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Sample records for functional image analysis

  1. Functional data analysis in brain imaging studies.

    PubMed

    Tian, Tian Siva

    2010-01-01

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

  2. 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.

  3. Technical considerations for functional magnetic resonance imaging analysis.

    PubMed

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

    2014-11-01

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

  4. Atlas-assisted localization analysis of functional images.

    PubMed

    Nowinski, W L; Thirunavuukarasuu, A

    2001-09-01

    This paper introduces a method for localization analysis of functional images assisted by a brain atlas. The usefulness of the system developed, based on this method, is analyzed for human brain mapping and neuroradiology. We use an enhanced and extended electronic Talairach-Tournoux brain atlas, containing segmented and labeled subcortical structures, Brodmann's areas, and gyri. The brain atlas serves as a tool for anatomy referencing, segmentation, labeling, registration, and providing 3D anatomical relationships. The process of localization analysis is decomposed into five steps: data loading, feature extraction, data normalization, identification and editing of loci, and getting labels and values. This analysis is supported by near real-time data-to-atlas warping based on the Talairach transformation. Metanalysis is enabled by merging the current and external lists of activation loci. We have designed, developed, tested, and deployed a commercial system for atlas-assisted localization analysis of functional images. This is the first system where an electronic version of the Talairach-Tournoux brain atlas is used interactively for analysis of functional images. This system runs on personal computers and provides functions for a rapid normalization of anatomical and functional volumetric data, data segmentation and labeling, readout of Talairach coordinates, and data display. It also is empowered with several unique features including: interactive warping facilitating fine tuning of the data-to-atlas fit, a backtracking mechanism to compensate for missing landmarks and enhancing the outcome of the overall process of data analysis, navigation on the triplanar formed by the data and the atlas, multiple-images-in-one display with atlas-anatomy-function blending, a fast locus-controlled generation of results, editing of loci, multiple label display, and saving and reading of loci. The system normalizes a single image in near real-time (0.7 s), so analysis of

  5. 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.

  6. Sensitivity analysis of near-infrared functional lymphatic imaging

    PubMed Central

    Weiler, Michael; Kassis, Timothy

    2012-01-01

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

  7. Distributed approximating functionals, wavelet analysis and image processing

    NASA Astrophysics Data System (ADS)

    Tan, Zhemin

    This work deals with the fundamental, mathematical properties and the applications of the Distributed Approximating Functionals. In the first part, different DAFs are discussed, the general formalism and the basic properties of the well-tempered DAFs, the interpolating DAFs and the Sine-DAFs are provided. The DAFs have the ability to approximate a function and its derivatives with a controllable accuracy is the principal reason for their successful applications in solving PDEs, in wavelet analysis and signal processing. The second part concerns the basic properties of Hermite DAFs. As an approximating low pass filter, its properties on the high pass band, low pass band, and transition band are presented. With properly chosen parameters, the HDAFs can make an infinite approximation to the ideal low pass filter, but with more good quality in the time and frequency domain. We also proved the HDAFs are infinitely approximate to 1/2 at the inflection point. In the third part, the low pass filter obtained from the periodization of the HDAF and normalization at the frequency zero and pi is proved to be an interpolating filter, and this is a good start to construct the interpolating wavelets. Then we presented the decay of the refinement function. In the last part of this dissertation, the theory is implemented in the field of image processing. Based on the well tempered property of HDAF and the iterative method, a new algorithm is used to restore the impulse noise corrupted images.

  8. Diaphragm postural function analysis using magnetic resonance imaging.

    PubMed

    Vostatek, Pavel; Novák, Daniel; Rychnovský, Tomas; Rychnovská, Sarka

    2013-01-01

    We present a postural analysis of diaphragm function using magnetic resonance imaging (MRI). The main aim of the study was to identify changes in diaphragm motion and shape when postural demands on the body were increased (loading applied to a distal part of the extended lower extremities against the flexion of the hips was used). Sixteen healthy subjects were compared with 17 subjects suffering from chronic low back pain and in whom structural spine disorders had been identified. Two sets of features were calculated from MRI recordings: dynamic parameters reflecting diaphragm action, and static parameters reflecting diaphragm anatomic characteristics. A statistical analysis showed that the diaphragm respiratory and postural changes were significantly slower, bigger in size and better balanced in the control group. When a load was applied to the lower limbs, the pathological subjects were mostly not able to maintain the respiratory diaphragm function, which was lowered significantly. Subjects from the control group showed more stable parameters of both respiratory and postural function. Our findings consistently affirmed worse muscle cooperation in the low back pain population subgroup. A clear relation with spinal findings and with low back pain remains undecided, but various findings in the literature were confirmed. The most important finding is the need to further address various mechanisms used by patients to compensate deep muscle insufficiency.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  11. Statistical analysis of dynamic sequences for functional imaging

    NASA Astrophysics Data System (ADS)

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

    2000-04-01

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

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

    PubMed

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

    2013-07-01

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

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

    NASA Astrophysics Data System (ADS)

    Hénault, François; Carlotti, Alexis; Vérinaud, Christophe

    2016-07-01

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

  14. 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.

  15. 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.

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

    PubMed

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

    2011-01-01

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

  17. Quality parameters analysis of optical imaging systems with enhanced focal depth using the Wigner distribution function

    PubMed

    Zalvidea; Colautti; Sicre

    2000-05-01

    An analysis of the Strehl ratio and the optical transfer function as imaging quality parameters of optical elements with enhanced focal length is carried out by employing the Wigner distribution function. To this end, we use four different pupil functions: a full circular aperture, a hyper-Gaussian aperture, a quartic phase plate, and a logarithmic phase mask. A comparison is performed between the quality parameters and test images formed by these pupil functions at different defocus distances.

  18. IMAGING OF BRAIN FUNCTION BASED ON THE ANALYSIS OF FUNCTIONAL CONNECTIVITY - IMAGING ANALYSIS OF BRAIN FUNCTION BY FMRI AFTER ACUPUNCTURE AT LR3 IN HEALTHY INDIVIDUALS.

    PubMed

    Zheng, Yu; Wang, Yuying; Lan, Yujun; Qu, Xiaodong; Lin, Kelin; Zhang, Jiping; Qu, Shanshan; Wang, Yanjie; Tang, Chunzhi; Huang, Yong

    2016-01-01

    This Study observed the relevant brain areas activated by acupuncture at the Taichong acupoint (LR3) and analyzed the functional connectivity among brain areas using resting state functional magnetic resonance imaging (fMRI) to explore the acupoint specificity of the Taichong acupoint. A total of 45 healthy subjects were randomly divided into the Taichong (LR3) group, sham acupuncture group and sham acupoint group. Subjects received resting state fMRI before acupuncture, after true (sham) acupuncture in each group. Analysis of changes in connectivity among the brain areas was performed using the brain functional connectivity method. The right cerebrum temporal lobe was selected as the seed point to analyze the functional connectivity. It had a functional connectivity with right cerebrum superior frontal gyrus, limbic lobe cingulate gyrus and left cerebrum inferior temporal gyrus (BA 37), inferior parietal lobule compared by before vs. after acupuncture at LR3, and right cerebrum sub-lobar insula and left cerebrum middle frontal gyrus, medial frontal gyrus compared by true vs. sham acupuncture at LR3, and right cerebrum occipital lobe cuneus, occipital lobe sub-gyral, parietal lobe precuneus and left cerebellum anterior lobe culmen by acupuncture at LR3 vs. sham acupoint. Acupuncture at LR3 mainly specifically activated the brain functional network that participates in visual function, associative function, and emotion cognition, which are similar to the features on LR3 in tradition Chinese medicine. These brain areas constituted a neural network structure with specific functions that had specific reference values for the interpretation of the acupoint specificity of the Taichong acupoint.

  19. 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

  20. Spatial independent component analysis of functional brain optical imaging

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  1. Image compression for functional imaging

    NASA Astrophysics Data System (ADS)

    Feng, Dagan D.; Li, Xianjin; Siu, Wan-Chi

    1997-04-01

    Function imaging has been playing an important role in modern biomedical research and clinical diagnosis, which provides human internal biochemical information previously not available. However, for a routine dynamic study with a typical medical function imaging system, such as positron emission tomography (PET), it is easily to acquire nearly 1000 images for just one patient in one study. Such a large number of images has given a considerable burden for computer image storage space, data processing and transmission time. In this paper, we present the theory and principles for the minimization of image frames in dynamic biomedical function imaging. We show that the minimum number of image frames required is just equal to the model identifiable parameters and that the quality of the physiological parameter estimation, based on these minimum number of image frames, can be controlled at a comparable level. As a result of our study, the image storage space required can be reduced by more than 80 percent.

  2. Statistical synthesis of sharpness functions for adaptation of optical systems: I. Sharpness functions with analysis in the image plane

    SciTech Connect

    Mal`tsev, G.N.

    1995-11-01

    Methods of the theory of statistical solutions are used to synthesize optimum sharpness functions for adaptation of imaging optical systems. Optimum sharpness functions mean that their extreme values give adequate estimates of the maximum likelihood of virtual phase distortions. It is shown that the synthesized optimum sharpness functions with an analysis in the image plane are rather sensitive to the amount of a priori data and may be used to observe spatially bounded objects on the condition that their shape is known. 10 refs., 1 fig.

  3. False dyssynchrony: problem with image-based cardiac functional analysis using x-ray computed tomography

    NASA Astrophysics Data System (ADS)

    Kidoh, Masafumi; Shen, Zeyang; Suzuki, Yuki; Ciuffo, Luisa; Ashikaga, Hiroshi; Fung, George S. K.; Otake, Yoshito; Zimmerman, Stefan L.; Lima, Joao A. C.; Higuchi, Takahiro; Lee, Okkyun; Sato, Yoshinobu; Becker, Lewis C.; Fishman, Elliot K.; Taguchi, Katsuyuki

    2017-03-01

    We have developed a digitally synthesized patient which we call "Zach" (Zero millisecond Adjustable Clinical Heart) phantom, which allows for an access to the ground truth and assessment of image-based cardiac functional analysis (CFA) using CT images with clinically realistic settings. The study using Zach phantom revealed a major problem with image-based CFA: "False dyssynchrony." Even though the true motion of wall segments is in synchrony, it may appear to be dyssynchrony with the reconstructed cardiac CT images. It is attributed to how cardiac images are reconstructed and how wall locations are updated over cardiac phases. The presence and the degree of false dyssynchrony may vary from scan-to-scan, which could degrade the accuracy and the repeatability (or precision) of image-based CT-CFA exams.

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

    PubMed

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

    2012-06-01

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

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

    PubMed

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

    2014-10-01

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

  6. 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.

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

    PubMed

    Merwa, Robert; Scharfetter, Hermann

    2007-07-01

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

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

    PubMed

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

    2013-11-12

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

  9. 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

  10. 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.

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

    PubMed

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

    2001-11-01

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

  12. Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures.

    PubMed

    Wong, Kelvin K L; Wang, Defeng; Ko, Jacky K L; Mazumdar, Jagannath; Le, Thu-Thao; Ghista, Dhanjoo

    2017-03-21

    Cardiac dysfunction constitutes common cardiovascular health issues in the society, and has been an investigation topic of strong focus by researchers in the medical imaging community. Diagnostic modalities based on echocardiography, magnetic resonance imaging, chest radiography and computed tomography are common techniques that provide cardiovascular structural information to diagnose heart defects. However, functional information of cardiovascular flow, which can in fact be used to support the diagnosis of many cardiovascular diseases with a myriad of hemodynamics performance indicators, remains unexplored to its full potential. Some of these indicators constitute important cardiac functional parameters affecting the cardiovascular abnormalities. With the advancement of computer technology that facilitates high speed computational fluid dynamics, the realization of a support diagnostic platform of hemodynamics quantification and analysis can be achieved. This article reviews the state-of-the-art medical imaging and high fidelity multi-physics computational analyses that together enable reconstruction of cardiovascular structures and hemodynamic flow patterns within them, such as of the left ventricle (LV) and carotid bifurcations. The combined medical imaging and hemodynamic analysis enables us to study the mechanisms of cardiovascular disease-causing dysfunctions, such as how (1) cardiomyopathy causes left ventricular remodeling and loss of contractility leading to heart failure, and (2) modeling of LV construction and simulation of intra-LV hemodynamics can enable us to determine the optimum procedure of surgical ventriculation to restore its contractility and health This combined medical imaging and hemodynamics framework can potentially extend medical knowledge of cardiovascular defects and associated hemodynamic behavior and their surgical restoration, by means of an integrated medical image diagnostics and hemodynamic performance analysis framework.

  13. Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data

    PubMed Central

    Wang, Yinxue; Shi, Guilai; Miller, David J.; Wang, Yizhi; Wang, Congchao; Broussard, Gerard; Wang, Yue; Tian, Lin; Yu, Guoqiang

    2017-01-01

    Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca2+ indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function. Current practice is essentially manual, which not only limits analysis throughput but also risks introducing bias and missing important information latent in complex, dynamic big data. Here, we report a suite of computational tools, called Functional AStrocyte Phenotyping (FASP), for automatically quantifying the functional status of astrocytes. Considering the complex nature of Ca2+ signaling in astrocytes and low signal to noise ratio, FASP is designed with data-driven and probabilistic principles, to flexibly account for various patterns and to perform robustly with noisy data. In particular, FASP explicitly models signal propagation, which rules out the applicability of tools designed for other types of data. We demonstrate the effectiveness of FASP using extensive synthetic and real data sets. The findings by FASP were verified by manual inspection. FASP also detected signals that were missed by purely manual analysis but could be confirmed by more careful manual examination under the guidance of automatic analysis. All algorithms and the analysis pipeline are packaged into a plugin for Fiji (ImageJ), with the source code freely available online at https://github.com/VTcbil/FASP. PMID:28769780

  14. Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data.

    PubMed

    Wang, Yinxue; Shi, Guilai; Miller, David J; Wang, Yizhi; Wang, Congchao; Broussard, Gerard; Wang, Yue; Tian, Lin; Yu, Guoqiang

    2017-01-01

    Recent discoveries that astrocytes exert proactive regulatory effects on neural information processing and that they are deeply involved in normal brain development and disease pathology have stimulated broad interest in understanding astrocyte functional roles in brain circuit. Measuring astrocyte functional status is now technically feasible, due to recent advances in modern microscopy and ultrasensitive cell-type specific genetically encoded Ca(2+) indicators for chronic imaging. However, there is a big gap between the capability of generating large dataset via calcium imaging and the availability of sophisticated analytical tools for decoding the astrocyte function. Current practice is essentially manual, which not only limits analysis throughput but also risks introducing bias and missing important information latent in complex, dynamic big data. Here, we report a suite of computational tools, called Functional AStrocyte Phenotyping (FASP), for automatically quantifying the functional status of astrocytes. Considering the complex nature of Ca(2+) signaling in astrocytes and low signal to noise ratio, FASP is designed with data-driven and probabilistic principles, to flexibly account for various patterns and to perform robustly with noisy data. In particular, FASP explicitly models signal propagation, which rules out the applicability of tools designed for other types of data. We demonstrate the effectiveness of FASP using extensive synthetic and real data sets. The findings by FASP were verified by manual inspection. FASP also detected signals that were missed by purely manual analysis but could be confirmed by more careful manual examination under the guidance of automatic analysis. All algorithms and the analysis pipeline are packaged into a plugin for Fiji (ImageJ), with the source code freely available online at https://github.com/VTcbil/FASP.

  15. Comparative study on similarity metrics for seed-based analysis of functional connectivity photoacoustic tomography images

    NASA Astrophysics Data System (ADS)

    Khodaei, Afsoon; Nasiriavanaki, Mohammadreza

    2017-03-01

    Seed-based correlation analysis is one of the most popular methods to explore the functional connectivity in the brain. Based on the time series of a seed, i.e., small regions of interest, connectivity is computed as the correlation of time series for all other pixels in the brain. Similarity metric to measure the similarity between time courses of different seeds plays an important role in the detection of functional connectivity maps. In this study, we investigate the performance of six similarity metrics including Pearson correlation, Kendall, Spearman, Goodman-Kruskal Gamma, normalized cross correlation and coherence analysis to determine their performance for the functional connectivity photoacoustic tomography (fcPAT) signals/images. The methods are implemented and applied on the fcPAT data of a mouse brain. We also add noise to the fcPAT data and explore the noise tolerance of these metrics.

  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. 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

  18. BrainCAT - a tool for automated and combined functional magnetic resonance imaging and diffusion tensor imaging brain connectivity analysis

    PubMed Central

    Marques, Paulo; Soares, José M.; Alves, Victor; Sousa, Nuno

    2013-01-01

    Multimodal neuroimaging studies have recently become a trend in the neuroimaging field and are certainly a standard for the future. Brain connectivity studies combining functional activation patterns using resting-state or task-related functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) tractography have growing popularity. However, there is a scarcity of solutions to perform optimized, intuitive, and consistent multimodal fMRI/DTI studies. Here we propose a new tool, brain connectivity analysis tool (BrainCAT), for an automated and standard multimodal analysis of combined fMRI/DTI data, using freely available tools. With a friendly graphical user interface, BrainCAT aims to make data processing easier and faster, implementing a fully automated data processing pipeline and minimizing the need for user intervention, which hopefully will expand the use of combined fMRI/DTI studies. Its validity was tested in an aging study of the default mode network (DMN) white matter connectivity. The results evidenced the cingulum bundle as the structural connector of the precuneus/posterior cingulate cortex and the medial frontal cortex, regions of the DMN. Moreover, mean fractional anisotropy (FA) values along the cingulum extracted with BrainCAT showed a strong correlation with FA values from the manual selection of the same bundle. Taken together, these results provide evidence that BrainCAT is suitable for these analyses. PMID:24319419

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

    PubMed

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

    2009-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

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

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

    PubMed

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

    2015-10-01

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

  2. Independent component analysis applied to self-paced functional MR imaging paradigms.

    PubMed

    Moritz, Chad H; Carew, John D; McMillan, Alan B; Meyerand, M Elizabeth

    2005-03-01

    Self-paced functional MR imaging (fMRI) paradigms, in which the task timing is determined by the subject's performance, can offer several advantages over commonly applied paradigms with predetermined stimulus timing. Independent component analysis (ICA) does not require specification of a timed response function, and could be an advantageous method of deriving results from fMRI data sets with varying response timings and durations. In this study normal volunteers (N = 10) each performed two self-paced fMRI motor and arithmetic paradigms. Individual data sets were analyzed with the Infomax spatial ICA algorithm. Conventional regression analysis was performed for comparison purposes. Spatial ICA effectively produced task-related components from each of the self-paced data sets, even in a few cases where regression analysis yielded non-specific functional maps. For the motor paradigm, these components consistently mapped to primary motor areas. ICA of the arithmetic paradigm yielded multiple task-related components that variably mapped to regions of parietal and frontal lobes. Regression analysis generally yielded similar spatial maps. The multiple task-related ICA components that were sometimes produced from each self-paced data set can be challenging to identify and evaluate for significance. These preliminary results indicate that ICA is useful as an exploratory and complementary method to conventional regression analysis for fMRI of self-paced paradigms.

  3. 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

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

    PubMed Central

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

    2009-01-01

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

  5. 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…

  6. 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…

  7. 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

  8. Independent Component Analysis of Resting-State Functional Magnetic Resonance Imaging in Pedophiles.

    PubMed

    Cantor, J M; Lafaille, S J; Hannah, J; Kucyi, A; Soh, D W; Girard, T A; Mikulis, D J

    2016-10-01

    Neuroimaging and other studies have changed the common view that pedophilia is a result of childhood sexual abuse and instead is a neurologic phenomenon with prenatal origins. Previous research has identified differences in the structural connectivity of the brain in pedophilia. To identify analogous differences in functional connectivity. Functional magnetic resonance images were recorded from three groups of participants while they were at rest: pedophilic men with a history of sexual offenses against children (n = 37) and two control groups: non-pedophilic men who committed non-sexual offenses (n = 28) and non-pedophilic men with no criminal history (n = 39). Functional magnetic resonance imaging data were subjected to independent component analysis to identify known functional networks of the brain, and groups were compared to identify differences in connectivity with those networks (or "components"). The pedophilic group demonstrated wide-ranging increases in functional connectivity with the default mode network compared with controls and regional differences (increases and decreases) with the frontoparietal network. Of these brain regions (total = 23), 20 have been identified by meta-analytic studies to respond to sexually relevant stimuli. Conversely, of the brain areas known to be those that respond to sexual stimuli, nearly all emerged in the present data as significantly different in pedophiles. This study confirms the presence of significant differences in the functional connectivity of the brain in pedophilia consistent with previously reported differences in structural connectivity. The connectivity differences detected here and elsewhere are opposite in direction from those associated with anti-sociality, arguing against anti-sociality and for pedophilia as the source of the neuroanatomic differences detected. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

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

    PubMed

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

    2015-08-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed

    Wang, Nizhuan; Zeng, Weiming; Chen, Lei

    2013-05-30

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-01-01

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

  13. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    PubMed

    Puah, Wee Choo; Wasser, Martin

    2016-03-01

    Time-lapse microscopy in developmental biology is an emerging tool for functional genomics. Phenotypic effects of gene perturbations can be studied non-invasively at multiple time points in chronological order. During metamorphosis of Drosophila melanogaster, time-lapse microscopy using fluorescent reporters allows visualization of alternative fates of larval muscles, which are a model for the study of genes related to muscle wasting. While doomed muscles enter hormone-induced programmed cell death, a smaller population of persistent muscles survives to adulthood and undergoes morphological remodeling that involves atrophy in early, and hypertrophy in late pupation. We developed a method that combines in vivo imaging, targeted gene perturbation and image analysis to identify and characterize genes involved in muscle development. Macrozoom microscopy helps to screen for interesting muscle phenotypes, while confocal microscopy in multiple locations over 4-5 days produces time-lapse images that are used to quantify changes in cell morphology. Performing a similar investigation using fixed pupal tissues would be too time-consuming and therefore impractical. We describe three applications of our pipeline. First, we show how quantitative microscopy can track and measure morphological changes of muscle throughout metamorphosis and analyze genes involved in atrophy. Second, our assay can help to identify genes that either promote or prevent histolysis of abdominal muscles. Third, we apply our approach to test new fluorescent proteins as live markers for muscle development. We describe mKO2 tagged Cysteine proteinase 1 (Cp1) and Troponin-I (TnI) as examples of proteins showing developmental changes in subcellular localization. Finally, we discuss strategies to improve throughput of our pipeline to permit genome-wide screens in the future. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  17. Functional MR imaging versus Wada test for evaluation of language lateralization: cost analysis.

    PubMed

    Medina, L Santiago; Aguirre, Elsa; Bernal, Byron; Altman, Nolan R

    2004-01-01

    To compare the total direct costs (fixed and variable costs) of functional magnetic resonance (MR) imaging and of the Wada test for evaluation of language lateralization. The direct fixed and variable costs of functional MR imaging (performed in 21 patients with mean age +/- SD of 15.5 years +/- 8.9) and of the Wada test (performed in 18 patients aged 19.2 years +/- 5.4) were determined prospectively with time and motion analyses. The labor of all personnel involved in evaluations of language lateralization was tracked, and involvement times were recorded to the nearest minute. All material items used in the studies were recorded. Costs of labor and of materials were determined from personnel reimbursement data and from vendor pricing, respectively. Direct fixed costs were determined from hospital accounting department records. Means (+/- SDs) were calculated for all direct fixed and variable costs. Total direct costs were determined for each procedure and compared by using the Student t test. The total direct costs of the Wada test (US dollars 1130.01 +/- US dollars 138.40) and of functional MR imaging (US dollars 301.82 +/- US dollars 10.65) were significantly different (P <.001). The cost of the Wada test was 3.7 times higher than that of functional MR imaging. Substantial savings are achievable with the use of functional MR imaging instead of the Wada test to evaluate language lateralization. Copyright RSNA, 2004

  18. Analysis of Two-Dimensional Ultrasound Cardiac Strain Imaging using Joint Probability Density Functions

    PubMed Central

    Ma, Chi; Varghese, Tomy

    2014-01-01

    Ultrasound frame rates play a key role for accurate cardiac deformation tracking. Insufficient frame rates lead to an increase in signal decorrelation 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 bimodal distributions in the joint probability density indicate inaccurate strain estimation over a cardiac cycle. In this study, we utilize similar analysis to evaluate a two-dimensional multi-level displacement tracking and strain estimation algorithm for cardiac strain imaging. The impact of different frame rates, final kernel dimensions, and a comparison of radiofrequency and envelope based processing are evaluated using echo signals derived from a three-dimensional finite element cardiac model and 5 healthy volunteers. Cardiac simulation model analysis demonstrate 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 radiofrequency signals. On the other hand, even a frame rate of 250Hz 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 radiofrequency analysis. We also show that an increase in the final kernel dimensions significantly impact the strain probability distribution and joint probability density function generated; with a smaller impact on the variation in the accumulated mean strain estimated over a cardiac cycle. Our results demonstrate that radiofrequency frame rates currently achievable on clinical cardiac ultrasound systems are sufficient for accurate analysis of the strain probability distribution, when a multi

  19. Accuracy of Presurgical Functional MR Imaging for Language Mapping of Brain Tumors: A Systematic Review and Meta-Analysis.

    PubMed

    Weng, Hsu-Huei; Noll, Kyle R; Johnson, Jason M; Prabhu, Sujit S; Tsai, Yuan-Hsiung; Chang, Sheng-Wei; Huang, Yen-Chu; Lee, Jiann-Der; Yang, Jen-Tsung; Yang, Cheng-Ta; Tsai, Ying-Huang; Yang, Chun-Yuh; Hazle, John D; Schomer, Donald F; Liu, Ho-Ling

    2017-10-04

    Purpose To compare functional magnetic resonance (MR) imaging for language mapping (hereafter, language functional MR imaging) with direct cortical stimulation (DCS) in patients with brain tumors and to assess factors associated with its accuracy. Materials and Methods PubMed/MEDLINE and related databases were searched for research articles published between January 2000 and September 2016. Findings were pooled by using bivariate random-effects and hierarchic summary receiver operating characteristic curve models. Meta-regression and subgroup analyses were performed to evaluate whether publication year, functional MR imaging paradigm, magnetic field strength, statistical threshold, and analysis software affected classification accuracy. Results Ten articles with a total of 214 patients were included in the analysis. On a per-patient basis, the pooled sensitivity and specificity of functional MR imaging was 44% (95% confidence interval [CI]: 14%, 78%) and 80% (95% CI: 54%, 93%), respectively. On a per-tag basis (ie, each DCS stimulation site or "tag" was considered a separate data point across all patients), the pooled sensitivity and specificity were 67% (95% CI: 51%, 80%) and 55% (95% CI: 25%, 82%), respectively. The per-tag analysis showed significantly higher sensitivity for studies with shorter functional MR imaging session times (P = .03) and relaxed statistical threshold (P = .05). Significantly higher specificity was found when expressive language task (P = .02), longer functional MR imaging session times (P < .01), visual presentation of stimuli (P = .04), and stringent statistical threshold (P = .01) were used. Conclusion Results of this study showed moderate accuracy of language functional MR imaging when compared with intraoperative DCS, and the included studies displayed significant methodologic heterogeneity. (©) RSNA, 2017 Online supplemental material is available for this article.

  20. Imaging basal ganglia function

    PubMed Central

    BROOKS, DAVID J.

    2000-01-01

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

  1. The impact of denoising on independent component analysis of functional magnetic resonance imaging data.

    PubMed

    Pignat, Jean Michel; Koval, Oleksiy; Van De Ville, Dimitri; Voloshynovskiy, Sviatoslav; Michel, Christoph; Pun, Thierry

    2013-02-15

    Independent component analysis (ICA) is a suitable method for decomposing functional magnetic resonance imaging (fMRI) activity into spatially independent patterns. Practice has revealed that low-pass filtering prior to ICA may improve ICA results by reducing noise and possibly by increasing source smoothness, which may enhance source independence; however, it eliminates useful information in high frequency features and it amplifies low signal fluctuations leading to independence loss. On the other hand, high-pass filtering may increase the independence by preserving spatial information, but its denoising properties are weak. Thus, such filtering strategies did not lead to simultaneous enhancements in independence and noise reduction; therefore, band-pass filtering or more sophisticated filtering methods are expected to be more appropriate. We used advanced wavelet filtering procedures, such as wavelet-based methods relying upon hard and soft coefficient thresholding and non-stationary Gaussian modelling based on geometrical prior information, to denoise artificial and real fMRI data. We compared the performance of these methods with the performance of traditional Gaussian smoothing techniques. First, we demonstrated both analytically and empirically the consistent performance increase of spatial filtering prior to ICA using spatial correlation and statistical sensitivity as quality measures. Second, all filtering methods were computationally efficient. Finally, denoising using low-pass filters was needed to improve ICA, suggesting that noise reduction may have a more significant effect on the component independence than the preservation of information contained within high frequencies. Copyright © 2012 Elsevier B.V. All rights reserved.

  2. Functional magnetic resonance imaging activation detection: fuzzy cluster analysis in wavelet and multiwavelet domains.

    PubMed

    Jahanian, Hesamoddin; Soltanian-Zadeh, Hamid; Hossein-Zadeh, Gholam-Ali

    2005-09-01

    To present novel feature spaces, based on multiscale decompositions obtained by scalar wavelet and multiwavelet transforms, to remedy problems associated with high dimension of functional magnetic resonance imaging (fMRI) time series (when they are used directly in clustering algorithms) and their poor signal-to-noise ratio (SNR) that limits accurate classification of fMRI time series according to their activation contents. Using randomization, the proposed method finds wavelet/multiwavelet coefficients that represent the activation content of fMRI time series and combines them to define new feature spaces. Using simulated and experimental fMRI data sets, the proposed feature spaces are compared to the cross-correlation (CC) feature space and their performances are evaluated. In these studies, the false positive detection rate is controlled using randomization. To compare different methods, several points of the receiver operating characteristics (ROC) curves, using simulated data, are estimated and compared. The proposed features suppress the effects of confounding signals and improve activation detection sensitivity. Experimental results show improved sensitivity and robustness of the proposed method compared to the conventional CC analysis. More accurate and sensitive activation detection can be achieved using the proposed feature spaces compared to CC feature space. Multiwavelet features show superior detection sensitivity compared to the scalar wavelet features. (c) 2005 Wiley-Liss, Inc.

  3. Reward pathway dysfunction in gambling disorder: A meta-analysis of functional magnetic resonance imaging studies.

    PubMed

    Meng, Ya-jing; Deng, Wei; Wang, Hui-yao; Guo, Wan-jun; Li, Tao; Lam, Chaw; Lin, Xia

    2014-12-15

    Recent emerging functional magnetic resonance imaging (fMRI) studies have identified many brain regions in which gambling cues or rewards elicit activation and may shed light upon the ongoing disputes regarding the diagnostic and neuroscientific issues of gambling disorder (GD). However, no studies to date have systemically reviewed fMRI studies of GD to analyze the brain areas activated by gambling-related cues and examine whether these areas were differentially activated between cases and healthy controls (HC). This study reviewed 62 candidate articles and ultimately selected 13 qualified voxel-wise whole brain analysis studies to perform a comprehensive series of meta-analyses using the effect size-signed differential mapping approach. Compared with HC, GD patients showed significant activation in right lentiform nucleus and left middle occipital gyrus. The increased activities in the lentiform nucleus compared to HC were also found in both GD subgroups, regardless of excluding or not excluding any kind of substance use disorder. In addition, the South Oaks Gambling Screen scores were associated with hyperactivity in right lentiform nucleus and bilateral parahippocampus, but negatively related to right middle frontal gyrus. These results suggest dysfunction within the frontostriatal cortical pathway in GD, which could contribute to our understanding of the categories and definition of GD and provide evidence for the reclassification of GD as a behavioral addiction in the DSM-5. Copyright © 2014 Elsevier B.V. All rights reserved.

  4. 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.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

    Kadah, Yasser M.

    2002-04-01

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

  7. Machine Learning Applications to Resting-State Functional MR Imaging Analysis.

    PubMed

    Billings, John M; Eder, Maxwell; Flood, William C; Dhami, Devendra Singh; Natarajan, Sriraam; Whitlow, Christopher T

    2017-11-01

    Machine learning is one of the most exciting and rapidly expanding fields within computer science. Academic and commercial research entities are investing in machine learning methods, especially in personalized medicine via patient-level classification. There is great promise that machine learning methods combined with resting state functional MR imaging will aid in diagnosis of disease and guide potential treatment for conditions thought to be impossible to identify based on imaging alone, such as psychiatric disorders. We discuss machine learning methods and explore recent advances. Copyright © 2017 Elsevier Inc. All rights reserved.

  8. 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

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

    PubMed Central

    Yang, Yaling; Raine, Adrian

    2009-01-01

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

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

    PubMed

    Spahn, Viola; Nockemann, Dinah; Machelska, Halina

    2015-01-01

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

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

    PubMed

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

    2011-04-01

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

  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. 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

  14. 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.

  15. Systematic analysis of functional and structural changes after coronary microembolization: a cardiac magnetic resonance imaging study.

    PubMed

    Breuckmann, Frank; Nassenstein, Kai; Bucher, Christina; Konietzka, Ina; Kaiser, Gernot; Konorza, Thomas; Naber, Christoph; Skyschally, Andreas; Gres, Petra; Heusch, Gerd; Erbel, Raimund; Barkhausen, Jörg

    2009-02-01

    Our study aimed to detect the morphological und functional effects of coronary microembolization (ME) in vivo by cardiac magnetic resonance (CMR) imaging in an established experimental animal model. Post-mortem morphological alterations of coronary ME include perifocal inflammatory edema and focal microinfarcts. Clinically, the detection of ME after successful coronary interventions identifies a population with a worse long-term prognosis. In 18 minipigs, ME was performed by intracoronary infusion of microspheres followed by repetitive in vivo imaging on a 1.5-T MR system from 30 min to 8 h after ME. Additionally, corresponding ex vivo CMR imaging and histomorphology were performed. Cine CMR imaging demonstrated a time-dependent increase of wall motion abnormalities from 9 of 18 animals after 30 min to all animals after 8 h (0.5 h, 50%; 2 h, 78%; 4 h, 75%; 8 h, 100%). Whereas T2 images were negative 30 min after ME, 4 of 18 animals showed myocardial edema at follow-up (0.5 h, 0%; 2 h, 6%; 4 h, 25%; 8 h, 17%). In vivo late gadolinium enhancement (LGE) was observed in none of the animals after 30 min, but in 33%, 50%, and 83% of animals at 2 h, 4 h, and 8 h, respectively, after ME. Ex vivo CMR imaging showed patchy areas of LGE in all but 1 animal (2 h, 83%; 4 h, 100%; 8 h, 100%). A significant correlation was seen between the maximum troponin I level and LGE in vivo (r = 0.63) and the spatial extent of ex vivo LGE (r = 0.76). Our results show that in vivo contrast-enhanced CMR imaging allows us to detect functional and structural myocardial changes after ME with a high sensitivity. Ex vivo, the pattern of LGE of high-resolution, contrast-enhanced CMR imaging is different from the well-known pattern of LGE in compact myocardial damage. Thus, improvements in spatial resolution are thought to be necessary to improve its ability to visualize ME-induced structural alterations even in vivo.

  16. 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.

  17. 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.

  18. Pain and functional imaging.

    PubMed Central

    Ingvar, M

    1999-01-01

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

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

    PubMed

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

    2016-08-29

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

  20. 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.

  1. 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.

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

    PubMed

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

    2013-01-01

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

  3. 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

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

    PubMed

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

    2005-12-01

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

  5. 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.

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

    PubMed

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

    2014-05-01

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

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

    PubMed

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

    2016-05-17

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

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

    PubMed

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

    2012-01-01

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

  9. Joint independent component analysis of structural and functional images reveals complex patterns of functional reorganisation in stroke aphasia.

    PubMed

    Specht, Karsten; Zahn, Roland; Willmes, Klaus; Weis, Susanne; Holtel, Christiane; Krause, Bernd J; Herzog, Hans; Huber, Walter

    2009-10-01

    Previous functional activation studies in patients with aphasia have mostly relied on standard group comparisons of aphasic patients with healthy controls, which are biased towards regions showing the most consistent effects and disregard variability within groups. Groups of aphasic patients, however, show considerable variability with respect to lesion localisation and extent. Here, we use a novel method, joint independent component analysis (jICA), which allowed us to investigate abnormal patterns of functional activation with O(15)-PET during lexical decision in aphasic patients after middle cerebral artery stroke and to directly relate them to lesion information from structural MRI. Our results demonstrate that with jICA we could detect a network of compensatory increases in activity within bilateral anterior inferior temporal areas (BA20), which was not revealed by standard group comparisons. In addition, both types of analyses, jICA and group comparison, showed increased activity in the right posterior superior temporal gyrus in aphasic patients. Further, whereas standard analyses revealed no decreases in activation, jICA identified that left perisylvian lesions were associated with decreased activation of left posterior inferior frontal cortex, damaged in most patients, and extralesional remote decreases of activity within polar parts of the inferior temporal gyrus (BA38/20) and the occipital cortex (BA19). Taken together, our results demonstrate that jICA may be superior in revealing complex patterns of functional reorganisation in aphasia.

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

    PubMed

    Cheng, H; Skosnik, P D; Pruce, B J; Brumbaugh, M S; Vollmer, J M; Fridberg, D J; O'Donnell, B F; Hetrick, W P; Newman, S D

    2014-11-01

    Chronic cannabis use can cause cognitive, perceptual and personality alterations, which are believed to be associated with regional brain changes and possible changes in connectivity between functional regions. This study aims to identify the changes from resting state functional magnetic resonance imaging scans. A two-level multi-voxel pattern analysis was proposed to classify male cannabis users from normal controls. The first level analysis works on a voxel basis and identifies clusters for the input of a second level analysis, which works on the functional connectivity between these regions. We found distinct clusters for male cannabis users in the middle frontal gyrus, precentral gyrus, superior frontal gyrus, posterior cingulate cortex, cerebellum and some other regions. Based on the functional connectivity of these clusters, a high overall accuracy rate of 84-88% in classification accuracy was achieved. High correlations were also found between the overall classification accuracy and Barrett Barrett Impulsiveness Scale factor scores of attention and motor. Our result suggests regional differences in the brains of male cannabis users that span from the cerebellum to the prefrontal cortex, which are associated with differences in functional connectivity. © The Author(s) 2014.

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

    PubMed

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

    2012-02-01

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

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

    PubMed

    Suwansukho, Kajpanya; Sumriddetchkajorn, Sarun; Buranasiri, Prathan

    2014-04-01

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

  13. Image Analysis and Modeling

    DTIC Science & Technology

    1976-03-01

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

  14. New Methods of Three-Dimensional Images Recognition Based on Stochastic Geometry and Functional Analysis

    NASA Astrophysics Data System (ADS)

    Fedotov, N. G.; Moiseev, A. V.; Syemov, A. A.; Lizunkov, V. G.; Kindaev, A. Y.

    2017-02-01

    A new approach to 3D objects recognition based on modern methods of stochastic geometry and functional analysis is proposed in the paper. A detailed mathematical description of the method developed on the approach is also presented. The 3D trace transform allows creating an invariant description of spatial objects, which better resist distortion and coordinate noise than the one, obtained as a result of the object normalization procedure, does. The ability to control properties of developed features increases intellectual capacities of the 3D trace transform significantly, which can be mentioned as its undeniable advantage. The justification of the proposed theory and mathematical model is a variety of worked out theoretical examples of hypertriplet features that have particular described properties. The paper considers in detail scan techniques of the hypertrace transform and its mathematical model as well as approaches to developing and distinguishing informative features.

  15. Brain Imaging Analysis

    PubMed Central

    BOWMAN, F. DUBOIS

    2014-01-01

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

  16. 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.

  17. [Therapeutic function of images].

    PubMed

    Aisenson Kogan, A

    1986-03-01

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

  18. Combined assessment of myocardial perfusion and regional left ventricular function by analysis of contrast-enhanced power modulation images.

    PubMed

    Mor-Avi, V; Caiani, E G; Collins, K A; Korcarz, C E; Bednarz, J E; Lang, R M

    2001-07-17

    Echocardiographic contrast media have been used to assess myocardial perfusion and to enhance endocardial definition for improved assessment of left ventricular (LV) function. These methodologies, however, have been qualitative or have required extensive offline image analysis. Power modulation is a recently developed imaging technique that provides selective enhancement of microbubble-generated reflections. Our goal was to test the feasibility of using power modulation for combined quantitative assessment of myocardial perfusion and regional LV function in an animal model of acute ischemia. Coronary balloon occlusions were performed in 18 anesthetized pigs. Transthoracic power modulation images (Agilent 5500) were obtained during continuous intravenous infusion of the contrast agent Definity (DuPont) at baseline and during brief coronary occlusion and reperfusion and were analyzed with custom software. At each phase, myocardial perfusion was assessed by calculation, in 6 myocardial regions of interest, of mean pixel intensity and the rate of contrast replenishment after high-power ultrasound impulses. LV function was assessed by calculation of regional fractional area change from semiautomatically detected endocardial borders. All ischemic episodes caused detectable and reversible changes in perfusion and function. Perfusion defects, validated with fluorescent microspheres, were visualized in real time and confirmed by a significant decrease in pixel intensity in the left anterior descending coronary artery territory after balloon inflation and reduced rate of contrast replenishment. Fractional area change decreased significantly in ischemic segments and was restored with reperfusion. Power modulation allows simultaneous online assessment of myocardial perfusion and regional LV wall motion, which may improve the echocardiographic diagnosis of myocardial ischemia.

  19. 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.

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

    PubMed

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

    2015-04-01

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

  1. Functional neurological disorders: imaging.

    PubMed

    Voon, V

    2014-10-01

    Functional neurological disorders, also known as conversion disorder, are unexplained neurological symptoms. These symptoms are common and can be associated with significant consequences. This review covers the neuroimaging literature focusing on functional motor symptoms including motor functioning and upstream influences including self-monitoring and internal representations, voluntariness and arousal and trauma. Copyright © 2014. Published by Elsevier SAS.

  2. Effect of injection rate on contrast-enhanced MR angiography image quality: Modulation transfer function analysis.

    PubMed

    Clark, Toshimasa J; Wilson, Gregory J; Maki, Jeffrey H

    2017-07-01

    Contrast-enhanced (CE)-MRA optimization involves interactions of sequence duration, bolus timing, contrast recirculation, and both R1 relaxivity and R2*-related reduction of signal. Prior data suggest superior image quality with slower gadolinium injection rates than typically used. A computer-based model of CE-MRA was developed, with contrast injection, physiologic, and image acquisition parameters varied over a wide gamut. Gadolinium concentration was derived using Verhoeven's model with recirculation, R1 and R2* calculated at each time point, and modulation transfer curves used to determine injection rates, resulting in optimal resolution and image contrast for renal and carotid artery CE-MRA. Validation was via a vessel stenosis phantom and example patients who underwent carotid CE-MRA with low effective injection rates. Optimal resolution for renal and carotid CE-MRA is achieved with injection rates between 0.5 to 0.9 mL/s and 0.2 to 0.3 mL/s, respectively, dependent on contrast volume. Optimal image contrast requires slightly faster injection rates. Expected signal-to-noise ratio varies with both contrast volume and cardiac output. Simulated vessel phantom and clinical carotid CE-MRA exams at an effective contrast injection rate of 0.4 to 0.5 mL/s demonstrate increased resolution. Optimal image resolution is achieved at intuitively low, effective injection rates (0.2-0.9 mL/s, dependent on imaging parameters and contrast injection volume). Magn Reson Med 78:357-369, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  3. Functional imaging in the fetus.

    PubMed

    Schöpf, Veronika; Kasprian, Gregor; Prayer, Daniela

    2011-06-01

    This review focuses on the application of magnetic resonance imaging methods in utero studying functional brain development of spontaneous brain activity generated under resting conditions and of task-evoked activity using stimulation. These imaging approaches have been useful to explore the brain's functional organization during development, as already shown in different substantial resting-state studies in preterms. We also discuss emerging future directions regarding analyzing methods and combination of functional and structural connectivity approaches.

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

    PubMed

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

    2015-03-30

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

  5. Functional Imaging: CT and MRI

    PubMed Central

    van Beek, Edwin JR; Hoffman, Eric A

    2008-01-01

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

  6. 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.

  7. 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.

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

    PubMed

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

    2012-01-01

    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. 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. 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. 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.

  9. Sequential functional analysis of left ventricle from 2D-echocardiography images.

    PubMed

    Chacko, Rani; Singh, Megha

    2014-06-01

    The sequential changes in shape of left ventricle (LV), which are the result of cellular interactions and their levels of organizational complexity, in its long axis view during one cardiac cycle are obtained. The changes are presented in terms of shape descriptors by processing of images obtained from a normal subject and two patients with dilated left ventricular cardio-myopathy. These images are processed, frame by frame, by a semi-automatic algorithm developed by MATLAB. This is consisting of gray scale conversion, the LV contour extraction by application of median and SRAD filters, and morphological operations. By filling the identified region with pixels and number of pixels along its contour the area and perimeter are calculated, respectively. From these the changes in LV volume and shape index are calculated. Based on these the stroke volume (SV) and ejection fraction (EF) are calculated. The changes in LV area, perimeter, volume and shape index in cardiac patients are less than that of normal subject. The calculated SV and EF of normal subject are within the range as obtained by various imaging procedures.

  10. Basics of image analysis

    USDA-ARS?s Scientific Manuscript database

    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...

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

    PubMed

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

    2014-01-01

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

  12. Analysis of STM images with pure and CO-functionalized tips: A first-principles and experimental study

    NASA Astrophysics Data System (ADS)

    Gustafsson, Alexander; Okabayashi, Norio; Peronio, Angelo; Giessibl, Franz J.; Paulsson, Magnus

    2017-08-01

    We describe a first-principles method to calculate scanning tunneling microscopy (STM) images, and compare the results to well-characterized experiments combining STM with atomic force microscopy (AFM). The theory is based on density functional theory with a localized basis set, where the wave functions in the vacuum gap are computed by propagating the localized-basis wave functions into the gap using a real-space grid. Constant-height STM images are computed using Bardeen's approximation method, including averaging over the reciprocal space. We consider copper adatoms and single CO molecules adsorbed on Cu(111), scanned with a single-atom copper tip with and without CO functionalization. The calculated images agree with state-of-the-art experiments, where the atomic structure of the tip apex is determined by AFM. The comparison further allows for detailed interpretation of the STM images.

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

    PubMed

    Vartanian, Oshin; Skov, Martin

    2014-06-01

    Many studies involving functional magnetic resonance imaging (fMRI) have exposed participants to paintings under varying task demands. To isolate neural systems that are activated reliably across fMRI studies in response to viewing paintings regardless of variation in task demands, a quantitative meta-analysis of fifteen experiments using the activation likelihood estimation (ALE) method was conducted. As predicted, viewing paintings was correlated with activation in a distributed system including the occipital lobes, temporal lobe structures in the ventral stream involved in object (fusiform gyrus) and scene (parahippocampal gyrus) perception, and the anterior insula-a key structure in experience of emotion. In addition, we also observed activation in the posterior cingulate cortex bilaterally-part of the brain's default network. These results suggest that viewing paintings engages not only systems involved in visual representation and object recognition, but also structures underlying emotions and internalized cognitions. Copyright © 2014 Elsevier Inc. All rights reserved.

  14. Quantitative imaging of lymph function.

    PubMed

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

    2007-06-01

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

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

    PubMed

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

    2004-08-01

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

  16. 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.

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

    ERIC Educational Resources Information Center

    STAATS, ARTHUR W.

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  1. Forensic video image analysis

    NASA Astrophysics Data System (ADS)

    Edwards, Thomas R.

    1997-02-01

    Forensic video image analysis is a new scientific tool for perpetrator enhancement and identification in poorly recorded crime scene situations. Forensic video image analysis is emerging technology for law enforcement, industrial security and surveillance addressing the following problems often found in these poor quality video recorded incidences.

  2. Molecular and functional imaging of internet addiction.

    PubMed

    Zhu, Yunqi; Zhang, Hong; Tian, Mei

    2015-01-01

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

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

    DTIC Science & Technology

    2007-11-02

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

  4. 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.

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

    PubMed Central

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

    2010-01-01

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

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

    PubMed Central

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

    2012-01-01

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

  7. A detailed analysis of functional magnetic resonance imaging in the frontal language area: a comparative study with extraoperative electrocortical stimulation.

    PubMed

    Kunii, Naoto; Kamada, Kyousuke; Ota, Takahiro; Kawai, Kensuke; Saito, Nobuhito

    2011-09-01

    Functional magnetic resonance imaging (fMRI) is a less invasive way of mapping brain functions. The reliability of fMRI for localizing language-related function is yet to be determined. We performed a detailed analysis of language fMRI reliability by comparing the results of 3-T fMRI with maps determined by extraoperative electrocortical stimulation (ECS). This study was performed on 8 epileptic patients who underwent subdural electrode placement. The tasks performed during fMRI included verb generation, abstract/concrete categorization, and picture naming. We focused on the frontal lobe, which was effectively activated by these tasks. In extraoperative ECS, 4 tasks were combined to determine the eloquent areas: spontaneous speech, picture naming, reading, and comprehension. We calculated the sensitivity and specificity with different Z score thresholds for each task and appropriate matching criteria. For further analysis, we divided the frontal lobe into 5 areas and investigated intergyrus variations in sensitivity and specificity. The abstract/concrete categorization task was the most sensitive and specific task in fMRI, whereas the picture naming task detected eloquent areas most efficiently in ECS. The combination of the abstract/concrete categorization task and a 3-mm matching criterion gave the best tradeoff (sensitivity, 83%; specificity, 61%) when the Z score was 2.24. As for intergyrus variation, the posterior inferior frontal gyrus showed the best tradeoff (sensitivity, 91%; specificity, 59%), whereas the anterior middle frontal gyrus had low specificity. Despite different tasks for fMRI and extraoperative ECS, the relatively low specificity might be caused by a fundamental discrepancy between the 2 techniques. Reliability of language fMRI activation might differ, depending on the brain region.

  8. 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.

  9. 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

  10. 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

  11. 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

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

    PubMed

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

    2015-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-11-01

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

  14. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. [Morphological and functional cartilage imaging].

    PubMed

    Rehnitz, C; Weber, M-A

    2014-06-01

    Excellent morphological imaging of cartilage is now possible and allows the detection of subtle cartilage pathologies. Besides the standard 2D sequences, a multitude of 3D sequences are available for high-resolution cartilage imaging. The first part therefore deals with modern possibilities of morphological imaging. The second part deals with functional cartilage imaging with which it is possible to detect changes in cartilage composition and thus early osteoarthritis as well as to monitor biochemical changes after therapeutic interventions. Validated techniques such as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T2 mapping as well the latest techniques, such as the glycosaminoglycan chemical exchange-dependent saturation transfer (gagCEST) technique will be discussed.

  16. [Morphological and functional cartilage imaging].

    PubMed

    Rehnitz, C; Weber, M-A

    2015-04-01

    Excellent morphological imaging of cartilage is now possible and allows the detection of subtle cartilage pathologies. Besides the standard 2D sequences, a multitude of 3D sequences are available for high-resolution cartilage imaging. The first part therefore deals with modern possibilities of morphological imaging. The second part deals with functional cartilage imaging with which it is possible to detect changes in cartilage composition and thus early osteoarthritis as well as to monitor biochemical changes after therapeutic interventions. Validated techniques such as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC) and T2 mapping as well the latest techniques, such as the glycosaminoglycan chemical exchange-dependent saturation transfer (gagCEST) technique will be discussed.

  17. 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. © 2016 Wiley Periodicals, Inc.

  18. Multisensor Image Analysis System

    DTIC Science & Technology

    1993-04-15

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2017-01-01

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

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

    PubMed

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

    2011-02-01

    Independent component analysis (ICA) is a statistical technique that estimates a set of sources mixed by an unknown mixing matrix using only a set of observations. For this purpose, the only assumption is that the sources are statistically independent. In many applications, some information about the nature of the unknown signals is available. In this paper we show a method for incorporating prior information about the mixing matrix to increase the levels of detection of responses to visual stimuli. Experimentally, our method matches the performance of known ICA algorithms for high SNR and can greatly improve the performance for low levels of SNR or low levels of signal-to-background ratio (SBR). For the problem of signal extraction, we have achieved detection for signals as small as 0.01% (-40 dB SBR) in hybrid live/synthetic data simulations. In experiments using a functional imager of the retina, measured changes in reflectance in response to visual stimulus are in the order of 0.1-1% of the total pixel intensity value, which makes the functional signal difficult to detect by standard methods. The results of the analysis show that using ICA-P signal levels of 0.1% can be detected. The approach also generalizes the standard Infomax algorithm which can be thought of as a special case of ICA-P when the confidence parameter or a tolerance value is zero. For in vivo animal experiments, we show that signal detection agreement over a range of confidence values parameters can be used to establish reflectance changes in response to the visual stimulus. Copyright © 2010 Elsevier B.V. All rights reserved.

  5. Functional imaging for regenerative medicine.

    PubMed

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

    2016-04-19

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

  6. Functional near-infrared imager

    NASA Astrophysics Data System (ADS)

    Luo, Qingming; Nioka, Shoko; Chance, Britton

    1997-08-01

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

  7. [Presurgical functional magnetic resonance imaging].

    PubMed

    Stippich, C

    2010-02-01

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

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

    PubMed Central

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

    2017-01-01

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

  9. 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.

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

    PubMed

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

    2010-05-15

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

  11. 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.

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

    PubMed

    Yang, Jie

    2014-01-01

    The role of the right hemisphere (RH) in metaphor comprehension is still controversial. Numerous neuroimaging studies have found that conventionality, sentential context, and task demand can influence the involvement of the RH in metaphor processing. The current meta-analysis used foci from 17 original functional magnetic resonance imaging studies to identify what factors modulate the involvement of the RH in metaphor processing. Activation likelihood estimation was used for quantification. We focused on the contrast of metaphorical meaning processing versus literal meaning processing and calculated the meta-analysis effects when (1) metaphorical meaning is conventional, (2) metaphorical meaning is novel, (3) metaphorical and literal meaning are presented in words, (4) metaphorical and literal meaning are presented in sentential context, (5) task is valence judgment, and (6) task is semantic relatedness judgment. The results indicated that the RH only showed significant effects in metaphor processing when the metaphorical meaning is novel, when metaphorical meaning is presented in sentential context, and when the task is semantic relatedness judgment. The effects were located in right fronto-temporal regions, including inferior frontal gyrus, middle frontal gyrus, insula, superior temporal gyrus, and middle temporal gyrus. These results suggest that conventionality, contextual complexity, and task demand can modulate the effect of figurativeness and influence the involvement of RH in metaphor comprehension. The main role of the RH in metaphor processing is related with activating broad semantic fields and integrating concepts that may have distant semantic relations, and hence provide support for the view that the RH is responsible for processing coarse semantic information in language comprehension. Copyright © 2012 Wiley Periodicals, Inc.

  13. Resting-state Functional Magnetic Resonance Imaging Analysis of Brain Functional Activity in Rats with Ischemic Stroke Treated by Electro-acupuncture.

    PubMed

    Liang, Shengxiang; Lin, Yunjiao; Lin, Bingbing; Li, Jianhong; Liu, Weilin; Chen, Lidian; Zhao, Shujun; Tao, Jing

    2017-09-01

    To evaluate whether electro-acupuncture (EA) treatment at acupoints of Zusanli (ST 36) and Quchi (LI 11) could reduce motor impairments and enhance brain functional recovery in rats with ischemic stroke. A rat model of middle cerebral artery occlusion (MCAO) was established. EA at ST 36 and LI 11was started at 24 hours (MCAO + EA group) after ischemic stroke. The nontreatment (MCAO) and sham-operated control (SC) groups were included as controls. The neurologic deficits of all groups were assessed by Zea Longa scores and the modified neurologic severity scores on 24 hours and 8 days after MCAO. To further investigate the effect of EA on infract volume and brain function, magnetic resonance imaging was used to estimate the brain lesion and brain neural activities of each group at 8 days after ischemic stroke. Within 1 week after EA treatment, the neurologic deficits were significantly alleviated, and the cerebral infarctions were improved, including visual cortex, motor cortex, striatum, dorsal thalamus, and hippocampus. Furthermore, whole brain neural activities of auditory cortex, lateral nucleus group of dorsal thalamus, hippocampus, motor cortex, orbital cortex, sensory cortex, and striatum were decreased in MCAO group, whereas that of brain neural activities were increased after EA treatment, suggesting these brain regions are in accordance with the brain structure analysis. EA at ST 36 and LI 11 could enhance the neural activity of motor function-related brain regions, including motor cortex, dorsal thalamus, and striatum in rats, which is a potential treatment for ischemia stroke. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

  14. Paraxial ghost image analysis

    NASA Astrophysics Data System (ADS)

    Abd El-Maksoud, Rania H.; Sasian, José M.

    2009-08-01

    This paper develops a methodology to model ghost images that are formed by two reflections between the surfaces of a multi-element lens system in the paraxial regime. An algorithm is presented to generate the ghost layouts from the nominal layout. For each possible ghost layout, paraxial ray tracing is performed to determine the ghost Gaussian cardinal points, the size of the ghost image at the nominal image plane, the location and diameter of the ghost entrance and exit pupils, and the location and diameter for the ghost entrance and exit windows. The paraxial ghost irradiance point spread function is obtained by adding up the irradiance contributions for all ghosts. Ghost simulation results for a simple lens system are provided. This approach provides a quick way to analyze ghost images in the paraxial regime.

  15. CT ventilation functional image-based IMRT treatment plans are comparable to SPECT ventilation functional image-based plans.

    PubMed

    Kida, Satoshi; Bal, Matthieu; Kabus, Sven; Negahdar, Mohammadreza; Shan, Xin; Loo, Billy W; Keall, Paul J; Yamamoto, Tokihiro

    2016-03-01

    To investigate the hypothesis that CT ventilation functional image-based IMRT plans designed to avoid irradiating highly-functional lung regions are comparable to single-photon emission CT (SPECT) ventilation functional image-based plans. Three IMRT plans were created for eight thoracic cancer patients using: (1) CT ventilation functional images, (2) SPECT ventilation functional images, and (3) anatomic images (no functional images). CT ventilation images were created by deformable image registration of 4D-CT image data sets and quantitative analysis. The resulting plans were analyzed for the relationship between the deviations of CT-functional plan metrics from anatomic plan metrics (ΔCT-anatomic) and those of SPECT-functional plans (ΔSPECT-anatomic), and moreover for agreements of various metrics between the CT-functional and SPECT-functional plans. The relationship between ΔCT-anatomic and ΔSPECT-anatomic was strong (e.g., R=0.94; linear regression slope 0.71). The average differences and 95% limits of agreement between the CT-functional and SPECT-functional plan metrics (except for monitor units) for various structures were mostly less than 1% and 2%, respectively. This study demonstrated a reasonable agreement between the CT ventilation functional image-based IMRT plans and SPECT-functional plans, suggesting the potential for CT ventilation imaging to serve as a surrogate for SPECT ventilation in functional image-guided radiotherapy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  16. 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.

  17. 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.

  18. 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.

  19. Brown adipose tissue in humans: detection and functional analysis using PET (positron emission tomography), MRI (magnetic resonance imaging), and DECT (dual energy computed tomography).

    PubMed

    Borga, Magnus; Virtanen, Kirsi A; Romu, Thobias; Leinhard, Olof Dahlqvist; Persson, Anders; Nuutila, Pirjo; Enerbäck, Sven

    2014-01-01

    If the beneficial effects of brown adipose tissue (BAT) on whole body metabolism, as observed in nonhuman experimental models, are to be translated to humans, tools that accurately measure how BAT influences human metabolism will be required. This chapter discusses such techniques, how they can be used, what they can measure and also some of their limitations. The focus is on detection and functional analysis of human BAT and how this can be facilitated by applying advanced imaging technology such as positron emission tomography, magnetic resonance imaging, and dual energy computed tomography. © 2014 Elsevier Inc. All rights reserved.

  20. Functional imaging in chronic migraine.

    PubMed

    Maniyar, Farooq H; Goadsby, Peter J

    2013-05-01

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

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

    SciTech Connect

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

    1989-02-01

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

  2. Functional brain imaging across development.

    PubMed

    Rubia, Katya

    2013-12-01

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

  3. 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.

  4. 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.

  5. [Functional imaging in mental disorders].

    PubMed

    Borbély, Katalin

    2004-02-08

    Considerable progress has been achieved by functional brain imaging over the past 20 years in uncovering the biological basis of major psychiatric disorders and to more effectively target therapeutics. Radioligand techniques, especially the PET (positron emission tomography) method, are specific and sensitive tools for quantitative in vivo imaging of molecular pathways and molecular interactions within brain tissues. Since 1980s, advances in neuroimaging and neurophysiological techniques have provided tremendous merits for investigations into different psychiatric disorders. PET and SPECT (single photon emission computer tomography) neuroreceptor imaging, especially in schizophrenia has been an extremely fruitful area of research. Evidences from these studies suggest that schizophrenia affects various cortical and subcortical regions involved in cognitive, emotional, and motivational aspects of human behavior. PET and SPECT provide useful data in studying the fundamental neurobiology of mood disorders. Both techniques are playing a central role in studying patients with new methods and ligands for specific receptor subtypes, and are likely to increase the application of PET/SPECT in the development of new pharmacotherapies. Nuclear medicine plays an important role in studying patients with other psychiatric disorders such as obsessive-compulsive disorder (OCD), attention deficit hyperactivity disorder (ADHD), anxiety, etc. Some forms of OCD seem to share a common genetic etiology with Tourette-syndrome (TS) and to be a facultative part of the TS phenotypic spectrum. In conclusion, PET and SPECT methods seem to be helpful in the diagnosis and management of patients with different psychiatric disorders and may provide a better understanding of clinical symptomatology or the relationship of these physiological parameters to the patient's prognosis. Additionally, radionuclide techniques may improve medical therapy by demonstrating individual biochemical abnormalities

  6. 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.

  7. Digital Image Analysis of Cereals

    USDA-ARS?s Scientific Manuscript database

    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...

  8. 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

  9. Anatomical and functional imaging in endocrine hypertension

    PubMed Central

    Chaudhary, Vikas; Bano, Shahina

    2012-01-01

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

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

    PubMed

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

    2011-08-01

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

  11. Analysis of central mechanism of cognitive training on cognitive impairment after stroke: Resting-state functional magnetic resonance imaging study.

    PubMed

    Lin, Zhi-cheng; Tao, Jing; Gao, Yan-lin; Yin, Da-zhi; Chen, A-zhen; Chen, Li-dian

    2014-06-01

    To investigate the central mechanism of cognitive training in patients with stroke, using resting state (RS) functional magnetic resonance imaging (fMRI). Patients with stroke and executive function and memory deficit were randomized to receive computer-assisted cognitive training (treatment group; total 60 h training over 10 weeks) or no training (control group). All participants received neuropsychological assessment and RS fMRI at baseline and 10 weeks. Patients in the treatment group (n = 16) showed increased functional connectivity (FC) of the hippocampus with the frontal lobe (right inferior, right middle, left middle, left inferior and left superior frontal gyrus) and left parietal lobe at 10 weeks compared with baseline. Patients in the control group (n = 18) showed decreased FC of the left hippocampus-right occipital gyrus, and right hippocampus-right posterior lobe of cerebellum and left superior temporal gyrus. Significant correlations were found between improved neuropsychological scores and increased FC of the hippocampus with the frontal lobe and left parietal lobe in the treatment group only. Increased RS FC of the hippocampus with the frontal and parietal lobes may be an important mechanism of cognitive recovery after stroke. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

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

    PubMed

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

    2017-03-01

    Several studies have recently demonstrated that the volumes of specific brain regions are reduced in children and adolescents with post-traumatic stress disorder (PTSD) compared with those of healthy controls. Our study investigated the potential association between early traumatic experiences and altered brain regions and functions. We conducted a systematic review of the scientific literature regarding functional magnetic resonance imaging and a meta-analysis of structural magnetic resonance imaging studies that investigated cerebral region volumes in pediatric patients with PTSD. We searched for articles from 2000 to 2014 in the PsycINFO, PubMed, Medline, Lilacs, and ISI (Web of Knowledge) databases. All data regarding the amygdala, hippocampus, corpus callosum, brain, and intracranial volumes that fit the inclusion criteria were extracted and combined in a meta-analysis that assessed differences between groups. The meta-analysis found reduced total corpus callosum areas and reduced total cerebral and intracranial volumes in the patients with PTSD. The total hippocampus (left and right hippocampus) and gray matter volumes of the amygdala and frontal lobe were also reduced, but these differences were not significant. The functional studies revealed differences in brain region activation in response to stimuli in the post-traumatic stress symptoms/PTSD group. Our results confirmed that the pediatric patients with PTSD exhibited structural and functional brain abnormalities and that some of the abnormalities occurred in different brain regions than those observed in adults. © 2016 The Authors. Psychiatry and Clinical Neurosciences © 2016 Japanese Society of Psychiatry and Neurology.

  13. 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

  14. Functional imaging of decision conflict.

    PubMed

    Pochon, Jean-Baptiste; Riis, Jason; Sanfey, Alan G; Nystrom, Leigh E; Cohen, Jonathan D

    2008-03-26

    Decision conflict occurs when people feel uncertain as to which option to choose from a set of similarly attractive (or unattractive) options, with many studies demonstrating that this conflict can lead to suboptimal decision making. In this article, we investigate the neurobiological underpinnings of decision conflict, in particular, the involvement of the anterior cingulate cortex (ACC). Previous studies have implicated the ACC in conflict monitoring during perceptual tasks, but there is considerable controversy as to whether the ACC actually indexes conflict related to choice, or merely conflict related to selection of competing motor responses. In a functional magnetic resonance imaging study, we dissociate the decision and response phases of a decision task, and show that the ACC does indeed index conflict at the decision stage. Furthermore, we show that it does so for a complex decision task, one that requires the integration of beliefs and preferences and not just perceptual judgments.

  15. Noninvasive evaluation of global and regional left ventricular function using computed tomography and magnetic resonance imaging: a meta-analysis.

    PubMed

    Kaniewska, Malwina; Schuetz, Georg M; Willun, Steffen; Schlattmann, Peter; Dewey, Marc

    2017-04-01

    To compare the diagnostic accuracy of computed tomography (CT) in the assessment of global and regional left ventricular (LV) function with magnetic resonance imaging (MRI). MEDLINE, EMBASE and ISI Web of Science were systematically reviewed. Evaluation included: ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV) and left ventricular mass (LVM). Differences between modalities were analysed using limits of agreement (LoA). Publication bias was measured by Egger's regression test. Heterogeneity was evaluated using Cochran's Q test and Higgins I(2) statistic. In the presence of heterogeneity the DerSimonian-Laird method was used for estimation of heterogeneity variance. Fifty-three studies including 1,814 patients were identified. The mean difference between CT and MRI was -0.56 % (LoA, -11.6-10.5 %) for EF, 2.62 ml (-34.1-39.3 ml) for EDV and 1.61 ml (-22.4-25.7 ml) for ESV, 3.21 ml (-21.8-28.3 ml) for SV and 0.13 g (-28.2-28.4 g) for LVM. CT detected wall motion abnormalities on a per-segment basis with 90 % sensitivity and 97 % specificity. CT is accurate for assessing global LV function parameters but the limits of agreement versus MRI are moderately wide, while wall motion deficits are detected with high accuracy. • CT helps to assess patients with coronary artery disease (CAD). • MRI is the reference standard for evaluation of left ventricular function. • CT provides accurate assessment of global left ventricular function.

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

    PubMed

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

    2010-03-01

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

  17. Effects of Image Contrast on Functional MRI Image Registration

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2016-09-16

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

  19. Correlations between renal function and the total kidney volume measured on imaging for autosomal dominant polycystic kidney disease: A systematic review and meta-analysis.

    PubMed

    Jo, Woo Ri; Kim, Seong Hee; Kim, Kyung Won; Suh, Chong Hyun; Kim, Jeong Kon; Kim, Hyosang; Lee, Jong Gu; Oh, Woo Yong; Choi, Seong Eun; Pyo, Junhee

    2017-10-01

    To provide a systematic summary of total kidney volume (TKV) as an imaging biomarker in clinical trials for autosomal dominant polycystic kidney disease (ADPKD), focusing on the correlation between TKV and renal function. A computerized literature search was performed using MEDLINE and EMBASE databases for studies that evaluated the correlation between TKV and the glomerular filtration rate (GFR) and between the TKV growth rate and GFR decline rate. A meta-analysis was performed to generate the summary correlation coefficient (r). A qualitative review was performed to evaluate the characteristics of TKV as an imaging biomarker. Eighteen articles including a total sample size of 2835 patients were retrieved. Meta-analysis revealed substantial correlations between TKV and GFR [r, -0.520; 95% confidence interval (CI), -0.60 to -0.43] and between the TKV growth rate and GFR decline rate [r, -0.320; 95% CI, -0.54 to -0.10]. The quantitative review revealed that baseline TKV can affect the TKV growth rate and GFR decline rate, such that patients with a higher baseline TKV showed faster TKV growth and GFR decline. There was significant variability in image acquisition and analysis methods. There were significant negative correlations between TKV and GFR as well as between TKV growth and GFR decline rates, suggesting that TKV imaging is a useful biomarker in clinical trials. However, standardization-or at least trial-specific standardization-of image acquisition and analysis techniques is required to use TKV as a reliable biomarker. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Interactive Image Analysis System Design,

    DTIC Science & Technology

    1982-12-01

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

  1. Parallel Algorithms for Image Analysis.

    DTIC Science & Technology

    1982-06-01

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

  2. Global lithospheric imaging using teleseismic receiver functions

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  3. Visual Function Assessment in Medical Imaging Research.

    PubMed

    Lança, Carla; Thompson, John D; Lança, Luis; Hogg, Peter

    2015-01-01

    Medical image perception research relies on visual data to study the diagnostic relationship between observers and medical images. A consistent method to assess visual function for participants in medical imaging research has not been developed and represents a significant gap in existing research. Three visual assessment factors appropriate to observer studies were identified: visual acuity, contrast sensitivity, and stereopsis. A test was designed for each, and 30 radiography observers (mean age 31.6 years) participated in each test. Mean binocular visual acuity for distance was 20/14 for all observers. The difference between observers who did and did not use corrective lenses was not statistically significant (P = .12). All subjects had a normal value for near visual acuity and stereoacuity. Contrast sensitivity was better than population norms. All observers had normal visual function and could participate in medical imaging visual analysis studies. Protocols of evaluation and populations norms are provided. Further studies are necessary to understand fully the relationship between visual performance on tests and diagnostic accuracy in practice.

  4. Grid computing in image analysis.

    PubMed

    Kayser, Klaus; Görtler, Jürgen; Borkenfeld, Stephan; Kayser, Gian

    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.

  5. Moving Image Analysis System

    NASA Astrophysics Data System (ADS)

    Shifley, Loren A.

    1989-02-01

    The recent introduction of a two dimensional interactive software package provides a new technique for quantitative analysis. Integrated with its corresponding peripherals, the same software offers either film or video data reduction. Digitized data points measured from the images are stored in the computer. With is data, a variety of information can be displayed, printed or plotted in a graphical form. The resultant graphs could determine such factors as: displacement, force, velocity, momentum, angular acceleration, center of gravity, energy, leng, , angle and time to name a few. Simple, efficient and precise analysis can now be quantified and documented. This paper will describe the detailed capabilities of the software along with a variety of applications where it might be used.

  6. Moving image analysis system

    NASA Astrophysics Data System (ADS)

    Shifley, Loren A.

    1990-08-01

    The recent introduction of a two dimensional interactive software package provides a new technique for quantitative analysis. Integrated with its corresponding peripherals, the same software offers either film or video data reduction. Digitized data points measured from the images are stored in the computer. With this data, a variety of information can be displayed, printed or plotted in a graphical form. The resultant graphs could determine such factors as: displacement, force, velocity, momentum, angular acceleration, center of gravity, energy, length, angle and time to name a few. Simple, efficient and precise analysis can now be quantified and documented. This paper will describe the detailed capabilities of the software along with a variety of applications where it might be used.

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

    PubMed

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

    2017-03-01

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

  8. Imaging visual function of the human brain

    SciTech Connect

    Marg, E.

    1988-10-01

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

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

    PubMed Central

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

    2015-01-01

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

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

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

    PubMed

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

    2014-01-01

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

  16. 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. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  17. 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

  18. 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. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

  19. DIDA - Dynamic Image Disparity Analysis.

    DTIC Science & Technology

    1982-12-31

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

  20. On image analysis in fractography (Methodological Notes)

    NASA Astrophysics Data System (ADS)

    Shtremel', M. A.

    2015-10-01

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

  1. Clock Scan Protocol for Image Analysis: ImageJ Plugins.

    PubMed

    Dobretsov, Maxim; Petkau, Georg; Hayar, Abdallah; Petkau, Eugen

    2017-06-19

    The clock scan protocol for image analysis is an efficient tool to quantify the average pixel intensity within, at the border, and outside (background) a closed or segmented convex-shaped region of interest, leading to the generation of an averaged integral radial pixel-intensity profile. This protocol was originally developed in 2006, as a visual basic 6 script, but as such, it had limited distribution. To address this problem and to join similar recent efforts by others, we converted the original clock scan protocol code into two Java-based plugins compatible with NIH-sponsored and freely available image analysis programs like ImageJ or Fiji ImageJ. Furthermore, these plugins have several new functions, further expanding the range of capabilities of the original protocol, such as analysis of multiple regions of interest and image stacks. The latter feature of the program is especially useful in applications in which it is important to determine changes related to time and location. Thus, the clock scan analysis of stacks of biological images may potentially be applied to spreading of Na(+) or Ca(++) within a single cell, as well as to the analysis of spreading activity (e.g., Ca(++) waves) in populations of synaptically-connected or gap junction-coupled cells. Here, we describe these new clock scan plugins and show some examples of their applications in image analysis.

  2. Program for Analysis and Enhancement of Images

    NASA Technical Reports Server (NTRS)

    Lu, Yun-Chi

    1987-01-01

    Land Analysis System (LAS) is collection of image-analysis computer programs designed to manipulate and analyze multispectral image data. Provides user with functions ingesting various sensor data, radiometric and geometric corrections, image registration, training site selection, supervised and unsupervised classification, Fourier domain filtering, and image enhancement. Sufficiently modular and includes extensive library of subroutines to permit inclusion of new algorithmic programs. Commercial package International Mathematical & Statistical Library (IMSL) required for full implementation of LAS. Written in VAX FORTRAN 77, C, and Macro assembler for DEC VAX operating under VMS 4.0.

  3. Compressed sensing cine imaging with high spatial or high temporal resolution for analysis of left ventricular function.

    PubMed

    Goebel, Juliane; Nensa, Felix; Schemuth, Haemi P; Maderwald, Stefan; Gratz, Marcel; Quick, Harald H; Schlosser, Thomas; Nassenstein, Kai

    2016-08-01

    To assess two compressed sensing cine magnetic resonance imaging (MRI) sequences with high spatial or high temporal resolution in comparison to a reference steady-state free precession cine (SSFP) sequence for reliable quantification of left ventricular (LV) volumes. LV short axis stacks of two compressed sensing breath-hold cine sequences with high spatial resolution (SPARSE-SENSE HS: temporal resolution: 40 msec, in-plane resolution: 1.0 × 1.0 mm(2) ) and high temporal resolution (SPARSE-SENSE HT: temporal resolution: 11 msec, in-plane resolution: 1.7 × 1.7 mm(2) ) and of a reference cine SSFP sequence (standard SSFP: temporal resolution: 40 msec, in-plane resolution: 1.7 × 1.7 mm(2) ) were acquired in 16 healthy volunteers on a 1.5T MR system. LV parameters were analyzed semiautomatically twice by one reader and once by a second reader. The volumetric agreement between sequences was analyzed using paired t-test, Bland-Altman plots, and Passing-Bablock regression. Small differences were observed between standard SSFP and SPARSE-SENSE HS for stroke volume (SV; -7 ± 11 ml; P = 0.024), ejection fraction (EF; -2 ± 3%; P = 0.019), and myocardial mass (9 ± 9 g; P = 0.001), but not for end-diastolic volume (EDV; P = 0.079) and end-systolic volume (ESV; P = 0.266). No significant differences were observed between standard SSFP and SPARSE-SENSE HT regarding EDV (P = 0.956), SV (P = 0.088), and EF (P = 0.103), but for ESV (3 ± 5 ml; P = 0.039) and myocardial mass (8 ± 10 ml; P = 0.007). Bland-Altman analysis showed good agreement between the sequences (maximum bias ≤ -8%). Two compressed sensing cine sequences, one with high spatial resolution and one with high temporal resolution, showed good agreement with standard SSFP for LV volume assessment. J. Magn. Reson. Imaging 2016;44:366-374. © 2016 Wiley Periodicals, Inc.

  4. 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

  5. Functional Magnetic Resonance Imaging Analysis of Food-Related Brain Activity in Patients with Lipodystrophy Undergoing Leptin Replacement Therapy

    PubMed Central

    Aotani, Daisuke; Sawamoto, Nobukatsu; Kusakabe, Toru; Aizawa-Abe, Megumi; Kataoka, Sachiko; Sakai, Takeru; Iogawa, Hitomi; Ebihara, Chihiro; Fujikura, Junji; Hosoda, Kiminori; Fukuyama, Hidenao; Nakao, Kazuwa

    2012-01-01

    Context: Lipodystrophy is a disease characterized by a paucity of adipose tissue and low circulating concentrations of adipocyte-derived leptin. Leptin-replacement therapy improves eating and metabolic disorders in patients with lipodystrophy. Objective: The aim of the study was to clarify the pathogenic mechanism of eating disorders in lipodystrophic patients and the action mechanism of leptin on appetite regulation. Subjects and Interventions: We investigated food-related neural activity using functional magnetic resonance imaging in lipodystrophic patients with or without leptin replacement therapy and in healthy controls. We also measured the subjective feelings of appetite. Results: Although there was little difference in the enhancement of neural activity by food stimuli between patients and controls under fasting, postprandial suppression of neural activity was insufficient in many regions of interest including amygdala, insula, nucleus accumbens, caudate, putamen, and globus pallidus in patients when compared with controls. Leptin treatment effectively suppressed postprandial neural activity in many of these regions of interest, whereas it showed little effect under fasting in patients. Consistent with these results, postprandial formation of satiety feeling was insufficient in patients when compared with controls, which was effectively reinforced by leptin treatment. Conclusions: This study demonstrated the insufficiency of postprandial suppression of food-related neural activity and formation of satiety feeling in lipodystrophic patients, which was effectively restored by leptin. The findings in this study emphasize the important pathological role of leptin in eating disorders in lipodystrophy and provide a clue to understanding the action mechanism of leptin in human, which may lead to development of novel strategies for prevention and treatment of obesity. PMID:22872692

  6. Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

    PubMed

    Moriguchi, Yoshiya; Noda, Takamasa; Nakayashiki, Kosei; Takata, Yohei; Setoyama, Shiori; Kawasaki, Shingo; Kunisato, Yoshihiko; Mishima, Kazuo; Nakagome, Kazuyuki; Hanakawa, Takashi

    2017-10-01

    Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  7. Functional magnetic resonance imaging analysis of food-related brain activity in patients with lipodystrophy undergoing leptin replacement therapy.

    PubMed

    Aotani, Daisuke; Ebihara, Ken; Sawamoto, Nobukatsu; Kusakabe, Toru; Aizawa-Abe, Megumi; Kataoka, Sachiko; Sakai, Takeru; Iogawa, Hitomi; Ebihara, Chihiro; Fujikura, Junji; Hosoda, Kiminori; Fukuyama, Hidenao; Nakao, Kazuwa

    2012-10-01

    Lipodystrophy is a disease characterized by a paucity of adipose tissue and low circulating concentrations of adipocyte-derived leptin. Leptin-replacement therapy improves eating and metabolic disorders in patients with lipodystrophy. The aim of the study was to clarify the pathogenic mechanism of eating disorders in lipodystrophic patients and the action mechanism of leptin on appetite regulation. We investigated food-related neural activity using functional magnetic resonance imaging in lipodystrophic patients with or without leptin replacement therapy and in healthy controls. We also measured the subjective feelings of appetite. Although there was little difference in the enhancement of neural activity by food stimuli between patients and controls under fasting, postprandial suppression of neural activity was insufficient in many regions of interest including amygdala, insula, nucleus accumbens, caudate, putamen, and globus pallidus in patients when compared with controls. Leptin treatment effectively suppressed postprandial neural activity in many of these regions of interest, whereas it showed little effect under fasting in patients. Consistent with these results, postprandial formation of satiety feeling was insufficient in patients when compared with controls, which was effectively reinforced by leptin treatment. This study demonstrated the insufficiency of postprandial suppression of food-related neural activity and formation of satiety feeling in lipodystrophic patients, which was effectively restored by leptin. The findings in this study emphasize the important pathological role of leptin in eating disorders in lipodystrophy and provide a clue to understanding the action mechanism of leptin in human, which may lead to development of novel strategies for prevention and treatment of obesity.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  9. Functional MRI using regularized parallel imaging acquisition.

    PubMed

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

    2005-08-01

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

  10. 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

  11. 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

  12. 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. Copyright © 2016 Elsevier B.V. All rights reserved.

  13. Spreadsheet-Like Image Analysis

    DTIC Science & Technology

    1992-08-01

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

  14. Knowledge-Based Image Analysis.

    DTIC Science & Technology

    1981-04-01

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

  15. Advances in noninvasive functional imaging of bone.

    PubMed

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

    2014-02-01

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

  16. Learning a cost function for microscope image segmentation.

    PubMed

    Nilufar, Sharmin; Perkins, Theodore J

    2014-01-01

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

  17. Longitudinal Functional Data Analysis.

    PubMed

    Park, So Young; Staicu, Ana-Maria

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

  18. Functional Magnetic Resonance Imaging and Pediatric Anxiety

    ERIC Educational Resources Information Center

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

    2008-01-01

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

  19. Functional 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.…

  20. Uncooled thermal imaging and image analysis

    NASA Astrophysics Data System (ADS)

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

    2006-09-01

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

  1. Functional CT imaging of prostate cancer

    NASA Astrophysics Data System (ADS)

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

    2003-09-01

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

  2. Intermediate elemental image reconstruction for refocused three-dimensional images in integral imaging by convolution with δ-function sequences

    NASA Astrophysics Data System (ADS)

    Yoo, Hoon; Jang, Jae-Young

    2017-10-01

    We propose a novel approach for intermediate elemental image reconstruction in integral imaging. To reconstruct intermediate elemental images, we introduce a null elemental image whose pixels are all zero. In the proposed method a number of null elemental images are inserted into a given elemental image array. The elemental image array with null elemental images is convolved with the δ-function sequence. The convolution result shows that the proposed method provides an efficient structure to expand an elemental image array. The resulting elemental image array from the proposed method can supply three-dimensional information for an object at a specific depth. In addition, the proposed method provides adjustable parameters, which can be utilized in design of integral imaging systems. The feasibility of the proposed method has been confirmed through preliminary experiments and theoretical analysis.

  3. 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.

  4. Magnetic resonance imaging based functional imaging in paediatric oncology.

    PubMed

    Manias, Karen A; Gill, Simrandip K; MacPherson, Lesley; Foster, Katharine; Oates, Adam; Peet, Andrew C

    2017-02-01

    Imaging is central to management of solid tumours in children. Conventional magnetic resonance imaging (MRI) is the standard imaging modality for tumours of the central nervous system (CNS) and limbs and is increasingly used in the abdomen. It provides excellent structural detail, but imparts limited information about tumour type, aggressiveness, metastatic potential or early treatment response. MRI based functional imaging techniques, such as magnetic resonance spectroscopy, diffusion and perfusion weighted imaging, probe tissue properties to provide clinically important information about metabolites, structure and blood flow. This review describes the role of and evidence behind these functional imaging techniques in paediatric oncology and implications for integrating them into routine clinical practice. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Analysis of dynamic brain imaging data.

    PubMed Central

    Mitra, P P; Pesaran, B

    1999-01-01

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

  6. 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.

  7. Functional imaging for prostate cancer: therapeutic implications.

    PubMed

    Mari Aparici, Carina; Seo, Youngho

    2012-09-01

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

  8. 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.

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

    PubMed

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

    2008-04-01

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

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

    PubMed

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

    2012-01-01

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

  11. Functional magnetic resonance imaging of the retina.

    PubMed

    Duong, Timothy Q; Ngan, Shing-Chung; Ugurbil, Kamil; Kim, Seong-Gi

    2002-04-01

    This study explored the feasibility of mapping the retina's responses to visual stimuli noninvasively, by using functional magnetic resonance imaging (fMRI). fMRI was performed on a 9.4-Tesla scanner to map activity-evoked signal changes of the retina-choroid complex associated with visual stimulation in anesthetized cats (n = 6). Three to 12 1-mm slices were acquired in a single shot using inversion-recovery, echo-planar imaging with a nominal in-plane resolution of 468 x 468 microm(2). Visual stimuli were presented to the full visual field and to the upper and lower visual fields. The stimuli were drifting or stationary gratings, which were compared with the dark condition. Activation maps were computed using cross-correlation analysis and overlaid on anatomic images. Multislice activation maps were reconstructed and flattened onto a two-dimensional surface. fMRI activation maps showed robust increased activity in the retina-choroid complex after visual stimulation. The average stimulus-evoked fMRI signal increase associated with drifting-grating stimulus was 1.7% +/- 0.5% (P < 10(-4), n = 6) compared with dark. Multislice functional images of the retina flattened onto a two-dimensional surface showed relatively uniform activation. No statistically significant activation was observed in and around the optic nerve head. Hemifield stimulation studies demonstrated that stimuli presented to the upper half of the visual field activated the lower part of the retina, and stimuli presented to the lower half of the visual field activated the upper part of the retina, as expected. Signal changes evoked by the stationary gratings compared with the dark basal condition were positive but were approximately half that evoked by the drifting gratings (1.0% +/- 0.1% versus 2.1% +/- 0.3%, P < 10(-4)). To the best of our knowledge, this is the first fMRI study of the retina, demonstrating its feasibility in imaging retinal function dynamically in a noninvasive manner and at

  12. 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.

  13. Functional Extended Redundancy Analysis

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  14. Functional Extended Redundancy Analysis

    ERIC Educational Resources Information Center

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

    2012-01-01

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

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

    PubMed

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

    2017-10-01

    Schizophrenia (SZ) and Bipolar Disorder (BD) are associated with deficits in both timing and cognitive control functions. However, the underlying neurological dysfunctions remain poorly understood. The main goal of this study was to identify brain structures activated both by increases in cognitive activity and during timing tasks in patients with SZ and BD relative to controls. We conducted two signed differential mapping (SDM) meta-analyses of functional magnetic resonance imaging studies assessing the brain response to increasing levels of cognitive difficulty: one concerned SZ, and the other BD patients. We conducted a similar SDM meta-analysis on neuroimaging of timing in SZ (no studies in BD could be included). Finally, we carried out a multimodal meta-analysis to identify common brain regions in the findings of the two previous meta-analyses. We found that SZ patients showed hypoactivation in timing-related cortical-subcortical areas. The dysfunction observed during timing partially coincided with deficits for cognitive control functions. We hypothesize that a dysfunctional temporal/cognitive control network underlies the persistent cognitive impairment observed in SZ. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    PubMed

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

    2012-11-01

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

  17. 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.

  18. Incorporating Functional Image Information to rpFNA Analysis for Breast Cancer Detection in High-Risk Women

    DTIC Science & Technology

    2011-03-01

    whole breast could differentiate between normal and abnormal tissues, but first the normal uptake of the 99mTc-sestamibi radiotracer must be established...acquire that baseline breast uptake information for future studies. Task 3: Optimize patient imaging and biopsy protocol. Task 3(b): Investigate how the...Publish research work in peer-reviewed journals In July 2010, “Characterizing the contribution of cardiac and hepatic uptake in dedicated breast SPECT

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

    DTIC Science & Technology

    2010-03-01

    for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data...counter, but no spatial information along the length of the needle would be available, and the length of time to measure the needle make it clinically...and biopsy procedures can be optimally integrated to minimize the patient scan times . Because we have decided not to pursue imaging the rpFNA

  20. Radiologist and automated image analysis

    NASA Astrophysics Data System (ADS)

    Krupinski, Elizabeth A.

    1999-07-01

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

  1. 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

  2. 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.

  3. Towards new functional nanostructures for medical imaging

    SciTech Connect

    Matsuura, Naomi; Rowlands, J. A.

    2008-10-15

    Nanostructures represent a promising new type of contrast agent for clinical medical imaging modalities, including magnetic resonance imaging, x-ray computed tomography, ultrasound, and nuclear imaging. Currently, most nanostructures are simple, single-purpose imaging agents based on spherical constructs (e.g., liposomes, micelles, nanoemulsions, macromolecules, dendrimers, and solid nanoparticle structures). In the next decade, new clinical imaging nanostructures will be designed as multi-functional constructs, to both amplify imaging signals at disease sites and deliver localized therapy. Proposals for nanostructures to fulfill these new functions will be outlined. New functional nanostructures are expected to develop in five main directions: Modular nanostructures with additive functionality; cooperative nanostructures with synergistic functionality; nanostructures activated by their in vivo environment; nanostructures activated by sources outside the patient; and novel, nonspherical nanostructures and components. The development and clinical translation of next-generation nanostructures will be facilitated by a combination of improved clarity of the in vivo imaging and biological challenges and the requirements to successfully overcome them; development of standardized characterization and validation systems tailored for the preclinical assessment of nanostructure agents; and development of streamlined commercialization strategies and pipelines tailored for nanostructure-based agents for their efficient translation to the clinic.

  4. 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

  5. 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.

  6. 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.

  7. Multispectral analysis of multimodal images.

    PubMed

    Kvinnsland, Yngve; Brekke, Njål; Taxt, Torfinn M; Grüner, Renate

    2009-01-01

    An increasing number of multimodal images represent a valuable increase in available image information, but at the same time it complicates the extraction of diagnostic information across the images. Multispectral analysis (MSA) has the potential to simplify this problem substantially as unlimited number of images can be combined, and tissue properties across the images can be extracted automatically. We have developed a software solution for MSA containing two algorithms for unsupervised classification, an EM-algorithm finding multinormal class descriptions and the k-means clustering algorithm, and two for supervised classification, a Bayesian classifier using multinormal class descriptions and a kNN-algorithm. The software has an efficient user interface for the creation and manipulation of class descriptions, and it has proper tools for displaying the results. The software has been tested on different sets of images. One application is to segment cross-sectional images of brain tissue (T1- and T2-weighted MR images) into its main normal tissues and brain tumors. Another interesting set of images are the perfusion maps and diffusion maps, derived images from raw MR images. The software returns segmentations that seem to be sensible. The MSA software appears to be a valuable tool for image analysis with multimodal images at hand. It readily gives a segmentation of image volumes that visually seems to be sensible. However, to really learn how to use MSA, it will be necessary to gain more insight into what tissues the different segments contain, and the upcoming work will therefore be focused on examining the tissues through for example histological sections.

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

    PubMed

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

    2010-05-01

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

  9. Functional Imaging and Migraine: New Connections?

    PubMed Central

    Schwedt, Todd J.; Chong, Catherine D.

    2015-01-01

    Purpose of Review Over the last several years, a growing number of brain functional imaging studies have provided insights into mechanisms underlying migraine. This manuscript reviews the recent migraine functional neuroimaging literature and provides recommendations for future studies that will help fill knowledge gaps. Recent Findings Positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) studies have identified brain regions that might be responsible for mediating the onset of a migraine attack and those associated with migraine symptoms. Enhanced activation of brain regions that facilitate processing of sensory stimuli suggests a mechanism by which migraineurs are hypersensitive to visual, olfactory, and cutaneous stimuli. Resting state functional connectivity MRI studies have identified numerous brain regions and functional networks with atypical functional connectivity in migraineurs, suggesting that migraine is associated with aberrant brain functional organization. Summary fMRI and PET studies that have identified brain regions and brain networks that are atypical in migraine have helped to describe the neurofunctional basis for migraine symptoms. Future studies should compare functional imaging findings in migraine to other headache and pain disorders and should explore the utility of functional imaging data as biomarkers for diagnostic and treatment purposes. PMID:25887764

  10. Knowledge based imaging for terrain analysis

    NASA Technical Reports Server (NTRS)

    Holben, Rick; Westrom, George; Rossman, David; Kurrasch, Ellie

    1992-01-01

    A planetary rover will have various vision based requirements for navigation, terrain characterization, and geological sample analysis. In this paper we describe a knowledge-based controller and sensor development system for terrain analysis. The sensor system consists of a laser ranger and a CCD camera. The controller, under the input of high-level commands, performs such functions as multisensor data gathering, data quality monitoring, and automatic extraction of sample images meeting various criteria. In addition to large scale terrain analysis, the system's ability to extract useful geological information from rock samples is illustrated. Image and data compression strategies are also discussed in light of the requirements of earth bound investigators.

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

    PubMed

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

    2013-02-01

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

  12. Functional magnetic resonance imaging studies of language.

    PubMed

    Small, Steven L; Burton, Martha W

    2002-11-01

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

  13. 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.

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

    PubMed Central

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

    2017-01-01

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

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

    PubMed Central

    Howseman, A M; Bowtell, R W

    1999-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  17. Functional minimization problems in image processing

    NASA Astrophysics Data System (ADS)

    Kim, Yunho; Vese, Luminita A.

    2008-02-01

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

  18. 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.

  19. 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

  20. Advantages in functional imaging of the brain

    PubMed Central

    Mier, Walter; Mier, Daniela

    2015-01-01

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

  1. 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

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

    PubMed

    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

    2016-03-01

    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 K(trans)(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 K(trans) obtained with unadjusted AIFs as high as 0.74. AIF-caused variations were larger in K(trans) 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 (= K(trans)/ve), was less sensitive to AIF variation than K(trans) (wCV for unadjusted AIFs: 0.45 for kepvs. 0.74 for K

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

    PubMed

    Garg, Nidhi; Krishan, Pawan; Syngle, Ashit

    2016-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    1995-05-01

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

  5. 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.

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

    PubMed

    Wu, Haiyan; Luo, Yi; Feng, Chunliang

    2016-12-01

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

  7. Computer assisted analysis of microscopy images

    NASA Astrophysics Data System (ADS)

    Sawicki, M.; Munhutu, P.; DaPonte, J.; Caragianis-Broadbridge, C.; Lehman, A.; Sadowski, T.; Garcia, E.; Heyden, C.; Mirabelle, L.; Benjamin, P.

    2009-01-01

    The use of Transmission Electron Microscopy (TEM) to characterize the microstructure of a material continues to grow in importance as technological advancements become increasingly more dependent on nanotechnology1 . Since nanoparticle properties such as size (diameter) and size distribution are often important in determining potential applications, a particle analysis is often performed on TEM images. Traditionally done manually, this has the potential to be labor intensive, time consuming, and subjective2. To resolve these issues, automated particle analysis routines are becoming more widely accepted within the community3. When using such programs, it is important to compare their performance, in terms of functionality and cost. The primary goal of this study was to apply one such software package, ImageJ to grayscale TEM images of nanoparticles with known size. A secondary goal was to compare this popular open-source general purpose image processing program to two commercial software packages. After a brief investigation of performance and price, ImageJ was identified as the software best suited for the particle analysis conducted in the study. While many ImageJ functions were used, the ability to break agglomerations that occur in specimen preparation into separate particles using a watershed algorithm was particularly helpful4.

  8. Errors from Image Analysis

    SciTech Connect

    Wood, William Monford

    2015-02-23

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

  9. Functional group analysis

    SciTech Connect

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

    1986-04-01

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

  10. 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.

  11. Predictors for functionally significant in-stent restenosis: an integrated analysis using coronary angiography, IVUS, and myocardial perfusion imaging.

    PubMed

    Kang, Soo-Jin; Cho, Young-Rak; Park, Gyung-Min; Ahn, Jung-Min; Han, Seung-Bong; Lee, Jong-Young; Kim, Won-Jang; Park, Duk-Woo; Lee, Seung-Whan; Kim, Young-Hak; Lee, Cheol Whan; Park, Seong-Wook; Mintz, Gary S; Park, Seung-Jung

    2013-11-01

    The aim of this study was to assess the clinical and morphological predictors for functionally significant in-stent restenosis (ISR). Although they have been studied de novo in native coronary artery lesions, the relationships between clinical and morphological characteristics and the hemodynamic significance of ISR are not well understood. In 175 patients with ISR of a single coronary artery (angiographic stenosis >50%), we compared quantitative coronary angiography and intravascular ultrasound (IVUS) with stress myocardial single-photon emission computed tomography (SPECT). A positive SPECT was a reversible perfusion defect in the territory of the ISR artery. Overall, 103 (59%) patients had a positive SPECT. In-segment IVUS minimal lumen area (MLA) was significantly smaller in lesions with positive SPECT compared with negative SPECT (1.7 ± 0.5 mm(2) vs. 2.4 ± 0.8 mm(2), p < 0.001). Stent underexpansion (minimal stent area <5.0 mm(2)) was more common in the positive SPECT group than in the negative SPECT group (52% vs. 32%, p = 0.010). A positive SPECT was seen in 54% (65 of 121) of focal ISR lesions compared with 70% (38 of 54) of multifocal or diffuse ISR lesions as assessed by IVUS (p = 0.039). Independent determinants for a positive SPECT were diabetes (odds ratio [OR]: 2.41; 95% confidence interval [CI]: 1.02 to 5.68; p = 0.046), in-segment angiographic diameter stenosis (OR: 1.06; 95% CI: 1.03 to 1.09; p < 0.001), in-segment IVUS-MLA (OR: 0.30; 95% CI: 0.14 to 0.63; p = 0.001), stent underexpansion (minimal stent area <5.0 mm(2)), (OR: 2.91; 95% CI: 1.19 to 7.07; p = 0.019), proximal location of the IVUS-MLA (OR: 4.62; 95% CI: 1.75 to 12.18; p = 0.002), and a multifocal or diffuse ISR pattern (OR: 2.50; 95% CI: 0.99 to 6.28; p = 0.050). An in-segment angiographic diameter stenosis ≥69.5% (72% sensitivity, 74% specificity, area under the curve = 0.793) and an IVUS-MLA ≤1.9 mm(2) (67% sensitivity, 75% specificity, area under the curve = 0.756) best

  12. Single particle raster image analysis of diffusion.

    PubMed

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

    2017-04-01

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

  13. 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.

  14. Contrast sensitivity function and image discrimination.

    PubMed

    Peli, E

    2001-02-01

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

  15. Functional outcome analysis of lumbar canal stenosis patients post decompression and posterior stabilization with stenosis grading using magnetic resonance imaging

    NASA Astrophysics Data System (ADS)

    Pili, M.; Tobing, S. D. A. L.

    2017-08-01

    Lumbar canal stenosis (LCS) is a condition that can potentially cause disability. It often occurs in aging populations. The aim of this study was to analyze the correlation between the clinical outcomes of postoperative patients and classifications that were based on MRI assessments. This prospective cohort study was carried out at Cipto Mangunkusumo General Hospital from January to July 2016 using consecutive sampling. Thirty-eight patient samples were obtained, all of whom were managed with the same surgical technique of decompression and posterior stabilization. The patients were categorized in four types based on MRI examination using the Schizas classification. Pre- and post-treatment (three months and six months) assessments of the patients were conducted according to Visual Analogue Scale (VAS), the Oswestry Disability Index (ODI), the Japanese Orthopedic Association Score (JOA), and the Roland-Morris Disability Questionnaire (RMDQ). The statistical analysis was performed using the statistical program for social science (SPSS) v.19. The average age of the patients in this sample was 58.92 years (range 50-70 years). There were 16 males and 22 females. Most patients were classified as type C (21 subjects) based on MRI examination. The improvement in the clinical scores of male subjects was better than in the female subjects. Significant differences were found in the six-month postoperative VAS (p = 0.003) and three-month postoperative JOA scores (p = 0.029). The results at follow-up showed that the VAS, ODI, JOA and RMDQ scores were improved. There were no statistical differences between the MRI-based classification and the clinical outcomes at preoperative, three and six months postoperative according to VAS (p = 0.451, p = 0.738, p = 0.448), ODI (p = 0.143, p = 0.929, p = 0.796), JOA (p = 0.157, p = 0.876, p = 0.961), and RMDQ (p = 0.065, p = 0.057, p = 0.094). There was clinical improvement after decompression and posterior stabilization in lumbar canal

  16. 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.

  17. 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.

  18. Functional Spectral Domain Optical Coherence Tomography imaging

    NASA Astrophysics Data System (ADS)

    Bower, Bradley A.

    Spectral Domain Optical Coherence Tomography (SDOCT) is a high-speed, high resolution imaging modality capable of structural and functional characterization of tissue microstructure. SDOCT fills a niche between histology and ultrasound imaging, providing non-contact, non-invasive backscattering amplitude and phase from a sample. Due to the translucent nature of the tissue, ophthalmic imaging is an ideal space for SDOCT imaging. Structural imaging of the retina has provided new insights into ophthalmic disease. The phase component of SDOCT images remains largely underexplored, though. While Doppler SDOCT has been explored in a research setting, it has yet to gain traction in the clinic. Other, functional exploitations of the phase are possible and necessary to expand the utility of SDOCT. Spectral Domain Phase Microscopy (SDPM) is an extension of SDOCT that is capable of resolving sub-wavelength displacements within a focal volume. Application of sub-wavelength displacement measurement imaging could provide a new method for non-invasive optophysiological measurement. This body of work encompasses both hardware and software design and development for implementation of SDOCT. Structural imaging was proven in both the lab and the clinic. Coarse phase changes associated with Doppler flow frequency shifts were recorded and a study was conducted to validate Doppler measurement. Fine phase changes were explored through SDPM applications. Preliminary optophysiology data was acquired to study the potential of sub-wavelength measurements in the retina. To remove the complexity associated with in-vivo human retinal imaging, a first principles approach using isolated nerve samples was applied using standard SDPM and a depthencoded technique for measuring conduction velocity. Results from amplitude as well as both coarse and fine phase processing are presented. In-vivo optophysiology using SDPM is a promising avenue for exploration, and projects furthering or extending this body

  19. Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia.

    PubMed

    Sundermann, Benedikt; Bode, Jens; Lueken, Ulrike; Westphal, Dorte; Gerlach, Alexander L; Straube, Benjamin; Wittchen, Hans-Ulrich; Ströhle, Andreas; Wittmann, André; Konrad, Carsten; Kircher, Tilo; Arolt, Volker; Pfleiderer, Bettina

    2017-01-01

    The approach to apply multivariate pattern analyses based on neuro imaging data for outcome prediction holds out the prospect to improve therapeutic decisions in mental disorders. Patients suffering from panic disorder with agoraphobia (PD/AG) often exhibit an increased perception of bodily sensations. The purpose of this investigation was to assess whether multivariate classification applied to a functional magnetic resonance imaging (fMRI) interoception paradigm can predict individual responses to cognitive behavioral therapy (CBT) in PD/AG. This analysis is based on pretreatment fMRI data during an interoceptive challenge from a multicenter trial of the German PANIC-NET. Patients with DSM-IV PD/AG were dichotomized as responders (n = 30) or non-responders (n = 29) based on the primary outcome (Hamilton Anxiety Scale Reduction ≥50%) after 6 weeks of CBT (2 h/week). fMRI parametric maps were used as features for response classification with linear support vector machines (SVM) with or without automated feature selection. Predictive accuracies were assessed using cross validation and permutation testing. The influence of methodological parameters and the predictive ability for specific interoception-related symptom reduction were further evaluated. SVM did not reach sufficient overall predictive accuracies (38.0-54.2%) for anxiety reduction in the primary outcome. In the exploratory analyses, better accuracies (66.7%) were achieved for predicting interoception-specific symptom relief as an alternative outcome domain. Subtle information regarding this alternative response criterion but not the primary outcome was revealed by post hoc univariate comparisons. In contrast to reports on other neurofunctional probes, SVM based on an interoception paradigm was not able to reliably predict individual response to CBT. Results speak against the clinical applicability of this technique.

  20. Multivariate image analysis in biomedicine.

    PubMed

    Nattkemper, Tim W

    2004-10-01

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

  1. Right ventricular plasticity and functional imaging

    PubMed Central

    Brittain, Evan L.; Hemnes, Anna R.; Keebler, Mary; Lawson, Mark; Byrd, Benjamin F.; DiSalvo, Tom

    2012-01-01

    Right ventricular (RV) function is a strong independent predictor of outcome in a number of distinct cardiopulmonary diseases. The RV has a remarkable ability to sustain damage and recover function which may be related to unique anatomic, physiologic, and genetic factors that differentiate it from the left ventricle. This capacity has been described in patients with RV myocardial infarction, pulmonary arterial hypertension, and chronic thromboembolic disease as well as post-lung transplant and post-left ventricular assist device implantation. Various echocardiographic and magnetic resonance imaging parameters of RV function contribute to the clinical assessment and predict outcomes in these patients; however, limitations remain with these techniques. Early diagnosis of RV function and better insight into the mechanisms of RV recovery could improve patient outcomes. Further refinement of established and emerging imaging techniques is necessary to aid subclinical diagnosis and inform treatment decisions. PMID:23130100

  2. 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.

  3. Integral-geometry morphological image analysis

    NASA Astrophysics Data System (ADS)

    Michielsen, K.; De Raedt, H.

    2001-07-01

    This paper reviews a general method to characterize the morphology of two- and three-dimensional patterns in terms of geometrical and topological descriptors. Based on concepts of integral geometry, it involves the calculation of the Minkowski functionals of black-and-white images representing the patterns. The result of this approach is an objective, numerical characterization of a given pattern. We briefly review the basic elements of morphological image processing, a technique to transform images to patterns that are amenable to further morphological image analysis. The image processing technique is applied to electron microscope images of nano-ceramic particles and metal-oxide precipitates. The emphasis of this review is on the practical aspects of the integral-geometry-based morphological image analysis but we discuss its mathematical foundations as well. Applications to simple lattice structures, triply periodic minimal surfaces, and the Klein bottle serve to illustrate the basic steps of the approach. More advanced applications include random point sets, percolation and complex structures found in block copolymers.

  4. 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.

  5. Analysis of Ventricular Function by Computed Tomography

    PubMed Central

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

    2014-01-01

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

  6. 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…

  7. Atlas-based analysis of cardiac shape and function: correction of regional shape bias due to imaging protocol for population studies.

    PubMed

    Medrano-Gracia, Pau; Cowan, Brett R; Bluemke, David A; Finn, J Paul; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Suinesiaputra, Avan; Young, Alistair A

    2013-09-13

    Cardiovascular imaging studies generate a wealth of data which is typically used only for individual study endpoints. By pooling data from multiple sources, quantitative comparisons can be made of regional wall motion abnormalities between different cohorts, enabling reuse of valuable data. Atlas-based analysis provides precise quantification of shape and motion differences between disease groups and normal subjects. However, subtle shape differences may arise due to differences in imaging protocol between studies. A mathematical model describing regional wall motion and shape was used to establish a coordinate system registered to the cardiac anatomy. The atlas was applied to data contributed to the Cardiac Atlas Project from two independent studies which used different imaging protocols: steady state free precession (SSFP) and gradient recalled echo (GRE) cardiovascular magnetic resonance (CMR). Shape bias due to imaging protocol was corrected using an atlas-based transformation which was generated from a set of 46 volunteers who were imaged with both protocols. Shape bias between GRE and SSFP was regionally variable, and was effectively removed using the atlas-based transformation. Global mass and volume bias was also corrected by this method. Regional shape differences between cohorts were more statistically significant after removing regional artifacts due to imaging protocol bias. Bias arising from imaging protocol can be both global and regional in nature, and is effectively corrected using an atlas-based transformation, enabling direct comparison of regional wall motion abnormalities between cohorts acquired in separate studies.

  8. Acoustic noise during functional magnetic resonance imaging.

    PubMed

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

    2000-10-01

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

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

    NASA Astrophysics Data System (ADS)

    Ying, Xiaoyou; Xiu, Rui-juan

    1994-05-01

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

  10. 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.

  11. Optical imaging device of retinal function

    NASA Astrophysics Data System (ADS)

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

    2002-06-01

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

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

    PubMed Central

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

    2011-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2005-03-01

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

  14. 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.

  15. A Unified Mathematical Approach to Image Analysis.

    DTIC Science & Technology

    1987-08-31

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

  16. ALISA: adaptive learning image and signal analysis

    NASA Astrophysics Data System (ADS)

    Bock, Peter

    1999-01-01

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

  17. Analysis of spatial pseudodepolarizers in imaging systems

    NASA Technical Reports Server (NTRS)

    Mcguire, James P., Jr.; Chipman, Russell A.

    1990-01-01

    The objective of a number of optical instruments is to measure the intensity accurately without bias as to the incident polarization state. One method to overcome polarization bias in optical systems is the insertion of a spatial pseudodepolarizer. Both the degree of depolarization and image degradation (from the polarization aberrations of the pseudodepolarizer) are analyzed for two depolarizer designs: (1) the Cornu pseudodepolarizer, effective for linearly polarized light, and (2) the dual Babinet compensator pseudodepolarizer, effective for all incident polarization states. The image analysis uses a matrix formalism to describe the polarization dependence of the diffraction patterns and optical transfer function.

  18. Characterization of microrod arrays by image analysis

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  19. Image reconstruction with analytical point spread functions

    NASA Astrophysics Data System (ADS)

    Asensio Ramos, A.; López Ariste, A.

    2010-07-01

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

  20. 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.

  1. Functional lung imaging using hyperpolarized gas MRI.

    PubMed

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

    2007-05-01

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

  2. Multifluorescence 2D gel imaging and image analysis.

    PubMed

    Vormbrock, Ingo; Hartwig, Sonja; Lehr, Stefan

    2012-01-01

    Although image acquisition and analysis are crucial steps within the multifluorescence two-dimensional gel electrophoresis workflow, some basics are frequently not carried out with the necessary diligence. This chapter should help to prevent easily avoidable failures during imaging and image preparation for comparative protein analysis.

  3. 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

  4. 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…

  5. 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…

  6. UV imaging in pharmaceutical analysis.

    PubMed

    Østergaard, Jesper

    2017-08-01

    UV imaging provides spatially and temporally resolved absorbance measurements, which are highly useful in pharmaceutical analysis. Commercial UV imaging instrumentation was originally developed as a detector for separation sciences, but the main use is in the area of in vitro dissolution and release testing studies. The review covers the basic principles of the technology and summarizes the main applications in relation to intrinsic dissolution rate determination, excipient compatibility studies and in vitro release characterization of drug substances and vehicles intended for parenteral administration. UV imaging has potential for providing new insights to drug dissolution and release processes in formulation development by real-time monitoring of swelling, precipitation, diffusion and partitioning phenomena. Limitations of current instrumentation are discussed and a perspective to new developments and opportunities given as new instrumentation is emerging. Copyright © 2017 Elsevier B.V. All rights reserved.

  7. 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.

  8. Fast Optical Imaging of Human Brain Function

    PubMed Central

    Gratton, Gabriele; Fabiani, Monica

    2010-01-01

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

  9. Longitudinal imaging pattern analysis (SPARE-CD index) detects early structural and functional changes before cognitive decline in healthy older adults

    PubMed Central

    Clark, Vanessa H.; Resnick, Susan M.; Doshi, Jimit; Beason-Held, Lori L.; Zhou, Yun; Ferrucci, Luigi; Wong, Dean F.; Kraut, Michael A.; Davatzikos, Christos

    2014-01-01

    This article investigates longitudinal imaging characteristics of early cognitive decline during normal aging, leveraging on high-dimensional imaging pattern classification methods for the development of early biomarkers of cognitive decline. By combining magnetic resonance imaging (MRI) and resting positron emission tomography (PET) cerebral blood flow (CBF) images, an individualized score is generated using high-dimensional pattern classification, which predicts subsequent cognitive decline in cognitively normal older adults of the Baltimore Longitudinal Study of Aging. The resulting score, termed SPARE-CD (Spatial Pattern of Abnormality for Recognition of Early Cognitive Decline), analyzed longitudinally for 143 cognitively normal subjects over 8 years, shows functional and structural changes well before (2.3–2.9 years) changes in neurocognitive testing (California Verbal Learning Test [CVLT] scores) can be measured. Additionally, this score is found to be correlated to the [11C] Pittsburgh compound B (PiB) PET mean distribution volume ratio at a later time. This work indicates that MRI and PET images, combined with advanced pattern recognition methods, may be useful for very early detection of cognitive decline. PMID:22365049

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

    PubMed

    Tong, Elizabeth; Komlosi, Peter; Wintermark, Max

    2015-12-01

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

  11. Electroencephalographic imaging of higher brain function

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  12. 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.

  13. 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

  14. 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.

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

    PubMed

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

    2016-05-01

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

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

    PubMed

    Anderson, Amy L; Thomason, Moriah E

    2013-11-01

    The organization of the brain is highly plastic in fetal life. Establishment of healthy neural functional systems during the fetal period is essential to normal growth and development. Across the last several decades, remarkable progress has been made in understanding the development of human fetal functional brain systems. This is largely due to advances in imaging methodologies. Fetal neuroimaging began in the 1950-1970's with fetal electroencephalography (EEG) applied during labor. Later, in the 1980's, magnetoencephalography (MEG) emerged as an effective approach for investigating fetal brain function. Most recently, functional magnetic resonance imaging (fMRI) has arisen as an additional powerful approach for examining fetal brain function. This review will discuss major developmental findings from fetal imaging studies such as the maturation of prenatal sensory system functions, functional hemispheric asymmetry, and sensory-driven neurodevelopment. We describe how with improved imaging and analysis techniques, functional imaging of the fetus has the potential to assess the earliest point of neural maturation and provide insight into the patterning and sequence of normal and abnormal brain development. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

    PubMed Central

    Dougherty, G

    2010-01-01

    Medical imaging has developed into one of the most important fields within scientific imaging due to the rapid and continuing progress in computerised medical image visualisation and advances in analysis methods and computer-aided diagnosis. Several research applications are selected to illustrate the advances in image analysis algorithms and visualisation. Recent results, including previously unpublished data, are presented to illustrate the challenges and ongoing developments. PMID:21611048

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

    PubMed

    Ganekal, S

    2013-01-01

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

  19. 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. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    PubMed

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

    2012-12-01

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

  1. Imaging analysis of LDEF craters

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  3. 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.

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

    PubMed

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

    2007-03-01

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

  5. Planning applications in image analysis

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  6. 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.

  7. Structural and functional brain imaging in schizophrenia.

    PubMed Central

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

    1991-01-01

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

  8. 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. 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

  10. Automated quantitative image analysis of nanoparticle assembly

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  11. Determining optimal medical image compression: psychometric and image distortion analysis

    PubMed Central

    2012-01-01

    Background Storage issues and bandwidth over networks have led to a need to optimally compress medical imaging files while leaving clinical image quality uncompromised. Methods To determine the range of clinically acceptable medical image compression across multiple modalities (CT, MR, and XR), we performed psychometric analysis of image distortion thresholds using physician readers and also performed subtraction analysis of medical image distortion by varying degrees of compression. Results When physician readers were asked to determine the threshold of compression beyond which images were clinically compromised, the mean image distortion threshold was a JPEG Q value of 23.1 ± 7.0. In Receiver-Operator Characteristics (ROC) plot analysis, compressed images could not be reliably distinguished from original images at any compression level between Q = 50 and Q = 95. Below this range, some readers were able to discriminate the compressed and original images, but high sensitivity and specificity for this discrimination was only encountered at the lowest JPEG Q value tested (Q = 5). Analysis of directly measured magnitude of image distortion from subtracted image pairs showed that the relationship between JPEG Q value and degree of image distortion underwent an upward inflection in the region of the two thresholds determined psychometrically (approximately Q = 25 to Q = 50), with 75 % of the image distortion occurring between Q = 50 and Q = 1. Conclusion It is possible to apply lossy JPEG compression to medical images without compromise of clinical image quality. Modest degrees of compression, with a JPEG Q value of 50 or higher (corresponding approximately to a compression ratio of 15:1 or less), can be applied to medical images while leaving the images indistinguishable from the original. PMID:22849336

  12. Determining optimal medical image compression: psychometric and image distortion analysis.

    PubMed

    Flint, Alexander C

    2012-07-31

    Storage issues and bandwidth over networks have led to a need to optimally compress medical imaging files while leaving clinical image quality uncompromised. To determine the range of clinically acceptable medical image compression across multiple modalities (CT, MR, and XR), we performed psychometric analysis of image distortion thresholds using physician readers and also performed subtraction analysis of medical image distortion by varying degrees of compression. When physician readers were asked to determine the threshold of compression beyond which images were clinically compromised, the mean image distortion threshold was a JPEG Q value of 23.1 ± 7.0. In Receiver-Operator Characteristics (ROC) plot analysis, compressed images could not be reliably distinguished from original images at any compression level between Q = 50 and Q = 95. Below this range, some readers were able to discriminate the compressed and original images, but high sensitivity and specificity for this discrimination was only encountered at the lowest JPEG Q value tested (Q = 5). Analysis of directly measured magnitude of image distortion from subtracted image pairs showed that the relationship between JPEG Q value and degree of image distortion underwent an upward inflection in the region of the two thresholds determined psychometrically (approximately Q = 25 to Q = 50), with 75 % of the image distortion occurring between Q = 50 and Q = 1. It is possible to apply lossy JPEG compression to medical images without compromise of clinical image quality. Modest degrees of compression, with a JPEG Q value of 50 or higher (corresponding approximately to a compression ratio of 15:1 or less), can be applied to medical images while leaving the images indistinguishable from the original.

  13. Overview of Functional Magnetic Resonance Imaging

    PubMed Central

    Glover, Gary H.

    2010-01-01

    Synopsis Blood Oxygen Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) depicts changes in deoxyhemoglobin concentration consequent to task-induced or spontaneous modulation of neural metabolism. Since its inception in 1990, this method has been widely employed in thousands of studies of cognition for clinical applications such as surgical planning, for monitoring treatment outcomes, and as a biomarker in pharmacologic and training programs. Technical developments have solved most of the challenges of applying fMRI in practice. These challenges include low contrast to noise ratio of BOLD signals, image distortion, and signal dropout. More recently, attention is turning to the use of pattern classification and other statistical methods to draw increasingly complex inferences about cognitive brain states from fMRI data. This paper reviews the methods, some of the challenges and the future of fMRI. PMID:21435566

  14. 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.

  15. 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

  16. 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

  17. High resolution multiplexed functional imaging in live embryos (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Xu, Dongli; Zhou, Weibin; Peng, Leilei

    2017-02-01

    Fourier multiplexed fluorescence lifetime imaging (FmFLIM) scanning laser optical tomography (FmFLIM-SLOT) combines FmFLIM and Scanning laser optical tomography (SLOT) to perform multiplexed 3D FLIM imaging of live embryos. The system had demonstrate multiplexed functional imaging of zebrafish embryos genetically express Foster Resonant Energy Transfer (FRET) sensors. However, previous system has a 20 micron resolution because the focused Gaussian beam diverges quickly from the focused plane, makes it difficult to achieve high resolution imaging over a long projection depth. Here, we present a high-resolution FmFLIM-SLOT system with achromatic Bessel beam, which achieves 3 micron resolution in 3D deep tissue imaging. In Bessel-FmFLIM-SLOT, multiple laser excitation lines are firstly intensity modulated by a Michelson interferometer with a spinning polygon mirror optical delay line, which enables Fourier multiplexed multi-channel lifetime measurements. Then, a spatial light modulator and a prism are used to transform the modulated Gaussian laser beam to an achromatic Bessel beam. The achromatic Bessel beam scans across the whole specimen with equal angular intervals as sample rotated. After tomography reconstruction and the frequency domain lifetime analysis method, both the 3D intensity and lifetime image of multiple excitation-emission can be obtained. Using Bessel-FmFLIM-SLOT system, we performed cellular-resolution FLIM tomography imaging of live zebrafish embryo. Genetically expressed FRET sensors in these embryo will allow non-invasive observation of multiple biochemical processes in vivo.

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

    PubMed Central

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

    2017-01-01

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

  19. Intravital multiphoton microscopy for imaging hepatobiliary function

    NASA Astrophysics Data System (ADS)

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

    2007-07-01

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

  20. Requirements for effective functional breast imaging

    NASA Astrophysics Data System (ADS)

    Weinberg, I. N.; Zawarzin, V.; Adler, L. P.; Pani, R.; DeVincentis, G.; Khalkhali, I.; Vargas, H.; Venegas, R.; Kim, S. C.; Bakale, G.; Levine, E.; Perrier, N.; Freimanis, R. I.; Lesko, N. M.; Newman, D. P.; Geisinger, K. R.; Berg, W. A.; Masood, S.

    2003-01-01

    Most nuclear medicine physicists were trained on devices aimed at functional neuroimaging. The clinical goals of brain-centered devices differ dramatically from the parameters needed to be useful in the breast clinic. We will discuss similarities and differences that impact on design considerations, and describe our latest generation of positron emission mammography and intraoperative products. Source of physiologic contrast: Clinical neuroimaging depends on flow agents to detect the presence of breaks in the blood-brain barrier. Breast flow agents are nonspecific, and may miss preinvasive lesions. Resolution: Brain cancers are generally diagnosed at late stages, so resolution is not so critical. Detecting early breast cancers, and specifying margins for surgery requires 3 mm spatial resolution or better. Prevalence: Primary brain cancer is uncommon, and lesions mimicking brain cancer are rare. Primary breast cancer is common, and benign lesions are even more common, so specificity and biopsy capability are very important. Anatomic references: Brain structure is standard, while breast structure is highly variable, requiring immobilization/compression for physiologic imaging and biopsy. Surgery: Complete cancer resections for brain are very rare, but are possible for breast with appropriate imaging guidance, implying the need for rapid and reliable imaging. To summarize, the breast clinic needs a rapid and highly sensitive method of assessing breast physiology, compatible with biopsy and surgery. Positron emission mammography devices, in handheld and X-ray platform based configurations, are ideal for this mission.

  1. 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

  2. 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. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  3. Multispectral Image Analysis of Hurricane Gilbert

    DTIC Science & Technology

    1989-05-19

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

  4. Automated Microarray Image Analysis Toolbox for MATLAB

    SciTech Connect

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

    2005-09-01

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

  5. 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.

  6. Statistical analysis of biophoton image

    NASA Astrophysics Data System (ADS)

    Wang, Susheng

    1998-08-01

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

  7. 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.

  8. Image analysis from root system pictures

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  9. Ultrasonic image analysis and image-guided interventions

    PubMed Central

    Noble, J. Alison; Navab, Nassir; Becher, H.

    2011-01-01

    The fields of medical image analysis and computer-aided interventions deal with reducing the large volume of digital images (X-ray, computed tomography, magnetic resonance imaging (MRI), positron emission tomography and ultrasound (US)) to more meaningful clinical information using software algorithms. US is a core imaging modality employed in these areas, both in its own right and used in conjunction with the other imaging modalities. It is receiving increased interest owing to the recent introduction of three-dimensional US, significant improvements in US image quality, and better understanding of how to design algorithms which exploit the unique strengths and properties of this real-time imaging modality. This article reviews the current state of art in US image analysis and its application in image-guided interventions. The article concludes by giving a perspective from clinical cardiology which is one of the most advanced areas of clinical application of US image analysis and describing some probable future trends in this important area of ultrasonic imaging research. PMID:22866237

  10. Final analysis of a prospective trial on functional imaging for nodal staging in patients with prostate cancer at high risk for lymph node involvement.

    PubMed

    Van den Bergh, Laura; Lerut, Evelyne; Haustermans, Karin; Deroose, Christophe M; Oyen, Raymond; Isebaert, Sofie; Budiharto, Tom; Ameye, Filip; Mottaghy, Felix M; Bogaerts, Kris; Van Poppel, Hendrik; Joniau, Steven

    2015-03-01

    Accurate staging modalities to diagnose lymph node involvement in patients with prostate cancer (PCa) are lacking. We wanted to prospectively assess sensitivity, specificity, and positive predictive value (PPV) and negative predictive value of (11)C-choline positron emission tomography (PET)-computed tomography (CT) and diffusion-weighted (DW) magnetic resonance imaging (MRI) for nodal staging in patients with PCa at high risk for lymph node involvement. In total, 75 patients with a risk≥10% but<35% for lymph node (LN) metastases (Partin tables) who had N0 lesions based on the findings of contrast-enhanced CT scans were included. Patients underwent (11)C-choline PET-CT and DW MRI before surgery, which consisted of a superextended lymph node dissection followed by radical prostatectomy. LNs were serially sectioned and histopathologically examined after pankeratin staining. These results were used as the gold standard to compare with the imaging results. Of 1,665 resected LNs (median = 21, range: 7-49), 106 affected LNs (median = 2, range: 1-10) were found in 37 of 75 patients (49%). On a region-based analysis, we found a low sensitivity of 8.2% and 9.5% and a PPV of 50.0% and 40.0% for (11)C-choline PET-CT and DW MRI, respectively. The patient-based analysis showed a sensitivity of 18.9% and 36.1% for and a PPV of 63.6% and 86.7% (11)C-choline PET-CT and DW MRI, respectively. Even when both imaging modalities were combined, sensitivity values remained too low to be clinically useful. Because of the low sensitivity, there is no indication for routine clinical use of either (11)C-choline PET-CT or DW MRI for LN staging in patients with PCa, in whom CT scan findings were normal. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. 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,…

  12. 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,…

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

    PubMed Central

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

    2015-01-01

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

  14. 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.

  15. 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.

  16. Percent area coverage through image analysis

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

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

  17. Nanoparticle Functionalization and Its Potentials for Molecular Imaging.

    PubMed

    Thiruppathi, Rukmani; Mishra, Sachin; Ganapathy, Mathangi; Padmanabhan, Parasuraman; Gulyás, Balázs

    2017-03-01

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

  18. Nanoparticle Functionalization and Its Potentials for Molecular Imaging

    PubMed Central

    Thiruppathi, Rukmani; Mishra, Sachin; Ganapathy, Mathangi

    2016-01-01

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

  19. Imaging of the diaphragm: anatomy and function.

    PubMed

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

    2012-01-01

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

  20. 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.

  1. Principles and clinical applications of image analysis.

    PubMed

    Kisner, H J

    1988-12-01

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

  2. 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.

  3. 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

  4. Quantifying pulmonary regurgitation and right ventricular function in surgically repaired tetralogy of Fallot: a comparative analysis of echocardiography and magnetic resonance imaging.

    PubMed

    Mercer-Rosa, Laura; Yang, Wei; Kutty, Shelby; Rychik, Jack; Fogel, Mark; Goldmuntz, Elizabeth

    2012-09-01

    Patients with repaired tetralogy of Fallot are monitored for pulmonary regurgitation (PR) and right ventricular (RV) function. We sought to compare measures of PR and RV function on echocardiogram to those on cardiac magnetic resonance (CMR) and to develop a new tool for assessing PR by echocardiogram. Patients with repaired tetralogy of Fallot (n=143; 12.5±3.2 years) had an echocardiogram and CMR within 3 months of each other. On echocardiogram, RV function was assessed by (1) Doppler tissue imaging of the RV free wall and (2) myocardial performance index. The ratio of diastolic and systolic time-velocity integrals measured by Doppler of the main pulmonary artery was calculated. CMR variables included RV ejection fraction, RV volumes, and pulmonary regurgitant fraction (RF). Pulmonary regurgitation was graded as mild (RF<20%), moderate (RF=20-40%), and severe (RF>40%). On CMR, RF was 34+17% and RV ejection fraction was 61+8%. Echocardiography had good sensitivity identifying cases with RF>20% (sensitivity 97%; 95% CI: 92-99%) but overestimated the amount of PR when RF<20% (false-positive rate 36%; 95% CI: 18-57%). The diastolic and systolic time-velocity integrals on echocardiogram showed moderate correlation with RF on CMR (R=0.60; P<0.0001). On CMR, RF of 20% and 40% corresponded with a diastolic and systolic time-velocity integral of 0.49 (95% CI: 0.44-0.56) and 0.72 (95% CI: 0.68-0.76), respectively. RV myocardial performance index correlated modestly with RV ejection fraction (r=-0.33; P<0.001). This study suggests that the diastolic and systolic time-velocity integrals ratio may make a modest contribution to the overall assessment of PR in patients with repaired tetralogy of Fallot and warrants further investigation. However, echocardiography continues to have a limited ability to quantify PR and RV function as compared with CMR.

  5. Image analysis: a consumer's guide.

    PubMed

    Meyer, F

    1983-01-01

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

  6. Functional Generalized Structured Component Analysis.

    PubMed

    Suk, Hye Won; Hwang, Heungsun

    2016-12-01

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

  7. Intramyocardial analysis of regional systolic and diastolic function in ischemic heart disease with Doppler tissue imaging: role of the different myocardial layers.

    PubMed

    Marcos-Alberca, Pedro; García-Fernández, Miguel A; Ledesma, María J; Malpica, Norberto; Santos, Andrés; Moreno, Mar; Bermejo, Javier; Antoranz, José C; Desco, Manuel

    2002-02-01

    Preliminary experimental data have shown a nonuniform distribution of myocardial velocities (MVs) across the myocardial wall in normal conditions. However, after ischemic damage to the myocardium, a different pattern of reduction in the myocardial layers has been reported. The aim of this study is to analyze the spatial distribution of MVs and the resultant myocardial velocity gradients (MVGs) during the systolic and diastolic time periods. Doppler tissue imaging (DTI) in color M-mode was used to evaluate 3 different myocardial layers (endocardium, mesocardium, and epicardium) and their changes as a result of ischemia. Thirty-two consecutive patients were studied with DTI color M-mode: 18 patients with a history of previous or ongoing myocardial infarction and 14 healthy subjects. Postprocessing of images was accomplished with proprietary software. MV and MVG values of all layers along both systolic and diastolic time were calculated. For temporal analysis, systole was subdivided in 3 equal periods. Early- and late-diastolic times were also identified. In ischemic patients, the mean MV and maximum MV throughout systole decreased significantly in the endocardium and mesocardium, whereas only slightly in the epicardium. The mean MVG was less in ischemic patients (0.66 +/- 0.11 vs 0.23 +/- 0.15, P <.03). Temporal analysis showed a decrease in the maximal MV and MVG in all layers over the 3 systolic periods. This decrease was the more consistent in mesocardium. In diastole, there was a decrease in maximal MV in all layers, being more pronounced in endocardium and mesocardium. Diastolic mean MVG was shown to be different between control and ischemic groups (-0.2 +/- 0.05 vs -0.10 +/- 0.04, P <.06). A significant decrease of the maximal MV in endocardium and mesocardium was reported in the temporal analysis during early diastole. No change was reported in the epicardium. The MVG value also showed a significant decrease (-2.69 +/- 0.29 vs -1.59 +/- 0.89, P <.02). In

  8. 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.

  9. Imaging Turkey's Crust with Receiver Functions and Ambient Noise

    NASA Astrophysics Data System (ADS)

    Cubuk, Y.; Vanacore, E. A.; Saygin, E.; Taymaz, T.

    2010-12-01

    Here we present preliminary results detailing the crustal structure of Turkey from a combination of receiver function and ambient seismic noise tomography analysis. We use over 250 3-component broadband stations from permanent and temporary networks in Turkey and surrounding regions to image structure in Turkey from a combination of receiver function and ambient seismic noise tomography from crust to upper-mantle. To date, receiver functions for teleseismic events between the period between 2008 and 2009 have been calculated using frequency domain deconvolution for approximately 120 of the available stations. Using the methodology of Niu and James (2002), the receiver functions are analyzed to joint solve for Vp/Vs ratio and Moho conversion depth. The resulting maps show a highly variable Moho with depths ranging between ~35 km and 58 km depth as well as a variable but generally high average Vp/Vs ratio. Rayleigh and Love wave group velocities extracted from the cross-correlations of ambient seismic noise are used in a nonlinear iterative tomographic inversion. Then the velocity models from the tomographic inversions are used in a joint inversion to create the Moho depth map of the region. We combine the receiver function results with results from ambient noise tomography to generate a comprehensive interpretation of the Moho and crustal structure of Turkey. The results mark the complex structure of the region. The seismic images from western Turkey show low velocities possibly linked to the elevated temperatures or fluid content. The images for central Turkey show low velocities for shallow depths but seismic velocity increases with depth; this also coincides with the geothermal potential of the region. The complex wavespeed images for eastern Turkey marks the effects of the ongoing geological processes such as the active collision of Anatolian block and Arabian plate.

  10. Naval Signal and Image Analysis Conference Report

    DTIC Science & Technology

    1998-02-26

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

  11. 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.

  12. Familial Essential Tremor Studied With Functional Magnetic Resonance Imaging

    NASA Astrophysics Data System (ADS)

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

    2003-09-01

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

  13. 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.

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

    SciTech Connect

    Hoffman, E.A.

    1995-12-31

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

  15. A comparative image analysis of radial Fourier-Chebyshev moments

    NASA Astrophysics Data System (ADS)

    Li, Bo

    2017-08-01

    On the basis of the discrete Fourier functions and the discrete Chebyshev polynomials, a new set of radial orthogonal moment functions were presented. The new moments construct a new discrete orthogonal plane, and take a new sampling method that overcomes the default of classical method, which can be effectively used in the image analysis. The experimental results show that the new radial moments are superior to the conventional moments in image reconstruction and computing efficiency.

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

    PubMed

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

    2014-03-01

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

  17. Microscopy image segmentation tool: Robust image data analysis

    SciTech Connect

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

    2014-03-15

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

  18. 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.

  19. Image registration with uncertainty analysis

    DOEpatents

    Simonson, Katherine M [Cedar Crest, NM

    2011-03-22

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

  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 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

  2. Image processing software for imaging spectrometry data analysis

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  3. Image processing software for imaging spectrometry data analysis

    NASA Astrophysics Data System (ADS)

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

    1988-02-01

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

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

    PubMed Central

    Victor, Jonathan D

    2006-01-01

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

  5. Information granules in image histogram analysis.

    PubMed

    Wieclawek, Wojciech

    2017-05-10

    A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced. The proposed approach is dedicated to digital images, especially to medical images acquired by Computed Tomography (CT). As the histogram equalization approach, this method is based on image histogram analysis. Yet, unlike the histogram equalization technique, it works on a selected range of the pixel intensity and is controlled by two parameters. Performance is tested on anonymous clinical CT series. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    PubMed Central

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

    2010-01-01

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

  7. Imaging the wave functions of adsorbed molecules.

    PubMed

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

    2014-01-14

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

  8. 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. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Functional analysis in MR urography - made simple.

    PubMed

    Khrichenko, Dmitry; Darge, Kassa

    2010-02-01

    MR urography (MRU) has proved to be a most advantageous imaging modality of the urinary tract in children, providing one-stop comprehensive morphological and functional information, without the utilization of ionizing radiation. The functional analysis of the MRU scan still requires external post-processing using relatively complex software. This has proved to be a limiting factor in widespread routine implementation of MRU functional analysis and use of MRU functional parameters similar to nuclear medicine. We present software, developed in a pediatric radiology department, that not only enables comprehensive automated functional analysis, but is also very user-friendly, fast, easily operated by the average radiologist or MR technician and freely downloadable at www.chop-fmru.com . A copy of IDL Virtual Machine is required for the installation, which is obtained at no charge at www.ittvis.com . The analysis software, known as "CHOP-fMRU," has the potential to help overcome the obstacles to widespread use of functional MRU in children.

  10. Objective assessment of olfactory function using functional magnetic resonance imaging.

    PubMed

    Toledano, Adolfo; Borromeo, Susana; Luna, Guillermo; Molina, Elena; Solana, Ana Beatriz; García-Polo, Pablo; Hernández, Juan Antonio; Álvarez-linera, Juan

    2012-01-01

    To show the results of a device that generates automated olfactory stimuli suitable for functional magnetic resonance imaging (fMRI) experiments. Ten normal volunteers, 5 women and 5 men, were studied. The system allows the programming of several sequences, providing the capability to synchronise the onset of odour presentation with acquisition by a trigger signal of the MRI scanner. The olfactometer is a device that allows selection of the odour, the event paradigm, the time of stimuli and the odour concentration. The paradigm used during fMRI scanning consisted of 15-s blocks. The odorant event took 2s with butanol, mint and coffee. We observed olfactory activity in the olfactory bulb, entorhinal cortex (4%), amygdala (2.5%) and temporo-parietal cortex, especially in the areas related to emotional integration. The device has demonstrated its effectiveness in stimulating olfactory areas and its capacity to adapt to fMRI equipment. Copyright © 2010 Elsevier España, S.L. All rights reserved.

  11. 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.

  12. 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

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

    PubMed

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

    2016-11-01

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

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

    PubMed Central

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

    2016-01-01

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

  15. 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.

  16. A Mathematical Framework for Image Analysis

    DTIC Science & Technology

    1991-08-01

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

  17. Functional calcium imaging in developing cortical networks.

    PubMed

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

    2011-10-22

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

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

    PubMed Central

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

    2016-01-01

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

  19. Sparse Superpixel Unmixing for Hyperspectral Image Analysis

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  20. 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.

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

    PubMed

    Merla, A; Romani, G L

    2006-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  3. 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

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

    PubMed

    Fongaro, Lorenzo; Alamprese, Cristina; Casiraghi, Ernestina

    2015-03-01

    During ripening of salami, colour changes occur due to oxidation phenomena involving myoglobin. Moreover, shrinkage due to dehydration results in aspect modifications, mainly ascribable to fat aggregation. The aim of this work was the application of image analysis (IA) and multivariate image analysis (MIA) techniques to the study of colour and aspect changes occurring in salami during ripening. IA results showed that red, green, blue, and intensity parameters decreased due to the development of a global darker colour, while Heterogeneity increased due to fat aggregation. By applying MIA, different salami slice areas corresponding to fat and three different degrees of oxidised meat were identified and quantified. It was thus possible to study the trend of these different areas as a function of ripening, making objective an evaluation usually performed by subjective visual inspection. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Functional micro-ultrasound imaging of rodent cerebral hemodynamics.

    PubMed

    van Raaij, Martijn E; Lindvere, Liis; Dorr, Adrienne; He, Jianfei; Sahota, Bhupinder; Foster, F Stuart; Stefanovic, Bojana

    2011-09-01

    Healthy cerebral microcirculation is crucial to neuronal functioning. We present a new method to investigate microvascular hemodynamics in living rodent brain through a focal cranial window based on high-frequency ultrasound imaging. The method has a temporal resolution of 40ms, and a 100μm in-plane and 600μm through-plane spatial resolution. We use a commercially available high-frequency ultrasound imaging system to quantify changes in the relative cerebral blood volume (CBV) by measuring the scattered signal intensity from an ultrasound contrast agent circulating in the vasculature. Generalized linear model analysis is then used to produce effect size and significance maps of changes in cerebral blood volume upon electrical stimulation of the forepaw. We observe larger CBV increases in the forelimb representation of the primary somatosensory cortex than in the deep gray matter with stimuli as short as 2s (5.1 ± 1.3% vs. 3.3 ± 0.6%). We also investigate the temporal evolution of the blood volume changes in cortical and subcortical gray matter, pial vessels and subcortical major vessels, and show shorter response onset times in the parenchymal regions than in the neighboring large vessels (1.6 ± 1.0s vs. 2.6 ± 1.3s in the cortex for a 10 second stimulus protocol). This method, which we termed functional micro-ultrasound imaging or fMUS, is a novel, highly accessible, and cost-effective way of imaging rodent brain microvascular topology and hemodynamics in vivo at 100micron resolution over a 1-by-1cm field of view with 10s-100s frames per second that opens up a new set of questions regarding brain function in preclinical models of health and disease. Copyright © 2011 Elsevier Inc. All rights reserved.

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

    PubMed

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

    2014-01-01

    The aim of this study was to assess a novel lactose functionalized magnetoliposomes (MLs) as an MR contrast agent to target hepatocytes as well as to evaluate the targeting ability of MLs for in vivo applications. In the present work, 17 nm sized iron oxide cores functionalized with anionic MLs bearing lactose moieties were used for targeting the asialoglycoprotein receptor (ASGP-r), which is highly expressed in hepatocytes. Non-functionalized anionic MLs were tested as negative controls. The size distribution of lactose and anionic MLs was determined by transmission electron microscopy (TEM) and dynamic light scattering (DLS). After intravenous administration of both MLs, contrast enhancement in the liver was observed by magnetic resonance imaging (MRI). Label retention was monitored non-invasively by MRI and validated with Prussian blue staining and TEM for up to eight days post MLs administration. Although the MRI signal intensity did not show significant differences between functionalized and non-functionalized particles, iron-specific Prussian blue staining and TEM analysis confirmed the uptake of lactose MLs mainly in hepatocytes. In contrast, non-functionalized anionic MLs were mainly taken up by Kupffer and sinusoidal cells. Target specificity was further confirmed by high-resolution MR imaging of phantoms containing isolated hepatocytes, Kupffer cell (KCs) and hepatic stellate cells (HSCs) fractions. Hypointense signal was observed for hepatocytes isolated from animals which received lactose MLs but not from animals which received anionic MLs. These data demonstrate that galactose-functionalized MLs can be used as a hepatocyte targeting MR contrast agent to potentially aid in the diagnosis of hepatic diseases if the non-specific uptake by KCs is taken into account. Copyright © 2013 Elsevier Ltd. All rights reserved.

  7. 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.

  8. Functional anatomy and imaging of the foot.

    PubMed

    Ridola, C; Palma, A

    2001-01-01

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

  9. Optical imaging of fast, dynamic neurophysiological function.

    SciTech Connect

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

    2002-01-01

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

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

    PubMed

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

    2007-05-01

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

  11. 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

  12. 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

  13. 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. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  14. 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

  15. 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.

  16. LANDSAT-4 image data quality analysis

    NASA Technical Reports Server (NTRS)

    Anuta, P. E.

    1984-01-01

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

  17. Merging Panchromatic and Multispectral Images for Enhanced Image Analysis

    DTIC Science & Technology

    1990-08-01

    Multispectral Images for Enhanced Image Analysis I, Curtis K. Munechika grant permission to the Wallace Memorial Library of the Rochester Institute of...0.0 ()0 (.0(%C’ trees 3. 5 2.5% 0.0%l 44. 1% 5 (.()0th ,crass .1 ().W 0.0% 0).0% 97. overall classification accuracy: 87.5%( T-able DlIb . Confusion

  18. 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.

  19. 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.

  20. 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.

  1. 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. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Landmark-based image registration using Gneiting's compactly supported functions

    NASA Astrophysics Data System (ADS)

    Cavoretto, Roberto; De Rossi, Alessandra

    2012-09-01

    In this paper we consider landmark-based image registration with compactly supported radial basis functions. Since using globally supported functions, as for example radial basis functions, a single landmark pair change may influence the whole registration result, in 2001 Fornefett et al. introduced the use of Wendland's compactly supported functions to define landmark-based image transformations [6]. Here we propose transformations defined by means of another family of compactly supported radial basis functions, known as Gneiting's functions [7, 5]. Firstly, we briefly review their definitions and properties. Secondly, numerical experiments are presented, where we compare Gneiting's functions with other interpolants.

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

    PubMed

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

    2015-06-01

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

  4. 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

  5. Dynamic ultrasound imaging applications to quantify musculoskeletal function.

    PubMed

    Sikdar, Siddhartha; Wei, Qi; Cortes, Nelson

    2014-07-01

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

  6. 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

  7. 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

  8. 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.

  9. 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

  10. Imaging flow cytometry for phytoplankton analysis.

    PubMed

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

    2017-01-01

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

  11. Digital Image Analysis for DETCHIP® Code Determination

    PubMed Central

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

    2013-01-01

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

  12. Impact of functional genomics and proteomics on radionuclide imaging.

    PubMed

    Haberkorn, Uwe; Altmann, Annette; Mier, Walter; Eisenhut, Michael

    2004-01-01

    The assessment of gene function following the completion of human genome sequencing may be performed using radionuclide imaging procedures. These procedures are needed for the evaluation of genetically manipulated animals or newly designed biomolecules, which requires a thorough understanding of physiology, biochemistry, and pharmacology. The experimental approaches will involve many new technologies, including in vivo imaging with single photon emission computed tomography and positron emission tomography. Nuclear medicine procedures may be applied for the determination of gene function and regulation using established and new tracers, or using in vivo reporter genes, such as genes encoding enzymes, receptors, antigens, or transporters. Visualization of in vivo reporter gene expression can be performed using radiolabeled substrates, antibodies, or ligands. Combinations of specific promoters and in vivo reporter genes may deliver information about the regulation of the corresponding genes. Furthermore, protein-protein interactions and activation of signal transduction pathways may be visualized noninvasively. The role of radiolabeled antisense molecules for the analysis of messenger ribonucleic acid (RNA) content has to be investigated. However, possible applications are therapeutic intervention using triplex oligonucleotides with therapeutic isotopes, which can be brought near to specific deoxyribonucleic acid sequences to induce deoxyribonucleic acid strand breaks at selected loci. Imaging of labeled siRNA makes sense if these are used for therapeutic purposes to assess the delivery of these new drugs to their target tissue. Pharmacogenomics will identify new surrogate markers for therapy monitoring, which may represent potential new tracers for imaging. Drug distribution studies for new therapeutic biomolecules are needed at least during preclinical stages of drug development. New treatment modalities, such as gene therapy with suicide genes, will need

  13. 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.

  14. Structural and Functional Imaging in Parkinsonian Syndromes

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2013-01-01

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

  16. 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.

  17. Theory of Image Analysis and Recognition.

    DTIC Science & Technology

    1983-01-24

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

  18. Bridging the Semantic Gap Between Diagnostic Histopathology and Image Analysis.

    PubMed

    Traore, Lamine; Kergosien, Yannick; Racoceanu, Daniel

    2017-01-01

    With the wider acceptance of Whole Slide Images (WSI) in histopathology domain, automatic image analysis algorithms represent a very promising solution to support pathologist's laborious tasks during the diagnosis process, to create a quantification-based second opinion and to enhance inter-observer agreement. In this context, reference vocabularies and formalization of the associated knowledge are especially needed to annotate histopathology images with labels complying with semantic standards. In this work, we elaborate a sustainable triptych able to bridge the gap between pathologists and image analysis scientists. The proposed paradigm is structured along three components: i) extracting a relevant semantic repository from the College of American Pathologists (CAP) organ-specific Cancer Checklists and associated Protocols (CC&P); ii) identifying imaging formalized knowledge issued from effective histopathology imaging methods highlighted by recent Digital Pathology (DP) contests and iii) proposing a formal representation of the imaging concepts and functionalities issued from major biomedical imaging software (MATLAB, ITK, ImageJ). Since the first step i) has been the object of a recent publication of our team, this study focuses on the steps ii) and iii). Our hypothesis is that the management of available semantic resources concerning the histopathology imaging tasks associated with effective methods highlighted by the recent DP challenges will facilitate the integration of WSI in clinical routine and support new generation of DP protocols.

  19. Variability of clinical functional MR imaging results: a multicenter study.

    PubMed

    Wurnig, Moritz C; Rath, Jakob; Klinger, Nicolaus; Höllinger, Ilse; Geissler, Alexander; Fischmeister, Florian P; Aichhorn, Markus; Foki, Thomas; Kronbichler, Martin; Nickel, Janpeter; Siedentopf, Christian; Staffen, Wolfgang; Verius, Michael; Golaszewski, Stefan; Koppelstätter, Florian; Knosp, Engelbert; Auff, Eduard; Felber, Stephan; Seitz, Rüdiger J; Beisteiner, Roland

    2013-08-01

    To investigate intersite variability of clinical functional magnetic resonance (MR) imaging, including influence of task standardization on variability and use of various parameters to inform the clinician whether the reliability of a given functional localization is high or low. Local ethics committees approved the study; all participants gave written informed consent. Eight women and seven men (mean age, 40 years) were prospectively investigated at three experienced functional MR sites with 1.5- (two sites) or 3-T (one site) MR. Nonstandardized motor and highly standardized somatosensory versions of a frequently requested clinical task (localization of the primary sensorimotor cortex) were used. Perirolandic functional MR variability was assessed (peak activation variability, center of mass [COM] variability, intraclass correlation values, overlap ratio [OR], activation size ratio). Data quality measures for functional MR images included percentage signal change (PSC), contrast-to-noise ratio (CNR), and head motion parameters. Data were analyzed with analysis of variance and a correlation analysis. Localization of perirolandic functional MR activity differed by 8 mm (peak activity) and 6 mm (COM activity) among sites. Peak activation varied up to 16.5 mm (COM range, 0.4-16.5 mm) and 45.5 mm (peak activity range, 1.8-45.5 mm). Signal strength (PSC, CNR) was significantly lower for the somatosensory task (mean PSC, 1.0% ± 0.5 [standard deviation]; mean CNR, 1.2 ± 0.4) than for the motor task (mean PSC, 2.4% ± 0.8; mean CNR, 2.9 ± 0.9) (P < .001, both). Intersite variability was larger with low signal strength (negative correlations between signal strength and peak activation variability) even if the task was highly standardized (mean OR, 22.0% ± 18.9 [somatosensory task] and 50.1% ± 18.8 [motor task]). Clinical practice and clinical functional MR biomarker studies should consider that the center of task-specific brain activation may vary up to 16.5 mm, with

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

    PubMed Central

    2016-01-01

    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

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1984-01-01

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

  3. Digital image processing in cephalometric analysis.

    PubMed

    Jäger, A; Döler, W; Schormann, T

    1989-01-01

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

  4. An Imaging And Graphics Workstation For Image Sequence Analysis

    NASA Astrophysics Data System (ADS)

    Mostafavi, Hassan

    1990-01-01

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

  5. Biophotonics techniques for structural and functional imaging, in vivo.

    PubMed

    Ardeshirpour, Yasaman; Gandjbakhche, Amir H; Najafizadeh, Laleh

    2013-01-01

    In vivo optical imaging is being conducted in a variety of medical applications, including optical breast cancer imaging, functional brain imaging, endoscopy, exercise medicine, and monitoring the photodynamic therapy and progress of neoadjuvant chemotherapy. In the past three decades, in vivo diffuse optical breast cancer imaging has shown promising results in cancer detection, and monitoring the progress of neoadjuvant chemotherapy. The use of near infrared spectroscopy for functional brain imaging has been growing rapidly. In fluorescence imaging, the difference between autofluorescence of cancer lesions compared to normal tissues were used in endoscopy to distinguish malignant lesions from normal tissue or inflammation and in determining the boarders of cancer lesions in surgery. Recent advances in drugs targeting specific tumor receptors, such as monoclonal antibodies (mAb), has created a new demand for developing non-invasive in vivo imaging techniques for detection of cancer biomarkers, and for monitoring their down regulations during therapy. Targeted treatments, combined with new imaging techniques, are expected to potentially result in new imaging and treatment paradigms in cancer therapy. Similar approaches can potentially be applied for the characterization of other disease-related biomarkers. In this chapter, we provide a review of diffuse optical and fluorescence imaging techniques with their application in functional brain imaging and cancer diagnosis.

  6. Biophotonics techniques for structural and functional imaging, in vivo.

    PubMed

    Ardeshirpour, Yasaman; Gandjbakhche, Amir H; Najafizadeh, Laleh

    2012-01-01

    In vivo optical imaging is being conducted in a variety of medical applications, including optical breast cancer imaging, functional brain imaging, endoscopy, exercise medicine, and monitoring the photodynamic therapy and progress of neoadjuvant chemotherapy. In the past three decades, in vivo diffuse optical breast cancer imaging has shown promising results in cancer detection, and monitoring the progress of neoadjuvant chemotherapy. The use of near infrared spectroscopy for functional brain imaging has been growing rapidly. In fluorescence imaging, the difference between autofluorescence of cancer lesions compared to normal tissues were used in endoscopy to distinguish malignant lesions from normal tissue or inflammation and in determining the boarders of cancer lesions in surgery. Recent advances in drugs targeting specific tumor receptors, such as AntiBodies (MAB), has created a new demand for developing non-invasive in vivo imaging techniques for detection of cancer biomarkers, and for monitoring their down regulations during therapy. Targeted treatments, combined with new imaging techniques, are expected to potentially result in new imaging and treatment paradigms in cancer therapy. Similar approaches can potentially be applied for the characterization of other disease-related biomarkers. In this chapter, we provide a review of diffuse optical and fluorescence imaging techniques with their application in functional brain imaging and cancer diagnosis.

  7. 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.

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

    PubMed

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

    2017-01-01

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

  9. Machine learning applications in cell image analysis.

    PubMed

    Kan, Andrey

    2017-04-04

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

  10. A Robust Actin Filaments Image Analysis Framework

    PubMed Central

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

    2016-01-01

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

  11. 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

  12. Parametric functional principal component analysis.

    PubMed

    Sang, Peijun; Wang, Liangliang; Cao, Jiguo

    2017-09-01

    Functional principal component analysis (FPCA) is a popular approach in functional data analysis to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs). Most existing FPCA approaches use a set of flexible basis functions such as B-spline basis to represent the FPCs, and control the smoothness of the FPCs by adding roughness penalties. However, the flexible representations pose difficulties for users to understand and interpret the FPCs. In this article, we consider a variety of applications of FPCA and find that, in many situations, the shapes of top FPCs are simple enough to be approximated using simple parametric functions. We propose a parametric approach to estimate the top FPCs to enhance their interpretability for users. Our parametric approach can also circumvent the smoothing parameter selecting process in conventional nonparametric FPCA methods. In addition, our simulation study shows that the proposed parametric FPCA is more robust when outlier curves exist. The parametric FPCA method is demonstrated by analyzing several datasets from a variety of applications. © 2017, The International Biometric Society.

  13. 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.

  14. A functional analysis of crying.

    PubMed

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

    2013-01-01

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

  15. 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.

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

    PubMed

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

    2002-01-01

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

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

    PubMed

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

    2006-01-01

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

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

    PubMed

    Lange, N

    1996-02-28

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

  19. Multiresolution morphological analysis of document images

    NASA Astrophysics Data System (ADS)

    Bloomberg, Dan S.

    1992-11-01

    An image-based approach to document image analysis is presented, that uses shape and textural properties interchangeably at multiple scales. Image-based techniques permit a relatively small number of simple and fast operations to be used for a wide variety of analysis problems with document images. The primary binary image operations are morphological and multiresolution. The generalized opening, a morphological operation, allows extraction of image features that have both shape and textural properties, and that are not limited by properties related to image connectivity. Reduction operations are necessary due to the large number of pixels at scanning resolution, and threshold reduction is used for efficient and controllable shape and texture transformations between resolution levels. Aspects of these techniques, which include sequences of threshold reductions, are illustrated by problems such as text/halftone segmentation and word-level extraction. Both the generalized opening and these multiresolution operations are then used to identify italic and bold words in text. These operations are performed without any attempt at identification of individual characters. Their robustness derives from the aggregation of statistical properties over entire words. However, the analysis of the statistical properties is performed implicitly, in large part through nonlinear image processing operations. The approximate computational cost of the basic operations is given, and the importance of operating at the lowest feasable resolution is demonstrated.

  20. The impact of functional imaging on radiation medicine.

    PubMed

    Sharma, Nidhi; Neumann, Donald; Macklis, Roger

    2008-09-15

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

  1. Edge enhanced morphology for infrared image analysis

    NASA Astrophysics Data System (ADS)

    Bai, Xiangzhi; Liu, Haonan

    2017-01-01

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

  2. Image Analysis of the Tumor Microenvironment.

    PubMed

    Lloyd, Mark C; Johnson, Joseph O; Kasprzak, Agnieszka; Bui, Marilyn M

    2016-01-01

    In the field of pathology it is clear that molecular genomics and digital imaging represent two promising future directions, and both are as relevant to the tumor microenvironment as they are to the tumor itself (Beck AH et al. Sci Transl Med 3(108):108ra113-08ra113, 2011). Digital imaging, or whole slide imaging (WSI), of glass histology slides facilitates a number of value-added competencies which were not previously possible with the traditional analog review of these slides under a microscope by a pathologist. As an important tool for investigational research, digital pathology can leverage the quantification and reproducibility offered by image analysis to add value to the pathology field. This chapter will focus on the application of image analysis to investigate the tumor microenvironment and how quantitative investigation can provide deeper insight into our understanding of the tumor to tumor microenvironment relationship.

  3. Topological image texture analysis for quality assessment

    NASA Astrophysics Data System (ADS)

    Asaad, Aras T.; Rashid, Rasber Dh.; Jassim, Sabah A.

    2017-05-01

    Image quality is a major factor influencing pattern recognition accuracy and help detect image tampering for forensics. We are concerned with investigating topological image texture analysis techniques to assess different type of degradation. We use Local Binary Pattern (LBP) as a texture feature descriptor. For any image construct simplicial complexes for selected groups of uniform LBP bins and calculate persistent homology invariants (e.g. number of connected components). We investigated image quality discriminating characteristics of these simplicial complexes by computing these models for a large dataset of face images that are affected by the presence of shadows as a result of variation in illumination conditions. Our tests demonstrate that for specific uniform LBP patterns, the number of connected component not only distinguish between different levels of shadow effects but also help detect the infected regions as well.

  4. 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.

  5. Single-image molecular analysis for accelerated fluorescence imaging

    NASA Astrophysics Data System (ADS)

    Wang, Yan Mei

    2011-03-01

    We have developed a new single-molecule fluorescence imaging analysis method, SIMA, to improve the temporal resolution of single-molecule localization and tracking studies to millisecond timescales without compromising the nanometer range spatial resolution [1,2]. In this method, the width of the fluorescence intensity profile of a static or mobile molecule, imaged using submillisecond to milliseconds exposure time, is used for localization and dynamics analysis. We apply this method to three single-molecule studies: (1) subdiffraction molecular separation measurements, (2) axial localization precision measurements, and (3) protein diffusion coefficient measurements in free solution. Applications of SIMA in flagella IFT particle analysis, localizations of UgtP (a cell division regulator protein) in live cells, and diffusion coefficient measurement of LacI in vitro and in vivo will be discussed.

  6. Is there an optimal deconvolution method for receiver function imaging?

    NASA Astrophysics Data System (ADS)

    Spieker, Kathrin; Rondenay, Stéphane; Halpaap, Felix

    2015-04-01

    Deconvolution is an essential processing step in receiver function analysis. A variety of deconvolution approaches have been employed over the past few decades, including frequency-domain spectral division, multi-taper cross-correlation, time-domain least squares filtering, and iterative time-domain deconvolution. Every deconvolution approach has its advantages and disadvantages but no systematic comparison of these approaches has yet been done. Here, we carry out benchmark tests on synthetic and real data to assess how the various approaches perform for different input conditions including noise content and the complexity of the target structure. We present the results of this comparison and evaluate the various deconvolution approaches to provide a set of guidelines on how to use the different types of deconvolutions more efficently. Generally, our results show that the different approaches produce receiver functions that are equally robust provided that a suitable regularization parameter is found. For this purpose, we propose an efficient way of finding an optimal regularization parameter through the measure of spectral flatness of the receiver function. Our deconvolution intercomparison results also help us estimate the uncertainty of the receiver functions more accurately. In the process, we find that some deconvolution approaches may be better adapted than others to addressing specific imaging goals.

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

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.; Juvvadi, Sridhar

    1988-06-01

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

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

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Jin, Weiqi

    2009-07-01

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

  9. Hybrid Expert Systems In Image Analysis

    NASA Astrophysics Data System (ADS)

    Dixon, Mark J.; Gregory, Paul J.

    1987-04-01

    Vision systems capable of inspecting industrial components and assemblies have a large potential market if they can be easily programmed and produced quickly. Currently, vision application software written in conventional high-level languages such as C or Pascal are produced by experts in program design, image analysis, and process control. Applications written this way are difficult to maintain and modify. Unless other similar inspection problems can be found, the final program is essentially one-off redundant code. A general-purpose vision system targeted for the Visual Machines Ltd. C-VAS 3000 image processing workstation, is described which wil