Science.gov

Sample records for improving image analysis

  1. [Decomposition of Interference Hyperspectral Images Using Improved Morphological Component Analysis].

    PubMed

    Wen, Jia; Zhao, Jun-suo; Wang, Cai-ling; Xia, Yu-li

    2016-01-01

    As the special imaging principle of the interference hyperspectral image data, there are lots of vertical interference stripes in every frames. The stripes' positions are fixed, and their pixel values are very high. Horizontal displacements also exist in the background between the frames. This special characteristics will destroy the regular structure of the original interference hyperspectral image data, which will also lead to the direct application of compressive sensing theory and traditional compression algorithms can't get the ideal effect. As the interference stripes signals and the background signals have different characteristics themselves, the orthogonal bases which can sparse represent them will also be different. According to this thought, in this paper the morphological component analysis (MCA) is adopted to separate the interference stripes signals and background signals. As the huge amount of interference hyperspectral image will lead to glow iterative convergence speed and low computational efficiency of the traditional MCA algorithm, an improved MCA algorithm is also proposed according to the characteristics of the interference hyperspectral image data, the conditions of iterative convergence is improved, the iteration will be terminated when the error of the separated image signals and the original image signals are almost unchanged. And according to the thought that the orthogonal basis can sparse represent the corresponding signals but cannot sparse represent other signals, an adaptive update mode of the threshold is also proposed in order to accelerate the computational speed of the traditional MCA algorithm, in the proposed algorithm, the projected coefficients of image signals at the different orthogonal bases are calculated and compared in order to get the minimum value and the maximum value of threshold, and the average value of them is chosen as an optimal threshold value for the adaptive update mode. The experimental results prove that

  2. Core analysis and CT imaging improve shale completions

    SciTech Connect

    Blauch, M.E.; Venditto, J.J. ); Rothman, E.; Hyde, P. )

    1992-11-16

    To improve hydraulic fracturing efficiency in Devonian shales, core analysis and computerized tomography (CT) can provide data for orienting perforations, determining fracture direction, and selecting deviated well trajectories. This article reports on technology tested in a West Virginia well for improving the economics of developing Devonian shale and other low permeability gas reservoirs. With slight production increase per well, Columbia Natural Resources Inc. (CNR) has determined that marginal gas well payout time can be shortened enough to encourage additional drilling. For eight wells completed by CNR in 1992, the absolute open flow (AOF) averaged 116 Mcfd before stimulation. After stimulation using long-standing fracture stimulation procedures, the AOF averaged 500 Mcfd.

  3. Textural Analysis of Hyperspectral Images for Improving Contaminant Detection Accuracy

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Previous studies demonstrated a hyperspectral imaging system has a potential for poultry fecal contaminant detection by measuring reflectance intensity. The simple image ratio at 565 and 517-nm images with optimal thresholding was able to detect fecal contaminants on broiler carcasses with high acc...

  4. Textural Analysis of Hyperspectral Images for Improving Detection Accuracy

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Detection of fecal contamination is crucial for food safety to protect consumers from food pathogens. Previous studies demonstrated a hyperspectral imaging system has a potential for poultry fecal contaminant detection by measuring reflectance intensity. The simple image ratio with optimal thresho...

  5. Improving Resolution and Depth of Astronomical Observations via Modern Mathematical Methods for Image Analysis

    NASA Astrophysics Data System (ADS)

    Castellano, M.; Ottaviani, D.; Fontana, A.; Merlin, E.; Pilo, S.; Falcone, M.

    2015-09-01

    In the past years modern mathematical methods for image analysis have led to a revolution in many fields, from computer vision to scientific imaging. However, some recently developed image processing techniques successfully exploited by other sectors have been rarely, if ever, experimented on astronomical observations. We present here tests of two classes of variational image enhancement techniques: "structure-texture decomposition" and "super-resolution" showing that they are effective in improving the quality of observations. Structure-texture decomposition allows to recover faint sources previously hidden by the background noise, effectively increasing the depth of available observations. Super-resolution yields an higher-resolution and a better sampled image out of a set of low resolution frames, thus mitigating problematics in data analysis arising from the difference in resolution/sampling between different instruments, as in the case of EUCLID VIS and NIR imagers.

  6. The influence of bonding agents in improving interactions in composite propellants determined using image analysis.

    PubMed

    Dostanić, J; Husović, T V; Usćumlić, G; Heinemann, R J; Mijin, D

    2008-12-01

    Binder-oxidizer interactions in rocket composite propellants can be improved using adequate bonding agents. In the present work, the effectiveness of different 1,3,5-trisubstituted isocyanurates was determined by stereo and metallographic microscopy and using the software package Image-Pro Plus. The chemical analysis of samples was performed by a scanning electron microscope equipped for energy dispersive spectrometry. PMID:19094035

  7. Improvement and error analysis of quantitative information extraction in diffraction-enhanced imaging

    NASA Astrophysics Data System (ADS)

    Yang, Hao; Xuan, Rui-Jiao; Hu, Chun-Hong; Duan, Jing-Hao

    2014-04-01

    Diffraction-enhanced imaging (DEI) is a powerful phase-sensitive technique that provides higher spatial resolution and supercontrast of weakly absorbing objects than conventional radiography. It derives contrast from the X-ray absorption, refraction, and ultra-small-angle X-ray scattering (USAXS) properties of an object. The separation of different-contrast contributions from images is an important issue for the potential application of DEI. In this paper, an improved DEI (IDEI) method is proposed based on the Gaussian curve fitting of the rocking curve (RC). Utilizing only three input images, the IDEI method can accurately separate the absorption, refraction, and USAXS contrasts produced by the object. The IDEI method can therefore be viewed as an improvement to the extended DEI (EDEI) method. In contrast, the IDEI method can circumvent the limitations of the EDEI method well since it does not impose a Taylor approximation on the RC. Additionally, analysis of the IDEI model errors is performed to further investigate the factors that lead to the image artifacts, and finally validation studies are conducted using computer simulation and synchrotron experimental data.

  8. Improved disparity map analysis through the fusion of monocular image segmentations

    NASA Technical Reports Server (NTRS)

    Perlant, Frederic P.; Mckeown, David M.

    1991-01-01

    The focus is to examine how estimates of three dimensional scene structure, as encoded in a scene disparity map, can be improved by the analysis of the original monocular imagery. The utilization of surface illumination information is provided by the segmentation of the monocular image into fine surface patches of nearly homogeneous intensity to remove mismatches generated during stereo matching. These patches are used to guide a statistical analysis of the disparity map based on the assumption that such patches correspond closely with physical surfaces in the scene. Such a technique is quite independent of whether the initial disparity map was generated by automated area-based or feature-based stereo matching. Stereo analysis results are presented on a complex urban scene containing various man-made and natural features. This scene contains a variety of problems including low building height with respect to the stereo baseline, buildings and roads in complex terrain, and highly textured buildings and terrain. The improvements are demonstrated due to monocular fusion with a set of different region-based image segmentations. The generality of this approach to stereo analysis and its utility in the development of general three dimensional scene interpretation systems are also discussed.

  9. Analysis of Scattering Components from Fully Polarimetric SAR Images for Improving Accuracies of Urban Density Estimation

    NASA Astrophysics Data System (ADS)

    Susaki, J.

    2016-06-01

    In this paper, we analyze probability density functions (PDFs) of scatterings derived from fully polarimetric synthetic aperture radar (SAR) images for improving the accuracies of estimated urban density. We have reported a method for estimating urban density that uses an index Tv+c obtained by normalizing the sum of volume and helix scatterings Pv+c. Validation results showed that estimated urban densities have a high correlation with building-to-land ratios (Kajimoto and Susaki, 2013b; Susaki et al., 2014). While the method is found to be effective for estimating urban density, it is not clear why Tv+c is more effective than indices derived from other scatterings, such as surface or double-bounce scatterings, observed in urban areas. In this research, we focus on PDFs of scatterings derived from fully polarimetric SAR images in terms of scattering normalization. First, we introduce a theoretical PDF that assumes that image pixels have scatterers showing random backscattering. We then generate PDFs of scatterings derived from observations of concrete blocks with different orientation angles, and from a satellite-based fully polarimetric SAR image. The analysis of the PDFs and the derived statistics reveals that the curves of the PDFs of Pv+c are the most similar to the normal distribution among all the scatterings derived from fully polarimetric SAR images. It was found that Tv+c works most effectively because of its similarity to the normal distribution.

  10. An improved panoramic digital image correlation method for vascular strain analysis and material characterization.

    PubMed

    Genovese, K; Lee, Y-U; Lee, A Y; Humphrey, J D

    2013-11-01

    The full potential of computational models of arterial wall mechanics has yet to be realized primarily because of a lack of data sufficient to quantify regional mechanical properties, especially in genetic, pharmacological, and surgical mouse models that can provide significant new information on the time course of adaptive or maladaptive changes as well as disease progression. The goal of this work is twofold: first, to present modifications to a recently developed panoramic-digital image correlation (p-DIC) system that significantly increase the rate of data acquisition, overall accuracy in specimen reconstruction, and thus full-field strain analysis, and the axial measurement domain for in vitro mechanical tests on excised mouse arteries and, second, to present a new method of data analysis that similarly increases the accuracy in image reconstruction while reducing the associated computational time. The utility of these advances is illustrated by presenting the first full-field strain measurements at multiple distending pressures and axial elongations for a suprarenal mouse aorta before and after exposure to elastase. Such data promise to enable improved inverse characterization of regional material properties using established computational methods. PMID:23290821

  11. The Comet Assay: Automated Imaging Methods for Improved Analysis and Reproducibility

    PubMed Central

    Braafladt, Signe; Reipa, Vytas; Atha, Donald H.

    2016-01-01

    Sources of variability in the comet assay include variations in the protocol used to process the cells, the microscope imaging system and the software used in the computerized analysis of the images. Here we focus on the effect of variations in the microscope imaging system and software analysis using fixed preparations of cells and a single cell processing protocol. To determine the effect of the microscope imaging and analysis on the measured percentage of damaged DNA (% DNA in tail), we used preparations of mammalian cells treated with etoposide or electrochemically induced DNA damage conditions and varied the settings of the automated microscope, camera, and commercial image analysis software. Manual image analysis revealed measurement variations in percent DNA in tail as high as 40% due to microscope focus, camera exposure time and the software image intensity threshold level. Automated image analysis reduced these variations as much as three-fold, but only within a narrow range of focus and exposure settings. The magnitude of variation, observed using both analysis methods, was highly dependent on the overall extent of DNA damage in the particular sample. Mitigating these sources of variability with optimal instrument settings facilitates an accurate evaluation of cell biological variability. PMID:27581626

  12. The Comet Assay: Automated Imaging Methods for Improved Analysis and Reproducibility.

    PubMed

    Braafladt, Signe; Reipa, Vytas; Atha, Donald H

    2016-01-01

    Sources of variability in the comet assay include variations in the protocol used to process the cells, the microscope imaging system and the software used in the computerized analysis of the images. Here we focus on the effect of variations in the microscope imaging system and software analysis using fixed preparations of cells and a single cell processing protocol. To determine the effect of the microscope imaging and analysis on the measured percentage of damaged DNA (% DNA in tail), we used preparations of mammalian cells treated with etoposide or electrochemically induced DNA damage conditions and varied the settings of the automated microscope, camera, and commercial image analysis software. Manual image analysis revealed measurement variations in percent DNA in tail as high as 40% due to microscope focus, camera exposure time and the software image intensity threshold level. Automated image analysis reduced these variations as much as three-fold, but only within a narrow range of focus and exposure settings. The magnitude of variation, observed using both analysis methods, was highly dependent on the overall extent of DNA damage in the particular sample. Mitigating these sources of variability with optimal instrument settings facilitates an accurate evaluation of cell biological variability. PMID:27581626

  13. Image quality analysis and improvement of Ladar reflective tomography for space object recognition

    NASA Astrophysics Data System (ADS)

    Wang, Jin-cheng; Zhou, Shi-wei; Shi, Liang; Hu, Yi-Hua; Wang, Yong

    2016-01-01

    Some problems in the application of Ladar reflective tomography for space object recognition are studied in this work. An analytic target model is adopted to investigate the image reconstruction properties with limited relative angle range, which are useful to verify the target shape from the incomplete image, analyze the shadowing effect of the target and design the satellite payloads against recognition via reflective tomography approach. We proposed an iterative maximum likelihood method basing on Bayesian theory, which can effectively compress the pulse width and greatly improve the image resolution of incoherent LRT system without loss of signal to noise ratio.

  14. Basics of image analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  15. Theoretical Analysis of the Sensitivity and Speed Improvement of ISIS over a Comparable Traditional Hyperspectral Imager

    SciTech Connect

    Brian R. Stallard; Stephen M. Gentry

    1998-09-01

    The analysis presented herein predicts that, under signal-independent noise limited conditions, an Information-efficient Spectral Imaging Sensor (ISIS) style hyperspectral imaging system design can obtain significant signal-to-noise ratio (SNR) and speed increase relative to a comparable traditional hyperspectral imaging (HSI) instrument. Factors of forty are reasonable for a single vector, and factors of eight are reasonable for a five-vector measurement. These advantages can be traded with other system parameters in an overall sensor system design to allow a variety of applications to be done that otherwise would be impossible within the constraints of the traditional HSI style design.

  16. Non-rigid registration and non-local principle component analysis to improve electron microscopy spectrum images

    NASA Astrophysics Data System (ADS)

    Yankovich, Andrew B.; Zhang, Chenyu; Oh, Albert; Slater, Thomas J. A.; Azough, Feridoon; Freer, Robert; Haigh, Sarah J.; Willett, Rebecca; Voyles, Paul M.

    2016-09-01

    Image registration and non-local Poisson principal component analysis (PCA) denoising improve the quality of characteristic x-ray (EDS) spectrum imaging of Ca-stabilized Nd2/3TiO3 acquired at atomic resolution in a scanning transmission electron microscope. Image registration based on the simultaneously acquired high angle annular dark field image significantly outperforms acquisition with a long pixel dwell time or drift correction using a reference image. Non-local Poisson PCA denoising reduces noise more strongly than conventional weighted PCA while preserving atomic structure more faithfully. The reliability of and optimal internal parameters for non-local Poisson PCA denoising of EDS spectrum images is assessed using tests on phantom data.

  17. The utility of texture analysis to improve per-pixel classification for CBERS02's CCD image

    NASA Astrophysics Data System (ADS)

    Peng, Guangxiong; He, Yuhua; Li, Jing; Chen, Yunhao; Hu, Deyong

    2006-10-01

    The maximum likelihood classification (MLC) is one of the most popular methods in remote sensing image classification. Because the maximum likelihood classification is based on spectrum of objects, it cannot correctly distinguish objects that have same spectrum and cannot reach the accuracy requirement. In this paper, we take an area of Langfang of Hebei province in China as an example and discuss the method of combining texture of panchromatic image with spectrum to improve the accuracy of CBERS02 CCD image information extraction. Firstly, analysis of the textures of the panchromatic image (CCD5) made by using texture analysis of Gray Level Coocurrence Matrices and statistic index. Then optimal texture window size of angular second moment, contrast, entropy and correlation is obtained according to variation coefficient of each texture measure for each thematic class. The chosen optimal window size is that from which the value of variation coefficient starts to stabilize while having the smallest value. The output images generated by texture analysis are used as additional bands together with other multi-spectral bands(CCD1-4) in classification. Objects that have same spectrums can be distinguished. Finally, the accuracy measurement is compared with the classification based on spectrum only .The result indicates that the objects with same spectrum are distinguished by using texture analysis in image classification, and the spectral /textural combination improves more than spectrum only in classification accuracy.

  18. Improving cervical region of interest by eliminating vaginal walls and cotton-swabs for automated image analysis

    NASA Astrophysics Data System (ADS)

    Venkataraman, Sankar; Li, Wenjing

    2008-03-01

    Image analysis for automated diagnosis of cervical cancer has attained high prominence in the last decade. Automated image analysis at all levels requires a basic segmentation of the region of interest (ROI) within a given image. The precision of the diagnosis is often reflected by the precision in detecting the initial region of interest, especially when some features outside the ROI mimic the ones within the same. Work described here discusses algorithms that are used to improve the cervical region of interest as a part of automated cervical image diagnosis. A vital visual aid in diagnosing cervical cancer is the aceto-whitening of the cervix after the application of acetic acid. Color and texture are used to segment acetowhite regions within the cervical ROI. Vaginal walls along with cottonswabs sometimes mimic these essential features leading to several false positives. Work presented here is focused towards detecting in-focus vaginal wall boundaries and then extrapolating them to exclude vaginal walls from the cervical ROI. In addition, discussed here is a marker-controlled watershed segmentation that is used to detect cottonswabs from the cervical ROI. A dataset comprising 50 high resolution images of the cervix acquired after 60 seconds of acetic acid application were used to test the algorithm. Out of the 50 images, 27 benefited from a new cervical ROI. Significant improvement in overall diagnosis was observed in these images as false positives caused by features outside the actual ROI mimicking acetowhite region were eliminated.

  19. Improved Dynamic Analysis method for quantitative PIXE and SXRF element imaging of complex materials

    NASA Astrophysics Data System (ADS)

    Ryan, C. G.; Laird, J. S.; Fisher, L. A.; Kirkham, R.; Moorhead, G. F.

    2015-11-01

    The Dynamic Analysis (DA) method in the GeoPIXE software provides a rapid tool to project quantitative element images from PIXE and SXRF imaging event data both for off-line analysis and in real-time embedded in a data acquisition system. Initially, it assumes uniform sample composition, background shape and constant model X-ray relative intensities. A number of image correction methods can be applied in GeoPIXE to correct images to account for chemical concentration gradients, differential absorption effects, and to correct images for pileup effects. A new method, applied in a second pass, uses an end-member phase decomposition obtained from the first pass, and DA matrices determined for each end-member, to re-process the event data with each pixel treated as an admixture of end-member terms. This paper describes the new method and demonstrates through examples and Monte-Carlo simulations how it better tracks spatially complex composition and background shape while still benefitting from the speed of DA.

  20. Improved triangular prism methods for fractal analysis of remotely sensed images

    NASA Astrophysics Data System (ADS)

    Zhou, Yu; Fung, Tung; Leung, Yee

    2016-05-01

    Feature extraction has been a major area of research in remote sensing, and fractal feature is a natural characterization of complex objects across scales. Extending on the modified triangular prism (MTP) method, we systematically discuss three factors closely related to the estimation of fractal dimensions of remotely sensed images. They are namely the (F1) number of steps, (F2) step size, and (F3) estimation accuracy of the facets' areas of the triangular prisms. Differing from the existing improved algorithms that separately consider these factors, we simultaneously take all factors to construct three new algorithms, namely the modification of the eight-pixel algorithm, the four corner and the moving-average MTP. Numerical experiments based on 4000 generated images show their superior performances over existing algorithms: our algorithms not only overcome the limitation of image size suffered by existing algorithms but also obtain similar average fractal dimension with smaller standard deviation, only 50% for images with high fractal dimensions. In the case of real-life application, our algorithms more likely obtain fractal dimensions within the theoretical range. Thus, the fractal nature uncovered by our algorithms is more reasonable in quantifying the complexity of remotely sensed images. Despite the similar performance of these three new algorithms, the moving-average MTP can mitigate the sensitivity of the MTP to noise and extreme values. Based on the numerical and real-life case study, we check the effect of the three factors, (F1)-(F3), and demonstrate that these three factors can be simultaneously considered for improving the performance of the MTP method.

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

    NASA Astrophysics Data System (ADS)

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

    2015-03-01

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

  2. Analysis of explosion in enclosure based on improved method of images

    NASA Astrophysics Data System (ADS)

    Wu, Z.; Guo, J.; Yao, X.; Chen, G.; Zhu, X.

    2016-05-01

    The aim of this paper is to present an improved method to calculate the pressure loading on walls during a confined explosion. When an explosion occurs inside of an enclosure, reflected shock waves produce multiple pressure peaks at a given wall location, especially at the corners. The effects of confined blast loading may bring about more serious damage to the structure due to multiple shock reflection. An approach, first proposed by Chan to describe the track of shock waves based on the mirror reflecting theory, using the method of images (MOI) is proposed to simplify internal explosion loading calculations. An improved method of images is proposed that takes into account wall openings and oblique reflections that cannot be considered with the standard MOI. The approach, validated using experimental data, provides a simplified and quick approach for loading calculation of a confined explosion. The results show that the peak overpressure tends to decline as the measurement point moves away from the center, and increases sharply as it approaches the enclosure corners. The specific impulse increases from the center to the corners. The improved method is capable of predicting pressure-time history and impulse with an accuracy comparable to that of three-dimensional AUTODYN code predictions.

  3. An Improved Method for Liver Diseases Detection by Ultrasound Image Analysis

    PubMed Central

    Owjimehr, Mehri; Danyali, Habibollah; Helfroush, Mohammad Sadegh

    2015-01-01

    Ultrasound imaging is a popular and noninvasive tool frequently used in the diagnoses of liver diseases. A system to characterize normal, fatty and heterogeneous liver, using textural analysis of liver Ultrasound images, is proposed in this paper. The proposed approach is able to select the optimum regions of interest of the liver images. These optimum regions of interests are analyzed by two level wavelet packet transform to extract some statistical features, namely, median, standard deviation, and interquartile range. Discrimination between heterogeneous, fatty and normal livers is performed in a hierarchical approach in the classification stage. This stage, first, classifies focal and diffused livers and then distinguishes between fatty and normal ones. Support vector machine and k-nearest neighbor classifiers have been used to classify the images into three groups, and their performance is compared. The Support vector machine classifier outperformed the compared classifier, attaining an overall accuracy of 97.9%, with a sensitivity of 100%, 100% and 95.1% for the heterogeneous, fatty and normal class, respectively. The Acc obtained by the proposed computer-aided diagnostic system is quite promising and suggests that the proposed system can be used in a clinical environment to support radiologists and experts in liver diseases interpretation. PMID:25709938

  4. Improving Three-Dimensional (3D) Range Gated Reconstruction Through Time-of-Flight (TOF) Imaging Analysis

    NASA Astrophysics Data System (ADS)

    Chua, S. Y.; Wang, X.; Guo, N.; Tan, C. S.; Chai, T. Y.; Seet, G. L.

    2016-04-01

    This paper performs an experimental investigation on the TOF imaging profile which strongly influences the quality of reconstruction to accomplish accurate range sensing. From our analysis, the reflected intensity profile recorded appears to deviate from Gaussian model which is commonly assumed and can be perceived as a mixture of noises and actual reflected signal. Noise-weighted Average range calculation is therefore proposed to alleviate noise influence based on the signal detection threshold and system noises. From our experimental result, this alternative range solution demonstrates better accuracy as compared to the conventional weighted average method and proven as a para-axial correction to improve range reconstruction in 3D gated imaging system.

  5. Image analysis techniques: Used to quantify and improve the precision of coatings testing results

    SciTech Connect

    Duncan, D.J.; Whetten, A.R.

    1993-12-31

    Coating evaluations often specify tests to measure performance characteristics rather than coating physical properties. These evaluation results are often very subjective. A new tool, Digital Video Image Analysis (DVIA), is successfully being used for two automotive evaluations; cyclic (scab) corrosion, and gravelometer (chip) test. An experimental design was done to evaluate variability and interactions among the instrumental factors. This analysis method has proved to be an order of magnitude more sensitive and reproducible than the current evaluations. Coating evaluations can be described and measured that had no way to be expressed previously. For example, DVIA chip evaluations can differentiate how much damage was done to the topcoat, primer even to the metal. DVIA with or without magnification, has the capability to become the quantitative measuring tool for several other coating evaluations, such as T-bends, wedge bends, acid etch analysis, coating defects, observing cure, defect formation or elimination over time, etc.

  6. Improved Hierarchical Optimization-Based Classification of Hyperspectral Images Using Shape Analysis

    NASA Technical Reports Server (NTRS)

    Tarabalka, Yuliya; Tilton, James C.

    2012-01-01

    A new spectral-spatial method for classification of hyperspectral images is proposed. The HSegClas method is based on the integration of probabilistic classification and shape analysis within the hierarchical step-wise optimization algorithm. First, probabilistic support vector machines classification is applied. Then, at each iteration two neighboring regions with the smallest Dissimilarity Criterion (DC) are merged, and classification probabilities are recomputed. The important contribution of this work consists in estimating a DC between regions as a function of statistical, classification and geometrical (area and rectangularity) features. Experimental results are presented on a 102-band ROSIS image of the Center of Pavia, Italy. The developed approach yields more accurate classification results when compared to previously proposed methods.

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

    PubMed Central

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

    2011-01-01

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

  8. Jeffries Matusita based mixed-measure for improved spectral matching in hyperspectral image analysis

    NASA Astrophysics Data System (ADS)

    Padma, S.; Sanjeevi, S.

    2014-10-01

    This paper proposes a novel hyperspectral matching technique by integrating the Jeffries-Matusita measure (JM) and the Spectral Angle Mapper (SAM) algorithm. The deterministic Spectral Angle Mapper and stochastic Jeffries-Matusita measure are orthogonally projected using the sine and tangent functions to increase their spectral ability. The developed JM-SAM algorithm is implemented in effectively discriminating the landcover classes and cover types in the hyperspectral images acquired by PROBA/CHRIS and EO-1 Hyperion sensors. The reference spectra for different land-cover classes were derived from each of these images. The performance of the proposed measure is compared with the performance of the individual SAM and JM approaches. From the values of the relative spectral discriminatory probability (RSDPB) and relative discriminatory entropy value (RSDE), it is inferred that the hybrid JM-SAM approach results in a high spectral discriminability than the SAM and JM measures. Besides, the use of the improved JM-SAM algorithm for supervised classification of the images results in 92.9% and 91.47% accuracy compared to 73.13%, 79.41%, and 85.69% of minimum-distance, SAM and JM measures. It is also inferred that the increased spectral discriminability of JM-SAM measure is contributed by the JM distance. Further, it is seen that the proposed JM-SAM measure is compatible with varying spectral resolutions of PROBA/CHRIS (62 bands) and Hyperion (242 bands).

  9. Improved texture analysis for automatic detection of tuberculosis (TB) on chest radiographs with bone suppression images

    NASA Astrophysics Data System (ADS)

    Maduskar, Pragnya; Hogeweg, Laurens; Philipsen, Rick; Schalekamp, Steven; van Ginneken, Bram

    2013-03-01

    Computer aided detection (CAD) of tuberculosis (TB) on chest radiographs (CXR) is challenging due to over-lapping structures. Suppression of normal structures can reduce overprojection effects and can enhance the appearance of diffuse parenchymal abnormalities. In this work, we compare two CAD systems to detect textural abnormalities in chest radiographs of TB suspects. One CAD system was trained and tested on the original CXR and the other CAD system was trained and tested on bone suppression images (BSI). BSI were created using a commercially available software (ClearRead 2.4, Riverain Medical). The CAD system is trained with 431 normal and 434 abnormal images with manually outlined abnormal regions. Subtlety rating (1-3) is assigned to each abnormal region, where 3 refers to obvious and 1 refers to subtle abnormalities. Performance is evaluated on normal and abnormal regions from an independent dataset of 900 images. These contain in total 454 normal and 1127 abnormal regions, which are divided into 3 subtlety categories containing 280, 527 and 320 abnormal regions, respectively. For normal regions, original/BSI CAD has an average abnormality score of 0.094+/-0.027/0.085+/-0.032 (p - 5.6×10-19). For abnormal regions, subtlety 1, 2, 3 categories have average abnormality scores for original/BSI of 0.155+/-0.073/0.156+/-0.089 (p = 0.73), 0.194+/-0.086/0.207+/-0.101 (p = 5.7×10-7), 0.225+/-0.119/0.247+/-0.117 (p = 4.4×10-7), respectively. Thus for normal regions, CAD scores slightly decrease when using BSI instead of the original images, and for abnormal regions, the scores increase slightly. We therefore conclude that the use of bone suppression results in slightly but significantly improved automated detection of textural abnormalities in chest radiographs.

  10. An Improved Method for Measuring Quantitative Resistance to the Wheat Pathogen Zymoseptoria tritici Using High-Throughput Automated Image Analysis.

    PubMed

    Stewart, Ethan L; Hagerty, Christina H; Mikaberidze, Alexey; Mundt, Christopher C; Zhong, Ziming; McDonald, Bruce A

    2016-07-01

    Zymoseptoria tritici causes Septoria tritici blotch (STB) on wheat. An improved method of quantifying STB symptoms was developed based on automated analysis of diseased leaf images made using a flatbed scanner. Naturally infected leaves (n = 949) sampled from fungicide-treated field plots comprising 39 wheat cultivars grown in Switzerland and 9 recombinant inbred lines (RIL) grown in Oregon were included in these analyses. Measures of quantitative resistance were percent leaf area covered by lesions, pycnidia size and gray value, and pycnidia density per leaf and lesion. These measures were obtained automatically with a batch-processing macro utilizing the image-processing software ImageJ. All phenotypes in both locations showed a continuous distribution, as expected for a quantitative trait. The trait distributions at both sites were largely overlapping even though the field and host environments were quite different. Cultivars and RILs could be assigned to two or more statistically different groups for each measured phenotype. Traditional visual assessments of field resistance were highly correlated with quantitative resistance measures based on image analysis for the Oregon RILs. These results show that automated image analysis provides a promising tool for assessing quantitative resistance to Z. tritici under field conditions. PMID:27050574

  11. Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects.

    PubMed

    Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

    2016-03-21

    Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI. PMID:26948513

  12. Improved spatial regression analysis of diffusion tensor imaging for lesion detection during longitudinal progression of multiple sclerosis in individual subjects

    NASA Astrophysics Data System (ADS)

    Liu, Bilan; Qiu, Xing; Zhu, Tong; Tian, Wei; Hu, Rui; Ekholm, Sven; Schifitto, Giovanni; Zhong, Jianhui

    2016-03-01

    Subject-specific longitudinal DTI study is vital for investigation of pathological changes of lesions and disease evolution. Spatial Regression Analysis of Diffusion tensor imaging (SPREAD) is a non-parametric permutation-based statistical framework that combines spatial regression and resampling techniques to achieve effective detection of localized longitudinal diffusion changes within the whole brain at individual level without a priori hypotheses. However, boundary blurring and dislocation limit its sensitivity, especially towards detecting lesions of irregular shapes. In the present study, we propose an improved SPREAD (dubbed improved SPREAD, or iSPREAD) method by incorporating a three-dimensional (3D) nonlinear anisotropic diffusion filtering method, which provides edge-preserving image smoothing through a nonlinear scale space approach. The statistical inference based on iSPREAD was evaluated and compared with the original SPREAD method using both simulated and in vivo human brain data. Results demonstrated that the sensitivity and accuracy of the SPREAD method has been improved substantially by adapting nonlinear anisotropic filtering. iSPREAD identifies subject-specific longitudinal changes in the brain with improved sensitivity, accuracy, and enhanced statistical power, especially when the spatial correlation is heterogeneous among neighboring image pixels in DTI.

  13. Improvements and artifact analysis in conductivity images using multiple internal electrodes.

    PubMed

    Farooq, Adnan; Tehrani, Joubin Nasehi; McEwan, Alistair Lee; Woo, Eung Je; Oh, Tong In

    2014-06-01

    Electrical impedance tomography is an attractive functional imaging method. It is currently limited in resolution and sensitivity due to the complexity of the inverse problem and the safety limits of introducing current. Recently, internal electrodes have been proposed for some clinical situations such as intensive care or RF ablation. This paper addresses the research question related to the benefit of one or more internal electrodes usage since these are invasive. Internal electrodes would be able to reduce the effect of insulating boundaries such as fat and bone and provide improved internal sensitivity. We found there was a measurable benefit with increased numbers of internal electrodes in saline tanks of a cylindrical and complex shape with up to two insulating boundary gel layers modeling fat and muscle. The internal electrodes provide increased sensitivity to internal changes, thereby increasing the amplitude response and improving resolution. However, they also present an additional challenge of increasing sensitivity to position and modeling errors. In comparison with previous work that used point sources for the internal electrodes, we found that it is important to use a detailed mesh of the internal electrodes with these voxels assigned to the conductivity of the internal electrode and its associated holder. A study of different internal electrode materials found that it is optimal to use a conductivity similar to the background. In the tank with a complex shape, the additional internal electrodes provided more robustness in a ventilation model of the lungs via air filled balloons. PMID:24845453

  14. An improved parameter estimation scheme for image modification detection based on DCT coefficient analysis.

    PubMed

    Yu, Liyang; Han, Qi; Niu, Xiamu; Yiu, S M; Fang, Junbin; Zhang, Ye

    2016-02-01

    Most of the existing image modification detection methods which are based on DCT coefficient analysis model the distribution of DCT coefficients as a mixture of a modified and an unchanged component. To separate the two components, two parameters, which are the primary quantization step, Q1, and the portion of the modified region, α, have to be estimated, and more accurate estimations of α and Q1 lead to better detection and localization results. Existing methods estimate α and Q1 in a completely blind manner, without considering the characteristics of the mixture model and the constraints to which α should conform. In this paper, we propose a more effective scheme for estimating α and Q1, based on the observations that, the curves on the surface of the likelihood function corresponding to the mixture model is largely smooth, and α can take values only in a discrete set. We conduct extensive experiments to evaluate the proposed method, and the experimental results confirm the efficacy of our method. PMID:26804669

  15. Robust biological parametric mapping: an improved technique for multimodal brain image analysis

    NASA Astrophysics Data System (ADS)

    Yang, Xue; Beason-Held, Lori; Resnick, Susan M.; Landman, Bennett A.

    2011-03-01

    Mapping the quantitative relationship between structure and function in the human brain is an important and challenging problem. Numerous volumetric, surface, region of interest and voxelwise image processing techniques have been developed to statistically assess potential correlations between imaging and non-imaging metrics. Recently, biological parametric mapping has extended the widely popular statistical parametric approach to enable application of the general linear model to multiple image modalities (both for regressors and regressands) along with scalar valued observations. This approach offers great promise for direct, voxelwise assessment of structural and functional relationships with multiple imaging modalities. However, as presented, the biological parametric mapping approach is not robust to outliers and may lead to invalid inferences (e.g., artifactual low p-values) due to slight mis-registration or variation in anatomy between subjects. To enable widespread application of this approach, we introduce robust regression and robust inference in the neuroimaging context of application of the general linear model. Through simulation and empirical studies, we demonstrate that our robust approach reduces sensitivity to outliers without substantial degradation in power. The robust approach and associated software package provides a reliable way to quantitatively assess voxelwise correlations between structural and functional neuroimaging modalities.

  16. 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

  17. Improvement of CAT scanned images

    NASA Technical Reports Server (NTRS)

    Roberts, E., Jr.

    1980-01-01

    Digital enhancement procedure improves definition of images. Tomogram is generated from large number of X-ray beams. Beams are collimated and small in diameter. Scanning device passes beams sequentially through human subject at many different angles. Battery of transducers opposite subject senses attenuated signals. Signals are transmitted to computer where they are used in construction of image on transverse plane through body.

  18. Improved defect analysis of Gallium Arsenide solar cells using image enhancement

    NASA Technical Reports Server (NTRS)

    Kilmer, Louis C.; Honsberg, Christiana; Barnett, Allen M.; Phillips, James E.

    1989-01-01

    A new technique has been developed to capture, digitize, and enhance the image of light emission from a forward biased direct bandgap solar cell. Since the forward biased light emission from a direct bandgap solar cell has been shown to display both qualitative and quantitative information about the solar cell's performance and its defects, signal processing techniques can be applied to the light emission images to identify and analyze shunt diodes. Shunt diodes are of particular importance because they have been found to be the type of defect which is likely to cause failure in a GaAs solar cell. The presence of a shunt diode can be detected from the light emission by using a photodetector to measure the quantity of light emitted at various current densities. However, to analyze how the shunt diodes affect the quality of the solar cell the pattern of the light emission must be studied. With the use of image enhancement routines, the light emission can be studied at low light emission levels where shunt diode effects are dominant.

  19. Improved structures of maximally decimated directional filter banks for spatial image analysis.

    PubMed

    Park, Sang-Il; Smith, Mark J T; Mersereau, Russell M

    2004-11-01

    This paper introduces an improved structure for directional filter banks (DFBs) that preserves the visual information in the subband domain. The new structure achieves this outcome while preserving both the efficient polyphase implementation and the exact reconstruction property. The paper outlines a step-by-step framework in which to examine the DFB, and within this framework discusses how, through the insertion of post-sampling matrices, visual distortions can be removed. In addition to the efficient tree structure, attention is given to the form and design of efficient linear phase filters. Most notably, linear phase IIR prototype filters are presented, together with the design details. These filters can enable the DFB to have more than a three-fold improvement in complexity reduction over quadrature mirror filters (QMFs). PMID:15540452

  20. Applying Chemical Imaging Analysis to Improve Our Understanding of Cold Cloud Formation

    NASA Astrophysics Data System (ADS)

    Laskin, A.; Knopf, D. A.; Wang, B.; Alpert, P. A.; Roedel, T.; Gilles, M. K.; Moffet, R.; Tivanski, A.

    2012-12-01

    The impact that atmospheric ice nucleation has on the global radiation budget is one of the least understood problems in atmospheric sciences. This is in part due to the incomplete understanding of various ice nucleation pathways that lead to ice crystal formation from pre-existing aerosol particles. Studies investigating the ice nucleation propensity of laboratory generated particles indicate that individual particle types are highly selective in their ice nucleating efficiency. This description of heterogeneous ice nucleation would present a challenge when applying to the atmosphere which contains a complex mixture of particles. Here, we employ a combination of micro-spectroscopic and optical single particle analytical methods to relate particle physical and chemical properties with observed water uptake and ice nucleation. Field-collected particles from urban environments impacted by anthropogenic and marine emissions and aging processes are investigated. Single particle characterization is provided by computer controlled scanning electron microscopy with energy dispersive analysis of X-rays (CCSEM/EDX) and scanning transmission X-ray microscopy with near edge X-ray absorption fine structure spectroscopy (STXM/NEXAFS). A particle-on-substrate approach coupled to a vapor controlled cooling-stage and a microscope system is applied to determine the onsets of water uptake and ice nucleation including immersion freezing and deposition ice nucleation as a function of temperature (T) as low as 200 K and relative humidity (RH) up to water saturation. We observe for urban aerosol particles that for T > 230 K the oxidation level affects initial water uptake and that subsequent immersion freezing depends on particle mixing state, e.g. by the presence of insoluble particles. For T < 230 K the particles initiate deposition ice nucleation well below the homogeneous freezing limit. Particles collected throughout one day for similar meteorological conditions show very similar

  1. Improving image segmentation performance and quantitative analysis via a computer-aided grading methodology for optical coherence tomography retinal image analysis

    NASA Astrophysics Data System (ADS)

    Cabrera Debuc, Delia; Salinas, Harry M.; Ranganathan, Sudarshan; Tátrai, Erika; Gao, Wei; Shen, Meixiao; Wang, Jianhua; Somfai, Gábor M.; Puliafito, Carmen A.

    2010-07-01

    We demonstrate quantitative analysis and error correction of optical coherence tomography (OCT) retinal images by using a custom-built, computer-aided grading methodology. A total of 60 Stratus OCT (Carl Zeiss Meditec, Dublin, California) B-scans collected from ten normal healthy eyes are analyzed by two independent graders. The average retinal thickness per macular region is compared with the automated Stratus OCT results. Intergrader and intragrader reproducibility is calculated by Bland-Altman plots of the mean difference between both gradings and by Pearson correlation coefficients. In addition, the correlation between Stratus OCT and our methodology-derived thickness is also presented. The mean thickness difference between Stratus OCT and our methodology is 6.53 μm and 26.71 μm when using the inner segment/outer segment (IS/OS) junction and outer segment/retinal pigment epithelium (OS/RPE) junction as the outer retinal border, respectively. Overall, the median of the thickness differences as a percentage of the mean thickness is less than 1% and 2% for the intragrader and intergrader reproducibility test, respectively. The measurement accuracy range of the OCT retinal image analysis (OCTRIMA) algorithm is between 0.27 and 1.47 μm and 0.6 and 1.76 μm for the intragrader and intergrader reproducibility tests, respectively. Pearson correlation coefficients demonstrate R2>0.98 for all Early Treatment Diabetic Retinopathy Study (ETDRS) regions. Our methodology facilitates a more robust and localized quantification of the retinal structure in normal healthy controls and patients with clinically significant intraretinal features.

  2. Enhancement of galaxy images for improved classification

    NASA Astrophysics Data System (ADS)

    Jenkinson, John; Grigoryan, Artyom M.; Agaian, Sos S.

    2015-03-01

    In this paper, the classification accuracy of galaxy images is demonstrated to be improved by enhancing the galaxy images. Galaxy images often contain faint regions that are of similar intensity to stars and the image background, resulting in data loss during background subtraction and galaxy segmentation. Enhancement darkens these faint regions, enabling them to be distinguished from other objects in the image and the image background, relative to their original intensities. The heap transform is employed for the purpose of enhancement. Segmentation then produces a galaxy image which closely resembles the structure of the original galaxy image, and one that is suitable for further processing and classification. 6 Morphological feature descriptors are applied to the segmented images after a preprocessing stage and used to extract the galaxy image structure for use in training the classifier. The support vector machine learning algorithm performs training and validation of the original and enhanced data, and a comparison between the classification accuracy of each data set is included. Principal component analysis is used to compress the data sets for the purpose of classification visualization and a comparison between the reduced and original feature spaces. Future directions for this research include galaxy image enhancement by various methods, and classification performed with the use of a sparse dictionary. Both future directions are introduced.

  3. Security Analysis of Image Encryption Based on Gyrator Transform by Searching the Rotation Angle with Improved PSO Algorithm.

    PubMed

    Sang, Jun; Zhao, Jun; Xiang, Zhili; Cai, Bin; Xiang, Hong

    2015-01-01

    Gyrator transform has been widely used for image encryption recently. For gyrator transform-based image encryption, the rotation angle used in the gyrator transform is one of the secret keys. In this paper, by analyzing the properties of the gyrator transform, an improved particle swarm optimization (PSO) algorithm was proposed to search the rotation angle in a single gyrator transform. Since the gyrator transform is continuous, it is time-consuming to exhaustedly search the rotation angle, even considering the data precision in a computer. Therefore, a computational intelligence-based search may be an alternative choice. Considering the properties of severe local convergence and obvious global fluctuations of the gyrator transform, an improved PSO algorithm was proposed to be suitable for such situations. The experimental results demonstrated that the proposed improved PSO algorithm can significantly improve the efficiency of searching the rotation angle in a single gyrator transform. Since gyrator transform is the foundation of image encryption in gyrator transform domains, the research on the method of searching the rotation angle in a single gyrator transform is useful for further study on the security of such image encryption algorithms. PMID:26251910

  4. Security Analysis of Image Encryption Based on Gyrator Transform by Searching the Rotation Angle with Improved PSO Algorithm

    PubMed Central

    Sang, Jun; Zhao, Jun; Xiang, Zhili; Cai, Bin; Xiang, Hong

    2015-01-01

    Gyrator transform has been widely used for image encryption recently. For gyrator transform-based image encryption, the rotation angle used in the gyrator transform is one of the secret keys. In this paper, by analyzing the properties of the gyrator transform, an improved particle swarm optimization (PSO) algorithm was proposed to search the rotation angle in a single gyrator transform. Since the gyrator transform is continuous, it is time-consuming to exhaustedly search the rotation angle, even considering the data precision in a computer. Therefore, a computational intelligence-based search may be an alternative choice. Considering the properties of severe local convergence and obvious global fluctuations of the gyrator transform, an improved PSO algorithm was proposed to be suitable for such situations. The experimental results demonstrated that the proposed improved PSO algorithm can significantly improve the efficiency of searching the rotation angle in a single gyrator transform. Since gyrator transform is the foundation of image encryption in gyrator transform domains, the research on the method of searching the rotation angle in a single gyrator transform is useful for further study on the security of such image encryption algorithms. PMID:26251910

  5. An improved image analysis method for cell counting lends credibility to the prognostic significance of T cells in colorectal cancer.

    PubMed

    Väyrynen, Juha P; Vornanen, Juha O; Sajanti, Sara; Böhm, Jan P; Tuomisto, Anne; Mäkinen, Markus J

    2012-05-01

    Numerous immunohistochemically detectable proteins, such as immune cell surface (CD) proteins, vascular endothelial growth factor, and matrix metalloproteinases, have been proposed as potential prognostic markers in colorectal cancer (CRC) and other malignancies. However, the lack of reproducibility has been a major problem in validating the clinical use of such markers, and this has been attributed to insufficiently robust methods used in immunohistochemical staining or its assessment. In this study, we assessed how computer-assisted image analysis might contribute to the reliable assessment of positive area percentage and immune cell density in CRC specimens, and subsequently, we applied the computer-assisted cell counting method in assessing the prognostic value of T cell infiltration in CRC. The computer-assisted analysis methods were based on separating hematoxylin and diaminobenzidine color layers and then applying a brightness threshold using open source image analysis software ImageJ. We found that computer-based analysis results in a more reproducible assessment of the immune positive area percentage than visual semiquantitative estimation. Computer-assisted immune cell counting was rapid to perform and accurate (Pearson r > 0.96 with exact manual cell counts). Moreover, the computer-assisted determination of peritumoral and stromal T cell density had independent prognostic value. Our results suggest that computer-assisted image analysis, utilizing freely available image analysis software, provides a valuable alternative to semiquantitative assessment of immunohistochemical results in cancer research, as well as in clinical practice. The advantages of using computer-assisted analysis include objectivity, accuracy, reproducibility, and time efficiency. This study supports the prognostic value of assessing T cell infiltration in CRC. PMID:22527018

  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. Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses

    NASA Astrophysics Data System (ADS)

    Agüera, Francisco; Aguilar, Fernando J.; Aguilar, Manuel A.

    The area occupied by plastic-covered greenhouses has undergone rapid growth in recent years, currently exceeding 500,000 ha worldwide. Due to the vast amount of input (water, fertilisers, fuel, etc.) required, and output of different agricultural wastes (vegetable, plastic, chemical, etc.), the environmental impact of this type of production system can be serious if not accompanied by sound and sustainable territorial planning. For this, the new generation of satellites which provide very high resolution imagery, such as QuickBird and IKONOS can be useful. In this study, one QuickBird and one IKONOS satellite image have been used to cover the same area under similar circumstances. The aim of this work was an exhaustive comparison of QuickBird vs. IKONOS images in land-cover detection. In terms of plastic greenhouse mapping, comparative tests were designed and implemented, each with separate objectives. Firstly, the Maximum Likelihood Classification (MLC) was applied using five different approaches combining R, G, B, NIR, and panchromatic bands. The combinations of the bands used, significantly influenced some of the indexes used to classify quality in this work. Furthermore, the quality classification of the QuickBird image was higher in all cases than that of the IKONOS image. Secondly, texture features derived from the panchromatic images at different window sizes and with different grey levels were added as a fifth band to the R, G, B, NIR images to carry out the MLC. The inclusion of texture information in the classification did not improve the classification quality. For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters. The optimum window size in these texture parameters was 3×3 for IK images, while for QB images it depended on the quality index studied, but the optimum window size was around 15×15. With regard to the grey level, the optimum was 128. Thus, the

  8. Potential use of combining the diffusion equation with the free Shrödinger equation to improve the Optical Coherence Tomography image analysis

    NASA Astrophysics Data System (ADS)

    Cabrera Fernandez, Delia; Salinas, Harry M.; Somfai, Gabor; Puliafito, Carmen A.

    2006-03-01

    Optical coherence tomography (OCT) is a rapidly emerging medical imaging technology. In ophthalmology, OCT is a powerful tool because it enables visualization of the cross sectional structure of the retina and anterior eye with higher resolutions than any other non-invasive imaging modality. Furthermore, OCT image information can be quantitatively analyzed, enabling objective assessment of features such as macular edema and diabetes retinopathy. We present specific improvements in the quantitative analysis of the OCT system, by combining the diffusion equation with the free Shrödinger equation. In such formulation, important features of the image can be extracted by extending the analysis from the real axis to the complex domain. Experimental results indicate that our proposed novel approach has good performance in speckle noise removal, enhancement and segmentation of the various cellular layers of the retina using the OCT system.

  9. 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.

  10. CovAmCoh-analysis: a method to improve the interpretation of high resolution repeat pass SAR images of urban areas

    NASA Astrophysics Data System (ADS)

    Schulz, Karsten; Boldt, Markus; Thiele, Antje

    2009-09-01

    The main advantages of SAR (Synthetic Aperture Radar) are the availability of data under nearly all weather conditions and its independence from natural illumination. Data can be gathered on demand and exploited to extract the needed information. However, due to the side looking imaging geometry, SAR images are difficult to interpret and there is a need for support of human interpreters by image analysis algorithms. In this paper a method is described to improve and to simplify the interpretation of high resolution repeat pass SAR images. Modern spaceborne SAR sensors provide imagery with high spatial resolution and the same imaging geometry in an equidistant time interval. These repeat pass orbits are e. g. used for interferometric evaluation. The information contained in a repeat pass image pair is visualized by the introduced method so that some basic features can be directly extracted from a color representation of three deduced features. The CoV (Coefficient of Variation), the amplitude and the coherence are calculated and jointly evaluated. The combined evaluation of these features can be used to identify regions dominated by volume scatterers (e. g. leafed vegetation), rough surfaces (e. g. grass, gravel) and smooth surfaces (e. g. streets, parking lots). Additionally the coherence between the two images includes information about changes between the acquisitions. The potential of the CovAmCoh- Analysis is demonstrated and discussed by the evaluation of a TerraSAR-X image pair of the Frankfurt airport. The method shows a simple way to improve the intuitive interpretation by the human interpreter and it is used to improve the classification of some basic urban features.

  11. Electronic image analysis

    NASA Astrophysics Data System (ADS)

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

    1980-12-01

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

  12. Principal component analysis with pre-normalization improves the signal-to-noise ratio and image quality in positron emission tomography studies of amyloid deposits in Alzheimer's disease

    NASA Astrophysics Data System (ADS)

    Razifar, Pasha; Engler, Henry; Blomquist, Gunnar; Ringheim, Anna; Estrada, Sergio; Långström, Bengt; Bergström, Mats

    2009-06-01

    This study introduces a new approach for the application of principal component analysis (PCA) with pre-normalization on dynamic positron emission tomography (PET) images. These images are generated using the amyloid imaging agent N-methyl [11C]2-(4'-methylaminophenyl)-6-hydroxy-benzothiazole ([11C]PIB) in patients with Alzheimer's disease (AD) and healthy volunteers (HVs). The aim was to introduce a method which, by using the whole dataset and without assuming a specific kinetic model, could generate images with improved signal-to-noise and detect, extract and illustrate changes in kinetic behavior between different regions in the brain. Eight AD patients and eight HVs from a previously published study with [11C]PIB were used. The approach includes enhancement of brain regions where the kinetics of the radiotracer are different from what is seen in the reference region, pre-normalization for differences in noise levels and removal of negative values. This is followed by slice-wise application of PCA (SW-PCA) on the dynamic PET images. Results obtained using the new approach were compared with results obtained using reference Patlak and summed images. The new approach generated images with good quality in which cortical brain regions in AD patients showed high uptake, compared to cerebellum and white matter. Cortical structures in HVs showed low uptake as expected and in good agreement with data generated using kinetic modeling. The introduced approach generated images with enhanced contrast and improved signal-to-noise ratio (SNR) and discrimination power (DP) compared to summed images and parametric images. This method is expected to be an important clinical tool in the diagnosis and differential diagnosis of dementia.

  13. Improvements to a Grating-Based Spectral Imaging Microscope and Its Application to Reflectance Analysis of Blue Pen Inks.

    PubMed

    McMillan, Leilani C; Miller, Kathleen P; Webb, Michael R

    2015-08-01

    A modified design of a chromatically resolved optical microscope (CROMoscope), a grating-based spectral imaging microscope, is described. By altering the geometry and adding a beam splitter, a twisting aberration that was present in the first version of the CROMoscope has been removed. Wavelength adjustment has been automated to decrease analysis time. Performance of the new design in transmission-absorption spectroscopy has been evaluated and found to be generally similar to the performance of the previous design. Spectral bandpass was found to be dependent on the sizes of apertures, and the smallest measured spectral bandpass was 1.8 nm with 1.0 mm diameter apertures. Wavelength was found to be very linear with the sine of the grating angle (R(2) = 0.9999995), and wavelength repeatability was found to be much better than the spectral bandpass. Reflectance spectral imaging with a CROMoscope is reported for the first time, and this reflectance spectral imaging was applied to blue ink samples on white paper. As a proof of concept, linear discriminant analysis was used to classify the inks by brand. In a leave-one-out cross-validation, 97.6% of samples were correctly classified. PMID:26162719

  14. 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

  15. Suggestions for automatic quantitation of endoscopic image analysis to improve detection of small intestinal pathology in celiac disease patients.

    PubMed

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

    2015-10-01

    Although many groups have attempted to develop an automated computerized method to detect pathology of the small intestinal mucosa caused by celiac disease, the efforts have thus far failed. This is due in part to the occult presence of the disease. When pathological evidence of celiac disease exists in the small bowel it is visually often patchy and subtle. Due to presence of extraneous substances such as air bubbles and opaque fluids, the use of computerized automation methods have only been partially successful in detecting the hallmarks of the disease in the small intestine-villous atrophy, fissuring, and a mottled appearance. By using a variety of computerized techniques and assigning a weight or vote to each technique, it is possible to improve the detection of abnormal regions which are indicative of celiac disease, and of treatment progress in diagnosed patients. Herein a paradigm is suggested for improving the efficacy of automated methods for measuring celiac disease manifestation in the small intestinal mucosa. The suggestions are applicable to both standard and videocapsule endoscopic imaging, since both methods could potentially benefit from computerized quantitation to improve celiac disease diagnosis. PMID:25976612

  16. Improved scanning laser fundus imaging using polarimetry

    NASA Astrophysics Data System (ADS)

    Bueno, Juan M.; Hunter, Jennifer J.; Cookson, Christopher J.; Kisilak, Marsha L.; Campbell, Melanie C. W.

    2007-05-01

    We present a polarimetric technique to improve fundus images that notably simplifies and extends a previous procedure [Opt. Lett.27, 830 (2002)]. A generator of varying polarization states was incorporated into the illumination path of a confocal scanning laser ophthalmoscope. A series of four images, corresponding to independent incoming polarization states, were recorded. From these images, the spatially resolved elements of the top row of the Mueller matrix were computed. From these elements, images with the highest and lowest quality (according to different image quality metrics) were constructed, some of which provided improved visualization of fundus structures of clinical importance (vessels and optic nerve head). The metric values were better for these constructed images than for the initially recorded images and better than averaged images. Entropy is the metric that is most sensitive to differences in the image quality. Improved visualization of features could aid in the detection, localization, and tracking of ocular disease and may be applicable in other biomedical imaging.

  17. Improving automatic analysis of the electrocardiogram acquired during magnetic resonance imaging using magnetic field gradient artefact suppression.

    PubMed

    Abächerli, Roger; Hornaff, Sven; Leber, Remo; Schmid, Hans-Jakob; Felblinger, Jacques

    2006-10-01

    The electrocardiogram (ECG) used for patient monitoring during magnetic resonance imaging (MRI) unfortunately suffers from severe artefacts. These artefacts are due to the special environment of the MRI. Modeling helped in finding solutions for the suppression of these artefacts superimposed on the ECG signal. After we validated the linear and time invariant model for the magnetic field gradient artefact generation, we applied offline and online filters for their suppression. Wiener filtering (offline) helped in generating reference annotations of the ECG beats. In online filtering, the least-mean-square filter suppressed the magnetic field gradient artefacts before the acquired ECG signal was input to the arrhythmia algorithm. Comparing the results of two runs (one run using online filtering and one run without) to our reference annotations, we found an eminent improvement in the arrhythmia module's performance, enabling reliable patient monitoring and MRI synchronization based on the ECG signal. PMID:17015063

  18. Interferogram conditioning for improved Fourier analysis and application to X-ray phase imaging by grating interferometry.

    PubMed

    Montaux-Lambert, Antoine; Mercère, Pascal; Primot, Jérôme

    2015-11-01

    An interferogram conditioning procedure, for subsequent phase retrieval by Fourier demodulation, is presented here as a fast iterative approach aiming at fulfilling the classical boundary conditions imposed by Fourier transform techniques. Interference fringe patterns with typical edge discontinuities were simulated in order to reveal the edge artifacts that classically appear in traditional Fourier analysis, and were consecutively used to demonstrate the correction efficiency of the proposed conditioning technique. Optimization of the algorithm parameters is also presented and discussed. Finally, the procedure was applied to grating-based interferometric measurements performed in the hard X-ray regime. The proposed algorithm enables nearly edge-artifact-free retrieval of the phase derivatives. A similar enhancement of the retrieved absorption and fringe visibility images is also achieved. PMID:26561119

  19. Multiresponse imaging system design for improved resolution

    NASA Technical Reports Server (NTRS)

    Alter-Gartenberg, Rachel; Fales, Carl L.; Huck, Friedrich O.; Rahman, Zia-Ur; Reichenbach, Stephen E.

    1991-01-01

    Multiresponse imaging is a process that acquires A images, each with a different optical response, and reassembles them into a single image with an improved resolution that can approach 1/sq rt A times the photodetector-array sampling lattice. Our goals are to optimize the performance of this process in terms of the resolution and fidelity of the restored image and to assess the amount of information required to do so. The theoretical approach is based on the extension of both image restoration and rate-distortion theories from their traditional realm of signal processing to image processing which includes image gathering and display.

  20. Tissue Doppler Imaging Combined with Advanced 12-Lead ECG Analysis Might Improve Early Diagnosis of Hypertrophic Cardiomyopathy in Childhood

    NASA Technical Reports Server (NTRS)

    Femlund, E.; Schlegel, T.; Liuba, P.

    2011-01-01

    Optimization of early diagnosis of childhood hypertrophic cardiomyopathy (HCM) is essential in lowering the risk of HCM complications. Standard echocardiography (ECHO) has shown to be less sensitive in this regard. In this study, we sought to assess whether spatial QRS-T angle deviation, which has shown to predict HCM in adults with high sensitivity, and myocardial Tissue Doppler Imaging (TDI) could be additional tools in early diagnosis of HCM in childhood. Methods: Children and adolescents with familial HCM (n=10, median age 16, range 5-27 years), and without obvious hypertrophy but with heredity for HCM (n=12, median age 16, range 4-25 years, HCM or sudden death with autopsy-verified HCM in greater than or equal to 1 first-degree relative, HCM-risk) were additionally investigated with TDI and advanced 12-lead ECG analysis using Cardiax(Registered trademark) (IMED Co Ltd, Budapest, Hungary and Houston). Spatial QRS-T angle (SA) was derived from Kors regression-related transformation. Healthy age-matched controls (n=21) were also studied. All participants underwent thorough clinical examination. Results: Spatial QRS-T angle (Figure/ Panel A) and septal E/Ea ratio (Figure/Panel B) were most increased in HCM group as compared to the HCM-risk and control groups (p less than 0.05). Of note, these 2 variables showed a trend toward higher levels in HCM-risk group than in control group (p=0.05 for E/Ea and 0.06 for QRS/T by ANOVA). In a logistic regression model, increased SA and septal E/Ea ratio appeared to significantly predict both the disease (Chi-square in HCM group: 9 and 5, respectively, p less than 0.05 for both) and the risk for HCM (Chi-square in HCM-risk group: 5 and 4 respectively, p less than 0.05 for both), with further increased predictability level when these 2 variables were combined (Chi-square 10 in HCM group, and 7 in HCM-risk group, p less than 0.01 for both). Conclusions: In this small material, Tissue Doppler Imaging and spatial mean QRS-T angle

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

    PubMed

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

    2016-05-01

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

  2. 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.

  3. Image Analysis of Foods.

    PubMed

    Russ, John C

    2015-09-01

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

  4. Improved real-time imaging spectrometer

    NASA Technical Reports Server (NTRS)

    Lambert, James L. (Inventor); Chao, Tien-Hsin (Inventor); Yu, Jeffrey W. (Inventor); Cheng, Li-Jen (Inventor)

    1993-01-01

    An improved AOTF-based imaging spectrometer that offers several advantages over prior art AOTF imaging spectrometers is presented. The ability to electronically set the bandpass wavelength provides observational flexibility. Various improvements in optical architecture provide simplified magnification variability, improved image resolution and light throughput efficiency and reduced sensitivity to ambient light. Two embodiments of the invention are: (1) operation in the visible/near-infrared domain of wavelength range 0.48 to 0.76 microns; and (2) infrared configuration which operates in the wavelength range of 1.2 to 2.5 microns.

  5. Improved Interactive Medical-Imaging System

    NASA Technical Reports Server (NTRS)

    Ross, Muriel D.; Twombly, Ian A.; Senger, Steven

    2003-01-01

    An improved computational-simulation system for interactive medical imaging has been invented. The system displays high-resolution, three-dimensional-appearing images of anatomical objects based on data acquired by such techniques as computed tomography (CT) and magnetic-resonance imaging (MRI). The system enables users to manipulate the data to obtain a variety of views for example, to display cross sections in specified planes or to rotate images about specified axes. Relative to prior such systems, this system offers enhanced capabilities for synthesizing images of surgical cuts and for collaboration by users at multiple, remote computing sites.

  6. Advanced endoscopic imaging to improve adenoma detection

    PubMed Central

    Neumann, Helmut; Nägel, Andreas; Buda, Andrea

    2015-01-01

    Advanced endoscopic imaging is revolutionizing our way on how to diagnose and treat colorectal lesions. Within recent years a variety of modern endoscopic imaging techniques was introduced to improve adenoma detection rates. Those include high-definition imaging, dye-less chromoendoscopy techniques and novel, highly flexible endoscopes, some of them equipped with balloons or multiple lenses in order to improve adenoma detection rates. In this review we will focus on the newest developments in the field of colonoscopic imaging to improve adenoma detection rates. Described techniques include high-definition imaging, optical chromoendoscopy techniques, virtual chromoendoscopy techniques, the Third Eye Retroscope and other retroviewing devices, the G-EYE endoscope and the Full Spectrum Endoscopy-system. PMID:25789092

  7. Can coffee improve image guidance?

    NASA Astrophysics Data System (ADS)

    Wirz, Raul; Lathrop, Ray A.; Godage, Isuru S.; Burgner-Kahrs, Jessica; Russell, Paul T.; Webster, Robert J.

    2015-03-01

    Anecdotally, surgeons sometimes observe large errors when using image guidance in endonasal surgery. We hypothesize that one contributing factor is the possibility that operating room personnel might accidentally bump the optically tracked rigid body attached to the patient after registration has been performed. In this paper we explore the registration error at the skull base that can be induced by simulated bumping of the rigid body, and find that large errors can occur when simulated bumps are applied to the rigid body. To address this, we propose a new fixation method for the rigid body based on granular jamming (i.e. using particles like ground coffee). Our results show that our granular jamming fixation prototype reduces registration error by 28%-68% (depending on bump direction) in comparison to a standard Brainlab reference headband.

  8. Picosecond Imaging Circuit Analysis

    NASA Astrophysics Data System (ADS)

    Kash, Jeffrey A.

    1998-03-01

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

  9. 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.

  10. Digital Image Analysis of Cereals

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  11. Quantitative analysis of the improvement in omnidirectional maritime surveillance and tracking due to real-time image enhancement

    NASA Astrophysics Data System (ADS)

    de Villiers, Jason P.; Bachoo, Asheer K.; Nicolls, Fred C.; le Roux, Francois P. J.

    2011-05-01

    Tracking targets in a panoramic image is in many senses the inverse problem of tracking targets with a narrow field of view camera on a pan-tilt pedestal. In a narrow field of view camera tracking a moving target, the object is constant and the background is changing. A panoramic camera is able to model the entire scene, or background, and those areas it cannot model well are the potential targets and typically subtended far fewer pixels in the panoramic view compared to the narrow field of view. The outputs of an outward staring array of calibrated machine vision cameras are stitched into a single omnidirectional panorama and used to observe False Bay near Simon's Town, South Africa. A ground truth data-set was created by geo-aligning the camera array and placing a differential global position system receiver on a small target boat thus allowing its position in the array's field of view to be determined. Common tracking techniques including level-sets, Kalman filters and particle filters were implemented to run on the central processing unit of the tracking computer. Image enhancement techniques including multi-scale tone mapping, interpolated local histogram equalisation and several sharpening techniques were implemented on the graphics processing unit. An objective measurement of each tracking algorithm's robustness in the presence of sea-glint, low contrast visibility and sea clutter - such as white caps is performed on the raw recorded video data. These results are then compared to those obtained with the enhanced video data.

  12. Radar image analysis utilizing junctive image metamorphosis

    NASA Astrophysics Data System (ADS)

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

    1998-09-01

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

  13. Improvement of image quality by polarization mixing

    NASA Astrophysics Data System (ADS)

    Kasahara, Ryosuke; Itoh, Izumi; Hirai, Hideaki

    2014-03-01

    Information about the polarization of light is valuable because it contains information about the light source illuminating an object, the illumination angle, and the object material. However, polarization information strongly depends on the direction of the light source, and it is difficult to use a polarization image with various recognition algorithms outdoors because the angle of the sun varies. We propose an image enhancement method for utilizing polarization information in many such situations where the light source is not fixed. We take two approaches to overcome this problem. First, we compute an image that is the combination of a polarization image and the corresponding brightness image. Because of the angle of the light source, the polarization contains no information about some scenes. Therefore, it is difficult to use only polarization information in any scene for applications such as object detection. However, if we use a combination of a polarization image and a brightness image, the brightness image can complement the lack of scene information. The second approach is finding features that depend less on the direction of the light source. We propose a method for extracting scene features based on a calculation of the reflection model including polarization effects. A polarization camera that has micro-polarizers on each pixel of the image sensor was built and used for capturing images. We discuss examples that demonstrate the improved visibility of objects by applying our proposed method to, e.g., the visibility of lane markers on wet roads.

  14. Improved digital breast tomosynthesis images using automated ultrasound

    PubMed Central

    Zhang, Xing; Yuan, Jie; Du, Sidan; Kripfgans, Oliver D.; Wang, Xueding; Carson, Paul L.; Liu, Xiaojun

    2014-01-01

    Purpose: Digital breast tomosynthesis (DBT) offers poor image quality along the depth direction. This paper presents a new method that improves the image quality of DBT considerably through the a priori information from automated ultrasound (AUS) images. Methods: DBT and AUS images of a complex breast-mimicking phantom are acquired by a DBT/AUS dual-modality system. The AUS images are taken in the same geometry as the DBT images and the gradient information of the in-slice AUS images is adopted into the new loss functional during the DBT reconstruction process. The additional data allow for new iterative equations through solving the optimization problem utilizing the gradient descent method. Both visual comparison and quantitative analysis are employed to evaluate the improvement on DBT images. Normalized line profiles of lesions are obtained to compare the edges of the DBT and AUS-corrected DBT images. Additionally, image quality metrics such as signal difference to noise ratio (SDNR) and artifact spread function (ASF) are calculated to quantify the effectiveness of the proposed method. Results: In traditional DBT image reconstructions, serious artifacts can be found along the depth direction (Z direction), resulting in the blurring of lesion edges in the off-focus planes parallel to the detector. However, by applying the proposed method, the quality of the reconstructed DBT images is greatly improved. Visually, the AUS-corrected DBT images have much clearer borders in both in-focus and off-focus planes, fewer Z direction artifacts and reduced overlapping effect compared to the conventional DBT images. Quantitatively, the corrected DBT images have better ASF, indicating a great reduction in Z direction artifacts as well as better Z resolution. The sharper line profiles along the Y direction show enhancement on the edges. Besides, noise is also reduced, evidenced by the obviously improved SDNR values. Conclusions: The proposed method provides great improvement on

  15. Contrast improvement of terahertz images of thin histopathologic sections

    PubMed Central

    Formanek, Florian; Brun, Marc-Aurèle; Yasuda, Akio

    2011-01-01

    We present terahertz images of 10 μm thick histopathologic sections obtained in reflection geometry with a time-domain spectrometer, and demonstrate improved contrast for sections measured in paraffin with water. Automated segmentation is applied to the complex refractive index data to generate clustered terahertz images distinguishing cancer from healthy tissues. The degree of classification of pixels is then evaluated using registered visible microscope images. Principal component analysis and propagation simulations are employed to investigate the origin and the gain of image contrast. PMID:21326635

  16. IMAGE ANALYSIS ALGORITHMS FOR DUAL MODE IMAGING SYSTEMS

    SciTech Connect

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

    2010-06-11

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

  17. 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.

  18. Improving dermoscopy image classification using color constancy.

    PubMed

    Barata, Catarina; Celebi, M Emre; Marques, Jorge S

    2015-05-01

    Robustness is one of the most important characteristics of computer-aided diagnosis systems designed for dermoscopy images. However, it is difficult to ensure this characteristic if the systems operate with multisource images acquired under different setups. Changes in the illumination and acquisition devices alter the color of images and often reduce the performance of the systems. Thus, it is important to normalize the colors of dermoscopy images before training and testing any system. In this paper, we investigate four color constancy algorithms: Gray World, max-RGB, Shades of Gray, and General Gray World. Our results show that color constancy improves the classification of multisource images, increasing the sensitivity of a bag-of-features system from 71.0% to 79.7% and the specificity from 55.2% to 76% using only 1-D RGB histograms as features. PMID:25073179

  19. Improving photoacoustic imaging contrast of brachytherapy seeds

    NASA Astrophysics Data System (ADS)

    Pan, Leo; Baghani, Ali; Rohling, Robert; Abolmaesumi, Purang; Salcudean, Septimiu; Tang, Shuo

    2013-03-01

    Prostate brachytherapy is a form of radiotherapy for treating prostate cancer where the radiation sources are seeds inserted into the prostate. Accurate localization of seeds during prostate brachytherapy is essential to the success of intraoperative treatment planning. The current standard modality used in intraoperative seeds localization is transrectal ultrasound. Transrectal ultrasound, however, suffers in image quality due to several factors such speckle, shadowing, and off-axis seed orientation. Photoacoustic imaging, based on the photoacoustic phenomenon, is an emerging imaging modality. The contrast generating mechanism in photoacoustic imaging is optical absorption that is fundamentally different from conventional B-mode ultrasound which depicts changes in acoustic impedance. A photoacoustic imaging system is developed using a commercial ultrasound system. To improve imaging contrast and depth penetration, absorption enhancing coating is applied to the seeds. In comparison to bare seeds, approximately 18.5 dB increase in signal-to-noise ratio as well as a doubling of imaging depth are achieved. Our results demonstrate that the coating of the seeds can further improve the discernibility of the seeds.

  20. Computational efficiency improvements for image colorization

    NASA Astrophysics Data System (ADS)

    Yu, Chao; Sharma, Gaurav; Aly, Hussein

    2013-03-01

    We propose an efficient algorithm for colorization of greyscale images. As in prior work, colorization is posed as an optimization problem: a user specifies the color for a few scribbles drawn on the greyscale image and the color image is obtained by propagating color information from the scribbles to surrounding regions, while maximizing the local smoothness of colors. In this formulation, colorization is obtained by solving a large sparse linear system, which normally requires substantial computation and memory resources. Our algorithm improves the computational performance through three innovations over prior colorization implementations. First, the linear system is solved iteratively without explicitly constructing the sparse matrix, which significantly reduces the required memory. Second, we formulate each iteration in terms of integral images obtained by dynamic programming, reducing repetitive computation. Third, we use a coarseto- fine framework, where a lower resolution subsampled image is first colorized and this low resolution color image is upsampled to initialize the colorization process for the fine level. The improvements we develop provide significant speedup and memory savings compared to the conventional approach of solving the linear system directly using off-the-shelf sparse solvers, and allow us to colorize images with typical sizes encountered in realistic applications on typical commodity computing platforms.

  1. Improving high resolution retinal image quality using speckle illumination HiLo imaging

    PubMed Central

    Zhou, Xiaolin; Bedggood, Phillip; Metha, Andrew

    2014-01-01

    Retinal image quality from flood illumination adaptive optics (AO) ophthalmoscopes is adversely affected by out-of-focus light scatter due to the lack of confocality. This effect is more pronounced in small eyes, such as that of rodents, because the requisite high optical power confers a large dioptric thickness to the retina. A recently-developed structured illumination microscopy (SIM) technique called HiLo imaging has been shown to reduce the effect of out-of-focus light scatter in flood illumination microscopes and produce pseudo-confocal images with significantly improved image quality. In this work, we adopted the HiLo technique to a flood AO ophthalmoscope and performed AO imaging in both (physical) model and live rat eyes. The improvement in image quality from HiLo imaging is shown both qualitatively and quantitatively by using spatial spectral analysis. PMID:25136486

  2. Improved Guided Image Fusion for Magnetic Resonance and Computed Tomography Imaging

    PubMed Central

    Jameel, Amina

    2014-01-01

    Improved guided image fusion for magnetic resonance and computed tomography imaging is proposed. Existing guided filtering scheme uses Gaussian filter and two-level weight maps due to which the scheme has limited performance for images having noise. Different modifications in filter (based on linear minimum mean square error estimator) and weight maps (with different levels) are proposed to overcome these limitations. Simulation results based on visual and quantitative analysis show the significance of proposed scheme. PMID:24695586

  3. Statistical image analysis of longitudinal RAVENS images

    PubMed Central

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

    2015-01-01

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

  4. Improving Performance During Image-Guided Procedures

    PubMed Central

    Duncan, James R.; Tabriz, David

    2015-01-01

    Objective Image-guided procedures have become a mainstay of modern health care. This article reviews how human operators process imaging data and use it to plan procedures and make intraprocedural decisions. Methods A series of models from human factors research, communication theory, and organizational learning were applied to the human-machine interface that occupies the center stage during image-guided procedures. Results Together, these models suggest several opportunities for improving performance as follows: 1. Performance will depend not only on the operator’s skill but also on the knowledge embedded in the imaging technology, available tools, and existing protocols. 2. Voluntary movements consist of planning and execution phases. Performance subscores should be developed that assess quality and efficiency during each phase. For procedures involving ionizing radiation (fluoroscopy and computed tomography), radiation metrics can be used to assess performance. 3. At a basic level, these procedures consist of advancing a tool to a specific location within a patient and using the tool. Paradigms from mapping and navigation should be applied to image-guided procedures. 4. Recording the content of the imaging system allows one to reconstruct the stimulus/response cycles that occur during image-guided procedures. Conclusions When compared with traditional “open” procedures, the technology used during image-guided procedures places an imaging system and long thin tools between the operator and the patient. Taking a step back and reexamining how information flows through an imaging system and how actions are conveyed through human-machine interfaces suggest that much can be learned from studying system failures. In the same way that flight data recorders revolutionized accident investigations in aviation, much could be learned from recording video data during image-guided procedures. PMID:24921628

  5. Do photographic images of pain improve communication during pain consultations?

    PubMed Central

    Padfield, Deborah; Zakrzewska, Joanna M; de C Williams, Amanda C

    2015-01-01

    BACKGROUND: Visual images may facilitate the communication of pain during consultations. OBJECTIVES: To assess whether photographic images of pain enrich the content and/or process of pain consultation by comparing patients’ and clinicians’ ratings of the consultation experience. METHODS: Photographic images of pain previously co-created by patients with a photographer were provided to new patients attending pain clinic consultations. Seventeen patients selected and used images that best expressed their pain and were compared with 21 patients who were not shown images. Ten clinicians conducted assessments in each condition. After consultation, patients and clinicians completed ratings of aspects of communication and, when images were used, how they influenced the consultation. RESULTS: The majority of both patients and clinicians reported that images enhanced the consultation. Ratings of communication were generally high, with no differences between those with and without images (with the exception of confidence in treatment plan, which was rated more highly in the image group). However, patients’ and clinicians’ ratings of communication were inversely related only in consultations with images. Methodological shortcomings may underlie the present findings of no difference. It is also possible that using images raised patients’ and clinicians’ expectations and encouraged emotional disclosure, in response to which clinicians were dissatisfied with their performance. CONCLUSIONS: Using images in clinical encounters did not have a negative impact on the consultation, nor did it improve communication or satisfaction. These findings will inform future analysis of behaviour in the video-recorded consultations. PMID:25996763

  6. Improving the Remedial Student's Self Image.

    ERIC Educational Resources Information Center

    Glazier, Teresa Ferster

    Teachers at Western Illinois University help improve the self-image of students in college remedial English courses in the following ways: (1) they try to alleviate students' feelings of failure through such methods as stressing the acceptability of spoken dialects but pointing out the practical need for writing in Standard English, and…

  7. Improving Synthetic Aperture Image by Image Compounding in Beamforming Process

    NASA Astrophysics Data System (ADS)

    Martínez-Graullera, Oscar; Higuti, Ricardo T.; Martín, Carlos J.; Ullate, Luis. G.; Romero, David; Parrilla, Montserrat

    2011-06-01

    In this work, signal processing techniques are used to improve the quality of image based on multi-element synthetic aperture techniques. Using several apodization functions to obtain different side lobes distribution, a polarity function and a threshold criterium are used to develop an image compounding technique. The spatial diversity is increased using an additional array, which generates complementary information about the defects, improving the results of the proposed algorithm and producing high resolution and contrast images. The inspection of isotropic plate-like structures using linear arrays and Lamb waves is presented. Experimental results are shown for a 1-mm-thick isotropic aluminum plate with artificial defects using linear arrays formed by 30 piezoelectric elements, with the low dispersion symmetric mode S0 at the frequency of 330 kHz.

  8. Image improvement and three-dimensional reconstruction using holographic image processing

    NASA Technical Reports Server (NTRS)

    Stroke, G. W.; Halioua, M.; Thon, F.; Willasch, D. H.

    1977-01-01

    Holographic computing principles make possible image improvement and synthesis in many cases of current scientific and engineering interest. Examples are given for the improvement of resolution in electron microscopy and 3-D reconstruction in electron microscopy and X-ray crystallography, following an analysis of optical versus digital computing in such applications.

  9. Image processing for improved eye-tracking accuracy

    NASA Technical Reports Server (NTRS)

    Mulligan, J. B.; Watson, A. B. (Principal Investigator)

    1997-01-01

    Video cameras provide a simple, noninvasive method for monitoring a subject's eye movements. An important concept is that of the resolution of the system, which is the smallest eye movement that can be reliably detected. While hardware systems are available that estimate direction of gaze in real-time from a video image of the pupil, such systems must limit image processing to attain real-time performance and are limited to a resolution of about 10 arc minutes. Two ways to improve resolution are discussed. The first is to improve the image processing algorithms that are used to derive an estimate. Off-line analysis of the data can improve resolution by at least one order of magnitude for images of the pupil. A second avenue by which to improve resolution is to increase the optical gain of the imaging setup (i.e., the amount of image motion produced by a given eye rotation). Ophthalmoscopic imaging of retinal blood vessels provides increased optical gain and improved immunity to small head movements but requires a highly sensitive camera. The large number of images involved in a typical experiment imposes great demands on the storage, handling, and processing of data. A major bottleneck had been the real-time digitization and storage of large amounts of video imagery, but recent developments in video compression hardware have made this problem tractable at a reasonable cost. Images of both the retina and the pupil can be analyzed successfully using a basic toolbox of image-processing routines (filtering, correlation, thresholding, etc.), which are, for the most part, well suited to implementation on vectorizing supercomputers.

  10. 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

  11. Imaging Arrays With Improved Transmit Power Capability

    PubMed Central

    Zipparo, Michael J.; Bing, Kristin F.; Nightingale, Kathy R.

    2010-01-01

    Bonded multilayer ceramics and composites incorporating low-loss piezoceramics have been applied to arrays for ultrasound imaging to improve acoustic transmit power levels and to reduce internal heating. Commercially available hard PZT from multiple vendors has been characterized for microstructure, ability to be processed, and electroacoustic properties. Multilayers using the best materials demonstrate the tradeoffs compared with the softer PZT5-H typically used for imaging arrays. Three-layer PZT4 composites exhibit an effective dielectric constant that is three times that of single layer PZT5H, a 50% higher mechanical Q, a 30% lower acoustic impedance, and only a 10% lower coupling coefficient. Application of low-loss multilayers to linear phased and large curved arrays results in equivalent or better element performance. A 3-layer PZT4 composite array achieved the same transmit intensity at 40% lower transmit voltage and with a 35% lower face temperature increase than the PZT-5 control. Although B-mode images show similar quality, acoustic radiation force impulse (ARFI) images show increased displacement for a given drive voltage. An increased failure rate for the multilayers following extended operation indicates that further development of the bond process will be necessary. In conclusion, bonded multilayer ceramics and composites allow additional design freedom to optimize arrays and improve the overall performance for increased acoustic output while maintaining image quality. PMID:20875996

  12. Method of improving a digital image

    NASA Technical Reports Server (NTRS)

    Rahman, Zia-ur (Inventor); Jobson, Daniel J. (Inventor); Woodell, Glenn A. (Inventor)

    1999-01-01

    A method of improving a digital image is provided. The image is initially represented by digital data indexed to represent positions on a display. The digital data is indicative of an intensity value I.sub.i (x,y) for each position (x,y) in each i-th spectral band. The intensity value for each position in each i-th spectral band is adjusted to generate an adjusted intensity value for each position in each i-th spectral band in accordance with ##EQU1## where S is the number of unique spectral bands included in said digital data, W.sub.n is a weighting factor and * denotes the convolution operator. Each surround function F.sub.n (x,y) is uniquely scaled to improve an aspect of the digital image, e.g., dynamic range compression, color constancy, and lightness rendition. The adjusted intensity value for each position in each i-th spectral band is filtered with a common function and then presented to a display device. For color images, a novel color restoration step is added to give the image true-to-life color that closely matches human observation.

  13. Improved image guidance of coronary stent deployment

    NASA Astrophysics Data System (ADS)

    Close, Robert A.; Abbey, Craig K.; Whiting, James S.

    2000-04-01

    Accurate placement and expansion of coronary stents is hindered by the fact that most stents are only slightly radiopaque, and hence difficult to see in a typical coronary x-rays. We propose a new technique for improved image guidance of multiple coronary stents deployment using layer decomposition of cine x-ray images of stented coronary arteries. Layer decomposition models the cone-beam x-ray projections through the chest as a set of superposed layers moving with translation, rotation, and scaling. Radiopaque markers affixed to the guidewire or delivery balloon provide a trackable feature so that the correct vessel motion can be measured for layer decomposition. In addition to the time- averaged layer image, we also derive a background-subtracted image sequence which removes moving background structures. Layer decomposition of contrast-free vessels can be used to guide placement of multiple stents and to assess uniformity of stent expansion. Layer decomposition of contrast-filled vessels can be used to measure residual stenosis to determine the adequacy of stent expansion. We demonstrate that layer decomposition of a clinical cine x-ray image sequence greatly improves the visibility of a previously deployed stent. We show that layer decomposition of contrast-filled vessels removes background structures and reduces noise.

  14. Reflections on ultrasound image analysis.

    PubMed

    Alison Noble, J

    2016-10-01

    Ultrasound (US) image analysis has advanced considerably in twenty years. Progress in ultrasound image analysis has always been fundamental to the advancement of image-guided interventions research due to the real-time acquisition capability of ultrasound and this has remained true over the two decades. But in quantitative ultrasound image analysis - which takes US images and turns them into more meaningful clinical information - thinking has perhaps more fundamentally changed. From roots as a poor cousin to Computed Tomography (CT) and Magnetic Resonance (MR) image analysis, both of which have richer anatomical definition and thus were better suited to the earlier eras of medical image analysis which were dominated by model-based methods, ultrasound image analysis has now entered an exciting new era, assisted by advances in machine learning and the growing clinical and commercial interest in employing low-cost portable ultrasound devices outside traditional hospital-based clinical settings. This short article provides a perspective on this change, and highlights some challenges ahead and potential opportunities in ultrasound image analysis which may both have high impact on healthcare delivery worldwide in the future but may also, perhaps, take the subject further away from CT and MR image analysis research with time. PMID:27503078

  15. Improving Secondary Ion Mass Spectrometry Image Quality with Image Fusion

    PubMed Central

    Tarolli, Jay G.; Jackson, Lauren M.; Winograd, Nicholas

    2014-01-01

    The spatial resolution of chemical images acquired with cluster secondary ion mass spectrometry (SIMS) is limited not only by the size of the probe utilized to create the images, but also by detection sensitivity. As the probe size is reduced to below 1 µm, for example, a low signal in each pixel limits lateral resolution due to counting statistics considerations. Although it can be useful to implement numerical methods to mitigate this problem, here we investigate the use of image fusion to combine information from scanning electron microscope (SEM) data with chemically resolved SIMS images. The advantage of this approach is that the higher intensity and, hence, spatial resolution of the electron images can help to improve the quality of the SIMS images without sacrificing chemical specificity. Using a pan-sharpening algorithm, the method is illustrated using synthetic data, experimental data acquired from a metallic grid sample, and experimental data acquired from a lawn of algae cells. The results show that up to an order of magnitude increase in spatial resolution is possible to achieve. A cross-correlation metric is utilized for evaluating the reliability of the procedure. PMID:24912432

  16. An improved SIFT algorithm based on KFDA in image registration

    NASA Astrophysics Data System (ADS)

    Chen, Peng; Yang, Lijuan; Huo, Jinfeng

    2016-03-01

    As a kind of stable feature matching algorithm, SIFT has been widely used in many fields. In order to further improve the robustness of the SIFT algorithm, an improved SIFT algorithm with Kernel Discriminant Analysis (KFDA-SIFT) is presented for image registration. The algorithm uses KFDA to SIFT descriptors for feature extraction matrix, and uses the new descriptors to conduct the feature matching, finally chooses RANSAC to deal with the matches for further purification. The experiments show that the presented algorithm is robust to image changes in scale, illumination, perspective, expression and tiny pose with higher matching accuracy.

  17. Improved Chen-Smith image coder

    NASA Astrophysics Data System (ADS)

    Rubino, Eduardo M.; de Queiroz, Ricardo L.; Malvar, Henrique S.

    1995-04-01

    A new transform coder based on the zonal sampling strategy, which outperforms the JPEG baseline coder with comparable computational complexity, is presented. The primary transform used is the 8- x 8-pixel-block discrete cosine transform, although it can be replaced by other transforms, such as the lapped orthogonal transform, without any change in the algorithm. This coder is originally based on the Chen-Smith coder; therefore we call it an improved Chen-Smith (ICS) coder. However, because many new features were incorporated in this improved version, it largely outperforms its predecessor. Key approaches in the ICS coder, such as a new quantizer design, arithmetic coders, noninteger bit-rate allocation, decimalized variance maps, distance-based block classification, and human visual sensitivity weighting, are essential for its high performance, Image compression programs were developed and applied to several test images. The results show that the ICS performs substantially better than the JPEG coder.

  18. [An improved medical image fusion algorithm and quality evaluation].

    PubMed

    Chen, Meiling; Tao, Ling; Qian, Zhiyu

    2009-08-01

    Medical image fusion is of very important value for application in medical image analysis and diagnosis. In this paper, the conventional method of wavelet fusion is improved,so a new algorithm of medical image fusion is presented and the high frequency and low frequency coefficients are studied respectively. When high frequency coefficients are chosen, the regional edge intensities of each sub-image are calculated to realize adaptive fusion. The choice of low frequency coefficient is based on the edges of images, so that the fused image preserves all useful information and appears more distinctly. We apply the conventional and the improved fusion algorithms based on wavelet transform to fuse two images of human body and also evaluate the fusion results through a quality evaluation method. Experimental results show that this algorithm can effectively retain the details of information on original images and enhance their edge and texture features. This new algorithm is better than the conventional fusion algorithm based on wavelet transform. PMID:19813594

  19. 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.

  20. 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.

  1. Perceived Image Quality Improvements from the Application of Image Deconvolution to Retinal Images from an Adaptive Optics Fundus Imager

    NASA Astrophysics Data System (ADS)

    Soliz, P.; Nemeth, S. C.; Erry, G. R. G.; Otten, L. J.; Yang, S. Y.

    Aim: The objective of this project was to apply an image restoration methodology based on wavefront measurements obtained with a Shack-Hartmann sensor and evaluating the restored image quality based on medical criteria.Methods: Implementing an adaptive optics (AO) technique, a fundus imager was used to achieve low-order correction to images of the retina. The high-order correction was provided by deconvolution. A Shack-Hartmann wavefront sensor measures aberrations. The wavefront measurement is the basis for activating a deformable mirror. Image restoration to remove remaining aberrations is achieved by direct deconvolution using the point spread function (PSF) or a blind deconvolution. The PSF is estimated using measured wavefront aberrations. Direct application of classical deconvolution methods such as inverse filtering, Wiener filtering or iterative blind deconvolution (IBD) to the AO retinal images obtained from the adaptive optical imaging system is not satisfactory because of the very large image size, dificulty in modeling the system noise, and inaccuracy in PSF estimation. Our approach combines direct and blind deconvolution to exploit available system information, avoid non-convergence, and time-consuming iterative processes. Results: The deconvolution was applied to human subject data and resulting restored images compared by a trained ophthalmic researcher. Qualitative analysis showed significant improvements. Neovascularization can be visualized with the adaptive optics device that cannot be resolved with the standard fundus camera. The individual nerve fiber bundles are easily resolved as are melanin structures in the choroid. Conclusion: This project demonstrated that computer-enhanced, adaptive optic images have greater detail of anatomical and pathological structures.

  2. Improved Scanners for Microscopic Hyperspectral Imaging

    NASA Technical Reports Server (NTRS)

    Mao, Chengye

    2009-01-01

    Improved scanners to be incorporated into hyperspectral microscope-based imaging systems have been invented. Heretofore, in microscopic imaging, including spectral imaging, it has been customary to either move the specimen relative to the optical assembly that includes the microscope or else move the entire assembly relative to the specimen. It becomes extremely difficult to control such scanning when submicron translation increments are required, because the high magnification of the microscope enlarges all movements in the specimen image on the focal plane. To overcome this difficulty, in a system based on this invention, no attempt would be made to move either the specimen or the optical assembly. Instead, an objective lens would be moved within the assembly so as to cause translation of the image at the focal plane: the effect would be equivalent to scanning in the focal plane. The upper part of the figure depicts a generic proposed microscope-based hyperspectral imaging system incorporating the invention. The optical assembly of this system would include an objective lens (normally, a microscope objective lens) and a charge-coupled-device (CCD) camera. The objective lens would be mounted on a servomotor-driven translation stage, which would be capable of moving the lens in precisely controlled increments, relative to the camera, parallel to the focal-plane scan axis. The output of the CCD camera would be digitized and fed to a frame grabber in a computer. The computer would store the frame-grabber output for subsequent viewing and/or processing of images. The computer would contain a position-control interface board, through which it would control the servomotor. There are several versions of the invention. An essential feature common to all versions is that the stationary optical subassembly containing the camera would also contain a spatial window, at the focal plane of the objective lens, that would pass only a selected portion of the image. In one version

  3. Hyperspectral image analysis. A tutorial.

    PubMed

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

    2015-10-01

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

  4. Improved imaging algorithm for bridge crack detection

    NASA Astrophysics Data System (ADS)

    Lu, Jingxiao; Song, Pingli; Han, Kaihong

    2012-04-01

    This paper present an improved imaging algorithm for bridge crack detection, through optimizing the eight-direction Sobel edge detection operator, making the positioning of edge points more accurate than without the optimization, and effectively reducing the false edges information, so as to facilitate follow-up treatment. In calculating the crack geometry characteristics, we use the method of extracting skeleton on single crack length. In order to calculate crack area, we construct the template of area by making logical bitwise AND operation of the crack image. After experiment, the results show errors of the crack detection method and actual manual measurement are within an acceptable range, meet the needs of engineering applications. This algorithm is high-speed and effective for automated crack measurement, it can provide more valid data for proper planning and appropriate performance of the maintenance and rehabilitation processes of bridge.

  5. Improved Imaging Resolution in Desorption Electrospray Ionization Mass Spectrometry

    SciTech Connect

    Kertesz, Vilmos; Van Berkel, Gary J

    2008-01-01

    Imaging resolution of desorption electrospray ionization mass spectrometry (DESI-MS) was investigated using printed patterns on paper and thin-layer chromatography (TLC) plate surfaces. Resolution approaching 40 m was achieved with a typical DESI-MS setup, which is approximately 5 times better than the best resolution reported previously. This improvement was accomplished with careful control of operational parameters (particularly spray tip-to-surface distance, solvent flow rate, and spacing of lane scans). Also, an appropriately strong analyte/surface interaction and uniform surface texture on the size scale no larger that the desired imaging resolution were required to achieve this resolution. Overall, conditions providing the smallest possible effective desorption/ionization area in the DESI impact plume region and minimizing the analyte redistribution on the surface during analysis led to the improved DESI-MS imaging resolution.

  6. Improved wheal detection from skin prick test images

    NASA Astrophysics Data System (ADS)

    Bulan, Orhan

    2014-03-01

    Skin prick test is a commonly used method for diagnosis of allergic diseases (e.g., pollen allergy, food allergy, etc.) in allergy clinics. The results of this test are erythema and wheal provoked on the skin where the test is applied. The sensitivity of the patient against a specific allergen is determined by the physical size of the wheal, which can be estimated from images captured by digital cameras. Accurate wheal detection from these images is an important step for precise estimation of wheal size. In this paper, we propose a method for improved wheal detection on prick test images captured by digital cameras. Our method operates by first localizing the test region by detecting calibration marks drawn on the skin. The luminance variation across the localized region is eliminated by applying a color transformation from RGB to YCbCr and discarding the luminance channel. We enhance the contrast of the captured images for the purpose of wheal detection by performing principal component analysis on the blue-difference (Cb) and red-difference (Cr) color channels. We finally, perform morphological operations on the contrast enhanced image to detect the wheal on the image plane. Our experiments performed on images acquired from 36 different patients show the efficiency of the proposed method for wheal detection from skin prick test images captured in an uncontrolled environment.

  7. Breast cancer histopathology image analysis: a review.

    PubMed

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

    2014-05-01

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

  8. Automatic identification of ROI in figure images toward improving hybrid (text and image) biomedical document retrieval

    NASA Astrophysics Data System (ADS)

    You, Daekeun; Antani, Sameer; Demner-Fushman, Dina; Rahman, Md Mahmudur; Govindaraju, Venu; Thoma, George R.

    2011-01-01

    Biomedical images are often referenced for clinical decision support (CDS), educational purposes, and research. They appear in specialized databases or in biomedical publications and are not meaningfully retrievable using primarily textbased retrieval systems. The task of automatically finding the images in an article that are most useful for the purpose of determining relevance to a clinical situation is quite challenging. An approach is to automatically annotate images extracted from scientific publications with respect to their usefulness for CDS. As an important step toward achieving the goal, we proposed figure image analysis for localizing pointers (arrows, symbols) to extract regions of interest (ROI) that can then be used to obtain meaningful local image content. Content-based image retrieval (CBIR) techniques can then associate local image ROIs with identified biomedical concepts in figure captions for improved hybrid (text and image) retrieval of biomedical articles. In this work we present methods that make robust our previous Markov random field (MRF)-based approach for pointer recognition and ROI extraction. These include use of Active Shape Models (ASM) to overcome problems in recognizing distorted pointer shapes and a region segmentation method for ROI extraction. We measure the performance of our methods on two criteria: (i) effectiveness in recognizing pointers in images, and (ii) improved document retrieval through use of extracted ROIs. Evaluation on three test sets shows 87% accuracy in the first criterion. Further, the quality of document retrieval using local visual features and text is shown to be better than using visual features alone.

  9. Depth-based selective image reconstruction using spatiotemporal image analysis

    NASA Astrophysics Data System (ADS)

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

    1999-03-01

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

  10. Using Image Analysis to Build Reading Comprehension

    ERIC Educational Resources Information Center

    Brown, Sarah Drake; Swope, John

    2010-01-01

    Content area reading remains a primary concern of history educators. In order to better prepare students for encounters with text, the authors propose the use of two image analysis strategies tied with a historical theme to heighten student interest in historical content and provide a basis for improved reading comprehension.

  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. Improved estimation of parametric images of cerebral glucose metabolic rate from dynamic FDG-PET using volume-wise principle component analysis

    NASA Astrophysics Data System (ADS)

    Dai, Xiaoqian; Tian, Jie; Chen, Zhe

    2010-03-01

    Parametric images can represent both spatial distribution and quantification of the biological and physiological parameters of tracer kinetics. The linear least square (LLS) method is a well-estimated linear regression method for generating parametric images by fitting compartment models with good computational efficiency. However, bias exists in LLS-based parameter estimates, owing to the noise present in tissue time activity curves (TTACs) that propagates as correlated error in the LLS linearized equations. To address this problem, a volume-wise principal component analysis (PCA) based method is proposed. In this method, firstly dynamic PET data are properly pre-transformed to standardize noise variance as PCA is a data driven technique and can not itself separate signals from noise. Secondly, the volume-wise PCA is applied on PET data. The signals can be mostly represented by the first few principle components (PC) and the noise is left in the subsequent PCs. Then the noise-reduced data are obtained using the first few PCs by applying 'inverse PCA'. It should also be transformed back according to the pre-transformation method used in the first step to maintain the scale of the original data set. Finally, the obtained new data set is used to generate parametric images using the linear least squares (LLS) estimation method. Compared with other noise-removal method, the proposed method can achieve high statistical reliability in the generated parametric images. The effectiveness of the method is demonstrated both with computer simulation and with clinical dynamic FDG PET study.

  13. Image Analysis in Surgical Pathology.

    PubMed

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

    2016-06-01

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

  14. Principal component analysis of scintimammographic images.

    PubMed

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

    2006-01-01

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

  15. Improvement of the detection rate in digital watermarked images against image degradation caused by image processing

    NASA Astrophysics Data System (ADS)

    Nishio, Masato; Ando, Yutaka; Tsukamoto, Nobuhiro; Kawashima, Hironao; Nakamura, Shinya

    2004-04-01

    In the current environment of medical information disclosure, the general-purpose image format such as JPEG/BMP which does not require special software for viewing, is suitable for carrying and managing medical image information individually. These formats have no way to know patient and study information. We have therefore developed two kinds of ID embedding methods: one is Bit-swapping method for embedding Alteration detection ID and the other is data-imposing method in Fourier domain using Discrete Cosine Transform (DCT) for embedding Original image source ID. We then applied these two digital watermark methods to four modality images (Chest X-ray, Head CT, Abdomen CT, Bone scintigraphy). However, there were some cases where the digital watermarked ID could not be detected correctly due to image degradation caused by image processing. In this study, we improved the detection rate in digital watermarked image using several techniques, which are Error correction method, Majority correction method, and Scramble location method. We applied these techniques to digital watermarked images against image processing (Smoothing) and evaluated the effectiveness. As a result, Majority correction method is effective to improve the detection rate in digital watermarked image against image degradation.

  16. Figure content analysis for improved biomedical article retrieval

    NASA Astrophysics Data System (ADS)

    You, Daekeun; Apostolova, Emilia; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

    2009-01-01

    Biomedical images are invaluable in medical education and establishing clinical diagnosis. Clinical decision support (CDS) can be improved by combining biomedical text with automatically annotated images extracted from relevant biomedical publications. In a previous study we reported 76.6% accuracy using supervised machine learning on the feasibility of automatically classifying images by combining figure captions and image content for usefulness in finding clinical evidence. Image content extraction is traditionally applied on entire images or on pre-determined image regions. Figure images articles vary greatly limiting benefit of whole image extraction beyond gross categorization for CDS due to the large variety. However, text annotations and pointers on them indicate regions of interest (ROI) that are then referenced in the caption or discussion in the article text. We have previously reported 72.02% accuracy in text and symbols localization but we failed to take advantage of the referenced image locality. In this work we combine article text analysis and figure image analysis for localizing pointer (arrows, symbols) to extract ROI pointed that can then be used to measure meaningful image content and associate it with the identified biomedical concepts for improved (text and image) content-based retrieval of biomedical articles. Biomedical concepts are identified using National Library of Medicine's Unified Medical Language System (UMLS) Metathesaurus. Our methods report an average precision and recall of 92.3% and 75.3%, respectively on identifying pointing symbols in images from a randomly selected image subset made available through the ImageCLEF 2008 campaign.

  17. Image analysis for DNA sequencing

    NASA Astrophysics Data System (ADS)

    Palaniappan, Kannappan; Huang, Thomas S.

    1991-07-01

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

  18. Improved MCA-TV algorithm for interference hyperspectral image decomposition

    NASA Astrophysics Data System (ADS)

    Wen, Jia; Zhao, Junsuo; Cailing, Wang

    2015-12-01

    The technology of interference hyperspectral imaging, which can get the spectral and spatial information of the observed targets, is a very powerful technology in the field of remote sensing. Due to the special imaging principle, there are many position-fixed interference fringes in each frame of the interference hyperspectral image (IHI) data. This characteristic will affect the result of compressed sensing theory and traditional compression algorithms used on IHI data. According to this characteristic of the IHI data, morphological component analysis (MCA) is adopted to separate the interference fringes layers and the background layers of the LSMIS (Large Spatially Modulated Interference Spectral Image) data, and an improved MCA and Total Variation (TV) combined algorithm is proposed in this paper. An update mode of the threshold in traditional MCA is proposed, and the traditional TV algorithm is also improved according to the unidirectional characteristic of the interference fringes in IHI data. The experimental results prove that the proposed improved MCA-TV (IMT) algorithm can get better results than the traditional MCA, and also can meet the convergence conditions much faster than the traditional MCA.

  19. 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.

  20. Analysis of image quality based on perceptual preference

    NASA Astrophysics Data System (ADS)

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

    2007-11-01

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

  1. Image analysis and quantitative morphology.

    PubMed

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

    2010-01-01

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

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

    SciTech Connect

    Shoaf, S.; APS Engineering Support Division

    2008-01-01

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

  3. 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.

  4. Quantitative histogram analysis of images

    NASA Astrophysics Data System (ADS)

    Holub, Oliver; Ferreira, Sérgio T.

    2006-11-01

    A routine for histogram analysis of images has been written in the object-oriented, graphical development environment LabVIEW. The program converts an RGB bitmap image into an intensity-linear greyscale image according to selectable conversion coefficients. This greyscale image is subsequently analysed by plots of the intensity histogram and probability distribution of brightness, and by calculation of various parameters, including average brightness, standard deviation, variance, minimal and maximal brightness, mode, skewness and kurtosis of the histogram and the median of the probability distribution. The program allows interactive selection of specific regions of interest (ROI) in the image and definition of lower and upper threshold levels (e.g., to permit the removal of a constant background signal). The results of the analysis of multiple images can be conveniently saved and exported for plotting in other programs, which allows fast analysis of relatively large sets of image data. The program file accompanies this manuscript together with a detailed description of two application examples: The analysis of fluorescence microscopy images, specifically of tau-immunofluorescence in primary cultures of rat cortical and hippocampal neurons, and the quantification of protein bands by Western-blot. The possibilities and limitations of this kind of analysis are discussed. Program summaryTitle of program: HAWGC Catalogue identifier: ADXG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADXG_v1_0 Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computers: Mobile Intel Pentium III, AMD Duron Installations: No installation necessary—Executable file together with necessary files for LabVIEW Run-time engine Operating systems or monitors under which the program has been tested: WindowsME/2000/XP Programming language used: LabVIEW 7.0 Memory required to execute with typical data:˜16MB for starting and ˜160MB used for

  5. Improving Accuracy of Image Classification Using GIS

    NASA Astrophysics Data System (ADS)

    Gupta, R. K.; Prasad, T. S.; Bala Manikavelu, P. M.; Vijayan, D.

    The Remote Sensing signal which reaches sensor on-board the satellite is the complex aggregation of signals (in agriculture field for example) from soil (with all its variations such as colour, texture, particle size, clay content, organic and nutrition content, inorganic content, water content etc.), plant (height, architecture, leaf area index, mean canopy inclination etc.), canopy closure status and atmospheric effects, and from this we want to find say, characteristics of vegetation. If sensor on- board the satellite makes measurements in n-bands (n of n*1 dimension) and number of classes in an image are c (f of c*1 dimension), then considering linear mixture modeling the pixel classification problem could be written as n = m* f +, where m is the transformation matrix of (n*c) dimension and therepresents the error vector (noise). The problem is to estimate f by inverting the above equation and the possible solutions for such problem are many. Thus, getting back individual classes from satellite data is an ill-posed inverse problem for which unique solution is not feasible and this puts limit to the obtainable classification accuracy. Maximum Likelihood (ML) is the constraint mostly practiced in solving such a situation which suffers from the handicaps of assumed Gaussian distribution and random nature of pixels (in-fact there is high auto-correlation among the pixels of a specific class and further high auto-correlation among the pixels in sub- classes where the homogeneity would be high among pixels). Due to this, achieving of very high accuracy in the classification of remote sensing images is not a straight proposition. With the availability of the GIS for the area under study (i) a priori probability for different classes could be assigned to ML classifier in more realistic terms and (ii) the purity of training sets for different thematic classes could be better ascertained. To what extent this could improve the accuracy of classification in ML classifier

  6. Hybrid µCT-FMT imaging and image analysis

    PubMed Central

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

    2015-01-01

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

  7. APPLICATION OF PRINCIPAL COMPONENT ANALYSIS TO RELAXOGRAPHIC IMAGES

    SciTech Connect

    STOYANOVA,R.S.; OCHS,M.F.; BROWN,T.R.; ROONEY,W.D.; LI,X.; LEE,J.H.; SPRINGER,C.S.

    1999-05-22

    Standard analysis methods for processing inversion recovery MR images traditionally have used single pixel techniques. In these techniques each pixel is independently fit to an exponential recovery, and spatial correlations in the data set are ignored. By analyzing the image as a complete dataset, improved error analysis and automatic segmentation can be achieved. Here, the authors apply principal component analysis (PCA) to a series of relaxographic images. This procedure decomposes the 3-dimensional data set into three separate images and corresponding recovery times. They attribute the 3 images to be spatial representations of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF) content.

  8. Improving resolution of optical coherence tomography for imaging of microstructures

    NASA Astrophysics Data System (ADS)

    Shen, Kai; Lu, Hui; Wang, James H.; Wang, Michael R.

    2015-03-01

    Multi-frame superresolution technique has been used to improve the lateral resolution of spectral domain optical coherence tomography (SD-OCT) for imaging of 3D microstructures. By adjusting the voltages applied to ? and ? galvanometer scanners in the measurement arm, small lateral imaging positional shifts have been introduced among different C-scans. Utilizing the extracted ?-? plane en face image frames from these specially offset C-scan image sets at the same axial position, we have reconstructed the lateral high resolution image by the efficient multi-frame superresolution technique. To further improve the image quality, we applied the latest K-SVD and bilateral total variation denoising algorithms to the raw SD-OCT lateral images before and along with the superresolution processing, respectively. The performance of the SD-OCT of improved lateral resolution is demonstrated by 3D imaging a microstructure fabricated by photolithography and a double-layer microfluidic device.

  9. An improved piecewise linear chaotic map based image encryption algorithm.

    PubMed

    Hu, Yuping; Zhu, Congxu; Wang, Zhijian

    2014-01-01

    An image encryption algorithm based on improved piecewise linear chaotic map (MPWLCM) model was proposed. The algorithm uses the MPWLCM to permute and diffuse plain image simultaneously. Due to the sensitivity to initial key values, system parameters, and ergodicity in chaotic system, two pseudorandom sequences are designed and used in the processes of permutation and diffusion. The order of processing pixels is not in accordance with the index of pixels, but it is from beginning or end alternately. The cipher feedback was introduced in diffusion process. Test results and security analysis show that not only the scheme can achieve good encryption results but also its key space is large enough to resist against brute attack. PMID:24592159

  10. An Improved Piecewise Linear Chaotic Map Based Image Encryption Algorithm

    PubMed Central

    Hu, Yuping; Wang, Zhijian

    2014-01-01

    An image encryption algorithm based on improved piecewise linear chaotic map (MPWLCM) model was proposed. The algorithm uses the MPWLCM to permute and diffuse plain image simultaneously. Due to the sensitivity to initial key values, system parameters, and ergodicity in chaotic system, two pseudorandom sequences are designed and used in the processes of permutation and diffusion. The order of processing pixels is not in accordance with the index of pixels, but it is from beginning or end alternately. The cipher feedback was introduced in diffusion process. Test results and security analysis show that not only the scheme can achieve good encryption results but also its key space is large enough to resist against brute attack. PMID:24592159

  11. Improvement of passive THz camera images

    NASA Astrophysics Data System (ADS)

    Kowalski, Marcin; Piszczek, Marek; Palka, Norbert; Szustakowski, Mieczyslaw

    2012-10-01

    Terahertz technology is one of emerging technologies that has a potential to change our life. There are a lot of attractive applications in fields like security, astronomy, biology and medicine. Until recent years, terahertz (THz) waves were an undiscovered, or most importantly, an unexploited area of electromagnetic spectrum. The reasons of this fact were difficulties in generation and detection of THz waves. Recent advances in hardware technology have started to open up the field to new applications such as THz imaging. The THz waves can penetrate through various materials. However, automated processing of THz images can be challenging. The THz frequency band is specially suited for clothes penetration because this radiation does not point any harmful ionizing effects thus it is safe for human beings. Strong technology development in this band have sparked with few interesting devices. Even if the development of THz cameras is an emerging topic, commercially available passive cameras still offer images of poor quality mainly because of its low resolution and low detectors sensitivity. Therefore, THz image processing is very challenging and urgent topic. Digital THz image processing is a really promising and cost-effective way for demanding security and defense applications. In the article we demonstrate the results of image quality enhancement and image fusion of images captured by a commercially available passive THz camera by means of various combined methods. Our research is focused on dangerous objects detection - guns, knives and bombs hidden under some popular types of clothing.

  12. Method for improving visualization of infrared images

    NASA Astrophysics Data System (ADS)

    Cimbalista, Mario

    2014-05-01

    Thermography has an extremely important difference from the other visual image converting electronic systems, like XRays or ultrasound: the infrared camera operator usually spend hour after hour with his/her eyes looking only at infrared images, sometimes several intermittent hours a day if not six or more continuous hours. This operational characteristic has a very important impact on yield, precision, errors and misinterpretation of the infrared images contents. Despite a great hardware development over the last fifty years, quality infrared thermography still lacks for a solution for these problems. The human eye physiology has not evolved to see infrared radiation neither the mind-brain has the capability to understand and decode infrared information. Chemical processes inside the human eye and functional cells distributions as well as cognitive-perceptual impact of images plays a crucial role in the perception, detection, and other steps of dealing with infrared images. The system presented here, called ThermoScala and patented in USA solves this problem using a coding process applicable to an original infrared image, generated from any value matrix, from any kind of infrared camera to make it much more suitable for human usage, causing a substantial difference in the way the retina and the brain processes the resultant images. The result obtained is a much less exhaustive way to see, identify and interpret infrared images generated by any infrared camera that uses this conversion process.

  13. Research on super-resolution image reconstruction based on an improved POCS algorithm

    NASA Astrophysics Data System (ADS)

    Xu, Haiming; Miao, Hong; Yang, Chong; Xiong, Cheng

    2015-07-01

    Super-resolution image reconstruction (SRIR) can improve the fuzzy image's resolution; solve the shortage of the spatial resolution, excessive noise, and low-quality problem of the image. Firstly, we introduce the image degradation model to reveal the essence of super-resolution reconstruction process is an ill-posed inverse problem in mathematics. Secondly, analysis the blurring reason of optical imaging process - light diffraction and small angle scattering is the main reason for the fuzzy; propose an image point spread function estimation method and an improved projection onto convex sets (POCS) algorithm which indicate effectiveness by analyzing the changes between the time domain and frequency domain algorithm in the reconstruction process, pointed out that the improved POCS algorithms based on prior knowledge have the effect to restore and approach the high frequency of original image scene. Finally, we apply the algorithm to reconstruct synchrotron radiation computer tomography (SRCT) image, and then use these images to reconstruct the three-dimensional slice images. Comparing the differences between the original method and super-resolution algorithm, it is obvious that the improved POCS algorithm can restrain the noise and enhance the image resolution, so it is indicated that the algorithm is effective. This study and exploration to super-resolution image reconstruction by improved POCS algorithm is proved to be an effective method. It has important significance and broad application prospects - for example, CT medical image processing and SRCT ceramic sintering analyze of microstructure evolution mechanism.

  14. Improved cancer diagnostics by different image processing techniques on OCT images

    NASA Astrophysics Data System (ADS)

    Kanawade, Rajesh; Lengenfelder, Benjamin; Marini Menezes, Tassiana; Hohmann, Martin; Kopfinger, Stefan; Hohmann, Tim; Grabiec, Urszula; Klämpfl, Florian; Gonzales Menezes, Jean; Waldner, Maximilian; Schmidt, Michael

    2015-07-01

    Optical-coherence tomography (OCT) is a promising non-invasive, high-resolution imaging modality which can be used for cancer diagnosis and its therapeutic assessment. However, speckle noise makes detection of cancer boundaries and image segmentation problematic and unreliable. Therefore, to improve the image analysis for a precise cancer border detection, the performance of different image processing algorithms such as mean, median, hybrid median filter and rotational kernel transformation (RKT) for this task is investigated. This is done on OCT images acquired from an ex-vivo human cancerous mucosa and in vitro by using cultivated tumour applied on organotypical hippocampal slice cultures. The preliminary results confirm that the border between the healthy and the cancer lesions can be identified precisely. The obtained results are verified with fluorescence microscopy. This research can improve cancer diagnosis and the detection of borders between healthy and cancerous tissue. Thus, it could also reduce the number of biopsies required during screening endoscopy by providing better guidance to the physician.

  15. IMPROVED BACKGROUND SUBTRACTION FOR THE SLOAN DIGITAL SKY SURVEY IMAGES

    SciTech Connect

    Blanton, Michael R.; Kazin, Eyal; Muna, Demitri; Weaver, Benjamin A.; Price-Whelan, Adrian

    2011-07-15

    We describe a procedure for background subtracting Sloan Digital Sky Survey (SDSS) imaging that improves the resulting detection and photometry of large galaxies on the sky. Within each SDSS drift scan run, we mask out detected sources and then fit a smooth function to the variation of the sky background. This procedure has been applied to all SDSS-III Data Release 8 images, and the results are available as part of that data set. We have tested the effect of our background subtraction on the photometry of large galaxies by inserting fake galaxies into the raw pixels, reanalyzing the data, and measuring them after background subtraction. Our technique results in no size-dependent bias in galaxy fluxes up to half-light radii r{sub 50} {approx} 100 arcsec; in contrast, for galaxies of that size the standard SDSS photometric catalog underestimates fluxes by about 1.5 mag. Our results represent a substantial improvement over the standard SDSS catalog results and should form the basis of any analysis of nearby galaxies using the SDSS imaging data.

  16. An improved fusion algorithm for infrared and visible images based on multi-scale transform

    NASA Astrophysics Data System (ADS)

    Li, He; Liu, Lei; Huang, Wei; Yue, Chao

    2016-01-01

    In this paper, an improved fusion algorithm for infrared and visible images based on multi-scale transform is proposed. First of all, Morphology-Hat transform is used for an infrared image and a visible image separately. Then two images were decomposed into high-frequency and low-frequency images by contourlet transform (CT). The fusion strategy of high-frequency images is based on mean gradient and the fusion strategy of low-frequency images is based on Principal Component Analysis (PCA). Finally, the final fused image is obtained by using the inverse contourlet transform (ICT). The experiments and results demonstrate that the proposed method can significantly improve image fusion performance, accomplish notable target information and high contrast and preserve rich details information at the same time.

  17. A computational image analysis glossary for biologists.

    PubMed

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

    2012-09-01

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

  18. Institutional Image: How to Define, Improve, Market It.

    ERIC Educational Resources Information Center

    Topor, Robert S.

    Advice for colleges on how to identify, develop, and communicate a positive image for the institution is offered in this handbook. The use of market research techniques to measure image is discussed along with advice on how to improve an image so that it contributes to a unified marketing plan. The first objective is to create and communicate some…

  19. Target identification by image analysis.

    PubMed

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

    2016-05-01

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

  20. Improving image segmentation by learning region affinities

    SciTech Connect

    Prasad, Lakshman; Yang, Xingwei; Latecki, Longin J

    2010-11-03

    We utilize the context information of other regions in hierarchical image segmentation to learn new regions affinities. It is well known that a single choice of quantization of an image space is highly unlikely to be a common optimal quantization level for all categories. Each level of quantization has its own benefits. Therefore, we utilize the hierarchical information among different quantizations as well as spatial proximity of their regions. The proposed affinity learning takes into account higher order relations among image regions, both local and long range relations, making it robust to instabilities and errors of the original, pairwise region affinities. Once the learnt affinities are obtained, we use a standard image segmentation algorithm to get the final segmentation. Moreover, the learnt affinities can be naturally unutilized in interactive segmentation. Experimental results on Berkeley Segmentation Dataset and MSRC Object Recognition Dataset are comparable and in some aspects better than the state-of-art methods.

  1. Image Inpainting Methods Evaluation and Improvement

    PubMed Central

    Vreja, Raluca

    2014-01-01

    With the upgrowing of digital processing of images and film archiving, the need for assisted or unsupervised restoration required the development of a series of methods and techniques. Among them, image inpainting is maybe the most impressive and useful. Based on partial derivative equations or texture synthesis, many other hybrid techniques have been proposed recently. The need for an analytical comparison, beside the visual one, urged us to perform the studies shown in the present paper. Starting with an overview of the domain, an evaluation of the five methods was performed using a common benchmark and measuring the PSNR. Conclusions regarding the performance of the investigated algorithms have been presented, categorizing them in function of the restored image structure. Based on these experiments, we have proposed an adaptation of Oliveira's and Hadhoud's algorithms, which are performing well on images with natural defects. PMID:25136700

  2. Image inpainting methods evaluation and improvement.

    PubMed

    Vreja, Raluca; Brad, Remus

    2014-01-01

    With the upgrowing of digital processing of images and film archiving, the need for assisted or unsupervised restoration required the development of a series of methods and techniques. Among them, image inpainting is maybe the most impressive and useful. Based on partial derivative equations or texture synthesis, many other hybrid techniques have been proposed recently. The need for an analytical comparison, beside the visual one, urged us to perform the studies shown in the present paper. Starting with an overview of the domain, an evaluation of the five methods was performed using a common benchmark and measuring the PSNR. Conclusions regarding the performance of the investigated algorithms have been presented, categorizing them in function of the restored image structure. Based on these experiments, we have proposed an adaptation of Oliveira's and Hadhoud's algorithms, which are performing well on images with natural defects. PMID:25136700

  3. An improved algorithm of mask image dodging for aerial image

    NASA Astrophysics Data System (ADS)

    Zhang, Zuxun; Zou, Songbai; Zuo, Zhiqi

    2011-12-01

    The technology of Mask image dodging based on Fourier transform is a good algorithm in removing the uneven luminance within a single image. At present, the difference method and the ratio method are the methods in common use, but they both have their own defects .For example, the difference method can keep the brightness uniformity of the whole image, but it is deficient in local contrast; meanwhile the ratio method can work better in local contrast, but sometimes it makes the dark areas of the original image too bright. In order to remove the defects of the two methods effectively, this paper on the basis of research of the two methods proposes a balance solution. Experiments show that the scheme not only can combine the advantages of the difference method and the ratio method, but also can avoid the deficiencies of the two algorithms.

  4. 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

  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. Grid computing in image analysis

    PubMed Central

    2011-01-01

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

  7. Quantitative image analysis of celiac disease

    PubMed Central

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

    2015-01-01

    We outline the use of quantitative techniques that are currently used for analysis of celiac disease. Image processing techniques can be useful to statistically analyze the pixular data of endoscopic images that is acquired with standard or videocapsule endoscopy. It is shown how current techniques have evolved to become more useful for gastroenterologists who seek to understand celiac disease and to screen for it in suspected patients. New directions for focus in the development of methodology for diagnosis and treatment of this disease are suggested. It is evident that there are yet broad areas where there is potential to expand the use of quantitative techniques for improved analysis in suspected or known celiac disease patients. PMID:25759524

  8. Advanced machine vision inspection of x-ray images for improved productivity

    SciTech Connect

    Novini, A.

    1995-12-31

    The imaging media has been, for the most part, x-ray sensitive photographic film or film coupled to scintillation screens. Electronic means of imaging through television technology has provided a cost effective, alternative method in many applications for the past three to four decades. Typically, film provides higher resolution and higher interscene dynamic range and mechanical flexibility suitable to image complex shape objects. However, this is offset by a labor intensive task of x-ray photography and processing which eliminate the ability to image in real time. The electronic means are typically achieved through an x-ray source, x-ray to visible light converter, and a television (TV) camera. The images can be displayed on a TV monitor for operator viewing or go to a computer system for capture, image processing, and automatic analysis. Although the present state of the art for electronic x-ray imaging does not quite produce the quality possible through film, it provides a level of flexibility and overall improved productivity not achievable through film. Further, electronic imaging means are improving in image quality as time goes on, and it is expected they will match or surpass film in the next decade. For many industrial applications, the present state of the art in electronic imaging provides more than adequate results. This type of imaging also allows for automatic analysis when practical. The first step in the automatic analysis chain is to obtain the best possible image. This requires an in-depth understanding of the x-ray imaging physics and techniques by the system designer. As previously mentioned, these images may go through some enhancement steps to further improve the detectability of defects. Almost always, image spatial resolution of 512 {times} 512 or greater is used with gray level information content of 8 bits (256 gray levels) or more for preservation of image quality. There are many methods available for analyzing the images.

  9. A linear mixture analysis-based compression for hyperspectral image analysis

    SciTech Connect

    C. I. Chang; I. W. Ginsberg

    2000-06-30

    In this paper, the authors present a fully constrained least squares linear spectral mixture analysis-based compression technique for hyperspectral image analysis, particularly, target detection and classification. Unlike most compression techniques that directly deal with image gray levels, the proposed compression approach generates the abundance fractional images of potential targets present in an image scene and then encodes these fractional images so as to achieve data compression. Since the vital information used for image analysis is generally preserved and retained in the abundance fractional images, the loss of information may have very little impact on image analysis. In some occasions, it even improves analysis performance. Airborne visible infrared imaging spectrometer (AVIRIS) data experiments demonstrate that it can effectively detect and classify targets while achieving very high compression ratios.

  10. Improving quantitative neutron radiography through image restoration

    NASA Astrophysics Data System (ADS)

    Hussey, D. S.; Coakley, K. J.; Baltic, E.; Jacobson, D. L.

    2013-11-01

    Commonly in neutron image experiments, the interpretation of the point spread function (PSF) is limited to describing the achievable spatial resolution in an image. In this article it is shown that for various PSF models, the resulting blurring due to the PSF affects the quantification of the neutron transmission of an object and that the effect is separate from the scattered neutron field from the sample. The effect is observed in several neutron imaging detector configurations using different neutron scintillators and light sensors. In the context of estimation of optical densities with an algorithm that assumes a parallel beam, the effect of blurring fractionates the neutron signal spatially and introduces an effective background that scales with the area of the detector illuminated by neutrons. Examples are provided that demonstrate that the illuminated field of view can alter the observed neutron transmission for nearly purely absorbing objects. It is found that by accurately modeling the PSF, image restoration methods can yield more accurate estimates of the neutron attenuation by an object.

  11. Technique for improving solid state mosaic images

    NASA Technical Reports Server (NTRS)

    Saboe, J. M.

    1969-01-01

    Method identifies and corrects mosaic image faults in solid state visual displays and opto-electronic presentation systems. Composite video signals containing faults due to defective sensing elements are corrected by a memory unit that contains the stored fault pattern and supplies the appropriate fault word to the blanking circuit.

  12. Scanning probe image wizard: A toolbox for automated scanning probe microscopy data analysis

    NASA Astrophysics Data System (ADS)

    Stirling, Julian; Woolley, Richard A. J.; Moriarty, Philip

    2013-11-01

    We describe SPIW (scanning probe image wizard), a new image processing toolbox for SPM (scanning probe microscope) images. SPIW can be used to automate many aspects of SPM data analysis, even for images with surface contamination and step edges present. Specialised routines are available for images with atomic or molecular resolution to improve image visualisation and generate statistical data on surface structure.

  13. Image enhancement algorithm based on improved lateral inhibition network

    NASA Astrophysics Data System (ADS)

    Yun, Haijiao; Wu, Zhiyong; Wang, Guanjun; Tong, Gang; Yang, Hua

    2016-05-01

    There is often substantial noise and blurred details in the images captured by cameras. To solve this problem, we propose a novel image enhancement algorithm combined with an improved lateral inhibition network. Firstly, we built a mathematical model of a lateral inhibition network in conjunction with biological visual perception; this model helped to realize enhanced contrast and improved edge definition in images. Secondly, we proposed that the adaptive lateral inhibition coefficient adhere to an exponential distribution thus making the model more flexible and more universal. Finally, we added median filtering and a compensation measure factor to build the framework with high pass filtering functionality thus eliminating image noise and improving edge contrast, addressing problems with blurred image edges. Our experimental results show that our algorithm is able to eliminate noise and the blurring phenomena, and enhance the details of visible and infrared images.

  14. Improved Rotating Kernel Transformation Based Contourlet Domain Image Denoising Framework

    PubMed Central

    Guo, Qing; Dong, Fangmin; Ren, Xuhong; Feng, Shiyu; Gao, Bruce Zhi

    2016-01-01

    A contourlet domain image denoising framework based on a novel Improved Rotating Kernel Transformation is proposed, where the difference of subbands in contourlet domain is taken into account. In detail: (1). A novel Improved Rotating Kernel Transformation (IRKT) is proposed to calculate the direction statistic of the image; The validity of the IRKT is verified by the corresponding extracted edge information comparing with the state-of-the-art edge detection algorithm. (2). The direction statistic represents the difference between subbands and is introduced to the threshold function based contourlet domain denoising approaches in the form of weights to get the novel framework. The proposed framework is utilized to improve the contourlet soft-thresholding (CTSoft) and contourlet bivariate-thresholding (CTB) algorithms. The denoising results on the conventional testing images and the Optical Coherence Tomography (OCT) medical images show that the proposed methods improve the existing contourlet based thresholding denoising algorithm, especially for the medical images. PMID:27148597

  15. Improved bat algorithm applied to multilevel image thresholding.

    PubMed

    Alihodzic, Adis; Tuba, Milan

    2014-01-01

    Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733

  16. Improved Bat Algorithm Applied to Multilevel Image Thresholding

    PubMed Central

    2014-01-01

    Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable problems. In this paper, we adjusted one of the latest swarm intelligence algorithms, the bat algorithm, for the multilevel image thresholding problem. The results of testing on standard benchmark images show that the bat algorithm is comparable with other state-of-the-art algorithms. We improved standard bat algorithm, where our modifications add some elements from the differential evolution and from the artificial bee colony algorithm. Our new proposed improved bat algorithm proved to be better than five other state-of-the-art algorithms, improving quality of results in all cases and significantly improving convergence speed. PMID:25165733

  17. Breast tomosynthesis imaging configuration analysis.

    PubMed

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

    2013-01-01

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

  18. Study on the improvement of overall optical image quality via digital image processing

    NASA Astrophysics Data System (ADS)

    Tsai, Cheng-Mu; Fang, Yi Chin; Lin, Yu Chin

    2008-12-01

    This paper studies the effects of improving overall optical image quality via Digital Image Processing (DIP) and compares the promoted optical image with the non-processed optical image. Seen from the optical system, the improvement of image quality has a great influence on chromatic aberration and monochromatic aberration. However, overall image capture systems-such as cellphones and digital cameras-include not only the basic optical system but also many other factors, such as the electronic circuit system, transducer system, and so forth, whose quality can directly affect the image quality of the whole picture. Therefore, in this thesis Digital Image Processing technology is utilized to improve the overall image. It is shown via experiments that system modulation transfer function (MTF) based on the proposed DIP technology and applied to a comparatively bad optical system can be comparable to, even possibly superior to, the system MTF derived from a good optical system.

  19. 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.

  20. Improved image quality for x-ray CT imaging of gel dosimeters

    SciTech Connect

    Kakakhel, M. B.; Kairn, T.; Kenny, J.; Trapp, J. V.

    2011-09-15

    Purpose: This study provides a simple method for improving precision of x-ray computed tomography (CT) scans of irradiated polymer gel dosimetry. The noise affecting CT scans of irradiated gels has been an impediment to the use of clinical CT scanners for gel dosimetry studies. Methods: In this study, it is shown that multiple scans of a single PAGAT gel dosimeter can be used to extrapolate a ''zero-scan'' image which displays a similar level of precision to an image obtained by averaging multiple CT images, without the compromised dose measurement resulting from the exposure of the gel to radiation from the CT scanner. Results: When extrapolating the zero-scan image, it is shown that exponential and simple linear fits to the relationship between Hounsfield unit and scan number, for each pixel in the image, provide an accurate indication of gel density. Conclusions: It is expected that this work will be utilized in the analysis of three-dimensional gel volumes irradiated using complex radiotherapy treatments.

  1. Improved Calibration Shows Images True Colors

    NASA Technical Reports Server (NTRS)

    2015-01-01

    Innovative Imaging and Research, located at Stennis Space Center, used a single SBIR contract with the center to build a large-scale integrating sphere, capable of calibrating a whole array of cameras simultaneously, at a fraction of the usual cost for such a device. Through the use of LEDs, the company also made the sphere far more efficient than existing products and able to mimic sunlight.

  2. Imaging system design for improved information capacity

    NASA Technical Reports Server (NTRS)

    Fales, C. L.; Huck, F. O.; Samms, R. W.

    1984-01-01

    Shannon's theory of information for communication channels is used to assess the performance of line-scan and sensor-array imaging systems and to optimize the design trade-offs involving sensitivity, spatial response, and sampling intervals. Formulations and computational evaluations account for spatial responses typical of line-scan and sensor-array mechanisms, lens diffraction and transmittance shading, defocus blur, and square and hexagonal sampling lattices.

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

    SciTech Connect

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

    1999-08-20

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

  4. Imaging quality full chip verification for yield improvement

    NASA Astrophysics Data System (ADS)

    Yang, Qing; Zhou, CongShu; Quek, ShyueFong; Lu, Mark; Foong, YeeMei; Qiu, JianHong; Pandey, Taksh; Dover, Russell

    2013-04-01

    Basic image intensity parameters, like maximum and minimum intensity values (Imin and Imax), image logarithm slope (ILS), normalized image logarithm slope (NILS) and mask error enhancement factor (MEEF) , are well known as indexes of photolithography imaging quality. For full chip verification, hotspot detection is typically based on threshold values for line pinching or bridging. For image intensity parameters it is generally harder to quantify an absolute value to define where the process limit will occur, and at which process stage; lithography, etch or post- CMP. However it is easy to conclude that hot spots captured by image intensity parameters are more susceptible to process variation and very likely to impact yield. In addition these image intensity hot spots can be missed by using resist model verification because the resist model normally is calibrated by the wafer data on a single resist plane and is an empirical model which is trying to fit the resist critical dimension by some mathematic algorithm with combining optical calculation. Also at resolution enhancement technology (RET) development stage, full chip imaging quality check is also a method to qualify RET solution, like Optical Proximity Correct (OPC) performance. To add full chip verification using image intensity parameters is also not as costly as adding one more resist model simulation. From a foundry yield improvement and cost saving perspective, it is valuable to quantify the imaging quality to find design hot spots to correctly define the inline process control margin. This paper studies the correlation between image intensity parameters and process weakness or catastrophic hard failures at different process stages. It also demonstrated how OPC solution can improve full chip image intensity parameters. Rigorous 3D resist profile simulation across the full height of the resist stack was also performed to identify a correlation to the image intensity parameter. A methodology of post-OPC full

  5. Neural network ultrasound image analysis

    NASA Astrophysics Data System (ADS)

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

    1993-09-01

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

  6. Contrast and harmonic imaging improves accuracy and efficiency of novice readers for dobutamine stress echocardiography

    NASA Technical Reports Server (NTRS)

    Vlassak, Irmien; Rubin, David N.; Odabashian, Jill A.; Garcia, Mario J.; King, Lisa M.; Lin, Steve S.; Drinko, Jeanne K.; Morehead, Annitta J.; Prior, David L.; Asher, Craig R.; Klein, Allan L.; Thomas, James D.

    2002-01-01

    BACKGROUND: Newer contrast agents as well as tissue harmonic imaging enhance left ventricular (LV) endocardial border delineation, and therefore, improve LV wall-motion analysis. Interpretation of dobutamine stress echocardiography is observer-dependent and requires experience. This study was performed to evaluate whether these new imaging modalities would improve endocardial visualization and enhance accuracy and efficiency of the inexperienced reader interpreting dobutamine stress echocardiography. METHODS AND RESULTS: Twenty-nine consecutive patients with known or suspected coronary artery disease underwent dobutamine stress echocardiography. Both fundamental (2.5 MHZ) and harmonic (1.7 and 3.5 MHZ) mode images were obtained in four standard views at rest and at peak stress during a standard dobutamine infusion stress protocol. Following the noncontrast images, Optison was administered intravenously in bolus (0.5-3.0 ml), and fundamental and harmonic images were obtained. The dobutamine echocardiography studies were reviewed by one experienced and one inexperienced echocardiographer. LV segments were graded for image quality and function. Time for interpretation also was recorded. Contrast with harmonic imaging improved the diagnostic concordance of the novice reader to the expert reader by 7.1%, 7.5%, and 12.6% (P < 0.001) as compared with harmonic imaging, fundamental imaging, and fundamental imaging with contrast, respectively. For the novice reader, reading time was reduced by 47%, 55%, and 58% (P < 0.005) as compared with the time needed for fundamental, fundamental contrast, and harmonic modes, respectively. With harmonic imaging, the image quality score was 4.6% higher (P < 0.001) than for fundamental imaging. Image quality scores were not significantly different for noncontrast and contrast images. CONCLUSION: Harmonic imaging with contrast significantly improves the accuracy and efficiency of the novice dobutamine stress echocardiography reader. The use

  7. Failure Analysis for Improved Reliability

    NASA Technical Reports Server (NTRS)

    Sood, Bhanu

    2016-01-01

    Outline: Section 1 - What is reliability and root cause? Section 2 - Overview of failure mechanisms. Section 3 - Failure analysis techniques (1. Non destructive analysis techniques, 2. Destructive Analysis, 3. Materials Characterization). Section 4 - Summary and Closure

  8. Improved vector quantization scheme for grayscale image compression

    NASA Astrophysics Data System (ADS)

    Hu, Y.-C.; Chen, W.-L.; Lo, C.-C.; Chuang, J.-C.

    2012-06-01

    This paper proposes an improved image coding scheme based on vector quantization. It is well known that the image quality of a VQ-compressed image is poor when a small-sized codebook is used. In order to solve this problem, the mean value of the image block is taken as an alternative block encoding rule to improve the image quality in the proposed scheme. To cut down the storage cost of compressed codes, a two-stage lossless coding approach including the linear prediction technique and the Huffman coding technique is employed in the proposed scheme. The results show that the proposed scheme achieves better image qualities than vector quantization while keeping low bit rates.

  9. Improving the Quality of Imaging in the Emergency Department.

    PubMed

    Blackmore, C Craig; Castro, Alexandra

    2015-12-01

    Imaging is critical for the care of emergency department (ED) patients. However, much of the imaging performed for acute care today is overutilization, creating substantial cost without significant benefit. Further, the value of imaging is not easily defined, as imaging only affects outcomes indirectly, through interaction with treatment. Improving the quality, including appropriateness, of emergency imaging requires understanding of how imaging contributes to patient care. The six-tier efficacy hierarchy of Fryback and Thornbury enables understanding of the value of imaging on multiple levels, ranging from technical efficacy to medical decision-making and higher-level patient and societal outcomes. The imaging efficacy hierarchy also allows definition of imaging quality through the Institute of Medicine (IOM)'s quality domains of safety, effectiveness, patient-centeredness, timeliness, efficiency, and equitability and provides a foundation for quality improvement. In this article, the authors elucidate the Fryback and Thornbury framework to define the value of imaging in the ED and to relate emergency imaging to the IOM quality domains. PMID:26568040

  10. Improved Imaging With Laser-Induced Eddy Currents

    NASA Technical Reports Server (NTRS)

    Chern, Engmin J.

    1993-01-01

    System tests specimen of material nondestructively by laser-induced eddy-current imaging improved by changing method of processing of eddy-current signal. Changes in impedance of eddy-current coil measured in absolute instead of relative units.

  11. Improved biliary detection and diagnosis through intelligent machine analysis.

    PubMed

    Logeswaran, Rajasvaran

    2012-09-01

    This paper reports on work undertaken to improve automated detection of bile ducts in magnetic resonance cholangiopancreatography (MRCP) images, with the objective of conducting preliminary classification of the images for diagnosis. The proposed I-BDeDIMA (Improved Biliary Detection and Diagnosis through Intelligent Machine Analysis) scheme is a multi-stage framework consisting of successive phases of image normalization, denoising, structure identification, object labeling, feature selection and disease classification. A combination of multiresolution wavelet, dynamic intensity thresholding, segment-based region growing, region elimination, statistical analysis and neural networks, is used in this framework to achieve good structure detection and preliminary diagnosis. Tests conducted on over 200 clinical images with known diagnosis have shown promising results of over 90% accuracy. The scheme outperforms related work in the literature, making it a viable framework for computer-aided diagnosis of biliary diseases. PMID:21194781

  12. High resolution PET breast imager with improved detection efficiency

    DOEpatents

    Majewski, Stanislaw

    2010-06-08

    A highly efficient PET breast imager for detecting lesions in the entire breast including those located close to the patient's chest wall. The breast imager includes a ring of imaging modules surrounding the imaged breast. Each imaging module includes a slant imaging light guide inserted between a gamma radiation sensor and a photodetector. The slant light guide permits the gamma radiation sensors to be placed in close proximity to the skin of the chest wall thereby extending the sensitive region of the imager to the base of the breast. Several types of photodetectors are proposed for use in the detector modules, with compact silicon photomultipliers as the preferred choice, due to its high compactness. The geometry of the detector heads and the arrangement of the detector ring significantly reduce dead regions thereby improving detection efficiency for lesions located close to the chest wall.

  13. Photoacoustic imaging with rotational compounding for improved signal detection

    NASA Astrophysics Data System (ADS)

    Forbrich, A.; Heinmiller, A.; Jose, J.; Needles, A.; Hirson, D.

    2015-03-01

    Photoacoustic microscopy with linear array transducers enables fast two-dimensional, cross-sectional photoacoustic imaging. Unfortunately, most ultrasound transducers are only sensitive to a very narrow angular acceptance range and preferentially detect signals along the main axis of the transducer. This often limits photoacoustic microscopy from detecting blood vessels which can extend in any direction. Rotational compounded photoacoustic imaging is introduced to overcome the angular-dependency of detecting acoustic signals with linear array transducers. An integrate system is designed to control the image acquisition using a linear array transducer, a motorized rotational stage, and a motorized lateral stage. Images acquired at multiple angular positions are combined to form a rotational compounded image. We found that the signal-to-noise ratio improved, while the sidelobe and reverberation artifacts were substantially reduced. Furthermore, the rotational compounded images of excised kidneys and hindlimb tumors of mice showed more structural information compared with any single image collected.

  14. Instrumentation for Improvement of Gas Imaging Systems

    NASA Astrophysics Data System (ADS)

    Happer, William

    2002-08-01

    Funds from the AFOSR:DURIP grant F49620-01-1-0254 have been used to purchase three major pieces of equipment: (1) a nuclear magnetic resonance-spectrometer; system for studies of the basic-physics of hyperpolarized.Xe-129 and He-3 gases; (2) a 9.4 T superconducting magnet with a 3 inch room temperature bore; (3) a Verdi diode-pumped Nd:YAG laser to replace the very expensive argon ion laser we have traditionally used for pumping our Ti:sapphire tunable laser. This new equipment has greatly improved the research productivity of our laboratory.

  15. Improved Compression of Wavelet-Transformed Images

    NASA Technical Reports Server (NTRS)

    Kiely, Aaron; Klimesh, Matthew

    2005-01-01

    A recently developed data-compression method is an adaptive technique for coding quantized wavelet-transformed data, nominally as part of a complete image-data compressor. Unlike some other approaches, this method admits a simple implementation and does not rely on the use of large code tables. A common data compression approach, particularly for images, is to perform a wavelet transform on the input data, and then losslessly compress a quantized version of the wavelet-transformed data. Under this compression approach, it is common for the quantized data to include long sequences, or runs, of zeros. The new coding method uses prefixfree codes for the nonnegative integers as part of an adaptive algorithm for compressing the quantized wavelet-transformed data by run-length coding. In the form of run-length coding used here, the data sequence to be encoded is parsed into strings consisting of some number (possibly 0) of zeros, followed by a nonzero value. The nonzero value and the length of the run of zeros are encoded. For a data stream that contains a sufficiently high frequency of zeros, this method is known to be more effective than using a single variable length code to encode each symbol. The specific prefix-free codes used are from two classes of variable-length codes: a class known as Golomb codes, and a class known as exponential-Golomb codes. The codes within each class are indexed by a single integer parameter. The present method uses exponential-Golomb codes for the lengths of the runs of zeros, and Golomb codes for the nonzero values. The code parameters within each code class are determined adaptively on the fly as compression proceeds, on the basis of statistics from previously encoded values. In particular, a simple adaptive method has been devised to select the parameter identifying the particular exponential-Golomb code to use. The method tracks the average number of bits used to encode recent runlengths, and takes the difference between this average

  16. Image analysis of Renaissance copperplate prints

    NASA Astrophysics Data System (ADS)

    Hedges, S. Blair

    2008-02-01

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

  17. Image segmentation using an improved differential algorithm

    NASA Astrophysics Data System (ADS)

    Gao, Hao; Shi, Yujiao; Wu, Dongmei

    2014-10-01

    Among all the existing segmentation techniques, the thresholding technique is one of the most popular due to its simplicity, robustness, and accuracy (e.g. the maximum entropy method, Otsu's method, and K-means clustering). However, the computation time of these algorithms grows exponentially with the number of thresholds due to their exhaustive searching strategy. As a population-based optimization algorithm, differential algorithm (DE) uses a population of potential solutions and decision-making processes. It has shown considerable success in solving complex optimization problems within a reasonable time limit. Thus, applying this method into segmentation algorithm should be a good choice during to its fast computational ability. In this paper, we first propose a new differential algorithm with a balance strategy, which seeks a balance between the exploration of new regions and the exploitation of the already sampled regions. Then, we apply the new DE into the traditional Otsu's method to shorten the computation time. Experimental results of the new algorithm on a variety of images show that, compared with the EA-based thresholding methods, the proposed DE algorithm gets more effective and efficient results. It also shortens the computation time of the traditional Otsu method.

  18. Improved colorization for night vision system based on image splitting

    NASA Astrophysics Data System (ADS)

    Ali, E.; Kozaitis, S. P.

    2015-03-01

    The success of a color night navigation system often depends on the accuracy of the colors in the resulting image. Often, small regions can incorrectly adopt the color of large regions simply due to size of the regions. We presented a method to improve the color accuracy of a night navigation system by initially splitting a fused image into two distinct sections before colorization. We split a fused image into two sections, generally road and sky regions, before colorization and processed them separately to obtain improved color accuracy of each region. Using this approach, small regions were colored correctly when compared to not separating regions.

  19. Improvements for Image Compression Using Adaptive Principal Component Extraction (APEX)

    NASA Technical Reports Server (NTRS)

    Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.

    1997-01-01

    The issues of image compression and pattern classification have been a primary focus of researchers among a variety of fields including signal and image processing, pattern recognition, data classification, etc. These issues depend on finding an efficient representation of the source data. In this paper we collate our earlier results where we introduced the application of the. Hilbe.rt scan to a principal component algorithm (PCA) with Adaptive Principal Component Extraction (APEX) neural network model. We apply these technique to medical imaging, particularly image representation and compression. We apply the Hilbert scan to the APEX algorithm to improve results

  20. An improved NAS-RIF algorithm for blind image restoration

    NASA Astrophysics Data System (ADS)

    Liu, Ning; Jiang, Yanbin; Lou, Shuntian

    2007-01-01

    Image restoration is widely applied in many areas, but when operating on images with different scales for the representation of pixel intensity levels or low SNR, the traditional restoration algorithm lacks validity and induces noise amplification, ringing artifacts and poor convergent ability. In this paper, an improved NAS-RIF algorithm is proposed to overcome the shortcomings of the traditional algorithm. The improved algorithm proposes a new cost function which adds a space-adaptive regularization term and a disunity gain of the adaptive filter. In determining the support region, a pre-segmentation is used to form it close to the object in the image. Compared with the traditional algorithm, simulations show that the improved algorithm behaves better convergence, noise resistance and provides a better estimate of original image.

  1. 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.

  2. Retinex Preprocessing for Improved Multi-Spectral Image Classification

    NASA Technical Reports Server (NTRS)

    Thompson, B.; Rahman, Z.; Park, S.

    2000-01-01

    The goal of multi-image classification is to identify and label "similar regions" within a scene. The ability to correctly classify a remotely sensed multi-image of a scene is affected by the ability of the classification process to adequately compensate for the effects of atmospheric variations and sensor anomalies. Better classification may be obtained if the multi-image is preprocessed before classification, so as to reduce the adverse effects of image formation. In this paper, we discuss the overall impact on multi-spectral image classification when the retinex image enhancement algorithm is used to preprocess multi-spectral images. The retinex is a multi-purpose image enhancement algorithm that performs dynamic range compression, reduces the dependence on lighting conditions, and generally enhances apparent spatial resolution. The retinex has been successfully applied to the enhancement of many different types of grayscale and color images. We show in this paper that retinex preprocessing improves the spatial structure of multi-spectral images and thus provides better within-class variations than would otherwise be obtained without the preprocessing. For a series of multi-spectral images obtained with diffuse and direct lighting, we show that without retinex preprocessing the class spectral signatures vary substantially with the lighting conditions. Whereas multi-dimensional clustering without preprocessing produced one-class homogeneous regions, the classification on the preprocessed images produced multi-class non-homogeneous regions. This lack of homogeneity is explained by the interaction between different agronomic treatments applied to the regions: the preprocessed images are closer to ground truth. The principle advantage that the retinex offers is that for different lighting conditions classifications derived from the retinex preprocessed images look remarkably "similar", and thus more consistent, whereas classifications derived from the original

  3. 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.

  4. 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.

  5. 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.

  6. An improved optical identity authentication system with significant output images

    NASA Astrophysics Data System (ADS)

    Yuan, Sheng; Liu, Ming-tang; Yao, Shu-xia; Xin, Yan-hui

    2012-06-01

    An improved method for optical identity authentication system with significant output images is proposed. In this method, a predefined image is digitally encoded into two phase-masks relating to a fixed phase-mask, and this fixed phase-mask acts as a lock to the system. When the two phase-masks, serving as the key, are presented to the system, the predefined image is generated at the output. In addition to simple verification, our method is capable of identifying the type of input phase-mask, and the duties of identity verification and recognition are separated and, respectively, assigned to the amplitude and phase of the output image. Numerical simulation results show that our proposed method is feasible and the output image with better image quality can be obtained.

  7. Resolution and quantitative accuracy improvements in ultrasound transmission imaging

    NASA Astrophysics Data System (ADS)

    Chenevert, T. L.

    The type of ultrasound transmission imaging, referred to as ultrasonic computed tomography (UCT), reconstructs distributions of tissue speed of sound and sound attenuation properties from measurements of acoustic pulse time of flight (TCF) and energy received through tissue. Although clinical studies with experimental UCT scanners have demonstrated UCT is sensitive to certain tissue pathologies not easily detected with conventional ultrasound imaging, they have also shown UCT to suffer from artifacts due to physical differences between the acoustic beam and its ray model implicit in image reconstruction algorithms. Artifacts are expressed as large quantitative errors in attenuation images, and poor spatial resolution and size distortion (exaggerated size of high speed of sound regions) in speed of sound images. Methods are introduced and investigated which alleviate these problems in UCT imaging by providing improved measurements of pulse TCF and energy.

  8. Automatic processing, analysis, and recognition of images

    NASA Astrophysics Data System (ADS)

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

    2004-11-01

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

  9. Restoration Of MEX SRC Images For Improved Topography: A New Image Product

    NASA Astrophysics Data System (ADS)

    Duxbury, T. C.

    2012-12-01

    Surface topography is an important constraint when investigating the evolution of solar system bodies. Topography is typically obtained from stereo photogrammetric or photometric (shape from shading) analyses of overlapping / stereo images and from laser / radar altimetry data. The ESA Mars Express Mission [1] carries a Super Resolution Channel (SRC) as part of the High Resolution Stereo Camera (HRSC) [2]. The SRC can build up overlapping / stereo coverage of Mars, Phobos and Deimos by viewing the surfaces from different orbits. The derivation of high precision topography data from the SRC raw images is degraded because the camera is out of focus. The point spread function (PSF) is multi-peaked, covering tens of pixels. After registering and co-adding hundreds of star images, an accurate SRC PSF was reconstructed and is being used to restore the SRC images to near blur free quality. The restored images offer a factor of about 3 in improved geometric accuracy as well as identifying the smallest of features to significantly improve the stereo photogrammetric accuracy in producing digital elevation models. The difference between blurred and restored images provides a new derived image product that can provide improved feature recognition to increase spatial resolution and topographic accuracy of derived elevation models. Acknowledgements: This research was funded by the NASA Mars Express Participating Scientist Program. [1] Chicarro, et al., ESA SP 1291(2009) [2] Neukum, et al., ESA SP 1291 (2009). A raw SRC image (h4235.003) of a Martian crater within Gale crater (the MSL landing site) is shown in the upper left and the restored image is shown in the lower left. A raw image (h0715.004) of Phobos is shown in the upper right and the difference between the raw and restored images, a new derived image data product, is shown in the lower right. The lower images, resulting from an image restoration process, significantly improve feature recognition for improved derived

  10. Automated digital image analysis of islet cell mass using Nikon's inverted eclipse Ti microscope and software to improve engraftment may help to advance the therapeutic efficacy and accessibility of islet transplantation across centers.

    PubMed

    Gmyr, Valery; Bonner, Caroline; Lukowiak, Bruno; Pawlowski, Valerie; Dellaleau, Nathalie; Belaich, Sandrine; Aluka, Isanga; Moermann, Ericka; Thevenet, Julien; Ezzouaoui, Rimed; Queniat, Gurvan; Pattou, Francois; Kerr-Conte, Julie

    2015-01-01

    Reliable assessment of islet viability, mass, and purity must be met prior to transplanting an islet preparation into patients with type 1 diabetes. The standard method for quantifying human islet preparations is by direct microscopic analysis of dithizone-stained islet samples, but this technique may be susceptible to inter-/intraobserver variability, which may induce false positive/negative islet counts. Here we describe a simple, reliable, automated digital image analysis (ADIA) technique for accurately quantifying islets into total islet number, islet equivalent number (IEQ), and islet purity before islet transplantation. Islets were isolated and purified from n = 42 human pancreata according to the automated method of Ricordi et al. For each preparation, three islet samples were stained with dithizone and expressed as IEQ number. Islets were analyzed manually by microscopy or automatically quantified using Nikon's inverted Eclipse Ti microscope with built-in NIS-Elements Advanced Research (AR) software. The AIDA method significantly enhanced the number of islet preparations eligible for engraftment compared to the standard manual method (p < 0.001). Comparisons of individual methods showed good correlations between mean values of IEQ number (r(2) = 0.91) and total islet number (r(2) = 0.88) and thus increased to r(2) = 0.93 when islet surface area was estimated comparatively with IEQ number. The ADIA method showed very high intraobserver reproducibility compared to the standard manual method (p < 0.001). However, islet purity was routinely estimated as significantly higher with the manual method versus the ADIA method (p < 0.001). The ADIA method also detected small islets between 10 and 50 µm in size. Automated digital image analysis utilizing the Nikon Instruments software is an unbiased, simple, and reliable teaching tool to comprehensively assess the individual size of each islet cell preparation prior to transplantation. Implementation of this

  11. Improvements in interpretation of posterior capsular opacification (PCO) images

    NASA Astrophysics Data System (ADS)

    Paplinski, Andrew P.; Boyce, James F.; Barman, Sarah A.

    2000-06-01

    We present further improvements to the methods of interpretation of the Posterior Capsular Opacification (PCO) images. These retro-illumination images of the back surface of the implanted lens are used to monitor the state of patient's vision after cataract operation. A common post-surgical complication is opacification of the posterior eye capsule caused by the growth of epithelial cells across the back surface of the capsule. Interpretation of the PCO images is based on their segmentation into transparent image areas and opaque areas, which are affected by the growth of epithelial cells and can be characterized by the increase in the image local variance. This assumption is valid in majority of cases. However, for different materials used for the implanted lenses it sometimes happens that the epithelial cells grow in a way characterized by low variance. In such a case segmentation gives a relatively big error. We describe an application of an anisotropic diffusion equation in a non-linear pre-processing of PCO images. The algorithm preserves the high-variance areas of PCO images and performs a low-pass filtering of small low- variance features. The algorithm maintains a mean value of the variance and guarantees existence of a stable solution and improves segmentation of the PCO images.

  12. Improving face image extraction by using deep learning technique

    NASA Astrophysics Data System (ADS)

    Xue, Zhiyun; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.

    2016-03-01

    The National Library of Medicine (NLM) has made a collection of over a 1.2 million research articles containing 3.2 million figure images searchable using the Open-iSM multimodal (text+image) search engine. Many images are visible light photographs, some of which are images containing faces ("face images"). Some of these face images are acquired in unconstrained settings, while others are studio photos. To extract the face regions in the images, we first applied one of the most widely-used face detectors, a pre-trained Viola-Jones detector implemented in Matlab and OpenCV. The Viola-Jones detector was trained for unconstrained face image detection, but the results for the NLM database included many false positives, which resulted in a very low precision. To improve this performance, we applied a deep learning technique, which reduced the number of false positives and as a result, the detection precision was improved significantly. (For example, the classification accuracy for identifying whether the face regions output by this Viola- Jones detector are true positives or not in a test set is about 96%.) By combining these two techniques (Viola-Jones and deep learning) we were able to increase the system precision considerably, while avoiding the need to manually construct a large training set by manual delineation of the face regions.

  13. 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.

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

    PubMed

    Niessen, Wiro J

    2016-10-01

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

  15. Flattening filter removal for improved image quality of megavoltage fluoroscopy

    SciTech Connect

    Christensen, James D.; Kirichenko, Alexander; Gayou, Olivier

    2013-08-15

    Purpose: Removal of the linear accelerator (linac) flattening filter enables a high rate of dose deposition with reduced treatment time. When used for megavoltage imaging, an unflat beam has reduced primary beam scatter resulting in sharper images. In fluoroscopic imaging mode, the unflat beam has higher photon count per image frame yielding higher contrast-to-noise ratio. The authors’ goal was to quantify the effects of an unflat beam on the image quality of megavoltage portal and fluoroscopic images.Methods: 6 MV projection images were acquired in fluoroscopic and portal modes using an electronic flat-panel imager. The effects of the flattening filter on the relative modulation transfer function (MTF) and contrast-to-noise ratio were quantified using the QC3 phantom. The impact of FF removal on the contrast-to-noise ratio of gold fiducial markers also was studied under various scatter conditions.Results: The unflat beam had improved contrast resolution, up to 40% increase in MTF contrast at the highest frequency measured (0.75 line pairs/mm). The contrast-to-noise ratio was increased as expected from the increased photon flux. The visualization of fiducial markers was markedly better using the unflat beam under all scatter conditions, enabling visualization of thin gold fiducial markers, the thinnest of which was not visible using the unflat beam.Conclusions: The removal of the flattening filter from a clinical linac leads to quantifiable improvements in the image quality of megavoltage projection images. These gains enable observers to more easily visualize thin fiducial markers and track their motion on fluoroscopic images.

  16. Image registration with uncertainty analysis

    DOEpatents

    Simonson, Katherine M.

    2011-03-22

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

  17. Image-plane processing for improved computer vision

    NASA Technical Reports Server (NTRS)

    Huck, F. O.; Fales, C. L.; Park, S. K.; Samms, R. W.

    1984-01-01

    The proper combination of optical design with image plane processing, as in the mechanism of human vision, which allows to improve the performance of sensor array imaging systems for edge detection and location was examined. Two dimensional bandpass filtering during image formation, optimizes edge enhancement and minimizes data transmission. It permits control of the spatial imaging system response to tradeoff edge enhancement for sensitivity at low light levels. It is shown that most of the information, up to about 94%, is contained in the signal intensity transitions from which the location of edges is determined for raw primal sketches. Shading the lens transmittance to increase depth of field and using a hexagonal instead of square sensor array lattice to decrease sensitivity to edge orientation improves edge information about 10%.

  18. An improved dehazing algorithm of aerial high-definition image

    NASA Astrophysics Data System (ADS)

    Jiang, Wentao; Ji, Ming; Huang, Xiying; Wang, Chao; Yang, Yizhou; Li, Tao; Wang, Jiaoying; Zhang, Ying

    2016-01-01

    For unmanned aerial vehicle(UAV) images, the sensor can not get high quality images due to fog and haze weather. To solve this problem, An improved dehazing algorithm of aerial high-definition image is proposed. Based on the model of dark channel prior, the new algorithm firstly extracts the edges from crude estimated transmission map and expands the extracted edges. Then according to the expended edges, the algorithm sets a threshold value to divide the crude estimated transmission map into different areas and makes different guided filter on the different areas compute the optimized transmission map. The experimental results demonstrate that the performance of the proposed algorithm is substantially the same as the one based on dark channel prior and guided filter. The average computation time of the new algorithm is around 40% of the one as well as the detection ability of UAV image is improved effectively in fog and haze weather.

  19. Digital Image Analysis for DETCHIP(®) Code Determination.

    PubMed

    Lyon, Marcus; Wilson, Mark V; Rouhier, Kerry A; Symonsbergen, David J; Bastola, Kiran; Thapa, Ishwor; Holmes, Andrea E; Sikich, Sharmin M; Jackson, Abby

    2012-08-01

    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

  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. Cascaded diffractive optical elements for improved multiplane image reconstruction.

    PubMed

    Gülses, A Alkan; Jenkins, B Keith

    2013-05-20

    Computer-generated phase-only diffractive optical elements in a cascaded setup are designed by one deterministic and one stochastic algorithm for multiplane image formation. It is hypothesized that increasing the number of elements as wavefront modulators in the longitudinal dimension would enlarge the available solution space, thus enabling enhanced image reconstruction. Numerical results show that increasing the number of holograms improves quality at the output. Design principles, computational methods, and specific conditions are discussed. PMID:23736247

  2. Millimeter-wave sensor image analysis

    NASA Technical Reports Server (NTRS)

    Wilson, William J.; Suess, Helmut

    1989-01-01

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

  3. 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.

  4. Structural anisotropy quantification improves the final superresolution image of localization microscopy

    NASA Astrophysics Data System (ADS)

    Wang, Yina; Huang, Zhen-li

    2016-07-01

    Superresolution localization microscopy initially produces a dataset of fluorophore coordinates instead of a conventional digital image. Therefore, superresolution localization microscopy requires additional data analysis to present a final superresolution image. However, methods of employing the structural information within the localization dataset to improve the data analysis performance remain poorly developed. Here, we quantify the structural information in a localization dataset using structural anisotropy, and propose to use it as a figure of merit for localization event filtering. With simulated as well as experimental data of a biological specimen, we demonstrate that exploring structural anisotropy has allowed us to obtain superresolution images with a much cleaner background.

  5. Quantitative analysis of digital microscope images.

    PubMed

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

    2013-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2003-12-01

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

  8. An improved image deconvolution approach using local constraint

    NASA Astrophysics Data System (ADS)

    Zhao, Jufeng; Feng, Huajun; Xu, Zhihai; Li, Qi

    2012-03-01

    Conventional deblurring approaches such as the Richardson-Lucy (RL) algorithm will introduce strong noise and ringing artifacts, though the point spread function (PSF) is known. Since it is difficult to estimate an accurate PSF in real imaging system, the results of those algorithms will be worse. A spatial weight matrix (SWM) is adopted as local constraint, which is incorporated into image statistical prior to improve the RL approach. Experiments show that our approach can make a good balance between preserving image details and suppressing ringing artifacts and noise.

  9. Computational methods for improving thermal imaging for consumer devices

    NASA Astrophysics Data System (ADS)

    Lynch, Colm N.; Devaney, Nicholas; Drimbarean, Alexandru

    2015-05-01

    In consumer imaging, the spatial resolution of thermal microbolometer arrays is limited by the large physical size of the individual detector elements. This also limits the number of pixels per image. If thermal sensors are to find a place in consumer imaging, as the newly released FLIR One would suggest, this resolution issue must be addressed. Our work focuses on improving the output quality of low resolution thermal cameras through computational means. The method we propose utilises sub-pixel shifts and temporal variations in the scene, using information from thermal and visible channels. Results from simulations and lab experiments are presented.

  10. A hybrid data-integration scheme for improved subsurface imaging

    NASA Astrophysics Data System (ADS)

    Moreira, L. P.; Friedel, M. J.

    2013-12-01

    A three-step modeling approach is presented for subsurface imaging with sparse and disparate data. First, seismic receiver function and surface wave dispersion data are jointly solved to estimate 1D velocity profiles at multiple locations. Second, a type of unsupervised artificial neural network is used to map the velocity and density profiles to the plane of a magnetotelluric survey. Third, the seismic and magnetotelluric data are jointly solved to improve the lateral and vertical resolution of images. The proposed approach is applied to image structural discontinuities and mineral deposit in Nevada, USA.

  11. Analysis on correlation imaging based on fractal interpolation

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  12. Improving analysis of radiochromic films

    NASA Astrophysics Data System (ADS)

    Baptista Neto, A. T.; Meira-Belo, L. C.; Faria, L. O.

    2014-02-01

    An appropriate radiochromic film should respond uniformly throughout its surface after exposure to a uniform radiation field. The evaluation of radiochromic films may be carried out, for example, by measuring color intensities in film-based digitized images. Fluctuations in color intensity may be caused by many different factors such as optical structure of the film's active layer, defects in structure of the film, scratches and external agents, such as dust. The use of high spatial resolution during film scanning should also increase microscopic uniformity. Since the average is strongly influenced by extreme values, the use of other statistical tools, for which this problem becomes inconspicuous, optimizes the application of higher spatial resolution as well as reduces standard deviations. This paper compares the calibration curves of the XR-QA2 Gafchromic® radiochromic film based on three different methods: the average of all color intensity readings, the median of these same readings and the average of readings that fall between the first and third quartiles. Results indicate that a higher spatial resolution may be adopted whenever the calibration curve is based on tools less influenced by extreme values such as those generated by the factors mentioned above.

  13. A 3D image analysis tool for SPECT imaging

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

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

  14. Improved iterative error analysis for endmember extraction from hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Sun, Lixin; Zhang, Ying; Guindon, Bert

    2008-08-01

    Automated image endmember extraction from hyperspectral imagery is a challenge and a critical step in spectral mixture analysis (SMA). Over the past years, great efforts were made and a large number of algorithms have been proposed to address this issue. Iterative error analysis (IEA) is one of the well-known existing endmember extraction methods. IEA identifies pixel spectra as a number of image endmembers by an iterative process. In each of the iterations, a fully constrained (abundance nonnegativity and abundance sum-to-one constraints) spectral unmixing based on previously identified endmembers is performed to model all image pixels. The pixel spectrum with the largest residual error is then selected as a new image endmember. This paper proposes an updated version of IEA by making improvements on three aspects of the method. First, fully constrained spectral unmixing is replaced by a weakly constrained (abundance nonnegativity and abundance sum-less-or-equal-to-one constraints) alternative. This is necessary due to the fact that only a subset of endmembers exhibit in a hyperspectral image have been extracted up to an intermediate iteration and the abundance sum-to-one constraint is invalid at the moment. Second, the search strategy for achieving an optimal set of image endmembers is changed from sequential forward selection (SFS) to sequential forward floating selection (SFFS) to reduce the so-called "nesting effect" in resultant set of endmembers. Third, a pixel spectrum is identified as a new image endmember depending on both its spectral extremity in the feature hyperspace of a dataset and its capacity to characterize other mixed pixels. This is achieved by evaluating a set of extracted endmembers using a criterion function, which is consisted of the mean and standard deviation of residual error image. Preliminary comparison between the image endmembers extracted using improved and original IEA are conducted based on an airborne visible infrared imaging

  15. Image Reconstruction Using Analysis Model Prior.

    PubMed

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

    2016-01-01

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

  16. Image Reconstruction Using Analysis Model Prior

    PubMed Central

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

    2016-01-01

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

  17. Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence.

    PubMed

    Beijbom, Oscar; Treibitz, Tali; Kline, David I; Eyal, Gal; Khen, Adi; Neal, Benjamin; Loya, Yossi; Mitchell, B Greg; Kriegman, David

    2016-01-01

    Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck. PMID:27021133

  18. Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence

    PubMed Central

    Beijbom, Oscar; Treibitz, Tali; Kline, David I.; Eyal, Gal; Khen, Adi; Neal, Benjamin; Loya, Yossi; Mitchell, B. Greg; Kriegman, David

    2016-01-01

    Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck. PMID:27021133

  19. Improving Automated Annotation of Benthic Survey Images Using Wide-band Fluorescence

    NASA Astrophysics Data System (ADS)

    Beijbom, Oscar; Treibitz, Tali; Kline, David I.; Eyal, Gal; Khen, Adi; Neal, Benjamin; Loya, Yossi; Mitchell, B. Greg; Kriegman, David

    2016-03-01

    Large-scale imaging techniques are used increasingly for ecological surveys. However, manual analysis can be prohibitively expensive, creating a bottleneck between collected images and desired data-products. This bottleneck is particularly severe for benthic surveys, where millions of images are obtained each year. Recent automated annotation methods may provide a solution, but reflectance images do not always contain sufficient information for adequate classification accuracy. In this work, the FluorIS, a low-cost modified consumer camera, was used to capture wide-band wide-field-of-view fluorescence images during a field deployment in Eilat, Israel. The fluorescence images were registered with standard reflectance images, and an automated annotation method based on convolutional neural networks was developed. Our results demonstrate a 22% reduction of classification error-rate when using both images types compared to only using reflectance images. The improvements were large, in particular, for coral reef genera Platygyra, Acropora and Millepora, where classification recall improved by 38%, 33%, and 41%, respectively. We conclude that convolutional neural networks can be used to combine reflectance and fluorescence imagery in order to significantly improve automated annotation accuracy and reduce the manual annotation bottleneck.

  20. Spatial image modulation to improve performance of computed tomography imaging spectrometer

    NASA Technical Reports Server (NTRS)

    Bearman, Gregory H. (Inventor); Wilson, Daniel W. (Inventor); Johnson, William R. (Inventor)

    2010-01-01

    Computed tomography imaging spectrometers ("CTIS"s) having patterns for imposing spatial structure are provided. The pattern may be imposed either directly on the object scene being imaged or at the field stop aperture. The use of the pattern improves the accuracy of the captured spatial and spectral information.

  1. Image analysis by integration of disparate information

    NASA Technical Reports Server (NTRS)

    Lemoigne, Jacqueline

    1993-01-01

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

  2. Image accuracy improvements in microwave tomographic thermometry: phantom experience.

    PubMed

    Meaney, P M; Paulsen, K D; Fanning, M W; Li, D; Fang, Q

    2003-01-01

    Evaluation of a laboratory-scale microwave imaging system for non-invasive temperature monitoring has previously been reported with good results in terms of both spatial and temperature resolution. However, a new formulation of the reconstruction algorithm in terms of the log-magnitude and phase of the electric fields has dramatically improved the ability of the system to track the temperature-dependent electrical conductivity distribution. This algorithmic enhancement was originally implemented as a way of improving overall imaging capability in cases of large, high contrast permittivity scatterers, but has also proved to be sensitive to subtle conductivity changes as required in thermal imaging. Additional refinements in the regularization procedure have strengthened the reliability and robustness of image convergence. Imaging experiments were performed for a single heated target consisting of a 5.1 cm diameter PVC tube located within 15 and 25 cm diameter monopole antenna arrays, respectively. The performance of both log-magnitude/phase and complex-valued reconstructions when subjected to four different regularization schemes has been compared based on this experimental data. The results demonstrate a significant accuracy improvement (to 0.2 degrees C as compared with 1.6 degrees C for the previously published approach) in tracking thermal changes in phantoms where electrical properties vary linearly with temperature over a range relevant to hyperthermia cancer therapy. PMID:12944168

  3. Improved restoration algorithm for weakly blurred and strongly noisy image

    NASA Astrophysics Data System (ADS)

    Liu, Qianshun; Xia, Guo; Zhou, Haiyang; Bai, Jian; Yu, Feihong

    2015-10-01

    In real applications, such as consumer digital imaging, it is very common to record weakly blurred and strongly noisy images. Recently, a state-of-art algorithm named geometric locally adaptive sharpening (GLAS) has been proposed. By capturing local image structure, it can effectively combine denoising and sharpening together. However, there still exist two problems in the practice. On one hand, two hard thresholds have to be constantly adjusted with different images so as not to produce over-sharpening artifacts. On the other hand, the smoothing parameter must be manually set precisely. Otherwise, it will seriously magnify the noise. However, these parameters have to be set in advance and totally empirically. In a practical application, this is difficult to achieve. Thus, it is not easy to use and not smart enough. In an effort to improve the restoration effect of this situation by way of GLAS, an improved GLAS (IGLAS) algorithm by introducing the local phase coherence sharpening Index (LPCSI) metric is proposed in this paper. With the help of LPCSI metric, the two hard thresholds can be fixed at constant values for all images. Compared to the original method, the thresholds in our new algorithm no longer need to change with different images. Based on our proposed IGLAS, its automatic version is also developed in order to compensate for the disadvantages of manual intervention. Simulated and real experimental results show that the proposed algorithm can not only obtain better performances compared with the original method, but it is very easy to apply.

  4. Improved QD-BRET conjugates for detection and imaging

    PubMed Central

    Xing, Yun; So, Min-kyung; Koh, Ai-leen; Sinclair, Robert; Rao, Jianghong

    2008-01-01

    Self-illuminating quantum dots, also known as QD-BRET conjugates, are a new class of quantum dots bioconjugates which do not need external light for excitation. Instead, light emission relies on the bioluminescence resonance energy transfer from the attached Renilla luciferase enzyme, which emits light upon the oxidation of its substrate. QD-BRET combines the advantages of the QDs (such as superior brightness & photostability, tunable emission, multiplexing) as well as the high sensitivity of bioluminescence imaging, thus holds the promise for improved deep tissue in vivo imaging. Although studies have demonstrated the superior sensitivity and deep tissue imaging potential, the stability of the QD-BRET conjugates in biological environment needs to be improved for long-term imaging studies such as in vivo cell trafficking. In this study, we seek to improve the stability of QD-BRET probes through polymeric encapsulation with a polyacrylamide gel. Results show that encapsulation caused some activity loss, but significantly improved both the in vitro serum stability and in vivo stability when subcutaneously injected into the animal. Stable QD-BRET probes should further facilitate their applications for both in vitro testing as well as in vivo cell tracking studies. PMID:18468518

  5. X-ray holographic microscopy: Improved images of zymogen granules

    SciTech Connect

    Jacobsen, C.; Howells, M.; Kirz, J.; McQuaid, K.; Rothman, S.

    1988-10-01

    Soft x-ray holography has long been considered as a technique for x-ray microscopy. It has been only recently, however, that sub-micron resolution has been obtained in x-ray holography. This paper will concentrate on recent progress we have made in obtaining reconstructed images of improved quality. 15 refs., 6 figs.

  6. Improved QD-BRET conjugates for detection and imaging

    SciTech Connect

    Xing Yun; So, Min-kyung; Koh, Ai Leen; Sinclair, Robert; Rao Jianghong

    2008-08-01

    Self-illuminating quantum dots, also known as QD-BRET conjugates, are a new class of quantum dot bioconjugates which do not need external light for excitation. Instead, light emission relies on the bioluminescence resonance energy transfer from the attached Renilla luciferase enzyme, which emits light upon the oxidation of its substrate. QD-BRET combines the advantages of the QDs (such as superior brightness and photostability, tunable emission, multiplexing) as well as the high sensitivity of bioluminescence imaging, thus holding the promise for improved deep tissue in vivo imaging. Although studies have demonstrated the superior sensitivity and deep tissue imaging potential, the stability of the QD-BRET conjugates in biological environment needs to be improved for long-term imaging studies such as in vivo cell tracking. In this study, we seek to improve the stability of QD-BRET probes through polymeric encapsulation with a polyacrylamide gel. Results show that encapsulation caused some activity loss, but significantly improved both the in vitro serum stability and in vivo stability when subcutaneously injected into the animal. Stable QD-BRET probes should further facilitate their applications for both in vitro testing as well as in vivo cell tracking studies.

  7. Improvement of automated image stitching system for DR X-ray images.

    PubMed

    Yang, Fan; He, Yan; Deng, Zhen Sheng; Yan, Ang

    2016-04-01

    The full bone structure of X-ray images cannot be captured in a single scan with Digital radiography (DR) system. The stitching method of X-ray images is very important for scoliosis or lower limb malformation diagnosing and pre-surgical planning. Based on the image registration technology, this paper proposes a new automated image stitching method for full-spine and lower limb X-ray images. The stitching method utilized down-sampling to decrease the size of image and reduce the amount of computation; improved phase correlation algorithm was adopted to find the overlapping region; correlation coefficient was used to evaluate the similarity of overlapping region; weighted blending is brought in to produce a panorama image. The performance of the proposed method was evaluated by 40 pairs of images from patients with scoliosis or lower limb malformation. The stitching method was fully automated without any user input required. The experimental results were compared with previous methods by analyzing the same database. It is demonstrated that the improved phase correlation has higher accuracy and shorter average stitching time than previous methods. It could tackle problems including image translation, rotation and small overlapping in image stitching. PMID:26914239

  8. 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.

  9. Characterization and analysis of infrared images

    NASA Astrophysics Data System (ADS)

    Raglin, Adrienne; Wetmore, Alan; Ligon, David

    2006-05-01

    Stokes images in the long-wave infrared (LWIR) and methods for processing polarimetric data continue to be areas of interest. Stokes images which are sensitive to geometry and material differences are acquired by measuring the polarization state of the received electromagnetic radiation. The polarimetric data from Stokes images may provide enhancements to conventional IR imagery data. It is generally agreed that polarimetric images can reveal information about objects or features within a scene that are not available through other imaging techniques. This additional information may generate different approaches to segmentation, detection, and recognition of objects or features. Previous research where horizontal and vertical polarization data is used supports the use of this type of data for image processing tasks. In this work we analyze a sample polarimetric image to show both improved segmentation of objects and derivation of their inherent 3-D geometry.

  10. Accuracy in Quantitative 3D Image Analysis

    PubMed Central

    Bassel, George W.

    2015-01-01

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

  11. Improving RLRN Image Splicing Detection with the Use of PCA and Kernel PCA

    PubMed Central

    Jalab, Hamid A.; Md Noor, Rafidah

    2014-01-01

    Digital image forgery is becoming easier to perform because of the rapid development of various manipulation tools. Image splicing is one of the most prevalent techniques. Digital images had lost their trustability, and researches have exerted considerable effort to regain such trustability by focusing mostly on algorithms. However, most of the proposed algorithms are incapable of handling high dimensionality and redundancy in the extracted features. Moreover, existing algorithms are limited by high computational time. This study focuses on improving one of the image splicing detection algorithms, that is, the run length run number algorithm (RLRN), by applying two dimension reduction methods, namely, principal component analysis (PCA) and kernel PCA. Support vector machine is used to distinguish between authentic and spliced images. Results show that kernel PCA is a nonlinear dimension reduction method that has the best effect on R, G, B, and Y channels and gray-scale images. PMID:25295304

  12. A Meta-Analytic Review of Stand-Alone Interventions to Improve Body Image

    PubMed Central

    Alleva, Jessica M.; Sheeran, Paschal; Webb, Thomas L.; Martijn, Carolien; Miles, Eleanor

    2015-01-01

    Objective Numerous stand-alone interventions to improve body image have been developed. The present review used meta-analysis to estimate the effectiveness of such interventions, and to identify the specific change techniques that lead to improvement in body image. Methods The inclusion criteria were that (a) the intervention was stand-alone (i.e., solely focused on improving body image), (b) a control group was used, (c) participants were randomly assigned to conditions, and (d) at least one pretest and one posttest measure of body image was taken. Effect sizes were meta-analysed and moderator analyses were conducted. A taxonomy of 48 change techniques used in interventions targeted at body image was developed; all interventions were coded using this taxonomy. Results The literature search identified 62 tests of interventions (N = 3,846). Interventions produced a small-to-medium improvement in body image (d+ = 0.38), a small-to-medium reduction in beauty ideal internalisation (d+ = -0.37), and a large reduction in social comparison tendencies (d+ = -0.72). However, the effect size for body image was inflated by bias both within and across studies, and was reliable but of small magnitude once corrections for bias were applied. Effect sizes for the other outcomes were no longer reliable once corrections for bias were applied. Several features of the sample, intervention, and methodology moderated intervention effects. Twelve change techniques were associated with improvements in body image, and three techniques were contra-indicated. Conclusions The findings show that interventions engender only small improvements in body image, and underline the need for large-scale, high-quality trials in this area. The review identifies effective techniques that could be deployed in future interventions. PMID:26418470

  13. Improved Image Registration by Sparse Patch-Based Deformation Estimation

    PubMed Central

    Kim, Minjeong; Wu, Guorong; Wang, Qian; Shen, Dinggang

    2014-01-01

    Despite of intensive efforts for decades, deformable image registration is still a challenging problem due to the potential large anatomical differences across individual images, which limits the registration performance. Fortunately, this issue could be alleviated if a good initial deformation can be provided for the two images under registration, which are often termed as the moving subject and the fixed template, respectively. In this work, we present a novel patch-based initial deformation prediction framework for improving the performance of existing registration algorithms. Our main idea is to estimate the initial deformation between subject and template in a patch-wise fashion by using the sparse representation technique. We argue that two image patches should follow the same deformation towards the template image if their patch-wise appearance patterns are similar. To this end, our framework consists of two stages, i.e., the training stage and the application stage. In the training stage, we register all training images to the pre-selected template, such that the deformation of each training image with respect to the template is known. In the application stage, we apply the following four steps to efficiently calculate the initial deformation field for the new test subject: (1) We pick a small number of key points in the distinctive regions of the test subject; (2) For each key point, we extract a local patch and form a coupled appearance-deformation dictionary from training images where each dictionary atom consists of the image intensity patch as well as their respective local deformations; (3) A small set of training image patches in the coupled dictionary are selected to represent the image patch of each subject key point by sparse representation. Then, we can predict the initial deformation for each subject key point by propagating the pre-estimated deformations on the selected training patches with the same sparse representation coefficients. (4) We

  14. 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

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

    NASA Astrophysics Data System (ADS)

    Rowberg, Alan H.

    1990-07-01

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

  16. Fundamental performance improvement to dispersive spectrograph based imaging technologies

    NASA Astrophysics Data System (ADS)

    Meade, Jeff T.; Behr, Bradford B.; Cenko, Andrew T.; Christensen, Peter; Hajian, Arsen R.; Hendrikse, Jan; Sweeney, Frederic D.

    2011-03-01

    Dispersive-based spectrometers may be qualified by their spectral resolving power and their throughput efficiency. A device known as a virtual slit is able to improve the resolving power by factors of several with a minimal loss in throughput, thereby fundamentally improving the quality of the spectrometer. A virtual slit was built and incorporated into a low performing spectrometer (R ~ 300) and was shown to increase the performance without a significant loss in signal. The operation and description of virtual slits is also given. High-performance, lowlight, and high-speed imaging instruments based on a dispersive-type spectrometer see the greatest impact from a virtual slit. The impact of a virtual slit on spectral domain optical coherence tomography (SD-OCT) is shown to improve the imaging quality substantially.

  17. Color camera computed tomography imaging spectrometer for improved spatial-spectral image accuracy

    NASA Technical Reports Server (NTRS)

    Wilson, Daniel W. (Inventor); Bearman, Gregory H. (Inventor); Johnson, William R. (Inventor)

    2011-01-01

    Computed tomography imaging spectrometers ("CTIS"s) having color focal plane array detectors are provided. The color FPA detector may comprise a digital color camera including a digital image sensor, such as a Foveon X3.RTM. digital image sensor or a Bayer color filter mosaic. In another embodiment, the CTIS includes a pattern imposed either directly on the object scene being imaged or at the field stop aperture. The use of a color FPA detector and the pattern improves the accuracy of the captured spatial and spectral information.

  18. Method for measuring anterior chamber volume by image analysis

    NASA Astrophysics Data System (ADS)

    Zhai, Gaoshou; Zhang, Junhong; Wang, Ruichang; Wang, Bingsong; Wang, Ningli

    2007-12-01

    Anterior chamber volume (ACV) is very important for an oculist to make rational pathological diagnosis as to patients who have some optic diseases such as glaucoma and etc., yet it is always difficult to be measured accurately. In this paper, a method is devised to measure anterior chamber volumes based on JPEG-formatted image files that have been transformed from medical images using the anterior-chamber optical coherence tomographer (AC-OCT) and corresponding image-processing software. The corresponding algorithms for image analysis and ACV calculation are implemented in VC++ and a series of anterior chamber images of typical patients are analyzed, while anterior chamber volumes are calculated and are verified that they are in accord with clinical observation. It shows that the measurement method is effective and feasible and it has potential to improve accuracy of ACV calculation. Meanwhile, some measures should be taken to simplify the handcraft preprocess working as to images.

  19. Multi-focus image fusion based on improved spectral graph wavelet transform

    NASA Astrophysics Data System (ADS)

    Yan, Xiang; Qin, Hanlin; Chen, Zhimin; Zhou, Huixin; Li, Jia; Zong, Jingguo

    2015-10-01

    Due to the limited depth-of-focus of optical lenses in imaging camera, it is impossible to acquire an image with all parts of the scene in focus. To make up for this defect, fusing the images at different focus settings into one image is a potential approach and many fusion methods have been developed. However, the existing methods can hardly deal with the problem of image detail blur. In this paper, a novel multiscale geometrical analysis called the directional spectral graph wavelet transform (DSGWT) is proposed, which integrates the nonsubsampled directional filter bank with the traditional spectral graph wavelet transform. Through combines the feature of efficiently representing the image containing regular or irregular areas of the spectral graph wavelet transform with the ability of capturing the directional information of the directional filter bank, the DSGWT can better represent the structure of images. Given the feature of the DSGWT, it is introduced to multi-focus image fusion to overcome the above disadvantage. On the one hand, using the high frequency subbands of the source images are obtained by the DSGWT, the proposed method efficiently represents the source images. On the other hand, using morphological filter to process the sparse feature matrix obtained by sum-modified-Laplacian focus measure criterion, the proposed method generates the fused subbands by morphological filtering. Comparison experiments have been performed on different image sets, and the experimental results demonstrate that the proposed method does significantly improve the fusion performance compared to the existing fusion methods.

  20. The use of image morphing to improve the detection of tumors in emission imaging

    SciTech Connect

    Dykstra, C.; Greer, K.; Jaszczak, R.; Celler, A.

    1999-06-01

    Two of the limitations on the utility of SPECT and planar scintigraphy for the non-invasive detection of carcinoma are the small sizes of many tumors and the possible low contrast between tumor uptake and background. This is particularly true for breast imaging. Use of some form of image processing can improve the visibility of tumors which are at the limit of hardware resolution. Smoothing, by some form of image averaging, either during or post-reconstruction, is widely used to reduce noise and thereby improve the detectability of regions of elevated activity. However, smoothing degrades resolution and, by averaging together closely spaced noise, may make noise look like a valid region of increased uptake. Image morphing by erosion and dilation does not average together image values; it instead selectively removes small features and irregularities from an image without changing the larger features. Application of morphing to emission images has shown that it does not, therefore, degrade resolution and does not always degrade contrast. For these reasons it may be a better method of image processing for noise removal in some images. In this paper the authors present a comparison of the effects of smoothing and morphing using breast and liver studies.

  1. Conductive resins improve charging and resolution of acquired images in electron microscopic volume imaging.

    PubMed

    Nguyen, Huy Bang; Thai, Truc Quynh; Saitoh, Sei; Wu, Bao; Saitoh, Yurika; Shimo, Satoshi; Fujitani, Hiroshi; Otobe, Hirohide; Ohno, Nobuhiko

    2016-01-01

    Recent advances in serial block-face imaging using scanning electron microscopy (SEM) have enabled the rapid and efficient acquisition of 3-dimensional (3D) ultrastructural information from a large volume of biological specimens including brain tissues. However, volume imaging under SEM is often hampered by sample charging, and typically requires specific sample preparation to reduce charging and increase image contrast. In the present study, we introduced carbon-based conductive resins for 3D analyses of subcellular ultrastructures, using serial block-face SEM (SBF-SEM) to image samples. Conductive resins were produced by adding the carbon black filler, Ketjen black, to resins commonly used for electron microscopic observations of biological specimens. Carbon black mostly localized around tissues and did not penetrate cells, whereas the conductive resins significantly reduced the charging of samples during SBF-SEM imaging. When serial images were acquired, embedding into the conductive resins improved the resolution of images by facilitating the successful cutting of samples in SBF-SEM. These results suggest that improving the conductivities of resins with a carbon black filler is a simple and useful option for reducing charging and enhancing the resolution of images obtained for volume imaging with SEM. PMID:27020327

  2. Conductive resins improve charging and resolution of acquired images in electron microscopic volume imaging

    PubMed Central

    Nguyen, Huy Bang; Thai, Truc Quynh; Saitoh, Sei; Wu, Bao; Saitoh, Yurika; Shimo, Satoshi; Fujitani, Hiroshi; Otobe, Hirohide; Ohno, Nobuhiko

    2016-01-01

    Recent advances in serial block-face imaging using scanning electron microscopy (SEM) have enabled the rapid and efficient acquisition of 3-dimensional (3D) ultrastructural information from a large volume of biological specimens including brain tissues. However, volume imaging under SEM is often hampered by sample charging, and typically requires specific sample preparation to reduce charging and increase image contrast. In the present study, we introduced carbon-based conductive resins for 3D analyses of subcellular ultrastructures, using serial block-face SEM (SBF-SEM) to image samples. Conductive resins were produced by adding the carbon black filler, Ketjen black, to resins commonly used for electron microscopic observations of biological specimens. Carbon black mostly localized around tissues and did not penetrate cells, whereas the conductive resins significantly reduced the charging of samples during SBF-SEM imaging. When serial images were acquired, embedding into the conductive resins improved the resolution of images by facilitating the successful cutting of samples in SBF-SEM. These results suggest that improving the conductivities of resins with a carbon black filler is a simple and useful option for reducing charging and enhancing the resolution of images obtained for volume imaging with SEM. PMID:27020327

  3. Image guidance improves localization of sonographically occult colorectal liver metastases

    NASA Astrophysics Data System (ADS)

    Leung, Universe; Simpson, Amber L.; Adams, Lauryn B.; Jarnagin, William R.; Miga, Michael I.; Kingham, T. Peter

    2015-03-01

    Assessing the therapeutic benefit of surgical navigation systems is a challenging problem in image-guided surgery. The exact clinical indications for patients that may benefit from these systems is not always clear, particularly for abdominal surgery where image-guidance systems have failed to take hold in the same way as orthopedic and neurosurgical applications. We report interim analysis of a prospective clinical trial for localizing small colorectal liver metastases using the Explorer system (Path Finder Technologies, Nashville, TN). Colorectal liver metastases are small lesions that can be difficult to identify with conventional intraoperative ultrasound due to echogeneity changes in the liver as a result of chemotherapy and other preoperative treatments. Interim analysis with eighteen patients shows that 9 of 15 (60%) of these occult lesions could be detected with image guidance. Image guidance changed intraoperative management in 3 (17%) cases. These results suggest that image guidance is a promising tool for localization of small occult liver metastases and that the indications for image-guided surgery are expanding.

  4. 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.

  5. Geopositioning Precision Analysis of Multiple Image Triangulation Using Lro Nac Lunar Images

    NASA Astrophysics Data System (ADS)

    Di, K.; Xu, B.; Liu, B.; Jia, M.; Liu, Z.

    2016-06-01

    This paper presents an empirical analysis of the geopositioning precision of multiple image triangulation using Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images at the Chang'e-3(CE-3) landing site. Nine LROC NAC images are selected for comparative analysis of geopositioning precision. Rigorous sensor models of the images are established based on collinearity equations with interior and exterior orientation elements retrieved from the corresponding SPICE kernels. Rational polynomial coefficients (RPCs) of each image are derived by least squares fitting using vast number of virtual control points generated according to rigorous sensor models. Experiments of different combinations of images are performed for comparisons. The results demonstrate that the plane coordinates can achieve a precision of 0.54 m to 2.54 m, with a height precision of 0.71 m to 8.16 m when only two images are used for three-dimensional triangulation. There is a general trend that the geopositioning precision, especially the height precision, is improved with the convergent angle of the two images increasing from several degrees to about 50°. However, the image matching precision should also be taken into consideration when choosing image pairs for triangulation. The precisions of using all the 9 images are 0.60 m, 0.50 m, 1.23 m in along-track, cross-track, and height directions, which are better than most combinations of two or more images. However, triangulation with selected fewer images could produce better precision than that using all the images.

  6. The Hinode/XRT Full-Sun Image Corrections and the Improved Synoptic Composite Image Archive

    NASA Astrophysics Data System (ADS)

    Takeda, Aki; Yoshimura, Keiji; Saar, Steven H.

    2016-01-01

    The XRT Synoptic Composite Image Archive (SCIA) is a storage and gallery of X-ray full-Sun images obtained through the synoptic program of the X-Ray Telescope (XRT) onboard the Hinode satellite. The archived images provide a quick history of solar activity through the daily and monthly layout pages and long-term data for morphological and quantitative studies of the X-ray corona. This article serves as an introduction to the SCIA, i.e., to the structure of the archive and specification of the data products included therein. We also describe a number of techniques used to improve the quality of the archived images: preparation of composite images to increase intensity dynamic range, removal of dark spots that are due to contaminants on the CCD, and correction of the visible stray light contamination that has been detected on the Ti-poly and C-poly filter images since May 2012.

  7. Improved satellite image compression and reconstruction via genetic algorithms

    NASA Astrophysics Data System (ADS)

    Babb, Brendan; Moore, Frank; Peterson, Michael; Lamont, Gary

    2008-10-01

    A wide variety of signal and image processing applications, including the US Federal Bureau of Investigation's fingerprint compression standard [3] and the JPEG-2000 image compression standard [26], utilize wavelets. This paper describes new research that demonstrates how a genetic algorithm (GA) may be used to evolve transforms that outperform wavelets for satellite image compression and reconstruction under conditions subject to quantization error. The new approach builds upon prior work by simultaneously evolving real-valued coefficients representing matched forward and inverse transform pairs at each of three levels of a multi-resolution analysis (MRA) transform. The training data for this investigation consists of actual satellite photographs of strategic urban areas. Test results show that a dramatic reduction in the error present in reconstructed satellite images may be achieved without sacrificing the compression capabilities of the forward transform. The transforms evolved during this research outperform previous start-of-the-art solutions, which optimized coefficients for the reconstruction transform only. These transforms also outperform wavelets, reducing error by more than 0.76 dB at a quantization level of 64. In addition, transforms trained using representative satellite images do not perform quite as well when subsequently tested against images from other classes (such as fingerprints or portraits). This result suggests that the GA developed for this research is automatically learning to exploit specific attributes common to the class of images represented in the training population.

  8. Research on an Improved Medical Image Enhancement Algorithm Based on P-M Model.

    PubMed

    Dong, Beibei; Yang, Jingjing; Hao, Shangfu; Zhang, Xiao

    2015-01-01

    Image enhancement can improve the detail of the image and so as to achieve the purpose of the identification of the image. At present, the image enhancement is widely used in medical images, which can help doctor's diagnosis. IEABPM (Image Enhancement Algorithm Based on P-M Model) is one of the most common image enhancement algorithms. However, it may cause the lost of the texture details and other features. To solve the problems, this paper proposes an IIEABPM (Improved Image Enhancement Algorithm Based on P-M Model). Simulation demonstrates that IIEABPM can effectively solve the problems of IEABPM, and improve image clarity, image contrast, and image brightness. PMID:26628929

  9. Analysis of the relationship between the volumetric soil moisture content and the NDVI from high resolution multi-spectral images for definition of vineyard management zones to improve irrigation

    NASA Astrophysics Data System (ADS)

    Martínez-Casasnovas, J. A.; Ramos, M. C.

    2009-04-01

    As suggested by previous research in the field of precision viticulture, intra-field yield variability is dependent on the variation of soil properties, and in particular the soil moisture content. Since the mapping in detail of this soil property for precision viticulture applications is highly costly, the objective of the present research is to analyse its relationship with the normalised difference vegetation index from high resolution satellite images to the use it in the definition of vineyard zonal management. The final aim is to improve irrigation in commercial vineyard blocks for better management of inputs and to deliver a more homogeneous fruit to the winery. The study was carried out in a vineyard block located in Raimat (NE Spain, Costers del Segre Designation of Origin). This is a semi-arid area with continental Mediterranean climate and a total annual precipitation between 300-400 mm. The vineyard block (4.5 ha) is planted with Syrah vines in a 3x2 m pattern. The vines are irrigated by means of drips under a partial root drying schedule. Initially, the irrigation sectors had a quadrangular distribution, with a size of about 1 ha each. Yield is highly variable within the block, presenting a coefficient of variation of 24.9%. For the measurement of the soil moisture content a regular sampling grid of 30 x 40 m was defined. This represents a sample density of 8 samples ha-1. At the nodes of the grid, TDR (Time Domain Reflectometer) probe tubes were permanently installed up to the 80 cm or up to reaching a contrasting layer. Multi-temporal measures were taken at different depths (each 20 cm) between November 2006 and December 2007. For each date, a map of the variability of the profile soil moisture content was interpolated by means of geostatistical analysis: from the measured values at the grid points the experimental variograms were computed and modelled and global block kriging (10 m squared blocks) undertaken with a grid spacing of 3 m x 3 m. On the

  10. Conducting a SWOT Analysis for Program Improvement

    ERIC Educational Resources Information Center

    Orr, Betsy

    2013-01-01

    A SWOT (strengths, weaknesses, opportunities, and threats) analysis of a teacher education program, or any program, can be the driving force for implementing change. A SWOT analysis is used to assist faculty in initiating meaningful change in a program and to use the data for program improvement. This tool is useful in any undergraduate or degree…