were integrated and analyzed. Parameters extracted from the distribution of the connectivity values, such as mean, standard deviation and skeweness, were considered. The distribution parameters estimated seem to provide an accurate multivariate classification of the considered cases that can be summarized as follows: connectivity in the severe ABI patients with DOC was on average lower than in the severe ABI non-DOC patient and healthy subjects. The dispersion of connectivity values of the severe ABI patients, non-DOC and DOC, was comparable, however the shape of the distribution was different in the non-DOC patient. Eventually, seed-based connectivity maps of the default mode network show a pattern of increasing disruption of this network from the healthy subjects to non-DOC and DOC patients. Consistent results are obtained using an ICA-based approach. PMID:26910178

  19. 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

  20. 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.…

  1. 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.

  2. 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

  3. 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

  4. Spreadsheet-like image analysis

    NASA Astrophysics Data System (ADS)

    Wilson, Paul

    1992-08-01

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

  5. Clinical applications of functional MR imaging.

    PubMed

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

    2013-05-01

    Functional magnetic resonance (fMR) imaging for neurosurgical planning has become the standard of care in centers where it is available. Although paradigms to measure eloquent cortices are not yet standardized, simple tasks elicit reliable maps for planning neurosurgical procedures. A patient-specific paradigm design will refine the usability of fMR imaging for prognostication and recovery of function. Certain pathologic conditions and technical issues limit the interpretation of fMR imaging maps in clinical use and should be considered carefully. However, fMR imaging for neurosurgical planning continues to provide insights into how the brain works and how it responds to pathologic insults. PMID:23642553

  6. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2008-03-01

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

  8. Spotlight-8 Image Analysis Software

    NASA Technical Reports Server (NTRS)

    Klimek, Robert; Wright, Ted

    2006-01-01

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

  9. Reliability of functional magnetic resonance imaging activation during working memory in a multi-site study: analysis from the North American Prodrome Longitudinal Study.

    PubMed

    Forsyth, Jennifer K; McEwen, Sarah C; Gee, Dylan G; Bearden, Carrie E; Addington, Jean; Goodyear, Brad; Cadenhead, Kristin S; Mirzakhanian, Heline; Cornblatt, Barbara A; Olvet, Doreen M; Mathalon, Daniel H; McGlashan, Thomas H; Perkins, Diana O; Belger, Aysenil; Seidman, Larry J; Thermenos, Heidi W; Tsuang, Ming T; van Erp, Theo G M; Walker, Elaine F; Hamann, Stephan; Woods, Scott W; Qiu, Maolin; Cannon, Tyrone D

    2014-08-15

    Multi-site neuroimaging studies offer an efficient means to study brain functioning in large samples of individuals with rare conditions; however, they present new challenges given that aggregating data across sites introduces additional variability into measures of interest. Assessing the reliability of brain activation across study sites and comparing statistical methods for pooling functional data are critical to ensuring the validity of aggregating data across sites. The current study used two samples of healthy individuals to assess the feasibility and reliability of aggregating multi-site functional magnetic resonance imaging (fMRI) data from a Sternberg-style verbal working memory task. Participants were recruited as part of the North American Prodrome Longitudinal Study (NAPLS), which comprises eight fMRI scanning sites across the United States and Canada. In the first study sample (n=8), one participant from each home site traveled to each of the sites and was scanned while completing the task on two consecutive days. Reliability was examined using generalizability theory. Results indicated that blood oxygen level-dependent (BOLD) signal was reproducible across sites and was highly reliable, or generalizable, across scanning sites and testing days for core working memory ROIs (generalizability ICCs=0.81 for left dorsolateral prefrontal cortex, 0.95 for left superior parietal cortex). In the second study sample (n=154), two statistical methods for aggregating fMRI data across sites for all healthy individuals recruited as control participants in the NAPLS study were compared. Control participants were scanned on one occasion at the site from which they were recruited. Results from the image-based meta-analysis (IBMA) method and mixed effects model with site covariance method both showed robust activation in expected regions (i.e. dorsolateral prefrontal cortex, anterior cingulate cortex, supplementary motor cortex, superior parietal cortex, inferior

  10. 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

  11. 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.

  12. In Vivo Performance of a Novel Fluorinated Magnetic Resonance Imaging Agent for Functional Analysis of Bile Acid Transport

    PubMed Central

    2015-01-01

    A novel trifluorinated cholic acid derivative, CA-lys-TFA, was designed and synthesized for use as a tool to measure bile acid transport noninvasively using magnetic resonance imaging (MRI). In the present study, the in vivo performance of CA-lys-TFA for measuring bile acid transport by MRI was investigated in mice. Gallbladder CA-lys-TFA content was quantified using MRI and liquid chromatography/tandem mass spectrometry. Results in wild-type (WT) C57BL/6J mice were compared to those in mice lacking expression of Asbt, the ileal bile acid transporter. 19F signals emanating from the gallbladders of WT mice 7 h after oral gavage with 150 mg/kg CA-lys-TFA were reproducibly detected by MRI. Asbt-deficient mice administered the same dose had undetectable 19F signals by MRI, and gallbladder bile CA-lys-TFA levels were 30-fold lower compared to WT animals. To our knowledge, this represents the first report of in vivo imaging of an orally absorbed drug using 19F MRI. Fluorinated bile acid analogues have potential as tools to measure and detect abnormal bile acid transport by MRI. PMID:24708306

  13. Functional imaging of the musculoskeletal system

    PubMed Central

    2015-01-01

    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

  14. 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.

  15. SPECT functional brain imaging. Technical considerations.

    PubMed

    Devous, M D

    1995-07-01

    The technical aspects of functional brain single-photon emission computed tomography (SPECT) imaging, referring primarily to the most common SPECT brain function measure--regional cerebral blood flow--are reviewed. SPECT images of regional cerebral blood flow are influenced by a number of factors unrelated to pathology, including tomographic quality, radiopharmaceuticals, environmental conditions at the time of radiotracer administration, characteristics of the subject (e.g., age, sex), image presentation, and image processing techniques. Modern SPECT scans yield excellent image quality, and instrumentation continues to improve. The armamentarium of regional cerebral blood flow and receptor radiopharmaceuticals is rapidly expanding. Standards regarding the environment for patient imaging and image presentation are emerging. However, there is still much to learn about the circumstances for performances and evaluation of SPECT functional brain imaging. Challenge tests, primarily established in cerebrovascular disease (i.e., the acetazolamide test), offer great promise in defining the extent and nature of disease, as well as predicting therapeutic responses. Clearly, SPECT brain imaging is a powerful clinical and research tool. However, SPECT will only achieve its full potential in the management of patients with cerebral pathology through close cooperation among members of the nuclear medicine, neurology, psychiatry, neurosurgery, and internal medicine specialties. PMID:7626833

  16. Hyperspectral image analysis. A tutorial.

    PubMed

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

    2015-10-01

    This tutorial aims at providing guidelines and practical tools to assist with the analysis of hyperspectral images. Topics like hyperspectral image acquisition, image pre-processing, multivariate exploratory analysis, hyperspectral image resolution, classification and final digital image processing will be exposed, and some guidelines given and discussed. Due to the broad character of current applications and the vast number of multivariate methods available, this paper has focused on an industrial chemical framework to explain, in a step-wise manner, how to develop a classification methodology to differentiate between several types of plastics by using Near infrared hyperspectral imaging and Partial Least Squares - Discriminant Analysis. Thus, the reader is guided through every single step and oriented in order to adapt those strategies to the user's case. PMID:26481986

  17. 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.

  18. 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. PMID:25450866

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

    PubMed Central

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

    2016-01-01

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

  20. 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.

  1. Functional cardiac imaging: positron emission tomography

    SciTech Connect

    Mullani, N.A.; Gould, K.L.

    1984-02-01

    Dynamic cardiovascular imaging plays a vital role in the diagnosis and treatment of cardiac disease by providing information about the function of the heart. During the past 30 years, cardiovascular imaging has evolved from the simple chest x-ray and fluoroscopy to such sophisticated techniques as invasive cardiac angiography and cinearteriography and, more recently, to noninvasive cardiac CT scanning, nuclear magnetic resonance, and positron emission tomography, which reflect more complex physiologic functions. As research tools, CT, NMR, and PET provide quantitative information on global as well as regional ventricular function, coronary artery stenosis, myocardial perfusion, glucose and fatty acid metabolism, or oxygen utilization, with little discomfort or risk to the patient. As imaging modalities become more sophisticated and more oriented toward clinical application, the prospect of routinely obtaining such functional information about the heart is becoming realistic. However, these advances are double-edged in that the interpretation of functional data is more complex than that of the anatomic imaging familiar to most physicians. They will require an enhanced understanding of the physiologic and biochemical processes, as well as of the instrumentation and techniques for analyzing the data. Of the new imaging modalities that provide functional information about the heart, PET is the most useful because it quantitates the regional distribution of radionuclides in vivo. Clinical applications, interpretation of data, and the impact of PET on our understanding of cardiac pathophysiology are discussed. 5 figures.

  2. 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

  3. Multimodal Imaging of Dynamic Functional Connectivity

    PubMed Central

    Tagliazucchi, Enzo; Laufs, Helmut

    2015-01-01

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

  4. 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.

  5. Functional Imaging in Hereditary Dystonia

    PubMed Central

    Carbon, Maren; Argyelan, Miklos; Eidelberg, David

    2015-01-01

    Background Impaired cortical inhibiton and maladaptive cortical plasticity are functional hallmarks of sporadic focal dystonias. Whether or not these mechanisms translate to generalized dystonias and whether these features reflect state or trait characteristics is a topic of research in hereditary dystonias. Methods We present a series of studies using a multitracer approach with positron emission tomography (PET) and diffusion tensor MRI (DTI) in the DYT1 and the DYT6 genotype. Results In these hereditary dystonias maladaptive motor cortical plasticity was present as a state characteristic. As a trait characteristic neuroplastic changes were also found in secondary motor cortices and in multimodal association regions. Consistent abnormalities of resting regional brain metabolism were additionally found in interconnected elements of cortico-striatal-pallido-thalamocortical (CSPTC) and related cerebellar-thalamo-cortical circuits. Changes in specific subsets of these regions have been found to relate to genotype, phenotype, or both. Thus, a penetrance-related metabolic network was characterized by increases in the pre-supplementary motor area (pre-SMA) and parietal association areas, associated with relative reductions in the cerebellum, brainstem, and ventral thalamus. By contrast, genotype-specific abnormalities were localized to the basal ganglia, SMA and cerebellum. In both genotypes, the striatal metabolic abnormalities were paralleled by genotype-specific reductions in D2 receptor availability. Moreover, DTI studies disclosed microstructural changes within CSPTC and related cerebellar pathways. These disruptions may represent the main intrinsic abnormality underlying cortical downstream effects, such as increased sensorimotor responsivity. Conclusions These studies are consistent with the view of primary torsion dystonia as a neurodevelopmental circuit disorder involving CSPTC and related cerebellar pathways. PMID:20590810

  6. funcLAB/G-service-oriented architecture for standards-based analysis of functional magnetic resonance imaging in HealthGrids.

    PubMed

    Erberich, Stephan G; Bhandekar, Manasee; Chervenak, Ann; Kesselman, Carl; Nelson, Marvin D

    2007-01-01

    Functional MRI is successfully being used in clinical and research applications including preoperative planning, language mapping, and outcome monitoring. However, clinical use of fMRI is less widespread due to its complexity of imaging, image workflow, post-processing, and lack of algorithmic standards hindering result comparability. As a consequence, wide-spread adoption of fMRI as clinical tool is low contributing to the uncertainty of community physicians how to integrate fMRI into practice. In addition, training of physicians with fMRI is in its infancy and requires clinical and technical understanding. Therefore, many institutions which perform fMRI have a team of basic researchers and physicians to perform fMRI as a routine imaging tool. In order to provide fMRI as an advanced diagnostic tool to the benefit of a larger patient population, image acquisition and image post-processing must be streamlined, standardized, and available at any institution which does not have these resources available. Here we describe a software architecture, the functional imaging laboratory (funcLAB/G), which addresses (i) standardized image processing using Statistical Parametric Mapping and (ii) its extension to secure sharing and availability for the community using standards-based Grid technology (Globus Toolkit). funcLAB/G carries the potential to overcome the limitations of fMRI in clinical use and thus makes standardized fMRI available to the broader healthcare enterprise utilizing the Internet and HealthGrid Web Services technology. PMID:17707204

  7. 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.

  8. Functional MR Imaging in Chest Malignancies.

    PubMed

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

    2016-02-01

    With recent advances in MR imaging, its application in the thorax has been feasible. The performance of both morphologic and functional techniques in the evaluation of thoracic malignances has improved not only differentiation from benign etiologies but also treatment monitoring based on a multiparametric approach. Several MR imaging-derived parameters have been described as potential biomarkers linked with prognosis and survival. Therefore, an integral approach with a nonradiating and noninvasive technique could be an optimal alternative for evaluating those patients. PMID:26613879

  9. 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

  10. 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

  11. 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

  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. 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…

  14. 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

  15. 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.

  16. Adolescent body image and psychosocial functioning.

    PubMed

    Davison, Tanya E; McCabe, Marita P

    2006-02-01

    Researchers have highlighted the significance of a poor body image in the development of dysfunctional eating but have systematically investigated few other outcomes. The authors examined the relationships between different aspects of body image and psychosocial functioning. Participants were 245 boys and 173 girls from Grades 8 and 9 (M age = 13.92 years, SD = 0.69 years). Respondents completed measures of physical attractiveness, body satisfaction, body image importance, body image behaviors, appearance comparison, social physique anxiety, self-esteem, depression, anxiety, and same-sex and opposite-sex relations. Whereas girls tended to report a more negative body image than did boys, the relevance of body image to self-esteem was similar for boys and girls. Concern about others' evaluation of their bodies was especially important in understanding low female self-esteem, whereas for boys, ratings of general attractiveness most strongly predicted self-esteem. The authors found a negative body image to be unrelated to symptoms of negative affect but to be strongly associated with poor opposite-sex peer relationships, especially among boys. A negative body image also affected same-sex relations among girls. PMID:16480119

  17. 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.

  18. Confocal scanning laser microscopy with complementary 3D image analysis allows quantitative studies of functional state of ionoregulatory cells in the Nile tilapia (Oreochromis niloticus) following salinity challenge.

    PubMed

    Fridman, Sophie; Rana, Krishen J; Bron, James E

    2013-04-01

    The development of a novel three-dimensional image analysis technique of stacks generated by confocal laser scanning microscopy is described allowing visualization of mitochondria-rich cells (MRCs) in the seawater-adapted Nile tilapia in relation to their spatial location. This method permits the assessment and classification of both active and nonactive MRCs based on the distance of the top of the immunopositive cell from the epithelial surface. In addition, this technique offers the potential for informative and quantitative studies, for example, densitometric and morphometric measurements based on MRC functional state. Confocal scanning laser microscopy used with triple staining whole-mount immunohistochemistry was used to detect integumental MRCs in the yolk-sac larvae tail of the Nile tilapia following transfer from freshwater to elevated salinities, that is, 12.5 and 20 ppt. Mean active MRC volume was always significantly larger and displayed a greater staining intensity (GLM; P<0.05) than nonactive MRCs. Following transfer, the percentage of active MRCs was seen to increase as did MRC volume (GLM; P<0.05). PMID:23390074

  19. Functional and Dysfunctional Sensorimotor Anatomy and Imaging.

    PubMed

    Ulmer, John L; Klein, Andrew P; Mark, Leighton P; Tuna, Ibrahim; Agarwal, Mohit; DeYoe, Edgar

    2015-06-01

    The sensorimotor system of the human brain and body is fundamental only in its central role in our daily lives. On further examination, it is a system with intricate and complex anatomical, physiological, and functional relationships. Sensorimotor areas including primary sensorimotor, premotor, supplementary motor, and higher order somatosensory cortices are critical for function and can be localized at routine neuroimaging with a familiarity of sulcal and gyral landmarks. Likewise, a thorough understanding of the functions and dysfunctions of these areas can empower the neuroradiologist and lead to superior imaging search patterns, diagnostic considerations, and patient care recommendations in daily clinical practice. Presurgical functional brain mapping of the sensorimotor system may be necessary in scenarios with distortion of anatomical landmarks, multiplanar localization, homunculus localization, congenital brain anomalies, informing diffusion tensor imaging interpretations, and localizing nonvisible targets. PMID:26233857

  20. Functional-metabolic imaging of neuroblastoma.

    PubMed

    Sharp, S E; Parisi, M T; Gelfand, M J; Yanik, G A; Shulkin, B L

    2013-03-01

    Neuroblastoma is the third most common malignant solid tumor of childhood. It originates from primitive neural crest cells of the sympathetic nervous system. Many imaging procedures help guide therapy and predict outcomes. Anatomic imaging methods, such as CT and MRI, are most useful for evaluation of the primary tumor mass and nearby involved lymph nodes. Functional imaging tracers, such as [123I]MIBG, [18F]FDG, and [99mTc]MDP, are used to assess the extent of disease and to search for distant metastases. [123I]MIBG is the principal functional imaging tracer for the detection and monitoring of neuroblastoma. [18F]FDG PET/CT is an alternative that is valuable in tumors with poor or no MIBG-uptake. [99mTc]MDP bone scans may be useful to assess cortical bone metastases. This article will review the use of [123I]MIBG and other functional imaging agents for the management of patients with neuroblastoma. PMID:23474631

  1. 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.

  2. 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. PMID:26342210

  3. Image analysis and quantitative morphology.

    PubMed

    Mandarim-de-Lacerda, Carlos Alberto; Fernandes-Santos, Caroline; Aguila, Marcia Barbosa

    2010-01-01

    Quantitative studies are increasingly found in the literature, particularly in the fields of development/evolution, pathology, and neurosciences. Image digitalization converts tissue images into a numeric form by dividing them into very small regions termed picture elements or pixels. Image analysis allows automatic morphometry of digitalized images, and stereology aims to understand the structural inner three-dimensional arrangement based on the analysis of slices showing two-dimensional information. To quantify morphological structures in an unbiased and reproducible manner, appropriate isotropic and uniform random sampling of sections, and updated stereological tools are needed. Through the correct use of stereology, a quantitative study can be performed with little effort; efficiency in stereology means as little counting as possible (little work), low cost (section preparation), but still good accuracy. This short text provides a background guide for non-expert morphologists. PMID:19960334

  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. 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.

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

    PubMed

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

    2009-07-01

    The Retinal Function Imager (RFI; Optical Imaging, Rehovot, Israel) is a unique, noninvasive multiparameter functional imaging instrument that directly measures hemodynamic parameters such as retinal blood-flow velocity, oximetric state, and metabolic responses to photic activation. In addition, it allows capillary perfusion mapping without any contrast agent. These parameters of retinal function are degraded by retinal abnormalities. This review delineates the development of these parameters and demonstrates their clinical applicability for noninvasive detection of retinal function in several modalities. The results suggest multiple clinical applications for early diagnosis of retinal diseases and possible critical guidance of their treatment. PMID:19763751

  8. 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

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

    NASA Astrophysics Data System (ADS)

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

    2003-05-01

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

  10. Advances in multimodality molecular imaging of bone structure and function

    PubMed Central

    Lambers, Floor M; Kuhn, Gisela; Müller, Ralph

    2012-01-01

    The skeleton is important to the body as a source of minerals and blood cells and provides a structural framework for strength, mobility and the protection of organs. Bone diseases and disorders can have deteriorating effects on the skeleton, but the biological processes underlying anatomical changes in bone diseases occurring in vivo are not well understood, mostly due to the lack of appropriate analysis techniques. Therefore, there is ongoing research in the development of novel in vivo imaging techniques and molecular markers that might help to gain more knowledge of these pathological pathways in animal models and patients. This perspective provides an overview of the latest developments in molecular imaging applied to bone. It emphasizes that multimodality imaging, the combination of multiple imaging techniques encompassing different image modalities, enhances the interpretability of data, and is imperative for the understanding of the biological processes and the associated changes in bone structure and function relationships in vivo. PMID:27127622

  11. Modulation transfer function measurement technique for image sensor arrays

    NASA Astrophysics Data System (ADS)

    Jin, Hui; Jiang, Huilin; Zhang, XiaoHui

    2010-08-01

    A new technique is demonstrated for measurement of modulation transfer function (MTF) on image sensor arrays. Fourier analysis of a low frequency bar target pattern is used to extract MTF at odd harmonics of a target pattern frequency up to and beyond Nyquist. The technique is particularly useful for linear image arrays (either conventional linescan or time-delay- integration devices) where conventional slanted-edge technique is not always applicable. The technique is well suited to simple implementation and can provide live presentation of the MTF curve, which helps to ensure optimal alignment conditions are achieved. Detailed analysis of the technique and demonstration of experimental results are presented.

  12. 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

  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. Imaging the genetics of executive function.

    PubMed

    Greene, Ciara M; Braet, Wouter; Johnson, Katherine A; Bellgrove, Mark A

    2008-09-01

    Recent advances in neuroimaging technologies have allowed ever more detailed studies of the human brain. The combination of neuroimaging techniques with genetics may provide a more sensitive measure of the influence of genetic variants on cognitive function than behavioural measures alone. Here we present a review of functional magnetic resonance imaging (fMRI) studies of genetic links to executive functions, focusing on sustained attention, working memory and response inhibition. In addition to studies in the normal population, we also address findings from three clinical populations: schizophrenia, ADHD and autism spectrum disorders. While the findings in the populations studied do not always converge, they all point to the usefulness of neuroimaging techniques such as fMRI as potential endophenotypes for parsing the genetic aetiology of executive function. PMID:18178303

  15. 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.

  16. 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

  17. Promise of new imaging technologies for assessing ovarian function

    PubMed Central

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

    2010-01-01

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

  18. Multiscale likelihood analysis and image reconstruction

    NASA Astrophysics Data System (ADS)

    Willett, Rebecca M.; Nowak, Robert D.

    2003-11-01

    The nonparametric multiscale polynomial and platelet methods presented here are powerful new tools for signal and image denoising and reconstruction. Unlike traditional wavelet-based multiscale methods, these methods are both well suited to processing Poisson or multinomial data and capable of preserving image edges. At the heart of these new methods lie multiscale signal decompositions based on polynomials in one dimension and multiscale image decompositions based on what the authors call platelets in two dimensions. Platelets are localized functions at various positions, scales and orientations that can produce highly accurate, piecewise linear approximations to images consisting of smooth regions separated by smooth boundaries. Polynomial and platelet-based maximum penalized likelihood methods for signal and image analysis are both tractable and computationally efficient. Polynomial methods offer near minimax convergence rates for broad classes of functions including Besov spaces. Upper bounds on the estimation error are derived using an information-theoretic risk bound based on squared Hellinger loss. Simulations establish the practical effectiveness of these methods in applications such as density estimation, medical imaging, and astronomy.

  19. 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,…

  20. Function Analysis and Decomposistion using Function Analysis Systems Technique

    SciTech Connect

    J. R. Wixson

    1999-06-01

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

  1. Function Analysis and Decomposistion using Function Analysis Systems Technique

    SciTech Connect

    Wixson, James Robert

    1999-06-01

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

  2. 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.

  3. 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

  4. 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

  5. A computational image analysis glossary for biologists.

    PubMed

    Roeder, Adrienne H K; Cunha, Alexandre; Burl, Michael C; Meyerowitz, Elliot M

    2012-09-01

    Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies. PMID:22872081

  6. 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

  7. 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

  8. Physiological basis and image processing in functional magnetic resonance imaging: Neuronal and motor activity in brain

    PubMed Central

    Sharma, Rakesh; Sharma, Avdhesh

    2004-01-01

    Functional magnetic resonance imaging (fMRI) is recently developing as imaging modality used for mapping hemodynamics of neuronal and motor event related tissue blood oxygen level dependence (BOLD) in terms of brain activation. Image processing is performed by segmentation and registration methods. Segmentation algorithms provide brain surface-based analysis, automated anatomical labeling of cortical fields in magnetic resonance data sets based on oxygen metabolic state. Registration algorithms provide geometric features using two or more imaging modalities to assure clinically useful neuronal and motor information of brain activation. This review article summarizes the physiological basis of fMRI signal, its origin, contrast enhancement, physical factors, anatomical labeling by segmentation, registration approaches with examples of visual and motor activity in brain. Latest developments are reviewed for clinical applications of fMRI along with other different neurophysiological and imaging modalities. PMID:15125779

  9. 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

  10. Multiresolution simulated annealing for brain image analysis

    NASA Astrophysics Data System (ADS)

    Loncaric, Sven; Majcenic, Zoran

    1999-05-01

    Analysis of biomedical images is an important step in quantification of various diseases such as human spontaneous intracerebral brain hemorrhage (ICH). In particular, the study of outcome in patients having ICH requires measurements of various ICH parameters such as hemorrhage volume and their change over time. A multiresolution probabilistic approach for segmentation of CT head images is presented in this work. This method views the segmentation problem as a pixel labeling problem. In this application the labels are: background, skull, brain tissue, and ICH. The proposed method is based on the Maximum A-Posteriori (MAP) estimation of the unknown pixel labels. The MAP method maximizes the a-posterior probability of segmented image given the observed (input) image. Markov random field (MRF) model has been used for the posterior distribution. The MAP estimation of the segmented image has been determined using the simulated annealing (SA) algorithm. The SA algorithm is used to minimize the energy function associated with MRF posterior distribution function. A multiresolution SA (MSA) has been developed to speed up the annealing process. MSA is presented in detail in this work. A knowledge-based classification based on the brightness, size, shape and relative position toward other regions is performed at the end of the procedure. The regions are identified as background, skull, brain, ICH and calcifications.

  11. 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.

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

    PubMed

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

    2016-05-01

    Imaging by Raman spectroscopy enables unparalleled label-free insights into cell and tissue composition at the molecular level. With established approaches limited to single image analysis, there are currently no general guidelines or consensus on how to quantify biochemical components across multiple Raman images. Here, we describe a broadly applicable methodology for the combination of multiple Raman images into a single image for analysis. This is achieved by removing image specific background interference, unfolding the series of Raman images into a single dataset, and normalisation of each Raman spectrum to render comparable Raman images. Multivariate image analysis is finally applied to derive the contributing 'pure' biochemical spectra for relative quantification. We present our methodology using four independently measured Raman images of control cells and four images of cells treated with strontium ions from substituted bioactive glass. We show that the relative biochemical distribution per area of the cells can be quantified. In addition, using k-means clustering, we are able to discriminate between the two cell types over multiple Raman images. This study shows a streamlined quantitative multi-image analysis tool for improving cell/tissue characterisation and opens new avenues in biomedical Raman spectroscopic imaging. PMID:26833935

  13. A design of novel type superconducting magnet for super-high field functional magnetic resonance imaging by using the harmonic analysis method of magnetic vector potentials

    NASA Astrophysics Data System (ADS)

    Zu, Dong-Lin; Guo, Hua; Song, Xiao-Yu; Bao, Shang-Lian

    2002-10-01

    The approach of expanding the magnetic scalar potential in a series of Legendre polynomials is suitable for designing a conventional superconducting magnetic resonance imaging magnet of distributed solenoidal configuration. Whereas the approach of expanding the magnetic vector potential in associated Legendre harmonics is suitable for designing a single-solenoid magnet that has multiple tiers, in which each tier may have multiple layers with different winding lengths. A set of three equations to suppress some of the lowest higher-order harmonics is found. As an example, a 4T single-solenoid magnetic resonance imaging magnet with 4×6 layers of superconducting wires is designed. The degree of homogeneity in the 0.5m diameter sphere volume is better than 5.8 ppm. The same degree of homogeneity is retained after optimal integralization of turns in each correction layer. The ratio Bm/B0 in the single-solenoid magnet is 30% lower than that in the conventional six-solenoid magnet. This tolerates higher rated superconducting current in the coil. The Lorentz force of the coil in the single-solenoid system is also much lower than in the six-solenoid system. This novel type of magnet possesses significant advantage over conventional magnets, especially when used as a super-high field functional magnetic resonance imaging magnet.

  14. Imaging Brain Dynamics Using Independent Component Analysis

    PubMed Central

    Jung, Tzyy-Ping; Makeig, Scott; McKeown, Martin J.; Bell, Anthony J.; Lee, Te-Won; Sejnowski, Terrence J.

    2010-01-01

    The analysis of electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings is important both for basic brain research and for medical diagnosis and treatment. Independent component analysis (ICA) is an effective method for removing artifacts and separating sources of the brain signals from these recordings. A similar approach is proving useful for analyzing functional magnetic resonance brain imaging (fMRI) data. In this paper, we outline the assumptions underlying ICA and demonstrate its application to a variety of electrical and hemodynamic recordings from the human brain. PMID:20824156

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. Breast tomosynthesis imaging configuration analysis.

    PubMed

    Rayford, Cleveland E; Zhou, Weihua; Chen, Ying

    2013-01-01

    Traditional two-dimensional (2D) X-ray mammography is the most commonly used method for breast cancer diagnosis. Recently, a three-dimensional (3D) Digital Breast Tomosynthesis (DBT) system has been invented, which is likely to challenge the current mammography technology. The DBT system provides stunning 3D information, giving physicians increased detail of anatomical information, while reducing the chance of false negative screening. In this research, two reconstruction algorithms, Back Projection (BP) and Shift-And-Add (SAA), were used to investigate and compare View Angle (VA) and the number of projection images (N) with parallel imaging configurations. In addition, in order to better determine which method displayed better-quality imaging, Modulation Transfer Function (MTF) analyses were conducted with both algorithms, ultimately producing results which improve upon better breast cancer detection. Research studies find evidence that early detection of the disease is the best way to conquer breast cancer, and earlier detection results in the increase of life span for the affected person. PMID:23900440

  20. 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

  1. Shannon information and ROC analysis in imaging.

    PubMed

    Clarkson, Eric; Cushing, Johnathan B

    2015-07-01

    Shannon information (SI) and the ideal-observer receiver operating characteristic (ROC) curve are two different methods for analyzing the performance of an imaging system for a binary classification task, such as the detection of a variable signal embedded within a random background. In this work we describe a new ROC curve, the Shannon information receiver operator curve (SIROC), that is derived from the SI expression for a binary classification task. We then show that the ideal-observer ROC curve and the SIROC have many properties in common, and are equivalent descriptions of the optimal performance of an observer on the task. This equivalence is described mathematically by an integral transform that maps the ideal-observer ROC curve onto the SIROC. This then leads to an integral transform relating the minimum probability of error, as a function of the odds against a signal, to the conditional entropy, as a function of the same variable. This last relation then gives us the complete mathematical equivalence between ideal-observer ROC analysis and SI analysis of the classification task for a given imaging system. We also find that there is a close relationship between the area under the ideal-observer ROC curve, which is often used as a figure of merit for imaging systems and the area under the SIROC. Finally, we show that the relationships between the two curves result in new inequalities relating SI to ROC quantities for the ideal observer. PMID:26367158

  2. Neural network ultrasound image analysis

    NASA Astrophysics Data System (ADS)

    Schneider, Alexander C.; Brown, David G.; Pastel, Mary S.

    1993-09-01

    Neural network based analysis of ultrasound image data was carried out on liver scans of normal subjects and those diagnosed with diffuse liver disease. In a previous study, ultrasound images from a group of normal volunteers, Gaucher's disease patients, and hepatitis patients were obtained by Garra et al., who used classical statistical methods to distinguish from among these three classes. In the present work, neural network classifiers were employed with the same image features found useful in the previous study for this task. Both standard backpropagation neural networks and a recently developed biologically-inspired network called Dystal were used. Classification performance as measured by the area under a receiver operating characteristic curve was generally excellent for the back propagation networks and was roughly comparable to that of classical statistical discriminators tested on the same data set and documented in the earlier study. Performance of the Dystal network was significantly inferior; however, this may be due to the choice of network parameter. Potential methods for enhancing network performance was identified.

  3. 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

  4. The synthesis and analysis of color images

    NASA Technical Reports Server (NTRS)

    Wandell, Brian A.

    1987-01-01

    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 efficiently 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.

  5. 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.

  6. Imaging regional renal function parameters using radionuclide tracers

    NASA Astrophysics Data System (ADS)

    Qiao, Yi

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

  7. [Functional magnetic resonance imaging in psychiatry and psychotherapy].

    PubMed

    Derntl, B; Habel, U; Schneider, F

    2010-01-01

    technical improvements, functional magnetic resonance imaging (fMRI) has become the most popular and versatile imaging method in psychiatric research. The scope of this manuscript is to briefly introduce the basics of MR physics, the blood oxygenation level-dependent (BOLD) contrast as well as the principles of MR study design and functional data analysis. The presentation of exemplary studies on emotion recognition and empathy in schizophrenia patients will highlight the importance of MR methods in psychiatry. Finally, we will demonstrate insights into new developments that will further boost MR techniques in clinical research and will help to gain more insight into dysfunctional neural networks underlying cognitive and emotional deficits in psychiatric patients. Moreover, some techniques such as neurofeedback seem promising for evaluation of therapy effects on a behavioral and neural level. PMID:20057981

  8. Advances in analysis of low signal-to-noise images link dynamin and AP2 to the functions of an endocytic checkpoint.

    PubMed

    Aguet, François; Antonescu, Costin N; Mettlen, Marcel; Schmid, Sandra L; Danuser, Gaudenz

    2013-08-12

    Numerous endocytic accessory proteins (EAPs) mediate assembly and maturation of clathrin-coated pits (CCPs) into cargo-containing vesicles. Analysis of EAP function through bulk measurement of cargo uptake has been hampered due to potential redundancy among EAPs and, as we show here, the plasticity and resilience of clathrin-mediated endocytosis (CME). Instead, EAP function is best studied by uncovering the correlation between variations in EAP association to individual CCPs and the resulting variations in maturation. However, most EAPs bind to CCPs in low numbers, making the measurement of EAP association via fused fluorescent reporters highly susceptible to detection errors. Here, we present a framework for unbiased measurement of EAP recruitment to CCPs and their direct effects on CCP dynamics. We identify dynamin and the EAP-binding α-adaptin appendage domain of the AP2 adaptor as switches in a regulated, multistep maturation process and provide direct evidence for a molecular checkpoint in CME. PMID:23891661

  9. 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. PMID:27374127

  10. Functional magnetic resonance imaging of awake monkeys: some approaches for improving imaging quality

    PubMed Central

    Chen, Gang; Wang, Feng; Dillenburger, Barbara C.; Friedman, Robert M.; Chen, Li M.; Gore, John C.; Avison, Malcolm J.; Roe, Anna W.

    2011-01-01

    Functional magnetic resonance imaging (fMRI), at high magnetic field strength can suffer from serious degradation of image quality because of motion and physiological noise, as well as spatial distortions and signal losses due to susceptibility effects. Overcoming such limitations is essential for sensitive detection and reliable interpretation of fMRI data. These issues are particularly problematic in studies of awake animals. As part of our initial efforts to study functional brain activations in awake, behaving monkeys using fMRI at 4.7T, we have developed acquisition and analysis procedures to improve image quality with encouraging results. We evaluated the influence of two main variables on image quality. First, we show how important the level of behavioral training is for obtaining good data stability and high temporal signal-to-noise ratios. In initial sessions, our typical scan session lasted 1.5 hours, partitioned into short (<10 minutes) runs. During reward periods and breaks between runs, the monkey exhibited movements resulting in considerable image misregistrations. After a few months of extensive behavioral training, we were able to increase the length of individual runs and the total length of each session. The monkey learned to wait until the end of a block for fluid reward, resulting in longer periods of continuous acquisition. Each additional 60 training sessions extended the duration of each session by 60 minutes, culminating, after about 140 training sessions, in sessions that last about four hours. As a result, the average translational movement decreased from over 500 μm to less than 80 μm, a displacement close to that observed in anesthetized monkeys scanned in a 7 T horizontal scanner. Another major source of distortion at high fields arises from susceptibility variations. To reduce such artifacts, we used segmented gradient-echo echo-planar imaging (EPI) sequences. Increasing the number of segments significantly decreased susceptibility

  11. Preprocessing functions for computed radiography images in a PACS environment

    NASA Astrophysics Data System (ADS)

    McNitt-Gray, Michael F.; Pietka, Ewa; Huang, H. K.

    1992-05-01

    In a picture archiving and communications system (PACS), images are acquired from several modalities including computed radiography (CR). This modality has unique image characteristics and presents several problems that need to be resolved before the image is available for viewing at a display workstation. A set of preprocessing functions have been applied to all CR images in a PACS environment to enhance the display of images. The first function reformats CR images that are acquired with different plate sizes to a standard size for display. Another function removes the distracting white background caused by the collimation used at the time of exposure. A third function determines the orientation of each image and rotates those images that are in nonstandard positions into a standard viewing position. Another function creates a default look-up table based on the gray levels actually used by the image (instead of allocated gray levels). Finally, there is a function which creates (for chest images only) the piece-wise linear look-up tables that can be applied to enhance different tissue densities. These functions have all been implemented in a PACS environment. Each of these functions have been very successful in improving the viewing conditions of CR images and contribute to the clinical acceptance of PACS by reducing the effort required to display CR images.

  12. Cloud based toolbox for image analysis, processing and reconstruction tasks.

    PubMed

    Bednarz, Tomasz; Wang, Dadong; Arzhaeva, Yulia; Lagerstrom, Ryan; Vallotton, Pascal; Burdett, Neil; Khassapov, Alex; Szul, Piotr; Chen, Shiping; Sun, Changming; Domanski, Luke; Thompson, Darren; Gureyev, Timur; Taylor, John A

    2015-01-01

    This chapter describes a novel way of carrying out image analysis, reconstruction and processing tasks using cloud based service provided on the Australian National eResearch Collaboration Tools and Resources (NeCTAR) infrastructure. The toolbox allows users free access to a wide range of useful blocks of functionalities (imaging functions) that can be connected together in workflows allowing creation of even more complex algorithms that can be re-run on different data sets, shared with others or additionally adjusted. The functions given are in the area of cellular imaging, advanced X-ray image analysis, computed tomography and 3D medical imaging and visualisation. The service is currently available on the website www.cloudimaging.net.au . PMID:25381109

  13. Continuous-wave terahertz scanning image resolution analysis and restoration

    NASA Astrophysics Data System (ADS)

    Li, Qi; Yin, Qiguo; Yao, Rui; Ding, Shenghui; Wang, Qi

    2010-03-01

    Resolution of continuous-wave (CW) terahertz scanning image is limited by many factors among which the aperture effect of finite focus diameter is very important. We have investigated the factors that affect terahertz (THz) image resolution in details through theory analysis and simulation. On the other hand, in order to enhance THz image resolution, Richardson-Lucy algorithm has been introduced as a promising approach to improve image details. By analyzing the imaging theory, it is proposed that intensity distribution function of actual THz laser focal spot can be approximatively used as point spread function (PSF) in the restoration algorithm. The focal spot image could be obtained by applying the pyroelectric camera, and mean filtering result of the focal spot image is used as the PSF. Simulation and experiment show that the algorithm implemented is comparatively effective.

  14. 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.

  15. 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

  16. 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

  17. Functional data analysis in hydrology

    NASA Astrophysics Data System (ADS)

    Chebana, F.; Dabo-Niang, S.; Ouarda, T.

    2013-12-01

    River flow records are essential for the prevention of flood risks and the effective planning and management of water resources among other engineering activities. The graphical representation of the temporal variation of flow over a period of time constitutes a hydrograph. The latter is usually characterized by its peak, volume and duration. These features are considered jointly in order to take into account their dependence structure within multivariate hydrological frequency analysis (HFA). However, all these multivariate HFA approaches are based on the analysis of a limited number of characteristics and do not make use of the full information provided by the hydrograph. This talk is to propose to introduce a new framework for HFA using the hydrographs as curves to be functional data. In the context, called functional data analysis (FDA), the whole hydrograph is considered as one infinite-dimensional observation. The FDA context in HFA has a number of advantages. A number of functional tools are introduced and adapted to flood HFA with a focus on exploratory analysis. A real-world flood analysis case-study is considered.

  18. Advances in functional magnetic resonance imaging of the human brainstem.

    PubMed

    Beissner, Florian; Schumann, Andy; Brunn, Franziska; Eisenträger, Daniela; Bär, Karl-Jürgen

    2014-02-01

    The brainstem is of tremendous importance for our daily survival, and yet the functional relationships between various nuclei, their projection targets, and afferent regulatory areas remain poorly characterized. The main reason for this lies in the sub-optimal performance of standard neuroimaging methods in this area. In particular, fMRI signals are much harder to detect in the brainstem region compared to cortical areas. Here we describe and validate a new approach to measure activation of brainstem nuclei in humans using standard fMRI sequences and widely available tools for statistical image processing. By spatially restricting an independent component analysis to an anatomically defined brainstem mask, we excluded those areas from the analysis that were strongly affected by physiological noise. This allowed us to identify for the first time intrinsic connectivity networks in the human brainstem and to map brainstem-cortical connectivity purely based on functionally defined regions of interest. PMID:23933038

  19. 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.

  20. 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

  1. FFDM image quality assessment using computerized image texture analysis

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  2. Image analysis applications for grain science

    NASA Astrophysics Data System (ADS)

    Zayas, Inna Y.; Steele, James L.

    1991-02-01

    Morphometrical features of single grain kernels or particles were used to discriminate two visibly similar wheat varieties foreign material in wheat hardsoft and spring-winter wheat classes and whole from broken corn kernels. Milled fractions of hard and soft wheat were evaluated using textural image analysis. Color image analysis of sound and mold damaged corn kernels yielded high recognition rates. The studies collectively demonstrate the potential for automated classification and assessment of grain quality using image analysis.

  3. Functional cardiac imaging by random access microscopy

    PubMed Central

    Crocini, Claudia; Coppini, Raffaele; Ferrantini, Cecilia; Pavone, Francesco S.; Sacconi, Leonardo

    2014-01-01

    Advances in the development of voltage sensitive dyes and Ca2+ sensors in combination with innovative microscopy techniques allowed researchers to perform functional measurements with an unprecedented spatial and temporal resolution. At the moment, one of the shortcomings of available technologies is their incapability of imaging multiple fast phenomena while controlling the biological determinants involved. In the near future, ultrafast deflectors can be used to rapidly scan laser beams across the sample, performing optical measurements of action potential and Ca2+ release from multiple sites within cardiac cells and tissues. The same scanning modality could also be used to control local Ca2+ release and membrane electrical activity by activation of caged compounds and light-gated ion channels. With this approach, local Ca2+ or voltage perturbations could be induced, simulating arrhythmogenic events, and their impact on physiological cell activity could be explored. The development of this optical methodology will provide fundamental insights in cardiac disease, boosting new therapeutic strategies, and, more generally, it will represent a new approach for the investigation of the physiology of excitable cells. PMID:25368580

  4. Imaging the wave functions of adsorbed molecules

    PubMed Central

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

    2014-01-01

    The basis for a quantum-mechanical description of matter is electron wave functions. For atoms and molecules, their spatial distributions and phases are known as orbitals. Although orbitals are very powerful concepts, experimentally only the electron densities and -energy levels are directly observable. Regardless whether orbitals are observed in real space with scanning probe experiments, or in reciprocal space by photoemission, the phase information of the orbital is lost. Here, we show that the experimental momentum maps of angle-resolved photoemission from molecular orbitals can be transformed to real-space orbitals via an iterative procedure which also retrieves the lost phase information. This is demonstrated with images obtained of a number of orbitals of the molecules pentacene (C22H14) and perylene-3,4,9,10-tetracarboxylic dianhydride (C24H8O6), adsorbed on silver, which are in excellent agreement with ab initio calculations. The procedure requires no a priori knowledge of the orbitals and is shown to be simple and robust. PMID:24344291

  5. Automatic processing, analysis, and recognition of images

    NASA Astrophysics Data System (ADS)

    Abrukov, Victor S.; Smirnov, Evgeniy V.; Ivanov, Dmitriy G.

    2004-11-01

    New approaches and computer codes (A&CC) for automatic processing, analysis and recognition of images are offered. The A&CC are based on presentation of object image as a collection of pixels of various colours and consecutive automatic painting of distinguished itself parts of the image. The A&CC have technical objectives centred on such direction as: 1) image processing, 2) image feature extraction, 3) image analysis and some others in any consistency and combination. The A&CC allows to obtain various geometrical and statistical parameters of object image and its parts. Additional possibilities of the A&CC usage deal with a usage of artificial neural networks technologies. We believe that A&CC can be used at creation of the systems of testing and control in a various field of industry and military applications (airborne imaging systems, tracking of moving objects), in medical diagnostics, at creation of new software for CCD, at industrial vision and creation of decision-making system, etc. The opportunities of the A&CC are tested at image analysis of model fires and plumes of the sprayed fluid, ensembles of particles, at a decoding of interferometric images, for digitization of paper diagrams of electrical signals, for recognition of the text, for elimination of a noise of the images, for filtration of the image, for analysis of the astronomical images and air photography, at detection of objects.

  6. Satellite image analysis using neural networks

    NASA Technical Reports Server (NTRS)

    Sheldon, Roger A.

    1990-01-01

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

  7. Functional and molecular image guidance in radiotherapy treatment planning optimization.

    PubMed

    Das, Shiva K; Ten Haken, Randall K

    2011-04-01

    Functional and molecular imaging techniques are increasingly being developed and used to quantitatively map the spatial distribution of parameters, such as metabolism, proliferation, hypoxia, perfusion, and ventilation, onto anatomically imaged normal organs and tumor. In radiotherapy optimization, these imaging modalities offer the promise of increased dose sparing to high-functioning subregions of normal organs or dose escalation to selected subregions of the tumor as well as the potential to adapt radiotherapy to functional changes that occur during the course of treatment. The practical use of functional/molecular imaging in radiotherapy optimization must take into cautious consideration several factors whose influences are still not clearly quantified or well understood including patient positioning differences between the planning computed tomography and functional/molecular imaging sessions, image reconstruction parameters and techniques, image registration, target/normal organ functional segmentation, the relationship governing the dose escalation/sparing warranted by the functional/molecular image intensity map, and radiotherapy-induced changes in the image intensity map over the course of treatment. The clinical benefit of functional/molecular image guidance in the form of improved local control or decreased normal organ toxicity has yet to be shown and awaits prospective clinical trials addressing this issue. PMID:21356479

  8. Two-dimensional modulation transfer functions of image scanning systems.

    PubMed

    Simonds, R M

    1981-02-15

    Image data processing based on optical scanning and digital reconstruction frequently ignores artifacts produced by the scanning process itself. Characterization of these artifacts by measurement of system modulation transfer function (MTF) using the traditional knife-edge scan technique produces only one section of the 2-D MTF, and interpretation of this as representative of the complete MTF may yield misleading re A theoretical analysis is presented which allows reconstruction of the complete 2-D MTF from a sequence of knife-edge measurements, and an experimental example is shown for the case of a vidicon camera based scanning system. PMID:20309166

  9. A proposed multidimensional analysis function

    NASA Astrophysics Data System (ADS)

    Knight, Byron F.; Hamilton, Mark K.

    2003-08-01

    Previous work has suggested a potential value in the combination of physical property data types (e.g. magnetic and terrain slope) when searching for oil and mineral deposits. This work studies a notional multi-dimensional function to determine the likelihood of finding such deposits. Additionally, this hypothesis assumes some basic requirements must be meet in order to validate this function. The standard for determining the value of commercially gathered electro optical imagery is the same as with any optical system -- the ability to determine object in the field of view. Further, this function is defined as the ability to determine the presence of two parallel lines, vice only one. The National Imagery and Mapping Agency (NIMA) uses a function called Digital Terrain Elevation Data (DTED) to determine the elevation within a field of view. The DTED values for each pixel within a digital, commercial image can be considered similar to a gradient, whereby higher values are merely higher elevations. For the commercial electro optical system IKONOS (owned by Space Imaging, Inc.), the "resolution" is commonly referred to as 1 meter, which is the least discernable, parallel-line, separation distance. This hypothesis uses gravity and magnetic data to augment the DTED "gradient". As with the terrain values on the earth, gravity and magnetic values are continuously changing. Further, they can change for various reasons. Both are greatly affected by the changes in the subsurface materials, or the density of the soil and metallic content (e.g. iron). It is precisely these variations, through the combination of such differing forms of data, which can help determine the presence of oil and mineral deposits. The core of this work is a notional function development. Previous peer review has rightly pointed out that data fusion principles state that data must be commensurable before it can be fused. This work does not attempt to redefine data fusion concepts, but merely establish

  10. 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.

  11. 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.

  12. Analysis on correlation imaging based on fractal interpolation

    NASA Astrophysics Data System (ADS)

    Li, Bailing; Zhang, Wenwen; Chen, Qian; Gu, Guohua

    2015-10-01

    One fractal interpolation algorithm has been discussed in detail and the statistical self-similarity characteristics of light field have been analized in correlated experiment. For the correlation imaging experiment in condition of low sampling frequent, an image analysis approach based on fractal interpolation algorithm is proposed. This approach aims to improve the resolution of original image which contains a fewer number of pixels and highlight the image contour feature which is fuzzy. By using this method, a new model for the light field has been established. For the case of different moments of the intensity in the receiving plane, the local field division also has been established and then the iterated function system based on the experimental data set can be obtained by choosing the appropriate compression ratio under a scientific error estimate. On the basis of the iterative function, an explicit fractal interpolation function expression is given out in this paper. The simulation results show that the correlation image reconstructed by fractal interpolation has good approximations to the original image. The number of pixels of image after interpolation is significantly increased. This method will effectively solve the difficulty of image pixel deficiency and significantly improved the outline of objects in the image. The rate of deviation as the parameter has been adopted in the paper in order to evaluate objectively the effect of the algorithm. To sum up, fractal interpolation method proposed in this paper not only keeps the overall image but also increases the local information of the original image.

  13. 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

  14. Medical image processing using novel wavelet filters based on atomic functions: optimal medical image compression.

    PubMed

    Landin, Cristina Juarez; Reyes, Magally Martinez; Martin, Anabelem Soberanes; Rosas, Rosa Maria Valdovinos; Ramirez, Jose Luis Sanchez; Ponomaryov, Volodymyr; Soto, Maria Dolores Torres

    2011-01-01

    The analysis of different Wavelets including novel Wavelet families based on atomic functions are presented, especially for ultrasound (US) and mammography (MG) images compression. This way we are able to determine with what type of filters Wavelet works better in compression of such images. Key properties: Frequency response, approximation order, projection cosine, and Riesz bounds were determined and compared for the classic Wavelets W9/7 used in standard JPEG2000, Daubechies8, Symlet8, as well as for the complex Kravchenko-Rvachev Wavelets ψ(t) based on the atomic functions up(t),  fup (2)(t), and eup(t). The comparison results show significantly better performance of novel Wavelets that is justified by experiments and in study of key properties. PMID:21431590

  15. 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.

  16. 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.

  17. Atomic force microscope, molecular imaging, and analysis.

    PubMed

    Chen, Shu-wen W; Teulon, Jean-Marie; Godon, Christian; Pellequer, Jean-Luc

    2016-01-01

    Image visibility is a central issue in analyzing all kinds of microscopic images. An increase of intensity contrast helps to raise the image visibility, thereby to reveal fine image features. Accordingly, a proper evaluation of results with current imaging parameters can be used for feedback on future imaging experiments. In this work, we have applied the Laplacian function of image intensity as either an additive component (Laplacian mask) or a multiplying factor (Laplacian weight) for enhancing image contrast of high-resolution AFM images of two molecular systems, an unknown protein imaged in air, provided by AFM COST Action TD1002 (http://www.afm4nanomedbio.eu/), and tobacco mosaic virus (TMV) particles imaged in liquid. Based on both visual inspection and quantitative representation of contrast measurements, we found that the Laplacian weight is more effective than the Laplacian mask for the unknown protein, whereas for the TMV system the strengthened Laplacian mask is superior to the Laplacian weight. The present results indicate that a mathematical function, as exemplified by the Laplacian function, may yield varied processing effects with different operations. To interpret the diversity of molecular structure and topology in images, an explicit expression for processing procedures should be included in scientific reports alongside instrumental setups. PMID:26224520

  18. Generalized functional extended redundancy analysis.

    PubMed

    Hwang, Heungsun; Suk, Hye Won; Takane, Yoshio; Lee, Jang-Han; Lim, Jooseop

    2015-03-01

    Functional extended redundancy analysis (FERA) was recently developed to integrate data reduction into functional linear models. This technique extracts a component from each of multiple sets of predictor data in such a way that the component accounts for the maximum variance of response data. Moreover, it permits predictor and/or response data to be functional. FERA can be of use in describing overall characteristics of each set of predictor data and in summarizing the relationships between predictor and response data. In this paper, we extend FERA into the framework of generalized linear models (GLM), so that it can deal with response data generated from a variety of distributions. Specifically, the proposed method reduces each set of predictor functions to a component and uses the component for explaining exponential-family responses. As in GLM, we specify the random, systematic, and link function parts of the proposed method. We develop an iterative algorithm to maximize a penalized log-likelihood criterion that is derived in combination with a basis function expansion approach. We conduct two simulation studies to investigate the performance of the proposed method based on synthetic data. In addition, we apply the proposed method to two examples to demonstrate its empirical usefulness. PMID:24271507

  19. 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.

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

    USGS Publications Warehouse

    Fitzpatrick, Joan J.

    2013-01-01

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

  1. Functional brain imaging of trigeminal neuralgia.

    PubMed

    Moisset, Xavier; Villain, Nicolas; Ducreux, Denis; Serrie, Alain; Cunin, Gérard; Valade, Dominique; Calvino, Bernard; Bouhassira, Didier

    2011-02-01

    We used functional magnetic resonance imaging (fMRI) to analyze changes in brain activity associated with stimulation of the cutaneous trigger zone in patients with classic trigeminal neuralgia (CTN). Fifteen consecutive patients with CTN in the second or third division of the nerve, were included in this study. The fMRI paradigm consisted of light tactile stimuli of the trigger zone and the homologous contralateral area. Stimulation of the affected side induced pain in seven patients, but was not painful in eight patients on the day of the experiment. Painful stimuli were associated with significantly increased activity in the spinal trigeminal nucleus (SpV), thalamus, primary and secondary somatosensory cortices (S1, S2), anterior cingulate cortex (ACC), insula, premotor/motor cortex, prefrontal areas, putamen, hippocampus and brainstem. Nonpainful stimulation of the trigger zone activated all but three of these structures (SpV, brainstem and ACC). After a successful surgical treatment, activation induced by stimulation of the operated side was confined to S1 and S2. Our data demonstrate the pathological hyperexcitability of the trigeminal nociceptive system, including the second order trigeminal sensory neurons during evoked attacks of CTN. Such sensitization may depend on pain modulatory systems involving both the brainstem (i.e. periaqueductal gray and adjacent structures) and interconnected cortical structures (i.e. ACC). The fact that large portions of the classical 'pain neuromatrix' were also activated during nonpainful stimulation of the trigger zone, could reflect a state of maintained sensitization of the trigeminal nociceptive systems in CTN. PMID:20609605

  2. Functional Tissue Pulsatility Imaging of the Brain during Visual Stimulation

    PubMed Central

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

    2007-01-01

    Functional tissue pulsatility imaging (fTPI) is a new ultrasonic technique being developed to map brain function by measuring changes in tissue pulsatility due to changes in blood flow with neuronal activation. The technique is based in principle on plethysmography, an older, non-ultrasound technology for measuring expansion of a whole limb or body part due to perfusion. Perfused tissue expands by a fraction of a percent early in each cardiac cycle when arterial inflow exceeds venous outflow and relaxes later in the cardiac cycle when venous drainage dominates. Tissue pulsatility imaging (TPI) uses tissue Doppler signal processing methods to measure this pulsatile “plethysmographic” signal from hundreds or thousands of sample volumes in an ultrasound image plane. A feasibility study was conducted to determine if TPI could be used to detect regional brain activation during a visual contrast-reversing checkerboard block paradigm study. During a study, ultrasound data were collected transcranially from the occipital lobe as a subject viewed alternating blocks of a reversing checkerboard (stimulus condition) and a static, gray screen (control condition). Multivariate Analysis of Variance (MANOVA) was used to identify sample volumes with significantly different pulsatility waveforms during the control and stimulus blocks. In 7 out 14 studies, consistent regions of activation were detected from tissue around the major vessels perfusing the visual cortex. PMID:17346872

  3. 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.

  4. Image processing software for imaging spectrometry data analysis

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. Functional calcium imaging in zebrafish lateral-line hair cells.

    PubMed

    Zhang, Q X; He, X J; Wong, H C; Kindt, K S

    2016-01-01

    Sensory hair-cell development, function, and regeneration are fundamental processes that are challenging to study in mammalian systems. Zebrafish are an excellent alternative model to study hair cells because they have an external auxiliary organ called the lateral line. The hair cells of the lateral line are easily accessible, which makes them suitable for live, function-based fluorescence imaging. In this chapter, we describe methods to perform functional calcium imaging in zebrafish lateral-line hair cells. We compare genetically encoded calcium indicators that have been used previously to measure calcium in lateral-line hair cells. We also outline equipment required for calcium imaging and compare different imaging systems. Lastly, we discuss how to set up optimal imaging parameters and how to process and visualize calcium signals. Overall, using these methods, in vivo calcium imaging is a powerful tool to examine sensory hair-cell function in an intact organism. PMID:27263415

  10. 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

  11. 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

  12. Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

    NASA Astrophysics Data System (ADS)

    Liang, Jianming; Järvi, Timo; Kiuru, Aaro; Kormano, Martti; Svedström, Erkki

    2003-12-01

    The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT) and nuclear medicine (NM) studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

  13. 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

  14. Functional MR imaging as a new paradigm for image guidance.

    PubMed

    Assumpcao, Lia; Choti, Michael; Pawlik, Timothy M; Gecshwind, Jean-Francois; Kamel, Ihab R

    2009-11-01

    Guidance and monitoring of locoregional minimally invasive treatment for primary or secondary liver tumor are critical to ensuring success and efficacy of therapy. In this article, we review advanced MR imaging techniques, including MR spectroscopy, diffusion and perfusion MR imaging, which can provide essential in vivo physiologic and metabolic information. These innovative imaging techniques can provide potential additional criteria to assess tumor response in addition to the accepted yet often limited Response Evaluation Criteria in Solid Tumors (RECIST) and the European Association for the Study of the Liver (EASL) criteria, which are based on decrease of tumor size and lesion enhancement, respectively. In this article, we also discuss the role of tumor size and enhancement in addition to apparent diffusion coefficient (ADC) findings after radiofrequency ablation (RFA), transarterial chemoembolization (TACE), and radioembolization. PMID:19048335

  15. Analytical modeling of PET imaging with correlated functional and structural images

    SciTech Connect

    Ma, Y.; Evans, A.C.

    1996-12-31

    Objective evaluation of dynamic imaging protocols needs a realistic simulation tool to model the data acquisition and image reconstruction of a PET system. Availability of correlated functional and anatomical images in many centers allows the creation of highly realistic objects to represent brain activity and attenuation distribution for each study. We have developed an analytical model incorporating key physical factors inherent in coincidence detection along with spatially variant 3-D detector response and detection efficiency. In this paper we use MR and PET data of a 3-D Hoffman brain phantom to demonstrate and validate our simulation methods. The simulated total projection, attenuation factor, and scatter profiles are in excellent agreement with the experimental measurements. Regional analysis shows a discrepancy of {le} 8.5 % in the gray matter and white matter activity concentrations between the real and simulated images. Our results also reveal quantitative distortions due to partial volume effects with the same magnitude as in clinical PET scans. This tool is particularly useful in evaluating projection data processing and image reconstruction algorithms.

  16. 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.

  17. 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.

  18. Functional imaging of the brain using computed tomography.

    PubMed

    Berninger, W H; Axel, L; Norman, D; Napel, S; Redington, R W

    1981-03-01

    Data from rapid-sequence CT scans of the same cross section, obtained following bolus injection of contrast material, were analyzed by functional imaging. The information contained in a large number of images can be compressed into one or two gray-scale images which can be evaluated both qualitatively and quantitatively. The computational techniques are described and applied to the generation of images depicting bolus transit time, arrival time, peak time, and effective width. PMID:7465851

  19. 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

  20. 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

  1. Histology image analysis for carcinoma detection and grading

    PubMed Central

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

    2012-01-01

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

  2. 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

  3. Generating text from functional brain images.

    PubMed

    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. 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.

  5. Receiver Functions Analysis across the Northen Apennines

    NASA Astrophysics Data System (ADS)

    Di Bona, M.; Lucente, F. P.; Piana Agostinetti, N.; Selvaggi, G.; Levin, V.; Park, J.

    2001-12-01

    The syn-collisional extension of the Northern Apennines is well established mainly from tomographic images, active faulting and geological data. A step forward in understanding how this process began, and how is going on, is the modelling of dynamic processes causing syn-collision extension. This requires the knowledge of several, still lacking, geometric characteristics of the deep structure. Among these, crustal structure, depth and geometry of main discontinuities is priority for dynamic modelling. For this reason, we deployed 10 continuosly recording broad-band seismic stations from Corsica to the Adriatic coast for five months during the past millennium, with the aim to apply receiver function analysis, to gain refined tomographic images, and to explore anisotropic characteristics of the upper mantle. We recorded several tens of teleseismic events with magnitude larger than 5.0 (up to Mw=8.3) with a good azimuthal coverage. Receiver functions are performed for teleseisms in the epicentral distance interval between 30° and 100° through classical frequency-domain deconvolution. Following the approach developed by Di Bona (1998), we could provide a variance estimate for single receiver function, assessing the statistical accuracy of amplitudes. This procedure allows us to use small magnitude events (Mb=5.0) generally excluded from receiver function analyses. Results show that individual converted arrivals have a large consistency for each station. The best receiver functions will be inverted for fine crustal structure following the inversion scheme proposed by Sambridge (1998). Finally, the dataset has been provided to the Dept. Of Geology and Geophysics (Yale University) with the aim to compare independent estimate of receiver functions (see Levin et al., this session).

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

    USGS Publications Warehouse

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

    1988-01-01

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

  7. 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

  8. 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

  9. Robust image registration for functional magnetic resonance imaging of the brain.

    PubMed

    Hsu, C C; Wu, M T; Lee, C

    2001-09-01

    Motion-related artifacts are still a major problem in data analysis of functional magnetic resonance imaging (FMRI) studies of brain activation. However, the traditional image registration algorithm is prone to inaccuracy when there are residual variations owing to counting statistics, partial volume effects or biological variation. In particular, susceptibility artifacts usually result in remarkable signal intensity variance, and they can mislead the estimation of motion parameters. In this study, Two robust estimation algorithms for the registration of FMRI images are described. The first estimation algorithm was based on the Newton method and used Tukey's biweight objective function. The second estimation algorithm was based on the Levenberg-Marquardt technique and used a skipped mean objective function. The robust M-estimators can suppress the effects of the outliers by scaling down their error magnitudes or completely rejecting outliers using a weighting function. The proposed registration methods consisted of the following steps: fast segmentation of the brain region from noisy background as a preprocessing step; pre-registration of the volume centroids to provide a good initial estimation; and two robust estimation algorithms and a voxel sampling technique to find the affine transformation parameters. The accuracy of the algorithms was within 0.5 mm in translation and within 0.5 degrees in rotation. For the FMRI data sets, the performance of the algorithms was visually compared with the AIR 2.0 software, which is a software for image registration, using colour-coded statistical mapping by the Kolmogorov-Smirov method. Experimental results showed, that the algorithms provided significant improvement in correcting motion-related artifacts and can enhance the detection of real brain activation. PMID:11712647

  10. Imaging 2-D Structures With Receiver Functions Using Harmonic Stripping

    NASA Astrophysics Data System (ADS)

    Schulte-Pelkum, V.

    2010-12-01

    I present a novel technique to image dipping and anisotropic structures using receiver functions. Receiver functions isolate phase conversions from interfaces close to the seismic station. Standard analysis assumes a quasi-flat layered structure and dampens arrivals from dipping interfaces and anisotropic layers, with attempts to extract information on such structures relying on cumbersome and nonunique forward modeling. I use a simple relationship between the radial and transverse component receiver function to detect dipping and anisotropic layers and map their depth and orientation. For dipping interfaces, layers with horizontal or plunging axis anisotropy, and point scatterers, the following relationships hold: After subtracting the azimuthally invariant portion of the radial receiver functions, the remaining signal is an azimuthally shifted version of the transverse receiver functions. The strike of the dipping interface or anisotropy is given by the azimuth of polarity reversals, and the type of structure can be inferred from the amount of phase shift between the components. For a known structure type, the phase shift between the two components provides pseudoevents from back-azimuths with little seismicity. The technique allows structural mapping at depth akin to geological mapping of rock fabric and dipping layers at the surface. It reduces complex wavefield effects to two simple and geologically meaningful parameters, similar to shear wave splitting. I demonstrate the method on the Wind River Thrust as well as other structures within the Transportable Array footprint.

  11. Enhanced perceptual distance functions and indexing for image replica recognition.

    PubMed

    Qamra, Arun; Meng, Yan; Chang, Edward Y

    2005-03-01

    The proliferation of digital images and the widespread distribution of digital data that has been made possible by the Internet has increased problems associated with copyright infringement on digital images. Watermarking schemes have been proposed to safeguard copyrighted images, but watermarks are vulnerable to image processing and geometric distortions and may not be very effective. Thus, the content-based detection of pirated images has become an important application. In this paper, we discuss two important aspects of such a replica detection system: distance functions for similarity measurement and scalability. We extend our previous work on perceptual distance functions, which proposed the Dynamic Partial Function (DPF), and present enhanced techniques that overcome the limitations of DPF. These techniques include the Thresholding, Sampling, and Weighting schemes. Experimental evaluations show superior performance compared to DPF and other distance functions. We then address the issue of using these perceptual distance functions to efficiently detect replicas in large image data sets. The problem of indexing is made challenging by the high-dimensionality and the nonmetric nature of the distance functions. We propose using Locality Sensitive Hashing (LSH) to index images while using the above perceptual distance functions and demonstrate good performance through empirical studies on a very large database of diverse images. PMID:15747793

  12. B Plant function analysis report

    SciTech Connect

    Lund, D.P.; B Plant Working Group

    1995-09-01

    The document contains the functions, function definitions, function interfaces, function interface definitions, Input Computer Automated Manufacturing Definition (IDEFO) diagrams, and a function hierarchy chart that describe what needs to be performed to deactivate B Plant.

  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'. PMID:27574313

  14. An imaging system for intraoperative functional imaging of optical intrinsic signals

    NASA Astrophysics Data System (ADS)

    Wong, Gregory Kai

    This dissertation focuses on the research, design, and implementation of a Neurosurgical Imaging System (NIS), having the principle characteristics of modularity, mobility, multispectral imaging capabilities, and an open software architecture. The NIS will enable functional imaging of humans and animals by implementing innovative hardware and software enhancements. The NIS is tightly integrated with data acquisition hardware and software for simultaneous measurements of real-time, physiological parameters and Optical Intrinsic Signals (OIS). The NIS provides a portable, versatile imaging system. High speed ``off the shelf'' hardware has been implemented and refined to reduce overall cost and maintenance of the NIS. Implementation of new, enhanced charge coupled device technology, such as, Electron Bombardment Charge Coupled Devices (EBCCD) dramatically increases sensitivity and multi-spectral image acquisition capabilities. Utilization of efficient calibration and testing protocols provides advanced trouble shooting and standard performance metrics for the NIS. The NIS was experimentally tested and validated on LED ``phantoms'' and a variety of mammalian brain models throughout its design phases. Implementation of an innovative imaging system such as the NIS provides a powerful research and clinical diagnostic tool that will enhance our current understanding of the various physiologic underpinnings of neurovascular coupling in normal and diseased brains. The development of this type of portable imaging instrumentation controlled by a robust software architecture that provides command and control, real time data acquisition, data analysis, auto calibration, and performance metrics lay the foundations for a comprehensive neurosurgical guidance tool, as well as, a powerful experimental research tool for mapping activity-related changes in cerebral perfusion and neuronal activity.

  15. 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.

  16. Accuracy in Quantitative 3D Image Analysis

    PubMed Central

    Bassel, George W.

    2015-01-01

    Quantitative 3D imaging is becoming an increasingly popular and powerful approach to investigate plant growth and development. With the increased use of 3D image analysis, standards to ensure the accuracy and reproducibility of these data are required. This commentary highlights how image acquisition and postprocessing can introduce artifacts into 3D image data and proposes steps to increase both the accuracy and reproducibility of these analyses. It is intended to aid researchers entering the field of 3D image processing of plant cells and tissues and to help general readers in understanding and evaluating such data. PMID:25804539

  17. 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…

  18. Robust Automatic Breast Cancer Staging Using A Combination of Functional Genomics and Image-Omics

    PubMed Central

    Su, Hai; Shen, Yong; Xing, Fuyong; Qi, Xin; Hirshfield, Kim M.; Yang, Lin; Foran, David J.

    2016-01-01

    Breast cancer is one of the leading cancers worldwide. Precision medicine is a new trend that systematically examines molecular and functional genomic information within each patient's cancer to identify the patterns that may affect treatment decisions and potential outcomes. As a part of precision medicine, computer-aided diagnosis enables joint analysis of functional genomic information and image from pathological images. In this paper we propose an integrated framework for breast cancer staging using image-omics and functional genomic information. The entire biomedical imaging informatics framework consists of image-omics extraction, feature combination, and classification. First, a robust automatic nuclei detection and segmentation is presented to identify tumor regions, delineate nuclei boundaries and calculate a set of image-based morphological features; next, the low dimensional image-omics is obtained through principal component analysis and is concatenated with the functional genomic features identified by a linear model. A support vector machine for differentiating stage I breast cancer from other stages are learned. We experimentally demonstrate that compared with a single type of representation (image-omics), the combination of image-omics and functional genomic feature can improve the classification accuracy by 3%. PMID:26737959

  19. Functional knee assessment with advanced imaging.

    PubMed

    Amano, Keiko; Li, Qi; Ma, C Benjamin

    2016-06-01

    The purpose of anterior cruciate ligament (ACL) reconstruction is to restore the native stability of the knee joint and to prevent further injury to meniscus and cartilage, yet studies have suggested that joint laxity remains prevalent in varying degrees after ACL reconstruction. Imaging can provide measurements of translational and rotational motions of the tibiofemoral joint that may be too small to detect in routine physical examinations. Various imaging modalities, including fluoroscopy, computed tomography (CT), and magnetic resonance imaging (MRI), have emerged as powerful methods in measuring the minute details involved in joint biomechanics. While each technique has its own strengths and limitations, they have all enhanced our understanding of the knee joint under various stresses and movements. Acquiring the knowledge of the complex and dynamic motions of the knee after surgery would help lead to improved surgical techniques and better patient outcomes. PMID:27052009

  20. 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

  1. 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

  2. Objective analysis of image quality of video image capture systems

    NASA Astrophysics Data System (ADS)

    Rowberg, Alan H.

    1990-07-01

    As Picture Archiving and Communication System (PACS) technology has matured, video image capture has become a common way of capturing digital images from many modalities. While digital interfaces, such as those which use the ACR/NEMA standard, will become more common in the future, and are preferred because of the accuracy of image transfer, video image capture will be the dominant method in the short term, and may continue to be used for some time because of the low cost and high speed often associated with such devices. Currently, virtually all installed systems use methods of digitizing the video signal that is produced for display on the scanner viewing console itself. A series of digital test images have been developed for display on either a GE CT9800 or a GE Signa MRI scanner. These images have been captured with each of five commercially available image capture systems, and the resultant images digitally transferred on floppy disk to a PC1286 computer containing Optimast' image analysis software. Here the images can be displayed in a comparative manner for visual evaluation, in addition to being analyzed statistically. Each of the images have been designed to support certain tests, including noise, accuracy, linearity, gray scale range, stability, slew rate, and pixel alignment. These image capture systems vary widely in these characteristics, in addition to the presence or absence of other artifacts, such as shading and moire pattern. Other accessories such as video distribution amplifiers and noise filters can also add or modify artifacts seen in the captured images, often giving unusual results. Each image is described, together with the tests which were performed using them. One image contains alternating black and white lines, each one pixel wide, after equilibration strips ten pixels wide. While some systems have a slew rate fast enough to track this correctly, others blur it to an average shade of gray, and do not resolve the lines, or give

  3. Scale-Specific Multifractal Medical Image Analysis

    PubMed Central

    Braverman, Boris

    2013-01-01

    Fractal geometry has been applied widely in the analysis of medical images to characterize the irregular complex tissue structures that do not lend themselves to straightforward analysis with traditional Euclidean geometry. In this study, we treat the nonfractal behaviour of medical images over large-scale ranges by considering their box-counting fractal dimension as a scale-dependent parameter rather than a single number. We describe this approach in the context of the more generalized Rényi entropy, in which we can also compute the information and correlation dimensions of images. In addition, we describe and validate a computational improvement to box-counting fractal analysis. This improvement is based on integral images, which allows the speedup of any box-counting or similar fractal analysis algorithm, including estimation of scale-dependent dimensions. Finally, we applied our technique to images of invasive breast cancer tissue from 157 patients to show a relationship between the fractal analysis of these images over certain scale ranges and pathologic tumour grade (a standard prognosticator for breast cancer). Our approach is general and can be applied to any medical imaging application in which the complexity of pathological image structures may have clinical value. PMID:24023588

  4. 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

  5. Exploiting temporal information in functional magnetic resonance imaging brain data.

    PubMed

    Zhang, Lei; Samaras, Dimitris; Tomasi, Dardo; Alia-Klein, Nelly; Cottone, Lisa; Leskovjan, Andreana; Volkow, Nora; Goldstein, Rita

    2005-01-01

    Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data analysis methods. In this paper, we contribute a comprehensive framework for spatial and temporal exploration of fMRI data, and apply it to a challenging case study: separating drug addicted subjects from healthy non-drug-using controls. To our knowledge, this is the first time that learning on fMRI data is performed explicitly on temporal information for classification in such applications. Experimental results demonstrate that, by selecting discriminative features, group classification can be successfully performed on our case study although training data are exceptionally high dimensional, sparse and noisy fMRI sequences. The classification performance can be significantly improved by incorporating temporal information into machine learning. Both statistical and neuroscientific validation of the method's generalization ability are provided. We demonstrate that incorporation of computer science principles into functional neuroimaging clinical studies, facilitates deduction about the behavioral probes from the brain activation data, thus providing a valid tool that incorporates objective brain imaging data into clinical classification of psychopathologies and identification of genetic vulnerabilities. PMID:16685905

  6. Testing anatomically specified hypotheses in functional imaging using cytoarchitectonic maps.

    PubMed

    Eickhoff, Simon B; Heim, Stefan; Zilles, Karl; Amunts, Katrin

    2006-08-15

    The statistical inference on functional imaging data is severely complicated by the embedded multiple testing problem. Defining a region of interest (ROI) where the activation is hypothesized a priori helps to circumvent this problem, since in this case the inference is restricted to fewer simultaneous tests, rendering it more sensitive. Cytoarchitectonic maps obtained from postmortem brains provide objective, a priori ROIs that can be used to test anatomically specified hypotheses about the localization of functional activations. We here analyzed three methods for the definition of ROIs based on probabilistic cytoarchitectonic maps. (1) ROIs defined by the volume assigned to a cytoarchitectonic area in the summary map of all areas (maximum probability map, MPM), (2) ROIs based on thresholding the individual probabilistic maps and (3) spherical ROIs build around the cytoarchitectonic center of gravity. The quality with which the thus defined ROIs represented the respective cytoarchitectonic areas as well as their sensitivity for detecting functional activations was subsequently statistically evaluated. Our data showed that the MPM method yields ROIs, which reflect most adequately the underlying anatomical hypotheses. These maps also show a high degree of sensitivity in the statistical analysis. We thus propose the use of MPMs for the definition of ROIs. In combination with thresholding based on the Gaussian random field theory, these ROIs can then be applied to test anatomically specified hypotheses in functional neuroimaging studies. PMID:16781166

  7. Materials characterization through quantitative digital image analysis

    SciTech Connect

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

    2000-07-01

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

  8. 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.

  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. Viewing angle analysis of integral imaging

    NASA Astrophysics Data System (ADS)

    Wang, Hong-Xia; Wu, Chun-Hong; Yang, Yang; Zhang, Lan

    2007-12-01

    Integral imaging (II) is a technique capable of displaying 3D images with continuous parallax in full natural color. It is becoming the most perspective technique in developing next generation three-dimensional TV (3DTV) and visualization field due to its outstanding advantages. However, most of conventional integral images are restricted by its narrow viewing angle. One reason is that the range in which a reconstructed integral image can be displayed with consistent parallax is limited. The other is that the aperture of system is finite. By far many methods , an integral imaging method to enhance the viewing angle of integral images has been proposed. Nevertheless, except Ren's MVW (Maximum Viewing Width) most of these methods involve complex hardware and modifications of optical system, which usually bring other disadvantages and make operation more difficult. At the same time the cost of these systems should be higher. In order to simplify optical systems, this paper systematically analyzes the viewing angle of traditional integral images instead of modified ones. Simultaneously for the sake of cost the research was based on computer generated integral images (CGII). With the analysis result we can know clearly how the viewing angle can be enhanced and how the image overlap or image flipping can be avoided. The result also promotes the development of optical instruments. Based on theoretical analysis, preliminary calculation was done to demonstrate how the other viewing properties which are closely related with the viewing angle, such as viewing distance, viewing zone, lens pitch, and etc. affect the viewing angle.

  11. 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

  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. Depth-based selective image reconstruction using spatiotemporal image analysis

    NASA Astrophysics Data System (ADS)

    Haga, Tetsuji; Sumi, Kazuhiko; Hashimoto, Manabu; Seki, Akinobu

    1999-03-01

    In industrial plants, a remote monitoring system which removes physical tour inspection is often considered desirable. However the image sequence given from the mobile inspection robot is hard to see because interested objects are often partially occluded by obstacles such as pillars or fences. Our aim is to improve the image sequence that increases the efficiency and reliability of remote visual inspection. We propose a new depth-based image processing technique, which removes the needless objects from the foreground and recovers the occluded background electronically. Our algorithm is based on spatiotemporal analysis that enables fine and dense depth estimation, depth-based precise segmentation, and accurate interpolation. We apply this technique to a real time sequence given from the mobile inspection robot. The resulted image sequence is satisfactory in that the operator can make correct visual inspection with less fatigue.

  14. 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

  15. Imaging analysis of collagen fiber networks in cusps of porcine aortic valves: effect of their local distribution and alignment on valve functionality.

    PubMed

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

    2016-07-01

    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

  16. 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.

  17. Functional Imaging and Related Techniques: An Introduction for Rehabilitation Researchers

    PubMed Central

    Crosson, Bruce; Ford, Anastasia; McGregor, Keith M.; Meinzer, Marcus; Cheshkov, Sergey; Li, Xiufeng; Walker-Batson, Delaina; Briggs, Richard W.

    2010-01-01

    Functional neuroimaging and related neuroimaging techniques are becoming important tools for rehabilitation research. Functional neuroimaging techniques can be used to determine the effects of brain injury or disease on brain systems related to cognition and behavior and to determine how rehabilitation changes brain systems. These techniques include: functional magnetic resonance imaging (fMRI), positron emission tomography (PET), electroencephalography (EEG), magnetoencephalography (MEG), near infrared spectroscopy (NIRS), and transcranial magnetic stimulation (TMS). Related diffusion weighted magnetic resonance imaging techniques (DWI), including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), can quantify white matter integrity. With the proliferation of these imaging techniques in rehabilitation research, it is critical that rehabilitation researchers, as well as consumers of rehabilitation research, become familiar with neuroimaging techniques, what they can offer, and their strengths and weaknesses The purpose to this review is to provide such an introduction to these neuroimaging techniques. PMID:20593321

  18. 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

  19. 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

  20. Renal relevant radiology: renal functional magnetic resonance imaging.

    PubMed

    Ebrahimi, Behzad; Textor, Stephen C; Lerman, Lilach O

    2014-02-01

    Because of its noninvasive nature and provision of quantitative measures of a wide variety of physiologic parameters, functional magnetic resonance imaging (MRI) shows great potential for research and clinical applications. Over the past decade, application of functional MRI extended beyond detection of cerebral activity, and techniques for abdominal functional MRI evolved. Assessment of renal perfusion, glomerular filtration, interstitial diffusion, and parenchymal oxygenation turned this modality into an essential research and potentially diagnostic tool. Variations in many renal physiologic markers can be detected using functional MRI before morphologic changes become evident in anatomic magnetic resonance images. Moreover, the framework of functional MRI opened a window of opportunity to develop novel pathophysiologic markers. This article reviews applications of some well validated functional MRI techniques, including perfusion, diffusion-weighted imaging, and blood oxygen level-dependent MRI, as well as some emerging new techniques such as magnetic resonance elastography, which might evolve into clinically useful tools. PMID:24370767

  1. Placental morphologic and functional imaging in high-risk pregnancies.

    PubMed

    Gudmundsson, Saemundur; Dubiel, Mariusz; Sladkevicius, Povilas

    2009-08-01

    The placenta is vital for fetal growth and development. Improvement in ultrasound and magnetic resonance imaging have improved our understanding of placental morphology that can be important as in the case of placental accrete/percreta. Functional imaging is presently mainly performed by the use of Doppler ultrasound and can give information on placental perfusion, which can be vital for clinical diagnosis. This review summarizes the present knowledge on placental imaging and it's clinical value in high-risk pregnancies. PMID:19631087

  2. Functional Analysis and Treatment of Nail Biting

    ERIC Educational Resources Information Center

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

    2008-01-01

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

  3. Functional imaging in the zebrafish retinotectal system using RGECO.

    PubMed

    Walker, Alison S; Burrone, Juan; Meyer, Martin P

    2013-01-01

    Genetically encoded calcium indicators (GECIs) allow repeated, non-invasive measurements of neural activity in defined populations of neurons, but until recently GECIs based on single fluorescent proteins have been limited to the green region of the color spectrum. Recent efforts in protein engineering have expanded the color palette of GECIs. One of these new GECIs, the red RGECO, is spectrally separate from the traditional GFP-based sensors such as GCaMP, and therefore opens the way for simultaneous, multicolor imaging of neural activity. While RGECO has been shown to report spontaneous calcium fluctuations in neurons, the precise relationship of RGECO signal to evoked-neural activity is not known. Measurements of neural activity using RGECO in vivo have also not been reported. Using dissociated hippocampal neurons we performed a systematic analysis of two forms of RGECO- a cytosolic form and a presynaptically localized form generated by fusion of RGECO to the presynaptic protein, synaptophysin (SyRGECO). We find that RGECO and GCaMP3 are comparable in terms of dynamic range, signal-to-noise ratios and kinetics but that RGECO is a more reliable reporter of single action potentials. In terms of performance SyGCaMP3 and SyRGECO are comparable, and both are more sensitive reporters of activity than the cytosolic form of each probe. Using the zebrafish retinotectal system we show that SyRGECO and RGECO are can report neural activity in vivo and that RGECO expression permits detailed structural analysis of neuronal arbors. We have exploited these attributes to provide a morphological and functional description of tectal cells selective for motion along the vertical axis. These results open up the possibility of using zebrafish to functionally image genetically defined pre- and postsynaptic circuit components, separable by color, which will be a powerful approach to studying neural interactions in the brain. PMID:23508811

  4. Linear digital imaging system fidelity analysis

    NASA Technical Reports Server (NTRS)

    Park, Stephen K.

    1989-01-01

    The combined effects of imaging gathering, sampling and reconstruction are analyzed in terms of image fidelity. The analysis is based upon a standard end-to-end linear system model which is sufficiently general so that the results apply to most line-scan and sensor-array imaging systems. Shift-variant sampling effects are accounted for with an expected value analysis based upon the use of a fixed deterministic input scene which is randomly shifted (mathematically) relative to the sampling grid. This random sample-scene phase approach has been used successfully by the author and associates in several previous related papers.

  5. Infrared image processing and data analysis

    NASA Astrophysics Data System (ADS)

    Ibarra-Castanedo, C.; González, D.; Klein, M.; Pilla, M.; Vallerand, S.; Maldague, X.

    2004-12-01

    Infrared thermography in nondestructive testing provides images (thermograms) in which zones of interest (defects) appear sometimes as subtle signatures. In this context, raw images are not often appropriate since most will be missed. In some other cases, what is needed is a quantitative analysis such as for defect detection and characterization. In this paper, presentation is made of various methods of data analysis required either at preprocessing and/or processing images. References from literature are provided for briefly discussed known methods while novelties are elaborated in more details within the text which include also experimental results.

  6. 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.

  7. 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.

  8. Imaging and functional assessment of bioresorbable scaffolds.

    PubMed

    Pighi, Michele; Tanguay, Jean F; L'allier, Philippe L

    2016-08-01

    Bioresorbable vascular scaffolds (BRS) are novel devices designed to provide transient vessel support to drug-delivery capability without the potential long-term limitations of metallic drug-eluting stents. The technology, heralded as the latest revolution in the field of percutaneous coronary intervention, could overcome many of the long-term safety concerns associated with metallic stents and possibly even convey a further clinical benefit. However, despite its theoretical advantages, the safety and efficacy of the first generation BRS remain unclear in all-comer patient populations. Invasive imaging modalities and methodologies were developed to guide BRS implantation and monitor the interaction between the scaffold and the vessel at long-term follow-up. These tools are helpful to avoid some of the pitfalls associated with BRS implantation and may improve the clinical outcome of these devices. The present review aims to report the most recent data regarding multi-imaging modalities as guidance and follow-up of coronary interventions involving the use of BRS. PMID:27195663

  9. 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

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

    PubMed

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

    1992-07-15

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

  11. Image texture analysis of crushed wheat kernels

    NASA Astrophysics Data System (ADS)

    Zayas, Inna Y.; Martin, C. R.; Steele, James L.; Dempster, Richard E.

    1992-03-01

    The development of new approaches for wheat hardness assessment may impact the grain industry in marketing, milling, and breeding. This study used image texture features for wheat hardness evaluation. Application of digital imaging to grain for grading purposes is principally based on morphometrical (shape and size) characteristics of the kernels. A composite sample of 320 kernels for 17 wheat varieties were collected after testing and crushing with a single kernel hardness characterization meter. Six wheat classes where represented: HRW, HRS, SRW, SWW, Durum, and Club. In this study, parameters which characterize texture or spatial distribution of gray levels of an image were determined and used to classify images of crushed wheat kernels. The texture parameters of crushed wheat kernel images were different depending on class, hardness and variety of the wheat. Image texture analysis of crushed wheat kernels showed promise for use in class, hardness, milling quality, and variety discrimination.

  12. Breast cancer histopathology image analysis: a review.

    PubMed

    Veta, Mitko; Pluim, Josien P W; van Diest, Paul J; Viergever, Max A

    2014-05-01

    This paper presents an overview of methods that have been proposed for the analysis of breast cancer histopathology images. This research area has become particularly relevant with the advent of whole slide imaging (WSI) scanners, which can perform cost-effective and high-throughput histopathology slide digitization, and which aim at replacing the optical microscope as the primary tool used by pathologist. Breast cancer is the most prevalent form of cancers among women, and image analysis methods that target this disease have a huge potential to reduce the workload in a typical pathology lab and to improve the quality of the interpretation. This paper is meant as an introduction for nonexperts. It starts with an overview of the tissue preparation, staining and slide digitization processes followed by a discussion of the different image processing techniques and applications, ranging from analysis of tissue staining to computer-aided diagnosis, and prognosis of breast cancer patients. PMID:24759275

  13. 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

  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. 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…

  16. Embodied image: gender differences in functional and aesthetic body image among Australian adolescents.

    PubMed

    Abbott, Bree D; Barber, Bonnie L

    2010-01-01

    Perceptions of the body are not restricted to the way the body "looks"; they may also extend to the way the body "functions". This research explores body image among male and female adolescents using the Embodied Image Scale (EIS), which incorporates body function into body image. Adolescents (N=1526, male=673, female=853) aged 12-17 (M=13.83, SD=1.02), from 26 Western Australian high schools were surveyed. Information was gathered on pubertal timing, body mass index (BMI) and body image. Participants reported significantly higher value of, behavioral-investment in, and satisfaction with the functional dimension of the body compared to the aesthetic dimension. After controlling for age, pubertal timing, and BMI, females reported significantly higher aesthetic values and aesthetic behavioral-investment, and lower aesthetic satisfaction, functional values, functional behavioral-investment and functional satisfaction than male participants. Grade, pubertal timing and BMI category differences were also explored. PMID:19945925

  17. Pre-clinical functional Magnetic Resonance Imaging Part II: The heart.

    PubMed

    Meßner, Nadja M; Zöllner, Frank G; Kalayciyan, Raffi; Schad, Lothar R

    2014-12-01

    One third of all deaths worldwide in 2008 were caused by cardiovascular diseases (CVD), and the incidence of CVD related deaths rises ever more. Thus, improved imaging techniques and modalities are needed for the evaluation of cardiac morphology and function. Cardiac magnetic resonance imaging (CMRI) is a minimally invasive technique that is increasingly important due to its high spatial and temporal resolution, its high soft tissue contrast and its ability of functional and quantitative imaging. It is widely accepted as the gold standard of cardiac functional analysis. In the short period of small animal MRI, remarkable progress has been achieved concerning new, fast imaging schemes as well as purpose-built equipment. Dedicated small animal scanners allow for tapping the full potential of recently developed animal models of cardiac disease. In this paper, we review state-of-the-art cardiac magnetic resonance imaging techniques and applications in small animals at ultra-high fields (UHF). PMID:25023418

  18. 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…

  19. 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.

  20. Bootstrapped DEPICT for error estimation in PET functional imaging.

    PubMed

    Kukreja, Sunil L; Gunn, Roger N

    2004-03-01

    Basis pursuit denoising is a new approach for data-driven estimation of parametric images from dynamic positron emission tomography (PET) data. At present, this kinetic modeling technique does not allow for the estimation of the errors on the parameters. These estimates are useful when performing subsequent statistical analysis, such as, inference across a group of subjects or when applying partial volume correction algorithms. The difficulty with calculating the error estimates is a consequence of using an overcomplete dictionary of kinetic basis functions. In this paper, a bootstrap approach for the estimation of parameter errors from dynamic PET data is presented. This paper shows that the bootstrap can be used successfully to compute parameter errors on a region of interest or parametric image basis. Validation studies evaluate the methods performance on simulated and measured PET data ([(11)C]Diprenorphine-opiate receptor and [(11)C]Raclopride-dopamine D(2) receptor). The method is presented in the context of PET neuroreceptor binding studies, however, it has general applicability to a wide range of PET/SPET radiotracers in neurology, oncology and cardiology. PMID:15006677

  1. 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

  2. Regional lung function and mechanics using image registration

    NASA Astrophysics Data System (ADS)

    Ding, Kai

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

  3. 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.

  4. Evaluation of ventricular function with gated cardiac magnetic resonance imaging.

    PubMed

    Osbakken, M; Yuschok, T

    1986-01-01

    To determine the feasibility of using planar images obtained with gated cardiac magnetic resonance imaging (MRI) techniques to evaluate ventricular contractile function, cardiac chamber volume (V), and ejection fraction (EF) were calculated using MR images obtained in five previously catheterized patients. Patients were imaged with a .15-Tesla 55-cm bore magnet using the ECG to gate the images. Spin echo pulse sequences (30/500, TE/TR) were used to produce images in the transverse (T), coronal (C), and sagittal (S) planes at end diastole (ED) and end systole (ES). Slice thickness was 1.5 cm, with 2-mm resolution. A calibration grid was imaged in each plane to determine correction factors. Cardiac chamber areas were determined via planimetry. An area-length-volume algorithm was used to obtain EDV and ESV. Three combinations of biplane images in ES and ED were used (T/C, T/S, C/S). Volume data were used to calculate EF. Contrast ventriculogram volumes tended to be greater than MRI volumes, but EFs were similar with both techniques. In conclusion, gated cardiac MR images can be used to evaluate the ventricular function parameters of volume and ejection fraction. PMID:3731263

  5. 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

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

    PubMed

    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

  7. 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.

  8. Deep-space satellite-image reconstructions from field data by use of speckle imaging techniques: images and functional assessment

    NASA Astrophysics Data System (ADS)

    Matson, Charles L.; Fox, Marsha; Hege, E. Keith; Hluck, Laura; Drummond, Jack; Harvey, David

    1997-05-01

    Speckle imaging techniques have been shown to mitigate atmospheric-resolution limits, allowing near-diffraction-limited images to be reconstructed. Few images of extended objects reconstructed by use of these techniques have been published, and most of these results are for relatively bright objects. We present image reconstructions of an orbiting Molniya 3 spacecraft from data collected by use of a 2.3-m ground-based telescope. The apparent brightness of the satellite was 15th visual magnitude. Power-spectrum and bispectrum speckle imaging techniques are used prior to image reconstruction to ameliorate atmospheric blurring. We discuss how these images, although poorly resolved, can be used to provide information on the satellite s functional status. It is shown that our previously published optimal algorithms produce a higher-quality image than do conventional speckle imaging methods.

  9. 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.

  10. Contrast sensitivity function calibration based on image quality prediction

    NASA Astrophysics Data System (ADS)

    Han, Yu; Cai, Yunze

    2014-11-01

    Contrast sensitivity functions (CSFs) describe visual stimuli based on their spatial frequency. However, CSF calibration is limited by the size of the sample collection and this remains an open issue. In this study, we propose an approach for calibrating CSFs that is based on the hypothesis that a precise CSF model can accurately predict image quality. Thus, CSF calibration is regarded as the inverse problem of image quality prediction according to our hypothesis. A CSF could be calibrated by optimizing the performance of a CSF-based image quality metric using a database containing images with known quality. Compared with the traditional method, this would reduce the work involved in sample collection dramatically. In the present study, we employed three image databases to optimize some existing CSF models. The experimental results showed that the performance of a three-parameter CSF model was better than that of other models. The results of this study may be helpful in CSF and image quality research.

  11. Wavelet smoothing of functional magnetic resonance images: a preliminary report

    NASA Astrophysics Data System (ADS)

    Lucier, Bradley J.

    2003-11-01

    Functional (time-dependent) Magnetic Resonance Imaging can be used to determine which parts of the brain are active during various limited activities; these parts of the brain are called activation regions. In this preliminary study we describe some experiments that are suggested from the following questions: Does one get improved results by analyzing the complex image data rather than just the real magnitude image data? Does wavelet shrinkage smoothing improve images? Should one smooth in time as well as within and between slices? If so, how should one model the relationship between time smoothness (or correlations) and spatial smoothness (or correlations). The measured data is really the Fourier coefficients of the complex image---should we remove noise in the Fourier domain before computing the complex images? In this preliminary study we describe some experiments related to these questions.

  12. Functional MR imaging of the female pelvis.

    PubMed

    Koyama, Takashi; Togashi, Kaori

    2007-06-01

    Recent developments in MR techniques have magnified the roles and potential of MRI in the female pelvis. This article reviews the techniques and clinical applications of functional MRI (fMRI) of the female pelvis, including cine MRI, diffusion-weighted MRI (DWI), and dynamic contrast-enhanced (DCE)-MRI. Cine MRI is a useful tool for evaluating uterine contractility, including sustained contraction and peristalsis, in a variety of conditions and gynecologic disorders, and for evaluating pelvic-floor weakness. DWI can demonstrate abnormal signals in pathologic foci based on differences in molecular diffusion. It also enables the quantitative evaluation of the apparent diffusion coefficient (ADC), which may be useful for distinguishing malignant from benign tissues and monitoring therapeutic outcome. DCE-MRI has the potential to improve tumor detection and local staging, and can also provide quantitative information about perfusion of the tumor, which may be useful for both monitoring therapeutic effects and predicting therapeutic outcome. Understanding the roles played by functional MR techniques in the female pelvic region is beneficial not only for determining clinical applications, but also for developing further investigations with MRI. PMID:17520731

  13. 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

  14. Image analysis tools and emerging algorithms for expression proteomics

    PubMed Central

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

    2012-01-01

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

  15. Quantitative analysis of qualitative images

    NASA Astrophysics Data System (ADS)

    Hockney, David; Falco, Charles M.

    2005-03-01

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

  16. 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

  17. 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

  18. 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

  19. 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

  20. Hippocampal shape analysis in Alzheimer's disease using functional data analysis.

    PubMed

    Epifanio, Irene; Ventura-Campos, Noelia

    2014-02-28

    The hippocampus is one of the first affected regions in Alzheimer's disease. The left hippocampi of control subjects, patients with mild cognitive impairment and patients with Alzheimer's disease are represented by spherical harmonics. Functional data analysis is used in the hippocampal shape analysis. Functional principal component analysis and functional independent component analysis are defined for multivariate functions with two arguments. A functional linear discriminant function is also defined. Comparisons with other approaches are carried out. Our functional approach gives promising results, especially in shape classification. PMID:24105806

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

    PubMed Central

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

    2015-01-01

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

  2. Membrane composition analysis by imaging mass spectrometry

    SciTech Connect

    Boxer, S G; Kraft, M L; Longo, M; Hutcheon, I D; Weber, P K

    2006-03-29

    Membranes on solid supports offer an ideal format for imaging. Secondary ion mass spectrometry (SIMS) can be used to obtain composition information on membrane-associated components. Using the NanoSIMS50, images of composition variations in membrane domains can be obtained with a lateral resolution better than 100 nm. By suitable calibration, these variations in composition can be translated into a quantitative analysis of the membrane composition. Progress towards imaging small phase-separated lipid domains, membrane-associated proteins and natural biological membranes will be described.

  3. 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.

  4. VAICo: visual analysis for image comparison.

    PubMed

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

    2013-12-01

    Scientists, engineers, and analysts are confronted with ever larger and more complex sets of data, whose analysis poses special challenges. In many situations it is necessary to compare two or more datasets. Hence there is a need for comparative visualization tools to help analyze differences or similarities among datasets. In this paper an approach for comparative visualization for sets of images is presented. Well-established techniques for comparing images frequently place them side-by-side. A major drawback of such approaches is that they do not scale well. Other image comparison methods encode differences in images by abstract parameters like color. In this case information about the underlying image data gets lost. This paper introduces a new method for visualizing differences and similarities in large sets of images which preserves contextual information, but also allows the detailed analysis of subtle variations. Our approach identifies local changes and applies cluster analysis techniques to embed them in a hierarchy. The results of this process are then presented in an interactive web application which allows users to rapidly explore the space of differences and drill-down on particular features. We demonstrate the flexibility of our approach by applying it to multiple distinct domains. PMID:24051775

  5. 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

  6. Functional connectivity magnetic resonance imaging classification of autism.

    PubMed

    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

    2011-12-01

    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 whether functional connectivity is sufficiently robust to be used as a diagnostic or prognostic metric in individual patients with autism. We obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the entire grey matter (26.4 million connections) in a well-characterized set of 40 male adolescents and young adults with autism and 40 age-, sex- and IQ-matched typically developing subjects. A single resting state blood oxygen level-dependent scan of 8 min was used for the classification in each subject. A leave-one-out classifier successfully distinguished autism from control subjects with 83% sensitivity and 75% specificity for a total accuracy of 79% (P = 1.1 × 10(-7)). In subjects <20 years of age, the classifier performed at 89% accuracy (P = 5.4 × 10(-7)). In a replication dataset consisting of 21 individuals from six families with both affected and unaffected siblings, the classifier performed at 71% accuracy (91% accuracy for subjects <20 years of age). Classification scores in subjects with autism were significantly correlated with the Social Responsiveness Scale (P = 0.05), verbal IQ (P = 0.02) and the Autism Diagnostic Observation Schedule-Generic's combined social and communication subscores (P = 0.05). An analysis of informative connections demonstrated that region of interest pairs with strongest correlation values were most abnormal in autism. Negatively correlated region of interest pairs showed higher correlation in autism (less anticorrelation), possibly representing weaker inhibitory connections, particularly for long connections (Euclidean distance >10 cm

  7. 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.

  8. Image analysis of insulation mineral fibres.

    PubMed

    Talbot, H; Lee, T; Jeulin, D; Hanton, D; Hobbs, L W

    2000-12-01

    We present two methods for measuring the diameter and length of man-made vitreous fibres based on the automated image analysis of scanning electron microscopy images. The fibres we want to measure are used in materials such as glass wool, which in turn are used for thermal and acoustic insulation. The measurement of the diameters and lengths of these fibres is used by the glass wool industry for quality control purposes. To obtain reliable quality estimators, the measurement of several hundred images is necessary. These measurements are usually obtained manually by operators. Manual measurements, although reliable when performed by skilled operators, are slow due to the need for the operators to rest often to retain their ability to spot faint fibres on noisy backgrounds. Moreover, the task of measuring thousands of fibres every day, even with the help of semi-automated image analysis systems, is dull and repetitive. The need for an automated procedure which could replace manual measurements is quite real. For each of the two methods that we propose to accomplish this task, we present the sample preparation, the microscope setting and the image analysis algorithms used for the segmentation of the fibres and for their measurement. We also show how a statistical analysis of the results can alleviate most measurement biases, and how we can estimate the true distribution of fibre lengths by diameter class by measuring only the lengths of the fibres visible in the field of view. PMID:11106965

  9. Automated eXpert Spectral Image Analysis

    Energy Science and Technology Software Center (ESTSC)

    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. Objective facial photograph analysis using imaging software.

    PubMed

    Pham, Annette M; Tollefson, Travis T

    2010-05-01

    Facial analysis is an integral part of the surgical planning process. Clinical photography has long been an invaluable tool in the surgeon's practice not only for accurate facial analysis but also for enhancing communication between the patient and surgeon, for evaluating postoperative results, for medicolegal documentation, and for educational and teaching opportunities. From 35-mm slide film to the digital technology of today, clinical photography has benefited greatly from technological advances. With the development of computer imaging software, objective facial analysis becomes easier to perform and less time consuming. Thus, while the original purpose of facial analysis remains the same, the process becomes much more efficient and allows for some objectivity. Although clinical judgment and artistry of technique is never compromised, the ability to perform objective facial photograph analysis using imaging software may become the standard in facial plastic surgery practices in the future. PMID:20511080

  11. 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.

  12. 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.

  13. Non-Harmonic Analysis Applied to Optical Coherence Tomography Imaging

    NASA Astrophysics Data System (ADS)

    Cao, Xu; Uchida, Tetsuya; Hirobayashi, Shigeki; Chong, Changho; Morosawa, Atsushi; Totsuka, Koki; Suzuki, Takuya

    2012-02-01

    A new processing technique called non-harmonic analysis (NHA) is proposed for optical coherence tomography (OCT) imaging. Conventional Fourier-domain OCT employs the discrete Fourier transform (DFT), which depends on the window function and length. The axial resolution of the OCT image, calculated by using DFT, is inversely proportional to the full width at half maximum (FWHM) of the wavelength range. The FWHM of wavelength range is limited by the sweeping range of the source in swept-source OCT and it is limited by the number of CCD pixels in spectral-domain OCT. However, the NHA process does not have such constraints; NHA can resolve high frequencies irrespective of the window function and the frame length of the sampled data. In this study, the NHA process is described and it is applied to OCT imaging. It is compared with OCT images based on the DFT. To demonstrate the benefits of using NHA for OCT, we perform OCT imaging with NHA of an onion skin. The results reveal that NHA can achieve an image resolution equivalent that of a 100-nm sweep range using a significantly reduced wavelength range. They also reveal the potential of using this technique to achieve high-resolution imaging without using a broadband source. However, the long calculation times required for NHA must be addressed if it is to be used in clinical applications.

  14. 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

  15. Image-Based Evaluation of Vascular Function and Hemodynamics

    PubMed Central

    Lee, Jongmin

    2013-01-01

    The noticeable characteristics of the blood vascular structure are the inconsistent viscosity of blood and the stiffness of the vascular wall. If we can control these two factors, we can solve more problems related to hemodynamics and vascular wall function. Understanding the properties of hemodynamics and vascular wall function may provide more information applicable to clinical practice for cardiovascular disease. The bedside techniques evaluating vascular function usually measure indirect parameters. In contrast, some medical imaging techniques provide clear and direct depictions of functional cardiovascular characteristics. In this review, image-based evaluation of hemodynamic and vascular wall functions is discussed from the perspective of blood flow velocity, flow volume, flow pattern, peripheral vascular resistance, intraluminal pressure, vascular wall stress, and wall stiffness. PMID:26587430

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

    NASA Astrophysics Data System (ADS)

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

    2011-07-01

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

  17. 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.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  20. 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.

  1. 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. PMID:23920564

  2. 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.

  3. Endoscopic image analysis in semantic space.

    PubMed

    Kwitt, R; Vasconcelos, N; Rasiwasia, N; Uhl, A; Davis, B; Häfner, M; Wrba, F

    2012-10-01

    A novel approach to the design of a semantic, low-dimensional, encoding for endoscopic imagery is proposed. This encoding is based on recent advances in scene recognition, where semantic modeling of image content has gained considerable attention over the last decade. While the semantics of scenes are mainly comprised of environmental concepts such as vegetation, mountains or sky, the semantics of endoscopic imagery are medically relevant visual elements, such as polyps, special surface patterns, or vascular structures. The proposed semantic encoding differs from the representations commonly used in endoscopic image analysis (for medical decision support) in that it establishes a semantic space, where each coordinate axis has a clear human interpretation. It is also shown to establish a connection to Riemannian geometry, which enables principled solutions to a number of problems that arise in both physician training and clinical practice. This connection is exploited by leveraging results from information geometry to solve problems such as (1) recognition of important semantic concepts, (2) semantically-focused image browsing, and (3) estimation of the average-case semantic encoding for a collection of images that share a medically relevant visual detail. The approach can provide physicians with an easily interpretable, semantic encoding of visual content, upon which further decisions, or operations, can be naturally carried out. This is contrary to the prevalent practice in endoscopic image analysis for medical decision support, where image content is primarily captured by discriminative, high-dimensional, appearance features, which possess discriminative power but lack human interpretability. PMID:22717411

  4. Endoscopic Image Analysis in Semantic Space

    PubMed Central

    Kwitt, R.; Vasconcelos, N.; Rasiwasia, N.; Uhl, A.; Davis, B.; Häfner, M.; Wrba, F.

    2013-01-01

    A novel approach to the design of a semantic, low-dimensional, encoding for endoscopic imagery is proposed. This encoding is based on recent advances in scene recognition, where semantic modeling of image content has gained considerable attention over the last decade. While the semantics of scenes are mainly comprised of environmental concepts such as vegetation, mountains or sky, the semantics of endoscopic imagery are medically relevant visual elements, such as polyps, special surface patterns, or vascular structures. The proposed semantic encoding differs from the representations commonly used in endoscopic image analysis (for medical decision support) in that it establishes a semantic space, where each coordinate axis has a clear human interpretation. It is also shown to establish a connection to Riemannian geometry, which enables principled solutions to a number of problems that arise in both physician training and clinical practice. This connection is exploited by leveraging results from information geometry to solve problems such as 1) recognition of important semantic concepts, 2) semantically-focused image browsing, and 3) estimation of the average-case semantic encoding for a collection of images that share a medically relevant visual detail. The approach can provide physicians with an easily interpretable, semantic encoding of visual content, upon which further decisions, or operations, can be naturally carried out. This is contrary to the prevalent practice in endoscopic image analysis for medical decision support, where image content is primarily captured by discriminative, high-dimensional, appearance features, which possess discriminative power but lack human interpretability. PMID:22717411

  5. 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.

  6. 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

  7. 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

  8. Noninvasive laser-induced photoacoustic tomography for structural and functional in vivo imaging of the brain.

    PubMed

    Wang, Xueding; Pang, Yongjiang; Ku, Geng; Xie, Xueyi; Stoica, George; Wang, Lihong V

    2003-07-01

    Imaging techniques based on optical contrast analysis can be used to visualize dynamic and functional properties of the nervous system via optical signals resulting from changes in blood volume, oxygen consumption and cellular swelling associated with brain physiology and pathology. Here we report in vivo noninvasive transdermal and transcranial imaging of the structure and function of rat brains by means of laser-induced photoacoustic tomography (PAT). The advantage of PAT over pure optical imaging is that it retains intrinsic optical contrast characteristics while taking advantage of the diffraction-limited high spatial resolution of ultrasound. We accurately mapped rat brain structures, with and without lesions, and functional cerebral hemodynamic changes in cortical blood vessels around the whisker-barrel cortex in response to whisker stimulation. We also imaged hyperoxia- and hypoxia-induced cerebral hemodynamic changes. This neuroimaging modality holds promise for applications in neurophysiology, neuropathology and neurotherapy. PMID:12808463

  9. Unsupervised hyperspectral image analysis using independent component analysis (ICA)

    SciTech Connect

    S. S. Chiang; I. W. Ginsberg

    2000-06-30

    In this paper, an ICA-based approach is proposed for hyperspectral image analysis. It can be viewed as a random version of the commonly used linear spectral mixture analysis, in which the abundance fractions in a linear mixture model are considered to be unknown independent signal sources. It does not require the full rank of the separating matrix or orthogonality as most ICA methods do. More importantly, the learning algorithm is designed based on the independency of the material abundance vector rather than the independency of the separating matrix generally used to constrain the standard ICA. As a result, the designed learning algorithm is able to converge to non-orthogonal independent components. This is particularly useful in hyperspectral image analysis since many materials extracted from a hyperspectral image may have similar spectral signatures and may not be orthogonal. The AVIRIS experiments have demonstrated that the proposed ICA provides an effective unsupervised technique for hyperspectral image classification.

  10. Curvelet Based Offline Analysis of SEM Images

    PubMed Central

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

    2014-01-01

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

  11. 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.

  12. 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.

  13. 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. PMID:20713305

  14. 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.

  15. 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.

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

  18. [Comparison among remotely sensed image fusion methods based on spectral response function].

    PubMed

    Dou, Wen; Sun, Hong-quan; Chen, Yun-hao

    2011-03-01

    Remotely sensed image fusion is a critical issue, and many methods have been developed to inject features from a high spatial resolution panchromatic sensor into low spatial resolution multi-spectral images, trying to preserve spectral signatures while improving spatial resolution of multi-spectral images. However, no explicit physical information of the detection system has been taken into account in usual methods, which might lead to undesirable effects such as severe spectral distortion. Benefiting from the proper decomposition of the image fusion problem by a concise image fusion mathematical model, the present paper focuses on comparing reasonable modulation coefficient of spatial details based on analysis of the spectral response function (SRF). According to the classification of former methods, three modulation coefficients based on SRF of sensors were concluded, which lead to three image fusion methods incorporating spatial detail retrieved by Gaussian high-pass filter. All these methods were validated on Ikonos data compared to GS and HPM method. PMID:21595232

  19. 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

  20. 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

  1. Morphometry of spermatozoa using semiautomatic image analysis.

    PubMed Central

    Jagoe, J R; Washbrook, N P; Hudson, E A

    1986-01-01

    Human sperm heads were detected and tracked using semiautomatic image analysis. Measurements of size and shape on two specimens from each of 26 men showed that the major component of variability both within and between subjects was the number of small elongated sperm heads. Variability of the computed features between subjects was greater than that between samples from the same subject. PMID:3805320

  2. 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…

  3. 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.

  4. Expert system for imaging spectrometer analysis results

    NASA Technical Reports Server (NTRS)

    Borchardt, Gary C.

    1985-01-01

    Information on an expert system for imaging spectrometer analysis results is outlined. Implementation requirements, the Simple Tool for Automated Reasoning (STAR) program that provides a software environment for the development and operation of rule-based expert systems, STAR data structures, and rule-based identification of surface materials are among the topics outlined.

  5. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2012-11-01

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

  7. 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.

  8. Dynamic contrast-enhanced magnetic resonance imaging: definitive imaging of placental function?

    PubMed

    Chalouhi, G E; Deloison, B; Siauve, N; Aimot, S; Balvay, D; Cuenod, C A; Ville, Y; Clément, O; Salomon, L J

    2011-02-01

    The placenta constitutes a complex circulatory interface between the mother and fetus, but the relationship between the maternal and fetal circulation is still very difficult to study in vivo. There is growing evidence that magnetic resonance imaging (MRI) is useful and safe during pregnancy, and MRI is increasingly used for fetal and placental anatomical imaging. MRI functional imaging is now a modern obstetric tool and has the potential to provide new insights into the physiology of the human placenta. Placental perfusion has been studied during the first pass of an MR contrast agent, by arterial spin labeling, diffusion imaging, T1 and T2 relaxation time measurement using echo-planar imaging, and by a combination of magnetization transfer with established stereological methods. The BOLD (blood oxygen level-dependent) effect offers new perspectives for functional MRI evaluation of the placenta. PMID:20851065

  9. 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.

  10. 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.

  11. Good relationships between computational image analysis and radiological physics

    NASA Astrophysics Data System (ADS)

    Arimura, Hidetaka; Kamezawa, Hidemi; Jin, Ze; Nakamoto, Takahiro; Soufi, Mazen

    2015-09-01

    Good relationships between computational image analysis and radiological physics have been constructed for increasing the accuracy of medical diagnostic imaging and radiation therapy in radiological physics. Computational image analysis has been established based on applied mathematics, physics, and engineering. This review paper will introduce how computational image analysis is useful in radiation therapy with respect to radiological physics.

  12. Difference image analysis: automatic kernel design using information criteria

    NASA Astrophysics Data System (ADS)

    Bramich, D. M.; Horne, Keith; Alsubai, K. A.; Bachelet, E.; Mislis, D.; Parley, N.

    2016-03-01

    We present a selection of methods for automatically constructing an optimal kernel model for difference image analysis which require very few external parameters to control the kernel design. Each method consists of two components; namely, a kernel design algorithm to generate a set of candidate kernel models, and a model selection criterion to select the simplest kernel model from the candidate models that provides a sufficiently good fit to the target image. We restricted our attention to the case of solving for a spatially invariant convolution kernel composed of delta basis functions, and we considered 19 different kernel solution methods including six employing kernel regularization. We tested these kernel solution methods by performing a comprehensive set of image simulations and investigating how their performance in terms of model error, fit quality, and photometric accuracy depends on the properties of the reference and target images. We find that the irregular kernel design algorithm employing unregularized delta basis functions, combined with either the Akaike or Takeuchi information criterion, is the best kernel solution method in terms of photometric accuracy. Our results are validated by tests performed on two independent sets of real data. Finally, we provide some important recommendations for software implementations of difference image analysis.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. ImageJ: Image processing and analysis in Java

    NASA Astrophysics Data System (ADS)

    Rasband, W. S.

    2012-06-01

    ImageJ is a public domain Java image processing program inspired by NIH Image. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. It can read many image formats including TIFF, GIF, JPEG, BMP, DICOM, FITS and "raw". It supports "stacks", a series of images that share a single window. It is multithreaded, so time-consuming operations such as image file reading can be performed in parallel with other operations.

  19. TOPICAL REVIEW: Multimodality imaging of structure and function

    NASA Astrophysics Data System (ADS)

    Townsend, D. W.

    2008-02-01

    Historically, medical devices to image either anatomical structure or functional processes have developed along somewhat independent paths. The recognition that combining images from different modalities can nevertheless offer significant diagnostic advantages gave rise to sophisticated software techniques to coregister structure and function. Recently, alternatives to retrospective software-based fusion have become available through instrumentation that combines two imaging modalities within a single device, an approach that has since been termed hardware fusion. As a result, following their recent introduction into the clinic, combined PET/CT and SPECT/CT devices are now playing an increasingly important role in the diagnosis and staging of human disease. Recently, although limited to the brain, the first clinical MR scanner with a PET insert, a technically-challenging design, has been undergoing evaluation. This review will follow the development of multimodality instrumentation for clinical use from conception to present-day technology and assess the status and future potential for such devices.

  20. Functional Connectivity Magnetic Resonance Imaging Classification of Autism

    ERIC Educational Resources Information Center

    Anderson, Jeffrey S.; Nielsen, Jared A.; Froehlich, Alyson L.; DuBray, Molly B.; Druzgal, T. Jason; Cariello, Annahir N.; Cooperrider, Jason R.; Zielinski, Brandon A.; Ravichandran, Caitlin; Fletcher, P. Thomas; Alexander, Andrew L.; Bigler, Erin D.; Lange, Nicholas; Lainhart, Janet E.

    2011-01-01

    Group differences in resting state functional magnetic resonance imaging connectivity between individuals with autism and typically developing controls have been widely replicated for a small number of discrete brain regions, yet the whole-brain distribution of connectivity abnormalities in autism is not well characterized. It is also unclear…

  1. Recent advances in morphological cell image analysis.

    PubMed

    Chen, Shengyong; Zhao, Mingzhu; Wu, Guang; Yao, Chunyan; Zhang, Jianwei

    2012-01-01

    This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed. PMID:22272215

  2. Optical image acquisition system for colony analysis

    NASA Astrophysics Data System (ADS)

    Wang, Weixing; Jin, Wenbiao

    2006-02-01

    For counting of both colonies and plaques, there is a large number of applications including food, dairy, beverages, hygiene, environmental monitoring, water, toxicology, sterility testing, AMES testing, pharmaceuticals, paints, sterile fluids and fungal contamination. Recently, many researchers and developers have made efforts for this kind of systems. By investigation, some existing systems have some problems since they belong to a new technology product. One of the main problems is image acquisition. In order to acquire colony images with good quality, an illumination box was constructed as: the box includes front lightning and back lightning, which can be selected by users based on properties of colony dishes. With the illumination box, lightning can be uniform; colony dish can be put in the same place every time, which make image processing easy. A digital camera in the top of the box connected to a PC computer with a USB cable, all the camera functions are controlled by the computer.

  3. Analysis of imaging system performance capabilities

    NASA Astrophysics Data System (ADS)

    Haim, Harel; Marom, Emanuel

    2013-06-01

    Present performance analysis of optical imaging systems based on results obtained with classic one-dimensional (1D) resolution targets (such as the USAF resolution chart) are significantly different than those obtained with a newly proposed 2D target [1]. We hereby prove such claim and show how the novel 2D target should be used for correct characterization of optical imaging systems in terms of resolution and contrast. We apply thereafter the consequences of these observations on the optimal design of some two-dimensional barcode structures.

  4. Texture Analysis of Medical Images Using the Wavelet Transform

    NASA Astrophysics Data System (ADS)

    Fernández, Margarita; Mavilio, Adriana

    2002-08-01

    Texture analysis of images can contribute to a better interpretation of medical images. This type of analysis provides not only qualitative but also quantitative information about tissue affection degree. In this work an algorithm is developed which uses the wavelet transform to carry out the supervised segmentation of echographic images corresponding to injured Achilles tendon of athletes. To construct the pattern, the image corresponding to healthy tendon tissue of the athlete, is taken as a reference based upon the duplicity of this structure. Texture features are calculated on the expansion wavelet coefficients of the images. The Mahalanobis distance between texture samples of the injured tissue and pattern texture is computed and used as the discriminating function. It is concluded that this distance, after appropriate medical calibrations, can offer quantitative information about the injury degree in every point along the damaged tissue. Further, its behavior along the segmented image can serve as a measure of the degree of change in tissue properties. The parameter, similarity degree, is defined and obtained by taking into account the correlation between distance histograms for the healthy tissue and the damaged one. It is also shown that this parameter, when properly calibrated, can offer a quantitative global evaluation of the state of the injured tissue.

  5. Phase transfer function based method to alleviate image artifacts in wavefront coding imaging system

    NASA Astrophysics Data System (ADS)

    Mo, Xutao; Wang, Jinjiang

    2013-09-01

    Wavefront coding technique can extend the depth of filed (DOF) of the incoherent imaging system. Several rectangular separable phase masks (such as cubic type, exponential type, logarithmic type, sinusoidal type, rational type, et al) have been proposed and discussed, because they can extend the DOF up to ten times of the DOF of ordinary imaging system. But according to the research on them, researchers have pointed out that the images are damaged by the artifacts, which usually come from the non-linear phase transfer function (PTF) differences between the PTF used in the image restoration filter and the PTF related to real imaging condition. In order to alleviate the image artifacts in imaging systems with wavefront coding, an optimization model based on the PTF was proposed to make the PTF invariance with the defocus. Thereafter, an image restoration filter based on the average PTF in the designed depth of field was introduced along with the PTF-based optimization. The combination of the optimization and the image restoration proposed can alleviate the artifacts, which was confirmed by the imaging simulation of spoke target. The cubic phase mask (CPM) and exponential phase mask (EPM) were discussed as example.

  6. 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

  7. 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

  8. 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.

  9. Principles of functional magnetic resonance imaging: application to auditory neuroscience.

    PubMed

    Cacace, A T; Tasciyan, T; Cousins, J P

    2000-05-01

    Functional imaging based on magnetic resonance methods is a new research frontier for exploring a wide range of central nervous system (CNS) functions, including information processing in sensory, motor, cognitive, and linguistic systems. Being able to localize and study human brain function in vivo, in relatively high resolution and in a noninvasive manner, makes this a technique of unparalleled importance. In order to appreciate and fully understand this area of investigation, a tutorial covering basic aspects of this methodology is presented. We introduce functional magnetic resonance imaging (fMRI) by providing an overview of the studies of different sensory systems in response to modality-specific stimuli, followed by an outline of other areas that have potential clinical relevance to the medical, cognitive, and communicative sciences. The discussion then focuses on the basic principles of magnetic resonance methods including magnetic resonance imaging, MR spectroscopy, fMRI, and the potential role that MR technology may play in understanding a wide range of auditory functions within the CNS, including tinnitus-related activity. Because the content of the material found herein might be unfamiliar to some, we provide a broad range of background and review articles to serve as a technical resource. PMID:10821504

  10. 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

  11. 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

  12. Human brain activity with functional NIR optical imager

    NASA Astrophysics Data System (ADS)

    Luo, Qingming

    2001-08-01

    In this paper we reviewed the applications of functional near infrared optical imager in human brain activity. Optical imaging results of brain activity, including memory for new association, emotional thinking, mental arithmetic, pattern recognition ' where's Waldo?, occipital cortex in visual stimulation, and motor cortex in finger tapping, are demonstrated. It is shown that the NIR optical method opens up new fields of study of the human population, in adults under conditions of simulated or real stress that may have important effects upon functional performance. It makes practical and affordable for large populations the complex technology of measuring brain function. It is portable and low cost. In cognitive tasks subjects could report orally. The temporal resolution could be millisecond or less in theory. NIR method will have good prospects in exploring human brain secret.

  13. 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

  14. Linear constraint minimum variance beamformer functional magnetic resonance inverse imaging

    PubMed Central

    Lin, Fa-Hsuan; Witzel, Thomas; Zeffiro, Thomas A.; Belliveau, John W.

    2011-01-01

    Accurate estimation of the timing of neural activity is required to fully model the information flow among functionally specialized regions whose joint activity underlies perception, cognition and action. Attempts to detect the fine temporal structure of task-related activity would benefit from functional imaging methods allowing higher sampling rates. Spatial filtering techniques have been used in magnetoencephalography source imaging applications. In this work, we use the linear constraint minimal variance (LCMV) beamformer localization method to reconstruct single-shot volumetric functional magnetic resonance imaging (fMRI) data using signals acquired simultaneously from all channels of a high density radio-frequency (RF) coil array. The LCMV beamformer method generalizes the existing volumetric magnetic resonance inverse imaging (InI) technique, achieving higher detection sensitivity while maintaining whole-brain spatial coverage and 100 ms temporal resolution. In this paper, we begin by introducing the LCMV reconstruction formulation and then quantitatively assess its performance using both simulated and empirical data. To demonstrate the sensitivity and inter-subject reliability of volumetric LCMV InI, we employ an event-related design to probe the spatial and temporal properties of task-related hemodynamic signal modulations in primary visual cortex. Compared to minimum-norm estimate (MNE) reconstructions, LCMV offers better localization accuracy and superior detection sensitivity. Robust results from both single subject and group analyses demonstrate the excellent sensitivity and specificity of volumetric InI in detecting the spatial and temporal structure of task-related brain activity. PMID:18672071

  15. 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.

  16. Pain related inflammation analysis using infrared images

    NASA Astrophysics Data System (ADS)

    Bhowmik, Mrinal Kanti; Bardhan, Shawli; Das, Kakali; Bhattacharjee, Debotosh; Nath, Satyabrata

    2016-05-01

    Medical Infrared Thermography (MIT) offers a potential non-invasive, non-contact and radiation free imaging modality for assessment of abnormal inflammation having pain in the human body. The assessment of inflammation mainly depends on the emission of heat from the skin surface. Arthritis is a disease of joint damage that generates inflammation in one or more anatomical joints of the body. Osteoarthritis (OA) is the most frequent appearing form of arthritis, and rheumatoid arthritis (RA) is the most threatening form of them. In this study, the inflammatory analysis has been performed on the infrared images of patients suffering from RA and OA. For the analysis, a dataset of 30 bilateral knee thermograms has been captured from the patient of RA and OA by following a thermogram acquisition standard. The thermograms are pre-processed, and areas of interest are extracted for further processing. The investigation of the spread of inflammation is performed along with the statistical analysis of the pre-processed thermograms. The objectives of the study include: i) Generation of a novel thermogram acquisition standard for inflammatory pain disease ii) Analysis of the spread of the inflammation related to RA and OA using K-means clustering. iii) First and second order statistical analysis of pre-processed thermograms. The conclusion reflects that, in most of the cases, RA oriented inflammation affects bilateral knees whereas inflammation related to OA present in the unilateral knee. Also due to the spread of inflammation in OA, contralateral asymmetries are detected through the statistical analysis.

  17. Image analysis for measuring rod network properties

    NASA Astrophysics Data System (ADS)

    Kim, Dongjae; Choi, Jungkyu; Nam, Jaewook

    2015-12-01

    In recent years, metallic nanowires have been attracting significant attention as next-generation flexible transparent conductive films. The performance of films depends on the network structure created by nanowires. Gaining an understanding of their structure, such as connectivity, coverage, and alignment of nanowires, requires the knowledge of individual nanowires inside the microscopic images taken from the film. Although nanowires are flexible up to a certain extent, they are usually depicted as rigid rods in many analysis and computational studies. Herein, we propose a simple and straightforward algorithm based on the filtering in the frequency domain for detecting the rod-shape objects inside binary images. The proposed algorithm uses a specially designed filter in the frequency domain to detect image segments, namely, the connected components aligned in a certain direction. Those components are post-processed to be combined under a given merging rule in a single rod object. In this study, the microscopic properties of the rod networks relevant to the analysis of nanowire networks were measured for investigating the opto-electric performance of transparent conductive films and their alignment distribution, length distribution, and area fraction. To verify and find the optimum parameters for the proposed algorithm, numerical experiments were performed on synthetic images with predefined properties. By selecting proper parameters, the algorithm was used to investigate silver nanowire transparent conductive films fabricated by the dip coating method.

  18. Point spread functions and deconvolution of ultrasonic images.

    PubMed

    Dalitz, Christoph; Pohle-Fröhlich, Regina; Michalk, Thorsten

    2015-03-01

    This article investigates the restoration of ultrasonic pulse-echo C-scan images by means of deconvolution with a point spread function (PSF). The deconvolution concept from linear system theory (LST) is linked to the wave equation formulation of the imaging process, and an analytic formula for the PSF of planar transducers is derived. For this analytic expression, different numerical and analytic approximation schemes for evaluating the PSF are presented. By comparing simulated images with measured C-scan images, we demonstrate that the assumptions of LST in combination with our formula for the PSF are a good model for the pulse-echo imaging process. To reconstruct the object from a C-scan image, we compare different deconvolution schemes: the Wiener filter, the ForWaRD algorithm, and the Richardson-Lucy algorithm. The best results are obtained with the Richardson-Lucy algorithm with total variation regularization. For distances greater or equal twice the near field distance, our experiments show that the numerically computed PSF can be replaced with a simple closed analytic term based on a far field approximation. PMID:25768819

  19. 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

  20. Automated analysis of investigational near-infrared fluorescence lymphatic imaging in humans

    PubMed Central

    Zhang, Jingdan; Zhou, Shaohua Kevin; Xiang, Xiaoyan; Bautista, Merrick L.; Niccum, Blake A.; Dickinson, Gabriel S.; Tan, I-Chih; Chan, Wenyaw; Sevick-Muraca, Eva M.; Rasmussen, John C.

    2012-01-01

    ALFIA (Automated Lymphatic Function Imaging Analysis), an algorithm providing quantitative analysis of investigational near-infrared fluorescence lymphatic images, is described. Images from nine human subjects were analyzed for apparent lymphatic propagation velocities and propulsion periods using manual analysis and ALFIA. While lymphatic propulsion was more easily detected using ALFIA than with manual analysis, statistical analyses indicate no significant difference in the apparent lymphatic velocities although ALFIA tended to calculate longer propulsion periods. With the base ALFIA algorithms validated, further automation can now proceed to provide a clinically relevant analytic tool for quantitatively assessing lymphatic function in humans. PMID:22808440

  1. 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. PMID:26218920

  2. SVM algorithm based on wavelet kernel function for medical image segmentation

    NASA Astrophysics Data System (ADS)

    Yang, Jun; Tian, Jinwen; Liu, Jian; Wei, Fang

    2009-10-01

    Along with more demand for 3D reconstruction, quantitative analysis and visualization, the more precise segmentation of medical image is required, especially MR head image. But the segmentation of MRI will be much more complex and difficult because of indistinct boundaries between brain tissues due to their overlapping and penetrating with each other, intrinsic uncertainty of MR images induced by heterogeneity of magnetic field, partial volume effect and noise. After studying the kernel function conditions of support vector, we constructed wavelet SVM algorithm based on wavelet kernel function. Its convergence and commonality as well as generalization are analyzed. The comparative experiments are made using the different number of training samples and the different scans, and it .The wavelet SVM can be extended easily and experiment results show that the SVM classifier offers lower computational time and better classification precision and it has good function approximation ability.

  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. 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. PMID:17706656

  5. Theoretical analysis of multispectral image segmentation criteria.

    PubMed

    Kerfoot, I B; Bresler, Y

    1999-01-01

    Markov random field (MRF) image segmentation algorithms have been extensively studied, and have gained wide acceptance. However, almost all of the work on them has been experimental. This provides a good understanding of the performance of existing algorithms, but not a unified explanation of the significance of each component. To address this issue, we present a theoretical analysis of several MRF image segmentation criteria. Standard methods of signal detection and estimation are used in the theoretical analysis, which quantitatively predicts the performance at realistic noise levels. The analysis is decoupled into the problems of false alarm rate, parameter selection (Neyman-Pearson and receiver operating characteristics), detection threshold, expected a priori boundary roughness, and supervision. Only the performance inherent to a criterion, with perfect global optimization, is considered. The analysis indicates that boundary and region penalties are very useful, while distinct-mean penalties are of questionable merit. Region penalties are far more important for multispectral segmentation than for greyscale. This observation also holds for Gauss-Markov random fields, and for many separable within-class PDFs. To validate the analysis, we present optimization algorithms for several criteria. Theoretical and experimental results agree fairly well. PMID:18267494

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. Texture image analysis: application to the classification of bovine muscles from meat slice images

    NASA Astrophysics Data System (ADS)

    Basset, Olivier; Dupont, Florent; Hernandez, Ange; Odet, Christophe; Abouelkaram, Said; Culioli, Joseph

    1999-11-01

    Image texture is analyzed to provide a series of features for the classification of several sets of images. Images of meat slices are processed to classify various samples of bovine muscle as a function of three factors: animal age, muscle and castration. The different images present a particular texture that is global representation of the connective tissue. The aim of texture analysis is to extract specific features for each kind of meat. The meat slices available for this study came from 19 animals, including 10 castrated animals. Their ages were 4 months (10 animals), 12 months (5 animals) and 16 months (4 animals). The same three muscles were studied for each animal. The texture analysis was carried out on digitized images using the first- and second-order statistics of the gray levels and morphological parameters, for the characterization of the marbling. Two classification methods were implemented: the method of a k- nearest neighbors and a method based on neural networks. Both methods give comparable results and lead to satisfactory classification of the samples in relation to the three variation factors. The correlation of the textural features with chemical and mechanical parameters measured on the meat samples is also examined. Regression experiments show that textural features have potential to indicate meat characteristics.

  12. 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.

  13. 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

  14. Hepatic functional scintigraphic imaging with 99mtechnetium galactosyl serum albumin.

    PubMed

    Kubota, Y; Kitagawa, S; Inoue, K; Ha-Kawa, S K; Kojima, M; Tanaka, Y

    1993-02-01

    99mTc-galactosyl serum albumin (GSA), a specific radiolabeled synthetic ligand for asialoglycoprotein receptors on hepatocytes, was used for functional liver imaging in 18 patients. Six patients had chronic hepatitis, and 12 had liver cirrhosis. Serial scintigraphic images were obtained for 60 minutes after intravenous administration of 1 mg of the ligand. High-quality images of the liver was obtained in all the patients. Dispersed accumulation in the liver in association with delayed clearance of the ligand from the heart was noted in cirrhotic patients. The activity of the entire liver (L) and that of the heart (H) were measured. The capacity of the liver in terms of elimination of the ligand was estimated by calculating [L/H+L] 15 and 30 minutes after the administration. [L/H+L] showed significant differences between patients with chronic hepatitis and those with liver cirrhosis, and also showed significant correlations with laboratory values such as indocyanine green clearance, prothrombin time, hepaplastin test, serum albumin level, and the Child-Turcotte classification score. 99mTc-GSA might be a useful radiopharmaceutical for obtaining hepatic functional images. PMID:8462925

  15. 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.

  16. Automated radial basis function neural network based image classification system for diabetic retinopathy detection in retinal images

    NASA Astrophysics Data System (ADS)

    Anitha, J.; Vijila, C. Kezi Selva; Hemanth, D. Jude

    2010-02-01

    Diabetic retinopathy (DR) is a chronic eye disease for which early detection is highly essential to avoid any fatal results. Image processing of retinal images emerge as a feasible tool for this early diagnosis. Digital image processing techniques involve image classification which is a significant technique to detect the abnormality in the eye. Various automated classification systems have been developed in the recent years but most of them lack high classification accuracy. Artificial neural networks are the widely preferred artificial intelligence technique since it yields superior results in terms of classification accuracy. In this work, Radial Basis function (RBF) neural network based bi-level classification system is proposed to differentiate abnormal DR Images and normal retinal images. The results are analyzed in terms of classification accuracy, sensitivity and specificity. A comparative analysis is performed with the results of the probabilistic classifier namely Bayesian classifier to show the superior nature of neural classifier. Experimental results show promising results for the neural classifier in terms of the performance measures.

  17. Functional Analysis and Intervention for Breath Holding.

    ERIC Educational Resources Information Center

    Kern, Lee; And Others

    1995-01-01

    A functional analysis of breath-holding episodes in a 7-year-old girl with severe mental retardation and Cornelia-de-Lange syndrome indicated that breath holding served an operant function, primarily to gain access to attention. Use of extinction, scheduled attention, and a picture card communication system decreased breath holding. (Author/SW)

  18. 2D imaging of functional structures in perfused pig heart

    NASA Astrophysics Data System (ADS)

    Kessler, Manfred D.; Cristea, Paul D.; Hiller, Michael; Trinks, Tobias

    2002-06-01

    In 2000 by 2D-imaging we were able for the first time to visualize in subcellular space functional structures of myocardium. For these experiments we used hemoglobin-free perfused pig hearts in our lab. Step by step we learned to understand the meaning of subcellular structures. Principally, the experiment revealed that in subcellular space very fast changes of light scattering can occur. Furthermore, coefficients of different parameters were determined on the basis of multicomponent system theory.

  19. 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

  20. Colour atlas of first pass functional imaging of the heart

    SciTech Connect

    Schad, N.; Andrews, E.J.; Fleming, J.W.

    1985-01-01

    This book contains 21 chapters. Some of the titles are: Functional imaging; Fist pass radionuclide studies in evaluation of mitral valve replacement in chronic insufficiency using Bjork-Shiley tilting disc valves; First pass radionuclide studies in evaluation of left and right ventricular function in patients with bioprosthetic mitral valve replacement after 9-11 years; and First pass radionuclide studies in the evaluation of long term (up to about 15 years) follow up of aortic valve replacement using Starr-Edwards ball prosthesis.

  1. Functional principal components analysis of workload capacity functions.

    PubMed

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

    2013-12-01

    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

  2. Applications of wavelets in morphometric analysis of medical images

    NASA Astrophysics Data System (ADS)

    Davatzikos, Christos; Tao, Xiaodong; Shen, Dinggang

    2003-11-01

    Morphometric analysis of medical images is playing an increasingly important role in understanding brain structure and function, as well as in understanding the way in which these change during development, aging and pathology. This paper presents three wavelet-based methods with related applications in morphometric analysis of magnetic resonance (MR) brain images. The first method handles cases where very limited datasets are available for the training of statistical shape models in the deformable segmentation. The method is capable of capturing a larger range of shape variability than the standard active shape models (ASMs) can, by using the elegant spatial-frequency decomposition of the shape contours provided by wavelet transforms. The second method addresses the difficulty of finding correspondences in anatomical images, which is a key step in shape analysis and deformable registration. The detection of anatomical correspondences is completed by using wavelet-based attribute vectors as morphological signatures of voxels. The third method uses wavelets to characterize the morphological measurements obtained from all voxels in a brain image, and the entire set of wavelet coefficients is further used to build a brain classifier. Since the classification scheme operates in a very-high-dimensional space, it can determine subtle population differences with complex spatial patterns. Experimental results are provided to demonstrate the performance of the proposed methods.

  3. Transthoracic Ultrafast Doppler Imaging of Human Left Ventricular Hemodynamic Function

    PubMed Central

    Osmanski, Bruno-Félix; Maresca, David; Messas, Emmanuel; Tanter, Mickael; Pernot, Mathieu

    2016-01-01

    Heart diseases can affect intraventricular blood flow patterns. Real-time imaging of blood flow patterns is challenging because it requires both a high frame rate and a large field of view. To date, standard Doppler techniques can only perform blood flow estimation with high temporal resolution within small regions of interest. In this work, we used ultrafast imaging to map in 2D human left ventricular blood flow patterns during the whole cardiac cycle. Cylindrical waves were transmitted at 4800 Hz with a transthoracic phased array probe to achieve ultrafast Doppler imaging of the left ventricle. The high spatio-temporal sampling of ultrafast imaging permits to rely on a much more effective wall filtering and to increase sensitivity when mapping blood flow patterns during the pre-ejection, ejection, early diastole, diastasis and late diastole phases of the heart cycle. The superior sensitivity and temporal resolution of ultrafast Doppler imaging makes it a promising tool for the noninvasive study of intraventricular hemodynamic function. PMID:25073134

  4. Image analysis of Renaissance copperplate prints

    NASA Astrophysics Data System (ADS)

    Hedges, S. Blair

    2008-02-01

    From the fifteenth to the nineteenth centuries, prints were a common form of visual communication, analogous to photographs. Copperplate prints have many finely engraved black lines which were used to create the illusion of continuous tone. Line densities generally are 100-2000 lines per square centimeter and a print can contain more than a million total engraved lines 20-300 micrometers in width. Because hundreds to thousands of prints were made from a single copperplate over decades, variation among prints can have historical value. The largest variation is plate-related, which is the thinning of lines over successive editions as a result of plate polishing to remove time-accumulated corrosion. Thinning can be quantified with image analysis and used to date undated prints and books containing prints. Print-related variation, such as over-inking of the print, is a smaller but significant source. Image-related variation can introduce bias if images were differentially illuminated or not in focus, but improved imaging technology can limit this variation. The Print Index, the percentage of an area composed of lines, is proposed as a primary measure of variation. Statistical methods also are proposed for comparing and identifying prints in the context of a print database.

  5. 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.

  6. Free-radical probes for functional in vivo EPR imaging

    NASA Astrophysics Data System (ADS)

    Subramanian, S.; Krishna, M. C.

    2007-02-01

    Electron paramagnetic resonance imaging (EPRI) is one of the recent functional imaging modalities that can provide valuable in vivo physiological information on its own merit and aids as a complimentary imaging technique to MRI and PET of tissues especially with respect to in vivo pO II (oxygen partial pressure), redox status and pharmacology. EPR imaging mainly deals with the measurement of distribution and in vivo dynamics and redox changes using special nontoxic paramagnetic spin probes that can be infused into the object of investigation. These spin probes should be characterized by simple EPR spectra, preferably with narrow EPR lines. The line width should be reversibly sensitive to the concentration of in vivo pO II with a linear dependence. Several non-toxic paramagnetic probes, some particulate and insoluble and others water-soluble and infusible (by intravenous or intramuscular injection) have been developed which can be effectively used to quantitatively assess tissue redox status, and tumor hypoxia. Quantitative assessment of the redox status of tissue in vivo is important in investigating oxidative stress, and that of tissue pO II is very important in radiation oncology. Other areas in which EPR imaging and oxymetry may help are in the investigation of tumorangiogenesis, wound healing, oxygenation of tumor tissue by the ingestion of oxygen-rich gases, etc. The correct choice of the spin probe will depend on the modality of measurement (whether by CW or time-domain EPR imaging) and the particular physiology interrogated. Examples of the available spin probes and some EPR imaging applications employing them are presented.

  7. Functional-anatomical image fusion in neuroendocrine tumors.

    PubMed

    Schillaci, Orazio

    2004-02-01

    Nuclear medicine provides physiologic and functional data for normal and pathologic organs but often the clear definition of the sites of radiotracers' uptake are difficult. Radiological methods are able to identify structural changes in a detailed way, but do not give precise information on function of organs or pathologic lesions. The registration and fusion of nuclear medicine studies with structural information obtained by radiological exams allows the precise correlation of functional and anatomical data. Software-based fusion of independently performed nuclear medicine and morphologic studies is uncertain of success and the alignment procedures are labor intensive. Recently, a new imaging device combining a dual-head, variable angle gamma camera with a low-dose x-ray tube has been introduced; the acquired single-photon emission computed tomography (SPECT) and x-ray computed tomography (CT) images are coregistered by means of the hardware in the same session. This new technology can be particularly useful when applied to scintigraphic procedures in neuroendocrine tumors. In-111 pentetreotide and radiolabeled MIBG play an important role in the study of patients with these tumors; the addition of anatomical maps provides a precise localization of SPECT findings and allows the exclusion of disease in sites of physiologic tracer uptake. SPECT/CT fused images are able to provide additional information that improves the accuracy of SPECT interpretation and leads to changes in therapeutic options, so enhancing the clinical role of nuclear medicine in evaluating patients with neuroendocrine tumors. PMID:15068621

  8. 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

  9. Three Systems of Insular Functional Connectivity Identified with Cluster Analysis

    PubMed Central

    Pitskel, Naomi B.; Pelphrey, Kevin A.

    2011-01-01

    Despite much research on the function of the insular cortex, few studies have investigated functional subdivisions of the insula in humans. The present study used resting-state functional connectivity magnetic resonance imaging (MRI) to parcellate the human insular lobe based on clustering of functional connectivity patterns. Connectivity maps were computed for each voxel in the insula based on resting-state functional MRI (fMRI) data and segregated using cluster analysis. We identified 3 insular subregions with distinct patterns of connectivity: a posterior region, functionally connected with primary and secondary somatomotor cortices; a dorsal anterior to middle region, connected with dorsal anterior cingulate cortex, along with other regions of a previously described control network; and a ventral anterior region, primarily connected with pregenual anterior cingulate cortex. Applying these regions to a separate task data set, we found that dorsal and ventral anterior insula responded selectively to disgusting images, while posterior insula did not. These results demonstrate that clustering of connectivity patterns can be used to subdivide cerebral cortex into anatomically and functionally meaningful subregions; the insular regions identified here should be useful in future investigations on the function of the insula. PMID:21097516

  10. TWave: high-order analysis of functional MRI.

    PubMed

    Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B

    2011-09-15

    The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with "high-order" structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the

  11. 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.

  12. Teleseismic receiver function imaging of the Pacific Northwest, United States

    NASA Astrophysics Data System (ADS)

    Eager, Kevin Charles

    The origins of widespread Cenozoic tectonomagmatism in the Pacific Northwest, United States likely involve complex dynamics including subduction of the Juan de Fuca plate and mantle upwelling processes, all of which are reflected in the crust and upper mantle. To provide an improved understanding of these processes, I analyze P-to- S converted phases using the receiver function method to image topographic variations on regional seismic discontinuities in the upper mantle, which provides constraints on mantle thermal structure, and the crust-mantle interface, which provides constraints on crustal thickness and composition. My results confirm complexity in the Juan de Fuca slab structure as found by regional tomographic studies, including limited evidence of the slab penetrating the transition zone between the 410 and 660 km discontinuities. Evidence is inconclusive for a simple mantle plume beneath the central Oregon High Lava Plains, but indicates a regional increase in mantle temperatures stretching to the east. This result implies the inflow of warm material, either from around the southern edge of the Juan de Fuca plate as it descends into the mantle, or from a regional upwelling to the east related to the Yellowstone hotspot. Results for regional crustal structure reveal thin (˜31 km) crust beneath the High Lava Plains relative to surrounding regions that exhibit thicker (35+ km) crust. The thick (≥ 40 km) crust of the Owyhee Plateau has a sharp western boundary and normal Poisson's ratio, a measure of crustal composition. I find a slightly thickened crust and low Poisson's ratio between Steens Mountain and the Owyhee Plateau, consistent with residuum from source magma of the Steens flood basalts. Central and southern Oregon exhibit very high Poisson's ratios and low velocity zones within the crust, suggesting a degree of intracrustal partial melt not seen along the center of the age-progressive High Lava Plains magmatic track, perhaps due to crustal melt

  13. 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

  14. 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. PMID:23892066

  15. 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.

  16. 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.

  17. 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

  18. Evaluation of Multivalent, Functional Polymeric Nanoparticles for Imaging Applications

    PubMed Central

    Shokeen, Monica; Pressly, Eric D.; Hagooly, Aviv; Zheleznyak, Alexander; Ramos, Nicholas; Fiamengo, Ashley L.; Welch, Michael J.; Hawker, Craig J.; Anderson, Carolyn J.

    2011-01-01

    A series of multivalent, functional polymer nanoparticles with diagnostic/imaging units and targeting ligands for molecular targeting were synthesized with the loading of the chain end functionalized, GRGDS peptide targeting sequence (model system based on integrin αvβ3) ranging from 0 to 50%. Accurate structural and functional group control in these systems was achieved through a modular approach involving the use of multiple functionalized macromonomer/monomer units combined with living free radical polymerization. In cellulo results show an increase in uptake in αvβ3 integrin-positive U87MG glioblastoma cells with increasing RGD loading and a possible upper limit on the effectiveness of the number of RGD peptides for targeting αvβ3 integrin. Significantly, this increased targeting efficiency is coupled with in vivo biodistribution results which show decreased blood circulation and increased liver uptake with increasing RGD loading. The results demonstrate the importance of controlling ligand loading in order to achieve optimal performance for therapeutic and imaging applications for multivalent nanoparticle based systems. PMID:21275414

  19. Analysis of katabatic flow using infrared imaging

    NASA Astrophysics Data System (ADS)

    Grudzielanek, M.; Cermak, J.

    2013-12-01

    We present a novel high-resolution IR method which is developed, tested and used for the analysis of katabatic flow. Modern thermal imaging systems allow for the recording of infrared picture sequences and thus the monitoring and analysis of dynamic processes. In order to identify, visualize and analyze dynamic air flow using infrared imaging, a highly reactive 'projection' surface is needed along the air flow. Here, a design for these types of analysis is proposed and evaluated. Air flow situations with strong air temperature gradients and fluctuations, such as katabatic flow, are particularly suitable for this new method. The method is applied here to analyze nocturnal cold air flows on gentle slopes. In combination with traditional methods the vertical and temporal dynamics of cold air flow are analyzed. Several assumptions on cold air flow dynamics can be confirmed explicitly for the first time. By observing the cold air flow in terms of frequency, size and period of the cold air fluctuations, drops are identified and organized in a newly derived classification system of cold air flow phases. In addition, new flow characteristics are detected, like sharp cold air caps and turbulence inside the drops. Vertical temperature gradients inside cold air drops and their temporal evolution are presented in high resolution Hovmöller-type diagrams and sequenced time lapse infrared videos.

  20. 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

  1. Functional Nonlinear Mixed Effects Models For Longitudinal Image Data

    PubMed Central

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

    2015-01-01

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

  2. Research on automatic human chromosome image analysis

    NASA Astrophysics Data System (ADS)

    Ming, Delie; Tian, Jinwen; Liu, Jian

    2007-11-01

    Human chromosome karyotyping is one of the essential tasks in cytogenetics, especially in genetic syndrome diagnoses. In this thesis, an automatic procedure is introduced for human chromosome image analysis. According to different status of touching and overlapping chromosomes, several segmentation methods are proposed to achieve the best results. Medial axis is extracted by the middle point algorithm. Chromosome band is enhanced by the algorithm based on multiscale B-spline wavelets, extracted by average gray profile, gradient profile and shape profile, and calculated by the WDD (Weighted Density Distribution) descriptors. The multilayer classifier is used in classification. Experiment results demonstrate that the algorithms perform well.

  3. 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…

  4. 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

  5. Functional Imaging of the Developing Brain at the Bedside Using Diffuse Optical Tomography.

    PubMed

    Ferradal, Silvina L; Liao, Steve M; Eggebrecht, Adam T; Shimony, Joshua S; Inder, Terrie E; Culver, Joseph P; Smyser, Christopher D

    2016-04-01

    While histological studies and conventional magnetic resonance imaging (MRI) investigations have elucidated the trajectory of structural changes in the developing brain, less is known regarding early functional cerebral development. Recent investigations have demonstrated that resting-state functional connectivity MRI (fcMRI) can identify networks of functional cerebral connections in infants. However, technical and logistical challenges frequently limit the ability to perform MRI scans early or repeatedly in neonates, particularly in those at greatest risk for adverse neurodevelopmental outcomes. High-density diffuse optical tomography (HD-DOT), a portable imaging modality, potentially enables early continuous and quantitative monitoring of brain function in infants. We introduce an HD-DOT imaging system that combines advancements in cap design, ergonomics, and data analysis methods to allow bedside mapping of functional brain development in infants. In a cohort of healthy, full-term neonates scanned within the first days of life, HD-DOT results demonstrate strong congruence with those obtained using co-registered, subject-matched fcMRI and reflect patterns of typical brain development. These findings represent a transformative advance in functional neuroimaging in infants, and introduce HD-DOT as a powerful and practical method for quantitative mapping of early functional brain development in normal and high-risk neonates. PMID:25595183

  6. Functional brain imaging in Sydenham's chorea and streptococcal tic disorders.

    PubMed

    Citak, Elvan Caglar; Gücüyener, Kivilcim; Karabacak, Nese Ilgin; Serdaroğlu, Ayşe; Okuyaz, Cetin; Aydin, Kurşad

    2004-05-01

    Group A streptococcal infections cause a wide range of neuropsychiatric disorders, such as Sydenham's chorea, tics, obsessive-compulsive disorders, and pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections (PANDAS). Structural (computed tomography and magnetic resonance imaging) and functional (positron emission tomography, single-photon emission computed tomography) imaging studies in patients with Sydenham's chorea have suggested reversible striatal abnormalities. The objective of this study was to investigate the cerebral perfusion patterns of the subcortical structures by using hexamethylpropylenamine oxime single-photon emission computed tomography (HMPAO-SPECT) in seven cases of Sydenham's chorea and two cases of streptococcal tic disorder. HMPAO-SPECT studies revealed a hyperperfusion pattern in two and a hypoperfusion pattern in five of the chorea patients and in two patients with tic disorder. The results are discussed in relation to the duration and severity of the symptoms and the response to therapy. Functional imaging findings can be variable in Sydenham's chorea, and hyperperfusion of the striatum and thalamus could be an indicator of the response to therapy and the severity of symptoms. However, the number of cases so far investigated by either SPECT or positron emission tomography is still too limited to draw any firm conclusions. PMID:15224712

  7. 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.

  8. Modelling human musculoskeletal functional movements using ultrasound imaging

    PubMed Central

    2010-01-01

    Background A widespread and fundamental assumption in the health sciences is that muscle functions are related to a wide variety of conditions, for example pain, ischemic and neurological disorder, exercise and injury. It is therefore highly desirable to study musculoskeletal contributions in clinical applications such as the treatment of muscle injuries, post-surgery evaluations, monitoring of progressive degeneration in neuromuscular disorders, and so on. The spatial image resolution in ultrasound systems has improved tremendously in the last few years and nowadays provides detailed information about tissue characteristics. It is now possible to study skeletal muscles in real-time during activity. Methods The ultrasound images are transformed to be congruent and are effectively compressed and stacked in order to be analysed with multivariate techniques. The method is applied to a relevant clinical orthopaedic research field, namely to describe the dynamics in the Achilles tendon and the calf during real-time movements. Results This study introduces a novel method to medical applications that can be used to examine ultrasound image sequences and to detect, visualise and quantify skeletal muscle dynamics and functions. Conclusions This new objective method is a powerful tool to use when visualising tissue activity and dynamics of musculoskeletal ultrasound registrations. PMID:20492648

  9. 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.

  10. Whole-central nervous system functional imaging in larval Drosophila

    PubMed Central

    Lemon, William C.; Pulver, Stefan R.; Höckendorf, Burkhard; McDole, Katie; Branson, Kristin; Freeman, Jeremy; Keller, Philipp J.

    2015-01-01

    Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord. PMID:26263051

  11. 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

  12. 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

  13. Disrupted Brain Functional Network in Internet Addiction Disorder: A Resting-State Functional Magnetic Resonance Imaging Study

    PubMed Central

    Yap, Pew-Thian; Wu, Guorong; Shi, Feng; Price, True; Du, Yasong; Xu, Jianrong; Zhou, Yan; Shen, Dinggang

    2014-01-01

    Internet addiction disorder (IAD) is increasingly recognized as a mental health disorder, particularly among adolescents. The pathogenesis associated with IAD, however, remains unclear. In this study, we aim to explore the encephalic functional characteristics of IAD adolescents at rest using functional magnetic resonance imaging data. We adopted a graph-theoretic approach to investigate possible disruptions of functional connectivity in terms of network properties including small-worldness, efficiency, and nodal centrality on 17 adolescents with IAD and 16 socio-demographically matched healthy controls. False discovery rate-corrected parametric tests were performed to evaluate the statistical significance of group-level network topological differences. In addition, a correlation analysis was performed to assess the relationships between functional connectivity and clinical measures in the IAD group. Our results demonstrate that there is significant disruption in the functional connectome of IAD patients, particularly between regions located in the frontal, occipital, and parietal lobes. The affected connections are long-range and inter-hemispheric connections. Although significant alterations are observed for regional nodal metrics, there is no difference in global network topology between IAD and healthy groups. In addition, correlation analysis demonstrates that the observed regional abnormalities are correlated with the IAD severity and behavioral clinical assessments. Our findings, which are relatively consistent between anatomically and functionally defined atlases, suggest that IAD causes disruptions of functional connectivity and, importantly, that such disruptions might link to behavioral impairments. PMID:25226035

  14. 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

  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. PMID:27075850

  16. 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.

  17. Image reconstruction from Pulsed Fast Neutron Analysis

    NASA Astrophysics Data System (ADS)

    Bendahan, Joseph; Feinstein, Leon; Keeley, Doug; Loveman, Rob

    1999-06-01

    Pulsed Fast Neutron Analysis (PFNA) has been demonstrated to detect drugs and explosives in trucks and large cargo containers. PFNA uses a collimated beam of nanosecond-pulsed fast neutrons that interact with the cargo contents to produce gamma rays characteristic to their elemental composition. By timing the arrival of the emitted radiation to an array of gamma-ray detectors a three-dimensional elemental density map or image of the cargo is created. The process to determine the elemental densities is complex and requires a number of steps. The first step consists of extracting from the characteristic gamma-ray spectra the counts associated with the elements of interest. Other steps are needed to correct for physical quantities such as gamma-ray production cross sections and angular distributions. The image processing includes also phenomenological corrections that take into account the neutron attenuation through the cargo, and the attenuation of the gamma rays from the point they were generated to the gamma-ray detectors. Additional processing is required to map the elemental densities from the data acquisition system of coordinates to a rectilinear system. This paper describes the image processing used to compute the elemental densities from the counts observed in the gamma-ray detectors.

  18. Image reconstruction from Pulsed Fast Neutron Analysis

    SciTech Connect

    Bendahan, Joseph; Feinstein, Leon; Keeley, Doug; Loveman, Rob

    1999-06-10

    Pulsed Fast Neutron Analysis (PFNA) has been demonstrated to detect drugs and explosives in trucks and large cargo containers. PFNA uses a collimated beam of nanosecond-pulsed fast neutrons that interact with the cargo contents to produce gamma rays characteristic to their elemental composition. By timing the arrival of the emitted radiation to an array of gamma-ray detectors a three-dimensional elemental density map or image of the cargo is created. The process to determine the elemental densities is complex and requires a number of steps. The first step consists of extracting from the characteristic gamma-ray spectra the counts associated with the elements of interest. Other steps are needed to correct for physical quantities such as gamma-ray production cross sections and angular distributions. The image processing includes also phenomenological corrections that take into account the neutron attenuation through the cargo, and the attenuation of the gamma rays from the point they were generated to the gamma-ray detectors. Additional processing is required to map the elemental densities from the data acquisition system of coordinates to a rectilinear system. This paper describes the image processing used to compute the elemental densities from the counts observed in the gamma-ray detectors.

  19. 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.

  20. Noise analysis in laser speckle contrast imaging

    NASA Astrophysics Data System (ADS)

    Yuan, Shuai; Chen, Yu; Dunn, Andrew K.; Boas, David A.

    2010-02-01

    Laser speckle contrast imaging (LSCI) is becoming an established method for full-field imaging of blood flow dynamics in animal models. A reliable quantitative model with comprehensive noise analysis is necessary to fully utilize this technique in biomedical applications and clinical trials. In this study, we investigated several major noise sources in LSCI: periodic physiology noise, shot noise and statistical noise. (1) We observed periodic physiology noise in our experiments and found that its sources consist principally of motions induced by heart beats and/or ventilation. (2) We found that shot noise caused an offset of speckle contrast (SC) values, and this offset is directly related to the incident light intensity. (3) A mathematical model of statistical noise was also developed. The model indicated that statistical noise in speckle contrast imaging is related to the SC values and the total number of pixels used in the SC calculation. Our experimental results are consistent with theoretical predications, as well as with other published works.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. Analysis of image quality based on perceptual preference

    NASA Astrophysics Data System (ADS)

    Xue, Liqin; Hua, Yuning; Zhao, Guangzhou; Qi, Yaping

    2007-11-01

    This paper deals with image quality analysis considering the impact of psychological factors involved in assessment. The attributes of image quality requirement were partitioned according to the visual perception characteristics and the preference of image quality were obtained by the factor analysis method. The features of image quality which support the subjective preference were identified, The adequacy of image is evidenced to be the top requirement issues to the display image quality improvement. The approach will be beneficial to the research of the image quality subjective quantitative assessment method.

  7. 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.

  8. REGULARIZED 3D FUNCTIONAL REGRESSION FOR BRAIN IMAGE DATA VIA HAAR WAVELETS

    PubMed Central

    Wang, Xuejing; Nan, Bin; Zhu, Ji; Koeppe, Robert

    2015-01-01

    The primary motivation and application in this article come from brain imaging studies on cognitive impairment in elderly subjects with brain disorders. We propose a regularized Haar wavelet-based approach for the analysis of three-dimensional brain image data in the framework of functional data analysis, which automatically takes into account the spatial information among neighboring voxels. We conduct extensive simulation studies to evaluate the prediction performance of the proposed approach and its ability to identify related regions to the outcome of interest, with the underlying assumption that only few relatively small subregions are truly predictive of the outcome of interest. We then apply the proposed approach to searching for brain subregions that are associated with cognition using PET images of patients with Alzheimer’s disease, patients with mild cognitive impairment, and normal controls. PMID:26082826

  9. Multilevel sparse functional principal component analysis.

    PubMed

    Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

    2014-01-29

    We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal co