Quality assessment of remote sensing image fusion using feature-based fourth-order correlation coefficient

NASA Astrophysics Data System (ADS)

Ma, Dan; Liu, Jun; Chen, Kai; Li, Huali; Liu, Ping; Chen, Huijuan; Qian, Jing

2016-04-01

In remote sensing fusion, the spatial details of a panchromatic (PAN) image and the spectrum information of multispectral (MS) images will be transferred into fused images according to the characteristics of the human visual system. Thus, a remote sensing image fusion quality assessment called feature-based fourth-order correlation coefficient (FFOCC) is proposed. FFOCC is based on the feature-based coefficient concept. Spatial features related to spatial details of the PAN image and spectral features related to the spectrum information of MS images are first extracted from the fused image. Then, the fourth-order correlation coefficient between the spatial and spectral features is calculated and treated as the assessment result. FFOCC was then compared with existing widely used indices, such as Erreur Relative Globale Adimensionnelle de Synthese, and quality assessed with no reference. Results of the fusion and distortion experiments indicate that the FFOCC is consistent with subjective evaluation. FFOCC significantly outperforms the other indices in evaluating fusion images that are produced by different fusion methods and that are distorted in spatial and spectral features by blurring, adding noise, and changing intensity. All the findings indicate that the proposed method is an objective and effective quality assessment for remote sensing image fusion.

Noise-immune complex correlation for optical coherence angiography based on standard and Jones matrix optical coherence tomography

PubMed Central

Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Miura, Masahiro; Yasuno, Yoshiaki

2016-01-01

This paper describes a complex correlation mapping algorithm for optical coherence angiography (cmOCA). The proposed algorithm avoids the signal-to-noise ratio dependence and exhibits low noise in vasculature imaging. The complex correlation coefficient of the signals, rather than that of the measured data are estimated, and two-step averaging is introduced. Algorithms of motion artifact removal based on non perfusing tissue detection using correlation are developed. The algorithms are implemented with Jones-matrix OCT. Simultaneous imaging of pigmented tissue and vasculature is also achieved using degree of polarization uniformity imaging with cmOCA. An application of cmOCA to in vivo posterior human eyes is presented to demonstrate that high-contrast images of patients’ eyes can be obtained. PMID:27446673

Correlated Topic Vector for Scene Classification.

PubMed

Wei, Pengxu; Qin, Fei; Wan, Fang; Zhu, Yi; Jiao, Jianbin; Ye, Qixiang

2017-07-01

Scene images usually involve semantic correlations, particularly when considering large-scale image data sets. This paper proposes a novel generative image representation, correlated topic vector, to model such semantic correlations. Oriented from the correlated topic model, correlated topic vector intends to naturally utilize the correlations among topics, which are seldom considered in the conventional feature encoding, e.g., Fisher vector, but do exist in scene images. It is expected that the involvement of correlations can increase the discriminative capability of the learned generative model and consequently improve the recognition accuracy. Incorporated with the Fisher kernel method, correlated topic vector inherits the advantages of Fisher vector. The contributions to the topics of visual words have been further employed by incorporating the Fisher kernel framework to indicate the differences among scenes. Combined with the deep convolutional neural network (CNN) features and Gibbs sampling solution, correlated topic vector shows great potential when processing large-scale and complex scene image data sets. Experiments on two scene image data sets demonstrate that correlated topic vector improves significantly the deep CNN features, and outperforms existing Fisher kernel-based features.

EIT image reconstruction with four dimensional regularization.

PubMed

Dai, Tao; Soleimani, Manuchehr; Adler, Andy

2008-09-01

Electrical impedance tomography (EIT) reconstructs internal impedance images of the body from electrical measurements on body surface. The temporal resolution of EIT data can be very high, although the spatial resolution of the images is relatively low. Most EIT reconstruction algorithms calculate images from data frames independently, although data are actually highly correlated especially in high speed EIT systems. This paper proposes a 4-D EIT image reconstruction for functional EIT. The new approach is developed to directly use prior models of the temporal correlations among images and 3-D spatial correlations among image elements. A fast algorithm is also developed to reconstruct the regularized images. Image reconstruction is posed in terms of an augmented image and measurement vector which are concatenated from a specific number of previous and future frames. The reconstruction is then based on an augmented regularization matrix which reflects the a priori constraints on temporal and 3-D spatial correlations of image elements. A temporal factor reflecting the relative strength of the image correlation is objectively calculated from measurement data. Results show that image reconstruction models which account for inter-element correlations, in both space and time, show improved resolution and noise performance, in comparison to simpler image models.

An efficient computational approach to model statistical correlations in photon counting x-ray detectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faby, Sebastian; Maier, Joscha; Sawall, Stefan

2016-07-15

Purpose: To introduce and evaluate an increment matrix approach (IMA) describing the signal statistics of energy-selective photon counting detectors including spatial–spectral correlations between energy bins of neighboring detector pixels. The importance of the occurring correlations for image-based material decomposition is studied. Methods: An IMA describing the counter increase patterns in a photon counting detector is proposed. This IMA has the potential to decrease the number of required random numbers compared to Monte Carlo simulations by pursuing an approach based on convolutions. To validate and demonstrate the IMA, an approximate semirealistic detector model is provided, simulating a photon counting detector inmore » a simplified manner, e.g., by neglecting count rate-dependent effects. In this way, the spatial–spectral correlations on the detector level are obtained and fed into the IMA. The importance of these correlations in reconstructed energy bin images and the corresponding detector performance in image-based material decomposition is evaluated using a statistically optimal decomposition algorithm. Results: The results of IMA together with the semirealistic detector model were compared to other models and measurements using the spectral response and the energy bin sensitivity, finding a good agreement. Correlations between the different reconstructed energy bin images could be observed, and turned out to be of weak nature. These correlations were found to be not relevant in image-based material decomposition. An even simpler simulation procedure based on the energy bin sensitivity was tested instead and yielded similar results for the image-based material decomposition task, as long as the fact that one incident photon can increase multiple counters across neighboring detector pixels is taken into account. Conclusions: The IMA is computationally efficient as it required about 10{sup 2} random numbers per ray incident on a detector pixel instead of an estimated 10{sup 8} random numbers per ray as Monte Carlo approaches would need. The spatial–spectral correlations as described by IMA are not important for the studied image-based material decomposition task. Respecting the absolute photon counts and thus the multiple counter increases by a single x-ray photon, the same material decomposition performance could be obtained with a simpler detector description using the energy bin sensitivity.« less

Optical correlators for recognition of human face thermal images

NASA Astrophysics Data System (ADS)

Bauer, Joanna; Podbielska, Halina; Suchwalko, Artur; Mazurkiewicz, Jacek

2005-09-01

In this paper, the application of the optical correlators for face thermograms recognition is described. The thermograms were colleted from 27 individuals. For each person 10 pictures in different conditions were recorded and the data base composed of 270 images was prepared. Two biometric systems based on joint transform correlator and 4f correlator were built. Each system was designed for realizing two various tasks: verification and identification. The recognition systems were tested and evaluated according to the Face Recognition Vendor Tests (FRVT).

Influence of a perturbation in the Gyrator domain for a joint transform correlator-based encryption system

NASA Astrophysics Data System (ADS)

Vilardy, Juan M.; Millán, María. S.; Pérez-Cabré, Elisabet

2017-08-01

We present the results of the noise and occlusion tests in the Gyrator domain (GD) for a joint transform correlator-based encryption system. This encryption system was recently proposed and it was implemented by using a fully phase nonzero-order joint transform correlator (JTC) and the Gyrator transform (GT). The decryption system was based on two successive GTs. In this paper, we make several numerical simulations in order to test the performance and robustness of the JTC-based encryption-decryption system in the GD when the encrypted image is corrupted by noise or occlusion. The encrypted image is affected by additive and multiplicative noise. We also test the effect of data loss due to partial occlusion of the encrypted information. Finally, we evaluate the performance and robustness of the encryption-decryption system in the GD by using the metric of the root mean square error (RMSE) between the original image and the decrypted image when the encrypted image is degraded by noise or modified by occlusion.

Enhance the Quality of Crowdsensing for Fine-Grained Urban Environment Monitoring via Data Correlation

PubMed Central

Kang, Xu; Liu, Liang; Ma, Huadong

2017-01-01

Monitoring the status of urban environments, which provides fundamental information for a city, yields crucial insights into various fields of urban research. Recently, with the popularity of smartphones and vehicles equipped with onboard sensors, a people-centric scheme, namely “crowdsensing”, for city-scale environment monitoring is emerging. This paper proposes a data correlation based crowdsensing approach for fine-grained urban environment monitoring. To demonstrate urban status, we generate sensing images via crowdsensing network, and then enhance the quality of sensing images via data correlation. Specifically, to achieve a higher quality of sensing images, we not only utilize temporal correlation of mobile sensing nodes but also fuse the sensory data with correlated environment data by introducing a collective tensor decomposition approach. Finally, we conduct a series of numerical simulations and a real dataset based case study. The results validate that our approach outperforms the traditional spatial interpolation-based method. PMID:28054968

Image correlation microscopy for uniform illumination.

PubMed

Gaborski, T R; Sealander, M N; Ehrenberg, M; Waugh, R E; McGrath, J L

2010-01-01

Image cross-correlation microscopy is a technique that quantifies the motion of fluorescent features in an image by measuring the temporal autocorrelation function decay in a time-lapse image sequence. Image cross-correlation microscopy has traditionally employed laser-scanning microscopes because the technique emerged as an extension of laser-based fluorescence correlation spectroscopy. In this work, we show that image correlation can also be used to measure fluorescence dynamics in uniform illumination or wide-field imaging systems and we call our new approach uniform illumination image correlation microscopy. Wide-field microscopy is not only a simpler, less expensive imaging modality, but it offers the capability of greater temporal resolution over laser-scanning systems. In traditional laser-scanning image cross-correlation microscopy, lateral mobility is calculated from the temporal de-correlation of an image, where the characteristic length is the illuminating laser beam width. In wide-field microscopy, the diffusion length is defined by the feature size using the spatial autocorrelation function. Correlation function decay in time occurs as an object diffuses from its original position. We show that theoretical and simulated comparisons between Gaussian and uniform features indicate the temporal autocorrelation function depends strongly on particle size and not particle shape. In this report, we establish the relationships between the spatial autocorrelation function feature size, temporal autocorrelation function characteristic time and the diffusion coefficient for uniform illumination image correlation microscopy using analytical, Monte Carlo and experimental validation with particle tracking algorithms. Additionally, we demonstrate uniform illumination image correlation microscopy analysis of adhesion molecule domain aggregation and diffusion on the surface of human neutrophils.

A method for predicting DCT-based denoising efficiency for grayscale images corrupted by AWGN and additive spatially correlated noise

NASA Astrophysics Data System (ADS)

Rubel, Aleksey S.; Lukin, Vladimir V.; Egiazarian, Karen O.

2015-03-01

Results of denoising based on discrete cosine transform for a wide class of images corrupted by additive noise are obtained. Three types of noise are analyzed: additive white Gaussian noise and additive spatially correlated Gaussian noise with middle and high correlation levels. TID2013 image database and some additional images are taken as test images. Conventional DCT filter and BM3D are used as denoising techniques. Denoising efficiency is described by PSNR and PSNR-HVS-M metrics. Within hard-thresholding denoising mechanism, DCT-spectrum coefficient statistics are used to characterize images and, subsequently, denoising efficiency for them. Results of denoising efficiency are fitted for such statistics and efficient approximations are obtained. It is shown that the obtained approximations provide high accuracy of prediction of denoising efficiency.

Change Detection via Selective Guided Contrasting Filters

NASA Astrophysics Data System (ADS)

Vizilter, Y. V.; Rubis, A. Y.; Zheltov, S. Y.

2017-05-01

Change detection scheme based on guided contrasting was previously proposed. Guided contrasting filter takes two images (test and sample) as input and forms the output as filtered version of test image. Such filter preserves the similar details and smooths the non-similar details of test image with respect to sample image. Due to this the difference between test image and its filtered version (difference map) could be a basis for robust change detection. Guided contrasting is performed in two steps: at the first step some smoothing operator (SO) is applied for elimination of test image details; at the second step all matched details are restored with local contrast proportional to the value of some local similarity coefficient (LSC). The guided contrasting filter was proposed based on local average smoothing as SO and local linear correlation as LSC. In this paper we propose and implement new set of selective guided contrasting filters based on different combinations of various SO and thresholded LSC. Linear average and Gaussian smoothing, nonlinear median filtering, morphological opening and closing are considered as SO. Local linear correlation coefficient, morphological correlation coefficient (MCC), mutual information, mean square MCC and geometrical correlation coefficients are applied as LSC. Thresholding of LSC allows operating with non-normalized LSC and enhancing the selective properties of guided contrasting filters: details are either totally recovered or not recovered at all after the smoothing. These different guided contrasting filters are tested as a part of previously proposed change detection pipeline, which contains following stages: guided contrasting filtering on image pyramid, calculation of difference map, binarization, extraction of change proposals and testing change proposals using local MCC. Experiments on real and simulated image bases demonstrate the applicability of all proposed selective guided contrasting filters. All implemented filters provide the robustness relative to weak geometrical discrepancy of compared images. Selective guided contrasting based on morphological opening/closing and thresholded morphological correlation demonstrates the best change detection result.

Ventilation/perfusion SPECT or SPECT/CT for lung function imaging in patients with pulmonary emphysema?

PubMed

Froeling, Vera; Heimann, Uwe; Huebner, Ralf-Harto; Kroencke, Thomas J; Maurer, Martin H; Doellinger, Felix; Geisel, Dominik; Hamm, Bernd; Brenner, Winfried; Schreiter, Nils F

2015-07-01

To evaluate the utility of attenuation correction (AC) of V/P SPECT images for patients with pulmonary emphysema. Twenty-one patients (mean age 67.6 years) with pulmonary emphysema who underwent V/P SPECT/CT were included. AC/non-AC V/P SPECT images were compared visually and semiquantitatively. Visual comparison of AC/non-AC images was based on a 5-point likert scale. Semiquantitative comparison assessed absolute counts per lung (aCpLu) and lung lobe (aCpLo) for AC/non-AC images using software-based analysis; percentage counts (PC = (aCpLo/aCpLu) × 100) were calculated. Correlation between AC/non-AC V/P SPECT images was analyzed using Spearman's rho correlation coefficient; differences were tested for significance with the Wilcoxon rank sum test. Visual analysis revealed high conformity for AC and non-AC V/P SPECT images. Semiquantitative analysis of PC in AC/non-AC images had an excellent correlation and showed no significant differences in perfusion (ρ = 0.986) or ventilation (ρ = 0.979, p = 0.809) SPECT/CT images. AC of V/P SPECT images for lung lobe-based function imaging in patients with pulmonary emphysema do not improve visual or semiquantitative image analysis.

Smartphone based scalable reverse engineering by digital image correlation

NASA Astrophysics Data System (ADS)

Vidvans, Amey; Basu, Saurabh

2018-03-01

There is a need for scalable open source 3D reconstruction systems for reverse engineering. This is because most commercially available reconstruction systems are capital and resource intensive. To address this, a novel reconstruction technique is proposed. The technique involves digital image correlation based characterization of surface speeds followed by normalization with respect to angular speed during rigid body rotational motion of the specimen. Proof of concept of the same is demonstrated and validated using simulation and empirical characterization. Towards this, smart-phone imaging and inexpensive off the shelf components along with those fabricated additively using poly-lactic acid polymer with a standard 3D printer are used. Some sources of error in this reconstruction methodology are discussed. It is seen that high curvatures on the surface suppress accuracy of reconstruction. Reasons behind this are delineated in the nature of the correlation function. Theoretically achievable resolution during smart-phone based 3D reconstruction by digital image correlation is derived.

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

NASA Technical Reports Server (NTRS)

Grycewicz, Thomas J.; Tan, Bin; Isaacson, Peter J.; De Luccia, Frank J.; Dellomo, John

2016-01-01

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

Image scale measurement with correlation filters in a volume holographic optical correlator

NASA Astrophysics Data System (ADS)

Zheng, Tianxiang; Cao, Liangcai; He, Qingsheng; Jin, Guofan

2013-08-01

A search engine containing various target images or different part of a large scene area is of great use for many applications, including object detection, biometric recognition, and image registration. The input image captured in realtime is compared with all the template images in the search engine. A volume holographic correlator is one type of these search engines. It performs thousands of comparisons among the images at a super high speed, with the correlation task accomplishing mainly in optics. However, the inputted target image always contains scale variation to the filtering template images. At the time, the correlation values cannot properly reflect the similarity of the images. It is essential to estimate and eliminate the scale variation of the inputted target image. There are three domains for performing the scale measurement, as spatial, spectral and time domains. Most methods dealing with the scale factor are based on the spatial or the spectral domains. In this paper, a method with the time domain is proposed to measure the scale factor of the input image. It is called a time-sequential scaled method. The method utilizes the relationship between the scale variation and the correlation value of two images. It sends a few artificially scaled input images to compare with the template images. The correlation value increases and decreases with the increasing of the scale factor at the intervals of 0.8~1 and 1~1.2, respectively. The original scale of the input image can be measured by estimating the largest correlation value through correlating the artificially scaled input image with the template images. The measurement range for the scale can be 0.8~4.8. Scale factor beyond 1.2 is measured by scaling the input image at the factor of 1/2, 1/3 and 1/4, correlating the artificially scaled input image with the template images, and estimating the new corresponding scale factor inside 0.8~1.2.

Wear Detection of Drill Bit by Image-based Technique

NASA Astrophysics Data System (ADS)

Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul

2018-03-01

Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

International inter-rater agreement in scoring acne severity utilizing cloud-based image sharing of mobile phone photographs.

PubMed

Foolad, Negar; Ornelas, Jennifer N; Clark, Ashley K; Ali, Ifrah; Sharon, Victoria R; Al Mubarak, Luluah; Lopez, Andrés; Alikhan, Ali; Al Dabagh, Bishr; Firooz, Alireza; Awasthi, Smita; Liu, Yu; Li, Chin-Shang; Sivamani, Raja K

2017-09-01

Cloud-based image sharing technology allows facilitated sharing of images. Cloud-based image sharing technology has not been well-studied for acne assessments or treatment preferences, among international evaluators. We evaluated inter-rater variability of acne grading and treatment recommendations among an international group of dermatologists that assessed photographs. This is a prospective, single visit photographic study to assess inter-rater agreement of acne photographs shared through an integrated mobile device, cloud-based, and HIPAA-compliant platform. Inter-rater agreements for global acne assessment and acne lesion counts were evaluated by the Kendall's coefficient of concordance while correlations between treatment recommendations and acne severity were calculated by Spearman's rank correlation coefficient. There was good agreement for the evaluation of inflammatory lesions (KCC = 0.62, P < 0.0001), noninflammatory lesions (KCC = 0.62, P < 0.0001), and the global acne grading system score (KCC = 0.69, P < 0.0001). Topical retinoid, oral antibiotic, and isotretinoin treatment preferences correlated with photographic based acne severity. Our study supports the use of mobile phone based photography and cloud-based image sharing for acne assessment. Cloud-based sharing may facilitate acne care and research among international collaborators. © 2017 The International Society of Dermatology.

Adapting the ISO 20462 softcopy ruler method for online image quality studies

NASA Astrophysics Data System (ADS)

Burns, Peter D.; Phillips, Jonathan B.; Williams, Don

2013-01-01

In this paper we address the problem of Image Quality Assessment of no reference metrics, focusing on JPEG corrupted images. In general no reference metrics are not able to measure with the same performance the distortions within their possible range and with respect to different image contents. The crosstalk between content and distortion signals influences the human perception. We here propose two strategies to improve the correlation between subjective and objective quality data. The first strategy is based on grouping the images according to their spatial complexity. The second one is based on a frequency analysis. Both the strategies are tested on two databases available in the literature. The results show an improvement in the correlations between no reference metrics and psycho-visual data, evaluated in terms of the Pearson Correlation Coefficient.

Correlation Filters for Detection of Cellular Nuclei in Histopathology Images.

PubMed

Ahmad, Asif; Asif, Amina; Rajpoot, Nasir; Arif, Muhammad; Minhas, Fayyaz Ul Amir Afsar

2017-11-21

Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for detection of cellular nuclei in hematoxylin and eosin stained histopathology images. Our proposed approach is based on kernelized correlation filters. Correlation filters have been widely used in object detection and tracking applications but their strength has not been explored in the medical imaging domain up till now. Our experimental results show that the proposed scheme gives state of the art accuracy and can learn complex nuclear morphologies. Like deep learning approaches, the proposed filters do not require engineering of image features as they can operate directly on histopathology images without significant preprocessing. However, unlike deep learning methods, the large-margin correlation filters developed in this work are interpretable, computationally efficient and do not require specialized or expensive computing hardware. A cloud based webserver of the proposed method and its python implementation can be accessed at the following URL: http://faculty.pieas.edu.pk/fayyaz/software.html#corehist .

Image correlation nondestructive evaluation of impact damage in a glass fiber composite

NASA Technical Reports Server (NTRS)

Russell, Samuel S.

1990-01-01

Presented in viewgraph format, digital image correlation, damage in fibrous composites, and damaged coupons (cross-ply scotchply GI-Ep laminate) are outlined. It was concluded that the image correlation accuracy was 0.03 percent; strains can be processed through Tsai-Hill failure criteria to qualify the damage; the statistical data base must be generated to evaluate certainty of the damage estimate; size effects need consideration; and better numerical techniques are needed.

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Neural correlates of monocular and binocular depth cues based on natural images: a LORETA analysis.

PubMed

Fischmeister, Florian Ph S; Bauer, Herbert

2006-10-01

Functional imaging studies investigating perception of depth rely solely on one type of depth cue based on non-natural stimulus material. To overcome these limitations and to provide a more realistic and complete set of depth cues natural stereoscopic images were used in this study. Using slow cortical potentials and source localization we aimed to identify the neural correlates of monocular and binocular depth cues. This study confirms and extends functional imaging studies, showing that natural images provide a good, reliable, and more realistic alternative to artificial stimuli, and demonstrates the possibility to separate the processing of different depth cues.

Imaging the square of the correlated two-electron wave function of a hydrogen molecule

DOE PAGES

Waitz, M.; Bello, R. Y.; Metz, D.; ...

2017-12-22

The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in whichmore » electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Finally, our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.« less

Imaging the square of the correlated two-electron wave function of a hydrogen molecule.

PubMed

Waitz, M; Bello, R Y; Metz, D; Lower, J; Trinter, F; Schober, C; Keiling, M; Lenz, U; Pitzer, M; Mertens, K; Martins, M; Viefhaus, J; Klumpp, S; Weber, T; Schmidt, L Ph H; Williams, J B; Schöffler, M S; Serov, V V; Kheifets, A S; Argenti, L; Palacios, A; Martín, F; Jahnke, T; Dörner, R

2017-12-22

The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in which electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.

Imaging the square of the correlated two-electron wave function of a hydrogen molecule

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waitz, M.; Bello, R. Y.; Metz, D.

The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in whichmore » electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Finally, our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.« less

Accelerometer-Based Method for Extracting Respiratory and Cardiac Gating Information for Dual Gating during Nuclear Medicine Imaging

PubMed Central

Pänkäälä, Mikko; Paasio, Ari

2014-01-01

Both respiratory and cardiac motions reduce the quality and consistency of medical imaging specifically in nuclear medicine imaging. Motion artifacts can be eliminated by gating the image acquisition based on the respiratory phase and cardiac contractions throughout the medical imaging procedure. Electrocardiography (ECG), 3-axis accelerometer, and respiration belt data were processed and analyzed from ten healthy volunteers. Seismocardiography (SCG) is a noninvasive accelerometer-based method that measures accelerations caused by respiration and myocardial movements. This study was conducted to investigate the feasibility of the accelerometer-based method in dual gating technique. The SCG provides accelerometer-derived respiratory (ADR) data and accurate information about quiescent phases within the cardiac cycle. The correct information about the status of ventricles and atria helps us to create an improved estimate for quiescent phases within a cardiac cycle. The correlation of ADR signals with the reference respiration belt was investigated using Pearson correlation. High linear correlation was observed between accelerometer-based measurement and reference measurement methods (ECG and Respiration belt). Above all, due to the simplicity of the proposed method, the technique has high potential to be applied in dual gating in clinical cardiac positron emission tomography (PET) to obtain motion-free images in the future. PMID:25120563

Dynamic deformation image de-blurring and image processing for digital imaging correlation measurement

NASA Astrophysics Data System (ADS)

Guo, X.; Li, Y.; Suo, T.; Liu, H.; Zhang, C.

2017-11-01

This paper proposes a method for de-blurring of images captured in the dynamic deformation of materials. De-blurring is achieved based on the dynamic-based approach, which is used to estimate the Point Spread Function (PSF) during the camera exposure window. The deconvolution process involving iterative matrix calculations of pixels, is then performed on the GPU to decrease the time cost. Compared to the Gauss method and the Lucy-Richardson method, it has the best result of the image restoration. The proposed method has been evaluated by using the Hopkinson bar loading system. In comparison to the blurry image, the proposed method has successfully restored the image. It is also demonstrated from image processing applications that the de-blurring method can improve the accuracy and the stability of the digital imaging correlation measurement.

Image annotation based on positive-negative instances learning

NASA Astrophysics Data System (ADS)

Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.

Noise-immune complex correlation for vasculature imaging based on standard and Jones-matrix optical coherence tomography

NASA Astrophysics Data System (ADS)

Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Li, En; Miura, Masahiro; Yasuno, Yoshiaki

2016-03-01

A new optical coherence angiography (OCA) method, called correlation mapping OCA (cmOCA), is presented by using the SNR-corrected complex correlation. An SNR-correction theory for the complex correlation calculation is presented. The method also integrates a motion-artifact-removal method for the sample motion induced decorrelation artifact. The theory is further extended to compute more reliable correlation by using multi- channel OCT systems, such as Jones-matrix OCT. The high contrast vasculature imaging of in vivo human posterior eye has been obtained. Composite imaging of cmOCA and degree of polarization uniformity indicates abnormalities of vasculature and pigmented tissues simultaneously.

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method

PubMed Central

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters – TCCF, Tθ, Tx and Ty are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images. PMID:26601045

Fired Cartridge Case Identification Using Optical Images and the Congruent Matching Cells (CMC) Method.

PubMed

Tong, Mingsi; Song, John; Chu, Wei; Thompson, Robert M

2014-01-01

The Congruent Matching Cells (CMC) method for ballistics identification was invented at the National Institute of Standards and Technology (NIST). The CMC method is based on the correlation of pairs of small correlation cells instead of the correlation of entire images. Four identification parameters - T CCF, T θ, T x and T y are proposed for identifying correlated cell pairs originating from the same firearm. The correlation conclusion (matching or non-matching) is determined by whether the number of CMC is ≥ 6. This method has been previously validated using a set of 780 pair-wise 3D topography images. However, most ballistic images stored in current local and national databases are in an optical intensity (grayscale) format. As a result, the reliability of applying the CMC method on optical intensity images is an important issue. In this paper, optical intensity images of breech face impressions captured on the same set of 40 cartridge cases are correlated and analyzed for the validation test of CMC method using optical images. This includes correlations of 63 pairs of matching images and 717 pairs of non-matching images under top ring lighting. Tests of the method do not produce any false identification (false positive) or false exclusion (false negative) results, which support the CMC method and the proposed identification criterion, C = 6, for firearm breech face identifications using optical intensity images.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography).

PubMed

Siegel, Nisan; Storrie, Brian; Bruce, Marc; Brooker, Gary

2015-02-07

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called "CINCH". An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution.

Model-based vision for space applications

NASA Technical Reports Server (NTRS)

Chaconas, Karen; Nashman, Marilyn; Lumia, Ronald

1992-01-01

This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.

Automated method and system for the alignment and correlation of images from two different modalities

DOEpatents

Giger, Maryellen L.; Chen, Chin-Tu; Armato, Samuel; Doi, Kunio

1999-10-26

A method and system for the computerized registration of radionuclide images with radiographic images, including generating image data from radiographic and radionuclide images of the thorax. Techniques include contouring the lung regions in each type of chest image, scaling and registration of the contours based on location of lung apices, and superimposition after appropriate shifting of the images. Specific applications are given for the automated registration of radionuclide lungs scans with chest radiographs. The method in the example given yields a system that spatially registers and correlates digitized chest radiographs with V/Q scans in order to correlate V/Q functional information with the greater structural detail of chest radiographs. Final output could be the computer-determined contours from each type of image superimposed on any of the original images, or superimposition of the radionuclide image data, which contains high activity, onto the radiographic chest image.

Toward a perceptual image quality assessment of color quantized images

NASA Astrophysics Data System (ADS)

Frackiewicz, Mariusz; Palus, Henryk

2018-04-01

Color image quantization is an important operation in the field of color image processing. In this paper, we consider new perceptual image quality metrics for assessment of quantized images. These types of metrics, e.g. DSCSI, MDSIs, MDSIm and HPSI achieve the highest correlation coefficients with MOS during tests on the six publicly available image databases. Research was limited to images distorted by two types of compression: JPG and JPG2K. Statistical analysis of correlation coefficients based on the Friedman test and post-hoc procedures showed that the differences between the four new perceptual metrics are not statistically significant.

New perspectives in face correlation: discrimination enhancement in face recognition based on iterative algorithm

NASA Astrophysics Data System (ADS)

Wang, Q.; Alfalou, A.; Brosseau, C.

2016-04-01

Here, we report a brief review on the recent developments of correlation algorithms. Several implementation schemes and specific applications proposed in recent years are also given to illustrate powerful applications of these methods. Following a discussion and comparison of the implementation of these schemes, we believe that all-numerical implementation is the most practical choice for application of the correlation method because the advantages of optical processing cannot compensate the technical and/or financial cost needed for an optical implementation platform. We also present a simple iterative algorithm to optimize the training images of composite correlation filters. By making use of three or four iterations, the peak-to-correlation energy (PCE) value of correlation plane can be significantly enhanced. A simulation test using the Pointing Head Pose Image Database (PHPID) illustrates the effectiveness of this statement. Our method can be applied in many composite filters based on linear composition of training images as an optimization means.

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

Automatic Methods in Image Processing and Their Relevance to Map-Making.

DTIC Science & Technology

1981-02-11

23b) and ECfg ) = DC1 1 reIc (5-24) Is an example, let the image function f be white noise so that Cf( ) = s, ,), the Dirac impulse . Then (5-24...based on image and correlator models which describe the behavior of correlation processors under condi- tions of low image contrast or signal-to- noise ...71 Sensor Noise ......................... 74 Self Noise .7.................. 6 Ma chine Noise ................ 81 Fixed Point Processing

Evaluation method based on the image correlation for laser jamming image

NASA Astrophysics Data System (ADS)

Che, Jinxi; Li, Zhongmin; Gao, Bo

2013-09-01

The jamming effectiveness evaluation of infrared imaging system is an important part of electro-optical countermeasure. The infrared imaging devices in the military are widely used in the searching, tracking and guidance and so many other fields. At the same time, with the continuous development of laser technology, research of laser interference and damage effect developed continuously, laser has been used to disturbing the infrared imaging device. Therefore, the effect evaluation of the infrared imaging system by laser has become a meaningful problem to be solved. The information that the infrared imaging system ultimately present to the user is an image, so the evaluation on jamming effect can be made from the point of assessment of image quality. The image contains two aspects of the information, the light amplitude and light phase, so the image correlation can accurately perform the difference between the original image and disturbed image. In the paper, the evaluation method of digital image correlation, the assessment method of image quality based on Fourier transform, the estimate method of image quality based on error statistic and the evaluation method of based on peak signal noise ratio are analysed. In addition, the advantages and disadvantages of these methods are analysed. Moreover, the infrared disturbing images of the experiment result, in which the thermal infrared imager was interfered by laser, were analysed by using these methods. The results show that the methods can better reflect the jamming effects of the infrared imaging system by laser. Furthermore, there is good consistence between evaluation results by using the methods and the results of subjective visual evaluation. And it also provides well repeatability and convenient quantitative analysis. The feasibility of the methods to evaluate the jamming effect was proved. It has some extent reference value for the studying and developing on electro-optical countermeasures equipments and effectiveness evaluation.

Invariant Feature Matching for Image Registration Application Based on New Dissimilarity of Spatial Features

PubMed Central

Mousavi Kahaki, Seyed Mostafa; Nordin, Md Jan; Ashtari, Amir H.; J. Zahra, Sophia

2016-01-01

An invariant feature matching method is proposed as a spatially invariant feature matching approach. Deformation effects, such as affine and homography, change the local information within the image and can result in ambiguous local information pertaining to image points. New method based on dissimilarity values, which measures the dissimilarity of the features through the path based on Eigenvector properties, is proposed. Evidence shows that existing matching techniques using similarity metrics—such as normalized cross-correlation, squared sum of intensity differences and correlation coefficient—are insufficient for achieving adequate results under different image deformations. Thus, new descriptor’s similarity metrics based on normalized Eigenvector correlation and signal directional differences, which are robust under local variation of the image information, are proposed to establish an efficient feature matching technique. The method proposed in this study measures the dissimilarity in the signal frequency along the path between two features. Moreover, these dissimilarity values are accumulated in a 2D dissimilarity space, allowing accurate corresponding features to be extracted based on the cumulative space using a voting strategy. This method can be used in image registration applications, as it overcomes the limitations of the existing approaches. The output results demonstrate that the proposed technique outperforms the other methods when evaluated using a standard dataset, in terms of precision-recall and corner correspondence. PMID:26985996

Proposed alteration of images of molecular orbitals obtained using a scanning tunneling microscope as a probe of electron correlation.

PubMed

Toroz, Dimitrios; Rontani, Massimo; Corni, Stefano

2013-01-04

Scanning tunneling spectroscopy (STS) allows us to image single molecules decoupled from the supporting substrate. The obtained images are routinely interpreted as the square moduli of molecular orbitals, dressed by the mean-field electron-electron interaction. Here we demonstrate that the effect of electron correlation beyond the mean field qualitatively alters the uncorrelated STS images. Our evidence is based on the ab initio many-body calculation of STS images of planar molecules with metal centers. We find that many-body correlations alter significantly the image spectral weight close to the metal center of the molecules. This change is large enough to be accessed experimentally, surviving to molecule-substrate interactions.

Diffractive-optical correlators: chances to make optical image preprocessing as intelligent as human vision

NASA Astrophysics Data System (ADS)

Lauinger, Norbert

2004-10-01

The human eye is a good model for the engineering of optical correlators. Three prominent intelligent functionalities in human vision could in the near future become realized by a new diffractive-optical hardware design of optical imaging sensors: (1) Illuminant-adaptive RGB-based color Vision, (2) Monocular 3D Vision based on RGB data processing, (3) Patchwise fourier-optical Object-Classification and Identification. The hardware design of the human eye has specific diffractive-optical elements (DOE's) in aperture and in image space and seems to execute the three jobs at -- or not far behind -- the loci of the images of objects.

Detection of correlated fragments in a sequence of images by superimposed Fourier holograms

NASA Astrophysics Data System (ADS)

Pavlov, A. V.

2016-08-01

The problem of detecting correlated fragments in a sequence of images recorded by the superimposing holograms within the Fourier holography scheme with angular multiplication of a spatially modulated reference beam is considered. The approach to the solution of this problem is based on the properties of the variance of the image sum. It is shown that this problem can be solved by providing a constant distance between the signal and reference images when recording superimposed holograms and a partial mutual correlatedness of reference images. The detection efficiency is analysed from the point of view of estimated image data capacity, the degree of mutual correlation of reference images, and the hologram recording conditions. The results of a numerical experiment under the most complicated conditions (representation of images by realisations of homogeneous random fields) confirm the theoretical conclusions.

Measurement of the Young's modulus of thin or flexible specimen with digital-image correlation method

NASA Astrophysics Data System (ADS)

Xu, Lianyun; Hou, Zhende; Qin, Yuwen

2002-05-01

Because some composite material, thin film material, and biomaterial, are very thin and some of them are flexible, the classical methods for measuring their Young's moduli, by mounting extensometers on specimens, are not available. A bi-image method based on image correlation for measuring Young's moduli is developed in this paper. The measuring precision achieved is one order enhanced with general digital image correlation or called single image method. By this way, the Young's modulus of a SS301 stainless steel thin tape, with thickness 0.067mm, is measured, and the moduli of polyester fiber films, a kind of flexible sheet with thickness 0.25 mm, are also measured.

In vivo spatial correlation between (18)F-BPA and (18)F-FDG uptakes in head and neck cancer.

PubMed

Kobayashi, Kazuma; Kurihara, Hiroaki; Watanabe, Yoshiaki; Murakami, Naoya; Inaba, Koji; Nakamura, Satoshi; Wakita, Akihisa; Okamoto, Hiroyuki; Umezawa, Rei; Takahashi, Kana; Igaki, Hiroshi; Ito, Yoshinori; Yoshimoto, Seiichi; Shigematsu, Naoyuki; Itami, Jun

2016-09-01

Borono-2-(18)F-fluoro-phenylalanine ((18)F-BPA) has been used to estimate the therapeutic effects of boron neutron capture therapy (BNCT), while (18)F-fluorodeoxyglucose ((18)F-FDG) is the most commonly used positron emission tomography (PET) radiopharmaceutical in a routine clinical use. The aim of the present study was to evaluate spatial correlation between (18)F-BPA and (18)F-FDG uptakes using a deformable image registration-based technique. Ten patients with head and neck cancer were recruited from January 2014 to December 2014. All patients underwent whole-body (18)F-BPA PET/computed tomography (CT) and (18)F-FDG PET/CT within a 2-week period. For each patient, (18)F-BPA PET/CT and (18)F-FDG PET/CT images were aligned based on a deformable image registration framework. The voxel-by-voxel spatial correlation of standardized uptake value (SUV) within the tumor was analyzed. Our image processing framework achieved accurate and validated registration results for each PET/CT image. In 9/10 patients, the spatial distribution of SUVs between (18)F-BPA and (18)F-FDG showed a significant, positive correlation in the tumor volume. Deformable image registration-based voxel-wise analysis demonstrated a spatial correlation between (18)F-BPA and (18)F-FDG uptakes in the head and neck cancer. A tumor sub-volume with a high (18)F-FDG uptake may predict high accumulation of (18)F-BPA. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Plus Disease in Retinopathy of Prematurity: Improving Diagnosis by Ranking Disease Severity and Using Quantitative Image Analysis.

PubMed

Kalpathy-Cramer, Jayashree; Campbell, J Peter; Erdogmus, Deniz; Tian, Peng; Kedarisetti, Dharanish; Moleta, Chace; Reynolds, James D; Hutcheson, Kelly; Shapiro, Michael J; Repka, Michael X; Ferrone, Philip; Drenser, Kimberly; Horowitz, Jason; Sonmez, Kemal; Swan, Ryan; Ostmo, Susan; Jonas, Karyn E; Chan, R V Paul; Chiang, Michael F

2016-11-01

To determine expert agreement on relative retinopathy of prematurity (ROP) disease severity and whether computer-based image analysis can model relative disease severity, and to propose consideration of a more continuous severity score for ROP. We developed 2 databases of clinical images of varying disease severity (100 images and 34 images) as part of the Imaging and Informatics in ROP (i-ROP) cohort study and recruited expert physician, nonexpert physician, and nonphysician graders to classify and perform pairwise comparisons on both databases. Six participating expert ROP clinician-scientists, each with a minimum of 10 years of clinical ROP experience and 5 ROP publications, and 5 image graders (3 physicians and 2 nonphysician graders) who analyzed images that were obtained during routine ROP screening in neonatal intensive care units. Images in both databases were ranked by average disease classification (classification ranking), by pairwise comparison using the Elo rating method (comparison ranking), and by correlation with the i-ROP computer-based image analysis system. Interexpert agreement (weighted κ statistic) compared with the correlation coefficient (CC) between experts on pairwise comparisons and correlation between expert rankings and computer-based image analysis modeling. There was variable interexpert agreement on diagnostic classification of disease (plus, preplus, or normal) among the 6 experts (mean weighted κ, 0.27; range, 0.06-0.63), but good correlation between experts on comparison ranking of disease severity (mean CC, 0.84; range, 0.74-0.93) on the set of 34 images. Comparison ranking provided a severity ranking that was in good agreement with ranking obtained by classification ranking (CC, 0.92). Comparison ranking on the larger dataset by both expert and nonexpert graders demonstrated good correlation (mean CC, 0.97; range, 0.95-0.98). The i-ROP system was able to model this continuous severity with good correlation (CC, 0.86). Experts diagnose plus disease on a continuum, with poor absolute agreement on classification but good relative agreement on disease severity. These results suggest that the use of pairwise rankings and a continuous severity score, such as that provided by the i-ROP system, may improve agreement on disease severity in the future. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography)

PubMed Central

Siegel, Nisan; Storrie, Brian; Bruce, Marc

2016-01-01

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called “CINCH”. An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution. PMID:26839443

Colour image compression by grey to colour conversion

NASA Astrophysics Data System (ADS)

Drew, Mark S.; Finlayson, Graham D.; Jindal, Abhilash

2011-03-01

Instead of de-correlating image luminance from chrominance, some use has been made of using the correlation between the luminance component of an image and its chromatic components, or the correlation between colour components, for colour image compression. In one approach, the Green colour channel was taken as a base, and the other colour channels or their DCT subbands were approximated as polynomial functions of the base inside image windows. This paper points out that we can do better if we introduce an addressing scheme into the image description such that similar colours are grouped together spatially. With a Luminance component base, we test several colour spaces and rearrangement schemes, including segmentation. and settle on a log-geometric-mean colour space. Along with PSNR versus bits-per-pixel, we found that spatially-keyed s-CIELAB colour error better identifies problem regions. Instead of segmentation, we found that rearranging on sorted chromatic components has almost equal performance and better compression. Here, we sort on each of the chromatic components and separately encode windows of each. The result consists of the original greyscale plane plus the polynomial coefficients of windows of rearranged chromatic values, which are then quantized. The simplicity of the method produces a fast and simple scheme for colour image and video compression, with excellent results.

Efficient Solar Scene Wavefront Estimation with Reduced Systematic and RMS Errors: Summary

NASA Astrophysics Data System (ADS)

Anugu, N.; Garcia, P.

2016-04-01

Wave front sensing for solar telescopes is commonly implemented with the Shack-Hartmann sensors. Correlation algorithms are usually used to estimate the extended scene Shack-Hartmann sub-aperture image shifts or slopes. The image shift is computed by correlating a reference sub-aperture image with the target distorted sub-aperture image. The pixel position where the maximum correlation is located gives the image shift in integer pixel coordinates. Sub-pixel precision image shifts are computed by applying a peak-finding algorithm to the correlation peak Poyneer (2003); Löfdahl (2010). However, the peak-finding algorithm results are usually biased towards the integer pixels, these errors are called as systematic bias errors Sjödahl (1994). These errors are caused due to the low pixel sampling of the images. The amplitude of these errors depends on the type of correlation algorithm and the type of peak-finding algorithm being used. To study the systematic errors in detail, solar sub-aperture synthetic images are constructed by using a Swedish Solar Telescope solar granulation image1. The performance of cross-correlation algorithm in combination with different peak-finding algorithms is investigated. The studied peak-finding algorithms are: parabola Poyneer (2003); quadratic polynomial Löfdahl (2010); threshold center of gravity Bailey (2003); Gaussian Nobach & Honkanen (2005) and Pyramid Bailey (2003). The systematic error study reveals that that the pyramid fit is the most robust to pixel locking effects. The RMS error analysis study reveals that the threshold centre of gravity behaves better in low SNR, although the systematic errors in the measurement are large. It is found that no algorithm is best for both the systematic and the RMS error reduction. To overcome the above problem, a new solution is proposed. In this solution, the image sampling is increased prior to the actual correlation matching. The method is realized in two steps to improve its computational efficiency. In the first step, the cross-correlation is implemented at the original image spatial resolution grid (1 pixel). In the second step, the cross-correlation is performed using a sub-pixel level grid by limiting the field of search to 4 × 4 pixels centered at the first step delivered initial position. The generation of these sub-pixel grid based region of interest images is achieved with the bi-cubic interpolation. The correlation matching with sub-pixel grid technique was previously reported in electronic speckle photography Sjö'dahl (1994). This technique is applied here for the solar wavefront sensing. A large dynamic range and a better accuracy in the measurements are achieved with the combination of the original pixel grid based correlation matching in a large field of view and a sub-pixel interpolated image grid based correlation matching within a small field of view. The results revealed that the proposed method outperforms all the different peak-finding algorithms studied in the first approach. It reduces both the systematic error and the RMS error by a factor of 5 (i.e., 75% systematic error reduction), when 5 times improved image sampling was used. This measurement is achieved at the expense of twice the computational cost. With the 5 times improved image sampling, the wave front accuracy is increased by a factor of 5. The proposed solution is strongly recommended for wave front sensing in the solar telescopes, particularly, for measuring large dynamic image shifts involved open loop adaptive optics. Also, by choosing an appropriate increment of image sampling in trade-off between the computational speed limitation and the aimed sub-pixel image shift accuracy, it can be employed in closed loop adaptive optics. The study is extended to three other class of sub-aperture images (a point source; a laser guide star; a Galactic Center extended scene). The results are planned to submit for the Optical Express journal.

Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging.

PubMed

Pertuz, Said; McDonald, Elizabeth S; Weinstein, Susan P; Conant, Emily F; Kontos, Despina

2016-04-01

To assess a fully automated method for volumetric breast density (VBD) estimation in digital breast tomosynthesis (DBT) and to compare the findings with those of full-field digital mammography (FFDM) and magnetic resonance (MR) imaging. Bilateral DBT images, FFDM images, and sagittal breast MR images were retrospectively collected from 68 women who underwent breast cancer screening from October 2011 to September 2012 with institutional review board-approved, HIPAA-compliant protocols. A fully automated computer algorithm was developed for quantitative estimation of VBD from DBT images. FFDM images were processed with U.S. Food and Drug Administration-cleared software, and the MR images were processed with a previously validated automated algorithm to obtain corresponding VBD estimates. Pearson correlation and analysis of variance with Tukey-Kramer post hoc correction were used to compare the multimodality VBD estimates. Estimates of VBD from DBT were significantly correlated with FFDM-based and MR imaging-based estimates with r = 0.83 (95% confidence interval [CI]: 0.74, 0.90) and r = 0.88 (95% CI: 0.82, 0.93), respectively (P < .001). The corresponding correlation between FFDM and MR imaging was r = 0.84 (95% CI: 0.76, 0.90). However, statistically significant differences after post hoc correction (α = 0.05) were found among VBD estimates from FFDM (mean ± standard deviation, 11.1% ± 7.0) relative to MR imaging (16.6% ± 11.2) and DBT (19.8% ± 16.2). Differences between VDB estimates from DBT and MR imaging were not significant (P = .26). Fully automated VBD estimates from DBT, FFDM, and MR imaging are strongly correlated but show statistically significant differences. Therefore, absolute differences in VBD between FFDM, DBT, and MR imaging should be considered in breast cancer risk assessment.

Tensor Fukunaga-Koontz transform for small target detection in infrared images

NASA Astrophysics Data System (ADS)

Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli

2016-09-01

Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.

Image features dependant correlation-weighting function for efficient PRNU based source camera identification.

PubMed

Tiwari, Mayank; Gupta, Bhupendra

2018-04-01

For source camera identification (SCI), photo response non-uniformity (PRNU) has been widely used as the fingerprint of the camera. The PRNU is extracted from the image by applying a de-noising filter then taking the difference between the original image and the de-noised image. However, it is observed that intensity-based features and high-frequency details (edges and texture) of the image, effect quality of the extracted PRNU. This effects correlation calculation and creates problems in SCI. For solving this problem, we propose a weighting function based on image features. We have experimentally identified image features (intensity and high-frequency contents) effect on the estimated PRNU, and then develop a weighting function which gives higher weights to image regions which give reliable PRNU and at the same point it gives comparatively less weights to the image regions which do not give reliable PRNU. Experimental results show that the proposed weighting function is able to improve the accuracy of SCI up to a great extent. Copyright © 2018 Elsevier B.V. All rights reserved.

A convergence algorithm for correlation of breech face images based on the congruent matching cells (CMC) method.

PubMed

Chen, Zhe; Song, John; Chu, Wei; Soons, Johannes A; Zhao, Xuezeng

2017-11-01

The Congruent Matching Cells (CMC) method was invented at the National Institute of Standards and Technology (NIST) for accurate firearm evidence identification and error rate estimation. The CMC method is based on the principle of discretization. The toolmark image of the reference sample is divided into correlation cells. Each cell is registered to the cell-sized area of the compared image that has maximum surface topography similarity. For each resulting cell pair, one parameter quantifies the similarity of the cell surface topography and three parameters quantify the pattern congruency of the registration position and orientation. An identification (declared match) requires a significant number of CMCs, that is, cell pairs that meet both similarity and pattern congruency requirements. The use of cell correlations reduces the effects of "invalid regions" in the compared image pairs and increases the correlation accuracy. The identification accuracy of the CMC method can be further improved by considering a feature named "convergence," that is, the tendency of the x-y registration positions of the correlated cell pairs to converge at the correct registration angle when comparing same-source samples at different relative orientations. In this paper, the difference of the convergence feature between known matching (KM) and known non-matching (KNM) image pairs is characterized, based on which an improved algorithm is developed for breech face image correlations using the CMC method. Its advantage is demonstrated by comparison with three existing CMC algorithms using four datasets. The datasets address three different brands of consecutively manufactured pistol slides, with significant differences in the distribution overlap of cell pair topography similarity for KM and KNM image pairs. For the same CMC threshold values, the convergence algorithm demonstrates noticeably improved results by reducing the number of false-positive or false-negative CMCs in a comparison. Published by Elsevier B.V.

A Query Expansion Framework in Image Retrieval Domain Based on Local and Global Analysis

PubMed Central

Rahman, M. M.; Antani, S. K.; Thoma, G. R.

2011-01-01

We present an image retrieval framework based on automatic query expansion in a concept feature space by generalizing the vector space model of information retrieval. In this framework, images are represented by vectors of weighted concepts similar to the keyword-based representation used in text retrieval. To generate the concept vocabularies, a statistical model is built by utilizing Support Vector Machine (SVM)-based classification techniques. The images are represented as “bag of concepts” that comprise perceptually and/or semantically distinguishable color and texture patches from local image regions in a multi-dimensional feature space. To explore the correlation between the concepts and overcome the assumption of feature independence in this model, we propose query expansion techniques in the image domain from a new perspective based on both local and global analysis. For the local analysis, the correlations between the concepts based on the co-occurrence pattern, and the metrical constraints based on the neighborhood proximity between the concepts in encoded images, are analyzed by considering local feedback information. We also analyze the concept similarities in the collection as a whole in the form of a similarity thesaurus and propose an efficient query expansion based on the global analysis. The experimental results on a photographic collection of natural scenes and a biomedical database of different imaging modalities demonstrate the effectiveness of the proposed framework in terms of precision and recall. PMID:21822350

Joint reconstruction of multiview compressed images.

PubMed

Thirumalai, Vijayaraghavan; Frossard, Pascal

2013-05-01

Distributed representation of correlated multiview images is an important problem that arises in vision sensor networks. This paper concentrates on the joint reconstruction problem where the distributively compressed images are decoded together in order to take benefit from the image correlation. We consider a scenario where the images captured at different viewpoints are encoded independently using common coding solutions (e.g., JPEG) with a balanced rate distribution among different cameras. A central decoder first estimates the inter-view image correlation from the independently compressed data. The joint reconstruction is then cast as a constrained convex optimization problem that reconstructs total-variation (TV) smooth images, which comply with the estimated correlation model. At the same time, we add constraints that force the reconstructed images to be as close as possible to their compressed versions. We show through experiments that the proposed joint reconstruction scheme outperforms independent reconstruction in terms of image quality, for a given target bit rate. In addition, the decoding performance of our algorithm compares advantageously to state-of-the-art distributed coding schemes based on motion learning and on the DISCOVER algorithm.

Symmetric Phase Only Filtering for Improved DPIV Data Processing

NASA Technical Reports Server (NTRS)

Wernet, Mark P.

2006-01-01

The standard approach in Digital Particle Image Velocimetry (DPIV) data processing is to use Fast Fourier Transforms to obtain the cross-correlation of two single exposure subregions, where the location of the cross-correlation peak is representative of the most probable particle displacement across the subregion. This standard DPIV processing technique is analogous to Matched Spatial Filtering, a technique commonly used in optical correlators to perform the crosscorrelation operation. Phase only filtering is a well known variation of Matched Spatial Filtering, which when used to process DPIV image data yields correlation peaks which are narrower and up to an order of magnitude larger than those obtained using traditional DPIV processing. In addition to possessing desirable correlation plane features, phase only filters also provide superior performance in the presence of DC noise in the correlation subregion. When DPIV image subregions contaminated with surface flare light or high background noise levels are processed using phase only filters, the correlation peak pertaining only to the particle displacement is readily detected above any signal stemming from the DC objects. Tedious image masking or background image subtraction are not required. Both theoretical and experimental analyses of the signal-to-noise ratio performance of the filter functions are presented. In addition, a new Symmetric Phase Only Filtering (SPOF) technique, which is a variation on the traditional phase only filtering technique, is described and demonstrated. The SPOF technique exceeds the performance of the traditionally accepted phase only filtering techniques and is easily implemented in standard DPIV FFT based correlation processing with no significant computational performance penalty. An "Automatic" SPOF algorithm is presented which determines when the SPOF is able to provide better signal to noise results than traditional PIV processing. The SPOF based optical correlation processing approach is presented as a new paradigm for more robust cross-correlation processing of low signal-to-noise ratio DPIV image data."

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lamichhane, N; Johnson, P; Chinea, F

Purpose: To evaluate the correlation between image features and the accuracy of manually drawn target contours on synthetic PET images Methods: A digital PET phantom was used in combination with Monte Carlo simulation to create a set of 26 simulated PET images featuring a variety of tumor shapes and activity heterogeneity. These tumor volumes were used as a gold standard in comparisons with manual contours delineated by 10 radiation oncologist on the simulated PET images. Metrics used to evaluate segmentation accuracy included the dice coefficient, false positive dice, false negative dice, symmetric mean absolute surface distance, and absolute volumetric difference.more » Image features extracted from the simulated tumors consisted of volume, shape complexity, mean curvature, and intensity contrast along with five texture features derived from the gray-level neighborhood difference matrices including contrast, coarseness, busyness, strength, and complexity. Correlation between these features and contouring accuracy were examined. Results: Contour accuracy was reasonably well correlated with a variety of image features. Dice coefficient ranged from 0.7 to 0.90 and was correlated closely with contrast (r=0.43, p=0.02) and complexity (r=0.5, p<0.001). False negative dice ranged from 0.10 to 0.50 and was correlated closely with contrast (r=0.68, p<0.001) and complexity (r=0.66, p<0.001). Absolute volumetric difference ranged from 0.0002 to 0.67 and was correlated closely with coarseness (r=0.46, p=0.02) and complexity (r=0.49, p=0.008). Symmetric mean absolute difference ranged from 0.02 to 1 and was correlated closely with mean curvature (r=0.57, p=0.02) and contrast (r=0.6, p=0.001). Conclusion: The long term goal of this study is to assess whether contouring variability can be reduced by providing feedback to the practitioner based on image feature analysis. The results are encouraging and will be used to develop a statistical model which will enable a prediction of contour accuracy based purely on image feature analysis.« less

Community detection for fluorescent lifetime microscopy image segmentation

NASA Astrophysics Data System (ADS)

Hu, Dandan; Sarder, Pinaki; Ronhovde, Peter; Achilefu, Samuel; Nussinov, Zohar

2014-03-01

Multiresolution community detection (CD) method has been suggested in a recent work as an efficient method for performing unsupervised segmentation of fluorescence lifetime (FLT) images of live cell images containing fluorescent molecular probes.1 In the current paper, we further explore this method in FLT images of ex vivo tissue slices. The image processing problem is framed as identifying clusters with respective average FLTs against a background or "solvent" in FLT imaging microscopy (FLIM) images derived using NIR fluorescent dyes. We have identified significant multiresolution structures using replica correlations in these images, where such correlations are manifested by information theoretic overlaps of the independent solutions ("replicas") attained using the multiresolution CD method from different starting points. In this paper, our method is found to be more efficient than a current state-of-the-art image segmentation method based on mixture of Gaussian distributions. It offers more than 1:25 times diversity based on Shannon index than the latter method, in selecting clusters with distinct average FLTs in NIR FLIM images.

Pseudo color ghost coding imaging with pseudo thermal light

NASA Astrophysics Data System (ADS)

Duan, De-yang; Xia, Yun-jie

2018-04-01

We present a new pseudo color imaging scheme named pseudo color ghost coding imaging based on ghost imaging but with multiwavelength source modulated by a spatial light modulator. Compared with conventional pseudo color imaging where there is no nondegenerate wavelength spatial correlations resulting in extra monochromatic images, the degenerate wavelength and nondegenerate wavelength spatial correlations between the idle beam and signal beam can be obtained simultaneously. This scheme can obtain more colorful image with higher quality than that in conventional pseudo color coding techniques. More importantly, a significant advantage of the scheme compared to the conventional pseudo color coding imaging techniques is the image with different colors can be obtained without changing the light source and spatial filter.

Correlative Microscopy Combining Secondary Ion Mass Spectrometry and Electron Microscopy: Comparison of Intensity-Hue-Saturation and Laplacian Pyramid Methods for Image Fusion.

PubMed

Vollnhals, Florian; Audinot, Jean-Nicolas; Wirtz, Tom; Mercier-Bonin, Muriel; Fourquaux, Isabelle; Schroeppel, Birgit; Kraushaar, Udo; Lev-Ram, Varda; Ellisman, Mark H; Eswara, Santhana

2017-10-17

Correlative microscopy combining various imaging modalities offers powerful insights into obtaining a comprehensive understanding of physical, chemical, and biological phenomena. In this article, we investigate two approaches for image fusion in the context of combining the inherently lower-resolution chemical images obtained using secondary ion mass spectrometry (SIMS) with the high-resolution ultrastructural images obtained using electron microscopy (EM). We evaluate the image fusion methods with three different case studies selected to broadly represent the typical samples in life science research: (i) histology (unlabeled tissue), (ii) nanotoxicology, and (iii) metabolism (isotopically labeled tissue). We show that the intensity-hue-saturation fusion method often applied for EM-sharpening can result in serious image artifacts, especially in cases where different contrast mechanisms interplay. Here, we introduce and demonstrate Laplacian pyramid fusion as a powerful and more robust alternative method for image fusion. Both physical and technical aspects of correlative image overlay and image fusion specific to SIMS-based correlative microscopy are discussed in detail alongside the advantages, limitations, and the potential artifacts. Quantitative metrics to evaluate the results of image fusion are also discussed.

Sensor-based auto-focusing system using multi-scale feature extraction and phase correlation matching.

PubMed

Jang, Jinbeum; Yoo, Yoonjong; Kim, Jongheon; Paik, Joonki

2015-03-10

This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. The proposed auto-focusing (AF) algorithm consists of four steps: (i) acquisition of left and right images using AF points in the region-of-interest; (ii) feature extraction in the left image under low illumination and out-of-focus blur; (iii) the generation of two feature images using the phase difference between the left and right images; and (iv) estimation of the phase shifting vector using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide faster, more robust auto focusing than existing systems.

Sensor-Based Auto-Focusing System Using Multi-Scale Feature Extraction and Phase Correlation Matching

PubMed Central

Jang, Jinbeum; Yoo, Yoonjong; Kim, Jongheon; Paik, Joonki

2015-01-01

This paper presents a novel auto-focusing system based on a CMOS sensor containing pixels with different phases. Robust extraction of features in a severely defocused image is the fundamental problem of a phase-difference auto-focusing system. In order to solve this problem, a multi-resolution feature extraction algorithm is proposed. Given the extracted features, the proposed auto-focusing system can provide the ideal focusing position using phase correlation matching. The proposed auto-focusing (AF) algorithm consists of four steps: (i) acquisition of left and right images using AF points in the region-of-interest; (ii) feature extraction in the left image under low illumination and out-of-focus blur; (iii) the generation of two feature images using the phase difference between the left and right images; and (iv) estimation of the phase shifting vector using phase correlation matching. Since the proposed system accurately estimates the phase difference in the out-of-focus blurred image under low illumination, it can provide faster, more robust auto focusing than existing systems. PMID:25763645

Improved Resolution and Reduced Clutter in Ultra-Wideband Microwave Imaging Using Cross-Correlated Back Projection: Experimental and Numerical Results

PubMed Central

Jacobsen, S.; Birkelund, Y.

2010-01-01

Microwave breast cancer detection is based on the dielectric contrast between healthy and malignant tissue. This radar-based imaging method involves illumination of the breast with an ultra-wideband pulse. Detection of tumors within the breast is achieved by some selected focusing technique. Image formation algorithms are tailored to enhance tumor responses and reduce early-time and late-time clutter associated with skin reflections and heterogeneity of breast tissue. In this contribution, we evaluate the performance of the so-called cross-correlated back projection imaging scheme by using a scanning system in phantom experiments. Supplementary numerical modeling based on commercial software is also presented. The phantom is synthetically scanned with a broadband elliptical antenna in a mono-static configuration. The respective signals are pre-processed by a data-adaptive RLS algorithm in order to remove artifacts caused by antenna reverberations and signal clutter. Successful detection of a 7 mm diameter cylindrical tumor immersed in a low permittivity medium was achieved in all cases. Selecting the widely used delay-and-sum (DAS) beamforming algorithm as a benchmark, we show that correlation based imaging methods improve the signal-to-clutter ratio by at least 10 dB and improves spatial resolution through a reduction of the imaged peak full-width half maximum (FWHM) of about 40–50%. PMID:21331362

Improved resolution and reduced clutter in ultra-wideband microwave imaging using cross-correlated back projection: experimental and numerical results.

PubMed

Jacobsen, S; Birkelund, Y

2010-01-01

Microwave breast cancer detection is based on the dielectric contrast between healthy and malignant tissue. This radar-based imaging method involves illumination of the breast with an ultra-wideband pulse. Detection of tumors within the breast is achieved by some selected focusing technique. Image formation algorithms are tailored to enhance tumor responses and reduce early-time and late-time clutter associated with skin reflections and heterogeneity of breast tissue. In this contribution, we evaluate the performance of the so-called cross-correlated back projection imaging scheme by using a scanning system in phantom experiments. Supplementary numerical modeling based on commercial software is also presented. The phantom is synthetically scanned with a broadband elliptical antenna in a mono-static configuration. The respective signals are pre-processed by a data-adaptive RLS algorithm in order to remove artifacts caused by antenna reverberations and signal clutter. Successful detection of a 7 mm diameter cylindrical tumor immersed in a low permittivity medium was achieved in all cases. Selecting the widely used delay-and-sum (DAS) beamforming algorithm as a benchmark, we show that correlation based imaging methods improve the signal-to-clutter ratio by at least 10 dB and improves spatial resolution through a reduction of the imaged peak full-width half maximum (FWHM) of about 40-50%.

Multiscale Anomaly Detection and Image Registration Algorithms for Airborne Landmine Detection

DTIC Science & Technology

2008-05-01

with the sensed image. The two- dimensional correlation coefficient r for two matrices A and B both of size M ×N is given by r = ∑ m ∑ n (Amn...correlation based method by matching features in a high- dimensional feature- space . The current implementation of the SIFT algorithm uses a brute-force...by repeatedly convolving the image with a Guassian kernel. Each plane of the scale

Using phase information to enhance speckle noise reduction in the ultrasonic NDE of coarse grain materials

NASA Astrophysics Data System (ADS)

Lardner, Timothy; Li, Minghui; Gachagan, Anthony

2014-02-01

Materials with a coarse grain structure are becoming increasingly prevalent in industry due to their resilience to stress and corrosion. These materials are difficult to inspect with ultrasound because reflections from the grains lead to high noise levels which hinder the echoes of interest. Spatially Averaged Sub-Aperture Correlation Imaging (SASACI) is an advanced array beamforming technique that uses the cross-correlation between images from array sub-apertures to generate an image weighting matrix, in order to reduce noise levels. This paper presents a method inspired by SASACI to further improve imaging using phase information to refine focusing and reduce noise. A-scans from adjacent array elements are cross-correlated using both signal amplitude and phase to refine delay laws and minimize phase aberration. The phase-based and amplitude-based corrected images are used as inputs to a two-dimensional cross-correlation algorithm that will output a weighting matrix that can be applied to any conventional image. This approach was validated experimentally using a 5MHz array a coarse grained Inconel 625 step wedge, and compared to the Total Focusing Method (TFM). Initial results have seen SNR improvements of over 20dB compared to TFM, and a resolution that is much higher.

Weakly supervised image semantic segmentation based on clustering superpixels

NASA Astrophysics Data System (ADS)

Yan, Xiong; Liu, Xiaohua

2018-04-01

In this paper, we propose an image semantic segmentation model which is trained from image-level labeled images. The proposed model starts with superpixel segmenting, and features of the superpixels are extracted by trained CNN. We introduce a superpixel-based graph followed by applying the graph partition method to group correlated superpixels into clusters. For the acquisition of inter-label correlations between the image-level labels in dataset, we not only utilize label co-occurrence statistics but also exploit visual contextual cues simultaneously. At last, we formulate the task of mapping appropriate image-level labels to the detected clusters as a problem of convex minimization. Experimental results on MSRC-21 dataset and LableMe dataset show that the proposed method has a better performance than most of the weakly supervised methods and is even comparable to fully supervised methods.

A Method for the Alignment of Heterogeneous Macromolecules from Electron Microscopy

PubMed Central

Shatsky, Maxim; Hall, Richard J.; Brenner, Steven E.; Glaeser, Robert M.

2009-01-01

We propose a feature-based image alignment method for single-particle electron microscopy that is able to accommodate various similarity scoring functions while efficiently sampling the two-dimensional transformational space. We use this image alignment method to evaluate the performance of a scoring function that is based on the Mutual Information (MI) of two images rather than one that is based on the cross-correlation function. We show that alignment using MI for the scoring function has far less model-dependent bias than is found with cross-correlation based alignment. We also demonstrate that MI improves the alignment of some types of heterogeneous data, provided that the signal to noise ratio is relatively high. These results indicate, therefore, that use of MI as the scoring function is well suited for the alignment of class-averages computed from single particle images. Our method is tested on data from three model structures and one real dataset. PMID:19166941

Frequency Based Design Partitioning to Achieve Higher Throughput in Digital Cross Correlator for Aperture Synthesis Passive MMW Imager.

PubMed

Asif, Muhammad; Guo, Xiangzhou; Zhang, Jing; Miao, Jungang

2018-04-17

Digital cross-correlation is central to many applications including but not limited to Digital Image Processing, Satellite Navigation and Remote Sensing. With recent advancements in digital technology, the computational demands of such applications have increased enormously. In this paper we are presenting a high throughput digital cross correlator, capable of processing 1-bit digitized stream, at the rate of up to 2 GHz, simultaneously on 64 channels i.e., approximately 4 Trillion correlation and accumulation operations per second. In order to achieve higher throughput, we have focused on frequency based partitioning of our design and tried to minimize and localize high frequency operations. This correlator is designed for a Passive Millimeter Wave Imager intended for the detection of contraband items concealed on human body. The goals are to increase the system bandwidth, achieve video rate imaging, improve sensitivity and reduce the size. Design methodology is detailed in subsequent sections, elaborating the techniques enabling high throughput. The design is verified for Xilinx Kintex UltraScale device in simulation and the implementation results are given in terms of device utilization and power consumption estimates. Our results show considerable improvements in throughput as compared to our baseline design, while the correlator successfully meets the functional requirements.

Optical image hiding based on computational ghost imaging

NASA Astrophysics Data System (ADS)

Wang, Le; Zhao, Shengmei; Cheng, Weiwen; Gong, Longyan; Chen, Hanwu

2016-05-01

Imaging hiding schemes play important roles in now big data times. They provide copyright protections of digital images. In the paper, we propose a novel image hiding scheme based on computational ghost imaging to have strong robustness and high security. The watermark is encrypted with the configuration of a computational ghost imaging system, and the random speckle patterns compose a secret key. Least significant bit algorithm is adopted to embed the watermark and both the second-order correlation algorithm and the compressed sensing (CS) algorithm are used to extract the watermark. The experimental and simulation results show that the authorized users can get the watermark with the secret key. The watermark image could not be retrieved when the eavesdropping ratio is less than 45% with the second-order correlation algorithm, whereas it is less than 20% with the TVAL3 CS reconstructed algorithm. In addition, the proposed scheme is robust against the 'salt and pepper' noise and image cropping degradations.

Measurement of fluid rotation, dilation, and displacement in particle image velocimetry using a Fourier–Mellin cross-correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Giarra, Matthew N.; Charonko, John J.; Vlachos, Pavlos P.

Traditional particle image velocimetry (PIV) uses discrete Cartesian cross correlations (CCs) to estimate the displacements of groups of tracer particles within small subregions of sequentially captured images. However, these CCs fail in regions with large velocity gradients or high rates of rotation. In this paper, we propose a new PIV correlation method based on the Fourier–Mellin transformation (FMT) that enables direct measurement of the rotation and dilation of particle image patterns. In previously unresolvable regions of large rotation, our algorithm significantly improves the velocity estimates compared to traditional correlations by aligning the rotated and stretched particle patterns prior to performingmore » Cartesian correlations to estimate their displacements. Furthermore, our algorithm, which we term Fourier–Mellin correlation (FMC), reliably measures particle pattern displacement between pairs of interrogation regions with up to ±180° of angular misalignment, compared to 6–8° for traditional correlations, and dilation/compression factors of 0.5–2.0, compared to 0.9–1.1 for a single iteration of traditional correlations.« less

Measurement of fluid rotation, dilation, and displacement in particle image velocimetry using a Fourier–Mellin cross-correlation

DOE PAGES

Giarra, Matthew N.; Charonko, John J.; Vlachos, Pavlos P.

2015-02-05

Traditional particle image velocimetry (PIV) uses discrete Cartesian cross correlations (CCs) to estimate the displacements of groups of tracer particles within small subregions of sequentially captured images. However, these CCs fail in regions with large velocity gradients or high rates of rotation. In this paper, we propose a new PIV correlation method based on the Fourier–Mellin transformation (FMT) that enables direct measurement of the rotation and dilation of particle image patterns. In previously unresolvable regions of large rotation, our algorithm significantly improves the velocity estimates compared to traditional correlations by aligning the rotated and stretched particle patterns prior to performingmore » Cartesian correlations to estimate their displacements. Furthermore, our algorithm, which we term Fourier–Mellin correlation (FMC), reliably measures particle pattern displacement between pairs of interrogation regions with up to ±180° of angular misalignment, compared to 6–8° for traditional correlations, and dilation/compression factors of 0.5–2.0, compared to 0.9–1.1 for a single iteration of traditional correlations.« less

A novel iris patterns matching algorithm of weighted polar frequency correlation

NASA Astrophysics Data System (ADS)

Zhao, Weijie; Jiang, Linhua

2014-11-01

Iris recognition is recognized as one of the most accurate techniques for biometric authentication. In this paper, we present a novel correlation method - Weighted Polar Frequency Correlation(WPFC) - to match and evaluate two iris images, actually it can also be used for evaluating the similarity of any two images. The WPFC method is a novel matching and evaluating method for iris image matching, which is complete different from the conventional methods. For instance, the classical John Daugman's method of iris recognition uses 2D Gabor wavelets to extract features of iris image into a compact bit stream, and then matching two bit streams with hamming distance. Our new method is based on the correlation in the polar coordinate system in frequency domain with regulated weights. The new method is motivated by the observation that the pattern of iris that contains far more information for recognition is fine structure at high frequency other than the gross shapes of iris images. Therefore, we transform iris images into frequency domain and set different weights to frequencies. Then calculate the correlation of two iris images in frequency domain. We evaluate the iris images by summing the discrete correlation values with regulated weights, comparing the value with preset threshold to tell whether these two iris images are captured from the same person or not. Experiments are carried out on both CASIA database and self-obtained images. The results show that our method is functional and reliable. Our method provides a new prospect for iris recognition system.

Differential brain growth in the infant born preterm: current knowledge and future developments from brain imaging.

PubMed

Counsell, Serena J; Boardman, James P

2005-10-01

Preterm birth is associated with a high prevalence of neuropsychiatric impairment in childhood and adolescence, but the neural correlates underlying these disorders are not fully understood. Quantitative magnetic resonance imaging techniques have been used to investigate subtle differences in cerebral growth and development among children and adolescents born preterm or with very low birth weight. Diffusion tensor imaging and computer-assisted morphometric techniques (including voxel-based morphometry and deformation-based morphometry) have identified abnormalities in tissue microstructure and cerebral morphology among survivors of preterm birth at different ages, and some of these alterations have specific functional correlates. This chapter reviews the literature reporting differential brain development following preterm birth, with emphasis on the morphological changes that correlate with neuropsychiatric impairment.

Art for reward's sake: visual art recruits the ventral striatum.

PubMed

Lacey, Simon; Hagtvedt, Henrik; Patrick, Vanessa M; Anderson, Amy; Stilla, Randall; Deshpande, Gopikrishna; Hu, Xiaoping; Sato, João R; Reddy, Srinivas; Sathian, K

2011-03-01

A recent study showed that people evaluate products more positively when they are physically associated with art images than similar non-art images. Neuroimaging studies of visual art have investigated artistic style and esthetic preference but not brain responses attributable specifically to the artistic status of images. Here we tested the hypothesis that the artistic status of images engages reward circuitry, using event-related functional magnetic resonance imaging (fMRI) during viewing of art and non-art images matched for content. Subjects made animacy judgments in response to each image. Relative to non-art images, art images activated, on both subject- and item-wise analyses, reward-related regions: the ventral striatum, hypothalamus and orbitofrontal cortex. Neither response times nor ratings of familiarity or esthetic preference for art images correlated significantly with activity that was selective for art images, suggesting that these variables were not responsible for the art-selective activations. Investigation of effective connectivity, using time-varying, wavelet-based, correlation-purged Granger causality analyses, further showed that the ventral striatum was driven by visual cortical regions when viewing art images but not non-art images, and was not driven by regions that correlated with esthetic preference for either art or non-art images. These findings are consistent with our hypothesis, leading us to propose that the appeal of visual art involves activation of reward circuitry based on artistic status alone and independently of its hedonic value. Copyright © 2010 Elsevier Inc. All rights reserved.

ART FOR REWARD’S SAKE: VISUAL ART RECRUITS THE VENTRAL STRIATUM

PubMed Central

Lacey, Simon; Hagtvedt, Henrik; Patrick, Vanessa M.; Anderson, Amy; Stilla, Randall; Deshpande, Gopikrishna; Hu, Xiaoping; Sato, João R.; Reddy, Srinivas; Sathian, K.

2010-01-01

A recent study showed that people evaluate products more positively when they are physically associated with art images than similar non-art images. Neuroimaging studies of visual art have investigated artistic style and esthetic preference but not brain responses attributable specifically to the artistic status of images. Here we tested the hypothesis that the artistic status of images engages reward circuitry, using event-related functional magnetic resonance imaging (fMRI) during viewing of art and non-art images matched for content. Subjects made animacy judgments in response to each image. Relative to non-art images, art images activated, on both subject- and item-wise analyses, reward-related regions: the ventral striatum, hypothalamus and orbitofrontal cortex. Neither response times nor ratings of familiarity or esthetic preference for art images correlated significantly with activity that was selective for art images, suggesting that these variables were not responsible for the art-selective activations. Investigation of effective connectivity, using time-varying, wavelet-based, correlation-purged Granger causality analyses, further showed that the ventral striatum was driven by visual cortical regions when viewing art images but not non-art images, and was not driven by regions that correlated with esthetic preference for either art or non -art images. These findings are consistent with our hypothesis, leading us to propose that the appeal of visual art involves activation of reward circuitry based on artistic status alone and independently of its hedonic value. PMID:21111833

From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

PubMed

Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R

2014-10-01

Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall correlation>0.4). Clustering results are largely improved based on our anchor concept method (accuracy>70% and mutual information>80%). Physicians' spoken narratives are valuable for the purpose of mining the domain knowledge that physicians use in medical image inspections. We also show that the semantic metrics introduced in the paper can be successfully applied to medical image understanding and allow discussion of additional uses of these metrics. Copyright © 2014 Elsevier B.V. All rights reserved.

Two-dimensional confocal laser scanning microscopy image correlation for nanoparticle flow velocimetry

NASA Astrophysics Data System (ADS)

Jun, Brian; Giarra, Matthew; Golz, Brian; Main, Russell; Vlachos, Pavlos

2016-11-01

We present a methodology to mitigate the major sources of error associated with two-dimensional confocal laser scanning microscopy (CLSM) images of nanoparticles flowing through a microfluidic channel. The correlation-based velocity measurements from CLSM images are subject to random error due to the Brownian motion of nanometer-sized tracer particles, and a bias error due to the formation of images by raster scanning. Here, we develop a novel ensemble phase correlation with dynamic optimal filter that maximizes the correlation strength, which diminishes the random error. In addition, we introduce an analytical model of CLSM measurement bias error correction due to two-dimensional image scanning of tracer particles. We tested our technique using both synthetic and experimental images of nanoparticles flowing through a microfluidic channel. We observed that our technique reduced the error by up to a factor of ten compared to ensemble standard cross correlation (SCC) for the images tested in the present work. Subsequently, we will assess our framework further, by interrogating nanoscale flow in the cell culture environment (transport within the lacunar-canalicular system) to demonstrate our ability to accurately resolve flow measurements in a biological system.

A novel fractal image compression scheme with block classification and sorting based on Pearson's correlation coefficient.

PubMed

Wang, Jianji; Zheng, Nanning

2013-09-01

Fractal image compression (FIC) is an image coding technology based on the local similarity of image structure. It is widely used in many fields such as image retrieval, image denoising, image authentication, and encryption. FIC, however, suffers from the high computational complexity in encoding. Although many schemes are published to speed up encoding, they do not easily satisfy the encoding time or the reconstructed image quality requirements. In this paper, a new FIC scheme is proposed based on the fact that the affine similarity between two blocks in FIC is equivalent to the absolute value of Pearson's correlation coefficient (APCC) between them. First, all blocks in the range and domain pools are chosen and classified using an APCC-based block classification method to increase the matching probability. Second, by sorting the domain blocks with respect to APCCs between these domain blocks and a preset block in each class, the matching domain block for a range block can be searched in the selected domain set in which these APCCs are closer to APCC between the range block and the preset block. Experimental results show that the proposed scheme can significantly speed up the encoding process in FIC while preserving the reconstructed image quality well.

Dependence of Adaptive Cross-correlation Algorithm Performance on the Extended Scene Image Quality

NASA Technical Reports Server (NTRS)

Sidick, Erkin

2008-01-01

Recently, we reported an adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels between two extended-scene sub-images captured by a Shack-Hartmann wavefront sensor. It determines the positions of all extended-scene image cells relative to a reference cell in the same frame using an FFT-based iterative image-shifting algorithm. It works with both point-source spot images as well as extended scene images. We have demonstrated previously based on some measured images that the ACC algorithm can determine image shifts with as high an accuracy as 0.01 pixel for shifts as large 3 pixels, and yield similar results for both point source spot images and extended scene images. The shift estimate accuracy of the ACC algorithm depends on illumination level, background, and scene content in addition to the amount of the shift between two image cells. In this paper we investigate how the performance of the ACC algorithm depends on the quality and the frequency content of extended scene images captured by a Shack-Hatmann camera. We also compare the performance of the ACC algorithm with those of several other approaches, and introduce a failsafe criterion for the ACC algorithm-based extended scene Shack-Hatmann sensors.

Time-of-flight camera via a single-pixel correlation image sensor

NASA Astrophysics Data System (ADS)

Mao, Tianyi; Chen, Qian; He, Weiji; Dai, Huidong; Ye, Ling; Gu, Guohua

2018-04-01

A time-of-flight imager based on single-pixel correlation image sensors is proposed for noise-free depth map acquisition in presence of ambient light. Digital micro-mirror device and time-modulated IR-laser provide spatial and temporal illumination on the unknown object. Compressed sensing and ‘four bucket principle’ method are combined to reconstruct the depth map from a sequence of measurements at a low sampling rate. Second-order correlation transform is also introduced to reduce the noise from the detector itself and direct ambient light. Computer simulations are presented to validate the computational models and improvement of reconstructions.

Chondromalacia patellae: diagnosis with MR imaging.

PubMed

McCauley, T R; Kier, R; Lynch, K J; Jokl, P

1992-01-01

Most previous studies of MR imaging for detection of chondromalacia have used T1-weighted images. We correlated findings on axial MR images of the knee with arthroscopic findings to determine MR findings of chondromalacia patellae on T2-weighted and proton density-weighted images. The study population included 52 patients who had MR examination of the knee with a 1.5-T unit and subsequent arthroscopy, which documented chondromalacia patellae in 29 patients and normal cartilage in 23. The patellar cartilage was assessed retrospectively for MR signal and contour characteristics. MR diagnosis based on the criteria of focal signal or focal contour abnormality on either the T2-weighted or proton density-weighted images yielded the highest correlation with the arthroscopic diagnosis of chondromalacia. When these criteria were used, patients with chondromalacia were detected with 86% sensitivity, 74% specificity, and 81% accuracy. MR diagnosis based on T2-weighted images alone was more sensitive and accurate than was diagnosis based on proton density-weighted images alone. In conclusion, most patients with chondromalacia patellae have focal signal or focal contour defects in the patellar cartilage on T2-weighted MR images. These findings are absent in most patients with arthroscopically normal cartilage.

The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lehoucq, R. B.; Reu, P. L.; Turner, D. Z.

Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.

The Effect of the Ill-posed Problem on Quantitative Error Assessment in Digital Image Correlation

DOE PAGES

Lehoucq, R. B.; Reu, P. L.; Turner, D. Z.

2017-11-27

Here, this work explores the effect of the ill-posed problem on uncertainty quantification for motion estimation using digital image correlation (DIC) (Sutton et al. 2009). We develop a correction factor for standard uncertainty estimates based on the cosine of the angle between the true motion and the image gradients, in an integral sense over a subregion of the image. This correction factor accounts for variability in the DIC solution previously unaccounted for when considering only image noise, interpolation bias, contrast, and the software settings such as subset size and spacing.

Development of a diffraction imaging flow cytometer

PubMed Central

Jacobs, Kenneth M.; Lu, Jun Q.

2013-01-01

Diffraction images record angle-resolved distribution of scattered light from a particle excited by coherent light and can correlate highly with the 3D morphology of a particle. We present a jet-in-fluid design of flow chamber for acquisition of clear diffraction images in a laminar flow. Diffraction images of polystyrene spheres of different diameters were acquired and found to correlate highly with the calculated ones based on the Mie theory. Fast Fourier transform analysis indicated that the measured images can be used to extract sphere diameter values. These results demonstrate the significant potentials of high-throughput diffraction imaging flow cytometry for extracting 3D morphological features of cells. PMID:19794790

Validation of a Smartphone Image-Based Dietary Assessment Method for Pregnant Women

PubMed Central

Ashman, Amy M.; Collins, Clare E.; Brown, Leanne J.; Rae, Kym M.; Rollo, Megan E.

2017-01-01

Image-based dietary records could lower participant burden associated with traditional prospective methods of dietary assessment. They have been used in children, adolescents and adults, but have not been evaluated in pregnant women. The current study evaluated relative validity of the DietBytes image-based dietary assessment method for assessing energy and nutrient intakes. Pregnant women collected image-based dietary records (via a smartphone application) of all food, drinks and supplements consumed over three non-consecutive days. Intakes from the image-based method were compared to intakes collected from three 24-h recalls, taken on random days; once per week, in the weeks following the image-based record. Data were analyzed using nutrient analysis software. Agreement between methods was ascertained using Pearson correlations and Bland-Altman plots. Twenty-five women (27 recruited, one withdrew, one incomplete), median age 29 years, 15 primiparas, eight Aboriginal Australians, completed image-based records for analysis. Significant correlations between the two methods were observed for energy, macronutrients and fiber (r = 0.58–0.84, all p < 0.05), and for micronutrients both including (r = 0.47–0.94, all p < 0.05) and excluding (r = 0.40–0.85, all p < 0.05) supplements in the analysis. Bland-Altman plots confirmed acceptable agreement with no systematic bias. The DietBytes method demonstrated acceptable relative validity for assessment of nutrient intakes of pregnant women. PMID:28106758

Multi-modal Registration for Correlative Microscopy using Image Analogies

PubMed Central

Cao, Tian; Zach, Christopher; Modla, Shannon; Powell, Debbie; Czymmek, Kirk; Niethammer, Marc

2014-01-01

Correlative microscopy is a methodology combining the functionality of light microscopy with the high resolution of electron microscopy and other microscopy technologies for the same biological specimen. In this paper, we propose an image registration method for correlative microscopy, which is challenging due to the distinct appearance of biological structures when imaged with different modalities. Our method is based on image analogies and allows to transform images of a given modality into the appearance-space of another modality. Hence, the registration between two different types of microscopy images can be transformed to a mono-modality image registration. We use a sparse representation model to obtain image analogies. The method makes use of corresponding image training patches of two different imaging modalities to learn a dictionary capturing appearance relations. We test our approach on backscattered electron (BSE) scanning electron microscopy (SEM)/confocal and transmission electron microscopy (TEM)/confocal images. We perform rigid, affine, and deformable registration via B-splines and show improvements over direct registration using both mutual information and sum of squared differences similarity measures to account for differences in image appearance. PMID:24387943

Use of multidimensional, multimodal imaging and PACS to support neurological diagnoses

NASA Astrophysics Data System (ADS)

Wong, Stephen T. C.; Knowlton, Robert C.; Hoo, Kent S.; Huang, H. K.

1995-05-01

Technological advances in brain imaging have revolutionized diagnosis in neurology and neurological surgery. Major imaging techniques include magnetic resonance imaging (MRI) to visualize structural anatomy, positron emission tomography (PET) to image metabolic function and cerebral blood flow, magnetoencephalography (MEG) to visualize the location of physiologic current sources, and magnetic resonance spectroscopy (MRS) to measure specific biochemicals. Each of these techniques studies different biomedical aspects of the brain, but there lacks an effective means to quantify and correlate the disparate imaging datasets in order to improve clinical decision making processes. This paper describes several techniques developed in a UNIX-based neurodiagnostic workstation to aid the noninvasive presurgical evaluation of epilepsy patients. These techniques include online access to the picture archiving and communication systems (PACS) multimedia archive, coregistration of multimodality image datasets, and correlation and quantitation of structural and functional information contained in the registered images. For illustration, we describe the use of these techniques in a patient case of nonlesional neocortical epilepsy. We also present out future work based on preliminary studies.

Efficient content-based low-altitude images correlated network and strips reconstruction

NASA Astrophysics Data System (ADS)

He, Haiqing; You, Qi; Chen, Xiaoyong

2017-01-01

The manual intervention method is widely used to reconstruct strips for further aerial triangulation in low-altitude photogrammetry. Clearly the method for fully automatic photogrammetric data processing is not an expected way. In this paper, we explore a content-based approach without manual intervention or external information for strips reconstruction. Feature descriptors in the local spatial patterns are extracted by SIFT to construct vocabulary tree, in which these features are encoded in terms of TF-IDF numerical statistical algorithm to generate new representation for each low-altitude image. Then images correlated network is reconstructed by similarity measure, image matching and geometric graph theory. Finally, strips are reconstructed automatically by tracing straight lines and growing adjacent images gradually. Experimental results show that the proposed approach is highly effective in automatically rearranging strips of lowaltitude images and can provide rough relative orientation for further aerial triangulation.

Reconstruction of pulse noisy images via stochastic resonance

PubMed Central

Han, Jing; Liu, Hongjun; Sun, Qibing; Huang, Nan

2015-01-01

We investigate a practical technology for reconstructing nanosecond pulse noisy images via stochastic resonance, which is based on the modulation instability. A theoretical model of this method for optical pulse signal is built to effectively recover the pulse image. The nanosecond noise-hidden images grow at the expense of noise during the stochastic resonance process in a photorefractive medium. The properties of output images are mainly determined by the input signal-to-noise intensity ratio, the applied voltage across the medium, and the correlation length of noise background. A high cross-correlation gain is obtained by optimizing these parameters. This provides a potential method for detecting low-level or hidden pulse images in various imaging applications. PMID:26067911

Effects of Instructional Strategies Using Cross Sections on the Recognition of Anatomical Structures in Correlated CT and MR Images

ERIC Educational Resources Information Center

Khalil, Mohammed K.; Paas, Fred; Johnson, Tristan E.; Su, Yung K.; Payer, Andrew F.

2008-01-01

This research is an effort to best utilize the interactive anatomical images for instructional purposes based on cognitive load theory. Three studies explored the differential effects of three computer-based instructional strategies that use anatomical cross-sections to enhance the interpretation of radiological images. These strategies include:…

Reduction of irregular breathing artifacts in respiration-correlated CT images using a respiratory motion model.

PubMed

Hertanto, Agung; Zhang, Qinghui; Hu, Yu-Chi; Dzyubak, Oleksandr; Rimner, Andreas; Mageras, Gig S

2012-06-01

Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans. Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states. Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data. © 2012 American Association of Physicists in Medicine.

ICER-3D: A Progressive Wavelet-Based Compressor for Hyperspectral Images

NASA Technical Reports Server (NTRS)

Kiely, A.; Klimesh, M.; Xie, H.; Aranki, N.

2005-01-01

ICER-3D is a progressive, wavelet-based compressor for hyperspectral images. ICER-3D is derived from the ICER image compressor. ICER-3D can provide lossless and lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The three-dimensional wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of hyperspectral data sets, while facilitating elimination of spectral ringing artifacts. Correlation is further exploited by a context modeler that effectively exploits spectral dependencies in the wavelet-transformed hyperspectral data. Performance results illustrating the benefits of these features are presented.

Image Quality Assessment Using the Joint Spatial/Spatial-Frequency Representation

NASA Astrophysics Data System (ADS)

Beghdadi, Azeddine; Iordache, Răzvan

2006-12-01

This paper demonstrates the usefulness of spatial/spatial-frequency representations in image quality assessment by introducing a new image dissimilarity measure based on 2D Wigner-Ville distribution (WVD). The properties of 2D WVD are shortly reviewed, and the important issue of choosing the analytic image is emphasized. The WVD-based measure is shown to be correlated with subjective human evaluation, which is the premise towards an image quality assessor developed on this principle.

Correlation between Gray/White Matter Volume and Cognition in Healthy Elderly People

ERIC Educational Resources Information Center

Taki, Yasuyuki; Kinomura, Shigeo; Sato, Kazunori; Goto, Ryoi; Wu, Kai; Kawashima, Ryuta; Fukuda, Hiroshi

2011-01-01

This study applied volumetric analysis and voxel-based morphometry (VBM) of brain magnetic resonance (MR) images to assess whether correlations exist between global and regional gray/white matter volume and the cognitive functions of semantic memory and short-term memory, which are relatively well preserved with aging, using MR image data from 109…

An image registration-based technique for noninvasive vascular elastography

NASA Astrophysics Data System (ADS)

Valizadeh, Sina; Makkiabadi, Bahador; Mirbagheri, Alireza; Soozande, Mehdi; Manwar, Rayyan; Mozaffarzadeh, Moein; Nasiriavanaki, Mohammadreza

2018-02-01

Non-invasive vascular elastography is an emerging technique in vascular tissue imaging. During the past decades, several techniques have been suggested to estimate the tissue elasticity by measuring the displacement of the Carotid vessel wall. Cross correlation-based methods are the most prevalent approaches to measure the strain exerted in the wall vessel by the blood pressure. In the case of a low pressure, the displacement is too small to be apparent in ultrasound imaging, especially in the regions far from the center of the vessel, causing a high error of displacement measurement. On the other hand, increasing the compression leads to a relatively large displacement in the regions near the center, which reduces the performance of the cross correlation-based methods. In this study, a non-rigid image registration-based technique is proposed to measure the tissue displacement for a relatively large compression. The results show that the error of the displacement measurement obtained by the proposed method is reduced by increasing the amount of compression while the error of the cross correlationbased method rises for a relatively large compression. We also used the synthetic aperture imaging method, benefiting the directivity diagram, to improve the image quality, especially in the superficial regions. The best relative root-mean-square error (RMSE) of the proposed method and the adaptive cross correlation method were 4.5% and 6%, respectively. Consequently, the proposed algorithm outperforms the conventional method and reduces the relative RMSE by 25%.

MRI Atlas-Based Measurement of Spinal Cord Injury Predicts Outcome in Acute Flaccid Myelitis.

PubMed

McCoy, D B; Talbott, J F; Wilson, Michael; Mamlouk, M D; Cohen-Adad, J; Wilson, Mark; Narvid, J

2017-02-01

Recent advances in spinal cord imaging analysis have led to the development of a robust anatomic template and atlas incorporated into an open-source platform referred to as the Spinal Cord Toolbox. Using the Spinal Cord Toolbox, we sought to correlate measures of GM, WM, and cross-sectional area pathology on T2 MR imaging with motor disability in patients with acute flaccid myelitis. Spinal cord imaging for 9 patients with acute flaccid myelitis was analyzed by using the Spinal Cord Toolbox. A semiautomated pipeline using the Spinal Cord Toolbox measured lesion involvement in GM, WM, and total spinal cord cross-sectional area. Proportions of GM, WM, and cross-sectional area affected by T2 hyperintensity were calculated across 3 ROIs: 1) center axial section of lesion; 2) full lesion segment; and 3) full cord atlas volume. Spearman rank order correlation was calculated to compare MR metrics with clinical measures of disability. Proportion of GM metrics at the center axial section significantly correlated with measures of motor impairment upon admission ( r [9] = -0.78; P = .014) and at 3-month follow-up ( r [9] = -0.66; P = .05). Further, proportion of GM extracted across the full lesion segment significantly correlated with initial motor impairment ( r [9] = -0.74, P = .024). No significant correlation was found for proportion of WM or proportion of cross-sectional area with clinical disability. Atlas-based measures of proportion of GM T2 signal abnormality measured on a single axial MR imaging section and across the full lesion segment correlate with motor impairment and outcome in patients with acute flaccid myelitis. This is the first atlas-based study to correlate clinical outcomes with segmented measures of T2 signal abnormality in the spinal cord. © 2017 by American Journal of Neuroradiology.

Effects of image-based and text-based active learning exercises on student examination performance in a musculoskeletal anatomy course.

PubMed

Gross, M Melissa; Wright, Mary C; Anderson, Olivia S

2017-09-01

Research on the benefits of visual learning has relied primarily on lecture-based pedagogy, but the potential benefits of combining active learning strategies with visual and verbal materials on learning anatomy has not yet been explored. In this study, the differential effects of text-based and image-based active learning exercises on examination performance were investigated in a functional anatomy course. Each class session was punctuated with an average of 12 text-based and image-based active learning exercises. Participation data from 231 students were compared with their examination performance on 262 questions associated with the in-class exercises. Students also rated the helpfulness and difficulty of the in-class exercises on a survey. Participation in the active learning exercises was positively correlated with examination performance (r = 0.63, P < 0.001). When controlling for other key demographics (gender, underrepresented minority status) and prior grade point average, participation in the image-based exercises was significantly correlated with performance on examination questions associated with image-based exercises (P < 0.001) and text-based exercises (P < 0.01), while participation in text-based exercises was not. Additionally, students reported that the active learning exercises were helpful for seeing images of key ideas (94%) and clarifying key course concepts (80%), and that the image-based exercises were significantly less demanding, less hard and required less effort than text-based exercises (P < 0.05). The findings confirm the positive effect of using images and active learning strategies on student learning, and suggest that integrating them may be especially beneficial for learning anatomy. Anat Sci Educ 10: 444-455. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

Blind CT image quality assessment via deep learning strategy: initial study

NASA Astrophysics Data System (ADS)

Li, Sui; He, Ji; Wang, Yongbo; Liao, Yuting; Zeng, Dong; Bian, Zhaoying; Ma, Jianhua

2018-03-01

Computed Tomography (CT) is one of the most important medical imaging modality. CT images can be used to assist in the detection and diagnosis of lesions and to facilitate follow-up treatment. However, CT images are vulnerable to noise. Actually, there are two major source intrinsically causing the CT data noise, i.e., the X-ray photo statistics and the electronic noise background. Therefore, it is necessary to doing image quality assessment (IQA) in CT imaging before diagnosis and treatment. Most of existing CT images IQA methods are based on human observer study. However, these methods are impractical in clinical for their complex and time-consuming. In this paper, we presented a blind CT image quality assessment via deep learning strategy. A database of 1500 CT images is constructed, containing 300 high-quality images and 1200 corresponding noisy images. Specifically, the high-quality images were used to simulate the corresponding noisy images at four different doses. Then, the images are scored by the experienced radiologists by the following attributes: image noise, artifacts, edge and structure, overall image quality, and tumor size and boundary estimation with five-point scale. We trained a network for learning the non-liner map from CT images to subjective evaluation scores. Then, we load the pre-trained model to yield predicted score from the test image. To demonstrate the performance of the deep learning network in IQA, correlation coefficients: Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are utilized. And the experimental result demonstrate that the presented deep learning based IQA strategy can be used in the CT image quality assessment.

Improved decryption quality and security of a joint transform correlator-based encryption system

NASA Astrophysics Data System (ADS)

Vilardy, Juan M.; Millán, María S.; Pérez-Cabré, Elisabet

2013-02-01

Some image encryption systems based on modified double random phase encoding and joint transform correlator architecture produce low quality decrypted images and are vulnerable to a variety of attacks. In this work, we analyse the algorithm of some reported methods that optically implement the double random phase encryption in a joint transform correlator. We show that it is possible to significantly improve the quality of the decrypted image by introducing a simple nonlinear operation in the encrypted function that contains the joint power spectrum. This nonlinearity also makes the system more resistant to chosen-plaintext attacks. We additionally explore the system resistance against this type of attack when a variety of probability density functions are used to generate the two random phase masks of the encryption-decryption process. Numerical results are presented and discussed.

The correlation study of parallel feature extractor and noise reduction approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dewi, Deshinta Arrova; Sundararajan, Elankovan; Prabuwono, Anton Satria

2015-05-15

This paper presents literature reviews that show variety of techniques to develop parallel feature extractor and finding its correlation with noise reduction approaches for low light intensity images. Low light intensity images are normally displayed as darker images and low contrast. Without proper handling techniques, those images regularly become evidences of misperception of objects and textures, the incapability to section them. The visual illusions regularly clues to disorientation, user fatigue, poor detection and classification performance of humans and computer algorithms. Noise reduction approaches (NR) therefore is an essential step for other image processing steps such as edge detection, image segmentation,more » image compression, etc. Parallel Feature Extractor (PFE) meant to capture visual contents of images involves partitioning images into segments, detecting image overlaps if any, and controlling distributed and redistributed segments to extract the features. Working on low light intensity images make the PFE face challenges and closely depend on the quality of its pre-processing steps. Some papers have suggested many well established NR as well as PFE strategies however only few resources have suggested or mentioned the correlation between them. This paper reviews best approaches of the NR and the PFE with detailed explanation on the suggested correlation. This finding may suggest relevant strategies of the PFE development. With the help of knowledge based reasoning, computational approaches and algorithms, we present the correlation study between the NR and the PFE that can be useful for the development and enhancement of other existing PFE.« less

Quantifying Particle Numbers and Mass Flux in Drifting Snow

NASA Astrophysics Data System (ADS)

Crivelli, Philip; Paterna, Enrico; Horender, Stefan; Lehning, Michael

2016-12-01

We compare two of the most common methods of quantifying mass flux, particle numbers and particle-size distribution for drifting snow events, the snow-particle counter (SPC), a laser-diode-based particle detector, and particle tracking velocimetry based on digital shadowgraphic imaging. The two methods were correlated for mass flux and particle number flux. For the SPC measurements, the device was calibrated by the manufacturer beforehand. The shadowgrapic imaging method measures particle size and velocity directly from consecutive images, and before each new test the image pixel length is newly calibrated. A calibration study with artificially scattered sand particles and glass beads provides suitable settings for the shadowgraphical imaging as well as obtaining a first correlation of the two methods in a controlled environment. In addition, using snow collected in trays during snowfall, several experiments were performed to observe drifting snow events in a cold wind tunnel. The results demonstrate a high correlation between the mass flux obtained for the calibration studies (r ≥slant 0.93) and good correlation for the drifting snow experiments (r ≥slant 0.81). The impact of measurement settings is discussed in order to reliably quantify particle numbers and mass flux in drifting snow. The study was designed and performed to optimize the settings of the digital shadowgraphic imaging system for both the acquisition and the processing of particles in a drifting snow event. Our results suggest that these optimal settings can be transferred to different imaging set-ups to investigate sediment transport processes.

Emotional textile image classification based on cross-domain convolutional sparse autoencoders with feature selection

NASA Astrophysics Data System (ADS)

Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin

2017-01-01

We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.

Ghost detection and removal based on super-pixel grouping in exposure fusion

NASA Astrophysics Data System (ADS)

Jiang, Shenyu; Xu, Zhihai; Li, Qi; Chen, Yueting; Feng, Huajun

2014-09-01

A novel multi-exposure images fusion method for dynamic scenes is proposed. The commonly used techniques for high dynamic range (HDR) imaging are based on the combination of multiple differently exposed images of the same scene. The drawback of these methods is that ghosting artifacts will be introduced into the final HDR image if the scene is not static. In this paper, a super-pixel grouping based method is proposed to detect the ghost in the image sequences. We introduce the zero mean normalized cross correlation (ZNCC) as a measure of similarity between a given exposure image and the reference. The calculation of ZNCC is implemented in super-pixel level, and the super-pixels which have low correlation with the reference are excluded by adjusting the weight maps for fusion. Without any prior information on camera response function or exposure settings, the proposed method generates low dynamic range (LDR) images which can be shown on conventional display devices directly with details preserving and ghost effects reduced. Experimental results show that the proposed method generates high quality images which have less ghost artifacts and provide a better visual quality than previous approaches.

Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.

PubMed

Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A

2011-04-01

Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.

Fully Automated Quantitative Estimation of Volumetric Breast Density from Digital Breast Tomosynthesis Images: Preliminary Results and Comparison with Digital Mammography and MR Imaging

PubMed Central

Pertuz, Said; McDonald, Elizabeth S.; Weinstein, Susan P.; Conant, Emily F.

2016-01-01

Purpose To assess a fully automated method for volumetric breast density (VBD) estimation in digital breast tomosynthesis (DBT) and to compare the findings with those of full-field digital mammography (FFDM) and magnetic resonance (MR) imaging. Materials and Methods Bilateral DBT images, FFDM images, and sagittal breast MR images were retrospectively collected from 68 women who underwent breast cancer screening from October 2011 to September 2012 with institutional review board–approved, HIPAA-compliant protocols. A fully automated computer algorithm was developed for quantitative estimation of VBD from DBT images. FFDM images were processed with U.S. Food and Drug Administration–cleared software, and the MR images were processed with a previously validated automated algorithm to obtain corresponding VBD estimates. Pearson correlation and analysis of variance with Tukey-Kramer post hoc correction were used to compare the multimodality VBD estimates. Results Estimates of VBD from DBT were significantly correlated with FFDM-based and MR imaging–based estimates with r = 0.83 (95% confidence interval [CI]: 0.74, 0.90) and r = 0.88 (95% CI: 0.82, 0.93), respectively (P < .001). The corresponding correlation between FFDM and MR imaging was r = 0.84 (95% CI: 0.76, 0.90). However, statistically significant differences after post hoc correction (α = 0.05) were found among VBD estimates from FFDM (mean ± standard deviation, 11.1% ± 7.0) relative to MR imaging (16.6% ± 11.2) and DBT (19.8% ± 16.2). Differences between VDB estimates from DBT and MR imaging were not significant (P = .26). Conclusion Fully automated VBD estimates from DBT, FFDM, and MR imaging are strongly correlated but show statistically significant differences. Therefore, absolute differences in VBD between FFDM, DBT, and MR imaging should be considered in breast cancer risk assessment. © RSNA, 2015 Online supplemental material is available for this article. PMID:26491909

Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

Refinement procedure for the image alignment in high-resolution electron tomography.

PubMed

Houben, L; Bar Sadan, M

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. Copyright © 2011 Elsevier B.V. All rights reserved.

Designing a composite correlation filter based on iterative optimization of training images for distortion invariant face recognition

NASA Astrophysics Data System (ADS)

Wang, Q.; Elbouz, M.; Alfalou, A.; Brosseau, C.

2017-06-01

We present a novel method to optimize the discrimination ability and noise robustness of composite filters. This method is based on the iterative preprocessing of training images which can extract boundary and detailed feature information of authentic training faces, thereby improving the peak-to-correlation energy (PCE) ratio of authentic faces and to be immune to intra-class variance and noise interference. By adding the training images directly, one can obtain a composite template with high discrimination ability and robustness for face recognition task. The proposed composite correlation filter does not involve any complicated mathematical analysis and computation which are often required in the design of correlation algorithms. Simulation tests have been conducted to check the effectiveness and feasibility of our proposal. Moreover, to assess robustness of composite filters using receiver operating characteristic (ROC) curves, we devise a new method to count the true positive and false positive rates for which the difference between PCE and threshold is involved.

Digital halftoning methods for selectively partitioning error into achromatic and chromatic channels

NASA Technical Reports Server (NTRS)

Mulligan, Jeffrey B.

1990-01-01

A method is described for reducing the visibility of artifacts arising in the display of quantized color images on CRT displays. The method is based on the differential spatial sensitivity of the human visual system to chromatic and achromatic modulations. Because the visual system has the highest spatial and temporal acuity for the luminance component of an image, a technique which will reduce luminance artifacts at the expense of introducing high-frequency chromatic errors is sought. A method based on controlling the correlations between the quantization errors in the individual phosphor images is explored. The luminance component is greatest when the phosphor errors are positively correlated, and is minimized when the phosphor errors are negatively correlated. The greatest effect of the correlation is obtained when the intensity quantization step sizes of the individual phosphors have equal luminances. For the ordered dither algorithm, a version of the method can be implemented by simply inverting the matrix of thresholds for one of the color components.

Optical correlation based pose estimation using bipolar phase grayscale amplitude spatial light modulators

NASA Astrophysics Data System (ADS)

Outerbridge, Gregory John, II

Pose estimation techniques have been developed on both optical and digital correlator platforms to aid in the autonomous rendezvous and docking of spacecraft. This research has focused on the optical architecture, which utilizes high-speed bipolar-phase grayscale-amplitude spatial light modulators as the image and correlation filter devices. The optical approach has the primary advantage of optical parallel processing: an extremely fast and efficient way of performing complex correlation calculations. However, the constraints imposed on optically implementable filters makes optical correlator based posed estimation technically incompatible with the popular weighted composite filter designs successfully used on the digital platform. This research employs a much simpler "bank of filters" approach to optical pose estimation that exploits the inherent efficiency of optical correlation devices. A novel logarithmically mapped optically implementable matched filter combined with a pose search algorithm resulted in sub-degree standard deviations in angular pose estimation error. These filters were extremely simple to generate, requiring no complicated training sets and resulted in excellent performance even in the presence of significant background noise. Common edge detection and scaling of the input image was the only image pre-processing necessary for accurate pose detection at all alignment distances of interest.

A method to classify schizophrenia using inter-task spatial correlations of functional brain images.

PubMed

Michael, Andrew M; Calhoun, Vince D; Andreasen, Nancy C; Baum, Stefi A

2008-01-01

The clinical heterogeneity of schizophrenia (scz) and the overlap of self reported and observed symptoms with other mental disorders makes its diagnosis a difficult task. At present no laboratory-based or image-based diagnostic tool for scz exists and such tools are desired to support existing methods for more precise diagnosis. Functional magnetic resonance imaging (fMRI) is currently employed to identify and correlate cognitive processes related to scz and its symptoms. Fusion of multiple fMRI tasks that probe different cognitive processes may help to better understand hidden networks of this complex disorder. In this paper we utilize three different fMRI tasks and introduce an approach to classify subjects based on inter-task spatial correlations of brain activation. The technique was applied to groups of patients and controls and its validity was checked with the leave-one-out method. We show that the classification rate increases when information from multiple tasks are combined.

Image classification at low light levels

NASA Astrophysics Data System (ADS)

Wernick, Miles N.; Morris, G. Michael

1986-12-01

An imaging photon-counting detector is used to achieve automatic sorting of two image classes. The classification decision is formed on the basis of the cross correlation between a photon-limited input image and a reference function stored in computer memory. Expressions for the statistical parameters of the low-light-level correlation signal are given and are verified experimentally. To obtain a correlation-based system for two-class sorting, it is necessary to construct a reference function that produces useful information for class discrimination. An expression for such a reference function is derived using maximum-likelihood decision theory. Theoretically predicted results are used to compare on the basis of performance the maximum-likelihood reference function with Fukunaga-Koontz basis vectors and average filters. For each method, good class discrimination is found to result in milliseconds from a sparse sampling of the input image.

Demosaicing images from colour cameras for digital image correlation

NASA Astrophysics Data System (ADS)

Forsey, A.; Gungor, S.

2016-11-01

Digital image correlation is not the intended use for consumer colour cameras, but with care they can be successfully employed in such a role. The main obstacle is the sparsely sampled colour data caused by the use of a colour filter array (CFA) to separate the colour channels. It is shown that the method used to convert consumer camera raw files into a monochrome image suitable for digital image correlation (DIC) can have a significant effect on the DIC output. A number of widely available software packages and two in-house methods are evaluated in terms of their performance when used with DIC. Using an in-plane rotating disc to produce a highly constrained displacement field, it was found that the bicubic spline based in-house demosaicing method outperformed the other methods in terms of accuracy and aliasing suppression.

Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography.

PubMed

Le Pogam, Adrien; Hatt, Mathieu; Descourt, Patrice; Boussion, Nicolas; Tsoumpas, Charalampos; Turkheimer, Federico E; Prunier-Aesch, Caroline; Baulieu, Jean-Louis; Guilloteau, Denis; Visvikis, Dimitris

2011-09-01

Partial volume effects (PVEs) are consequences of the limited spatial resolution in emission tomography leading to underestimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multiresolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low-resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model, which may introduce artifacts in regions where no significant correlation exists between anatomical and functional details. A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present, the new model outperformed the 2D global approach, avoiding artifacts and significantly improving quality of the corrected images and their quantitative accuracy. A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multiresolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information.

Evaluation of a 3D local multiresolution algorithm for the correction of partial volume effects in positron emission tomography

PubMed Central

Le Pogam, Adrien; Hatt, Mathieu; Descourt, Patrice; Boussion, Nicolas; Tsoumpas, Charalampos; Turkheimer, Federico E.; Prunier-Aesch, Caroline; Baulieu, Jean-Louis; Guilloteau, Denis; Visvikis, Dimitris

2011-01-01

Purpose Partial volume effects (PVE) are consequences of the limited spatial resolution in emission tomography leading to under-estimation of uptake in tissues of size similar to the point spread function (PSF) of the scanner as well as activity spillover between adjacent structures. Among PVE correction methodologies, a voxel-wise mutual multi-resolution analysis (MMA) was recently introduced. MMA is based on the extraction and transformation of high resolution details from an anatomical image (MR/CT) and their subsequent incorporation into a low resolution PET image using wavelet decompositions. Although this method allows creating PVE corrected images, it is based on a 2D global correlation model which may introduce artefacts in regions where no significant correlation exists between anatomical and functional details. Methods A new model was designed to overcome these two issues (2D only and global correlation) using a 3D wavelet decomposition process combined with a local analysis. The algorithm was evaluated on synthetic, simulated and patient images, and its performance was compared to the original approach as well as the geometric transfer matrix (GTM) method. Results Quantitative performance was similar to the 2D global model and GTM in correlated cases. In cases where mismatches between anatomical and functional information were present the new model outperformed the 2D global approach, avoiding artefacts and significantly improving quality of the corrected images and their quantitative accuracy. Conclusions A new 3D local model was proposed for a voxel-wise PVE correction based on the original mutual multi-resolution analysis approach. Its evaluation demonstrated an improved and more robust qualitative and quantitative accuracy compared to the original MMA methodology, particularly in the absence of full correlation between anatomical and functional information. PMID:21978037

Evaluation of magnetic nanoparticle samples made from biocompatible ferucarbotran by time-correlation magnetic particle imaging reconstruction method

PubMed Central

2013-01-01

Background Molecular imaging using magnetic nanoparticles (MNPs)—magnetic particle imaging (MPI)—has attracted interest for the early diagnosis of cancer and cardiovascular disease. However, because a steep local magnetic field distribution is required to obtain a defined image, sophisticated hardware is required. Therefore, it is desirable to realize excellent image quality even with low-performance hardware. In this study, the spatial resolution of MPI was evaluated using an image reconstruction method based on the correlation information of the magnetization signal in a time domain and by applying MNP samples made from biocompatible ferucarbotran that have adjusted particle diameters. Methods The magnetization characteristics and particle diameters of four types of MNP samples made from ferucarbotran were evaluated. A numerical analysis based on our proposed method that calculates the image intensity from correlation information between the magnetization signal generated from MNPs and the system function was attempted, and the obtained image quality was compared with that using the prototype in terms of image resolution and image artifacts. Results MNP samples obtained by adjusting ferucarbotran showed superior properties to conventional ferucarbotran samples, and numerical analysis showed that the same image quality could be obtained using a gradient magnetic field generator with 0.6 times the performance. However, because image blurring was included theoretically by the proposed method, an algorithm will be required to improve performance. Conclusions MNP samples obtained by adjusting ferucarbotran showed magnetizing properties superior to conventional ferucarbotran samples, and by using such samples, comparable image quality (spatial resolution) could be obtained with a lower gradient magnetic field intensity. PMID:23734917

A combined method for correlative 3D imaging of biological samples from macro to nano scale

NASA Astrophysics Data System (ADS)

Kellner, Manuela; Heidrich, Marko; Lorbeer, Raoul-Amadeus; Antonopoulos, Georgios C.; Knudsen, Lars; Wrede, Christoph; Izykowski, Nicole; Grothausmann, Roman; Jonigk, Danny; Ochs, Matthias; Ripken, Tammo; Kühnel, Mark P.; Meyer, Heiko

2016-10-01

Correlative analysis requires examination of a specimen from macro to nano scale as well as applicability of analytical methods ranging from morphological to molecular. Accomplishing this with one and the same sample is laborious at best, due to deformation and biodegradation during measurements or intermediary preparation steps. Furthermore, data alignment using differing imaging techniques turns out to be a complex task, which considerably complicates the interconnection of results. We present correlative imaging of the accessory rat lung lobe by combining a modified Scanning Laser Optical Tomography (SLOT) setup with a specially developed sample preparation method (CRISTAL). CRISTAL is a resin-based embedding method that optically clears the specimen while allowing sectioning and preventing degradation. We applied and correlated SLOT with Multi Photon Microscopy, histological and immunofluorescence analysis as well as Transmission Electron Microscopy, all in the same sample. Thus, combining CRISTAL with SLOT enables the correlative utilization of a vast variety of imaging techniques.

Fast image matching algorithm based on projection characteristics

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Yue, Xiaobo; Zhou, Lijun

2011-06-01

Based on analyzing the traditional template matching algorithm, this paper identified the key factors restricting the speed of matching and put forward a brand new fast matching algorithm based on projection. Projecting the grayscale image, this algorithm converts the two-dimensional information of the image into one-dimensional one, and then matches and identifies through one-dimensional correlation, meanwhile, because of normalization has been done, when the image brightness or signal amplitude increasing in proportion, it could also perform correct matching. Experimental results show that the projection characteristics based image registration method proposed in this article could greatly improve the matching speed, which ensuring the matching accuracy as well.

Correlated optical and isotopic nanoscopy

NASA Astrophysics Data System (ADS)

Saka, Sinem K.; Vogts, Angela; Kröhnert, Katharina; Hillion, François; Rizzoli, Silvio O.; Wessels, Johannes T.

2014-04-01

The isotopic composition of different materials can be imaged by secondary ion mass spectrometry. In biology, this method is mainly used to study cellular metabolism and turnover, by pulsing the cells with marker molecules such as amino acids labelled with stable isotopes (15N, 13C). The incorporation of the markers is then imaged with a lateral resolution that can surpass 100 nm. However, secondary ion mass spectrometry cannot identify specific subcellular structures like organelles, and needs to be correlated with a second technique, such as fluorescence imaging. Here, we present a method based on stimulated emission depletion microscopy that provides correlated optical and isotopic nanoscopy (COIN) images. We use this approach to study the protein turnover in different organelles from cultured hippocampal neurons. Correlated optical and isotopic nanoscopy can be applied to a variety of biological samples, and should therefore enable the investigation of the isotopic composition of many organelles and subcellular structures.

Correlation pattern recognition: optimal parameters for quality standards control of chocolate marshmallow candy

NASA Astrophysics Data System (ADS)

Flores, Jorge L.; García-Torales, G.; Ponce Ávila, Cristina

2006-08-01

This paper describes an in situ image recognition system designed to inspect the quality standards of the chocolate pops during their production. The essence of the recognition system is the localization of the events (i.e., defects) in the input images that affect the quality standards of pops. To this end, processing modules, based on correlation filter, and segmentation of images are employed with the objective of measuring the quality standards. Therefore, we designed the correlation filter and defined a set of features from the correlation plane. The desired values for these parameters are obtained by exploiting information about objects to be rejected in order to find the optimal discrimination capability of the system. Regarding this set of features, the pop can be correctly classified. The efficacy of the system has been tested thoroughly under laboratory conditions using at least 50 images, containing 3 different types of possible defects.

Enhanced Visualization of Subtle Outer Retinal Pathology by En Face Optical Coherence Tomography and Correlation with Multi-Modal Imaging

PubMed Central

Chew, Avenell L.; Lamey, Tina; McLaren, Terri; De Roach, John

2016-01-01

Purpose To present en face optical coherence tomography (OCT) images generated by graph-search theory algorithm-based custom software and examine correlation with other imaging modalities. Methods En face OCT images derived from high density OCT volumetric scans of 3 healthy subjects and 4 patients using a custom algorithm (graph-search theory) and commercial software (Heidelberg Eye Explorer software (Heidelberg Engineering)) were compared and correlated with near infrared reflectance, fundus autofluorescence, adaptive optics flood-illumination ophthalmoscopy (AO-FIO) and microperimetry. Results Commercial software was unable to generate accurate en face OCT images in eyes with retinal pigment epithelium (RPE) pathology due to segmentation error at the level of Bruch’s membrane (BM). Accurate segmentation of the basal RPE and BM was achieved using custom software. The en face OCT images from eyes with isolated interdigitation or ellipsoid zone pathology were of similar quality between custom software and Heidelberg Eye Explorer software in the absence of any other significant outer retinal pathology. En face OCT images demonstrated angioid streaks, lesions of acute macular neuroretinopathy, hydroxychloroquine toxicity and Bietti crystalline deposits that correlated with other imaging modalities. Conclusions Graph-search theory algorithm helps to overcome the limitations of outer retinal segmentation inaccuracies in commercial software. En face OCT images can provide detailed topography of the reflectivity within a specific layer of the retina which correlates with other forms of fundus imaging. Our results highlight the need for standardization of image reflectivity to facilitate quantification of en face OCT images and longitudinal analysis. PMID:27959968

A projector calibration method for monocular structured light system based on digital image correlation

NASA Astrophysics Data System (ADS)

Feng, Zhixin

2018-02-01

Projector calibration is crucial for a camera-projector three-dimensional (3-D) structured light measurement system, which has one camera and one projector. In this paper, a novel projector calibration method is proposed based on digital image correlation. In the method, the projector is viewed as an inverse camera, and a plane calibration board with feature points is used to calibrate the projector. During the calibration processing, a random speckle pattern is projected onto the calibration board with different orientations to establish the correspondences between projector images and camera images. Thereby, dataset for projector calibration are generated. Then the projector can be calibrated using a well-established camera calibration algorithm. The experiment results confirm that the proposed method is accurate and reliable for projector calibration.

Efficient 3D porous microstructure reconstruction via Gaussian random field and hybrid optimization.

PubMed

Jiang, Z; Chen, W; Burkhart, C

2013-11-01

Obtaining an accurate three-dimensional (3D) structure of a porous microstructure is important for assessing the material properties based on finite element analysis. Whereas directly obtaining 3D images of the microstructure is impractical under many circumstances, two sets of methods have been developed in literature to generate (reconstruct) 3D microstructure from its 2D images: one characterizes the microstructure based on certain statistical descriptors, typically two-point correlation function and cluster correlation function, and then performs an optimization process to build a 3D structure that matches those statistical descriptors; the other method models the microstructure using stochastic models like a Gaussian random field and generates a 3D structure directly from the function. The former obtains a relatively accurate 3D microstructure, but computationally the optimization process can be very intensive, especially for problems with large image size; the latter generates a 3D microstructure quickly but sacrifices the accuracy due to issues in numerical implementations. A hybrid optimization approach of modelling the 3D porous microstructure of random isotropic two-phase materials is proposed in this paper, which combines the two sets of methods and hence maintains the accuracy of the correlation-based method with improved efficiency. The proposed technique is verified for 3D reconstructions based on silica polymer composite images with different volume fractions. A comparison of the reconstructed microstructures and the optimization histories for both the original correlation-based method and our hybrid approach demonstrates the improved efficiency of the approach. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Autofocus algorithm using one-dimensional Fourier transform and Pearson correlation

NASA Astrophysics Data System (ADS)

Bueno Mario, A.; Alvarez-Borrego, Josue; Acho, L.

2004-10-01

A new autofocus algorithm based on one-dimensional Fourier transform and Pearson correlation for Z automatized microscope is proposed. Our goal is to determine in fast response time and accuracy, the best focused plane through an algorithm. We capture in bright and dark field several images set at different Z distances from biological organism sample. The algorithm uses the one-dimensional Fourier transform to obtain the image frequency content of a vectors pattern previously defined comparing the Pearson correlation of these frequency vectors versus the reference image frequency vector, the most out of focus image, we find the best focusing. Experimental results showed the algorithm has fast response time and accuracy in getting the best focus plane from captured images. In conclusions, the algorithm can be implemented in real time systems due fast response time, accuracy and robustness. The algorithm can be used to get focused images in bright and dark field and it can be extended to include fusion techniques to construct multifocus final images beyond of this paper.

Comparison Of Eigenvector-Based Statistical Pattern Recognition Algorithms For Hybrid Processing

NASA Astrophysics Data System (ADS)

Tian, Q.; Fainman, Y.; Lee, Sing H.

1989-02-01

The pattern recognition algorithms based on eigenvector analysis (group 2) are theoretically and experimentally compared in this part of the paper. Group 2 consists of Foley-Sammon (F-S) transform, Hotelling trace criterion (HTC), Fukunaga-Koontz (F-K) transform, linear discriminant function (LDF) and generalized matched filter (GMF). It is shown that all eigenvector-based algorithms can be represented in a generalized eigenvector form. However, the calculations of the discriminant vectors are different for different algorithms. Summaries on how to calculate the discriminant functions for the F-S, HTC and F-K transforms are provided. Especially for the more practical, underdetermined case, where the number of training images is less than the number of pixels in each image, the calculations usually require the inversion of a large, singular, pixel correlation (or covariance) matrix. We suggest solving this problem by finding its pseudo-inverse, which requires inverting only the smaller, non-singular image correlation (or covariance) matrix plus multiplying several non-singular matrices. We also compare theoretically the effectiveness for classification with the discriminant functions from F-S, HTC and F-K with LDF and GMF, and between the linear-mapping-based algorithms and the eigenvector-based algorithms. Experimentally, we compare the eigenvector-based algorithms using a set of image data bases each image consisting of 64 x 64 pixels.

Visible Light Image-Based Method for Sugar Content Classification of Citrus

PubMed Central

Wang, Xuefeng; Wu, Chunyan; Hirafuji, Masayuki

2016-01-01

Visible light imaging of citrus fruit from Mie Prefecture of Japan was performed to determine whether an algorithm could be developed to predict the sugar content. This nondestructive classification showed that the accurate segmentation of different images can be realized by a correlation analysis based on the threshold value of the coefficient of determination. There is an obvious correlation between the sugar content of citrus fruit and certain parameters of the color images. The selected image parameters were connected by addition algorithm. The sugar content of citrus fruit can be predicted by the dummy variable method. The results showed that the small but orange citrus fruits often have a high sugar content. The study shows that it is possible to predict the sugar content of citrus fruit and to perform a classification of the sugar content using light in the visible spectrum and without the need for an additional light source. PMID:26811935

Region-Based Prediction for Image Compression in the Cloud.

PubMed

Begaint, Jean; Thoreau, Dominique; Guillotel, Philippe; Guillemot, Christine

2018-04-01

Thanks to the increasing number of images stored in the cloud, external image similarities can be leveraged to efficiently compress images by exploiting inter-images correlations. In this paper, we propose a novel image prediction scheme for cloud storage. Unlike current state-of-the-art methods, we use a semi-local approach to exploit inter-image correlation. The reference image is first segmented into multiple planar regions determined from matched local features and super-pixels. The geometric and photometric disparities between the matched regions of the reference image and the current image are then compensated. Finally, multiple references are generated from the estimated compensation models and organized in a pseudo-sequence to differentially encode the input image using classical video coding tools. Experimental results demonstrate that the proposed approach yields significant rate-distortion performance improvements compared with the current image inter-coding solutions such as high efficiency video coding.

Evaluation of physiological strain in hot work areas using thermal imagery.

PubMed

Holm, Clint A; Pahler, Leon; Thiese, Matthew S; Handy, Rodney

2016-10-01

Monitoring core body temperature to identify heat strain in workers engaged in hot work in heat stress environments is intrusive and expensive. Nonintrusive, inexpensive methods are needed to calculate individual Physiological Strain Index (PSI). Thermal imaging and heart rate monitoring were used in this study to calculate Physiological Strain Index (PSI) from thermal imaging temperatures of human subjects wearing thermal protective garments during recovery from hot work. Ten male subjects were evaluated for physiological strain while participating in hot work. Thermal images of the head and neck were captured with a high-resolution thermal imaging camera concomitant with measures of gastrointestinal and skin temperature. Lin's concordance correlation coefficient (rho_c), Pearson's coefficient (r) and bias correction factor (C-b) were calculated to compare thermal imaging based temperatures to gastrointestinal temperatures. Calculations of PSI based thermal imaging recorded temperatures were compared to gastrointestinal based PSI. Participants reached a peak PSI of 5.2, indicating moderate heat strain. Sagittal measurements showed low correlation (rho_c=0.133), moderate precision (r=0.496) and low accuracy (C_b=0.269) with gastrointestinal temperature. Bland-Altman plots of imaging measurements showed increasing agreement as gastrointestinal temperature rose; however, the Limits of Agreement (LoA) fell outside the ±0.25C range of clinical significance. Bland-Altman plots of PSI calculated from imaging measurements showed increasing agreement as gastrointestinal temperature rose; however, the LoA fell outside the ±0.5 range of clinical significance. Results of this study confirmed previous research showing thermal imagery is not highly correlated to body core temperature during recovery from moderate heat strain in mild ambient conditions. Measurements display a trend toward increasing correlation at higher body core temperatures. Accuracy was not sufficient at mild to moderate heat strain to allow calculation of individual physiological stress. Copyright © 2016 Elsevier Ltd. All rights reserved.

A comparative study of volumetric breast density estimation in digital mammography and magnetic resonance imaging: results from a high-risk population

NASA Astrophysics Data System (ADS)

Kontos, Despina; Xing, Ye; Bakic, Predrag R.; Conant, Emily F.; Maidment, Andrew D. A.

2010-03-01

We performed a study to compare methods for volumetric breast density estimation in digital mammography (DM) and magnetic resonance imaging (MRI) for a high-risk population of women. DM and MRI images of the unaffected breast from 32 women with recently detected abnormalities and/or previously diagnosed breast cancer (age range 31-78 yrs, mean 50.3 yrs) were retrospectively analyzed. DM images were analyzed using QuantraTM (Hologic Inc). The MRI images were analyzed using a fuzzy-C-means segmentation algorithm on the T1 map. Both methods were compared to Cumulus (Univ. Toronto). Volumetric breast density estimates from DM and MRI are highly correlated (r=0.90, p<=0.001). The correlation between the volumetric and the area-based density measures is lower and depends on the training background of the Cumulus software user (r=0.73-84, p<=0.001). In terms of absolute values, MRI provides the lowest volumetric estimates (mean=14.63%), followed by the DM volumetric (mean=22.72%) and area-based measures (mean=29.35%). The MRI estimates of the fibroglandular volume are statistically significantly lower than the DM estimates for women with very low-density breasts (p<=0.001). We attribute these differences to potential partial volume effects in MRI and differences in the computational aspects of the image analysis methods in MRI and DM. The good correlation between the volumetric and the area-based measures, shown to correlate with breast cancer risk, suggests that both DM and MRI volumetric breast density measures can aid in breast cancer risk assessment. Further work is underway to fully-investigate the association between volumetric breast density measures and breast cancer risk.

Comparison of Fundus Autofluorescence Between Fundus Camera and Confocal Scanning Laser Ophthalmoscope–based Systems

PubMed Central

Park, Sung Pyo; Siringo, Frank S.; Pensec, Noelle; Hong, In Hwan; Sparrow, Janet; Barile, Gaetano; Tsang, Stephen H.; Chang, Stanley

2015-01-01

BACKGROUND AND OBJECTIVE To compare fundus autofluorescence (FAF) imaging via fundus camera (FC) and confocal scanning laser ophthalmoscope (cSLO). PATIENTS AND METHODS FAF images were obtained with a digital FC (530 to 580 nm excitation) and a cSLO (488 nm excitation). Two authors evaluated correlation of autofluorescence pattern, atrophic lesion size, and image quality between the two devices. RESULTS In 120 eyes, the autofluorescence pattern correlated in 86% of lesions. By lesion subtype, correlation rates were 100% in hemorrhage, 97% in geographic atrophy, 82% in flecks, 75% in drusen, 70% in exudates, 67% in pigment epithelial detachment, 50% in fibrous scars, and 33% in macular hole. The mean lesion size in geographic atrophy was 4.57 ± 2.3 mm2 via cSLO and 3.81 ± 1.94 mm2 via FC (P < .0001). Image quality favored cSLO in 71 eyes. CONCLUSION FAF images were highly correlated between the FC and cSLO. Differences between the two devices revealed contrasts. Multiple image capture and confocal optics yielded higher image contrast with the cSLO, although acquisition and exposure time was longer. PMID:24221461

Correlation based system to assess the completeness and correctness of cognitive stimulation activities of elders

NASA Astrophysics Data System (ADS)

González-Fraga, J. A.; Morán, A. L.; Meza-Kubo, V.; Tentori, M.; Santiago, E.

2009-08-01

During a cognitive stimulation session where elders with cognitive decline perform stimulation activities, such as solving puzzles, we observed that they require constant supervision and support from their caregivers, and caregivers must be able to monitor the stimulation activity of more than one patient at a time. In this paper, aiming at providing support for the caregiver, we developed a vision-based system using an Phase-SDF filter that generates a composite reference image which is correlated to a captured wooden-puzzle image. The output correlation value allows to automatically verify the progress on the puzzle solving task, and to assess its completeness and correctness.

Use of multidimensional, multimodal imaging and PACS to support neurological diagnoses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, S.T.C.; Knowlton, R.; Hoo, K.S.

1995-12-31

Technological advances in brain imaging have revolutionized diagnosis in neurology and neurological surgery. Major imaging techniques include magnetic resonance imaging (MRI) to visualize structural anatomy, positron emission tomography (PET) to image metabolic function and cerebral blood flow, magnetoencephalography (MEG) to visualize the location of physiologic current sources, and magnetic resonance spectroscopy (MRS) to measure specific biochemicals. Each of these techniques studies different biomedical aspects of the grain, but there lacks an effective means to quantify and correlate the disparate imaging datasets in order to improve clinical decision making processes. This paper describes several techniques developed in a UNIX-based neurodiagnostic workstationmore » to aid the non-invasive presurgical evaluation of epilepsy patients. These techniques include on-line access to the picture archiving and communication systems (PACS) multimedia archive, coregistration of multimodality image datasets, and correlation and quantitative of structural and functional information contained in the registered images. For illustration, the authors describe the use of these techniques in a patient case of non-lesional neocortical epilepsy. They also present the future work based on preliminary studies.« less

Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Time Series Data-fMRI Study.

PubMed

Eslami, Taban; Saeed, Fahad

2018-04-20

Functional magnetic resonance imaging (fMRI) is a non-invasive brain imaging technique, which has been regularly used for studying brain’s functional activities in the past few years. A very well-used measure for capturing functional associations in brain is Pearson’s correlation coefficient. Pearson’s correlation is widely used for constructing functional network and studying dynamic functional connectivity of the brain. These are useful measures for understanding the effects of brain disorders on connectivities among brain regions. The fMRI scanners produce huge number of voxels and using traditional central processing unit (CPU)-based techniques for computing pairwise correlations is very time consuming especially when large number of subjects are being studied. In this paper, we propose a graphics processing unit (GPU)-based algorithm called Fast-GPU-PCC for computing pairwise Pearson’s correlation coefficient. Based on the symmetric property of Pearson’s correlation, this approach returns N ( N − 1 ) / 2 correlation coefficients located at strictly upper triangle part of the correlation matrix. Storing correlations in a one-dimensional array with the order as proposed in this paper is useful for further usage. Our experiments on real and synthetic fMRI data for different number of voxels and varying length of time series show that the proposed approach outperformed state of the art GPU-based techniques as well as the sequential CPU-based versions. We show that Fast-GPU-PCC runs 62 times faster than CPU-based version and about 2 to 3 times faster than two other state of the art GPU-based methods.

Spatiotemporal analysis of tumor uptake patterns in dynamic (18)FDG-PET and dynamic contrast enhanced CT.

PubMed

Malinen, Eirik; Rødal, Jan; Knudtsen, Ingerid Skjei; Søvik, Åste; Skogmo, Hege Kippenes

2011-08-01

Molecular and functional imaging techniques such as dynamic positron emission tomography (DPET) and dynamic contrast enhanced computed tomography (DCECT) may provide improved characterization of tumors compared to conventional anatomic imaging. The purpose of the current work was to compare spatiotemporal uptake patterns in DPET and DCECT images. A PET/CT protocol comprising DCECT with an iodine based contrast agent and DPET with (18)F-fluorodeoxyglucose was set up. The imaging protocol was used for examination of three dogs with spontaneous tumors of the head and neck at sessions prior to and after fractionated radiotherapy. Software tools were developed for downsampling the DCECT image series to the PET image dimensions, for segmentation of tracer uptake pattern in the tumors and for spatiotemporal correlation analysis of DCECT and DPET images. DCECT images evaluated one minute post injection qualitatively resembled the DPET images at most imaging sessions. Segmentation by region growing gave similar tumor extensions in DCECT and DPET images, with a median Dice similarity coefficient of 0.81. A relatively high correlation (median 0.85) was found between temporal tumor uptake patterns from DPET and DCECT. The heterogeneity in tumor uptake was not significantly different in the DPET and DCECT images. The median of the spatial correlation was 0.72. DCECT and DPET gave similar temporal wash-in characteristics, and the images also showed a relatively high spatial correlation. Hence, if the limited spatial resolution of DPET is considered adequate, a single DPET scan only for assessing both tumor perfusion and metabolic activity may be considered. However, further work on a larger number of cases is needed to verify the correlations observed in the present study.

Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction: Repeatability and Accuracy of an MR Imaging-based, Semiautomated Analysis Method.

PubMed

Middleton, Michael S; Haufe, William; Hooker, Jonathan; Borga, Magnus; Dahlqvist Leinhard, Olof; Romu, Thobias; Tunón, Patrik; Hamilton, Gavin; Wolfson, Tanya; Gamst, Anthony; Loomba, Rohit; Sirlin, Claude B

2017-05-01

Purpose To determine the repeatability and accuracy of a commercially available magnetic resonance (MR) imaging-based, semiautomated method to quantify abdominal adipose tissue and thigh muscle volume and hepatic proton density fat fraction (PDFF). Materials and Methods This prospective study was institutional review board- approved and HIPAA compliant. All subjects provided written informed consent. Inclusion criteria were age of 18 years or older and willingness to participate. The exclusion criterion was contraindication to MR imaging. Three-dimensional T1-weighted dual-echo body-coil images were acquired three times. Source images were reconstructed to generate water and calibrated fat images. Abdominal adipose tissue and thigh muscle were segmented, and their volumes were estimated by using a semiautomated method and, as a reference standard, a manual method. Hepatic PDFF was estimated by using a confounder-corrected chemical shift-encoded MR imaging method with hybrid complex-magnitude reconstruction and, as a reference standard, MR spectroscopy. Tissue volume and hepatic PDFF intra- and interexamination repeatability were assessed by using intraclass correlation and coefficient of variation analysis. Tissue volume and hepatic PDFF accuracy were assessed by means of linear regression with the respective reference standards. Results Adipose and thigh muscle tissue volumes of 20 subjects (18 women; age range, 25-76 years; body mass index range, 19.3-43.9 kg/m 2 ) were estimated by using the semiautomated method. Intra- and interexamination intraclass correlation coefficients were 0.996-0.998 and coefficients of variation were 1.5%-3.6%. For hepatic MR imaging PDFF, intra- and interexamination intraclass correlation coefficients were greater than or equal to 0.994 and coefficients of variation were less than or equal to 7.3%. In the regression analyses of manual versus semiautomated volume and spectroscopy versus MR imaging, PDFF slopes and intercepts were close to the identity line, and correlations of determination at multivariate analysis (R 2 ) ranged from 0.744 to 0.994. Conclusion This MR imaging-based, semiautomated method provides high repeatability and accuracy for estimating abdominal adipose tissue and thigh muscle volumes and hepatic PDFF. © RSNA, 2017.

Spread spectrum image watermarking based on perceptual quality metric.

PubMed

Zhang, Fan; Liu, Wenyu; Lin, Weisi; Ngan, King Ngi

2011-11-01

Efficient image watermarking calls for full exploitation of the perceptual distortion constraint. Second-order statistics of visual stimuli are regarded as critical features for perception. This paper proposes a second-order statistics (SOS)-based image quality metric, which considers the texture masking effect and the contrast sensitivity in Karhunen-Loève transform domain. Compared with the state-of-the-art metrics, the quality prediction by SOS better correlates with several subjectively rated image databases, in which the images are impaired by the typical coding and watermarking artifacts. With the explicit metric definition, spread spectrum watermarking is posed as an optimization problem: we search for a watermark to minimize the distortion of the watermarked image and to maximize the correlation between the watermark pattern and the spread spectrum carrier. The simple metric guarantees the optimal watermark a closed-form solution and a fast implementation. The experiments show that the proposed watermarking scheme can take full advantage of the distortion constraint and improve the robustness in return.

3D displacement field measurement with correlation based on the micro-geometrical surface texture

NASA Astrophysics Data System (ADS)

Bubaker-Isheil, Halima; Serri, Jérôme; Fontaine, Jean-François

2011-07-01

Image correlation methods are widely used in experimental mechanics to obtain displacement field measurements. Currently, these methods are applied using digital images of the initial and deformed surfaces sprayed with black or white paint. Speckle patterns are then captured and the correlation is performed with a high degree of accuracy to an order of 0.01 pixels. In 3D, however, stereo-correlation leads to a lower degree of accuracy. Correlation techniques are based on the search for a sub-image (or pattern) displacement field. The work presented in this paper introduces a new correlation-based approach for 3D displacement field measurement that uses an additional 3D laser scanner and a CMM (Coordinate Measurement Machine). Unlike most existing methods that require the presence of markers on the observed object (such as black speckle, grids or random patterns), this approach relies solely on micro-geometrical surface textures such as waviness, roughness and aperiodic random defects. The latter are assumed to remain sufficiently small thus providing an adequate estimate of the particle displacement. The proposed approach can be used in a wide range of applications such as sheet metal forming with large strains. The method proceeds by first obtaining cloud points using the 3D laser scanner mounted on a CMM. These points are used to create 2D maps that are then correlated. In this respect, various criteria have been investigated for creating maps consisting of patterns, which facilitate the correlation procedure. Once the maps are created, the correlation between both configurations (initial and moved) is carried out using traditional methods developed for field measurements. Measurement validation was conducted using experiments in 2D and 3D with good results for rigid displacements in 2D, 3D and 2D rotations.

Tracking quasi-stationary flow of weak fluorescent signals by adaptive multi-frame correlation.

PubMed

Ji, L; Danuser, G

2005-12-01

We have developed a novel cross-correlation technique to probe quasi-stationary flow of fluorescent signals in live cells at a spatial resolution that is close to single particle tracking. By correlating image blocks between pairs of consecutive frames and integrating their correlation scores over multiple frame pairs, uncertainty in identifying a globally significant maximum in the correlation score function has been greatly reduced as compared with conventional correlation-based tracking using the signal of only two consecutive frames. This approach proves robust and very effective in analysing images with a weak, noise-perturbed signal contrast where texture characteristics cannot be matched between only a pair of frames. It can also be applied to images that lack prominent features that could be utilized for particle tracking or feature-based template matching. Furthermore, owing to the integration of correlation scores over multiple frames, the method can handle signals with substantial frame-to-frame intensity variation where conventional correlation-based tracking fails. We tested the performance of the method by tracking polymer flow in actin and microtubule cytoskeleton structures labelled at various fluorophore densities providing imagery with a broad range of signal modulation and noise. In applications to fluorescent speckle microscopy (FSM), where the fluorophore density is sufficiently low to reveal patterns of discrete fluorescent marks referred to as speckles, we combined the multi-frame correlation approach proposed above with particle tracking. This hybrid approach allowed us to follow single speckles robustly in areas of high speckle density and fast flow, where previously published FSM analysis methods were unsuccessful. Thus, we can now probe cytoskeleton polymer dynamics in living cells at an entirely new level of complexity and with unprecedented detail.

A novel iris transillumination grading scale allowing flexible assessment with quantitative image analysis and visual matching.

PubMed

Wang, Chen; Brancusi, Flavia; Valivullah, Zaheer M; Anderson, Michael G; Cunningham, Denise; Hedberg-Buenz, Adam; Power, Bradley; Simeonov, Dimitre; Gahl, William A; Zein, Wadih M; Adams, David R; Brooks, Brian

2018-01-01

To develop a sensitive scale of iris transillumination suitable for clinical and research use, with the capability of either quantitative analysis or visual matching of images. Iris transillumination photographic images were used from 70 study subjects with ocular or oculocutaneous albinism. Subjects represented a broad range of ocular pigmentation. A subset of images was subjected to image analysis and ranking by both expert and nonexpert reviewers. Quantitative ordering of images was compared with ordering by visual inspection. Images were binned to establish an 8-point scale. Ranking consistency was evaluated using the Kendall rank correlation coefficient (Kendall's tau). Visual ranking results were assessed using Kendall's coefficient of concordance (Kendall's W) analysis. There was a high degree of correlation among the image analysis, expert-based and non-expert-based image rankings. Pairwise comparisons of the quantitative ranking with each reviewer generated an average Kendall's tau of 0.83 ± 0.04 (SD). Inter-rater correlation was also high with Kendall's W of 0.96, 0.95, and 0.95 for nonexpert, expert, and all reviewers, respectively. The current standard for assessing iris transillumination is expert assessment of clinical exam findings. We adapted an image-analysis technique to generate quantitative transillumination values. Quantitative ranking was shown to be highly similar to a ranking produced by both expert and nonexpert reviewers. This finding suggests that the image characteristics used to quantify iris transillumination do not require expert interpretation. Inter-rater rankings were also highly similar, suggesting that varied methods of transillumination ranking are robust in terms of producing reproducible results.

Investigation of Thermal Effects of Photocoagulation on Retinal Tissue Using Fine-Motion-Sensitive Dynamic Optical Coherence Tomography.

PubMed

Kurokawa, Kazuhiro; Makita, Shuichi; Yasuno, Yoshiaki

2016-01-01

To enable an objective evaluation of photocoagulation, we characterize thermal tissue changes induced by laser irradiation with different laser parameters using optical coherence tomography (OCT). Spectral-domain OCT with a newly developed image processing method was used to monitor the thermal changes of ex vivo porcine retina. A sequence of OCT B-scans was obtained at the same retinal position simultaneously with the photocoagulation. Cross-sectional tissue displacement maps with respect to an OCT image taken before laser irradiation were computed for images taken before, during, and after laser irradiation, by using a correlation-based custom algorithm. Cross-sectional correlation maps (OCT correlation maps) were also computed from an OCT image taken before laser irradiation as a base-line to visualize alterations of tissue microstructure induced by laser irradiation. By systematically controlling laser power and exposure times, tissue displacements and structural changes of 200 retinal regions of 10 porcine eyes were characterized. Thermal tissue changes were characterized by B-scan images, OCT correlation maps, and tissue displacement maps. Larger tissue deformation was induced with higher laser power and shorter exposure time, while the same total laser energy (10 mJ) was applied. The measured tissue displacements revealed the complicated dynamics of tissue displacements. Three types of dynamics were observed; lateral expansion, lateral constriction, and a type showing more complicated dynamics. The results demonstrated the ability of this OCT-based method to evaluate retinal changes induced by laser irradiation. This evaluation could lead to further understanding of thermal effects, and increasing reproducibility of photocoagulation therapy.

Adaptive Cross-correlation Algorithm and Experiment of Extended Scene Shack-Hartmann Wavefront Sensing

NASA Technical Reports Server (NTRS)

Sidick, Erkin; Morgan, Rhonda M.; Green, Joseph J.; Ohara, Catherine M.; Redding, David C.

2007-01-01

We have developed a new, adaptive cross-correlation (ACC) algorithm to estimate with high accuracy the shift as large as several pixels in two extended-scene images captured by a Shack-Hartmann wavefront sensor (SH-WFS). It determines the positions of all of the extended-scene image cells relative to a reference cell using an FFT-based iterative image shifting algorithm. It works with both point-source spot images as well as extended scene images. We have also set up a testbed for extended0scene SH-WFS, and tested the ACC algorithm with the measured data of both point-source and extended-scene images. In this paper we describe our algorithm and present out experimental results.

Voxel-based correlation between coregistered single-photon emission computed tomography and dynamic susceptibility contrast magnetic resonance imaging in subjects with suspected Alzheimer disease.

PubMed

Cavallin, L; Axelsson, R; Wahlund, L O; Oksengard, A R; Svensson, L; Juhlin, P; Wiberg, M Kristoffersen; Frank, A

2008-12-01

Current diagnosis of Alzheimer disease is made by clinical, neuropsychologic, and neuroimaging assessments. Neuroimaging techniques such as magnetic resonance imaging (MRI) and single-photon emission computed tomography (SPECT) could be valuable in the differential diagnosis of Alzheimer disease, as well as in assessing prognosis. To compare SPECT and MRI in a cohort of patients examined for suspected dementia, including patients with no objective cognitive impairment (control group), mild cognitive impairment (MCI), and Alzheimer disease (AD). 24 patients, eight with AD, 10 with MCI, and six controls, were investigated with SPECT using (99m)Tc-hexamethylpropyleneamine oxime (HMPAO, Ceretec; GE Healthcare Ltd., Little Chalsont UK) and dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) with a contrast-enhancing gadobutrol formula (Gadovist; Bayer Schering Pharma, Berlin, Germany). Voxel-based correlation between coregistered SPECT and DSC-MR images was calculated. Region-of-interest (ROI) analyses were then performed in 24 different brain areas using brain registration and analysis of SPECT studies (BRASS; Nuclear Diagnostics AB, Stockholm, Sweden) on both SPECT and DSC-MRI. Voxel-based correlation between coregistered SPECT and DSC-MR showed a high correlation, with a mean correlation coefficient of 0.94. ROI analyses of 24 regions showed significant differences between the control group and AD patients in 10 regions using SPECT and five regions in DSC-MR. SPECT remains superior to DSC-MRI in differentiating normal from pathological perfusion, and DSC-MRI could not replace SPECT in the diagnosis of patients with Alzheimer disease.

Phase retrieval using regularization method in intensity correlation imaging

NASA Astrophysics Data System (ADS)

Li, Xiyu; Gao, Xin; Tang, Jia; Lu, Changming; Wang, Jianli; Wang, Bin

2014-11-01

Intensity correlation imaging(ICI) method can obtain high resolution image with ground-based low precision mirrors, in the imaging process, phase retrieval algorithm should be used to reconstituted the object's image. But the algorithm now used(such as hybrid input-output algorithm) is sensitive to noise and easy to stagnate. However the signal-to-noise ratio of intensity interferometry is low especially in imaging astronomical objects. In this paper, we build the mathematical model of phase retrieval and simplified it into a constrained optimization problem of a multi-dimensional function. New error function was designed by noise distribution and prior information using regularization method. The simulation results show that the regularization method can improve the performance of phase retrieval algorithm and get better image especially in low SNR condition

SU-E-E-16: The Application of Texture Analysis for Differentiation of Central Cancer From Atelectasis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, M; Fan, T; Duan, J

2015-06-15

Purpose: Prospectively assess the potential utility of texture analysis for differentiation of central cancer from atelectasis. Methods: 0 consecutive central lung cancer patients who were referred for CT imaging and PET-CT were enrolled. Radiotherapy doctor delineate the tumor and atelectasis according to the fusion imaging based on CT image and PET-CT image. The texture parameters (such as energy, correlation, sum average, difference average, difference entropy), were obtained respectively to quantitatively discriminate tumor and atelectasis based on gray level co-occurrence matrix (GLCM) Results: The texture analysis results showed that the parameters of correlation and sum average had an obviously statistical significance(P<0.05).more » Conclusion: the results of this study indicate that texture analysis may be useful for the differentiation of central lung cancer and atelectasis.« less

Multispectral image sharpening using a shift-invariant wavelet transform and adaptive processing of multiresolution edges

USGS Publications Warehouse

Lemeshewsky, G.P.; Rahman, Z.-U.; Schowengerdt, R.A.; Reichenbach, S.E.

2002-01-01

Enhanced false color images from mid-IR, near-IR (NIR), and visible bands of the Landsat thematic mapper (TM) are commonly used for visually interpreting land cover type. Described here is a technique for sharpening or fusion of NIR with higher resolution panchromatic (Pan) that uses a shift-invariant implementation of the discrete wavelet transform (SIDWT) and a reported pixel-based selection rule to combine coefficients. There can be contrast reversals (e.g., at soil-vegetation boundaries between NIR and visible band images) and consequently degraded sharpening and edge artifacts. To improve performance for these conditions, I used a local area-based correlation technique originally reported for comparing image-pyramid-derived edges for the adaptive processing of wavelet-derived edge data. Also, using the redundant data of the SIDWT improves edge data generation. There is additional improvement because sharpened subband imagery is used with the edge-correlation process. A reported technique for sharpening three-band spectral imagery used forward and inverse intensity, hue, and saturation transforms and wavelet-based sharpening of intensity. This technique had limitations with opposite contrast data, and in this study sharpening was applied to single-band multispectral-Pan image pairs. Sharpening used simulated 30-m NIR imagery produced by degrading the spatial resolution of a higher resolution reference. Performance, evaluated by comparison between sharpened and reference image, was improved when sharpened subband data were used with the edge correlation.

Correlation of contrast-detail analysis and clinical image quality assessment in chest radiography with a human cadaver study.

PubMed

De Crop, An; Bacher, Klaus; Van Hoof, Tom; Smeets, Peter V; Smet, Barbara S; Vergauwen, Merel; Kiendys, Urszula; Duyck, Philippe; Verstraete, Koenraad; D'Herde, Katharina; Thierens, Hubert

2012-01-01

To determine the correlation between the clinical and physical image quality of chest images by using cadavers embalmed with the Thiel technique and a contrast-detail phantom. The use of human cadavers fulfilled the requirements of the institutional ethics committee. Clinical image quality was assessed by using three human cadavers embalmed with the Thiel technique, which results in excellent preservation of the flexibility and plasticity of organs and tissues. As a result, lungs can be inflated during image acquisition to simulate the pulmonary anatomy seen on a chest radiograph. Both contrast-detail phantom images and chest images of the Thiel-embalmed bodies were acquired with an amorphous silicon flat-panel detector. Tube voltage (70, 81, 90, 100, 113, 125 kVp), copper filtration (0.1, 0.2, 0.3 mm Cu), and exposure settings (200, 280, 400, 560, 800 speed class) were altered to simulate different quality levels. Four experienced radiologists assessed the image quality by using a visual grading analysis (VGA) technique based on European Quality Criteria for Chest Radiology. The phantom images were scored manually and automatically with use of dedicated software, both resulting in an inverse image quality figure (IQF). Spearman rank correlations between inverse IQFs and VGA scores were calculated. A statistically significant correlation (r = 0.80, P < .01) was observed between the VGA scores and the manually obtained inverse IQFs. Comparison of the VGA scores and the automated evaluated phantom images showed an even better correlation (r = 0.92, P < .001). The results support the value of contrast-detail phantom analysis for evaluating clinical image quality in chest radiography. © RSNA, 2011.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

NASA Astrophysics Data System (ADS)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve the speed and orientation efficiency of target identification effectively, and validate the feasibility of this method primarily.

Experimental results for correlation-based wavefront sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poyneer, L A; Palmer, D W; LaFortune, K N

2005-07-01

Correlation wave-front sensing can improve Adaptive Optics (AO) system performance in two keys areas. For point-source-based AO systems, Correlation is more accurate, more robust to changing conditions and provides lower noise than a centroiding algorithm. Experimental results from the Lick AO system and the SSHCL laser AO system confirm this. For remote imaging, Correlation enables the use of extended objects for wave-front sensing. Results from short horizontal-path experiments will show algorithm properties and requirements.

Correlation between CT-based measured renal volumes and nuclear-renography-based split renal function in living kidney donors. Clinical diagnostic utility and practice patterns.

PubMed

Diez, Alejandro; Powelson, John; Sundaram, Chandru P; Taber, Tim E; Mujtaba, Muhammad A; Yaqub, Muhammad S; Mishler, Dennis P; Goggins, William C; Sharfuddin, Asif A

2014-06-01

Living donor evaluation involves imaging to determine the choice of kidney for nephrectomy. Our aim was to study the diagnostic accuracy and correlation between CT-based volume measurements and split renal function (SRF) as measured by nuclear renography in potential living donors and its impact on kidney selection decision. We analyzed 190 CT-based volume measurements in healthy donors, of which 65 donors had a radionuclide study performed to determine SRF. There were no differences in demographics, anthropometric measurements, total volumes, eGFR, creatinine clearances between those who required a nuclear scan and those who did not. There was a significant correlation between CT-volume-measurement-based SRF and nuclear-scan-based SRF (Pearson coefficient r 0.59; p < 0.001). Furthermore, selective nuclear-based SRF allowed careful selection of donor nephrectomy, leaving the donor with the higher functioning kidney in most cases. There was also a significantly higher number of right-sided nephrectomies selected after nuclear-based SRF studies. CT-based volume measurements in living donor imaging have sufficient correlation with nuclear-based SRF. Selective use of nuclear-scan-based SRF allows careful selection for donor nephrectomy. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Applying Amide Proton Transfer MR Imaging to Hybrid Brain PET/MR: Concordance with Gadolinium Enhancement and Added Value to [18F]FDG PET.

PubMed

Sun, Hongzan; Xin, Jun; Zhou, Jinyuan; Lu, Zaiming; Guo, Qiyong

2018-06-01

The purpose of this study is to evaluate the diagnostic concordance and metric correlations of amide proton transfer (APT) imaging with gadolinium-enhanced magnetic resonance imaging (MRI) and 2-deoxy-2-[ 18 F-]fluoro-D-glucose ([ 18 F]FDG) positron emission tomography (PET), using hybrid brain PET/MRI. Twenty-one subjects underwent brain gadolinium-enhanced [ 18 F]FDG PET/MRI prospectively. Imaging accuracy was compared between unenhanced MRI, MRI with enhancement, APT-weighted (APTW) images, and PET based on six diagnostic criteria. Among tumors, the McNemar test was further used for concordance assessment between gadolinium-enhanced imaging, APT imaging, and [ 18 F]FDG PET. As well, the relation of metrics between APT imaging and PET was analyzed by the Pearson correlation analysis. APT imaging and gadolinium-enhanced MRI showed superior and similar diagnostic accuracy. APTW signal intensity and gadolinium enhancement were concordant in 19 tumors (100 %), while high [ 18 F]FDG avidity was shown in only 12 (63.2 %). For the metrics from APT imaging and PET, there was significant correlation for 13 hypermetabolic tumors (P < 0.05) and no correlation for the remaining six [ 18 F]FDG-avid tumors. APT imaging can be used to increase diagnostic accuracy with no need to administer gadolinium chelates. APT imaging may provide an added value to [ 18 F]FDG PET in the evaluation of tumor metabolic activity during brain PET/MR studies.

Improved maximum average correlation height filter with adaptive log base selection for object recognition

NASA Astrophysics Data System (ADS)

Tehsin, Sara; Rehman, Saad; Awan, Ahmad B.; Chaudry, Qaiser; Abbas, Muhammad; Young, Rupert; Asif, Afia

2016-04-01

Sensitivity to the variations in the reference image is a major concern when recognizing target objects. A combinational framework of correlation filters and logarithmic transformation has been previously reported to resolve this issue alongside catering for scale and rotation changes of the object in the presence of distortion and noise. In this paper, we have extended the work to include the influence of different logarithmic bases on the resultant correlation plane. The meaningful changes in correlation parameters along with contraction/expansion in the correlation plane peak have been identified under different scenarios. Based on our research, we propose some specific log bases to be used in logarithmically transformed correlation filters for achieving suitable tolerance to different variations. The study is based upon testing a range of logarithmic bases for different situations and finding an optimal logarithmic base for each particular set of distortions. Our results show improved correlation and target detection accuracies.

Calculation of left ventricular volumes and ejection fraction from dynamic cardiac-gated 15O-water PET/CT: 5D-PET.

PubMed

Nordström, Jonny; Kero, Tanja; Harms, Hendrik Johannes; Widström, Charles; Flachskampf, Frank A; Sörensen, Jens; Lubberink, Mark

2017-11-14

Quantitative measurement of myocardial blood flow (MBF) is of increasing interest in the clinical assessment of patients with suspected coronary artery disease (CAD). 15 O-water positron emission tomography (PET) is considered the gold standard for non-invasive MBF measurements. However, calculation of left ventricular (LV) volumes and ejection fraction (EF) is not possible from standard 15 O-water uptake images. The purpose of the present work was to investigate the possibility of calculating LV volumes and LVEF from cardiac-gated parametric blood volume (V B ) 15 O-water images and from first pass (FP) images. Sixteen patients with mitral or aortic regurgitation underwent an eight-gate dynamic cardiac-gated 15 O-water PET/CT scan and cardiac MRI. V B and FP images were generated for each gate. Calculations of end-systolic volume (ESV), end-diastolic volume (EDV), stroke volume (SV) and LVEF were performed with automatic segmentation of V B and FP images, using commercially available software. LV volumes and LVEF were calculated with surface-, count-, and volume-based methods, and the results were compared with gold standard MRI. Using V B images, high correlations between PET and MRI ESV (r = 0.89, p < 0.001), EDV (r = 0.85, p < 0.001), SV (r = 0.74, p = 0.006) and LVEF (r = 0.72, p = 0.008) were found for the volume-based method. Correlations for FP images were slightly, but not significantly, lower than those for V B images when compared to MRI. Surface- and count-based methods showed no significant difference compared with the volume-based correlations with MRI. The volume-based method showed the best agreement with MRI with no significant difference on average for EDV and LVEF but with an overestimation of values for ESV (14%, p = 0.005) and SV (18%, p = 0.004) when using V B images. Using FP images, none of the parameters showed a significant difference from MRI. Inter-operator repeatability was excellent for all parameters (ICC > 0.86, p < 0.001). Calculation of LV volumes and LVEF from dynamic 15 O-water PET is feasible and shows good correlation with MRI. However, the analysis method is laborious, and future work is needed for more automation to make the method more easily applicable in a clinical setting.

Score-Level Fusion of Phase-Based and Feature-Based Fingerprint Matching Algorithms

NASA Astrophysics Data System (ADS)

Ito, Koichi; Morita, Ayumi; Aoki, Takafumi; Nakajima, Hiroshi; Kobayashi, Koji; Higuchi, Tatsuo

This paper proposes an efficient fingerprint recognition algorithm combining phase-based image matching and feature-based matching. In our previous work, we have already proposed an efficient fingerprint recognition algorithm using Phase-Only Correlation (POC), and developed commercial fingerprint verification units for access control applications. The use of Fourier phase information of fingerprint images makes it possible to achieve robust recognition for weakly impressed, low-quality fingerprint images. This paper presents an idea of improving the performance of POC-based fingerprint matching by combining it with feature-based matching, where feature-based matching is introduced in order to improve recognition efficiency for images with nonlinear distortion. Experimental evaluation using two different types of fingerprint image databases demonstrates efficient recognition performance of the combination of the POC-based algorithm and the feature-based algorithm.

Photoacoustic phasoscopy super-contrast imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Fei; Feng, Xiaohua; Zheng, Yuanjin, E-mail: yjzheng@ntu.edu.sg

2014-05-26

Phasoscopy is a recently proposed concept correlating electromagnetic (EM) absorption and scattering properties based on energy conservation. Phase information can be extracted from EM absorption induced acoustic wave and scattered EM wave for biological tissue characterization. In this paper, an imaging modality, termed photoacoustic phasoscopy imaging (PAPS), is proposed and verified experimentally based on phasoscopy concept with laser illumination. Both endogenous photoacoustic wave and scattered photons are collected simultaneously to extract the phase information. The PAPS images are then reconstructed on vessel-mimicking phantom and ex vivo porcine tissues to show significantly improved contrast than conventional photoacoustic imaging.

An automated method for tracking clouds in planetary atmospheres

NASA Astrophysics Data System (ADS)

Luz, D.; Berry, D. L.; Roos-Serote, M.

2008-05-01

We present an automated method for cloud tracking which can be applied to planetary images. The method is based on a digital correlator which compares two or more consecutive images and identifies patterns by maximizing correlations between image blocks. This approach bypasses the problem of feature detection. Four variations of the algorithm are tested on real cloud images of Jupiter's white ovals from the Galileo mission, previously analyzed in Vasavada et al. [Vasavada, A.R., Ingersoll, A.P., Banfield, D., Bell, M., Gierasch, P.J., Belton, M.J.S., Orton, G.S., Klaasen, K.P., Dejong, E., Breneman, H.H., Jones, T.J., Kaufman, J.M., Magee, K.P., Senske, D.A. 1998. Galileo imaging of Jupiter's atmosphere: the great red spot, equatorial region, and white ovals. Icarus, 135, 265, doi:10.1006/icar.1998.5984]. Direct correlation, using the sum of squared differences between image radiances as a distance estimator (baseline case), yields displacement vectors very similar to this previous analysis. Combining this distance estimator with the method of order ranks results in a technique which is more robust in the presence of outliers and noise and of better quality. Finally, we introduce a distance metric which, combined with order ranks, provides results of similar quality to the baseline case and is faster. The new approach can be applied to data from a number of space-based imaging instruments with a non-negligible gain in computing time.

An image mosaic method based on corner

NASA Astrophysics Data System (ADS)

Jiang, Zetao; Nie, Heting

2015-08-01

In view of the shortcomings of the traditional image mosaic, this paper describes a new algorithm for image mosaic based on the Harris corner. Firstly, Harris operator combining the constructed low-pass smoothing filter based on splines function and circular window search is applied to detect the image corner, which allows us to have better localisation performance and effectively avoid the phenomenon of cluster. Secondly, the correlation feature registration is used to find registration pair, remove the false registration using random sampling consensus. Finally use the method of weighted trigonometric combined with interpolation function for image fusion. The experiments show that this method can effectively remove the splicing ghosting and improve the accuracy of image mosaic.

A secure image encryption method based on dynamic harmony search (DHS) combined with chaotic map

NASA Astrophysics Data System (ADS)

Mirzaei Talarposhti, Khadijeh; Khaki Jamei, Mehrzad

2016-06-01

In recent years, there has been increasing interest in the security of digital images. This study focuses on the gray scale image encryption using dynamic harmony search (DHS). In this research, first, a chaotic map is used to create cipher images, and then the maximum entropy and minimum correlation coefficient is obtained by applying a harmony search algorithm on them. This process is divided into two steps. In the first step, the diffusion of a plain image using DHS to maximize the entropy as a fitness function will be performed. However, in the second step, a horizontal and vertical permutation will be applied on the best cipher image, which is obtained in the previous step. Additionally, DHS has been used to minimize the correlation coefficient as a fitness function in the second step. The simulation results have shown that by using the proposed method, the maximum entropy and the minimum correlation coefficient, which are approximately 7.9998 and 0.0001, respectively, have been obtained.

Incoherent digital holograms acquired by interferenceless coded aperture correlation holography system without refractive lenses.

PubMed

Kumar, Manoj; Vijayakumar, A; Rosen, Joseph

2017-09-14

We present a lensless, interferenceless incoherent digital holography technique based on the principle of coded aperture correlation holography. The acquired digital hologram by this technique contains a three-dimensional image of some observed scene. Light diffracted by a point object (pinhole) is modulated using a random-like coded phase mask (CPM) and the intensity pattern is recorded and composed as a point spread hologram (PSH). A library of PSHs is created using the same CPM by moving the pinhole to all possible axial locations. Intensity diffracted through the same CPM from an object placed within the axial limits of the PSH library is recorded by a digital camera. The recorded intensity this time is composed as the object hologram. The image of the object at any axial plane is reconstructed by cross-correlating the object hologram with the corresponding component of the PSH library. The reconstruction noise attached to the image is suppressed by various methods. The reconstruction results of multiplane and thick objects by this technique are compared with regular lens-based imaging.

Objective quality assessment for multiexposure multifocus image fusion.

PubMed

Hassen, Rania; Wang, Zhou; Salama, Magdy M A

2015-09-01

There has been a growing interest in image fusion technologies, but how to objectively evaluate the quality of fused images has not been fully understood. Here, we propose a method for objective quality assessment of multiexposure multifocus image fusion based on the evaluation of three key factors of fused image quality: 1) contrast preservation; 2) sharpness; and 3) structure preservation. Subjective experiments are conducted to create an image fusion database, based on which, performance evaluation shows that the proposed fusion quality index correlates well with subjective scores, and gives a significant improvement over the existing fusion quality measures.

SU-F-J-94: Development of a Plug-in Based Image Analysis Tool for Integration Into Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Owen, D; Anderson, C; Mayo, C

Purpose: To extend the functionality of a commercial treatment planning system (TPS) to support (i) direct use of quantitative image-based metrics within treatment plan optimization and (ii) evaluation of dose-functional volume relationships to assist in functional image adaptive radiotherapy. Methods: A script was written that interfaces with a commercial TPS via an Application Programming Interface (API). The script executes a program that performs dose-functional volume analyses. Written in C#, the script reads the dose grid and correlates it with image data on a voxel-by-voxel basis through API extensions that can access registration transforms. A user interface was designed through WinFormsmore » to input parameters and display results. To test the performance of this program, image- and dose-based metrics computed from perfusion SPECT images aligned to the treatment planning CT were generated, validated, and compared. Results: The integration of image analysis information was successfully implemented as a plug-in to a commercial TPS. Perfusion SPECT images were used to validate the calculation and display of image-based metrics as well as dose-intensity metrics and histograms for defined structures on the treatment planning CT. Various biological dose correction models, custom image-based metrics, dose-intensity computations, and dose-intensity histograms were applied to analyze the image-dose profile. Conclusion: It is possible to add image analysis features to commercial TPSs through custom scripting applications. A tool was developed to enable the evaluation of image-intensity-based metrics in the context of functional targeting and avoidance. In addition to providing dose-intensity metrics and histograms that can be easily extracted from a plan database and correlated with outcomes, the system can also be extended to a plug-in optimization system, which can directly use the computed metrics for optimization of post-treatment tumor or normal tissue response models. Supported by NIH - P01 - CA059827.« less

Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns.

PubMed

Pan, Shaoming; Li, Yongkai; Xu, Zhengquan; Chong, Yanwen

2015-01-01

Declustering techniques are widely used in distributed environments to reduce query response time through parallel I/O by splitting large files into several small blocks and then distributing those blocks among multiple storage nodes. Unfortunately, however, many small geospatial image data files cannot be further split for distributed storage. In this paper, we propose a complete theoretical system for the distributed storage of small geospatial image data files based on mining the access patterns of geospatial image data using their historical access log information. First, an algorithm is developed to construct an access correlation matrix based on the analysis of the log information, which reveals the patterns of access to the geospatial image data. Then, a practical heuristic algorithm is developed to determine a reasonable solution based on the access correlation matrix. Finally, a number of comparative experiments are presented, demonstrating that our algorithm displays a higher total parallel access probability than those of other algorithms by approximately 10-15% and that the performance can be further improved by more than 20% by simultaneously applying a copy storage strategy. These experiments show that the algorithm can be applied in distributed environments to help realize parallel I/O and thereby improve system performance.

The Effect of Training Data Set Composition on the Performance of a Neural Image Caption Generator

DTIC Science & Technology

2017-09-01

objects was compared using the Metric for Evaluation of Translation with Explicit Ordering (METEOR) and Consensus-Based Image Description Evaluation...using automated scoring systems. Many such systems exist, including Bilingual Evaluation Understudy (BLEU), Consensus-Based Image Description Evaluation...shown to be essential to automated scoring, which correlates highly with human precision.5 CIDEr uses a system of consensus among the captions and

Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using {sup 68}Ga-labeled nanoparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kipritidis, John, E-mail: john.kipritidis@sydney.edu.au; Keall, Paul J.; Siva, Shankar

Purpose: CT ventilation imaging is a novel functional lung imaging modality based on deformable image registration. The authors present the first validation study of CT ventilation using positron emission tomography with{sup 68}Ga-labeled nanoparticles (PET-Galligas). The authors quantify this agreement for different CT ventilation metrics and PET reconstruction parameters. Methods: PET-Galligas ventilation scans were acquired for 12 lung cancer patients using a four-dimensional (4D) PET/CT scanner. CT ventilation images were then produced by applying B-spline deformable image registration between the respiratory correlated phases of the 4D-CT. The authors test four ventilation metrics, two existing and two modified. The two existing metricsmore » model mechanical ventilation (alveolar air-flow) based on Hounsfield unit (HU) change (V{sub HU}) or Jacobian determinant of deformation (V{sub Jac}). The two modified metrics incorporate a voxel-wise tissue-density scaling (ρV{sub HU} and ρV{sub Jac}) and were hypothesized to better model the physiological ventilation. In order to assess the impact of PET image quality, comparisons were performed using both standard and respiratory-gated PET images with the former exhibiting better signal. Different median filtering kernels (σ{sub m} = 0 or 3 mm) were also applied to all images. As in previous studies, similarity metrics included the Spearman correlation coefficient r within the segmented lung volumes, and Dice coefficient d{sub 20} for the (0 − 20)th functional percentile volumes. Results: The best agreement between CT and PET ventilation was obtained comparing standard PET images to the density-scaled HU metric (ρV{sub HU}) with σ{sub m} = 3 mm. This leads to correlation values in the ranges 0.22 ⩽ r ⩽ 0.76 and 0.38 ⩽ d{sub 20} ⩽ 0.68, with r{sup ¯}=0.42±0.16 and d{sup ¯}{sub 20}=0.52±0.09 averaged over the 12 patients. Compared to Jacobian-based metrics, HU-based metrics lead to statistically significant improvements in r{sup ¯} and d{sup ¯}{sub 20} (p < 0.05), with density scaled metrics also showing higher r{sup ¯} than for unscaled versions (p < 0.02). r{sup ¯} and d{sup ¯}{sub 20} were also sensitive to image quality, with statistically significant improvements using standard (as opposed to gated) PET images and with application of median filtering. Conclusions: The use of modified CT ventilation metrics, in conjunction with PET-Galligas and careful application of image filtering has resulted in improved correlation compared to earlier studies using nuclear medicine ventilation. However, CT ventilation and PET-Galligas do not always provide the same functional information. The authors have demonstrated that the agreement can improve for CT ventilation metrics incorporating a tissue density scaling, and also with increasing PET image quality. CT ventilation imaging has clear potential for imaging regional air volume change in the lung, and further development is warranted.« less

Voxel-based statistical analysis of uncertainties associated with deformable image registration

NASA Astrophysics Data System (ADS)

Li, Shunshan; Glide-Hurst, Carri; Lu, Mei; Kim, Jinkoo; Wen, Ning; Adams, Jeffrey N.; Gordon, James; Chetty, Indrin J.; Zhong, Hualiang

2013-09-01

Deformable image registration (DIR) algorithms have inherent uncertainties in their displacement vector fields (DVFs).The purpose of this study is to develop an optimal metric to estimate DIR uncertainties. Six computational phantoms have been developed from the CT images of lung cancer patients using a finite element method (FEM). The FEM generated DVFs were used as a standard for registrations performed on each of these phantoms. A mechanics-based metric, unbalanced energy (UE), was developed to evaluate these registration DVFs. The potential correlation between UE and DIR errors was explored using multivariate analysis, and the results were validated by landmark approach and compared with two other error metrics: DVF inverse consistency (IC) and image intensity difference (ID). Landmark-based validation was performed using the POPI-model. The results show that the Pearson correlation coefficient between UE and DIR error is rUE-error = 0.50. This is higher than rIC-error = 0.29 for IC and DIR error and rID-error = 0.37 for ID and DIR error. The Pearson correlation coefficient between UE and the product of the DIR displacements and errors is rUE-error × DVF = 0.62 for the six patients and rUE-error × DVF = 0.73 for the POPI-model data. It has been demonstrated that UE has a strong correlation with DIR errors, and the UE metric outperforms the IC and ID metrics in estimating DIR uncertainties. The quantified UE metric can be a useful tool for adaptive treatment strategies, including probability-based adaptive treatment planning.

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Yueqi; Lava, Pascal; Reu, Phillip

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

Theoretical analysis on the measurement errors of local 2D DIC: Part I temporal and spatial uncertainty quantification of displacement measurements

DOE PAGES

Wang, Yueqi; Lava, Pascal; Reu, Phillip; ...

2015-12-23

This study presents a theoretical uncertainty quantification of displacement measurements by subset-based 2D-digital image correlation. A generalized solution to estimate the random error of displacement measurement is presented. The obtained solution suggests that the random error of displacement measurements is determined by the image noise, the summation of the intensity gradient in a subset, the subpixel part of displacement, and the interpolation scheme. The proposed method is validated with virtual digital image correlation tests.

Compress compound images in H.264/MPGE-4 AVC by exploiting spatial correlation.

PubMed

Lan, Cuiling; Shi, Guangming; Wu, Feng

2010-04-01

Compound images are a combination of text, graphics and natural image. They present strong anisotropic features, especially on the text and graphics parts. These anisotropic features often render conventional compression inefficient. Thus, this paper proposes a novel coding scheme from the H.264 intraframe coding. In the scheme, two new intramodes are developed to better exploit spatial correlation in compound images. The first is the residual scalar quantization (RSQ) mode, where intrapredicted residues are directly quantized and coded without transform. The second is the base colors and index map (BCIM) mode that can be viewed as an adaptive color quantization. In this mode, an image block is represented by several representative colors, referred to as base colors, and an index map to compress. Every block selects its coding mode from two new modes and the previous intramodes in H.264 by rate-distortion optimization (RDO). Experimental results show that the proposed scheme improves the coding efficiency even more than 10 dB at most bit rates for compound images and keeps a comparable efficient performance to H.264 for natural images.

Novel Image Encryption Scheme Based on Chebyshev Polynomial and Duffing Map

PubMed Central

2014-01-01

We present a novel image encryption algorithm using Chebyshev polynomial based on permutation and substitution and Duffing map based on substitution. Comprehensive security analysis has been performed on the designed scheme using key space analysis, visual testing, histogram analysis, information entropy calculation, correlation coefficient analysis, differential analysis, key sensitivity test, and speed test. The study demonstrates that the proposed image encryption algorithm shows advantages of more than 10113 key space and desirable level of security based on the good statistical results and theoretical arguments. PMID:25143970

Quantitative 4D Transcatheter Intraarterial Perfusion MR Imaging as a Method to Standardize Angiographic Chemoembolization Endpoints

PubMed Central

Jin, Brian; Wang, Dingxin; Lewandowski, Robert J.; Ryu, Robert K.; Sato, Kent T.; Larson, Andrew C.; Salem, Riad; Omary, Reed A.

2011-01-01

PURPOSE We aimed to test the hypothesis that subjective angiographic endpoints during transarterial chemoembolization (TACE) of hepatocellular carcinoma (HCC) exhibit consistency and correlate with objective intraprocedural reductions in tumor perfusion as determined by quantitative four dimensional (4D) transcatheter intraarterial perfusion (TRIP) magnetic resonance (MR) imaging. MATERIALS AND METHODS This prospective study was approved by the institutional review board. Eighteen consecutive patients underwent TACE in a combined MR/interventional radiology (MR-IR) suite. Three board-certified interventional radiologists independently graded the angiographic endpoint of each procedure based on a previously described subjective angiographic chemoembolization endpoint (SACE) scale. A consensus SACE rating was established for each patient. Patients underwent quantitative 4D TRIP-MR imaging immediately before and after TACE, from which mean whole tumor perfusion (Fρ) was calculated. Consistency of SACE ratings between observers was evaluated using the intraclass correlation coefficient (ICC). The relationship between SACE ratings and intraprocedural TRIP-MR imaging perfusion changes was evaluated using Spearman’s rank correlation coefficient. RESULTS The SACE rating scale demonstrated very good consistency among all observers (ICC = 0.80). The consensus SACE rating was significantly correlated with both absolute (r = 0.54, P = 0.022) and percent (r = 0.85, P < 0.001) intraprocedural perfusion reduction. CONCLUSION The SACE rating scale demonstrates very good consistency between raters, and significantly correlates with objectively measured intraprocedural perfusion reductions during TACE. These results support the use of the SACE scale as a standardized alternative method to quantitative 4D TRIP-MR imaging to classify patients based on embolic endpoints of TACE. PMID:22021520

The Utility of the Extended Images in Ambient Seismic Wavefield Migration

NASA Astrophysics Data System (ADS)

Girard, A. J.; Shragge, J. C.

2015-12-01

Active-source 3D seismic migration and migration velocity analysis (MVA) are robust and highly used methods for imaging Earth structure. One class of migration methods uses extended images constructed by incorporating spatial and/or temporal wavefield correlation lags to the imaging conditions. These extended images allow users to directly assess whether images focus better with different parameters, which leads to MVA techniques that are based on the tenets of adjoint-state theory. Under certain conditions (e.g., geographical, cultural or financial), however, active-source methods can prove impractical. Utilizing ambient seismic energy that naturally propagates through the Earth is an alternate method currently used in the scientific community. Thus, an open question is whether extended images are similarly useful for ambient seismic migration processing and verifying subsurface velocity models, and whether one can similarly apply adjoint-state methods to perform ambient migration velocity analysis (AMVA). Herein, we conduct a number of numerical experiments that construct extended images from ambient seismic recordings. We demonstrate that, similar to active-source methods, there is a sensitivity to velocity in ambient seismic recordings in the migrated extended image domain. In synthetic ambient imaging tests with varying degrees of error introduced to the velocity model, the extended images are sensitive to velocity model errors. To determine the extent of this sensitivity, we utilize acoustic wave-equation propagation and cross-correlation-based migration methods to image weak body-wave signals present in the recordings. Importantly, we have also observed scenarios where non-zero correlation lags show signal while zero-lags show none. This may be a valuable missing piece for ambient migration techniques that have yielded largely inconclusive results, and might be an important piece of information for performing AMVA from ambient seismic recordings.

High-speed technique based on a parallel projection correlation procedure for digital image correlation

NASA Astrophysics Data System (ADS)

Zaripov, D. I.; Renfu, Li

2018-05-01

The implementation of high-efficiency digital image correlation methods based on a zero-normalized cross-correlation (ZNCC) procedure for high-speed, time-resolved measurements using a high-resolution digital camera is associated with big data processing and is often time consuming. In order to speed-up ZNCC computation, a high-speed technique based on a parallel projection correlation procedure is proposed. The proposed technique involves the use of interrogation window projections instead of its two-dimensional field of luminous intensity. This simplification allows acceleration of ZNCC computation up to 28.8 times compared to ZNCC calculated directly, depending on the size of interrogation window and region of interest. The results of three synthetic test cases, such as a one-dimensional uniform flow, a linear shear flow and a turbulent boundary-layer flow, are discussed in terms of accuracy. In the latter case, the proposed technique is implemented together with an iterative window-deformation technique. On the basis of the results of the present work, the proposed technique is recommended to be used for initial velocity field calculation, with further correction using more accurate techniques.

Knee osteoarthritis image registration: data from the Osteoarthritis Initiative

NASA Astrophysics Data System (ADS)

Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Treviño, Victor; Tamez-Peña, José G.

2015-03-01

Knee osteoarthritis is a very common disease, in early stages, changes in joint structures are shown, some of the most common symptoms are; formation of osteophytes, cartilage degradation and joint space reduction, among others. Based on a joint space reduction measurement, Kellgren-Lawrence grading scale, is a very extensive used tool to asses radiological OA knee x-ray images, based on information obtained from these assessments, the objective of this work is to correlate the Kellgren-Lawrence score to the bilateral asymmetry between knees. Using public data from the Osteoarthritis initiative (OAI), a set of images with different Kellgren-Lawrencescores were used to determine a relationship of Kellgren-Lawrence score and the bilateral asymmetry, in order to measure the asymmetry between the knees, the right knee was registered to match the left knee, then a series of similarity metrics, mutual information, correlation, and mean squared error where computed to correlate the deformation (mismatch) of the knees to the Kellgren-Lawrence score. Radiological information was evaluated and scored by OAI radiologist groups. The results of the study suggest an association between Radiological Kellgren-Lawrence score and image registration metrics, mutual information and correlation is higher in the early stages, and mean squared error is higher in advanced stages. This association can be helpful to develop a computer aided grading tool.

Speaker-independent phoneme recognition with a binaural auditory image model

NASA Astrophysics Data System (ADS)

Francis, Keith Ivan

1997-09-01

This dissertation presents phoneme recognition techniques based on a binaural fusion of outputs of the auditory image model and subsequent azimuth-selective phoneme recognition in a noisy environment. Background information concerning speech variations, phoneme recognition, current binaural fusion techniques and auditory modeling issues is explained. The research is constrained to sources in the frontal azimuthal plane of a simulated listener. A new method based on coincidence detection of neural activity patterns from the auditory image model of Patterson is used for azimuth-selective phoneme recognition. The method is tested in various levels of noise and the results are reported in contrast to binaural fusion methods based on various forms of correlation to demonstrate the potential of coincidence- based binaural phoneme recognition. This method overcomes smearing of fine speech detail typical of correlation based methods. Nevertheless, coincidence is able to measure similarity of left and right inputs and fuse them into useful feature vectors for phoneme recognition in noise.

Ultrafast Target Recognition via Super-Parallel Holograph Based Correlator, RAM and Associative Memory

DTIC Science & Technology

2008-03-11

JTC) 2𔃾 based on a dynamic material answers the challenge of fast correlation with large databases. Images retrieved from the SPHRAM and used as the...transform (JTC) and matched spatial filter or VanderLugt ( VLC ) correlators, either of which can be implemented in real-time by degenerate four wave-mixing in...proposed system, consisting of the SPHROM coupled with a shift-invariant real-time VLC . The correlation is performed in the VLC architecture to

Incoherent coincidence imaging of space objects

NASA Astrophysics Data System (ADS)

Mao, Tianyi; Chen, Qian; He, Weiji; Gu, Guohua

2016-10-01

Incoherent Coincidence Imaging (ICI), which is based on the second or higher order correlation of fluctuating light field, has provided great potentialities with respect to standard conventional imaging. However, the deployment of reference arm limits its practical applications in the detection of space objects. In this article, an optical aperture synthesis with electronically connected single-pixel photo-detectors was proposed to remove the reference arm. The correlation in our proposed method is the second order correlation between the intensity fluctuations observed by any two detectors. With appropriate locations of single-pixel detectors, this second order correlation is simplified to absolute-square Fourier transform of source and the unknown object. We demonstrate the image recovery with the Gerchberg-Saxton-like algorithms and investigate the reconstruction quality of our approach. Numerical experiments has been made to show that both binary and gray-scale objects can be recovered. This proposed method provides an effective approach to promote detection of space objects and perhaps even the exo-planets.

A correlative imaging based methodology for accurate quantitative assessment of bone formation in additive manufactured implants.

PubMed

Geng, Hua; Todd, Naomi M; Devlin-Mullin, Aine; Poologasundarampillai, Gowsihan; Kim, Taek Bo; Madi, Kamel; Cartmell, Sarah; Mitchell, Christopher A; Jones, Julian R; Lee, Peter D

2016-06-01

A correlative imaging methodology was developed to accurately quantify bone formation in the complex lattice structure of additive manufactured implants. Micro computed tomography (μCT) and histomorphometry were combined, integrating the best features from both, while demonstrating the limitations of each imaging modality. This semi-automatic methodology registered each modality using a coarse graining technique to speed the registration of 2D histology sections to high resolution 3D μCT datasets. Once registered, histomorphometric qualitative and quantitative bone descriptors were directly correlated to 3D quantitative bone descriptors, such as bone ingrowth and bone contact. The correlative imaging allowed the significant volumetric shrinkage of histology sections to be quantified for the first time (~15 %). This technique demonstrated the importance of location of the histological section, demonstrating that up to a 30 % offset can be introduced. The results were used to quantitatively demonstrate the effectiveness of 3D printed titanium lattice implants.

Trends in Correlation-Based Pattern Recognition and Tracking in Forward-Looking Infrared Imagery

PubMed Central

Alam, Mohammad S.; Bhuiyan, Sharif M. A.

2014-01-01

In this paper, we review the recent trends and advancements on correlation-based pattern recognition and tracking in forward-looking infrared (FLIR) imagery. In particular, we discuss matched filter-based correlation techniques for target detection and tracking which are widely used for various real time applications. We analyze and present test results involving recently reported matched filters such as the maximum average correlation height (MACH) filter and its variants, and distance classifier correlation filter (DCCF) and its variants. Test results are presented for both single/multiple target detection and tracking using various real-life FLIR image sequences. PMID:25061840

Lower-upper-threshold correlation for underwater range-gated imaging self-adaptive enhancement.

PubMed

Sun, Liang; Wang, Xinwei; Liu, Xiaoquan; Ren, Pengdao; Lei, Pingshun; He, Jun; Fan, Songtao; Zhou, Yan; Liu, Yuliang

2016-10-10

In underwater range-gated imaging (URGI), enhancement of low-brightness and low-contrast images is critical for human observation. Traditional histogram equalizations over-enhance images, with the result of details being lost. To compress over-enhancement, a lower-upper-threshold correlation method is proposed for underwater range-gated imaging self-adaptive enhancement based on double-plateau histogram equalization. The lower threshold determines image details and compresses over-enhancement. It is correlated with the upper threshold. First, the upper threshold is updated by searching for the local maximum in real time, and then the lower threshold is calculated by the upper threshold and the number of nonzero units selected from a filtered histogram. With this method, the backgrounds of underwater images are constrained with enhanced details. Finally, the proof experiments are performed. Peak signal-to-noise-ratio, variance, contrast, and human visual properties are used to evaluate the objective quality of the global and regions of interest images. The evaluation results demonstrate that the proposed method adaptively selects the proper upper and lower thresholds under different conditions. The proposed method contributes to URGI with effective image enhancement for human eyes.

Global rotational motion and displacement estimation of digital image stabilization based on the oblique vectors matching algorithm

NASA Astrophysics Data System (ADS)

Yu, Fei; Hui, Mei; Zhao, Yue-jin

2009-08-01

The image block matching algorithm based on motion vectors of correlative pixels in oblique direction is presented for digital image stabilization. The digital image stabilization is a new generation of image stabilization technique which can obtains the information of relative motion among frames of dynamic image sequences by the method of digital image processing. In this method the matching parameters are calculated from the vectors projected in the oblique direction. The matching parameters based on the vectors contain the information of vectors in transverse and vertical direction in the image blocks at the same time. So the better matching information can be obtained after making correlative operation in the oblique direction. And an iterative weighted least square method is used to eliminate the error of block matching. The weights are related with the pixels' rotational angle. The center of rotation and the global emotion estimation of the shaking image can be obtained by the weighted least square from the estimation of each block chosen evenly from the image. Then, the shaking image can be stabilized with the center of rotation and the global emotion estimation. Also, the algorithm can run at real time by the method of simulated annealing in searching method of block matching. An image processing system based on DSP was used to exam this algorithm. The core processor in the DSP system is TMS320C6416 of TI, and the CCD camera with definition of 720×576 pixels was chosen as the input video signal. Experimental results show that the algorithm can be performed at the real time processing system and have an accurate matching precision.

A review of supervised object-based land-cover image classification

NASA Astrophysics Data System (ADS)

Ma, Lei; Li, Manchun; Ma, Xiaoxue; Cheng, Liang; Du, Peijun; Liu, Yongxue

2017-08-01

Object-based image classification for land-cover mapping purposes using remote-sensing imagery has attracted significant attention in recent years. Numerous studies conducted over the past decade have investigated a broad array of sensors, feature selection, classifiers, and other factors of interest. However, these research results have not yet been synthesized to provide coherent guidance on the effect of different supervised object-based land-cover classification processes. In this study, we first construct a database with 28 fields using qualitative and quantitative information extracted from 254 experimental cases described in 173 scientific papers. Second, the results of the meta-analysis are reported, including general characteristics of the studies (e.g., the geographic range of relevant institutes, preferred journals) and the relationships between factors of interest (e.g., spatial resolution and study area or optimal segmentation scale, accuracy and number of targeted classes), especially with respect to the classification accuracy of different sensors, segmentation scale, training set size, supervised classifiers, and land-cover types. Third, useful data on supervised object-based image classification are determined from the meta-analysis. For example, we find that supervised object-based classification is currently experiencing rapid advances, while development of the fuzzy technique is limited in the object-based framework. Furthermore, spatial resolution correlates with the optimal segmentation scale and study area, and Random Forest (RF) shows the best performance in object-based classification. The area-based accuracy assessment method can obtain stable classification performance, and indicates a strong correlation between accuracy and training set size, while the accuracy of the point-based method is likely to be unstable due to mixed objects. In addition, the overall accuracy benefits from higher spatial resolution images (e.g., unmanned aerial vehicle) or agricultural sites where it also correlates with the number of targeted classes. More than 95.6% of studies involve an area less than 300 ha, and the spatial resolution of images is predominantly between 0 and 2 m. Furthermore, we identify some methods that may advance supervised object-based image classification. For example, deep learning and type-2 fuzzy techniques may further improve classification accuracy. Lastly, scientists are strongly encouraged to report results of uncertainty studies to further explore the effects of varied factors on supervised object-based image classification.

Submillisievert Radiation Dose Coronary CT Angiography: Clinical Impact of the Knowledge-Based Iterative Model Reconstruction.

PubMed

Iyama, Yuji; Nakaura, Takeshi; Kidoh, Masafumi; Oda, Seitaro; Utsunomiya, Daisuke; Sakaino, Naritsugu; Tokuyasu, Shinichi; Osakabe, Hirokazu; Harada, Kazunori; Yamashita, Yasuyuki

2016-11-01

The purpose of this study was to evaluate the noise and image quality of images reconstructed with a knowledge-based iterative model reconstruction (knowledge-based IMR) in ultra-low dose cardiac computed tomography (CT). We performed submillisievert radiation dose coronary CT angiography on 43 patients. We also performed a phantom study to evaluate the influence of object size with the automatic exposure control phantom. We reconstructed clinical and phantom studies with filtered back projection (FBP), hybrid iterative reconstruction (hybrid IR), and knowledge-based IMR. We measured effective dose of patients and compared CT number, image noise, and contrast noise ratio in ascending aorta of each reconstruction technique. We compared the relationship between image noise and body mass index for the clinical study, and object size for phantom study. The mean effective dose was 0.98 ± 0.25 mSv. The image noise of knowledge-based IMR images was significantly lower than those of FBP and hybrid IR images (knowledge-based IMR: 19.4 ± 2.8; FBP: 126.7 ± 35.0; hybrid IR: 48.8 ± 12.8, respectively) (P < .01). The contrast noise ratio of knowledge-based IMR images was significantly higher than those of FBP and hybrid IR images (knowledge-based IMR: 29.1 ± 5.4; FBP: 4.6 ± 1.3; hybrid IR: 13.1 ± 3.5, respectively) (P < .01). There were moderate correlations between image noise and body mass index in FBP (r = 0.57, P < .01) and hybrid IR techniques (r = 0.42, P < .01); however, these correlations were weak in knowledge-based IMR (r = 0.27, P < .01). Compared to FBP and hybrid IR, the knowledge-based IMR offers significant noise reduction and improvement in image quality in submillisievert radiation dose cardiac CT. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Quantum correlation enhanced super-resolution localization microscopy enabled by a fibre bundle camera

PubMed Central

Israel, Yonatan; Tenne, Ron; Oron, Dan; Silberberg, Yaron

2017-01-01

Despite advances in low-light-level detection, single-photon methods such as photon correlation have rarely been used in the context of imaging. The few demonstrations, for example of subdiffraction-limited imaging utilizing quantum statistics of photons, have remained in the realm of proof-of-principle demonstrations. This is primarily due to a combination of low values of fill factors, quantum efficiencies, frame rates and signal-to-noise characteristic of most available single-photon sensitive imaging detectors. Here we describe an imaging device based on a fibre bundle coupled to single-photon avalanche detectors that combines a large fill factor, a high quantum efficiency, a low noise and scalable architecture. Our device enables localization-based super-resolution microscopy in a non-sparse non-stationary scene, utilizing information on the number of active emitters, as gathered from non-classical photon statistics. PMID:28287167

Neuroanatomical Correlates of Theory of Mind Deficit in Parkinson’s Disease: A Multimodal Imaging Study

PubMed Central

Díez-Cirarda, María; Ojeda, Natalia; Peña, Javier; Cabrera-Zubizarreta, Alberto; Gómez-Beldarrain, María Ángeles; Gómez-Esteban, Juan Carlos; Ibarretxe-Bilbao, Naroa

2015-01-01

Background Parkinson’s disease (PD) patients show theory of mind (ToM) deficit since the early stages of the disease, and this deficit has been associated with working memory, executive functions and quality of life impairment. To date, neuroanatomical correlates of ToM have not been assessed with magnetic resonance imaging in PD. The main objective of this study was to assess cerebral correlates of ToM deficit in PD. The second objective was to explore the relationships between ToM, working memory and executive functions, and to analyse the neural correlates of ToM, controlling for both working memory and executive functions. Methods Thirty-seven PD patients (Hoehn and Yahr median = 2.0) and 15 healthy controls underwent a neuropsychological assessment and magnetic resonance images in a 3T-scanner were acquired. T1-weighted images were analysed with voxel-based morphometry, and white matter integrity and diffusivity measures were obtained from diffusion weighted images and analysed using tract-based spatial statistics. Results PD patients showed impairments in ToM, working memory and executive functions; grey matter loss and white matter reduction compared to healthy controls. Grey matter volume decrease in the precentral and postcentral gyrus, middle and inferior frontal gyrus correlated with ToM deficit in PD. White matter in the superior longitudinal fasciculus (adjacent to the parietal lobe) and white matter adjacent to the frontal lobe correlated with ToM impairment in PD. After controlling for executive functions, the relationship between ToM deficit and white matter remained significant for white matter areas adjacent to the precuneus and the parietal lobe. Conclusions Findings reinforce the existence of ToM impairment from the early Hoehn and Yahr stages in PD, and the findings suggest associations with white matter and grey matter volume decrease. This study contributes to better understand ToM deficit and its neural correlates in PD, which is a basic skill for development of healthy social relationships. PMID:26559669

Neuroanatomical Correlates of Theory of Mind Deficit in Parkinson's Disease: A Multimodal Imaging Study.

PubMed

Díez-Cirarda, María; Ojeda, Natalia; Peña, Javier; Cabrera-Zubizarreta, Alberto; Gómez-Beldarrain, María Ángeles; Gómez-Esteban, Juan Carlos; Ibarretxe-Bilbao, Naroa

2015-01-01

Parkinson's disease (PD) patients show theory of mind (ToM) deficit since the early stages of the disease, and this deficit has been associated with working memory, executive functions and quality of life impairment. To date, neuroanatomical correlates of ToM have not been assessed with magnetic resonance imaging in PD. The main objective of this study was to assess cerebral correlates of ToM deficit in PD. The second objective was to explore the relationships between ToM, working memory and executive functions, and to analyse the neural correlates of ToM, controlling for both working memory and executive functions. Thirty-seven PD patients (Hoehn and Yahr median = 2.0) and 15 healthy controls underwent a neuropsychological assessment and magnetic resonance images in a 3T-scanner were acquired. T1-weighted images were analysed with voxel-based morphometry, and white matter integrity and diffusivity measures were obtained from diffusion weighted images and analysed using tract-based spatial statistics. PD patients showed impairments in ToM, working memory and executive functions; grey matter loss and white matter reduction compared to healthy controls. Grey matter volume decrease in the precentral and postcentral gyrus, middle and inferior frontal gyrus correlated with ToM deficit in PD. White matter in the superior longitudinal fasciculus (adjacent to the parietal lobe) and white matter adjacent to the frontal lobe correlated with ToM impairment in PD. After controlling for executive functions, the relationship between ToM deficit and white matter remained significant for white matter areas adjacent to the precuneus and the parietal lobe. Findings reinforce the existence of ToM impairment from the early Hoehn and Yahr stages in PD, and the findings suggest associations with white matter and grey matter volume decrease. This study contributes to better understand ToM deficit and its neural correlates in PD, which is a basic skill for development of healthy social relationships.

Information content exploitation of imaging spectrometer's images for lossless compression

NASA Astrophysics Data System (ADS)

Wang, Jianyu; Zhu, Zhenyu; Lin, Kan

1996-11-01

Imaging spectrometer, such as MAIS produces a tremendous volume of image data with up to 5.12 Mbps raw data rate, which needs urgently a real-time, efficient and reversible compression implementation. Between the lossy scheme with high compression ratio and the lossless scheme with high fidelity, we must make our choice based on the particular information content analysis of each imaging spectrometer's image data. In this paper, we present a careful analysis of information-preserving compression of imaging spectrometer MAIS with an entropy and autocorrelation study on the hyperspectral images. First, the statistical information in an actual MAIS image, captured in Marble Bar Australia, is measured with its entropy, conditional entropy, mutual information and autocorrelation coefficients on both spatial dimensions and spectral dimension. With these careful analyses, it is shown that there is high redundancy existing in the spatial dimensions, but the correlation in spectral dimension of the raw images is smaller than expected. The main reason of the nonstationarity on spectral dimension is attributed to the instruments's discrepancy on detector's response and channel's amplification in different spectral bands. To restore its natural correlation, we preprocess the signal in advance. There are two methods to accomplish this requirement: onboard radiation calibration and normalization. A better result can be achieved by the former one. After preprocessing, the spectral correlation increases so high that it contributes much redundancy in addition to spatial correlation. At last, an on-board hardware implementation for the lossless compression is presented with an ideal result.

Image analysis to evaluate the browning degree of banana (Musa spp.) peel.

PubMed

Cho, Jeong-Seok; Lee, Hyeon-Jeong; Park, Jung-Hoon; Sung, Jun-Hyung; Choi, Ji-Young; Moon, Kwang-Deog

2016-03-01

Image analysis was applied to examine banana peel browning. The banana samples were divided into 3 treatment groups: no treatment and normal packaging (Cont); CO2 gas exchange packaging (CO); normal packaging with an ethylene generator (ET). We confirmed that the browning of banana peels developed more quickly in the CO group than the other groups based on sensory test and enzyme assay. The G (green) and CIE L(∗), a(∗), and b(∗) values obtained from the image analysis sharply increased or decreased in the CO group. And these colour values showed high correlation coefficients (>0.9) with the sensory test results. CIE L(∗)a(∗)b(∗) values using a colorimeter also showed high correlation coefficients but comparatively lower than those of image analysis. Based on this analysis, browning of the banana occurred more quickly for CO2 gas exchange packaging, and image analysis can be used to evaluate the browning of banana peels. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mapping correlations between ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer’s disease, mild cognitive impairment and elderly controls

PubMed Central

Chou, Yi-Yu; Leporé, Natasha; Avedissian, Christina; Madsen, Sarah K.; Parikshak, Neelroop; Hua, Xue; Shaw, Leslie M.; Trojanowski, John Q.; Weiner, Michael W.; Toga, Arthur W.; Thompson, Paul M.

2009-01-01

Automated ventricular mapping with multi-atlas fluid image alignment reveals genetic effects in Alzheimer’s disease, NeuroImage 40(2): 615–630); with this method, we calculated minimal numbers of subjects needed to detect correlations between clinical scores and ventricular maps. We also assessed correlations between emerging CSF biomarkers of Alzheimer’s disease pathology and localizable deficits in the brain, in 80 AD, 80 mild cognitive impairment (MCI), and 80 healthy controls from the Alzheimer’s Disease Neuroimaging Initiative. Six expertly segmented images and their embedded parametric mesh surfaces were fluidly registered to each brain; segmentations were averaged within subjects to reduce errors. Surface-based statistical maps revealed powerful correlations between surface morphology and 4 variables: (1) diagnosis, (2) depression severity, (3) cognitive function at baseline, and (4) future cognitive decline over the following year. Cognitive function was assessed using the mini-mental state exam (MMSE), global and sum-of-boxes clinical dementia rating (CDR) scores, at baseline and 1-year follow-up. Lower CSF Aβ1–42 protein levels, a biomarker of AD pathology assessed in 138 of the 240 subjects, were correlated with lateral ventricular expansion. Using false discovery rate (FDR) methods, 40 and 120 subjects, respectively, were needed to discriminate AD and MCI from normal groups. 120 subjects were required to detect correlations between ventricular enlargement and MMSE, global CDR, sum-of-boxes CDR and clinical depression scores. Ventricular expansion maps correlate with pathological and cognitive measures in AD, and may be useful in future imaging-based clinical trials. PMID:19236926

Through-the-Wall Radar Simulations for Complex Room Imaging

DTIC Science & Technology

2010-05-01

obtained by combining images from different aspect angles. We demonstrate the advantages of using cross -polarization for detecting human targets. We...3. Numerical Results 6 3.1 SAR Images from a Ground-based Radar System ..........................................................6 3.2 Using Cross ...bottom row contains the cross -correlation between the images created by the two methods. ....................16 vi Acknowledgments This study

Radiogenomics of hepatocellular carcinoma: multiregion analysis-based identification of prognostic imaging biomarkers by integrating gene data—a preliminary study

NASA Astrophysics Data System (ADS)

Xia, Wei; Chen, Ying; Zhang, Rui; Yan, Zhuangzhi; Zhou, Xiaobo; Zhang, Bo; Gao, Xin

2018-02-01

Our objective was to identify prognostic imaging biomarkers for hepatocellular carcinoma in contrast-enhanced computed tomography (CECT) with biological interpretations by associating imaging features and gene modules. We retrospectively analyzed 371 patients who had gene expression profiles. For the 38 patients with CECT imaging data, automatic intra-tumor partitioning was performed, resulting in three spatially distinct subregions. We extracted a total of 37 quantitative imaging features describing intensity, geometry, and texture from each subregion. Imaging features were selected after robustness and redundancy analysis. Gene modules acquired from clustering were chosen for their prognostic significance. By constructing an association map between imaging features and gene modules with Spearman rank correlations, the imaging features that significantly correlated with gene modules were obtained. These features were evaluated with Cox’s proportional hazard models and Kaplan-Meier estimates to determine their prognostic capabilities for overall survival (OS). Eight imaging features were significantly correlated with prognostic gene modules, and two of them were associated with OS. Among these, the geometry feature volume fraction of the subregion, which was significantly correlated with all prognostic gene modules representing cancer-related interpretation, was predictive of OS (Cox p  =  0.022, hazard ratio  =  0.24). The texture feature cluster prominence in the subregion, which was correlated with the prognostic gene module representing lipid metabolism and complement activation, also had the ability to predict OS (Cox p  =  0.021, hazard ratio  =  0.17). Imaging features depicting the volume fraction and textural heterogeneity in subregions have the potential to be predictors of OS with interpretable biological meaning.

Speckle tracking imaging in inflammatory heart diseases.

PubMed

Leitman, Marina; Vered, Zvi; Tyomkin, Vladimir; Macogon, Boris; Moravsky, Gil; Peleg, Eli; Copel, Laurian

2018-05-01

Accurate diagnosis of acute myocarditis is important for the prognosis and risk stratification of these patients. Cardiac magnetic resonance (CMR) has become a major modality for diagnosis of myocarditis, but not widely available. In this study, we tried to evaluate regional and global longitudinal strain by speckle tracking echocardiography in patients with acute inflammatory myocardial diseases in correlation with CMR. Patients with suspected acute myocarditis were recruited prospectively. Clinical diagnosis was established based on clinical, electrocardiographic, laboratory and conventional echocardiographic data. All patients underwent CMR and repeat echocardiographic examination within 24 h of CMR. Echocardiographic examinations were analyzed offline with speckle tracking imaging software. Thirty-two patients with acute perimyocarditis and myopericarditis were included. Mean age was 29 ± 8, 30 males. All patients presented with chest pain and an abnormal electrocardiogram, in 28 ST elevation was found. Troponin was elevated in 30 and was 0.7 ± 0.5 ng/ml. Creatine kinase was 487 ± 319 U. LVEF was 56 ± 5%. Wall motion abnormalities were present in postero-lateral (53%), and inferior wall (21%). Delayed enhancement on CMR was found in 29 patients. Echocardiographic EF based on speckle tracking imaging correlated with CMR calculated EF. There was a positive correlation between the amplitude of regional strain and delayed enhancement, r = 0.52. Sensitivity and specificity of regional strain for prediction of delayed enhancement was 85 and 73% respectively. Speckle tracking imaging can help in the diagnosis of acute myocarditis when CMR is not readily available. Speckle tracking imaging based EF correlates with CMR calculated LVEF and with global strain.

Design of a cathodoluminescence image generator using a Raspberry Pi coupled to a scanning electron microscope.

PubMed

Benítez, Alfredo; Santiago, Ulises; Sanchez, John E; Ponce, Arturo

2018-01-01

In this work, an innovative cathodoluminescence (CL) system is coupled to a scanning electron microscope and synchronized with a Raspberry Pi computer integrated with an innovative processing signal. The post-processing signal is based on a Python algorithm that correlates the CL and secondary electron (SE) images with a precise dwell time correction. For CL imaging, the emission signal is collected through an optical fiber and transduced to an electrical signal via a photomultiplier tube (PMT). CL Images are registered in a panchromatic mode and can be filtered using a monochromator connected between the optical fiber and the PMT to produce monochromatic CL images. The designed system has been employed to study ZnO samples prepared by electrical arc discharge and microwave methods. CL images are compared with SE images and chemical elemental mapping images to correlate the emission regions of the sample.

Design of a cathodoluminescence image generator using a Raspberry Pi coupled to a scanning electron microscope

NASA Astrophysics Data System (ADS)

Benítez, Alfredo; Santiago, Ulises; Sanchez, John E.; Ponce, Arturo

2018-01-01

In this work, an innovative cathodoluminescence (CL) system is coupled to a scanning electron microscope and synchronized with a Raspberry Pi computer integrated with an innovative processing signal. The post-processing signal is based on a Python algorithm that correlates the CL and secondary electron (SE) images with a precise dwell time correction. For CL imaging, the emission signal is collected through an optical fiber and transduced to an electrical signal via a photomultiplier tube (PMT). CL Images are registered in a panchromatic mode and can be filtered using a monochromator connected between the optical fiber and the PMT to produce monochromatic CL images. The designed system has been employed to study ZnO samples prepared by electrical arc discharge and microwave methods. CL images are compared with SE images and chemical elemental mapping images to correlate the emission regions of the sample.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tanabe, S; Utsunomiya, S; Abe, E

Purpose: To assess an accuracy of fiducial maker-based setup using ExacTrac (ExT-based setup) as compared with soft tissue-based setup using Cone-beam CT (CBCT-based setup) for patients with prostate cancer receiving intensity-modulated radiation therapy (IMRT) for the purpose of investigating whether ExT-based setup can be an alternative to CBCT-based setup. Methods: The setup accuracy was analyzed prospectively for 7 prostate cancer patients with implanted three fiducial markers received IMRT. All patients were treated after CBCT-based setup was performed and corresponding shifts were recorded. ExacTrac images were obtained before and after CBCT-based setup. The fiducial marker-based shifts were calculated based on thosemore » two images and recorded on the assumption that the setup correction was carried out by fiducial marker-based auto correction. Mean and standard deviation of absolute differences and the correlation between CBCT and ExT shifts were estimated. Results: A total of 178 image dataset were analyzed. On the differences between CBCT and ExT shifts, 133 (75%) of 178 image dataset resulted in smaller differences than 3 mm in all dimensions. Mean differences in the anterior-posterior (AP), superior-inferior (SI), and left-right (LR) dimensions were 1.8 ± 1.9 mm, 0.7 ± 1.9 mm, and 0.6 ± 0.8 mm, respectively. The percentages of shift agreements within ±3 mm were 76% for AP, 90% for SI, and 100% for LR. The Pearson coefficient of correlation for CBCT and ExT shifts were 0.80 for AP, 0.80 for SI, and 0.65 for LR. Conclusion: This work showed that the accuracy of ExT-based setup was correlated with that of CBCT-based setup, implying that ExT-based setup has a potential ability to be an alternative to CBCT-based setup. The further work is to specify the conditions that ExT-based setup can provide the accuracy comparable to CBCT-based setup.« less

Computerized tool mark comparison

NASA Astrophysics Data System (ADS)

Feigin, Gavriel; Aperman, Arie; Springer, Eliot; Jungmann, Noam

1995-09-01

The computerized toolmark comparison system is based on a cross correlation between a striation mark left by a tool on a lock and a test mark made by a suspect or the data base. The cross correlation is applied in the frequency domain for time saving. The area to be correlated is defined by the toolmark expert. A profile line is calculated and displayed based on the defined area. The two compared images may appear relatively shifted to one another, or only part of the toolmark that appears in the other. The same length of profiles is chosen from the two samples for entering to the updated correlation process. All possible correlations are checked by cutting and shifting through all cobinations. The database contains the defined images and the profiles calculated from them. The system consists of a 486 PC with a frame grabber and a video camera attached to a microscope. Results show that if the striation marks are clear and are wider than a minimum pixel limit, the correlation result higher than 0.6 is a possible match and has to be checked by the expert for a final decision. Future plans are to implement a 2D correlation. This method will enable us to deal with combinations of striations which are found frequently in real case work.

Optimal monochromatic color combinations for fusion imaging of FDG-PET and diffusion-weighted MR images.

PubMed

Kamei, Ryotaro; Watanabe, Yuji; Sagiyama, Koji; Isoda, Takuro; Togao, Osamu; Honda, Hiroshi

2018-05-23

To investigate the optimal monochromatic color combination for fusion imaging of FDG-PET and diffusion-weighted MR images (DW) regarding lesion conspicuity of each image. Six linear monochromatic color-maps of red, blue, green, cyan, magenta, and yellow were assigned to each of the FDG-PET and DW images. Total perceptual color differences of the lesions were calculated based on the lightness and chromaticity measured with the photometer. Visual lesion conspicuity was also compared among the PET-only, DW-only and PET-DW-double positive portions with mean conspicuity scores. Statistical analysis was performed with a one-way analysis of variance and Spearman's rank correlation coefficient. Among all the 12 possible monochromatic color-map combinations, the 3 combinations of red/cyan, magenta/green, and red/green produced the highest conspicuity scores. Total color differences between PET-positive and double-positive portions correlated with conspicuity scores (ρ = 0.2933, p < 0.005). Lightness differences showed a significant negative correlation with conspicuity scores between the PET-only and DWI-only positive portions. Chromaticity differences showed a marginally significant correlation with conspicuity scores between DWI-positive and double-positive portions. Monochromatic color combinations can facilitate the visual evaluation of FDG-uptake and diffusivity as well as registration accuracy on the FDG-PET/DW fusion images, when red- and green-colored elements are assigned to FDG-PET and DW images, respectively.

Mapped Landmark Algorithm for Precision Landing

NASA Technical Reports Server (NTRS)

Johnson, Andrew; Ansar, Adnan; Matthies, Larry

2007-01-01

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Investigation of Portevin-Le Chatelier effect in 5456 Al-based alloy using digital image correlation

NASA Astrophysics Data System (ADS)

Cheng, Teng; Xu, Xiaohai; Cai, Yulong; Fu, Shihua; Gao, Yue; Su, Yong; Zhang, Yong; Zhang, Qingchuan

2015-02-01

A variety of experimental methods have been proposed for Portevin-Le Chatelier (PLC) effect. They mainly focused on the in-plane deformation. In order to achieve the high-accuracy measurement, three-dimensional digital image correlation (3D-DIC) was employed in this work to investigate the PLC effect in 5456 Al-based alloy. The temporal and spatial evolutions of deformation in the full field of specimen surface were observed. The large deformation of localized necking was determined experimentally. The distributions of out-of-plane displacement over the loading procedure were also obtained. Furthermore, a comparison of measurement accuracy between two-dimensional digital image correlation (2D-DIC) and 3D-DIC was also performed. Due to the theoretical restriction, the measurement accuracy of 2D-DIC decreases with the increase of deformation. A maximum discrepancy of about 20% with 3D-DIC was observed in this work. Therefore, 3D-DIC is actually more essential for the high-accuracy investigation of PLC effect.

New regularization scheme for blind color image deconvolution

NASA Astrophysics Data System (ADS)

Chen, Li; He, Yu; Yap, Kim-Hui

2011-01-01

This paper proposes a new regularization scheme to address blind color image deconvolution. Color images generally have a significant correlation among the red, green, and blue channels. Conventional blind monochromatic deconvolution algorithms handle each color image channels independently, thereby ignoring the interchannel correlation present in the color images. In view of this, a unified regularization scheme for image is developed to recover edges of color images and reduce color artifacts. In addition, by using the color image properties, a spectral-based regularization operator is adopted to impose constraints on the blurs. Further, this paper proposes a reinforcement regularization framework that integrates a soft parametric learning term in addressing blind color image deconvolution. A blur modeling scheme is developed to evaluate the relevance of manifold parametric blur structures, and the information is integrated into the deconvolution scheme. An optimization procedure called alternating minimization is then employed to iteratively minimize the image- and blur-domain cost functions. Experimental results show that the method is able to achieve satisfactory restored color images under different blurring conditions.

Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features.

PubMed

Rios Velazquez, Emmanuel; Meier, Raphael; Dunn, William D; Alexander, Brian; Wiest, Roland; Bauer, Stefan; Gutman, David A; Reyes, Mauricio; Aerts, Hugo J W L

2015-11-18

Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. MRI sets of 109 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA). Spearman's correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Auto-segmented sub-volumes showed moderate to high agreement with manually delineated volumes (range (r): 0.4 - 0.86). Also, the auto and manual volumes showed similar correlation with VASARI features (auto r = 0.35, 0.43 and 0.36; manual r = 0.17, 0.67, 0.41, for contrast-enhancing, necrosis and edema, respectively). The auto-segmented contrast-enhancing volume and post-contrast abnormal volume showed the highest AUC (0.66, CI: 0.55-0.77 and 0.65, CI: 0.54-0.76), comparable to manually defined volumes (0.64, CI: 0.53-0.75 and 0.63, CI: 0.52-0.74, respectively). BraTumIA and manual tumor sub-compartments showed comparable performance in terms of prognosis and correlation with VASARI features. This method can enable more reproducible definition and quantification of imaging based biomarkers and has potential in high-throughput medical imaging research.

Relationships of pediatric anthropometrics for CT protocol selection.

PubMed

Phillips, Grace S; Stanescu, Arta-Luana; Alessio, Adam M

2014-07-01

Determining the optimal CT technique to minimize patient radiation exposure while maintaining diagnostic utility requires patient-specific protocols that are based on patient characteristics. This work develops relationships between different anthropometrics and CT image noise to determine appropriate protocol classification schemes. We measured the image noise in 387 CT examinations of pediatric patients (222 boys, 165 girls) of the chest, abdomen, and pelvis and generated mathematic relationships between image noise and patient lateral and anteroposterior dimensions, age, and weight. At the chest level, lateral distance (ld) across the body is strongly correlated with weight (ld = 0.23 × weight + 16.77; R(2) = 0.93) and is less well correlated with age (ld = 1.10 × age + 17.13; R(2) = 0.84). Similar trends were found for anteroposterior dimensions and at the abdomen level. Across all studies, when acquisition-specific parameters are factored out of the noise, the log of image noise was highly correlated with lateral distance (R(2) = 0.72) and weight (R(2) = 0.72) and was less correlated with age (R(2) = 0.62). Following first-order relationships of image noise and scanner technique, plots were formed to show techniques that could achieve matched noise across the pediatric population. Patient lateral distance and weight are essentially equally effective metrics to base maximum technique settings for pediatric patient-specific protocols. These metrics can also be used to help categorize appropriate reference levels for CT technique and size-specific dose estimates across the pediatric population.

Single-step scanner-based digital image correlation (SB-DIC) method for large deformation mapping in rubber

NASA Astrophysics Data System (ADS)

Goh, C. P.; Ismail, H.; Yen, K. S.; Ratnam, M. M.

2017-01-01

The incremental digital image correlation (DIC) method has been applied in the past to determine strain in large deformation materials like rubber. This method is, however, prone to cumulative errors since the total displacement is determined by combining the displacements in numerous stages of the deformation. In this work, a method of mapping large strains in rubber using DIC in a single-step without the need for a series of deformation images is proposed. The reference subsets were deformed using deformation factors obtained from the fitted mean stress-axial stretch ratio curve obtained experimentally and the theoretical Poisson function. The deformed reference subsets were then correlated with the deformed image after loading. The recently developed scanner-based digital image correlation (SB-DIC) method was applied on dumbbell rubber specimens to obtain the in-plane displacement fields up to 350% axial strain. Comparison of the mean axial strains determined from the single-step SB-DIC method with those from the incremental SB-DIC method showed an average difference of 4.7%. Two rectangular rubber specimens containing circular and square holes were deformed and analysed using the proposed method. The resultant strain maps from the single-step SB-DIC method were compared with the results of finite element modeling (FEM). The comparison shows that the proposed single-step SB-DIC method can be used to map the strain distribution accurately in large deformation materials like rubber at much shorter time compared to the incremental DIC method.

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalisedcross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalised cross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Correlation between positron emission tomography and Cerenkov luminescence imaging in vivo and ex vivo using 64Cu-labeled antibodies in a neuroblastoma mouse model.

PubMed

Maier, Florian C; Schmitt, Julia; Maurer, Andreas; Ehrlichmann, Walter; Reischl, Gerald; Nikolaou, Konstantin; Handgretinger, Rupert; Pichler, Bernd J; Thaiss, Wolfgang M

2016-10-11

Antibody-based therapies gain momentum in clinical therapy, thus the need for accurate imaging modalities with respect to target identification and therapy monitoring are of increasing relevance. Cerenkov luminescence imaging (CLI) are a novel method detecting charged particles emitted during radioactive decay with optical imaging. Here, we compare Position Emission Tomography (PET) with CLI in a multimodal imaging study aiming at the fast and efficient screening of monoclonal antibodies (mAb) designated for targeting of the neuroblastoma-characteristic epitope disialoganglioside GD2. Neuroblastoma-bearing SHO mice were injected with a 64Cu-labeled GD2-specific mAb. The tumor uptake was imaged 3 h, 24 h and 48 h after tracer injection with both, PET and CLI, and was compared to the accumulation in GD2-negative control tumors (human embryonic kidney, HEK-293). In addition to an in vivo PET/CLI-correlation over time, we also demonstrate linear correlations of CLI- and γ-counter-based biodistribution analysis. CLI with its comparably short acquisition time can thus be used as an attractive one-stop-shop modality for the longitudinal monitoring of antibody-based tumor targeting and ex vivo biodistribution.These findings suggest CLI as a reliable alternative for PET and biodistribution studies with respect to fast and high-throughput screenings in subcutaneous tumors traced with radiolabeled antibodies. However, in contrast to PET, CLI is not limited to positron-emitting isotopes and can therefore also be used for the visualization of mAb labeled with therapeutic isotopes like electron emitters.

Alterations in white matter volume and its correlation with neuropsychological scales in patients with Alzheimer's disease: a DARTEL-based voxel-based morphometry study.

PubMed

Moon, Chung-Man; Shin, Il-Seon; Jeong, Gwang-Woo

2017-02-01

Background Non-invasive imaging markers can be used to diagnose Alzheimer's disease (AD) in its early stages, but an optimized quantification analysis to measure the brain integrity has been less studied. Purpose To evaluate white matter volume change and its correlation with neuropsychological scales in patients with AD using a diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL)-based voxel-based morphometry (VBM). Material and Methods The 21 participants comprised 11 patients with AD and 10 age-matched healthy controls. High-resolution magnetic resonance imaging (MRI) data were processed by VBM analysis based on DARTEL algorithm. Results The patients showed significant white matter volume reductions in the posterior limb of the internal capsule, cerebral peduncle of the midbrain, and parahippocampal gyrus compared to healthy controls. In correlation analysis, the parahippocampal volume was positively correlated with the Korean-mini mental state examination score in AD. Conclusion This study provides an evidence for localized white matter volume deficits in conjunction with cognitive dysfunction in AD. These findings would be helpful to understand the neuroanatomical mechanisms in AD and to robust the diagnostic accuracy for AD.

Topographical and Chemical Imaging of a Phase Separated Polymer Using a Combined Atomic Force Microscopy/Infrared Spectroscopy/Mass Spectrometry Platform

DOE PAGES

Tai, Tamin; Karácsony, Orsolya; Bocharova, Vera; ...

2016-02-18

This article describes how the use of a hybrid atomic force microscopy/infrared spectroscopy/mass spectrometry imaging platform was demonstrated for the acquisition and correlation of nanoscale sample surface topography and chemical images based on infrared spectroscopy and mass spectrometry.

Automated Ki-67 Quantification of Immunohistochemical Staining Image of Human Nasopharyngeal Carcinoma Xenografts.

PubMed

Shi, Peng; Zhong, Jing; Hong, Jinsheng; Huang, Rongfang; Wang, Kaijun; Chen, Yunbin

2016-08-26

Nasopharyngeal carcinoma is one of the malignant neoplasm with high incidence in China and south-east Asia. Ki-67 protein is strictly associated with cell proliferation and malignant degree. Cells with higher Ki-67 expression are always sensitive to chemotherapy and radiotherapy, the assessment of which is beneficial to NPC treatment. It is still challenging to automatically analyze immunohistochemical Ki-67 staining nasopharyngeal carcinoma images due to the uneven color distributions in different cell types. In order to solve the problem, an automated image processing pipeline based on clustering of local correlation features is proposed in this paper. Unlike traditional morphology-based methods, our algorithm segments cells by classifying image pixels on the basis of local pixel correlations from particularly selected color spaces, then characterizes cells with a set of grading criteria for the reference of pathological analysis. Experimental results showed high accuracy and robustness in nucleus segmentation despite image data variance. Quantitative indicators obtained in this essay provide a reliable evidence for the analysis of Ki-67 staining nasopharyngeal carcinoma microscopic images, which would be helpful in relevant histopathological researches.

3D Wavelet-Based Filter and Method

DOEpatents

Moss, William C.; Haase, Sebastian; Sedat, John W.

2008-08-12

A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.

Correlation mapping: rapid method for retrieving microcirculation morphology from optical coherence tomography intensity images

NASA Astrophysics Data System (ADS)

Jonathan, E.; Enfield, J.; Leahy, M. J.

2011-03-01

The microcirculation plays a critical role is maintaining organ health and function by serving as a vascular are where trophic metabolism exchanges between blood and tissue takes place. To facilitate regular assessment in vivo, noninvasive microcirculation imagers are required in clinics. Among this group of clinical devices, are those that render microcirculation morphology such as nailfold capillaroscopy, a common device for early diagnosis and monitoring of microangiopathies. However, depth ambiguity disqualify this and other similar techniques in medical tomography where due to the 3-D nature of biological organs, imagers that support depth-resolved 2-D imaging and 3-D image reconstruction are required. Here, we introduce correlation map OCT (cmOCT), a promising technique for microcirculation morphology imaging that combines standard optical coherence tomography and an agile imaging analysis software based on correlation statistic. Promising results are presented of the microcirculation morphology images of the brain region of a small animal model as well as measurements of vessel geometry at bifurcations, such as vessel diameters, branch angles. These data will be useful for obtaining cardiovascular related characteristics such as volumetric flow, velocity profile and vessel-wall shear stress for circulatory and respiratory system.

Correlation based efficient face recognition and color change detection

NASA Astrophysics Data System (ADS)

Elbouz, M.; Alfalou, A.; Brosseau, C.; Alam, M. S.; Qasmi, S.

2013-01-01

Identifying the human face via correlation is a topic attracting widespread interest. At the heart of this technique lies the comparison of an unknown target image to a known reference database of images. However, the color information in the target image remains notoriously difficult to interpret. In this paper, we report a new technique which: (i) is robust against illumination change, (ii) offers discrimination ability to detect color change between faces having similar shape, and (iii) is specifically designed to detect red colored stains (i.e. facial bleeding). We adopt the Vanderlugt correlator (VLC) architecture with a segmented phase filter and we decompose the color target image using normalized red, green, and blue (RGB), and hue, saturation, and value (HSV) scales. We propose a new strategy to effectively utilize color information in signatures for further increasing the discrimination ability. The proposed algorithm has been found to be very efficient for discriminating face subjects with different skin colors, and those having color stains in different areas of the facial image.

Pulsed terahertz imaging of breast cancer in freshly excised murine tumors

NASA Astrophysics Data System (ADS)

Bowman, Tyler; Chavez, Tanny; Khan, Kamrul; Wu, Jingxian; Chakraborty, Avishek; Rajaram, Narasimhan; Bailey, Keith; El-Shenawee, Magda

2018-02-01

This paper investigates terahertz (THz) imaging and classification of freshly excised murine xenograft breast cancer tumors. These tumors are grown via injection of E0771 breast adenocarcinoma cells into the flank of mice maintained on high-fat diet. Within 1 h of excision, the tumor and adjacent tissues are imaged using a pulsed THz system in the reflection mode. The THz images are classified using a statistical Bayesian mixture model with unsupervised and supervised approaches. Correlation with digitized pathology images is conducted using classification images assigned by a modal class decision rule. The corresponding receiver operating characteristic curves are obtained based on the classification results. A total of 13 tumor samples obtained from 9 tumors are investigated. The results show good correlation of THz images with pathology results in all samples of cancer and fat tissues. For tumor samples of cancer, fat, and muscle tissues, THz images show reasonable correlation with pathology where the primary challenge lies in the overlapping dielectric properties of cancer and muscle tissues. The use of a supervised regression approach shows improvement in the classification images although not consistently in all tissue regions. Advancing THz imaging of breast tumors from mice and the development of accurate statistical models will ultimately progress the technique for the assessment of human breast tumor margins.

Sparse models for correlative and integrative analysis of imaging and genetic data

PubMed Central

Lin, Dongdong; Cao, Hongbao; Calhoun, Vince D.

2014-01-01

The development of advanced medical imaging technologies and high-throughput genomic measurements has enhanced our ability to understand their interplay as well as their relationship with human behavior by integrating these two types of datasets. However, the high dimensionality and heterogeneity of these datasets presents a challenge to conventional statistical methods; there is a high demand for the development of both correlative and integrative analysis approaches. Here, we review our recent work on developing sparse representation based approaches to address this challenge. We show how sparse models are applied to the correlation and integration of imaging and genetic data for biomarker identification. We present examples on how these approaches are used for the detection of risk genes and classification of complex diseases such as schizophrenia. Finally, we discuss future directions on the integration of multiple imaging and genomic datasets including their interactions such as epistasis. PMID:25218561

Ground-Cover Measurements: Assessing Correlation Among Aerial and Ground-Based Methods

NASA Astrophysics Data System (ADS)

Booth, D. Terrance; Cox, Samuel E.; Meikle, Tim; Zuuring, Hans R.

2008-12-01

Wyoming’s Green Mountain Common Allotment is public land providing livestock forage, wildlife habitat, and unfenced solitude, amid other ecological services. It is also the center of ongoing debate over USDI Bureau of Land Management’s (BLM) adjudication of land uses. Monitoring resource use is a BLM responsibility, but conventional monitoring is inadequate for the vast areas encompassed in this and other public-land units. New monitoring methods are needed that will reduce monitoring costs. An understanding of data-set relationships among old and new methods is also needed. This study compared two conventional methods with two remote sensing methods using images captured from two meters and 100 meters above ground level from a camera stand (a ground, image-based method) and a light airplane (an aerial, image-based method). Image analysis used SamplePoint or VegMeasure software. Aerial methods allowed for increased sampling intensity at low cost relative to the time and travel required by ground methods. Costs to acquire the aerial imagery and measure ground cover on 162 aerial samples representing 9000 ha were less than 3000. The four highest correlations among data sets for bare ground—the ground-cover characteristic yielding the highest correlations (r)—ranged from 0.76 to 0.85 and included ground with ground, ground with aerial, and aerial with aerial data-set associations. We conclude that our aerial surveys are a cost-effective monitoring method, that ground with aerial data-set correlations can be equal to, or greater than those among ground-based data sets, and that bare ground should continue to be investigated and tested for use as a key indicator of rangeland health.

Correlation coefficient based supervised locally linear embedding for pulmonary nodule recognition.

PubMed

Wu, Panpan; Xia, Kewen; Yu, Hengyong

2016-11-01

Dimensionality reduction techniques are developed to suppress the negative effects of high dimensional feature space of lung CT images on classification performance in computer aided detection (CAD) systems for pulmonary nodule detection. An improved supervised locally linear embedding (SLLE) algorithm is proposed based on the concept of correlation coefficient. The Spearman's rank correlation coefficient is introduced to adjust the distance metric in the SLLE algorithm to ensure that more suitable neighborhood points could be identified, and thus to enhance the discriminating power of embedded data. The proposed Spearman's rank correlation coefficient based SLLE (SC(2)SLLE) is implemented and validated in our pilot CAD system using a clinical dataset collected from the publicly available lung image database consortium and image database resource initiative (LICD-IDRI). Particularly, a representative CAD system for solitary pulmonary nodule detection is designed and implemented. After a sequential medical image processing steps, 64 nodules and 140 non-nodules are extracted, and 34 representative features are calculated. The SC(2)SLLE, as well as SLLE and LLE algorithm, are applied to reduce the dimensionality. Several quantitative measurements are also used to evaluate and compare the performances. Using a 5-fold cross-validation methodology, the proposed algorithm achieves 87.65% accuracy, 79.23% sensitivity, 91.43% specificity, and 8.57% false positive rate, on average. Experimental results indicate that the proposed algorithm outperforms the original locally linear embedding and SLLE coupled with the support vector machine (SVM) classifier. Based on the preliminary results from a limited number of nodules in our dataset, this study demonstrates the great potential to improve the performance of a CAD system for nodule detection using the proposed SC(2)SLLE. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Astigmatism compensation in digital holographic microscopy using complex-amplitude correlation

NASA Astrophysics Data System (ADS)

Tamrin, Khairul Fikri; Rahmatullah, Bahbibi; Samuri, Suzani Mohamad

2015-07-01

Digital holographic microscopy (DHM) is a promising tool for a three-dimensional imaging of microscopic particles. It offers the possibility of wavefront processing by manipulating amplitude and phase of the recorded digital holograms. With a view to compensate for aberration in the reconstructed particle images, this paper discusses a new approach of aberration compensation based on complex amplitude correlation and the use of a priori information. The approach is applied to holograms of microscopic particles flowing inside a cylindrical micro-channel recorded using an off-axis digital holographic microscope. The approach results in improvements in the image and signal qualities.

Image motion compensation by area correlation and centroid tracking of solar surface features

NASA Technical Reports Server (NTRS)

Nein, M. E.; Mcintosh, W. R.; Cumings, N. P.

1983-01-01

An experimental solar correlation tracker was tested and evaluated on a ground-based solar magnetograph. Using sunspots as fixed targets, tracking error signals were derived by which the telescope image was stabilized against wind induced perturbations. Two methods of stabilization were investigated; mechanical stabilization of the image by controlled two-axes motion of an active optical element in the telescope beam, and electronic stabilization by biasing of the electron scan in the recording camera. Both approaches have demonstrated telescope stability of about 0.6 arc sec under random perturbations which can cause the unstabilized image to move up to 120 arc sec at frequencies up to 30 Hz.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

NASA Astrophysics Data System (ADS)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy.

PubMed

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-09

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Novel Near-Lossless Compression Algorithm for Medical Sequence Images with Adaptive Block-Based Spatial Prediction.

PubMed

Song, Xiaoying; Huang, Qijun; Chang, Sheng; He, Jin; Wang, Hao

2016-12-01

To address the low compression efficiency of lossless compression and the low image quality of general near-lossless compression, a novel near-lossless compression algorithm based on adaptive spatial prediction is proposed for medical sequence images for possible diagnostic use in this paper. The proposed method employs adaptive block size-based spatial prediction to predict blocks directly in the spatial domain and Lossless Hadamard Transform before quantization to improve the quality of reconstructed images. The block-based prediction breaks the pixel neighborhood constraint and takes full advantage of the local spatial correlations found in medical images. The adaptive block size guarantees a more rational division of images and the improved use of the local structure. The results indicate that the proposed algorithm can efficiently compress medical images and produces a better peak signal-to-noise ratio (PSNR) under the same pre-defined distortion than other near-lossless methods.

Correlation mapping for visualizing propagation of pulsatile CSF motion in intracranial space based on magnetic resonance phase contrast velocity images: preliminary results.

PubMed

Yatsushiro, Satoshi; Hirayama, Akihiro; Matsumae, Mitsunori; Kajiwara, Nao; Abdullah, Afnizanfaizal; Kuroda, Kagayaki

2014-01-01

Correlation time mapping based on magnetic resonance (MR) velocimetry has been applied to pulsatile cerebrospinal fluid (CSF) motion to visualize the pressure transmission between CSF at different locations and/or between CSF and arterial blood flow. Healthy volunteer experiments demonstrated that the technique exhibited transmitting pulsatile CSF motion from CSF space in the vicinity of blood vessels with short delay and relatively high correlation coefficients. Patient and healthy volunteer experiments indicated that the properties of CSF motion were different from the healthy volunteers. Resultant images in healthy volunteers implied that there were slight individual difference in the CSF driving source locations. Clinical interpretation for these preliminary results is required to apply the present technique for classifying status of hydrocephalus.

Relationship between trabecular texture features of CT images and an amount of bone cement volume injection in percutaneous vertebroplasty

NASA Astrophysics Data System (ADS)

Tack, Gye Rae; Choi, Hyung Guen; Shin, Kyu-Chul; Lee, Sung J.

2001-06-01

Percutaneous vertebroplasty is a surgical procedure that was introduced for the treatment of compression fracture of the vertebrae. This procedure includes puncturing vertebrae and filling with polymethylmethacrylate (PMMA). Recent studies have shown that the procedure could provide structural reinforcement for the osteoporotic vertebrae while being minimally invasive and safe with immediate pain relief. However, treatment failures due to disproportionate PMMA volume injection have been reported as one of complications in vertebroplasty. It is believed that control of PMMA volume is one of the most critical factors that can reduce the incidence of complications. In this study, appropriate amount of PMMA volume was assessed based on the imaging data of a given patient under the following hypotheses: (1) a relationship can be drawn between the volume of PMMA injection and textural features of the trabecular bone in preoperative CT images and (2) the volume of PMMA injection can be estimated based on 3D reconstruction of postoperative CT images. Gray-level run length analysis was used to determine the textural features of the trabecular bone. The width of trabecular (T-texture) and the width of intertrabecular spaces (I-texture) were calculated. The correlation between PMMA volume and textural features of patient's CT images was also examined to evaluate the appropriate PMMA amount. Results indicated that there was a strong correlation between the actual PMMA injection volume and the area of the intertrabecular space and that of trabecular bone calculated from the CT image (correlation coefficient, requals0.96 and requals-0.95, respectively). T- texture (requals-0.93) did correlate better with the actual PMMA volume more than the I-texture (requals0.57). Therefore, it was demonstrated that appropriate PMMA injection volume could be predicted based on the textural analysis for better clinical management of the osteoporotic spine.

Automatic co-segmentation of lung tumor based on random forest in PET-CT images

NASA Astrophysics Data System (ADS)

Jiang, Xueqing; Xiang, Dehui; Zhang, Bin; Zhu, Weifang; Shi, Fei; Chen, Xinjian

2016-03-01

In this paper, a fully automatic method is proposed to segment the lung tumor in clinical 3D PET-CT images. The proposed method effectively combines PET and CT information to make full use of the high contrast of PET images and superior spatial resolution of CT images. Our approach consists of three main parts: (1) initial segmentation, in which spines are removed in CT images and initial connected regions achieved by thresholding based segmentation in PET images; (2) coarse segmentation, in which monotonic downhill function is applied to rule out structures which have similar standardized uptake values (SUV) to the lung tumor but do not satisfy a monotonic property in PET images; (3) fine segmentation, random forests method is applied to accurately segment the lung tumor by extracting effective features from PET and CT images simultaneously. We validated our algorithm on a dataset which consists of 24 3D PET-CT images from different patients with non-small cell lung cancer (NSCLC). The average TPVF, FPVF and accuracy rate (ACC) were 83.65%, 0.05% and 99.93%, respectively. The correlation analysis shows our segmented lung tumor volumes has strong correlation ( average 0.985) with the ground truth 1 and ground truth 2 labeled by a clinical expert.

Dual energy CT kidney stone differentiation in photon counting computed tomography

NASA Astrophysics Data System (ADS)

Gutjahr, R.; Polster, C.; Henning, A.; Kappler, S.; Leng, S.; McCollough, C. H.; Sedlmair, M. U.; Schmidt, B.; Krauss, B.; Flohr, T. G.

2017-03-01

This study evaluates the capabilities of a whole-body photon counting CT system to differentiate between four common kidney stone materials, namely uric acid (UA), calcium oxalate monohydrate (COM), cystine (CYS), and apatite (APA) ex vivo. Two different x-ray spectra (120 kV and 140 kV) were applied and two acquisition modes were investigated. The macro-mode generates two energy threshold based image-volumes and two energy bin based image-volumes. In the chesspattern-mode four energy thresholds are applied. A virtual low energy image, as well as a virtual high energy image are derived from initial threshold-based images, while considering their statistically correlated nature. The energy bin based images of the macro-mode, as well as the virtual low and high energy image of the chesspattern-mode serve as input for our dual energy evaluation. The dual energy ratio of the individually segmented kidney stones were utilized to quantify the discriminability of the different materials. The dual energy ratios of the two acquisition modes showed high correlation for both applied spectra. Wilcoxon-rank sum tests and the evaluation of the area under the receiver operating characteristics curves suggest that the UA kidney stones are best differentiable from all other materials (AUC = 1.0), followed by CYS (AUC ≍ 0.9 compared against COM and APA). COM and APA, however, are hardly distinguishable (AUC between 0.63 and 0.76). The results hold true for the measurements of both spectra and both acquisition modes.

Susceptibility-based functional brain mapping by 3D deconvolution of an MR-phase activation map.

PubMed

Chen, Zikuan; Liu, Jingyu; Calhoun, Vince D

2013-05-30

The underlying source of T2*-weighted magnetic resonance imaging (T2*MRI) for brain imaging is magnetic susceptibility (denoted by χ). T2*MRI outputs a complex-valued MR image consisting of magnitude and phase information. Recent research has shown that both the magnitude and the phase images are morphologically different from the source χ, primarily due to 3D convolution, and that the source χ can be reconstructed from complex MR images by computed inverse MRI (CIMRI). Thus, we can obtain a 4D χ dataset from a complex 4D MR dataset acquired from a brain functional MRI study by repeating CIMRI to reconstruct 3D χ volumes at each timepoint. Because the reconstructed χ is a more direct representation of neuronal activity than the MR image, we propose a method for χ-based functional brain mapping, which is numerically characterised by a temporal correlation map of χ responses to a stimulant task. Under the linear imaging conditions used for T2*MRI, we show that the χ activation map can be calculated from the MR phase map by CIMRI. We validate our approach using numerical simulations and Gd-phantom experiments. We also analyse real data from a finger-tapping visuomotor experiment and show that the χ-based functional mapping provides additional activation details (in the form of positive and negative correlation patterns) beyond those generated by conventional MR-magnitude-based mapping. Copyright © 2013 Elsevier B.V. All rights reserved.

Potential accuracy of translation estimation between radar and optical images

NASA Astrophysics Data System (ADS)

Uss, M.; Vozel, B.; Lukin, V.; Chehdi, K.

2015-10-01

This paper investigates the potential accuracy achievable for optical to radar image registration by area-based approach. The analysis is carried out mainly based on the Cramér-Rao Lower Bound (CRLB) on translation estimation accuracy previously proposed by the authors and called CRLBfBm. This bound is now modified to take into account radar image speckle noise properties: spatial correlation and signal-dependency. The newly derived theoretical bound is fed with noise and texture parameters estimated for the co-registered pair of optical Landsat 8 and radar SIR-C images. It is found that difficulty of optical to radar image registration stems more from speckle noise influence than from dissimilarity of the considered kinds of images. At finer scales (and higher speckle noise level), probability of finding control fragments (CF) suitable for registration is low (1% or less) but overall number of such fragments is high thanks to image size. Conversely, at the coarse scale, where speckle noise level is reduced, probability of finding CFs suitable for registration can be as high as 40%, but overall number of such CFs is lower. Thus, the study confirms and supports area-based multiresolution approach for optical to radar registration where coarse scales are used for fast registration "lock" and finer scales for reaching higher registration accuracy. The CRLBfBm is found inaccurate for the main scale due to intensive speckle noise influence. For other scales, the validity of the CRLBfBm bound is confirmed by calculating statistical efficiency of area-based registration method based on normalized correlation coefficient (NCC) measure that takes high values of about 25%.

Quantum Color Image Encryption Algorithm Based on A Hyper-Chaotic System and Quantum Fourier Transform

NASA Astrophysics Data System (ADS)

Tan, Ru-Chao; Lei, Tong; Zhao, Qing-Min; Gong, Li-Hua; Zhou, Zhi-Hong

2016-12-01

To improve the slow processing speed of the classical image encryption algorithms and enhance the security of the private color images, a new quantum color image encryption algorithm based on a hyper-chaotic system is proposed, in which the sequences generated by the Chen's hyper-chaotic system are scrambled and diffused with three components of the original color image. Sequentially, the quantum Fourier transform is exploited to fulfill the encryption. Numerical simulations show that the presented quantum color image encryption algorithm possesses large key space to resist illegal attacks, sensitive dependence on initial keys, uniform distribution of gray values for the encrypted image and weak correlation between two adjacent pixels in the cipher-image.

Nondestructive assessment of collagen hydrogel cross-linking using time-resolved autofluorescence imaging

NASA Astrophysics Data System (ADS)

Sherlock, Benjamin E.; Harvestine, Jenna N.; Mitra, Debika; Haudenschild, Anne; Hu, Jerry; Athanasiou, Kyriacos A.; Leach, J. Kent; Marcu, Laura

2018-03-01

We investigate the use of a fiber-based, multispectral fluorescence lifetime imaging (FLIm) system to nondestructively monitor changes in mechanical properties of collagen hydrogels caused by controlled application of widely used cross-linking agents, glutaraldehyde (GTA) and ribose. Postcross-linking, fluorescence lifetime images are acquired prior to the hydrogels being processed by rheological or tensile testing to directly probe gel mechanical properties. To preserve the sterility of the ribose-treated gels, FLIm is performed inside a biosafety cabinet (BSC). A pairwise correlation analysis is used to quantify the relationship between mean hydrogel fluorescence lifetimes and the storage or Young's moduli of the gels. In the GTA study, we observe strong and specific correlations between fluorescence lifetime and the storage and Young's moduli. Similar correlations are not observed in the ribose study and we postulate a reason for this. Finally, we demonstrate the ability of FLIm to longitudinally monitor dynamic cross-link formation. The strength of the GTA correlations and deployment of our fiber-based FLIm system inside the aseptic environment of a BSC suggests that this technique may be a valuable tool for the tissue engineering community where longitudinal assessment of tissue construct maturation in vitro is highly desirable.

Relationship between analysis of laser speckle image and Knoop hardness on softening enamel.

PubMed

Koshoji, Nelson H; Prates, Renato A; Bussadori, Sandra K; Bortoletto, Carolina C; de Miranda Junior, Walter G; Librantz, André F H; Leal, Cintia Raquel Lima; Oliveira, Marcelo T; Deana, Alessandro M

2016-09-01

In this study is presented the correlation between laser speckle images and enamel hardness loss. In order to shift the enamel hardness, a dental demineralization model was applied to 32 samples of vestibular bovine teeth. After they were cleaned, cut and polished, the samples were divided into 4 groups and immersed in 30ml of a cola-based soft drink for 10, 20, 30 and 40min twice a day for 7 consecutive days with half the surface protected by two layers of nail polish. Each sample was analyzed by Knoop hardness and laser speckle imaging. Pearson's correlation analysis demonstrated that the laser speckle image technique presents a strong correlation with the hardness loss of the enamel (r=0.7085, p<0.0001). This finding is corroborated by Blend & Altman analysis, in which the data presented a constant behavior throughout the whole interval. For both analyses, more than 95% of the data is within the confidence interval, as expected. This work demonstrates, for the first time to our knowledge, an empirical model for correlating laser speckle images with the loss of tooth enamel hardness. Copyright © 2016. Published by Elsevier B.V.

Adaptive radiotherapy for NSCLC patients: utilizing the principle of energy conservation to evaluate dose mapping operations

NASA Astrophysics Data System (ADS)

Zhong, Hualiang; Chetty, Indrin J.

2017-06-01

Tumor regression during the course of fractionated radiotherapy confounds the ability to accurately estimate the total dose delivered to tumor targets. Here we present a new criterion to improve the accuracy of image intensity-based dose mapping operations for adaptive radiotherapy for patients with non-small cell lung cancer (NSCLC). Six NSCLC patients were retrospectively investigated in this study. An image intensity-based B-spline registration algorithm was used for deformable image registration (DIR) of weekly CBCT images to a reference image. The resultant displacement vector fields were employed to map the doses calculated on weekly images to the reference image. The concept of energy conservation was introduced as a criterion to evaluate the accuracy of the dose mapping operations. A finite element method (FEM)-based mechanical model was implemented to improve the performance of the B-Spline-based registration algorithm in regions involving tumor regression. For the six patients, deformed tumor volumes changed by 21.2  ±  15.0% and 4.1  ±  3.7% on average for the B-Spline and the FEM-based registrations performed from fraction 1 to fraction 21, respectively. The energy deposited in the gross tumor volume (GTV) was 0.66 Joules (J) per fraction on average. The energy derived from the fractional dose reconstructed by the B-spline and FEM-based DIR algorithms in the deformed GTV’s was 0.51 J and 0.64 J, respectively. Based on landmark comparisons for the 6 patients, mean error for the FEM-based DIR algorithm was 2.5  ±  1.9 mm. The cross-correlation coefficient between the landmark-measured displacement error and the loss of radiation energy was  -0.16 for the FEM-based algorithm. To avoid uncertainties in measuring distorted landmarks, the B-Spline-based registrations were compared to the FEM registrations, and their displacement differences equal 4.2  ±  4.7 mm on average. The displacement differences were correlated to their relative loss of radiation energy with a cross-correlation coefficient equal to 0.68. Based on the principle of energy conservation, the FEM-based mechanical model has a better performance than the B-Spline-based DIR algorithm. It is recommended that the principle of energy conservation be incorporated into a comprehensive QA protocol for adaptive radiotherapy.

Investigation of TM Band-to-band Registration Using the JSC Registration Processor

NASA Technical Reports Server (NTRS)

Yao, S. S.; Amis, M. L.

1984-01-01

The JSC registration processor performs scene-to-scene (or band-to-band) correlation based on edge images. The edge images are derived from a percentage of the edge pixels calculated from the raw scene data, excluding clouds and other extraneous data in the scene. Correlations are performed on patches (blocks) of the edge images, and the correlation peak location in each patch is estimated iteratively to fractional pixel location accuracy. Peak offset locations from all patches over the scene are then considered together, and a variety of tests are made to weed out outliers and other inconsistencies before a distortion model is assumed. Thus, the correlation peak offset locations in each patch indicate quantitatively how well the two TM bands register to each other over that patch of scene data. The average of these offsets indicate the overall accuracies of the band-to-band registration. The registration processor was also used to register one acquisition to another acquisition of multitemporal TM data acquired over the same ground track. Band 4 images from both acquisitions were correlated and an rms error of a fraction of a pixel was routinely obtained.

Adaptation of reference volumes for correlation-based digital holographic particle tracking

NASA Astrophysics Data System (ADS)

Hesseling, Christina; Peinke, Joachim; Gülker, Gerd

2018-04-01

Numerically reconstructed reference volumes tailored to particle images are used for particle position detection by means of three-dimensional correlation. After a first tracking of these positions, the experimentally recorded particle images are retrieved as a posteriori knowledge about the particle images in the system. This knowledge is used for a further refinement of the detected positions. A transparent description of the individual algorithm steps including the results retrieved with experimental data complete the paper. The work employs extraordinarily small particles, smaller than the pixel pitch of the camera sensor. It is the first approach known to the authors that combines numerical knowledge about particle images and particle images retrieved from the experimental system to an iterative particle tracking approach for digital holographic particle tracking velocimetry.

SU-E-J-120: Comparing 4D CT Computed Ventilation to Lung Function Measured with Hyperpolarized Xenon-129 MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neal, B; Chen, Q

2015-06-15

Purpose: To correlate ventilation parameters computed from 4D CT to ventilation, profusion, and gas exchange measured with hyperpolarized Xenon-129 MRI for a set of lung cancer patients. Methods: Hyperpolarized Xe-129 MRI lung scans were acquired for lung cancer patients, before and after radiation therapy, measuring ventilation, perfusion, and gas exchange. In the standard clinical workflow, these patients also received 4D CT scans before treatment. Ventilation was computed from 4D CT using deformable image registration (DIR). All phases of the 4D CT scan were registered using a B-spline deformable registration. Ventilation at the voxel level was then computed for each phasemore » based on a Jacobian volume expansion metric, yielding phase sorted ventilation images. Ventilation based upon 4D CT and Xe-129 MRI were co-registered, allowing qualitative visual comparison and qualitative comparison via the Pearson correlation coefficient. Results: Analysis shows a weak correlation between hyperpolarized Xe-129 MRI and 4D CT DIR ventilation, with a Pearson correlation coefficient of 0.17 to 0.22. Further work will refine the DIR parameters to optimize the correlation. The weak correlation could be due to the limitations of 4D CT, registration algorithms, or the Xe-129 MRI imaging. Continued development will refine parameters to optimize correlation. Conclusion: Current analysis yields a minimal correlation between 4D CT DIR and Xe-129 MRI ventilation. Funding provided by the 2014 George Amorino Pilot Grant in Radiation Oncology at the University of Virginia.« less

Translational-circular scanning for magneto-acoustic tomography with current injection.

PubMed

Wang, Shigang; Ma, Ren; Zhang, Shunqi; Yin, Tao; Liu, Zhipeng

2016-01-27

Magneto-acoustic tomography with current injection involves using electrical impedance imaging technology. To explore the potential applications in imaging biological tissue and enhance image quality, a new scan mode for the transducer is proposed that is based on translational and circular scanning to record acoustic signals from sources. An imaging algorithm to analyze these signals is developed in respect to this alternative scanning scheme. Numerical simulations and physical experiments were conducted to evaluate the effectiveness of this scheme. An experiment using a graphite sheet as a tissue-mimicking phantom medium was conducted to verify simulation results. A pulsed voltage signal was applied across the sample, and acoustic signals were recorded as the transducer performed stepped translational or circular scans. The imaging algorithm was used to obtain an acoustic-source image based on the signals. In simulations, the acoustic-source image is correlated with the conductivity at the sample boundaries of the sample, but image results change depending on distance and angular aspect of the transducer. In general, as angle and distance decreases, the image quality improves. Moreover, experimental data confirmed the correlation. The acoustic-source images resulting from the alternative scanning mode has yielded the outline of a phantom medium. This scan mode enables improvements to be made in the sensitivity of the detecting unit and a change to a transducer array that would improve the efficiency and accuracy of acoustic-source images.

Quantitative myocardial blood flow imaging with integrated time-of-flight PET-MR.

PubMed

Kero, Tanja; Nordström, Jonny; Harms, Hendrik J; Sörensen, Jens; Ahlström, Håkan; Lubberink, Mark

2017-12-01

The use of integrated PET-MR offers new opportunities for comprehensive assessment of cardiac morphology and function. However, little is known on the quantitative accuracy of cardiac PET imaging with integrated time-of-flight PET-MR. The aim of the present work was to validate the GE Signa PET-MR scanner for quantitative cardiac PET perfusion imaging. Eleven patients (nine male; mean age 59 years; range 46-74 years) with known or suspected coronary artery disease underwent 15 O-water PET scans at rest and during adenosine-induced hyperaemia on a GE Discovery ST PET-CT and a GE Signa PET-MR scanner. PET-MR images were reconstructed using settings recommended by the manufacturer, including time-of-flight (TOF). Data were analysed semi-automatically using Cardiac VUer software, resulting in both parametric myocardial blood flow (MBF) images and segment-based MBF values. Correlation and agreement between PET-CT-based and PET-MR-based MBF values for all three coronary artery territories were assessed using regression analysis and intra-class correlation coefficients (ICC). In addition to the cardiac PET-MR reconstruction protocol as recommended by the manufacturer, comparisons were made using a PET-CT resolution-matched reconstruction protocol both without and with TOF to assess the effect of time-of-flight and reconstruction parameters on quantitative MBF values. Stress MBF data from one patient was excluded due to movement during the PET-CT scanning. Mean MBF values at rest and stress were (0.92 ± 0.12) and (2.74 ± 1.37) mL/g/min for PET-CT and (0.90 ± 0.23) and (2.65 ± 1.15) mL/g/min for PET-MR (p = 0.33 and p = 0.74). ICC between PET-CT-based and PET-MR-based regional MBF was 0.98. Image quality was improved with PET-MR as compared to PET-CT. ICC between PET-MR-based regional MBF with and without TOF and using different filter and reconstruction settings was 1.00. PET-MR-based MBF values correlated well with PET-CT-based MBF values and the parametric PET-MR images were excellent. TOF and reconstruction settings had little impact on MBF values.

Morphology classification of galaxies in CL 0939+4713 using a ground-based telescope image

NASA Technical Reports Server (NTRS)

Fukugita, M.; Doi, M.; Dressler, A.; Gunn, J. E.

1995-01-01

Morphological classification is studied for galaxies in cluster CL 0939+4712 at z = 0.407 using simple photometric parameters obtained from a ground-based telescope image with seeing of 1-2 arcseconds full width at half maximim (FWHM). By ploting the galaxies in a plane of the concentration parameter versus mean surface brightness, we find a good correlation between the location on the plane and galaxy colors, which are known to correlate with morphological types from a recent Hubble Space Telescope (HST) study. Using the present method, we expect a success rate of classification into early and late types of about 70% or possibly more.

Advances in Magnetic Resonance Imaging of the Skull Base

PubMed Central

Kirsch, Claudia F.E.

2014-01-01

Introduction Over the past 20 years, magnetic resonance imaging (MRI) has advanced due to new techniques involving increased magnetic field strength and developments in coils and pulse sequences. These advances allow increased opportunity to delineate the complex skull base anatomy and may guide the diagnosis and treatment of the myriad of pathologies that can affect the skull base. Objectives The objective of this article is to provide a brief background of the development of MRI and illustrate advances in skull base imaging, including techniques that allow improved conspicuity, characterization, and correlative physiologic assessment of skull base pathologies. Data Synthesis Specific radiographic illustrations of increased skull base conspicuity including the lower cranial nerves, vessels, foramina, cerebrospinal fluid (CSF) leaks, and effacement of endolymph are provided. In addition, MRIs demonstrating characterization of skull base lesions, such as recurrent cholesteatoma versus granulation tissue or abscess versus tumor, are also provided as well as correlative clinical findings in CSF flow studies in a patient pre- and post-suboccipital decompression for a Chiari I malformation. Conclusions This article illustrates MRI radiographic advances over the past 20 years, which have improved clinicians' ability to diagnose, define, and hopefully improve the treatment and outcomes of patients with underlying skull base pathologies. PMID:25992137

Comparison of prostate contours between conventional stepping transverse imaging and Twister-based sagittal imaging in permanent interstitial prostate brachytherapy.

PubMed

Kawakami, Shogo; Ishiyama, Hiromichi; Satoh, Takefumi; Tsumura, Hideyasu; Sekiguchi, Akane; Takenaka, Kouji; Tabata, Ken-Ichi; Iwamura, Masatsugu; Hayakawa, Kazushige

2017-08-01

To compare prostate contours on conventional stepping transverse image acquisitions with those on twister-based sagittal image acquisitions. Twenty prostate cancer patients who were planned to have permanent interstitial prostate brachytherapy were prospectively accrued. A transrectal ultrasonography probe was inserted, with the patient in lithotomy position. Transverse images were obtained with stepping movement of the transverse transducer. In the same patient, sagittal images were also obtained through rotation of the sagittal transducer using the "Twister" mode. The differences of prostate size among the two types of image acquisitions were compared. The relationships among the difference of the two types of image acquisitions, dose-volume histogram (DVH) parameters on the post-implant computed tomography (CT) analysis, as well as other factors were analyzed. The sagittal image acquisitions showed a larger prostate size compared to the transverse image acquisitions especially in the anterior-posterior (AP) direction ( p < 0.05). Interestingly, relative size of prostate apex in AP direction in sagittal image acquisitions compared to that in transverse image acquisitions was correlated to DVH parameters such as D 90 ( R = 0.518, p = 0.019), and V 100 ( R = 0.598, p = 0.005). There were small but significant differences in the prostate contours between the transverse and the sagittal planning image acquisitions. Furthermore, our study suggested that the differences between the two types of image acquisitions might correlated to dosimetric results on CT analysis.

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.

PubMed

Huang, Ming-Xiong; Huang, Charles W; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L; Baker, Dewleen G; Song, Tao; Harrington, Deborah L; Theilmann, Rebecca J; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M; Edgar, J Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T; Drake, Angela; Lee, Roland R

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses. © 2013.

MEG Source Imaging Method using Fast L1 Minimum-norm and its Applications to Signals with Brain Noise and Human Resting-state Source Amplitude Images

PubMed Central

Huang, Ming-Xiong; Huang, Charles W.; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L.; Baker, Dewleen G.; Song, Tao; Harrington, Deborah L.; Theilmann, Rebecca J.; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M.; Edgar, J. Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T.; Drake, Angela; Lee, Roland R.

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL’s performance of was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL’s performance was then examined in the analysis of human mediannerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer’s problems of signal leaking and distorted source time-courses. PMID:24055704

Validation of an image-based technique to assess the perceptual quality of clinical chest radiographs with an observer study

NASA Astrophysics Data System (ADS)

Lin, Yuan; Choudhury, Kingshuk R.; McAdams, H. Page; Foos, David H.; Samei, Ehsan

2014-03-01

We previously proposed a novel image-based quality assessment technique1 to assess the perceptual quality of clinical chest radiographs. In this paper, an observer study was designed and conducted to systematically validate this technique. Ten metrics were involved in the observer study, i.e., lung grey level, lung detail, lung noise, riblung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm-lung contrast, and subdiaphragm area. For each metric, three tasks were successively presented to the observers. In each task, six ROI images were randomly presented in a row and observers were asked to rank the images only based on a designated quality and disregard the other qualities. A range slider on the top of the images was used for observers to indicate the acceptable range based on the corresponding perceptual attribute. Five boardcertificated radiologists from Duke participated in this observer study on a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions. The observer data were analyzed in terms of the correlations between the observer ranking orders and the algorithmic ranking orders. Based on the collected acceptable ranges, quality consistency ranges were statistically derived. The observer study showed that, for each metric, the averaged ranking orders of the participated observers were strongly correlated with the algorithmic orders. For the lung grey level, the observer ranking orders completely accorded with the algorithmic ranking orders. The quality consistency ranges derived from this observer study were close to these derived from our previous study. The observer study indicates that the proposed image-based quality assessment technique provides a robust reflection of the perceptual image quality of the clinical chest radiographs. The derived quality consistency ranges can be used to automatically predict the acceptability of a clinical chest radiograph.

A magnetic resonance imaging study on the articulatory and acoustic speech parameters of Malay vowels

PubMed Central

2014-01-01

The phonetic properties of six Malay vowels are investigated using magnetic resonance imaging (MRI) to visualize the vocal tract in order to obtain dynamic articulatory parameters during speech production. To resolve image blurring due to the tongue movement during the scanning process, a method based on active contour extraction is used to track tongue contours. The proposed method efficiently tracks tongue contours despite the partial blurring of MRI images. Consequently, the articulatory parameters that are effectively measured as tongue movement is observed, and the specific shape of the tongue and its position for all six uttered Malay vowels are determined. Speech rehabilitation procedure demands some kind of visual perceivable prototype of speech articulation. To investigate the validity of the measured articulatory parameters based on acoustic theory of speech production, an acoustic analysis based on the uttered vowels by subjects has been performed. As the acoustic speech and articulatory parameters of uttered speech were examined, a correlation between formant frequencies and articulatory parameters was observed. The experiments reported a positive correlation between the constriction location of the tongue body and the first formant frequency, as well as a negative correlation between the constriction location of the tongue tip and the second formant frequency. The results demonstrate that the proposed method is an effective tool for the dynamic study of speech production. PMID:25060583

A magnetic resonance imaging study on the articulatory and acoustic speech parameters of Malay vowels.

PubMed

Zourmand, Alireza; Mirhassani, Seyed Mostafa; Ting, Hua-Nong; Bux, Shaik Ismail; Ng, Kwan Hoong; Bilgen, Mehmet; Jalaludin, Mohd Amin

2014-07-25

The phonetic properties of six Malay vowels are investigated using magnetic resonance imaging (MRI) to visualize the vocal tract in order to obtain dynamic articulatory parameters during speech production. To resolve image blurring due to the tongue movement during the scanning process, a method based on active contour extraction is used to track tongue contours. The proposed method efficiently tracks tongue contours despite the partial blurring of MRI images. Consequently, the articulatory parameters that are effectively measured as tongue movement is observed, and the specific shape of the tongue and its position for all six uttered Malay vowels are determined.Speech rehabilitation procedure demands some kind of visual perceivable prototype of speech articulation. To investigate the validity of the measured articulatory parameters based on acoustic theory of speech production, an acoustic analysis based on the uttered vowels by subjects has been performed. As the acoustic speech and articulatory parameters of uttered speech were examined, a correlation between formant frequencies and articulatory parameters was observed. The experiments reported a positive correlation between the constriction location of the tongue body and the first formant frequency, as well as a negative correlation between the constriction location of the tongue tip and the second formant frequency. The results demonstrate that the proposed method is an effective tool for the dynamic study of speech production.

Estimation of glacier surface motion by robust phase correlation and point like features of SAR intensity images

NASA Astrophysics Data System (ADS)

Fang, Li; Xu, Yusheng; Yao, Wei; Stilla, Uwe

2016-11-01

For monitoring of glacier surface motion in pole and alpine areas, radar remote sensing is becoming a popular technology accounting for its specific advantages of being independent of weather conditions and sunlight. In this paper we propose a method for glacier surface motion monitoring using phase correlation (PC) based on point-like features (PLF). We carry out experiments using repeat-pass TerraSAR X-band (TSX) and Sentinel-1 C-band (S1C) intensity images of the Taku glacier in Juneau icefield located in southeast Alaska. The intensity imagery is first filtered by an improved adaptive refined Lee filter while the effect of topographic reliefs is removed via SRTM-X DEM. Then, a robust phase correlation algorithm based on singular value decomposition (SVD) and an improved random sample consensus (RANSAC) algorithm is applied to sequential PLF pairs generated by correlation using a 2D sinc function template. The approaches for glacier monitoring are validated by both simulated SAR data and real SAR data from two satellites. The results obtained from these three test datasets confirm the superiority of the proposed approach compared to standard correlation-like methods. By the use of the proposed adaptive refined Lee filter, we achieve a good balance between the suppression of noise and the preservation of local image textures. The presented phase correlation algorithm shows the accuracy of better than 0.25 pixels, when conducting matching tests using simulated SAR intensity images with strong noise. Quantitative 3D motions and velocities of the investigated Taku glacier during a repeat-pass period are obtained, which allows a comprehensive and reliable analysis for the investigation of large-scale glacier surface dynamics.

Separating twin images and locating the center of a microparticle in dense suspensions using correlations among reconstructed fields of two parallel holograms.

PubMed

Ling, Hangjian; Katz, Joseph

2014-09-20

This paper deals with two issues affecting the application of digital holographic microscopy (DHM) for measuring the spatial distribution of particles in a dense suspension, namely discriminating between real and virtual images and accurate detection of the particle center. Previous methods to separate real and virtual fields have involved applications of multiple phase-shifted holograms, combining reconstructed fields of multiple axially displaced holograms, and analysis of intensity distributions of weakly scattering objects. Here, we introduce a simple approach based on simultaneously recording two in-line holograms, whose planes are separated by a short distance from each other. This distance is chosen to be longer than the elongated trace of the particle. During reconstruction, the real images overlap, whereas the virtual images are displaced by twice the distance between hologram planes. Data analysis is based on correlating the spatial intensity distributions of the two reconstructed fields to measure displacement between traces. This method has been implemented for both synthetic particles and a dense suspension of 2 μm particles. The correlation analysis readily discriminates between real and virtual images of a sample containing more than 1300 particles. Consequently, we can now implement DHM for three-dimensional tracking of particles when the hologram plane is located inside the sample volume. Spatial correlations within the same reconstructed field are also used to improve the detection of the axial location of the particle center, extending previously introduced procedures to suspensions of microscopic particles. For each cross section within a particle trace, we sum the correlations among intensity distributions in all planes located symmetrically on both sides of the section. This cumulative correlation has a sharp peak at the particle center. Using both synthetic and recorded particle fields, we show that the uncertainty in localizing the axial location of the center is reduced to about one particle's diameter.

Self-calibrated correlation imaging with k-space variant correlation functions.

PubMed

Li, Yu; Edalati, Masoud; Du, Xingfu; Wang, Hui; Cao, Jie J

2018-03-01

Correlation imaging is a previously developed high-speed MRI framework that converts parallel imaging reconstruction into the estimate of correlation functions. The presented work aims to demonstrate this framework can provide a speed gain over parallel imaging by estimating k-space variant correlation functions. Because of Fourier encoding with gradients, outer k-space data contain higher spatial-frequency image components arising primarily from tissue boundaries. As a result of tissue-boundary sparsity in the human anatomy, neighboring k-space data correlation varies from the central to the outer k-space. By estimating k-space variant correlation functions with an iterative self-calibration method, correlation imaging can benefit from neighboring k-space data correlation associated with both coil sensitivity encoding and tissue-boundary sparsity, thereby providing a speed gain over parallel imaging that relies only on coil sensitivity encoding. This new approach is investigated in brain imaging and free-breathing neonatal cardiac imaging. Correlation imaging performs better than existing parallel imaging techniques in simulated brain imaging acceleration experiments. The higher speed enables real-time data acquisition for neonatal cardiac imaging in which physiological motion is fast and non-periodic. With k-space variant correlation functions, correlation imaging gives a higher speed than parallel imaging and offers the potential to image physiological motion in real-time. Magn Reson Med 79:1483-1494, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Image encryption based on a delayed fractional-order chaotic logistic system

NASA Astrophysics Data System (ADS)

Wang, Zhen; Huang, Xia; Li, Ning; Song, Xiao-Na

2012-05-01

A new image encryption scheme is proposed based on a delayed fractional-order chaotic logistic system. In the process of generating a key stream, the time-varying delay and fractional derivative are embedded in the proposed scheme to improve the security. Such a scheme is described in detail with security analyses including correlation analysis, information entropy analysis, run statistic analysis, mean-variance gray value analysis, and key sensitivity analysis. Experimental results show that the newly proposed image encryption scheme possesses high security.

In-vivo study of blood flow in capillaries using μPIV method

NASA Astrophysics Data System (ADS)

Kurochkin, Maxim A.; Fedosov, Ivan V.; Tuchin, Valery V.

2014-01-01

A digital optical system for intravital capillaroscopy has been developed. It implements the particle image velocimetry (PIV) based approach for measurements of red blood cells velocity in individual capillary of human nailfold. We propose to use a digital real time stabilization technique for compensation of impact of involuntary movements of a finger on results of measurements. Image stabilization algorithm is based on correlation of feature tracking. The efficiency of designed image stabilization algorithm was experimentally demonstrated.

A robust automated left ventricle region of interest localization technique using a cardiac cine MRI atlas

NASA Astrophysics Data System (ADS)

Ben-Zikri, Yehuda Kfir; Linte, Cristian A.

2016-03-01

Region of interest detection is a precursor to many medical image processing and analysis applications, including segmentation, registration and other image manipulation techniques. The optimal region of interest is often selected manually, based on empirical knowledge and features of the image dataset. However, if inconsistently identified, the selected region of interest may greatly affect the subsequent image analysis or interpretation steps, in turn leading to incomplete assessment during computer-aided diagnosis or incomplete visualization or identification of the surgical targets, if employed in the context of pre-procedural planning or image-guided interventions. Therefore, the need for robust, accurate and computationally efficient region of interest localization techniques is prevalent in many modern computer-assisted diagnosis and therapy applications. Here we propose a fully automated, robust, a priori learning-based approach that provides reliable estimates of the left and right ventricle features from cine cardiac MR images. The proposed approach leverages the temporal frame-to-frame motion extracted across a range of short axis left ventricle slice images with small training set generated from les than 10% of the population. This approach is based on histogram of oriented gradients features weighted by local intensities to first identify an initial region of interest depicting the left and right ventricles that exhibits the greatest extent of cardiac motion. This region is correlated with the homologous region that belongs to the training dataset that best matches the test image using feature vector correlation techniques. Lastly, the optimal left ventricle region of interest of the test image is identified based on the correlation of known ground truth segmentations associated with the training dataset deemed closest to the test image. The proposed approach was tested on a population of 100 patient datasets and was validated against the ground truth region of interest of the test images manually annotated by experts. This tool successfully identified a mask around the LV and RV and furthermore the minimal region of interest around the LV that fully enclosed the left ventricle from all testing datasets, yielding a 98% overlap with their corresponding ground truth. The achieved mean absolute distance error between the two contours that normalized by the radius of the ground truth is 0.20 +/- 0.09.

The Extended-Image Tracking Technique Based on the Maximum Likelihood Estimation

NASA Technical Reports Server (NTRS)

Tsou, Haiping; Yan, Tsun-Yee

2000-01-01

This paper describes an extended-image tracking technique based on the maximum likelihood estimation. The target image is assume to have a known profile covering more than one element of a focal plane detector array. It is assumed that the relative position between the imager and the target is changing with time and the received target image has each of its pixels disturbed by an independent additive white Gaussian noise. When a rotation-invariant movement between imager and target is considered, the maximum likelihood based image tracking technique described in this paper is a closed-loop structure capable of providing iterative update of the movement estimate by calculating the loop feedback signals from a weighted correlation between the currently received target image and the previously estimated reference image in the transform domain. The movement estimate is then used to direct the imager to closely follow the moving target. This image tracking technique has many potential applications, including free-space optical communications and astronomy where accurate and stabilized optical pointing is essential.

Vision based tunnel inspection using non-rigid registration

NASA Astrophysics Data System (ADS)

Badshah, Amir; Ullah, Shan; Shahzad, Danish

2015-04-01

Growing numbers of long tunnels across the globe has increased the need for safety measurements and inspections of tunnels in these days. To avoid serious damages, tunnel inspection is highly recommended at regular intervals of time to find any deformations or cracks at the right time. While following the stringent safety and tunnel accessibility standards, conventional geodetic surveying using techniques of civil engineering and other manual and mechanical methods are time consuming and results in troublesome of routine life. An automatic tunnel inspection by image processing techniques using non rigid registration has been proposed. There are many other image processing methods used for image registration purposes. Most of the processes are operation of images in its spatial domain like finding edges and corners by Harris edge detection method. These methods are quite time consuming and fail for some or other reasons like for blurred or images with noise. Due to use of image features directly by these methods in the process, are known by the group, correlation by image features. The other method is featureless correlation, in which the images are converted into its frequency domain and then correlated with each other. The shift in spatial domain is the same as in frequency domain, but the processing is order faster than in spatial domain. In the proposed method modified normalized phase correlation has been used to find any shift between two images. As pre pre-processing the tunnel images i.e. reference and template are divided into small patches. All these relative patches are registered by the proposed modified normalized phase correlation. By the application of the proposed algorithm we get the pixel movement of the images. And then these pixels shifts are converted to measuring units like mm, cm etc. After the complete process if there is any shift in the tunnel at described points are located.

A Highly Accurate Face Recognition System Using Filtering Correlation

NASA Astrophysics Data System (ADS)

Watanabe, Eriko; Ishikawa, Sayuri; Kodate, Kashiko

2007-09-01

The authors previously constructed a highly accurate fast face recognition optical correlator (FARCO) [E. Watanabe and K. Kodate: Opt. Rev. 12 (2005) 460], and subsequently developed an improved, super high-speed FARCO (S-FARCO), which is able to process several hundred thousand frames per second. The principal advantage of our new system is its wide applicability to any correlation scheme. Three different configurations were proposed, each depending on correlation speed. This paper describes and evaluates a software correlation filter. The face recognition function proved highly accurate, seeing that a low-resolution facial image size (64 × 64 pixels) has been successfully implemented. An operation speed of less than 10 ms was achieved using a personal computer with a central processing unit (CPU) of 3 GHz and 2 GB memory. When we applied the software correlation filter to a high-security cellular phone face recognition system, experiments on 30 female students over a period of three months yielded low error rates: 0% false acceptance rate and 2% false rejection rate. Therefore, the filtering correlation works effectively when applied to low resolution images such as web-based images or faces captured by a monitoring camera.

Penalized Weighted Least-Squares Approach to Sinogram Noise Reduction and Image Reconstruction for Low-Dose X-Ray Computed Tomography

PubMed Central

Wang, Jing; Li, Tianfang; Lu, Hongbing; Liang, Zhengrong

2006-01-01

Reconstructing low-dose X-ray CT (computed tomography) images is a noise problem. This work investigated a penalized weighted least-squares (PWLS) approach to address this problem in two dimensions, where the WLS considers first- and second-order noise moments and the penalty models signal spatial correlations. Three different implementations were studied for the PWLS minimization. One utilizes a MRF (Markov random field) Gibbs functional to consider spatial correlations among nearby detector bins and projection views in sinogram space and minimizes the PWLS cost function by iterative Gauss-Seidel algorithm. Another employs Karhunen-Loève (KL) transform to de-correlate data signals among nearby views and minimizes the PWLS adaptively to each KL component by analytical calculation, where the spatial correlation among nearby bins is modeled by the same Gibbs functional. The third one models the spatial correlations among image pixels in image domain also by a MRF Gibbs functional and minimizes the PWLS by iterative successive over-relaxation algorithm. In these three implementations, a quadratic functional regularization was chosen for the MRF model. Phantom experiments showed a comparable performance of these three PWLS-based methods in terms of suppressing noise-induced streak artifacts and preserving resolution in the reconstructed images. Computer simulations concurred with the phantom experiments in terms of noise-resolution tradeoff and detectability in low contrast environment. The KL-PWLS implementation may have the advantage in terms of computation for high-resolution dynamic low-dose CT imaging. PMID:17024831

WE-AB-BRA-06: 4DCT-Ventilation: A Novel Imaging Modality for Thoracic Surgical Evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vinogradskiy, Y; Jackson, M; Schubert, L

Purpose: The current standard-of-care imaging used to evaluate lung cancer patients for surgical resection is nuclear-medicine ventilation. Surgeons use nuclear-medicine images along with pulmonary function tests (PFT) to calculate percent predicted postoperative (%PPO) PFT values by estimating the amount of functioning lung that would be lost with surgery. 4DCT-ventilation is an emerging imaging modality developed in radiation oncology that uses 4DCT data to calculate lung ventilation maps. We perform the first retrospective study to assess the use of 4DCT-ventilation for pre-operative surgical evaluation. The purpose of this work was to compare %PPO-PFT values calculated with 4DCT-ventilation and nuclear-medicine imaging. Methods:more » 16 lung cancer patients retrospectively reviewed had undergone 4DCTs, nuclear-medicine imaging, and had Forced Expiratory Volume in 1 second (FEV1) acquired as part of a standard PFT. For each patient, 4DCT data sets, spatial registration, and a density-change based model were used to compute 4DCT-ventilation maps. Both 4DCT and nuclear-medicine images were used to calculate %PPO-FEV1 using %PPO-FEV1=pre-operative FEV1*(1-fraction of total ventilation of resected lung). Fraction of ventilation resected was calculated assuming lobectomy and pneumonectomy. The %PPO-FEV1 values were compared between the 4DCT-ventilation-based calculations and the nuclear-medicine-based calculations using correlation coefficients and average differences. Results: The correlation between %PPO-FEV1 values calculated with 4DCT-ventilation and nuclear-medicine were 0.81 (p<0.01) and 0.99 (p<0.01) for pneumonectomy and lobectomy respectively. The average difference between the 4DCT-ventilation based and the nuclear-medicine-based %PPO-FEV1 values were small, 4.1±8.5% and 2.9±3.0% for pneumonectomy and lobectomy respectively. Conclusion: The high correlation results provide a strong rationale for a clinical trial translating 4DCT-ventilation to the surgical domain. Compared to nuclear-medicine, 4DCT-ventilation is cheaper, does not require a radioactive contrast agent, provides a faster imaging procedure, and has improved spatial resolution. 4DCT-ventilation can reduce the cost and imaging time for patients while providing improved spatial accuracy and quantitative results for surgeons. YV discloses grant from State of Colorado.« less

Evaluation of mathematical algorithms for automatic patient alignment in radiosurgery.

PubMed

Williams, Kenneth M; Schulte, Reinhard W; Schubert, Keith E; Wroe, Andrew J

2015-06-01

Image registration techniques based on anatomical features can serve to automate patient alignment for intracranial radiosurgery procedures in an effort to improve the accuracy and efficiency of the alignment process as well as potentially eliminate the need for implanted fiducial markers. To explore this option, four two-dimensional (2D) image registration algorithms were analyzed: the phase correlation technique, mutual information (MI) maximization, enhanced correlation coefficient (ECC) maximization, and the iterative closest point (ICP) algorithm. Digitally reconstructed radiographs from the treatment planning computed tomography scan of a human skull were used as the reference images, while orthogonal digital x-ray images taken in the treatment room were used as the captured images to be aligned. The accuracy of aligning the skull with each algorithm was compared to the alignment of the currently practiced procedure, which is based on a manual process of selecting common landmarks, including implanted fiducials and anatomical skull features. Of the four algorithms, three (phase correlation, MI maximization, and ECC maximization) demonstrated clinically adequate (ie, comparable to the standard alignment technique) translational accuracy and improvements in speed compared to the interactive, user-guided technique; however, the ICP algorithm failed to give clinically acceptable results. The results of this work suggest that a combination of different algorithms may provide the best registration results. This research serves as the initial groundwork for the translation of automated, anatomy-based 2D algorithms into a real-world system for 2D-to-2D image registration and alignment for intracranial radiosurgery. This may obviate the need for invasive implantation of fiducial markers into the skull and may improve treatment room efficiency and accuracy. © The Author(s) 2014.

Mapping Diffusion in a Living Cell via the Phasor Approach

PubMed Central

Ranjit, Suman; Lanzano, Luca; Gratton, Enrico

2014-01-01

Diffusion of a fluorescent protein within a cell has been measured using either fluctuation-based techniques (fluorescence correlation spectroscopy (FCS) or raster-scan image correlation spectroscopy) or particle tracking. However, none of these methods enables us to measure the diffusion of the fluorescent particle at each pixel of the image. Measurement using conventional single-point FCS at every individual pixel results in continuous long exposure of the cell to the laser and eventual bleaching of the sample. To overcome this limitation, we have developed what we believe to be a new method of scanning with simultaneous construction of a fluorescent image of the cell. In this believed new method of modified raster scanning, as it acquires the image, the laser scans each individual line multiple times before moving to the next line. This continues until the entire area is scanned. This is different from the original raster-scan image correlation spectroscopy approach, where data are acquired by scanning each frame once and then scanning the image multiple times. The total time of data acquisition needed for this method is much shorter than the time required for traditional FCS analysis at each pixel. However, at a single pixel, the acquired intensity time sequence is short; requiring nonconventional analysis of the correlation function to extract information about the diffusion. These correlation data have been analyzed using the phasor approach, a fit-free method that was originally developed for analysis of FLIM images. Analysis using this method results in an estimation of the average diffusion coefficient of the fluorescent species at each pixel of an image, and thus, a detailed diffusion map of the cell can be created. PMID:25517145

Medical image security using modified chaos-based cryptography approach

NASA Astrophysics Data System (ADS)

Talib Gatta, Methaq; Al-latief, Shahad Thamear Abd

2018-05-01

The progressive development in telecommunication and networking technologies have led to the increased popularity of telemedicine usage which involve storage and transfer of medical images and related information so security concern is emerged. This paper presents a method to provide the security to the medical images since its play a major role in people healthcare organizations. The main idea in this work based on the chaotic sequence in order to provide efficient encryption method that allows reconstructing the original image from the encrypted image with high quality and minimum distortion in its content and doesn’t effect in human treatment and diagnosing. Experimental results prove the efficiency of the proposed method using some of statistical measures and robust correlation between original image and decrypted image.

The prediction of cyclic proximal humerus fracture fixation failure by various bone density measures.

PubMed

Varga, Peter; Grünwald, Leonard; Windolf, Markus

2018-02-22

Fixation of osteoporotic proximal humerus fractures has remained challenging, but may be improved by careful pre-operative planning. The aim of this study was to investigate how well the failure of locking plate fixation of osteoporotic proximal humerus fractures can be predicted by bone density measures assessed with currently available clinical imaging (realistic case) and a higher resolution and quality modality (theoretical best-case). Various density measures were correlated to experimentally assessed number of cycles to construct failure of plated unstable low-density proximal humerus fractures (N = 18). The influence of density evaluation technique was investigated by comparing local (peri-implant) versus global evaluation regions; HR-pQCT-based versus clinical QCT-based image data; ipsilateral versus contralateral side; and bone mineral content (BMC) versus bone mineral density (BMD). All investigated density measures were significantly correlated with the experimental cycles to failure. The best performing clinically feasible parameter was the QCT-based BMC of the contralateral articular cap region, providing significantly better correlation (R 2  = 0.53) compared to a previously proposed clinical density measure (R 2  = 0.30). BMC had consistently, but not significantly stronger correlations with failure than BMD. The overall best results were obtained with the ipsilateral HR-pQCT-based local BMC (R 2  = 0.74) that may be used for implant optimization. Strong correlations were found between the corresponding density measures of the two CT image sources, as well as between the two sides. Future studies should investigate if BMC of the contralateral articular cap region could provide improved prediction of clinical fixation failure compared to previously proposed measures. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res. © 2018 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Intrinsic Resting-State Functional Connectivity in the Human Spinal Cord at 3.0 T.

PubMed

San Emeterio Nateras, Oscar; Yu, Fang; Muir, Eric R; Bazan, Carlos; Franklin, Crystal G; Li, Wei; Li, Jinqi; Lancaster, Jack L; Duong, Timothy Q

2016-04-01

To apply resting-state functional magnetic resonance (MR) imaging to map functional connectivity of the human spinal cord. Studies were performed in nine self-declared healthy volunteers with informed consent and institutional review board approval. Resting-state functional MR imaging was performed to map functional connectivity of the human cervical spinal cord from C1 to C4 at 1 × 1 × 3-mm resolution with a 3.0-T clinical MR imaging unit. Independent component analysis (ICA) was performed to derive resting-state functional MR imaging z-score maps rendered on two-dimensional and three-dimensional images. Seed-based analysis was performed for cross validation with ICA networks by using Pearson correlation. Reproducibility analysis of resting-state functional MR imaging maps from four repeated trials in a single participant yielded a mean z score of 6 ± 1 (P < .0001). The centroid coordinates across the four trials deviated by 2 in-plane voxels ± 2 mm (standard deviation) and up to one adjacent image section ± 3 mm. ICA of group resting-state functional MR imaging data revealed prominent functional connectivity patterns within the spinal cord gray matter. There were statistically significant (z score > 3, P < .001) bilateral, unilateral, and intersegmental correlations in the ventral horns, dorsal horns, and central spinal cord gray matter. Three-dimensional surface rendering provided visualization of these components along the length of the spinal cord. Seed-based analysis showed that many ICA components exhibited strong and significant (P < .05) correlations, corroborating the ICA results. Resting-state functional MR imaging connectivity networks are qualitatively consistent with known neuroanatomic and functional structures in the spinal cord. Resting-state functional MR imaging of the human cervical spinal cord with a 3.0-T clinical MR imaging unit and standard MR imaging protocols and hardware reveals prominent functional connectivity patterns within the spinal cord gray matter, consistent with known functional and anatomic layouts of the spinal cord.

High-Performance Computational Analysis of Glioblastoma Pathology Images with Database Support Identifies Molecular and Survival Correlates.

PubMed

Kong, Jun; Wang, Fusheng; Teodoro, George; Cooper, Lee; Moreno, Carlos S; Kurc, Tahsin; Pan, Tony; Saltz, Joel; Brat, Daniel

2013-12-01

In this paper, we present a novel framework for microscopic image analysis of nuclei, data management, and high performance computation to support translational research involving nuclear morphometry features, molecular data, and clinical outcomes. Our image analysis pipeline consists of nuclei segmentation and feature computation facilitated by high performance computing with coordinated execution in multi-core CPUs and Graphical Processor Units (GPUs). All data derived from image analysis are managed in a spatial relational database supporting highly efficient scientific queries. We applied our image analysis workflow to 159 glioblastomas (GBM) from The Cancer Genome Atlas dataset. With integrative studies, we found statistics of four specific nuclear features were significantly associated with patient survival. Additionally, we correlated nuclear features with molecular data and found interesting results that support pathologic domain knowledge. We found that Proneural subtype GBMs had the smallest mean of nuclear Eccentricity and the largest mean of nuclear Extent, and MinorAxisLength. We also found gene expressions of stem cell marker MYC and cell proliferation maker MKI67 were correlated with nuclear features. To complement and inform pathologists of relevant diagnostic features, we queried the most representative nuclear instances from each patient population based on genetic and transcriptional classes. Our results demonstrate that specific nuclear features carry prognostic significance and associations with transcriptional and genetic classes, highlighting the potential of high throughput pathology image analysis as a complementary approach to human-based review and translational research.

Modified dixon‐based renal dynamic contrast‐enhanced MRI facilitates automated registration and perfusion analysis

PubMed Central

Leiner, Tim; Vink, Eva E.; Blankestijn, Peter J.; van den Berg, Cornelis A.T.

2017-01-01

Purpose Renal dynamic contrast‐enhanced (DCE) MRI provides information on renal perfusion and filtration. However, clinical implementation is hampered by challenges in postprocessing as a result of misalignment of the kidneys due to respiration. We propose to perform automated image registration using the fat‐only images derived from a modified Dixon reconstruction of a dual‐echo acquisition because these provide consistent contrast over the dynamic series. Methods DCE data of 10 hypertensive patients was used. Dual‐echo images were acquired at 1.5 T with temporal resolution of 3.9 s during contrast agent injection. Dixon fat, water, and in‐phase and opposed‐phase (OP) images were reconstructed. Postprocessing was automated. Registration was performed both to fat images and OP images for comparison. Perfusion and filtration values were extracted from a two‐compartment model fit. Results Automatic registration to fat images performed better than automatic registration to OP images with visible contrast enhancement. Median vertical misalignment of the kidneys was 14 mm prior to registration, compared to 3 mm and 5 mm with registration to fat images and OP images, respectively (P = 0.03). Mean perfusion values and MR‐based glomerular filtration rates (GFR) were 233 ± 64 mL/100 mL/min and 60 ± 36 mL/minute, respectively, based on fat‐registered images. MR‐based GFR correlated with creatinine‐based GFR (P = 0.04) for fat‐registered images. For unregistered and OP‐registered images, this correlation was not significant. Conclusion Absence of contrast changes on Dixon fat images improves registration in renal DCE MRI and enables automated postprocessing, resulting in a more accurate estimation of GFR. Magn Reson Med 80:66–76, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. PMID:29134673

Automated characterization of perceptual quality of clinical chest radiographs: Validation and calibration to observer preference

DOE Office of Scientific and Technical Information (OSTI.GOV)

Samei, Ehsan, E-mail: samei@duke.edu; Lin, Yuan; Choudhury, Kingshuk R.

Purpose: The authors previously proposed an image-based technique [Y. Lin et al. Med. Phys. 39, 7019–7031 (2012)] to assess the perceptual quality of clinical chest radiographs. In this study, an observer study was designed and conducted to validate the output of the program against rankings by expert radiologists and to establish the ranges of the output values that reflect the acceptable image appearance so the program output can be used for image quality optimization and tracking. Methods: Using an IRB-approved protocol, 2500 clinical chest radiographs (PA/AP) were collected from our clinical operation. The images were processed through our perceptual qualitymore » assessment program to measure their appearance in terms of ten metrics of perceptual image quality: lung gray level, lung detail, lung noise, rib–lung contrast, rib sharpness, mediastinum detail, mediastinum noise, mediastinum alignment, subdiaphragm–lung contrast, and subdiaphragm area. From the results, for each targeted appearance attribute/metric, 18 images were selected such that the images presented a relatively constant appearance with respect to all metrics except the targeted one. The images were then incorporated into a graphical user interface, which displayed them into three panels of six in a random order. Using a DICOM calibrated diagnostic display workstation and under low ambient lighting conditions, each of five participating attending chest radiologists was tasked to spatially order the images based only on the targeted appearance attribute regardless of the other qualities. Once ordered, the observer also indicated the range of image appearances that he/she considered clinically acceptable. The observer data were analyzed in terms of the correlations between the observer and algorithmic rankings and interobserver variability. An observer-averaged acceptable image appearance was also statistically derived for each quality attribute based on the collected individual acceptable ranges. Results: The observer study indicated that, for each image quality attribute, the averaged observer ranking strongly correlated with the algorithmic ranking (linear correlation coefficient R > 0.92), with highest correlation (R = 1) for lung gray level and the lowest (R = 0.92) for mediastinum noise. There was a strong concordance between the observers in terms of their rankings (i.e., Kendall’s tau agreement > 0.84). The observers also generally indicated similar tolerance and preference levels in terms of acceptable ranges, as 85% of the values were close to the overall tolerance or preference levels and the differences were smaller than 0.15. Conclusions: The observer study indicates that the previously proposed technique provides a robust reflection of the perceptual image quality in clinical images. The results established the range of algorithmic outputs for each metric that can be used to quantitatively assess and qualify the appearance quality of clinical chest radiographs.« less

Fabric pilling measurement using three-dimensional image

NASA Astrophysics Data System (ADS)

Ouyang, Wenbin; Wang, Rongwu; Xu, Bugao

2013-10-01

We introduce a stereovision system and the three-dimensional (3-D) image analysis algorithms for fabric pilling measurement. Based on the depth information available in the 3-D image, the pilling detection process starts from the seed searching at local depth maxima to the region growing around the selected seeds using both depth and distance criteria. After the pilling detection, the density, height, and area of individual pills in the image can be extracted to describe the pilling appearance. According to the multivariate regression analysis on the 3-D images of 30 cotton fabrics treated by the random-tumble and home-laundering machines, the pilling grade is highly correlated with the pilling density (R=0.923) but does not consistently change with the pilling height and area. The pilling densities measured from the 3-D images also correlate well with those counted manually from the samples (R=0.985).

Experimental validation of 2D uncertainty quantification for digital image correlation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reu, Phillip L.

Because digital image correlation (DIC) has become such an important and standard tool in the toolbox of experimental mechanicists, a complete uncertainty quantification of the method is needed. It should be remembered that each DIC setup and series of images will have a unique uncertainty based on the calibration quality and the image and speckle quality of the analyzed images. Any pretest work done with a calibrated DIC stereo-rig to quantify the errors using known shapes and translations, while useful, do not necessarily reveal the uncertainty of a later test. This is particularly true with high-speed applications where actual testmore » images are often less than ideal. Work has previously been completed on the mathematical underpinnings of DIC uncertainty quantification and is already published, this paper will present corresponding experimental work used to check the validity of the uncertainty equations.« less

Real time SAR processing

NASA Technical Reports Server (NTRS)

Premkumar, A. B.; Purviance, J. E.

1990-01-01

A simplified model for the SAR imaging problem is presented. The model is based on the geometry of the SAR system. Using this model an expression for the entire phase history of the received SAR signal is formulated. From the phase history, it is shown that the range and the azimuth coordinates for a point target image can be obtained by processing the phase information during the intrapulse and interpulse periods respectively. An architecture for a VLSI implementation for the SAR signal processor is presented which generates images in real time. The architecture uses a small number of chips, a new correlation processor, and an efficient azimuth correlation process.

Adaptive Microwave Staring Correlated Imaging for Targets Appearing in Discrete Clusters.

PubMed

Tian, Chao; Jiang, Zheng; Chen, Weidong; Wang, Dongjin

2017-10-21

Microwave staring correlated imaging (MSCI) can achieve ultra-high resolution in real aperture staring radar imaging using the correlated imaging process (CIP) under all-weather and all-day circumstances. The CIP must combine the received echo signal with the temporal-spatial stochastic radiation field. However, a precondition of the CIP is that the continuous imaging region must be discretized to a fine grid, and the measurement matrix should be accurately computed, which makes the imaging process highly complex when the MSCI system observes a wide area. This paper proposes an adaptive imaging approach for the targets in discrete clusters to reduce the complexity of the CIP. The approach is divided into two main stages. First, as discrete clustered targets are distributed in different range strips in the imaging region, the transmitters of the MSCI emit narrow-pulse waveforms to separate the echoes of the targets in different strips in the time domain; using spectral entropy, a modified method robust against noise is put forward to detect the echoes of the discrete clustered targets, based on which the strips with targets can be adaptively located. Second, in a strip with targets, the matched filter reconstruction algorithm is used to locate the regions with targets, and only the regions of interest are discretized to a fine grid; sparse recovery is used, and the band exclusion is used to maintain the non-correlation of the dictionary. Simulation results are presented to demonstrate that the proposed approach can accurately and adaptively locate the regions with targets and obtain high-quality reconstructed images.

Image analysis of pubic bone for age estimation in a computed tomography sample.

PubMed

López-Alcaraz, Manuel; González, Pedro Manuel Garamendi; Aguilera, Inmaculada Alemán; López, Miguel Botella

2015-03-01

Radiology has demonstrated great utility for age estimation, but most of the studies are based on metrical and morphological methods in order to perform an identification profile. A simple image analysis-based method is presented, aimed to correlate the bony tissue ultrastructure with several variables obtained from the grey-level histogram (GLH) of computed tomography (CT) sagittal sections of the pubic symphysis surface and the pubic body, and relating them with age. The CT sample consisted of 169 hospital Digital Imaging and Communications in Medicine (DICOM) archives of known sex and age. The calculated multiple regression models showed a maximum R (2) of 0.533 for females and 0.726 for males, with a high intra- and inter-observer agreement. The method suggested is considered not only useful for performing an identification profile during virtopsy, but also for application in further studies in order to attach a quantitative correlation for tissue ultrastructure characteristics, without complex and expensive methods beyond image analysis.

Application of image recognition-based automatic hyphae detection in fungal keratitis.

PubMed

Wu, Xuelian; Tao, Yuan; Qiu, Qingchen; Wu, Xinyi

2018-03-01

The purpose of this study is to evaluate the accuracy of two methods in diagnosis of fungal keratitis, whereby one method is automatic hyphae detection based on images recognition and the other method is corneal smear. We evaluate the sensitivity and specificity of the method in diagnosis of fungal keratitis, which is automatic hyphae detection based on image recognition. We analyze the consistency of clinical symptoms and the density of hyphae, and perform quantification using the method of automatic hyphae detection based on image recognition. In our study, 56 cases with fungal keratitis (just single eye) and 23 cases with bacterial keratitis were included. All cases underwent the routine inspection of slit lamp biomicroscopy, corneal smear examination, microorganism culture and the assessment of in vivo confocal microscopy images before starting medical treatment. Then, we recognize the hyphae images of in vivo confocal microscopy by using automatic hyphae detection based on image recognition to evaluate its sensitivity and specificity and compare with the method of corneal smear. The next step is to use the index of density to assess the severity of infection, and then find the correlation with the patients' clinical symptoms and evaluate consistency between them. The accuracy of this technology was superior to corneal smear examination (p < 0.05). The sensitivity of the technology of automatic hyphae detection of image recognition was 89.29%, and the specificity was 95.65%. The area under the ROC curve was 0.946. The correlation coefficient between the grading of the severity in the fungal keratitis by the automatic hyphae detection based on image recognition and the clinical grading is 0.87. The technology of automatic hyphae detection based on image recognition was with high sensitivity and specificity, able to identify fungal keratitis, which is better than the method of corneal smear examination. This technology has the advantages when compared with the conventional artificial identification of confocal microscope corneal images, of being accurate, stable and does not rely on human expertise. It was the most useful to the medical experts who are not familiar with fungal keratitis. The technology of automatic hyphae detection based on image recognition can quantify the hyphae density and grade this property. Being noninvasive, it can provide an evaluation criterion to fungal keratitis in a timely, accurate, objective and quantitative manner.

Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study

PubMed Central

Sappa, Angel D.; Carvajal, Juan A.; Aguilera, Cristhian A.; Oliveira, Miguel; Romero, Dennis; Vintimilla, Boris X.

2016-01-01

This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR). PMID:27294938

Wavelet-Based Visible and Infrared Image Fusion: A Comparative Study.

PubMed

Sappa, Angel D; Carvajal, Juan A; Aguilera, Cristhian A; Oliveira, Miguel; Romero, Dennis; Vintimilla, Boris X

2016-06-10

This paper evaluates different wavelet-based cross-spectral image fusion strategies adopted to merge visible and infrared images. The objective is to find the best setup independently of the evaluation metric used to measure the performance. Quantitative performance results are obtained with state of the art approaches together with adaptations proposed in the current work. The options evaluated in the current work result from the combination of different setups in the wavelet image decomposition stage together with different fusion strategies for the final merging stage that generates the resulting representation. Most of the approaches evaluate results according to the application for which they are intended for. Sometimes a human observer is selected to judge the quality of the obtained results. In the current work, quantitative values are considered in order to find correlations between setups and performance of obtained results; these correlations can be used to define a criteria for selecting the best fusion strategy for a given pair of cross-spectral images. The whole procedure is evaluated with a large set of correctly registered visible and infrared image pairs, including both Near InfraRed (NIR) and Long Wave InfraRed (LWIR).

Physically motivated correlation formalism in hyperspectral imaging

NASA Astrophysics Data System (ADS)

Roy, Ankita; Rafert, J. Bruce

2004-05-01

Most remote sensing data-sets contain a limiting number of independent spatial and spectral measurements, beyond which no effective increase in information is achieved. This paper presents a Physically Motivated Correlation Formalism (PMCF) ,which places both Spatial and Spectral data on an equivalent mathematical footing in the context of a specific Kernel, such that, optimal combinations of independent data can be selected from the entire Hypercube via the method of "Correlation Moments". We present an experimental and computational analysis of Hyperspectral data sets using the Michigan Tech VFTHSI [Visible Fourier Transform Hyperspectral Imager] based on a Sagnac Interferometer, adjusted to obtain high SNR levels. The captured Signal Interferograms of different targets - aerial snaps of Houghton and lab-based data (white light , He-Ne laser , discharge tube sources) with the provision of customized scan of targets with the same exposures are processed using inverse imaging transformations and filtering techniques to obtain the Spectral profiles and generate Hypercubes to compute Spectral/Spatial/Cross Moments. PMCF answers the question of how optimally the entire hypercube should be sampled and finds how many spatial-spectral pixels are required for a particular target recognition.

GPUs benchmarking in subpixel image registration algorithm

NASA Astrophysics Data System (ADS)

Sanz-Sabater, Martin; Picazo-Bueno, Jose Angel; Micó, Vicente; Ferrerira, Carlos; Granero, Luis; Garcia, Javier

2015-05-01

Image registration techniques are used among different scientific fields, like medical imaging or optical metrology. The straightest way to calculate shifting between two images is using the cross correlation, taking the highest value of this correlation image. Shifting resolution is given in whole pixels which cannot be enough for certain applications. Better results can be achieved interpolating both images, as much as the desired resolution we want to get, and applying the same technique described before, but the memory needed by the system is significantly higher. To avoid memory consuming we are implementing a subpixel shifting method based on FFT. With the original images, subpixel shifting can be achieved multiplying its discrete Fourier transform by a linear phase with different slopes. This method is high time consuming method because checking a concrete shifting means new calculations. The algorithm, highly parallelizable, is very suitable for high performance computing systems. GPU (Graphics Processing Unit) accelerated computing became very popular more than ten years ago because they have hundreds of computational cores in a reasonable cheap card. In our case, we are going to register the shifting between two images, doing the first approach by FFT based correlation, and later doing the subpixel approach using the technique described before. We consider it as `brute force' method. So we will present a benchmark of the algorithm consisting on a first approach (pixel resolution) and then do subpixel resolution approaching, decreasing the shifting step in every loop achieving a high resolution in few steps. This program will be executed in three different computers. At the end, we will present the results of the computation, with different kind of CPUs and GPUs, checking the accuracy of the method, and the time consumed in each computer, discussing the advantages, disadvantages of the use of GPUs.

Use of Landsat Thematic Mapper images in regional correlation of syntectonic strata, Colorado river extensional corridor, California and Arizona

NASA Technical Reports Server (NTRS)

Beratan, K. K.; Blom, R. G.; Crippen, R. E.; Nielson, J. E.

1990-01-01

Enhanced Landsat TM images were used in conjunction with field work to investigate the regional correlation of Miocene rocks in the Colorado River extensional corridor of California and Arizona. Based on field investigations, four sequences of sedimentary and volcanic strata could be recognized in the Mohave Mountains (Arizona) and the eastern Whipple Mountains (California), which display significantly different relative volumes and organization of lithologies. The four sequences were also found to have distinctive appearances on the TM image. The recognition criteria derived from field mapping and image interpretation in the Mohave Mountains and Whipple Mountains were applied to an adjacent area in which stratigraphic affinities were less well known. The results of subsequent field work confirmed the stratigraphic and structural relations suggested by the Tm image analysis.

Neuroanatomical Correlates of Intelligence

ERIC Educational Resources Information Center

Luders, Eileen; Narr, Katherine L.; Thompson, Paul M.; Toga, Arthur W.

2009-01-01

With the advancement of image acquisition and analysis methods in recent decades, unique opportunities have emerged to study the neuroanatomical correlates of intelligence. Traditional approaches examining global measures have been complemented by insights from more regional analyses based on pre-defined areas. Newer state-of-the-art approaches…

Feedback mechanism for smart nozzles and nebulizers

DOEpatents

Montaser, Akbar [Potomac, MD; Jorabchi, Kaveh [Arlington, VA; Kahen, Kaveh [Kleinburg, CA

2009-01-27

Nozzles and nebulizers able to produce aerosol with optimum and reproducible quality based on feedback information obtained using laser imaging techniques. Two laser-based imaging techniques based on particle image velocimetry (PTV) and optical patternation map and contrast size and velocity distributions for indirect and direct pneumatic nebulizations in plasma spectrometry. Two pulses from thin laser sheet with known time difference illuminate droplets flow field. Charge coupled device (CCL)) captures scattering of laser light from droplets, providing two instantaneous particle images. Pointwise cross-correlation of corresponding images yields two-dimensional velocity map of aerosol velocity field. For droplet size distribution studies, solution is doped with fluorescent dye and both laser induced florescence (LIF) and Mie scattering images are captured simultaneously by two CCDs with the same field of view. Ratio of LIF/Mie images provides relative droplet size information, then scaled by point calibration method via phase Doppler particle analyzer.

Hierarchical multivariate covariance analysis of metabolic connectivity.

PubMed

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Wavelet-space correlation imaging for high-speed MRI without motion monitoring or data segmentation.

PubMed

Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

2015-12-01

This study aims to (i) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and (ii) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called "wavelet-space correlation imaging", is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI, and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. © 2014 Wiley Periodicals, Inc.

Advanced image based methods for structural integrity monitoring: Review and prospects

NASA Astrophysics Data System (ADS)

Farahani, Behzad V.; Sousa, Pedro José; Barros, Francisco; Tavares, Paulo J.; Moreira, Pedro M. G. P.

2018-02-01

There is a growing trend in engineering to develop methods for structural integrity monitoring and characterization of in-service mechanical behaviour of components. The fast growth in recent years of image processing techniques and image-based sensing for experimental mechanics, brought about a paradigm change in phenomena sensing. Hence, several widely applicable optical approaches are playing a significant role in support of experiment. The current review manuscript describes advanced image based methods for structural integrity monitoring, and focuses on methods such as Digital Image Correlation (DIC), Thermoelastic Stress Analysis (TSA), Electronic Speckle Pattern Interferometry (ESPI) and Speckle Pattern Shearing Interferometry (Shearography). These non-contact full-field techniques rely on intensive image processing methods to measure mechanical behaviour, and evolve even as reviews such as this are being written, which justifies a special effort to keep abreast of this progress.

Measuring hepatic functional reserve using T1 mapping of Gd-EOB-DTPA enhanced 3T MR imaging: A preliminary study comparing with 99mTc GSA scintigraphy and signal intensity based parameters.

PubMed

Nakagawa, Masataka; Namimoto, Tomohiro; Shimizu, Kie; Morita, Kosuke; Sakamoto, Fumi; Oda, Seitaro; Nakaura, Takeshi; Utsunomiya, Daisuke; Shiraishi, Shinya; Yamashita, Yasuyuki

2017-07-01

To determine the utility of liver T1-mapping on gadolinium-ethoxybenzyl-diethylenetriamine-pentaacetic acid (Gd-EOB-DTPA) enhanced magnetic resonance (MR) imaging for the measurement of liver functional reserve compared with the signal intensity (SI) based parameters, technetium-99m-galactosyl serum albumin ( 99m Tc-GSA) scintigraphy and indocyanine green (ICG) clearance. This retrospective study included 111 patients (Child-Pugh-A 90; -B 21) performed with both Gd-EOB-DTPA enhanced liver MR imaging and 99m Tc-GSA (76 patients with ICG). Receiver operating characteristic (ROC) curve analysis was performed to compare diagnostic performances of T1-relaxation-time parameters [pre-(T1pre) and post-contrast (T1hb) Gd-EOB-DTPA], SI based parameters [relative enhancement (RE), liver-to-muscle-ratio (LMR), liver-to-spleen-ratio (LSR)] and 99m Tc-GSA scintigraphy blood clearance index (HH15)] for Child-Pugh classification. Pearson's correlation was used for comparisons among T1-relaxation-time parameters, SI-based parameters, HH15 and ICG. A significant difference was obtained for Child-Pugh classification with T1hb, ΔT1, all SI based parameters and HH15. T1hb had the highest AUC followed by RE, LMR, LSR, ΔT1, HH15 and T1pre. The correlation coefficients with HH15 were T1pre 0.22, T1hb 0.53, ΔT1 -0.38 of T1 relaxation parameters; RE -0.44, LMR -0.45, LSR -0.43 of SI-based parameters. T1hb was highest for correlation with HH15. The correlation coefficients with ICG were T1pre 0.29, T1hb 0.64, ΔT1 -0.42 of T1 relaxation parameters; RE -0.50, LMR -0.61, LSR -0.58 of SI-based parameters; 0.64 of HH15. Both T1hb and HH15 were highest for correlation with ICG. T1 relaxation time at post-contrast of Gd-EOB-DTPA (T1hb) was strongly correlated with ICG clearance and moderately correlated HH15 with 99m Tc-GSA. T1hb has the potential to provide robust parameter of liver functional reserve. Copyright © 2017 Elsevier B.V. All rights reserved.

A study of respiration-correlated cone-beam CT scans to correct target positioning errors in radiotherapy of thoracic cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santoro, J. P.; McNamara, J.; Yorke, E.

2012-10-15

Purpose: There is increasingly widespread usage of cone-beam CT (CBCT) for guiding radiation treatment in advanced-stage lung tumors, but difficulties associated with daily CBCT in conventionally fractionated treatments include imaging dose to the patient, increased workload and longer treatment times. Respiration-correlated cone-beam CT (RC-CBCT) can improve localization accuracy in mobile lung tumors, but further increases the time and workload for conventionally fractionated treatments. This study investigates whether RC-CBCT-guided correction of systematic tumor deviations in standard fractionated lung tumor radiation treatments is more effective than 2D image-based correction of skeletal deviations alone. A second study goal compares respiration-correlated vs respiration-averaged imagesmore » for determining tumor deviations. Methods: Eleven stage II-IV nonsmall cell lung cancer patients are enrolled in an IRB-approved prospective off-line protocol using RC-CBCT guidance to correct for systematic errors in GTV position. Patients receive a respiration-correlated planning CT (RCCT) at simulation, daily kilovoltage RC-CBCT scans during the first week of treatment and weekly scans thereafter. Four types of correction methods are compared: (1) systematic error in gross tumor volume (GTV) position, (2) systematic error in skeletal anatomy, (3) daily skeletal corrections, and (4) weekly skeletal corrections. The comparison is in terms of weighted average of the residual GTV deviations measured from the RC-CBCT scans and representing the estimated residual deviation over the treatment course. In the second study goal, GTV deviations computed from matching RCCT and RC-CBCT are compared to deviations computed from matching respiration-averaged images consisting of a CBCT reconstructed using all projections and an average-intensity-projection CT computed from the RCCT. Results: Of the eleven patients in the GTV-based systematic correction protocol, two required no correction, seven required a single correction, one required two corrections, and one required three corrections. Mean residual GTV deviation (3D distance) following GTV-based systematic correction (mean {+-} 1 standard deviation 4.8 {+-} 1.5 mm) is significantly lower than for systematic skeletal-based (6.5 {+-} 2.9 mm, p= 0.015), and weekly skeletal-based correction (7.2 {+-} 3.0 mm, p= 0.001), but is not significantly lower than daily skeletal-based correction (5.4 {+-} 2.6 mm, p= 0.34). In two cases, first-day CBCT images reveal tumor changes-one showing tumor growth, the other showing large tumor displacement-that are not readily observed in radiographs. Differences in computed GTV deviations between respiration-correlated and respiration-averaged images are 0.2 {+-} 1.8 mm in the superior-inferior direction and are of similar magnitude in the other directions. Conclusions: An off-line protocol to correct GTV-based systematic error in locally advanced lung tumor cases can be effective at reducing tumor deviations, although the findings need confirmation with larger patient statistics. In some cases, a single cone-beam CT can be useful for assessing tumor changes early in treatment, if more than a few days elapse between simulation and the start of treatment. Tumor deviations measured with respiration-averaged CT and CBCT images are consistent with those measured with respiration-correlated images; the respiration-averaged method is more easily implemented in the clinic.« less

Model-based position correlation between breast images

NASA Astrophysics Data System (ADS)

Georgii, J.; Zöhrer, F.; Hahn, H. K.

2013-02-01

Nowadays, breast diagnosis is based on images of different projections and modalities, such that sensitivity and specificity of the diagnosis can be improved. However, this emburdens radiologists to find corresponding locations in these data sets, which is a time consuming task, especially since the resolution of the images increases and thus more and more data have to be considered in the diagnosis. Therefore, we aim at support radiologist by automatically synchronizing cursor positions between different views of the breast. Specifically, we present an automatic approach to compute the spatial correlation between MLO and CC mammogram or tomosynthesis projections of the breast. It is based on pre-computed finite element simulations of generic breast models, which are adapted to the patient-specific breast using a contour mapping approach. Our approach is designed to be fully automatic and efficient, such that it can be implemented directly into existing multimodal breast workstations. Additionally, it is extendable to support other breast modalities in future, too.

Imaging-based biomarkers of cognitive performance in older adults constructed via high-dimensional pattern regression applied to MRI and PET.

PubMed

Wang, Ying; Goh, Joshua O; Resnick, Susan M; Davatzikos, Christos

2013-01-01

In this study, we used high-dimensional pattern regression methods based on structural (gray and white matter; GM and WM) and functional (positron emission tomography of regional cerebral blood flow; PET) brain data to identify cross-sectional imaging biomarkers of cognitive performance in cognitively normal older adults from the Baltimore Longitudinal Study of Aging (BLSA). We focused on specific components of executive and memory domains known to decline with aging, including manipulation, semantic retrieval, long-term memory (LTM), and short-term memory (STM). For each imaging modality, brain regions associated with each cognitive domain were generated by adaptive regional clustering. A relevance vector machine was adopted to model the nonlinear continuous relationship between brain regions and cognitive performance, with cross-validation to select the most informative brain regions (using recursive feature elimination) as imaging biomarkers and optimize model parameters. Predicted cognitive scores using our regression algorithm based on the resulting brain regions correlated well with actual performance. Also, regression models obtained using combined GM, WM, and PET imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with LTM showing stronger correlation with the temporal lobe than STM. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. The PET modality had higher contribution to most cognitive domains except manipulation, which had higher WM contribution from the superior longitudinal fasciculus and the genu of the corpus callosum. These findings based on machine-learning methods demonstrate the importance of combining structural and functional imaging data in understanding complex cognitive mechanisms and also their potential usage as biomarkers that predict cognitive status.

Deformation-induced speckle-pattern evolution and feasibility of correlational speckle tracking in optical coherence elastography.

PubMed

Zaitsev, Vladimir Y; Matveyev, Alexandr L; Matveev, Lev A; Gelikonov, Grigory V; Gelikonov, Valentin M; Vitkin, Alex

2015-07-01

Feasibility of speckle tracking in optical coherence tomography (OCT) based on digital image correlation (DIC) is discussed in the context of elastography problems. Specifics of applying DIC methods to OCT, compared to processing of photographic images in mechanical engineering applications, are emphasized and main complications are pointed out. Analytical arguments are augmented by accurate numerical simulations of OCT speckle patterns. In contrast to DIC processing for displacement and strain estimation in photographic images, the accuracy of correlational speckle tracking in deformed OCT images is strongly affected by the coherent nature of speckles, for which strain-induced complications of speckle “blinking” and “boiling” are typical. The tracking accuracy is further compromised by the usually more pronounced pixelated structure of OCT scans compared with digital photographic images in classical DIC applications. Processing of complex-valued OCT data (comprising both amplitude and phase) compared to intensity-only scans mitigates these deleterious effects to some degree. Criteria of the attainable speckle tracking accuracy and its dependence on the key OCT system parameters are established.

Optical-Correlator Neural Network Based On Neocognitron

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

"Radio-oncomics" : The potential of radiomics in radiation oncology.

PubMed

Peeken, Jan Caspar; Nüsslin, Fridtjof; Combs, Stephanie E

2017-10-01

Radiomics, a recently introduced concept, describes quantitative computerized algorithm-based feature extraction from imaging data including computer tomography (CT), magnetic resonance imaging (MRT), or positron-emission tomography (PET) images. For radiation oncology it offers the potential to significantly influence clinical decision-making and thus therapy planning and follow-up workflow. After image acquisition, image preprocessing, and defining regions of interest by structure segmentation, algorithms are applied to calculate shape, intensity, texture, and multiscale filter features. By combining multiple features and correlating them with clinical outcome, prognostic models can be created. Retrospective studies have proposed radiomics classifiers predicting, e. g., overall survival, radiation treatment response, distant metastases, or radiation-related toxicity. Besides, radiomics features can be correlated with genomic information ("radiogenomics") and could be used for tumor characterization. Distinct patterns based on data-based as well as genomics-based features will influence radiation oncology in the future. Individualized treatments in terms of dose level adaption and target volume definition, as well as other outcome-related parameters will depend on radiomics and radiogenomics. By integration of various datasets, the prognostic power can be increased making radiomics a valuable part of future precision medicine approaches. This perspective demonstrates the evidence for the radiomics concept in radiation oncology. The necessity of further studies to integrate radiomics classifiers into clinical decision-making and the radiation therapy workflow is emphasized.

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

NASA Astrophysics Data System (ADS)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

Blind image quality assessment via probabilistic latent semantic analysis.

PubMed

Yang, Xichen; Sun, Quansen; Wang, Tianshu

2016-01-01

We propose a blind image quality assessment that is highly unsupervised and training free. The new method is based on the hypothesis that the effect caused by distortion can be expressed by certain latent characteristics. Combined with probabilistic latent semantic analysis, the latent characteristics can be discovered by applying a topic model over a visual word dictionary. Four distortion-affected features are extracted to form the visual words in the dictionary: (1) the block-based local histogram; (2) the block-based local mean value; (3) the mean value of contrast within a block; (4) the variance of contrast within a block. Based on the dictionary, the latent topics in the images can be discovered. The discrepancy between the frequency of the topics in an unfamiliar image and a large number of pristine images is applied to measure the image quality. Experimental results for four open databases show that the newly proposed method correlates well with human subjective judgments of diversely distorted images.

Implementation of digital image encryption algorithm using logistic function and DNA encoding

NASA Astrophysics Data System (ADS)

Suryadi, MT; Satria, Yudi; Fauzi, Muhammad

2018-03-01

Cryptography is a method to secure information that might be in form of digital image. Based on past research, in order to increase security level of chaos based encryption algorithm and DNA based encryption algorithm, encryption algorithm using logistic function and DNA encoding was proposed. Digital image encryption algorithm using logistic function and DNA encoding use DNA encoding to scramble the pixel values into DNA base and scramble it in DNA addition, DNA complement, and XOR operation. The logistic function in this algorithm used as random number generator needed in DNA complement and XOR operation. The result of the test show that the PSNR values of cipher images are 7.98-7.99 bits, the entropy values are close to 8, the histogram of cipher images are uniformly distributed and the correlation coefficient of cipher images are near 0. Thus, the cipher image can be decrypted perfectly and the encryption algorithm has good resistance to entropy attack and statistical attack.

3D printed pathological sectioning boxes to facilitate radiological-pathological correlation in hepatectomy cases.

PubMed

Trout, Andrew T; Batie, Matthew R; Gupta, Anita; Sheridan, Rachel M; Tiao, Gregory M; Towbin, Alexander J

2017-11-01

Radiogenomics promises to identify tumour imaging features indicative of genomic or proteomic aberrations that can be therapeutically targeted allowing precision personalised therapy. An accurate radiological-pathological correlation is critical to the process of radiogenomic characterisation of tumours. An accurate correlation, however, is difficult to achieve with current pathological sectioning techniques which result in sectioning in non-standard planes. The purpose of this work is to present a technique to standardise hepatic sectioning to facilitateradiological-pathological correlation. We describe a process in which three-dimensional (3D)-printed specimen boxes based on preoperative cross-sectional imaging (CT and MRI) can be used to facilitate pathological sectioning in standard planes immediately on hepatic resection enabling improved tumour mapping. We have applied this process in 13 patients undergoing hepatectomy and have observed close correlation between imaging and gross pathology in patients with both unifocal and multifocal tumours. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

In Vivo Dark-Field Radiography for Early Diagnosis and Staging of Pulmonary Emphysema.

PubMed

Hellbach, Katharina; Yaroshenko, Andre; Meinel, Felix G; Yildirim, Ali Ö; Conlon, Thomas M; Bech, Martin; Mueller, Mark; Velroyen, Astrid; Notohamiprodjo, Mike; Bamberg, Fabian; Auweter, Sigrid; Reiser, Maximilian; Eickelberg, Oliver; Pfeiffer, Franz

2015-07-01

The aim of this study was to evaluate the suitability of in vivo x-ray dark-field radiography for early-stage diagnosis of pulmonary emphysema in mice. Furthermore, we aimed to analyze how the dark-field signal correlates with morphological changes of lung architecture at distinct stages of emphysema. Female 8- to 10-week-old C57Bl/6N mice were used throughout all experiments. Pulmonary emphysema was induced by orotracheal injection of porcine pancreatic elastase (80-U/kg body weight) (n = 30). Control mice (n = 11) received orotracheal injection of phosphate-buffered saline. To monitor the temporal patterns of emphysema development over time, the mice were imaged 7, 14, or 21 days after the application of elastase or phosphate-buffered saline. X-ray transmission and dark-field images were acquired with a prototype grating-based small-animal scanner. In vivo pulmonary function tests were performed before killing the animals. In addition, lungs were obtained for detailed histopathological analysis, including mean cord length (MCL) quantification as a parameter for the assessment of emphysema. Three blinded readers, all of them experienced radiologists and familiar with dark-field imaging, were asked to grade the severity of emphysema for both dark-field and transmission images. Histopathology and MCL quantification confirmed the introduction of different stages of emphysema, which could be clearly visualized and differentiated on the dark-field radiograms, whereas early stages were not detected on transmission images. The correlation between MCL and dark-field signal intensities (r = 0.85) was significantly higher than the correlation between MCL and transmission signal intensities (r = 0.37). The readers' visual ratings for dark-field images correlated significantly better with MCL (r = 0.85) than visual ratings for transmission images (r = 0.36). Interreader agreement and the diagnostic accuracy of both quantitative and visual assessment were significantly higher for dark-field imaging than those for conventional transmission images. X-ray dark-field radiography can reliably visualize different stages of emphysema in vivo and demonstrates significantly higher diagnostic accuracy for early stages of emphysema than conventional attenuation-based radiography.

Facebook photo activity associated with body image disturbance in adolescent girls.

PubMed

Meier, Evelyn P; Gray, James

2014-04-01

The present study examined the relationship between body image and adolescent girls' activity on the social networking site (SNS) Facebook (FB). Research has shown that elevated Internet "appearance exposure" is positively correlated with increased body image disturbance among adolescent girls, and there is a particularly strong association with FB use. The present study sought to replicate and extend upon these findings by identifying the specific FB features that correlate with body image disturbance in adolescent girls. A total of 103 middle and high school females completed questionnaire measures of total FB use, specific FB feature use, weight dissatisfaction, drive for thinness, thin ideal internalization, appearance comparison, and self-objectification. An appearance exposure score was calculated based on subjects' use of FB photo applications relative to total FB use. Elevated appearance exposure, but not overall FB usage, was significantly correlated with weight dissatisfaction, drive for thinness, thin ideal internalization, and self-objectification. Implications for eating disorder prevention programs and best practices in researching SNSs are discussed.

Atmospheric scanning electron microscope for correlative microscopy.

PubMed

Morrison, Ian E G; Dennison, Clare L; Nishiyama, Hidetoshi; Suga, Mitsuo; Sato, Chikara; Yarwood, Andrew; O'Toole, Peter J

2012-01-01

The JEOL ClairScope is the first truly correlative scanning electron and optical microscope. An inverted scanning electron microscope (SEM) column allows electron images of wet samples to be obtained in ambient conditions in a biological culture dish, via a silicon nitride film window in the base. A standard inverted optical microscope positioned above the dish holder can be used to take reflected light and epifluorescence images of the same sample, under atmospheric conditions that permit biochemical modifications. For SEM, the open dish allows successive staining operations to be performed without moving the holder. The standard optical color camera used for fluorescence imaging can be exchanged for a high-sensitivity monochrome camera to detect low-intensity fluorescence signals, and also cathodoluminescence emission from nanophosphor particles. If these particles are applied to the sample at a suitable density, they can greatly assist the task of perfecting the correlation between the optical and electron images. Copyright © 2012 Elsevier Inc. All rights reserved.

Chemical Shift MR Imaging Methods for the Quantification of Transcatheter Lipiodol Delivery to the Liver: Preclinical Feasibility Studies in a Rodent Model

PubMed Central

Yin, Xiaoming; Guo, Yang; Li, Weiguo; Huo, Eugene; Zhang, Zhuoli; Nicolai, Jodi; Kleps, Robert A.; Hernando, Diego; Katsaggelos, Aggelos K.; Omary, Reed A.

2012-01-01

Purpose: To demonstrate the feasibility of using chemical shift magnetic resonance (MR) imaging fat-water separation methods for quantitative estimation of transcatheter lipiodol delivery to liver tissues. Materials and Methods: Studies were performed in accordance with institutional Animal Care and Use Committee guidelines. Proton nuclear MR spectroscopy was first performed to identify lipiodol spectral peaks and relative amplitudes. Next, phantoms were constructed with increasing lipiodol-water volume fractions. A multiecho chemical shift–based fat-water separation method was used to quantify lipiodol concentration within each phantom. Six rats served as controls; 18 rats underwent catheterization with digital subtraction angiography guidance for intraportal infusion of a 15%, 30%, or 50% by volume lipiodol-saline mixture. MR imaging measurements were used to quantify lipiodol delivery to each rat liver. Lipiodol concentration maps were reconstructed by using both single-peak and multipeak chemical shift models. Intraclass and Spearman correlation coefficients were calculated for statistical comparison of MR imaging–based lipiodol concentration and volume measurements to reference standards (known lipiodol phantom compositions and the infused lipiodol dose during rat studies). Results: Both single-peak and multipeak measurements were well correlated to phantom lipiodol concentrations (r2 > 0.99). Lipiodol volume measurements were progressively and significantly higher when comparing between animals receiving different doses (P < .05 for each comparison). MR imaging–based lipiodol volume measurements strongly correlated with infused dose (intraclass correlation coefficients > 0.93, P < .001) with both single- and multipeak approaches. Conclusion: Chemical shift MR imaging fat-water separation methods can be used for quantitative measurements of lipiodol delivery to liver tissues. © RSNA, 2012 PMID:22623693

Quantitative analysis of collagen change between normal and cancerous thyroid tissues based on SHG method

NASA Astrophysics Data System (ADS)

Chen, Xiwen; Huang, Zufang; Xi, Gangqin; Chen, Yongjian; Lin, Duo; Wang, Jing; Li, Zuanfang; Sun, Liqing; Chen, Jianxin; Chen, Rong

2012-03-01

Second-harmonic generation (SHG) is proved to be a high spatial resolution, large penetration depth and non-photobleaching method. In our study, SHG method was used to investigate the normal and cancerous thyroid tissue. For SHG imaging performance, system parameters were adjusted for high-contrast images acquisition. Each x-y image was recorded in pseudo-color, which matches the wavelength range in the visible spectrum. The acquisition time for a 512×512-pixels image was 1.57 sec; each acquired image was averaged four frames to improve the signal-to-noise ratio. Our results indicated that collagen presence as determined by counting the ratio of the SHG pixels over the whole pixels for normal and cancerous thyroid tissues were 0.48+/-0.05, 0.33+/-0.06 respectively. In addition, to quantitatively assess collagen-related changes, we employed GLCM texture analysis to the SHG images. Corresponding results showed that the correlation both fell off with distance in normal and cancerous group. Calculated value of Corr50 (the distance where the correlation crossed 50% of the initial correlation) indicated significant difference. This study demonstrates that SHG method can be used as a complementary tool in thyroid histopathology.

Wavelet-space Correlation Imaging for High-speed MRI without Motion Monitoring or Data Segmentation

PubMed Central

Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

2014-01-01

Purpose This study aims to 1) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and 2) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Methods Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called “wavelet-space correlation imaging”, is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Results Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Conclusion Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. PMID:25470230

Registration of 3D ultrasound computer tomography and MRI for evaluation of tissue correspondences

NASA Astrophysics Data System (ADS)

Hopp, T.; Dapp, R.; Zapf, M.; Kretzek, E.; Gemmeke, H.; Ruiter, N. V.

2015-03-01

3D Ultrasound Computer Tomography (USCT) is a new imaging method for breast cancer diagnosis. In the current state of development it is essential to correlate USCT with a known imaging modality like MRI to evaluate how different tissue types are depicted. Due to different imaging conditions, e.g. with the breast subject to buoyancy in USCT, a direct correlation is demanding. We present a 3D image registration method to reduce positioning differences and allow direct side-by-side comparison of USCT and MRI volumes. It is based on a two-step approach including a buoyancy simulation with a biomechanical model and free form deformations using cubic B-Splines for a surface refinement. Simulation parameters are optimized patient-specifically in a simulated annealing scheme. The method was evaluated with in-vivo datasets resulting in an average registration error below 5mm. Correlating tissue structures can thereby be located in the same or nearby slices in both modalities and three-dimensional non-linear deformations due to the buoyancy are reduced. Image fusion of MRI volumes and USCT sound speed volumes was performed for intuitive display. By applying the registration to data of our first in-vivo study with the KIT 3D USCT, we could correlate several tissue structures in MRI and USCT images and learn how connective tissue, carcinomas and breast implants observed in the MRI are depicted in the USCT imaging modes.

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

Image velocimetry for clouds with relaxation labeling based on deformation consistency

NASA Astrophysics Data System (ADS)

Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto

2017-08-01

Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.

Quantitative characterization of brain β-amyloid using a joint PiB/FDG PET image histogram

NASA Astrophysics Data System (ADS)

Camp, Jon J.; Hanson, Dennis P.; Holmes, David R.; Kemp, Bradley J.; Senjem, Matthew L.; Murray, Melissa E.; Dickson, Dennis W.; Parisi, Joseph; Petersen, Ronald C.; Lowe, Val J.; Robb, Richard A.

2014-03-01

A complex analysis performed by spatial registration of PiB and MRI patient images in order to localize the PiB signal to specific cortical brain regions has been proven effective in identifying imaging characteristics associated with underlying Alzheimer's Disease (AD) and Lewy Body Disease (LBD) pathology. This paper presents an original method of image analysis and stratification of amyloid-related brain disease based on the global spatial correlation of PiB PET images with 18F-FDG PET images (without MR images) to categorize the PiB signal arising from the cortex. Rigid registration of PiB and 18F-FDG images is relatively straightforward, and in registration the 18F-FDG signal serves to identify the cortical region in which the PiB signal is relevant. Cortical grey matter demonstrates the highest levels of amyloid accumulation and therefore the greatest PiB signal related to amyloid pathology. The highest intensity voxels in the 18F-FDG image are attributed to the cortical grey matter. The correlation of the highest intensity PiB voxels with the highest 18F-FDG values indicates the presence of β-amyloid protein in the cortex in disease states, while correlation of the highest intensity PiB voxels with mid-range 18F-FDG values indicates only nonspecific binding in the white matter.

Intensity ratio to improve black hole assessment in multiple sclerosis.

PubMed

Adusumilli, Gautam; Trinkaus, Kathryn; Sun, Peng; Lancia, Samantha; Viox, Jeffrey D; Wen, Jie; Naismith, Robert T; Cross, Anne H

2018-01-01

Improved imaging methods are critical to assess neurodegeneration and remyelination in multiple sclerosis. Chronic hypointensities observed on T1-weighted brain MRI, "persistent black holes," reflect severe focal tissue damage. Present measures consist of determining persistent black holes numbers and volumes, but do not quantitate severity of individual lesions. Develop a method to differentiate black and gray holes and estimate the severity of individual multiple sclerosis lesions using standard magnetic resonance imaging. 38 multiple sclerosis patients contributed images. Intensities of lesions on T1-weighted scans were assessed relative to cerebrospinal fluid intensity using commercial software. Magnetization transfer imaging, diffusion tensor imaging and clinical testing were performed to assess associations with T1w intensity-based measures. Intensity-based assessments of T1w hypointensities were reproducible and achieved > 90% concordance with expert rater determinations of "black" and "gray" holes. Intensity ratio values correlated with magnetization transfer ratios (R = 0.473) and diffusion tensor imaging metrics (R values ranging from 0.283 to -0.531) that have been associated with demyelination and axon loss. Intensity ratio values incorporated into T1w hypointensity volumes correlated with clinical measures of cognition. This method of determining the degree of hypointensity within multiple sclerosis lesions can add information to conventional imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

An image adaptive, wavelet-based watermarking of digital images

NASA Astrophysics Data System (ADS)

Agreste, Santa; Andaloro, Guido; Prestipino, Daniela; Puccio, Luigia

2007-12-01

In digital management, multimedia content and data can easily be used in an illegal way--being copied, modified and distributed again. Copyright protection, intellectual and material rights protection for authors, owners, buyers, distributors and the authenticity of content are crucial factors in solving an urgent and real problem. In such scenario digital watermark techniques are emerging as a valid solution. In this paper, we describe an algorithm--called WM2.0--for an invisible watermark: private, strong, wavelet-based and developed for digital images protection and authenticity. Using discrete wavelet transform (DWT) is motivated by good time-frequency features and well-matching with human visual system directives. These two combined elements are important in building an invisible and robust watermark. WM2.0 works on a dual scheme: watermark embedding and watermark detection. The watermark is embedded into high frequency DWT components of a specific sub-image and it is calculated in correlation with the image features and statistic properties. Watermark detection applies a re-synchronization between the original and watermarked image. The correlation between the watermarked DWT coefficients and the watermark signal is calculated according to the Neyman-Pearson statistic criterion. Experimentation on a large set of different images has shown to be resistant against geometric, filtering and StirMark attacks with a low rate of false alarm.

Predicting Electron Population Characteristics in 2-D Using Multispectral Ground-Based Imaging

NASA Astrophysics Data System (ADS)

Grubbs, Guy; Michell, Robert; Samara, Marilia; Hampton, Donald; Jahn, Jorg-Micha

2018-01-01

Ground-based imaging and in situ sounding rocket data are compared to electron transport modeling for an active inverted-V type auroral event. The Ground-to-Rocket Electrodynamics-Electrons Correlative Experiment (GREECE) mission successfully launched from Poker Flat, Alaska, on 3 March 2014 at 11:09:50 UT and reached an apogee of approximately 335 km over the aurora. Multiple ground-based electron-multiplying charge-coupled device (EMCCD) imagers were positioned at Venetie, Alaska, and aimed toward magnetic zenith. The imagers observed the intensity of different auroral emission lines (427.8, 557.7, and 844.6 nm) at the magnetic foot point of the rocket payload. Emission line intensity data are correlated with electron characteristics measured by the GREECE onboard electron spectrometer. A modified version of the GLobal airglOW (GLOW) model is used to estimate precipitating electron characteristics based on optical emissions. GLOW predicted the electron population characteristics with 20% error given the observed spectral intensities within 10° of magnetic zenith. Predictions are within 30% of the actual values within 20° of magnetic zenith for inverted-V-type aurora. Therefore, it is argued that this technique can be used, at least in certain types of aurora, such as the inverted-V type presented here, to derive 2-D maps of electron characteristics. These can then be used to further derive 2-D maps of ionospheric parameters as a function of time, based solely on multispectral optical imaging data.

Impact of tumor size and tracer uptake heterogeneity in (18)F-FDG PET and CT non-small cell lung cancer tumor delineation.

PubMed

Hatt, Mathieu; Cheze-le Rest, Catherine; van Baardwijk, Angela; Lambin, Philippe; Pradier, Olivier; Visvikis, Dimitris

2011-11-01

The objectives of this study were to investigate the relationship between CT- and (18)F-FDG PET-based tumor volumes in non-small cell lung cancer (NSCLC) and the impact of tumor size and uptake heterogeneity on various approaches to delineating uptake on PET images. Twenty-five NSCLC cancer patients with (18)F-FDG PET/CT were considered. Seventeen underwent surgical resection of their tumor, and the maximum diameter was measured. Two observers manually delineated the tumors on the CT images and the tumor uptake on the corresponding PET images, using a fixed threshold at 50% of the maximum (T(50)), an adaptive threshold methodology, and the fuzzy locally adaptive Bayesian (FLAB) algorithm. Maximum diameters of the delineated volumes were compared with the histopathology reference when available. The volumes of the tumors were compared, and correlations between the anatomic volume and PET uptake heterogeneity and the differences between delineations were investigated. All maximum diameters measured on PET and CT images significantly correlated with the histopathology reference (r > 0.89, P < 0.0001). Significant differences were observed among the approaches: CT delineation resulted in large overestimation (+32% ± 37%), whereas all delineations on PET images resulted in underestimation (from -15% ± 17% for T(50) to -4% ± 8% for FLAB) except manual delineation (+8% ± 17%). Overall, CT volumes were significantly larger than PET volumes (55 ± 74 cm(3) for CT vs. from 18 ± 25 to 47 ± 76 cm(3) for PET). A significant correlation was found between anatomic tumor size and heterogeneity (larger lesions were more heterogeneous). Finally, the more heterogeneous the tumor uptake, the larger was the underestimation of PET volumes by threshold-based techniques. Volumes based on CT images were larger than those based on PET images. Tumor size and tracer uptake heterogeneity have an impact on threshold-based methods, which should not be used for the delineation of cases of large heterogeneous NSCLC, as these methods tend to largely underestimate the spatial extent of the functional tumor in such cases. For an accurate delineation of PET volumes in NSCLC, advanced image segmentation algorithms able to deal with tracer uptake heterogeneity should be preferred.

Investigation of four-dimensional computed tomography-based pulmonary ventilation imaging in patients with emphysematous lung regions

NASA Astrophysics Data System (ADS)

Yamamoto, Tokihiro; Kabus, Sven; Klinder, Tobias; Lorenz, Cristian; von Berg, Jens; Blaffert, Thomas; Loo, Billy W., Jr.; Keall, Paul J.

2011-04-01

A pulmonary ventilation imaging technique based on four-dimensional (4D) computed tomography (CT) has advantages over existing techniques. However, physiologically accurate 4D-CT ventilation imaging has not been achieved in patients. The purpose of this study was to evaluate 4D-CT ventilation imaging by correlating ventilation with emphysema. Emphysematous lung regions are less ventilated and can be used as surrogates for low ventilation. We tested the hypothesis: 4D-CT ventilation in emphysematous lung regions is significantly lower than in non-emphysematous regions. Four-dimensional CT ventilation images were created for 12 patients with emphysematous lung regions as observed on CT, using a total of four combinations of two deformable image registration (DIR) algorithms: surface-based (DIRsur) and volumetric (DIRvol), and two metrics: Hounsfield unit (HU) change (VHU) and Jacobian determinant of deformation (VJac), yielding four ventilation image sets per patient. Emphysematous lung regions were detected by density masking. We tested our hypothesis using the one-tailed t-test. Visually, different DIR algorithms and metrics yielded spatially variant 4D-CT ventilation images. The mean ventilation values in emphysematous lung regions were consistently lower than in non-emphysematous regions for all the combinations of DIR algorithms and metrics. VHU resulted in statistically significant differences for both DIRsur (0.14 ± 0.14 versus 0.29 ± 0.16, p = 0.01) and DIRvol (0.13 ± 0.13 versus 0.27 ± 0.15, p < 0.01). However, VJac resulted in non-significant differences for both DIRsur (0.15 ± 0.07 versus 0.17 ± 0.08, p = 0.20) and DIRvol (0.17 ± 0.08 versus 0.19 ± 0.09, p = 0.30). This study demonstrated the strong correlation between the HU-based 4D-CT ventilation and emphysema, which indicates the potential for HU-based 4D-CT ventilation imaging to achieve high physiologic accuracy. A further study is needed to confirm these results.

Study on Mosaic and Uniform Color Method of Satellite Image Fusion in Large Srea

NASA Astrophysics Data System (ADS)

Liu, S.; Li, H.; Wang, X.; Guo, L.; Wang, R.

2018-04-01

Due to the improvement of satellite radiometric resolution and the color difference for multi-temporal satellite remote sensing images and the large amount of satellite image data, how to complete the mosaic and uniform color process of satellite images is always an important problem in image processing. First of all using the bundle uniform color method and least squares mosaic method of GXL and the dodging function, the uniform transition of color and brightness can be realized in large area and multi-temporal satellite images. Secondly, using Color Mapping software to color mosaic images of 16bit to mosaic images of 8bit based on uniform color method with low resolution reference images. At last, qualitative and quantitative analytical methods are used respectively to analyse and evaluate satellite image after mosaic and uniformity coloring. The test reflects the correlation of mosaic images before and after coloring is higher than 95 % and image information entropy increases, texture features are enhanced which have been proved by calculation of quantitative indexes such as correlation coefficient and information entropy. Satellite image mosaic and color processing in large area has been well implemented.

Nondestructive assessment of collagen hydrogel cross-linking using time-resolved autofluorescence imaging.

PubMed

Sherlock, Benjamin E; Harvestine, Jenna N; Mitra, Debika; Haudenschild, Anne; Hu, Jerry; Athanasiou, Kyriacos A; Leach, J Kent; Marcu, Laura

2018-03-01

We investigate the use of a fiber-based, multispectral fluorescence lifetime imaging (FLIm) system to nondestructively monitor changes in mechanical properties of collagen hydrogels caused by controlled application of widely used cross-linking agents, glutaraldehyde (GTA) and ribose. Postcross-linking, fluorescence lifetime images are acquired prior to the hydrogels being processed by rheological or tensile testing to directly probe gel mechanical properties. To preserve the sterility of the ribose-treated gels, FLIm is performed inside a biosafety cabinet (BSC). A pairwise correlation analysis is used to quantify the relationship between mean hydrogel fluorescence lifetimes and the storage or Young's moduli of the gels. In the GTA study, we observe strong and specific correlations between fluorescence lifetime and the storage and Young's moduli. Similar correlations are not observed in the ribose study and we postulate a reason for this. Finally, we demonstrate the ability of FLIm to longitudinally monitor dynamic cross-link formation. The strength of the GTA correlations and deployment of our fiber-based FLIm system inside the aseptic environment of a BSC suggests that this technique may be a valuable tool for the tissue engineering community where longitudinal assessment of tissue construct maturation in vitro is highly desirable. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Quantitative validation of a nonlinear histology-MRI coregistration method using Generalized Q-sampling Imaging in complex human cortical white matter

PubMed Central

Gangolli, Mihika; Holleran, Laurena; Kim, Joong Hee; Stein, Thor D.; Alvarez, Victor; McKee, Ann C.; Brody, David L.

2017-01-01

Advanced diffusion MRI methods have recently been proposed for detection of pathologies such as traumatic axonal injury and chronic traumatic encephalopathy which commonly affect complex cortical brain regions. However, radiological-pathological correlations in human brain tissue that detail the relationship between the multi-component diffusion signal and underlying pathology are lacking. We present a nonlinear voxel based two dimensional coregistration method that is useful for matching diffusion signals to quantitative metrics of high resolution histological images. When validated in ex vivo human cortical tissue at a 250 × 250 × 500 micron spatial resolution, the method proved robust in correlations between generalized q-sampling imaging and histologically based white matter fiber orientations, with r = 0.94 for the primary fiber direction and r = 0.88 for secondary fiber direction in each voxel. Importantly, however, the correlation was substantially worse with reduced spatial resolution or with fiber orientations derived using a diffusion tensor model. Furthermore, we have detailed a quantitative histological metric of white matter fiber integrity termed power coherence capable of distinguishing between architecturally complex but intact white matter from disrupted white matter regions. These methods may allow for more sensitive and specific radiological-pathological correlations of neurodegenerative diseases affecting complex gray and white matter. PMID:28365421

Correlation-based discrimination between cardiac tissue and blood for segmentation of 3D echocardiographic images

NASA Astrophysics Data System (ADS)

Saris, Anne E. C. M.; Nillesen, Maartje M.; Lopata, Richard G. P.; de Korte, Chris L.

2013-03-01

Automated segmentation of 3D echocardiographic images in patients with congenital heart disease is challenging, because the boundary between blood and cardiac tissue is poorly defined in some regions. Cardiologists mentally incorporate movement of the heart, using temporal coherence of structures to resolve ambiguities. Therefore, we investigated the merit of temporal cross-correlation for automated segmentation over the entire cardiac cycle. Optimal settings for maximum cross-correlation (MCC) calculation, based on a 3D cross-correlation based displacement estimation algorithm, were determined to obtain the best contrast between blood and myocardial tissue over the entire cardiac cycle. Resulting envelope-based as well as RF-based MCC values were used as additional external force in a deformable model approach, to segment the left-ventricular cavity in entire systolic phase. MCC values were tested against, and combined with, adaptive filtered, demodulated RF-data. Segmentation results were compared with manually segmented volumes using a 3D Dice Similarity Index (3DSI). Results in 3D pediatric echocardiographic images sequences (n = 4) demonstrate that incorporation of temporal information improves segmentation. The use of MCC values, either alone or in combination with adaptive filtered, demodulated RF-data, resulted in an increase of the 3DSI in 75% of the cases (average 3DSI increase: 0.71 to 0.82). Results might be further improved by optimizing MCC-contrast locally, in regions with low blood-tissue contrast. Reducing underestimation of the endocardial volume due to MCC processing scheme (choice of window size) and consequential border-misalignment, could also lead to more accurate segmentations. Furthermore, increasing the frame rate will also increase MCC-contrast and thus improve segmentation.

Binary image encryption in a joint transform correlator scheme by aid of run-length encoding and QR code

NASA Astrophysics Data System (ADS)

Qin, Yi; Wang, Zhipeng; Wang, Hongjuan; Gong, Qiong

2018-07-01

We propose a binary image encryption method in joint transform correlator (JTC) by aid of the run-length encoding (RLE) and Quick Response (QR) code, which enables lossless retrieval of the primary image. The binary image is encoded with RLE to obtain the highly compressed data, and then the compressed binary image is further scrambled using a chaos-based method. The compressed and scrambled binary image is then transformed into one QR code that will be finally encrypted in JTC. The proposed method successfully, for the first time to our best knowledge, encodes a binary image into a QR code with the identical size of it, and therefore may probe a new way for extending the application of QR code in optical security. Moreover, the preprocessing operations, including RLE, chaos scrambling and the QR code translation, append an additional security level on JTC. We present digital results that confirm our approach.

A content-based image retrieval method for optical colonoscopy images based on image recognition techniques

NASA Astrophysics Data System (ADS)

Nosato, Hirokazu; Sakanashi, Hidenori; Takahashi, Eiichi; Murakawa, Masahiro

2015-03-01

This paper proposes a content-based image retrieval method for optical colonoscopy images that can find images similar to ones being diagnosed. Optical colonoscopy is a method of direct observation for colons and rectums to diagnose bowel diseases. It is the most common procedure for screening, surveillance and treatment. However, diagnostic accuracy for intractable inflammatory bowel diseases, such as ulcerative colitis (UC), is highly dependent on the experience and knowledge of the medical doctor, because there is considerable variety in the appearances of colonic mucosa within inflammations with UC. In order to solve this issue, this paper proposes a content-based image retrieval method based on image recognition techniques. The proposed retrieval method can find similar images from a database of images diagnosed as UC, and can potentially furnish the medical records associated with the retrieved images to assist the UC diagnosis. Within the proposed method, color histogram features and higher order local auto-correlation (HLAC) features are adopted to represent the color information and geometrical information of optical colonoscopy images, respectively. Moreover, considering various characteristics of UC colonoscopy images, such as vascular patterns and the roughness of the colonic mucosa, we also propose an image enhancement method to highlight the appearances of colonic mucosa in UC. In an experiment using 161 UC images from 32 patients, we demonstrate that our method improves the accuracy of retrieving similar UC images.

Reducing 4D CT artifacts using optimized sorting based on anatomic similarity.

PubMed

Johnston, Eric; Diehn, Maximilian; Murphy, James D; Loo, Billy W; Maxim, Peter G

2011-05-01

Four-dimensional (4D) computed tomography (CT) has been widely used as a tool to characterize respiratory motion in radiotherapy. The two most commonly used 4D CT algorithms sort images by the associated respiratory phase or displacement into a predefined number of bins, and are prone to image artifacts at transitions between bed positions. The purpose of this work is to demonstrate a method of reducing motion artifacts in 4D CT by incorporating anatomic similarity into phase or displacement based sorting protocols. Ten patient datasets were retrospectively sorted using both the displacement and phase based sorting algorithms. Conventional sorting methods allow selection of only the nearest-neighbor image in time or displacement within each bin. In our method, for each bed position either the displacement or the phase defines the center of a bin range about which several candidate images are selected. The two dimensional correlation coefficients between slices bordering the interface between adjacent couch positions are then calculated for all candidate pairings. Two slices have a high correlation if they are anatomically similar. Candidates from each bin are then selected to maximize the slice correlation over the entire data set using the Dijkstra's shortest path algorithm. To assess the reduction of artifacts, two thoracic radiation oncologists independently compared the resorted 4D datasets pairwise with conventionally sorted datasets, blinded to the sorting method, to choose which had the least motion artifacts. Agreement between reviewers was evaluated using the weighted kappa score. Anatomically based image selection resulted in 4D CT datasets with significantly reduced motion artifacts with both displacement (P = 0.0063) and phase sorting (P = 0.00022). There was good agreement between the two reviewers, with complete agreement 34 times and complete disagreement 6 times. Optimized sorting using anatomic similarity significantly reduces 4D CT motion artifacts compared to conventional phase or displacement based sorting. This improved sorting algorithm is a straightforward extension of the two most common 4D CT sorting algorithms.

Improved initial guess with semi-subpixel level accuracy in digital image correlation by feature-based method

NASA Astrophysics Data System (ADS)

Zhang, Yunlu; Yan, Lei; Liou, Frank

2018-05-01

The quality initial guess of deformation parameters in digital image correlation (DIC) has a serious impact on convergence, robustness, and efficiency of the following subpixel level searching stage. In this work, an improved feature-based initial guess (FB-IG) scheme is presented to provide initial guess for points of interest (POIs) inside a large region. Oriented FAST and Rotated BRIEF (ORB) features are semi-uniformly extracted from the region of interest (ROI) and matched to provide initial deformation information. False matched pairs are eliminated by the novel feature guided Gaussian mixture model (FG-GMM) point set registration algorithm, and nonuniform deformation parameters of the versatile reproducing kernel Hilbert space (RKHS) function are calculated simultaneously. Validations on simulated images and real-world mini tensile test verify that this scheme can robustly and accurately compute initial guesses with semi-subpixel level accuracy in cases with small or large translation, deformation, or rotation.

Homo-FRET Based Biosensors and Their Application to Multiplexed Imaging of Signalling Events in Live Cells

PubMed Central

Warren, Sean C.; Margineanu, Anca; Katan, Matilda; Dunsby, Chris; French, Paul M. W.

2015-01-01

Multiplexed imaging of Förster Resonance Energy Transfer (FRET)-based biosensors potentially presents a powerful approach to monitoring the spatio-temporal correlation of signalling pathways within a single live cell. Here, we discuss the potential of homo-FRET based biosensors to facilitate multiplexed imaging. We demonstrate that the homo-FRET between pleckstrin homology domains of Akt (Akt-PH) labelled with mCherry may be used to monitor 3′-phosphoinositide accumulation in live cells and show how global analysis of time resolved fluorescence anisotropy measurements can be used to quantify this accumulation. We further present multiplexed imaging readouts of calcium concentration, using fluorescence lifetime measurements of TN-L15-a CFP/YFP based hetero-FRET calcium biosensor-with 3′-phosphoinositide accumulation. PMID:26133241

Progressive cone beam CT dose control in image-guided radiation therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yan Hao; Cervino, Laura; Jiang, Steve B.

2013-06-15

Purpose: Cone beam CT (CBCT) in image-guided radiotherapy (IGRT) offers a tremendous advantage for treatment guidance. The associated imaging dose is a clinical concern. One unique feature of CBCT-based IGRT is that the same patient is repeatedly scanned during a treatment course, and the contents of CBCT images at different fractions are similar. The authors propose a progressive dose control (PDC) scheme to utilize this temporal correlation for imaging dose reduction. Methods: A dynamic CBCT scan protocol, as opposed to the static one in the current clinical practice, is proposed to gradually reduce the imaging dose in each treatment fraction.more » The CBCT image from each fraction is processed by a prior-image based nonlocal means (PINLM) module to enhance its quality. The increasing amount of prior information from previous CBCT images prevents degradation of image quality due to the reduced imaging dose. Two proof-of-principle experiments have been conducted using measured phantom data and Monte Carlo simulated patient data with deformation. Results: In the measured phantom case, utilizing a prior image acquired at 0.4 mAs, PINLM is able to improve the image quality of a CBCT acquired at 0.2 mAs by reducing the noise level from 34.95 to 12.45 HU. In the synthetic patient case, acceptable image quality is maintained at four consecutive fractions with gradually decreasing exposure levels of 0.4, 0.1, 0.07, and 0.05 mAs. When compared with the standard low-dose protocol of 0.4 mAs for each fraction, an overall imaging dose reduction of more than 60% is achieved. Conclusions: PINLM-PDC is able to reduce CBCT imaging dose in IGRT utilizing the temporal correlations among the sequence of CBCT images while maintaining the quality.« less

Experimental research of digital image correlation system in high temperature test

NASA Astrophysics Data System (ADS)

Chen, Li; Wang, Yonghong; Dan, Xizuo; Xiao, Ying; Yang, Lianxiang

2016-01-01

Digital Image Correlation (DIC) is a full-field technique based on white-light illumination for displacement and strain measurement. But radiation on the specimen surface at high temperature affects the quality of acquired speckle pattern images for traditional DIC measurement. In order to minimize the radiation effect in high temperature measurement, this paper proposes a two-dimensional ultraviolet digital image correlation system (2D UV-DIC) containing UV LED and UV band-pass filter. It is confirmed by experiments that images acquired by this system saturate at higher temperature in comparison with DIC using filtered blue light imaging system. And the UV-DIC remains minimally affected by radiation at the temperature which is nearing the specimen's maximum working temperature (about 1250°C). In addition, considering the heat disturbance that can't be ignored in actual high temperature measurement, this paper also proposes a method using an air controller in combination with image average algorithm, and the method was then used to obtain the thermal expansion coefficient of the Austenitic chromium-nickel stainless steel specimen at different temperatures. By comparing the coefficients with the results calculated by other method, it shows that this comprehensive method has the advantages of strong anti-interference ability and high precision.

A comparison of stereology, structural rigidity and a novel 3D failure surface analysis method in the assessment of torsional strength and stiffness in a mouse tibia fracture model.

PubMed

Wright, David A; Nam, Diane; Whyne, Cari M

2012-08-31

In attempting to develop non-invasive image based measures for the determination of the biomechanical integrity of healing fractures, traditional μCT based measurements have been limited. This study presents the development and evaluation of a tool for assessment of fracture callus mechanical properties through determination of the geometric characteristics of the fracture callus, specifically along the surface of failure identified during destructive mechanical testing. Fractures were created in tibias of ten male mice and subjected to μCT imaging and biomechanical torsion testing. Failure surface analysis, along with previously described image based measures was calculated using the μCT image data, and correlated with mechanical strength and stiffness. Three-dimensional measures along the surface of failure, specifically the surface area and torsional rigidity of bone, were shown to be significantly correlating with mechanical strength and stiffness. It was also shown that surface area of bone along the failure surface exhibits stronger correlations with both strength and stiffness than measures of average and minimum torsional rigidity of the entire callus. Failure surfaces observed in this study were generally oriented at 45° to the long axis of the bone, and were not contained exclusively within the callus. This work represents a proof of concept study, and shows the potential utility of failure surface analysis in the assessment of fracture callus stability. Copyright © 2012 Elsevier Ltd. All rights reserved.

Fluorescence hyperspectral imaging technique for the foreign substance detection on fresh-cut lettuce

USDA-ARS?s Scientific Manuscript database

Nondestructive methods based on fluorescence hyperspectral imaging (HSI) techniques were developed in order to detect worms on fresh-cut lettuce. The optimal wavebands for detecting worms on fresh-cut lettuce were investigated using the one-way ANOVA analysis and correlation analysis. The worm detec...

Four-Photon Imaging with Thermal Light

NASA Astrophysics Data System (ADS)

Wen, Feng; Xue, Xinxin; Zhang, Xun; Yuan, Chenzhi; Sun, Jia; Song, Jianping; Zhang, Yanpeng

2014-10-01

In a near-field four-photon correlation measurement, ghost imaging with classical incoherent light is investigated. By applying the Klyshko advanced-wave picture, we consider the properties of four-photon spatial correlation and find that the fourth-order spatial correlation function can be decomposed into multiple lower-order correlation functions. On the basis of the spatial correlation properties, a proof-of-principle four-photon ghost imaging is proposed, and the effect of each part in a fourth-order correlation function on imaging is also analyzed. In addition, the similarities and differences among ghost imaging by fourth-, second-, and third-order correlations are also discussed. It is shown that the contrast and visibility of fourth-order correlated imaging are improved significantly, while the resolution is unchanged. Such studies can be very useful in better understanding multi photon interference and multi-channel correlation imaging.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shcheslavskiy, V. I.; Institute of Biomedical Technologies, Nizhny Novgorod State Medical Academy, Minin and Pozharsky Square, 10/1, Nizhny Novgorod 603005; Neubauer, A.

We present a lifetime imaging technique that simultaneously records the fluorescence and phosphorescence lifetime images in confocal laser scanning systems. It is based on modulating a high-frequency pulsed laser synchronously with the pixel clock of the scanner, and recording the fluorescence and phosphorescence signals by multidimensional time-correlated single photon counting board. We demonstrate our technique on the recording of the fluorescence/phosphorescence lifetime images of human embryonic kidney cells at different environmental conditions.

An autonomous surface discontinuity detection and quantification method by digital image correlation and phase congruency

NASA Astrophysics Data System (ADS)

Cinar, A. F.; Barhli, S. M.; Hollis, D.; Flansbjer, M.; Tomlinson, R. A.; Marrow, T. J.; Mostafavi, M.

2017-09-01

Digital image correlation has been routinely used to measure full-field displacements in many areas of solid mechanics, including fracture mechanics. Accurate segmentation of the crack path is needed to study its interaction with the microstructure and stress fields, and studies of crack behaviour, such as the effect of closure or residual stress in fatigue, require data on its opening displacement. Such information can be obtained from any digital image correlation analysis of cracked components, but it collection by manual methods is quite onerous, particularly for massive amounts of data. We introduce the novel application of Phase Congruency to detect and quantify cracks and their opening. Unlike other crack detection techniques, Phase Congruency does not rely on adjustable threshold values that require user interaction, and so allows large datasets to be treated autonomously. The accuracy of the Phase Congruency based algorithm in detecting cracks is evaluated and compared with conventional methods such as Heaviside function fitting. As Phase Congruency is a displacement-based method, it does not suffer from the noise intensification to which gradient-based methods (e.g. strain thresholding) are susceptible. Its application is demonstrated to experimental data for cracks in quasi-brittle (Granitic rock) and ductile (Aluminium alloy) materials.

Evaluation of adaptive treatment planning for patients with non-small cell lung cancer

NASA Astrophysics Data System (ADS)

Zhong, Hualiang; Siddiqui, Salim M.; Movsas, Benjamin; Chetty, Indrin J.

2017-06-01

The purpose of this study was to develop metrics to evaluate uncertainties in deformable dose accumulation for patients with non-small cell lung cancer (NSCLC). Initial treatment plans (primary) and cone-beam CT (CBCT) images were retrospectively processed for seven NSCLC patients, who showed significant tumor regression during the course of treatment. Each plan was developed with IMRT for 2 Gy  ×  33 fractions. A B-spline-based DIR algorithm was used to register weekly CBCT images to a reference image acquired at fraction 21 and the resultant displacement vector fields (DVFs) were then modified using a finite element method (FEM). The doses were calculated on each of these CBCT images and mapped to the reference image using a tri-linear dose interpolation method, based on the B-spline and FEM-generated DVFs. Contours propagated from the planning image were adjusted to the residual tumor and OARs on the reference image to develop a secondary plan. For iso-prescription adaptive plans (relative to initial plans), mean lung dose (MLD) was reduced, on average from 17.3 Gy (initial plan) to 15.2, 14.5 and 14.8 Gy for the plans adapted using the rigid, B-Spline and FEM-based registrations. Similarly, for iso-toxic adaptive plans (considering MLD relative to initial plans) using the rigid, B-Spline and FEM-based registrations, the average doses were 69.9  ±  6.8, 65.7  ±  5.1 and 67.2  ±  5.6 Gy in the initial volume (PTV1), and 81.5  ±  25.8, 77.7  ±  21.6, and 78.9  ±  22.5 Gy in the residual volume (PTV21), respectively. Tumor volume reduction was correlated with dose escalation (for isotoxic plans, correlation coefficient  =  0.92), and with MLD reduction (for iso-fractional plans, correlation coefficient  =  0.85). For the case of the iso-toxic dose escalation, plans adapted with the B-Spline and FEM DVFs differed from the primary plan adapted with rigid registration by 2.8  ±  1.0 Gy and 1.8  ±  0.9 Gy in PTV1, and the mean difference between doses accumulated using the B-spline and FEM DVF’s was 1.1  ±  0.6 Gy. As a dose mapping-induced energy change, energy defect in the tumor volume was 20.8  ±  13.4% and 4.5  ±  2.4% for the B-spline and FEM-based dose accumulations, respectively. The energy defect of the B-Spline-based dose accumulation is significant in the tumor volume and highly correlated to the difference between the B-Spline and FEM-accumulated doses with their correlation coefficient equal to 0.79. Adaptive planning helps escalate target dose and spare normal tissue for patients with NSCLC, but deformable dose accumulation may have a significant loss of energy in regressed tumor volumes when using image intensity-based DIR algorithms. The metric of energy defect is a useful tool for evaluation of adaptive planning accuracy for lung cancer patients.

Detection of Cardiac Quiescence from B-Mode Echocardiography Using a Correlation-Based Frame-to-Frame Deviation Measure

PubMed Central

Mcclellan, James H.; Ravichandran, Lakshminarayan; Tridandapani, Srini

2013-01-01

Two novel methods for detecting cardiac quiescent phases from B-mode echocardiography using a correlation-based frame-to-frame deviation measure were developed. Accurate knowledge of cardiac quiescence is crucial to the performance of many imaging modalities, including computed tomography coronary angiography (CTCA). Synchronous electrocardiography (ECG) and echocardiography data were obtained from 10 healthy human subjects (four male, six female, 23–45 years) and the interventricular septum (IVS) was observed using the apical four-chamber echocardiographic view. The velocity of the IVS was derived from active contour tracking and verified using tissue Doppler imaging echocardiography methods. In turn, the frame-to-frame deviation methods for identifying quiescence of the IVS were verified using active contour tracking. The timing of the diastolic quiescent phase was found to exhibit both inter- and intra-subject variability, suggesting that the current method of CTCA gating based on the ECG is suboptimal and that gating based on signals derived from cardiac motion are likely more accurate in predicting quiescence for cardiac imaging. Two robust and efficient methods for identifying cardiac quiescent phases from B-mode echocardiographic data were developed and verified. The methods presented in this paper will be used to develop new CTCA gating techniques and quantify the resulting potential improvement in CTCA image quality. PMID:26609501

Speckle noise reduction for optical coherence tomography based on adaptive 2D dictionary

NASA Astrophysics Data System (ADS)

Lv, Hongli; Fu, Shujun; Zhang, Caiming; Zhai, Lin

2018-05-01

As a high-resolution biomedical imaging modality, optical coherence tomography (OCT) is widely used in medical sciences. However, OCT images often suffer from speckle noise, which can mask some important image information, and thus reduce the accuracy of clinical diagnosis. Taking full advantage of nonlocal self-similarity and adaptive 2D-dictionary-based sparse representation, in this work, a speckle noise reduction algorithm is proposed for despeckling OCT images. To reduce speckle noise while preserving local image features, similar nonlocal patches are first extracted from the noisy image and put into groups using a gamma- distribution-based block matching method. An adaptive 2D dictionary is then learned for each patch group. Unlike traditional vector-based sparse coding, we express each image patch by the linear combination of a few matrices. This image-to-matrix method can exploit the local correlation between pixels. Since each image patch might belong to several groups, the despeckled OCT image is finally obtained by aggregating all filtered image patches. The experimental results demonstrate the superior performance of the proposed method over other state-of-the-art despeckling methods, in terms of objective metrics and visual inspection.

Verbal working memory performance correlates with regional white matter structures in the frontoparietal regions.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Sassa, Yuko; Hashizume, Hiroshi; Sekiguchi, Atsushi; Fukushima, Ai; Kawashima, Ryuta

2011-10-01

Working memory is the limited capacity storage system involved in the maintenance and manipulation of information over short periods of time. Previous imaging studies have suggested that the frontoparietal regions are activated during working memory tasks; a putative association between the structure of the frontoparietal regions and working memory performance has been suggested based on the analysis of individuals with varying pathologies. This study aimed to identify correlations between white matter and individual differences in verbal working memory performance in normal young subjects. We performed voxel-based morphometry (VBM) analyses using T1-weighted structural images as well as voxel-based analyses of fractional anisotropy (FA) using diffusion tensor imaging. Using the letter span task, we measured verbal working memory performance in normal young adult men and women (mean age, 21.7 years, SD=1.44; 42 men and 13 women). We observed positive correlations between working memory performance and regional white matter volume (rWMV) in the frontoparietal regions. In addition, FA was found to be positively correlated with verbal working memory performance in a white matter region adjacent to the right precuneus. These regions are consistently recruited by working memory. Our findings suggest that, among normal young subjects, verbal working memory performance is associated with various regions that are recruited during working memory tasks, and this association is not limited to specific parts of the working memory network. Copyright © 2011 Elsevier Ltd. All rights reserved.

TU-AB-BRA-11: Evaluation of Fully Automatic Volumetric GBM Segmentation in the TCGA-GBM Dataset: Prognosis and Correlation with VASARI Features

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rios Velazquez, E; Meier, R; Dunn, W

Purpose: Reproducible definition and quantification of imaging biomarkers is essential. We evaluated a fully automatic MR-based segmentation method by comparing it to manually defined sub-volumes by experienced radiologists in the TCGA-GBM dataset, in terms of sub-volume prognosis and association with VASARI features. Methods: MRI sets of 67 GBM patients were downloaded from the Cancer Imaging archive. GBM sub-compartments were defined manually and automatically using the Brain Tumor Image Analysis (BraTumIA), including necrosis, edema, contrast enhancing and non-enhancing tumor. Spearman’s correlation was used to evaluate the agreement with VASARI features. Prognostic significance was assessed using the C-index. Results: Auto-segmented sub-volumes showedmore » high agreement with manually delineated volumes (range (r): 0.65 – 0.91). Also showed higher correlation with VASARI features (auto r = 0.35, 0.60 and 0.59; manual r = 0.29, 0.50, 0.43, for contrast-enhancing, necrosis and edema, respectively). The contrast-enhancing volume and post-contrast abnormal volume showed the highest C-index (0.73 and 0.72), comparable to manually defined volumes (p = 0.22 and p = 0.07, respectively). The non-enhancing region defined by BraTumIA showed a significantly higher prognostic value (CI = 0.71) than the edema (CI = 0.60), both of which could not be distinguished by manual delineation. Conclusion: BraTumIA tumor sub-compartments showed higher correlation with VASARI data, and equivalent performance in terms of prognosis compared to manual sub-volumes. This method can enable more reproducible definition and quantification of imaging based biomarkers and has a large potential in high-throughput medical imaging research.« less

A novel measure and significance testing in data analysis of cell image segmentation.

PubMed

Wu, Jin Chu; Halter, Michael; Kacker, Raghu N; Elliott, John T; Plant, Anne L

2017-03-14

Cell image segmentation (CIS) is an essential part of quantitative imaging of biological cells. Designing a performance measure and conducting significance testing are critical for evaluating and comparing the CIS algorithms for image-based cell assays in cytometry. Many measures and methods have been proposed and implemented to evaluate segmentation methods. However, computing the standard errors (SE) of the measures and their correlation coefficient is not described, and thus the statistical significance of performance differences between CIS algorithms cannot be assessed. We propose the total error rate (TER), a novel performance measure for segmenting all cells in the supervised evaluation. The TER statistically aggregates all misclassification error rates (MER) by taking cell sizes as weights. The MERs are for segmenting each single cell in the population. The TER is fully supported by the pairwise comparisons of MERs using 106 manually segmented ground-truth cells with different sizes and seven CIS algorithms taken from ImageJ. Further, the SE and 95% confidence interval (CI) of TER are computed based on the SE of MER that is calculated using the bootstrap method. An algorithm for computing the correlation coefficient of TERs between two CIS algorithms is also provided. Hence, the 95% CI error bars can be used to classify CIS algorithms. The SEs of TERs and their correlation coefficient can be employed to conduct the hypothesis testing, while the CIs overlap, to determine the statistical significance of the performance differences between CIS algorithms. A novel measure TER of CIS is proposed. The TER's SEs and correlation coefficient are computed. Thereafter, CIS algorithms can be evaluated and compared statistically by conducting the significance testing.

Comparing image quality of print-on-demand books and photobooks from web-based vendors

NASA Astrophysics Data System (ADS)

Phillips, Jonathan; Bajorski, Peter; Burns, Peter; Fredericks, Erin; Rosen, Mitchell

2010-01-01

Because of the emergence of e-commerce and developments in print engines designed for economical output of very short runs, there are increased business opportunities and consumer options for print-on-demand books and photobooks. The current state of these printing modes allows for direct uploading of book files via the web, printing on nonoffset printers, and distributing by standard parcel or mail delivery services. The goal of this research is to assess the image quality of print-on-demand books and photobooks produced by various Web-based vendors and to identify correlations between psychophysical results and objective metrics. Six vendors were identified for one-off (single-copy) print-on-demand books, and seven vendors were identified for photobooks. Participants rank ordered overall quality of a subset of individual pages from each book, where the pages included text, photographs, or a combination of the two. Observers also reported overall quality ratings and price estimates for the bound books. Objective metrics of color gamut, color accuracy, accuracy of International Color Consortium profile usage, eye-weighted root mean square L*, and cascaded modulation transfer acutance were obtained and compared to the observer responses. We introduce some new methods for normalizing data as well as for strengthening the statistical significance of the results. Our approach includes the use of latent mixed-effect models. We found statistically significant correlation with overall image quality and some of the spatial metrics, but correlations between psychophysical results and other objective metrics were weak or nonexistent. Strong correlation was found between psychophysical results of overall quality assessment and estimated price associated with quality. The photobook set of vendors reached higher image-quality ratings than the set of print-on-demand vendors. However, the photobook set had higher image-quality variability.

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy

PubMed Central

Kim, Dahan; Curthoys, Nikki M.; Parent, Matthew T.; Hess, Samuel T.

2015-01-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined. PMID:26185614

Bleed-through correction for rendering and correlation analysis in multi-colour localization microscopy.

PubMed

Kim, Dahan; Curthoys, Nikki M; Parent, Matthew T; Hess, Samuel T

2013-09-01

Multi-colour localization microscopy has enabled sub-diffraction studies of colocalization between multiple biological species and quantification of their correlation at length scales previously inaccessible with conventional fluorescence microscopy. However, bleed-through, or misidentification of probe species, creates false colocalization and artificially increases certain types of correlation between two imaged species, affecting the reliability of information provided by colocalization and quantified correlation. Despite the potential risk of these artefacts of bleed-through, neither the effect of bleed-through on correlation nor methods of its correction in correlation analyses has been systematically studied at typical rates of bleed-through reported to affect multi-colour imaging. Here, we present a reliable method of bleed-through correction applicable to image rendering and correlation analysis of multi-colour localization microscopy. Application of our bleed-through correction shows our method accurately corrects the artificial increase in both types of correlations studied (Pearson coefficient and pair correlation), at all rates of bleed-through tested, in all types of correlations examined. In particular, anti-correlation could not be quantified without our bleed-through correction, even at rates of bleed-through as low as 2%. Demonstrated with dichroic-based multi-colour FPALM here, our presented method of bleed-through correction can be applied to all types of localization microscopy (PALM, STORM, dSTORM, GSDIM, etc.), including both simultaneous and sequential multi-colour modalities, provided the rate of bleed-through can be reliably determined.

Hyperspectral image compressing using wavelet-based method

NASA Astrophysics Data System (ADS)

Yu, Hui; Zhang, Zhi-jie; Lei, Bo; Wang, Chen-sheng

2017-10-01

Hyperspectral imaging sensors can acquire images in hundreds of continuous narrow spectral bands. Therefore each object presented in the image can be identified from their spectral response. However, such kind of imaging brings a huge amount of data, which requires transmission, processing, and storage resources for both airborne and space borne imaging. Due to the high volume of hyperspectral image data, the exploration of compression strategies has received a lot of attention in recent years. Compression of hyperspectral data cubes is an effective solution for these problems. Lossless compression of the hyperspectral data usually results in low compression ratio, which may not meet the available resources; on the other hand, lossy compression may give the desired ratio, but with a significant degradation effect on object identification performance of the hyperspectral data. Moreover, most hyperspectral data compression techniques exploits the similarities in spectral dimensions; which requires bands reordering or regrouping, to make use of the spectral redundancy. In this paper, we explored the spectral cross correlation between different bands, and proposed an adaptive band selection method to obtain the spectral bands which contain most of the information of the acquired hyperspectral data cube. The proposed method mainly consist three steps: First, the algorithm decomposes the original hyperspectral imagery into a series of subspaces based on the hyper correlation matrix of the hyperspectral images between different bands. And then the Wavelet-based algorithm is applied to the each subspaces. At last the PCA method is applied to the wavelet coefficients to produce the chosen number of components. The performance of the proposed method was tested by using ISODATA classification method.

Correlated FLIM and PLIM for cell metabolism

NASA Astrophysics Data System (ADS)

Rück, A.; Breymayer, J.; Kalinina, S.

2016-03-01

Correlated imaging of phosphorescence and fluorescence lifetime parameters of metabolic markers is a challenge for direct investigating mechanisms related to cell metabolism and oxygen tension. A large variety of clinical phenotypes is associated with mitochondrial defects accomplished with changes in cell metabolism. In many cases the hypoxic microenvironment of cancer cells shifts metabolism from oxidative phosphorylation (OXPHOS) to anaerobic or aerobic glycolysis, a process known as "Warburg" effect. Also during stem cell differentiation a switch in cell metabolism is observed. A defective mitochondrial function associated with hypoxia has been invoked in many complex disorders such as type 2 diabetes, Alzheimers disease, cardiac ischemia/reperfusion injury, tissue inflammation and cancer. Cellular responses to oxygen tension have been studied extensively, optical imaging techniques based on time correlated single photon counting (TCSPC) to detect the underlying metabolic mechanisms are therefore of prominent interest. They offer the possibility by inspecting fluorescence decay characteristics of intrinsic coenzymes to directly image metabolic pathways. Moreover oxygen tension can be determined by considering the phosphorescence lifetime of a phosphorescent probe. The combination of both fluorescence lifetime imaging (FLIM) of coenzymes like NADH and FAD and phosphorescence lifetime (PLIM) of phosphorescent dyes could provide valuable information about correlation of metabolic pathways and oxygen tension.

Correlation between blink reflex abnormalities and magnetic resonance imaging findings in patients with multiple sclerosis.

PubMed

Degirmenci, Eylem; Erdogan, Cagdas; Bir, Levent Sinan

2013-09-01

This study investigates the correlation between brain magnetic resonance imaging findings and blink reflex abnormalities in patients with relapsing remitting multiple sclerosis. Twenty-six patients and 17 healthy subjects were included in this study. Blink reflex test (BRT) results were obtained using right and left stimulations; thus, 52 BRT results were recorded for the patient group, and 34 BRT results were recorded for the control group. The magnetic resonance imaging (MRI) findings were classified based on the existence of brainstem lesions (hyperintense lesion on T2 weighted (W) and fast fluid-attenuated inversion recovery MRI or contrast-enhancing lesion on T1W MRI). Correlation analysis was performed for the BRT and MRI findings. The percentage of individuals with abnormal BRT results (including R1 latency, ipsilateral R2 latency, and contralateral R2 latency) was significantly higher in the patient group as compared to the control group (p values: 0.015, 0.001, and 0.002, respectively). Correlation analysis revealed significant correlations between contralateral R2 latency abnormalities and brainstem lesions (p value: 0.011). Our results showed significant correlation correlations between contralateral R2 latency abnormalities and brainstem lesions and these results may be explained the effects of multiple demyelinating lesions of the brain stem of patients with relapsing remitting multiple sclerosis.

Fractal analysis of INSAR and correlation with graph-cut based image registration for coastline deformation analysis: post seismic hazard assessment of the 2011 Tohoku earthquake region

NASA Astrophysics Data System (ADS)

Dutta, P. K.; Mishra, O. P.

2012-04-01

Satellite imagery for 2011 earthquake off the Pacific coast of Tohoku has provided an opportunity to conduct image transformation analyses by employing multi-temporal images retrieval techniques. In this study, we used a new image segmentation algorithm to image coastline deformation by adopting graph cut energy minimization framework. Comprehensive analysis of available INSAR images using coastline deformation analysis helped extract disaster information of the affected region of the 2011 Tohoku tsunamigenic earthquake source zone. We attempted to correlate fractal analysis of seismic clustering behavior with image processing analogies and our observations suggest that increase in fractal dimension distribution is associated with clustering of events that may determine the level of devastation of the region. The implementation of graph cut based image registration technique helps us to detect the devastation across the coastline of Tohoku through change of intensity of pixels that carries out regional segmentation for the change in coastal boundary after the tsunami. The study applies transformation parameters on remotely sensed images by manually segmenting the image to recovering translation parameter from two images that differ by rotation. Based on the satellite image analysis through image segmentation, it is found that the area of 0.997 sq km for the Honshu region was a maximum damage zone localized in the coastal belt of NE Japan forearc region. The analysis helps infer using matlab that the proposed graph cut algorithm is robust and more accurate than other image registration methods. The analysis shows that the method can give a realistic estimate for recovered deformation fields in pixels corresponding to coastline change which may help formulate the strategy for assessment during post disaster need assessment scenario for the coastal belts associated with damages due to strong shaking and tsunamis in the world under disaster risk mitigation programs.

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading.

PubMed

Xie, Tian; Chen, Xiao; Fang, Jingqin; Kang, Houyi; Xue, Wei; Tong, Haipeng; Cao, Peng; Wang, Sumei; Yang, Yizeng; Zhang, Weiguo

2018-04-01

Presurgical glioma grading by dynamic contrast-enhanced MRI (DCE-MRI) has unresolved issues. The aim of this study was to investigate the ability of textural features derived from pharmacokinetic model-based or model-free parameter maps of DCE-MRI in discriminating between different grades of gliomas, and their correlation with pathological index. Retrospective. Forty-two adults with brain gliomas. 3.0T, including conventional anatomic sequences and DCE-MRI sequences (variable flip angle T1-weighted imaging and three-dimensional gradient echo volumetric imaging). Regions of interest on the cross-sectional images with maximal tumor lesion. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inverse Difference Moment (IDM), were generated. All textural features of model-free parameters (initial area under curve [IAUC], maximal signal intensity [Max SI], maximal up-slope [Max Slope]) could effectively differentiate between grade II (n = 15), grade III (n = 13), and grade IV (n = 14) gliomas (P < 0.05). Two textural features, Entropy and IDM, of four DCE-MRI parameters, including Max SI, Max Slope (model-free parameters), vp (Extended Tofts), and vp (Patlak) could differentiate grade III and IV gliomas (P < 0.01) in four measurements. Both Entropy and IDM of Patlak-based K trans and vp could differentiate grade II (n = 15) from III (n = 13) gliomas (P < 0.01) in four measurements. No textural features of any DCE-MRI parameter maps could discriminate between subtypes of grade II and III gliomas (P < 0.05). Both Entropy and IDM of Extended Tofts- and Patlak-based vp showed highest area under curve in discriminating between grade III and IV gliomas. However, intraclass correlation coefficient (ICC) of these features revealed relatively lower inter-observer agreement. No significant correlation was found between microvascular density and textural features, compared with a moderate correlation found between cellular proliferation index and those features. Textural features of DCE-MRI parameter maps displayed a good ability in glioma grading. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1099-1111. © 2017 International Society for Magnetic Resonance in Medicine.

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

NASA Technical Reports Server (NTRS)

Lin, Qian; Allebach, Jan P.

1990-01-01

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

Two-dimensional compression of surface electromyographic signals using column-correlation sorting and image encoders.

PubMed

Costa, Marcus V C; Carvalho, Joao L A; Berger, Pedro A; Zaghetto, Alexandre; da Rocha, Adson F; Nascimento, Francisco A O

2009-01-01

We present a new preprocessing technique for two-dimensional compression of surface electromyographic (S-EMG) signals, based on correlation sorting. We show that the JPEG2000 coding system (originally designed for compression of still images) and the H.264/AVC encoder (video compression algorithm operating in intraframe mode) can be used for compression of S-EMG signals. We compare the performance of these two off-the-shelf image compression algorithms for S-EMG compression, with and without the proposed preprocessing step. Compression of both isotonic and isometric contraction S-EMG signals is evaluated. The proposed methods were compared with other S-EMG compression algorithms from the literature.

Deep learning for staging liver fibrosis on CT: a pilot study.

PubMed

Yasaka, Koichiro; Akai, Hiroyuki; Kunimatsu, Akira; Abe, Osamu; Kiryu, Shigeru

2018-05-14

To investigate whether liver fibrosis can be staged by deep learning techniques based on CT images. This clinical retrospective study, approved by our institutional review board, included 496 CT examinations of 286 patients who underwent dynamic contrast-enhanced CT for evaluations of the liver and for whom histopathological information regarding liver fibrosis stage was available. The 396 portal phase images with age and sex data of patients (F0/F1/F2/F3/F4 = 113/36/56/66/125) were used for training a deep convolutional neural network (DCNN); the data for the other 100 (F0/F1/F2/F3/F4 = 29/9/14/16/32) were utilised for testing the trained network, with the histopathological fibrosis stage used as reference. To improve robustness, additional images for training data were generated by rotating or parallel shifting the images, or adding Gaussian noise. Supervised training was used to minimise the difference between the liver fibrosis stage and the fibrosis score obtained from deep learning based on CT images (F DLCT score) output by the model. Testing data were input into the trained DCNNs to evaluate their performance. The F DLCT scores showed a significant correlation with liver fibrosis stage (Spearman's correlation coefficient = 0.48, p < 0.001). The areas under the receiver operating characteristic curves (with 95% confidence intervals) for diagnosing significant fibrosis (≥ F2), advanced fibrosis (≥ F3) and cirrhosis (F4) by using F DLCT scores were 0.74 (0.64-0.85), 0.76 (0.66-0.85) and 0.73 (0.62-0.84), respectively. Liver fibrosis can be staged by using a deep learning model based on CT images, with moderate performance. • Liver fibrosis can be staged by a deep learning model based on magnified CT images including the liver surface, with moderate performance. • Scores from a trained deep learning model showed moderate correlation with histopathological liver fibrosis staging. • Further improvement are necessary before utilisation in clinical settings.

A beam hardening and dispersion correction for x-ray dark-field radiography.

PubMed

Pelzer, Georg; Anton, Gisela; Horn, Florian; Rieger, Jens; Ritter, André; Wandner, Johannes; Weber, Thomas; Michel, Thilo

2016-06-01

X-ray dark-field imaging promises information on the small angle scattering properties even of large samples. However, the dark-field image is correlated with the object's attenuation and phase-shift if a polychromatic x-ray spectrum is used. A method to remove part of these correlations is proposed. The experimental setup for image acquisition was modeled in a wave-field simulation to quantify the dark-field signals originating solely from a material's attenuation and phase-shift. A calibration matrix was simulated for ICRU46 breast tissue. Using the simulated data, a dark-field image of a human mastectomy sample was corrected for the finger print of attenuation- and phase-image. Comparing the simulated, attenuation-based dark-field values to a phantom measurement, a good agreement was found. Applying the proposed method to mammographic dark-field data, a reduction of the dark-field background and anatomical noise was achieved. The contrast between microcalcifications and their surrounding background was increased. The authors show that the influence of and dispersion can be quantified by simulation and, thus, measured image data can be corrected. The simulation allows to determine the corresponding dark-field artifacts for a wide range of setup parameters, like tube-voltage and filtration. The application of the proposed method to mammographic dark-field data shows an increase in contrast compared to the original image, which might simplify a further image-based diagnosis.

Diffusion processes in tumors: A nuclear medicine approach

NASA Astrophysics Data System (ADS)

Amaya, Helman

2016-07-01

The number of counts used in nuclear medicine imaging techniques, only provides physical information about the desintegration of the nucleus present in the the radiotracer molecules that were uptaken in a particular anatomical region, but that information is not a real metabolic information. For this reason a mathematical method was used to find a correlation between number of counts and 18F-FDG mass concentration. This correlation allows a better interpretation of the results obtained in the study of diffusive processes in an agar phantom, and based on it, an image from the PETCETIX DICOM sample image set from OsiriX-viewer software was processed. PET-CT gradient magnitude and Laplacian images could show direct information on diffusive processes for radiopharmaceuticals that enter into the cells by simple diffusion. In the case of the radiopharmaceutical 18F-FDG is necessary to include pharmacokinetic models, to make a correct interpretation of the gradient magnitude and Laplacian of counts images.

In-flight measurements of aircraft propeller deformation by means of an autarkic fast rotating imaging system

NASA Astrophysics Data System (ADS)

Stasicki, Boleslaw; Boden, Fritz

2015-03-01

The non-intrusive in-flight measurement of the deformation and pitch of the aircraft propeller is a demanding task. The idea of an imaging system integrated and rotating with the aircraft propeller has been presented on the 30th International Congress on High-Speed Imaging and Photonics (ICHSIP30) in 2012. Since then this system has been constructed and tested in the laboratory as well as on the real aircraft. In this paper we outline the principle of Image Pattern Correlation Technique (IPCT) based on Digital Image Correlation (DIC) and describe the construction of a dedicated autarkic 3D camera system placed on the investigated propeller and rotating at its full speed. Furthermore, the results of the first ground and in-flight tests are shown and discussed. This development has been found by the European Commission within the 7th frame project AIM2 (contract no. 266107).

Damage estimation of sewer pipe using subtitles of CCTV inspection video

NASA Astrophysics Data System (ADS)

Park, Kitae; Kim, Byeongcheol; Kim, Taeheon; Seo, Dongwoo

2017-04-01

Recent frequent occurrence of urban sinkhole serves as a momentum of the periodic inspection of sewer pipelines. Sewer inspection using a CCTV device needs a lot of time and efforts. Many of previous studies which reduce the laborious tasks are mainly interested in the developments of image processing S/W and exploring H/W. And there has been no attempt to find meaningful information from the existing CCTV images stored by the sewer maintenance manager. This study adopts a cross-correlation based image processing method and extracts sewer inspection device's location data from CCTV images. As a result of the analysis of location-time relation, it show strong correlation between device stand time and the sewer damages. In case of using this method to investigate sewer inspection CCTV images, it will save the investigator's efforts and improve sewer maintenance efficiency and reliability.

Brain tumor segmentation with Vander Lugt correlator based active contour.

PubMed

Essadike, Abdelaziz; Ouabida, Elhoussaine; Bouzid, Abdenbi

2018-07-01

The manual segmentation of brain tumors from medical images is an error-prone, sensitive, and time-absorbing process. This paper presents an automatic and fast method of brain tumor segmentation. In the proposed method, a numerical simulation of the optical Vander Lugt correlator is used for automatically detecting the abnormal tissue region. The tumor filter, used in the simulated optical correlation, is tailored to all the brain tumor types and especially to the Glioblastoma, which considered to be the most aggressive cancer. The simulated optical correlation, computed between Magnetic Resonance Images (MRI) and this filter, estimates precisely and automatically the initial contour inside the tumorous tissue. Further, in the segmentation part, the detected initial contour is used to define an active contour model and presenting the problematic as an energy minimization problem. As a result, this initial contour assists the algorithm to evolve an active contour model towards the exact tumor boundaries. Equally important, for a comparison purposes, we considered different active contour models and investigated their impact on the performance of the segmentation task. Several images from BRATS database with tumors anywhere in images and having different sizes, contrast, and shape, are used to test the proposed system. Furthermore, several performance metrics are computed to present an aggregate overview of the proposed method advantages. The proposed method achieves a high accuracy in detecting the tumorous tissue by a parameter returned by the simulated optical correlation. In addition, the proposed method yields better performance compared to the active contour based methods with the averages of Sensitivity=0.9733, Dice coefficient = 0.9663, Hausdroff distance = 2.6540, Specificity = 0.9994, and faster with a computational time average of 0.4119 s per image. Results reported on BRATS database reveal that our proposed system improves over the recently published state-of-the-art methods in brain tumor detection and segmentation. Copyright © 2018 Elsevier B.V. All rights reserved.

Structural brain alterations in primary open angle glaucoma: a 3T MRI study

PubMed Central

Wang, Jieqiong; Li, Ting; Sabel, Bernhard A.; Chen, Zhiqiang; Wen, Hongwei; Li, Jianhong; Xie, Xiaobin; Yang, Diya; Chen, Weiwei; Wang, Ningli; Xian, Junfang; He, Huiguang

2016-01-01

Glaucoma is not only an eye disease but is also associated with degeneration of brain structures. We now investigated the pattern of visual and non-visual brain structural changes in 25 primary open angle glaucoma (POAG) patients and 25 age-gender-matched normal controls using T1-weighted imaging. MRI images were subjected to volume-based analysis (VBA) and surface-based analysis (SBA) in the whole brain as well as ROI-based analysis of the lateral geniculate nucleus (LGN), visual cortex (V1/2), amygdala and hippocampus. While VBA showed no significant differences in the gray matter volumes of patients, SBA revealed significantly reduced cortical thickness in the right frontal pole and ROI-based analysis volume shrinkage in LGN bilaterally, right V1 and left amygdala. Structural abnormalities were correlated with clinical parameters in a subset of the patients revealing that the left LGN volume was negatively correlated with bilateral cup-to-disk ratio (CDR), the right LGN volume was positively correlated with the mean deviation of the right visual hemifield, and the right V1 cortical thickness was negatively correlated with the right CDR in glaucoma. These results demonstrate that POAG affects both vision-related structures and non-visual cortical regions. Moreover, alterations of the brain visual structures reflect the clinical severity of glaucoma. PMID:26743811

DOE Office of Scientific and Technical Information (OSTI.GOV)

Galavis, P; Friedman, K; Chandarana, H

Purpose: Radiomics involves the extraction of texture features from different imaging modalities with the purpose of developing models to predict patient treatment outcomes. The purpose of this study is to investigate texture feature reproducibility across [18F]FDG PET/CT and [18F]FDG PET/MR imaging in patients with primary malignancies. Methods: Twenty five prospective patients with solid tumors underwent clinical [18F]FDG PET/CT scan followed by [18F]FDG PET/MR scans. In all patients the lesions were identified using nuclear medicine reports. The images were co-registered and segmented using an in-house auto-segmentation method. Fifty features, based on the intensity histogram, second and high order matrices, were extractedmore » from the segmented regions from both image data sets. One-way random-effects ANOVA model of the intra-class correlation coefficient (ICC) was used to establish texture feature correlations between both data sets. Results: Fifty features were classified based on their ICC values, which were found in the range from 0.1 to 0.86, in three categories: high, intermediate, and low. Ten features extracted from second and high-order matrices showed large ICC ≥ 0.70. Seventeen features presented intermediate 0.5 ≤ ICC ≤ 0.65 and the remaining twenty three presented low ICC ≤ 0.45. Conclusion: Features with large ICC values could be reliable candidates for quantification as they lead to similar results from both imaging modalities. Features with small ICC indicates a lack of correlation. Therefore, the use of these features as a quantitative measure will lead to different assessments of the same lesion depending on the imaging modality from where they are extracted. This study shows the importance of the need for further investigation and standardization of features across multiple imaging modalities.« less

Speckle reduction in optical coherence tomography images based on wave atoms

PubMed Central

Du, Yongzhao; Liu, Gangjun; Feng, Guoying; Chen, Zhongping

2014-01-01

Abstract. Optical coherence tomography (OCT) is an emerging noninvasive imaging technique, which is based on low-coherence interferometry. OCT images suffer from speckle noise, which reduces image contrast. A shrinkage filter based on wave atoms transform is proposed for speckle reduction in OCT images. Wave atoms transform is a new multiscale geometric analysis tool that offers sparser expansion and better representation for images containing oscillatory patterns and textures than other traditional transforms, such as wavelet and curvelet transforms. Cycle spinning-based technology is introduced to avoid visual artifacts, such as Gibbs-like phenomenon, and to develop a translation invariant wave atoms denoising scheme. The speckle suppression degree in the denoised images is controlled by an adjustable parameter that determines the threshold in the wave atoms domain. The experimental results show that the proposed method can effectively remove the speckle noise and improve the OCT image quality. The signal-to-noise ratio, contrast-to-noise ratio, average equivalent number of looks, and cross-correlation (XCOR) values are obtained, and the results are also compared with the wavelet and curvelet thresholding techniques. PMID:24825507

Evaluation of a web based informatics system with data mining tools for predicting outcomes with quantitative imaging features in stroke rehabilitation clinical trials

NASA Astrophysics Data System (ADS)

Wang, Ximing; Kim, Bokkyu; Park, Ji Hoon; Wang, Erik; Forsyth, Sydney; Lim, Cody; Ravi, Ragini; Karibyan, Sarkis; Sanchez, Alexander; Liu, Brent

2017-03-01

Quantitative imaging biomarkers are used widely in clinical trials for tracking and evaluation of medical interventions. Previously, we have presented a web based informatics system utilizing quantitative imaging features for predicting outcomes in stroke rehabilitation clinical trials. The system integrates imaging features extraction tools and a web-based statistical analysis tool. The tools include a generalized linear mixed model(GLMM) that can investigate potential significance and correlation based on features extracted from clinical data and quantitative biomarkers. The imaging features extraction tools allow the user to collect imaging features and the GLMM module allows the user to select clinical data and imaging features such as stroke lesion characteristics from the database as regressors and regressands. This paper discusses the application scenario and evaluation results of the system in a stroke rehabilitation clinical trial. The system was utilized to manage clinical data and extract imaging biomarkers including stroke lesion volume, location and ventricle/brain ratio. The GLMM module was validated and the efficiency of data analysis was also evaluated.

Automatic Tracking Of Remote Sensing Precipitation Data Using Genetic Algorithm Image Registration Based Automatic Morphing: September 1999 Storm Floyd Case Study

NASA Astrophysics Data System (ADS)

Chiu, L.; Vongsaard, J.; El-Ghazawi, T.; Weinman, J.; Yang, R.; Kafatos, M.

U Due to the poor temporal sampling by satellites, data gaps exist in satellite derived time series of precipitation. This poses a challenge for assimilating rain- fall data into forecast models. To yield a continuous time series, the classic image processing technique of digital image morphing has been used. However, the digital morphing technique was applied manually and that is time consuming. In order to avoid human intervention in the process, an automatic procedure for image morphing is needed for real-time operations. For this purpose, Genetic Algorithm Based Image Registration Automatic Morphing (GRAM) model was developed and tested in this paper. Specifically, automatic morphing technique was integrated with Genetic Algo- rithm and Feature Based Image Metamorphosis technique to fill in data gaps between satellite coverage. The technique was tested using NOWRAD data which are gener- ated from the network of NEXRAD radars. Time series of NOWRAD data from storm Floyd that occurred at the US eastern region on September 16, 1999 for 00:00, 01:00, 02:00,03:00, and 04:00am were used. The GRAM technique was applied to data col- lected at 00:00 and 04:00am. These images were also manually morphed. Images at 01:00, 02:00 and 03:00am were interpolated from the GRAM and manual morphing and compared with the original NOWRAD rainrates. The results show that the GRAM technique outperforms manual morphing. The correlation coefficients between the im- ages generated using manual morphing are 0.905, 0.900, and 0.905 for the images at 01:00, 02:00,and 03:00 am, while the corresponding correlation coefficients are 0.946, 0.911, and 0.913, respectively, based on the GRAM technique. Index terms ­ Remote Sensing, Image Registration, Hydrology, Genetic Algorithm, Morphing, NEXRAD

Image correlation and sampling study

NASA Technical Reports Server (NTRS)

Popp, D. J.; Mccormack, D. S.; Sedwick, J. L.

1972-01-01

The development of analytical approaches for solving image correlation and image sampling of multispectral data is discussed. Relevant multispectral image statistics which are applicable to image correlation and sampling are identified. The general image statistics include intensity mean, variance, amplitude histogram, power spectral density function, and autocorrelation function. The translation problem associated with digital image registration and the analytical means for comparing commonly used correlation techniques are considered. General expressions for determining the reconstruction error for specific image sampling strategies are developed.

Theoretical scheme of thermal-light many-ghost imaging by Nth-order intensity correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu Yingchuan; College of Mathematics and Physics, University of South China, Hengyang 421001; Kuang Leman

2011-05-15

In this paper, we propose a theoretical scheme of many-ghost imaging in terms of Nth-order correlated thermal light. We obtain the Gaussian thin lens equations in the many-ghost imaging protocol. We show that it is possible to produce N-1 ghost images of an object at different places in a nonlocal fashion by means of a higher order correlated imaging process with an Nth-order correlated thermal source and correlation measurements. We investigate the visibility of the ghost images in the scheme and obtain the upper bounds of the visibility for the Nth-order correlated thermal-light ghost imaging. It is found that themore » visibility of the ghost images can be dramatically enhanced when the order of correlation becomes larger. It is pointed out that the many-ghost imaging phenomenon is an observable physical effect induced by higher order coherence or higher order correlations of optical fields.« less

Optical multiple-image authentication based on cascaded phase filtering structure

NASA Astrophysics Data System (ADS)

Wang, Q.; Alfalou, A.; Brosseau, C.

2016-10-01

In this study, we report on the recent developments of optical image authentication algorithms. Compared with conventional optical encryption, optical image authentication achieves more security strength because such methods do not need to recover information of plaintext totally during the decryption period. Several recently proposed authentication systems are briefly introduced. We also propose a novel multiple-image authentication system, where multiple original images are encoded into a photon-limited encoded image by using a triple-plane based phase retrieval algorithm and photon counting imaging (PCI) technique. One can only recover a noise-like image using correct keys. To check authority of multiple images, a nonlinear fractional correlation is employed to recognize the original information hidden in the decrypted results. The proposal can be implemented optically using a cascaded phase filtering configuration. Computer simulation results are presented to evaluate the performance of this proposal and its effectiveness.

Digital image measurement of specimen deformation based on CCD cameras and Image J software: an application to human pelvic biomechanics

NASA Astrophysics Data System (ADS)

Jia, Yongwei; Cheng, Liming; Yu, Guangrong; Lou, Yongjian; Yu, Yan; Chen, Bo; Ding, Zuquan

2008-03-01

A method of digital image measurement of specimen deformation based on CCD cameras and Image J software was developed. This method was used to measure the biomechanics behavior of human pelvis. Six cadaveric specimens from the third lumbar vertebra to the proximal 1/3 part of femur were tested. The specimens without any structural abnormalities were dissected of all soft tissue, sparing the hip joint capsules and the ligaments of the pelvic ring and floor. Markers with black dot on white background were affixed to the key regions of the pelvis. Axial loading from the proximal lumbar was applied by MTS in the gradient of 0N to 500N, which simulated the double feet standing stance. The anterior and lateral images of the specimen were obtained through two CCD cameras. Based on Image J software, digital image processing software, which can be freely downloaded from the National Institutes of Health, digital 8-bit images were processed. The procedure includes the recognition of digital marker, image invert, sub-pixel reconstruction, image segmentation, center of mass algorithm based on weighted average of pixel gray values. Vertical displacements of S1 (the first sacral vertebrae) in front view and micro-angular rotation of sacroiliac joint in lateral view were calculated according to the marker movement. The results of digital image measurement showed as following: marker image correlation before and after deformation was excellent. The average correlation coefficient was about 0.983. According to the 768 × 576 pixels image (pixel size 0.68mm × 0.68mm), the precision of the displacement detected in our experiment was about 0.018 pixels and the comparatively error could achieve 1.11\\perthou. The average vertical displacement of S1 of the pelvis was 0.8356+/-0.2830mm under vertical load of 500 Newtons and the average micro-angular rotation of sacroiliac joint in lateral view was 0.584+/-0.221°. The load-displacement curves obtained from our optical measure system matched the clinical results. Digital image measurement of specimen deformation based on CCD cameras and Image J software has good perspective for application in biomechanical research, which has the advantage of simple optical setup, no-contact, high precision, and no special requirement of test environment.

Illumination-tolerant face verification of low-bit-rate JPEG2000 wavelet images with advanced correlation filters for handheld devices

NASA Astrophysics Data System (ADS)

Wijaya, Surya Li; Savvides, Marios; Vijaya Kumar, B. V. K.

2005-02-01

Face recognition on mobile devices, such as personal digital assistants and cell phones, is a big challenge owing to the limited computational resources available to run verifications on the devices themselves. One approach is to transmit the captured face images by use of the cell-phone connection and to run the verification on a remote station. However, owing to limitations in communication bandwidth, it may be necessary to transmit a compressed version of the image. We propose using the image compression standard JPEG2000, which is a wavelet-based compression engine used to compress the face images to low bit rates suitable for transmission over low-bandwidth communication channels. At the receiver end, the face images are reconstructed with a JPEG2000 decoder and are fed into the verification engine. We explore how advanced correlation filters, such as the minimum average correlation energy filter [Appl. Opt. 26, 3633 (1987)] and its variants, perform by using face images captured under different illumination conditions and encoded with different bit rates under the JPEG2000 wavelet-encoding standard. We evaluate the performance of these filters by using illumination variations from the Carnegie Mellon University's Pose, Illumination, and Expression (PIE) face database. We also demonstrate the tolerance of these filters to noisy versions of images with illumination variations.

Cotton growth modeling and assessment using unmanned aircraft system visual-band imagery

NASA Astrophysics Data System (ADS)

Chu, Tianxing; Chen, Ruizhi; Landivar, Juan A.; Maeda, Murilo M.; Yang, Chenghai; Starek, Michael J.

2016-07-01

This paper explores the potential of using unmanned aircraft system (UAS)-based visible-band images to assess cotton growth. By applying the structure-from-motion algorithm, the cotton plant height (ph) and canopy cover (cc) information were retrieved from the point cloud-based digital surface models (DSMs) and orthomosaic images. Both UAS-based ph and cc follow a sigmoid growth pattern as confirmed by ground-based studies. By applying an empirical model that converts the cotton ph to cc, the estimated cc shows strong correlation (R2=0.990) with the observed cc. An attempt for modeling cotton yield was carried out using the ph and cc information obtained on June 26, 2015, the date when sigmoid growth curves for both ph and cc tended to decline in slope. In a cross-validation test, the correlation between the ground-measured yield and the estimated equivalent derived from the ph and/or cc was compared. Generally, combining ph and cc, the performance of the yield estimation is most comparable against the observed yield. On the other hand, the observed yield and cc-based estimation produce the second strongest correlation, regardless of the complexity of the models.

Cerebral morphology and dopamine D2/D3receptor distribution in humans: A combined [18F]fallypride and voxel-based morphometry study

PubMed Central

Woodward, Neil D.; Zald, David H.; Ding, Zhaohua; Riccardi, Patrizia; Ansari, M. Sib; Baldwin, Ronald M.; Cowan, Ronald L.; Li, Rui; Kessler, Robert M.

2009-01-01

The relationship between cerebral morphology and the expression of dopamine receptors has not been extensively studied in humans. Elucidation of such relationships may have important methodological implications for clinical studies of dopamine receptor ligand binding differences between control and patient groups. The association between cerebral morphology and dopamine receptor distribution was examined in 45 healthy subjects who completed T1-weighted structural MRI and PET scanning with the D2/D3 ligand [18F]fallypride. Optimized voxel-based morphometry was used to create grey matter volume and density images. Grey matter volume and density images were correlated with binding potential (BPND) images on a voxel-by-voxel basis using the Biological Parametric Mapping toolbox. Associations between cerebral morphology and BPND were also examined for selected regions-of-interest (ROIs) after spatial normalization. Voxel-wise analyses indicated that grey matter volume and density positively correlated with BPND throughout the midbrain, including the substantia nigra. Positive correlations were observed in medial cortical areas, including anterior cingulate and medial prefrontal cortex, and circumscribed regions of the temporal, frontal, and parietal lobes. ROI analyses revealed significant positive correlations between BPND and cerebral morphology in the caudate, thalamus, and amygdala. Few negative correlations between morphology and BPND were observed. Overall, grey matter density appeared more strongly correlated with BPND than grey matter volume. Cerebral morphology, particularly grey matter density, correlates with [18F]fallypride BPND in a regionally specific manner. Clinical studies comparing dopamine receptor availability between clinical and control groups may benefit by accounting for potential differences in cerebral morphology that exist even after spatial normalization. PMID:19457373

Cerebral morphology and dopamine D2/D3 receptor distribution in humans: a combined [18F]fallypride and voxel-based morphometry study.

PubMed

Woodward, Neil D; Zald, David H; Ding, Zhaohua; Riccardi, Patrizia; Ansari, M Sib; Baldwin, Ronald M; Cowan, Ronald L; Li, Rui; Kessler, Robert M

2009-05-15

The relationship between cerebral morphology and the expression of dopamine receptors has not been extensively studied in humans. Elucidation of such relationships may have important methodological implications for clinical studies of dopamine receptor ligand binding differences between control and patient groups. The association between cerebral morphology and dopamine receptor distribution was examined in 45 healthy subjects who completed T1-weighted structural MRI and PET scanning with the D(2)/D(3) ligand [(18)F]fallypride. Optimized voxel-based morphometry was used to create grey matter volume and density images. Grey matter volume and density images were correlated with binding potential (BP(ND)) images on a voxel-by-voxel basis using the Biological Parametric Mapping toolbox. Associations between cerebral morphology and BP(ND) were also examined for selected regions-of-interest (ROIs) after spatial normalization. Voxel-wise analyses indicated that grey matter volume and density positively correlated with BP(ND) throughout the midbrain, including the substantia nigra. Positive correlations were observed in medial cortical areas, including anterior cingulate and medial prefrontal cortex, and circumscribed regions of the temporal, frontal, and parietal lobes. ROI analyses revealed significant positive correlations between BP(ND) and cerebral morphology in the caudate, thalamus, and amygdala. Few negative correlations between morphology and BP(ND) were observed. Overall, grey matter density appeared more strongly correlated with BP(ND) than grey matter volume. Cerebral morphology, particularly grey matter density, correlates with [(18)F]fallypride BP(ND) in a regionally specific manner. Clinical studies comparing dopamine receptor availability between clinical and control groups may benefit by accounting for potential differences in cerebral morphology that exist even after spatial normalization.

Extraction and labeling high-resolution images from PDF documents

NASA Astrophysics Data System (ADS)

Chachra, Suchet K.; Xue, Zhiyun; Antani, Sameer; Demner-Fushman, Dina; Thoma, George R.

2013-12-01

Accuracy of content-based image retrieval is affected by image resolution among other factors. Higher resolution images enable extraction of image features that more accurately represent the image content. In order to improve the relevance of search results for our biomedical image search engine, Open-I, we have developed techniques to extract and label high-resolution versions of figures from biomedical articles supplied in the PDF format. Open-I uses the open-access subset of biomedical articles from the PubMed Central repository hosted by the National Library of Medicine. Articles are available in XML and in publisher supplied PDF formats. As these PDF documents contain little or no meta-data to identify the embedded images, the task includes labeling images according to their figure number in the article after they have been successfully extracted. For this purpose we use the labeled small size images provided with the XML web version of the article. This paper describes the image extraction process and two alternative approaches to perform image labeling that measure the similarity between two images based upon the image intensity projection on the coordinate axes and similarity based upon the normalized cross-correlation between the intensities of two images. Using image identification based on image intensity projection, we were able to achieve a precision of 92.84% and a recall of 82.18% in labeling of the extracted images.

SU-E-J-132: Automated Segmentation with Post-Registration Atlas Selection Based On Mutual Information

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, X; Gao, H; Sharp, G

2015-06-15

Purpose: The delineation of targets and organs-at-risk is a critical step during image-guided radiation therapy, for which manual contouring is the gold standard. However, it is often time-consuming and may suffer from intra- and inter-rater variability. The purpose of this work is to investigate the automated segmentation. Methods: The automatic segmentation here is based on mutual information (MI), with the atlas from Public Domain Database for Computational Anatomy (PDDCA) with manually drawn contours.Using dice coefficient (DC) as the quantitative measure of segmentation accuracy, we perform leave-one-out cross-validations for all PDDCA images sequentially, during which other images are registered to eachmore » chosen image and DC is computed between registered contour and ground truth. Meanwhile, six strategies, including MI, are selected to measure the image similarity, with MI to be the best. Then given a target image to be segmented and an atlas, automatic segmentation consists of: (a) the affine registration step for image positioning; (b) the active demons registration method to register the atlas to the target image; (c) the computation of MI values between the deformed atlas and the target image; (d) the weighted image fusion of three deformed atlas images with highest MI values to form the segmented contour. Results: MI was found to be the best among six studied strategies in the sense that it had the highest positive correlation between similarity measure (e.g., MI values) and DC. For automated segmentation, the weighted image fusion of three deformed atlas images with highest MI values provided the highest DC among four proposed strategies. Conclusion: MI has the highest correlation with DC, and therefore is an appropriate choice for post-registration atlas selection in atlas-based segmentation. Xuhua Ren and Hao Gao were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)« less

An improved image alignment procedure for high-resolution transmission electron microscopy.

PubMed

Lin, Fang; Liu, Yan; Zhong, Xiaoyan; Chen, Jianghua

2010-06-01

Image alignment is essential for image processing methods such as through-focus exit-wavefunction reconstruction and image averaging in high-resolution transmission electron microscopy. Relative image displacements exist in any experimentally recorded image series due to the specimen drifts and image shifts, hence image alignment for correcting the image displacements has to be done prior to any further image processing. The image displacement between two successive images is determined by the correlation function of the two relatively shifted images. Here it is shown that more accurate image alignment can be achieved by using an appropriate aperture to filter the high-frequency components of the images being aligned, especially for a crystalline specimen with little non-periodic information. For the image series of crystalline specimens with little amorphous, the radius of the filter aperture should be as small as possible, so long as it covers the innermost lattice reflections. Testing with an experimental through-focus series of Si[110] images, the accuracies of image alignment with different correlation functions are compared with respect to the error functions in through-focus exit-wavefunction reconstruction based on the maximum-likelihood method. Testing with image averaging over noisy experimental images from graphene and carbon-nanotube samples, clear and sharp crystal lattice fringes are recovered after applying optimal image alignment. Copyright 2010 Elsevier Ltd. All rights reserved.

Single-image super-resolution based on Markov random field and contourlet transform

NASA Astrophysics Data System (ADS)

Wu, Wei; Liu, Zheng; Gueaieb, Wail; He, Xiaohai

2011-04-01

Learning-based methods are well adopted in image super-resolution. In this paper, we propose a new learning-based approach using contourlet transform and Markov random field. The proposed algorithm employs contourlet transform rather than the conventional wavelet to represent image features and takes into account the correlation between adjacent pixels or image patches through the Markov random field (MRF) model. The input low-resolution (LR) image is decomposed with the contourlet transform and fed to the MRF model together with the contourlet transform coefficients from the low- and high-resolution image pairs in the training set. The unknown high-frequency components/coefficients for the input low-resolution image are inferred by a belief propagation algorithm. Finally, the inverse contourlet transform converts the LR input and the inferred high-frequency coefficients into the super-resolved image. The effectiveness of the proposed method is demonstrated with the experiments on facial, vehicle plate, and real scene images. A better visual quality is achieved in terms of peak signal to noise ratio and the image structural similarity measurement.

Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions.

PubMed

Robson, Philip M; Grant, Aaron K; Madhuranthakam, Ananth J; Lattanzi, Riccardo; Sodickson, Daniel K; McKenzie, Charles A

2008-10-01

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g-factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal-to-noise ratio and g-factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple "prescan" measurement of noise amplitude and correlation in the phased-array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal-to-noise ratio and g-factor. The "pseudo multiple replica" method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel-by-pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k-space trajectories, image reconstruction, or noise conditioning techniques. (c) 2008 Wiley-Liss, Inc.

Voxel-based morphometry findings in Alzheimer's disease: neuropsychiatric symptoms and disability correlations - preliminary results.

PubMed

Vasconcelos, Luciano de Gois; Jackowski, Andrea Parolin; Oliveira, Maira Okada de; Flor, Yoná Mayara Ribeiro; Bueno, Orlando Francisco Amodeo; Brucki, Sonia Maria Dozzi

2011-01-01

The role of structural brain changes and their correlations with neuropsychiatric symptoms and disability in Alzheimer's disease are still poorly understood. To establish whether structural changes in grey matter volume in patients with mild Alzheimer's disease are associated with neuropsychiatric symptoms and disability Nineteen Alzheimer's disease patients (9 females; total mean age =75.2 y old +4.7; total mean education level =8.5 y +4.9) underwent a magnetic resonance imaging (MRI) examination and voxel-based morphometry analysis. T1-weighted images were spatially normalized and segmented. Grey matter images were smoothed and analyzed using a multiple regression design. The results were corrected for multiple comparisons. The Neuropsychiatric Inventory was used to evaluate the neuropsychiatric symptoms, and the Functional Activities Questionnaire and Disability Assessment for Dementia were used for functional evaluation A significant negative correlation was found between the bilateral middle frontal gyri, left inferior temporal gyrus, right orbitofrontal gyrus, and Neuropsychiatric Inventory scores. A negative correlation was found between bilateral middle temporal gyri, left hippocampus, bilateral fusiform gyri, and the Functional Activities Questionnaire. There was a positive correlation between the right amygdala, bilateral fusiform gyri, right anterior insula, left inferior and middle temporal gyri, right superior temporal gyrus, and Disability Assessment for Dementia scores The results suggest that the neuropsychiatric symptoms observed in Alzheimer's disease patients could be mainly due to frontal structural abnormalities, whereas disability could be associated with reductions in temporal structures.

Estimation of Error in Maximal Intensity Projection-Based Internal Target Volume of Lung Tumors: A Simulation and Comparison Study Using Dynamic Magnetic Resonance Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai Jing; Read, Paul W.; Baisden, Joseph M.

Purpose: To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Methods and Materials: Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA)more » from RedCAM ({epsilon}), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability ({nu}). Results: Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies ({epsilon} = -21.64% {+-} 8.23%) and lung tumor patient studies ({epsilon} = -20.31% {+-} 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly ({epsilon} = -5.13{nu} - 6.71, r{sup 2} = 0.76) with the subjects' respiratory variability. Conclusions: Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.« less

Estimation of error in maximal intensity projection-based internal target volume of lung tumors: a simulation and comparison study using dynamic magnetic resonance imaging.

PubMed

Cai, Jing; Read, Paul W; Baisden, Joseph M; Larner, James M; Benedict, Stanley H; Sheng, Ke

2007-11-01

To evaluate the error in four-dimensional computed tomography (4D-CT) maximal intensity projection (MIP)-based lung tumor internal target volume determination using a simulation method based on dynamic magnetic resonance imaging (dMRI). Eight healthy volunteers and six lung tumor patients underwent a 5-min MRI scan in the sagittal plane to acquire dynamic images of lung motion. A MATLAB program was written to generate re-sorted dMRI using 4D-CT acquisition methods (RedCAM) by segmenting and rebinning the MRI scans. The maximal intensity projection images were generated from RedCAM and dMRI, and the errors in the MIP-based internal target area (ITA) from RedCAM (epsilon), compared with those from dMRI, were determined and correlated with the subjects' respiratory variability (nu). Maximal intensity projection-based ITAs from RedCAM were comparatively smaller than those from dMRI in both phantom studies (epsilon = -21.64% +/- 8.23%) and lung tumor patient studies (epsilon = -20.31% +/- 11.36%). The errors in MIP-based ITA from RedCAM correlated linearly (epsilon = -5.13nu - 6.71, r(2) = 0.76) with the subjects' respiratory variability. Because of the low temporal resolution and retrospective re-sorting, 4D-CT might not accurately depict the excursion of a moving tumor. Using a 4D-CT MIP image to define the internal target volume might therefore cause underdosing and an increased risk of subsequent treatment failure. Patient-specific respiratory variability might also be a useful predictor of the 4D-CT-induced error in MIP-based internal target volume determination.

Nanoparticle discrimination based on wavelength and lifetime-multiplexed cathodoluminescence microscopy.

PubMed

Garming, Mathijs W H; Weppelman, I Gerward C; de Boer, Pascal; Martínez, Felipe Perona; Schirhagl, Romana; Hoogenboom, Jacob P; Moerland, Robert J

2017-08-31

Nanomaterials can be identified in high-resolution electron microscopy images using spectrally-selective cathodoluminescence. Capabilities for multiplex detection can however be limited, e.g., due to spectral overlap or availability of filters. Also, the available photon flux may be limited due to degradation under electron irradiation. Here, we demonstrate single-pass cathodoluminescence-lifetime based discrimination of different nanoparticles, using a pulsed electron beam. We also show that cathodoluminescence lifetime is a robust parameter even when the nanoparticle cathodoluminescence intensity decays over an order of magnitude. We create lifetime maps, where the lifetime of the cathodoluminescence emission is correlated with the emission intensity and secondary-electron images. The consistency of lifetime-based discrimination is verified by also correlating the emission wavelength and the lifetime of nanoparticles. Our results show how cathodoluminescence lifetime provides an additional channel of information in electron microscopy.

Automated brain tumor segmentation in magnetic resonance imaging based on sliding-window technique and symmetry analysis.

PubMed

Lian, Yanyun; Song, Zhijian

2014-01-01

Brain tumor segmentation from magnetic resonance imaging (MRI) is an important step toward surgical planning, treatment planning, monitoring of therapy. However, manual tumor segmentation commonly used in clinic is time-consuming and challenging, and none of the existed automated methods are highly robust, reliable and efficient in clinic application. An accurate and automated tumor segmentation method has been developed for brain tumor segmentation that will provide reproducible and objective results close to manual segmentation results. Based on the symmetry of human brain, we employed sliding-window technique and correlation coefficient to locate the tumor position. At first, the image to be segmented was normalized, rotated, denoised, and bisected. Subsequently, through vertical and horizontal sliding-windows technique in turn, that is, two windows in the left and the right part of brain image moving simultaneously pixel by pixel in two parts of brain image, along with calculating of correlation coefficient of two windows, two windows with minimal correlation coefficient were obtained, and the window with bigger average gray value is the location of tumor and the pixel with biggest gray value is the locating point of tumor. At last, the segmentation threshold was decided by the average gray value of the pixels in the square with center at the locating point and 10 pixels of side length, and threshold segmentation and morphological operations were used to acquire the final tumor region. The method was evaluated on 3D FSPGR brain MR images of 10 patients. As a result, the average ratio of correct location was 93.4% for 575 slices containing tumor, the average Dice similarity coefficient was 0.77 for one scan, and the average time spent on one scan was 40 seconds. An fully automated, simple and efficient segmentation method for brain tumor is proposed and promising for future clinic use. Correlation coefficient is a new and effective feature for tumor location.

Entangled-photon coincidence fluorescence imaging

PubMed Central

Scarcelli, Giuliano; Yun, Seok H.

2009-01-01

We describe fluorescence imaging using the second-order correlation of entangled photon pairs. The proposed method is based on the principle that one photon of the pair carries information on where the other photon has been absorbed and has produced fluorescence in a sample. Because fluorescent molecules serve as “detectors” breaking the entanglement, multiply-scattered fluorescence photons within the sample do not cause image blur. We discuss experimental implementations. PMID:18825257

Distributed Kernelized Locality-Sensitive Hashing for Faster Image Based Navigation

DTIC Science & Technology

2015-03-26

Facebook, Google, and Yahoo !. Current methods for image retrieval become problematic when implemented on image datasets that can easily reach billions of...correlations. Tech industry leaders like Facebook, Google, and Yahoo ! sort and index even larger volumes of “big data” daily. When attempting to process...open source implementation of Google’s MapReduce programming paradigm [13] which has been used for many different things. Using Apache Hadoop, Yahoo

Evaluation of Interpolation Effects on Upsampling and Accuracy of Cost Functions-Based Optimized Automatic Image Registration

PubMed Central

Mahmoudzadeh, Amir Pasha; Kashou, Nasser H.

2013-01-01

Interpolation has become a default operation in image processing and medical imaging and is one of the important factors in the success of an intensity-based registration method. Interpolation is needed if the fractional unit of motion is not matched and located on the high resolution (HR) grid. The purpose of this work is to present a systematic evaluation of eight standard interpolation techniques (trilinear, nearest neighbor, cubic Lagrangian, quintic Lagrangian, hepatic Lagrangian, windowed Sinc, B-spline 3rd order, and B-spline 4th order) and to compare the effect of cost functions (least squares (LS), normalized mutual information (NMI), normalized cross correlation (NCC), and correlation ratio (CR)) for optimized automatic image registration (OAIR) on 3D spoiled gradient recalled (SPGR) magnetic resonance images (MRI) of the brain acquired using a 3T GE MR scanner. Subsampling was performed in the axial, sagittal, and coronal directions to emulate three low resolution datasets. Afterwards, the low resolution datasets were upsampled using different interpolation methods, and they were then compared to the high resolution data. The mean squared error, peak signal to noise, joint entropy, and cost functions were computed for quantitative assessment of the method. Magnetic resonance image scans and joint histogram were used for qualitative assessment of the method. PMID:24000283

Evaluation of interpolation effects on upsampling and accuracy of cost functions-based optimized automatic image registration.

PubMed

Mahmoudzadeh, Amir Pasha; Kashou, Nasser H

2013-01-01

Interpolation has become a default operation in image processing and medical imaging and is one of the important factors in the success of an intensity-based registration method. Interpolation is needed if the fractional unit of motion is not matched and located on the high resolution (HR) grid. The purpose of this work is to present a systematic evaluation of eight standard interpolation techniques (trilinear, nearest neighbor, cubic Lagrangian, quintic Lagrangian, hepatic Lagrangian, windowed Sinc, B-spline 3rd order, and B-spline 4th order) and to compare the effect of cost functions (least squares (LS), normalized mutual information (NMI), normalized cross correlation (NCC), and correlation ratio (CR)) for optimized automatic image registration (OAIR) on 3D spoiled gradient recalled (SPGR) magnetic resonance images (MRI) of the brain acquired using a 3T GE MR scanner. Subsampling was performed in the axial, sagittal, and coronal directions to emulate three low resolution datasets. Afterwards, the low resolution datasets were upsampled using different interpolation methods, and they were then compared to the high resolution data. The mean squared error, peak signal to noise, joint entropy, and cost functions were computed for quantitative assessment of the method. Magnetic resonance image scans and joint histogram were used for qualitative assessment of the method.

Adaptive optics system application for solar telescope

NASA Astrophysics Data System (ADS)

Lukin, V. P.; Grigor'ev, V. M.; Antoshkin, L. V.; Botugina, N. N.; Emaleev, O. N.; Konyaev, P. A.; Kovadlo, P. G.; Krivolutskiy, N. P.; Lavrionova, L. N.; Skomorovski, V. I.

2008-07-01

The possibility of applying adaptive correction to ground-based solar astronomy is considered. Several experimental systems for image stabilization are described along with the results of their tests. Using our work along several years and world experience in solar adaptive optics (AO) we are assuming to obtain first light to the end of 2008 for the first Russian low order ANGARA solar AO system on the Big Solar Vacuum Telescope (BSVT) with 37 subapertures Shack-Hartmann wavefront sensor based of our modified correlation tracker algorithm, DALSTAR video camera, 37 elements deformable bimorph mirror, home made fast tip-tip mirror with separate correlation tracker. Too strong daytime turbulence is on the BSVT site and we are planning to obtain a partial correction for part of Sun surface image.

A procedure for testing the quality of LANDSAT atmospheric correction algorithms

NASA Technical Reports Server (NTRS)

Dias, L. A. V. (Principal Investigator); Vijaykumar, N. L.; Neto, G. C.

1982-01-01

There are two basic methods for testing the quality of an algorithm to minimize atmospheric effects on LANDSAT imagery: (1) test the results a posteriori, using ground truth or control points; (2) use a method based on image data plus estimation of additional ground and/or atmospheric parameters. A procedure based on the second method is described. In order to select the parameters, initially the image contrast is examined for a series of parameter combinations. The contrast improves for better corrections. In addition the correlation coefficient between two subimages, taken at different times, of the same scene is used for parameter's selection. The regions to be correlated should not have changed considerably in time. A few examples using this proposed procedure are presented.

FPGA design of correlation-based pattern recognition

NASA Astrophysics Data System (ADS)

Jridi, Maher; Alfalou, Ayman

2017-05-01

Optical/Digital pattern recognition and tracking based on optical/digital correlation are a well-known techniques to detect, identify and localize a target object in a scene. Despite the limited number of treatments required by the correlation scheme, computational time and resources are relatively high. The most computational intensive treatment required by the correlation is the transformation from spatial to spectral domain and then from spectral to spatial domain. Furthermore, these transformations are used on optical/digital encryption schemes like the double random phase encryption (DRPE). In this paper, we present a VLSI architecture for the correlation scheme based on the fast Fourier transform (FFT). One interesting feature of the proposed scheme is its ability to stream image processing in order to perform correlation for video sequences. A trade-off between the hardware consumption and the robustness of the correlation can be made in order to understand the limitations of the correlation implementation in reconfigurable and portable platforms. Experimental results obtained from HDL simulations and FPGA prototype have demonstrated the advantages of the proposed scheme.

An improved algorithm to reduce noise in high-order thermal ghost imaging.

PubMed

Chen, Xi-Hao; Wu, Shuang-Shuang; Wu, Wei; Guo, Wang-Yuan; Meng, Shao-Ying; Sun, Zhi-Bin; Zhai, Guang-Jie; Li, Ming-Fei; Wu, Ling-An

2014-09-01

A modified Nth-order correlation function is derived that can effectively remove the noise background encountered in high-order thermal light ghost imaging (GI). Based on this, the quality of the reconstructed images in an Nth-order lensless GI setup has been greatly enhanced compared to former high-order schemes for the same sampling number. In addition, the dependence of the visibility and signal-to-noise ratio for different high-order images on the sampling number has been measured and compared.

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

PubMed

Stankov, L

1979-07-01

The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

A Microfluidic Platform for Correlative Live-Cell and Super-Resolution Microscopy

PubMed Central

Tam, Johnny; Cordier, Guillaume Alan; Bálint, Štefan; Sandoval Álvarez, Ángel; Borbely, Joseph Steven; Lakadamyali, Melike

2014-01-01

Recently, super-resolution microscopy methods such as stochastic optical reconstruction microscopy (STORM) have enabled visualization of subcellular structures below the optical resolution limit. Due to the poor temporal resolution, however, these methods have mostly been used to image fixed cells or dynamic processes that evolve on slow time-scales. In particular, fast dynamic processes and their relationship to the underlying ultrastructure or nanoscale protein organization cannot be discerned. To overcome this limitation, we have recently developed a correlative and sequential imaging method that combines live-cell and super-resolution microscopy. This approach adds dynamic background to ultrastructural images providing a new dimension to the interpretation of super-resolution data. However, currently, it suffers from the need to carry out tedious steps of sample preparation manually. To alleviate this problem, we implemented a simple and versatile microfluidic platform that streamlines the sample preparation steps in between live-cell and super-resolution imaging. The platform is based on a microfluidic chip with parallel, miniaturized imaging chambers and an automated fluid-injection device, which delivers a precise amount of a specified reagent to the selected imaging chamber at a specific time within the experiment. We demonstrate that this system can be used for live-cell imaging, automated fixation, and immunostaining of adherent mammalian cells in situ followed by STORM imaging. We further demonstrate an application by correlating mitochondrial dynamics, morphology, and nanoscale mitochondrial protein distribution in live and super-resolution images. PMID:25545548

3D pattern of brain atrophy in HIV/AIDS visualized using tensor-based morphometry

PubMed Central

Chiang, Ming-Chang; Dutton, Rebecca A.; Hayashi, Kiralee M.; Lopez, Oscar L.; Aizenstein, Howard J.; Toga, Arthur W.; Becker, James T.; Thompson, Paul M.

2011-01-01

35% of HIV-infected patients have cognitive impairment, but the profile of HIV-induced brain damage is still not well understood. Here we used tensor-based morphometry (TBM) to visualize brain deficits and clinical/anatomical correlations in HIV/AIDS. To perform TBM, we developed a new MRI-based analysis technique that uses fluid image warping, and a new α-entropy-based information-theoretic measure of image correspondence, called the Jensen–Rényi divergence (JRD). Methods 3D T1-weighted brain MRIs of 26 AIDS patients (CDC stage C and/or 3 without HIV-associated dementia; 47.2 ± 9.8 years; 25M/1F; CD4+ T-cell count: 299.5 ± 175.7/µl; log10 plasma viral load: 2.57 ± 1.28 RNA copies/ml) and 14 HIV-seronegative controls (37.6 ± 12.2 years; 8M/6F) were fluidly registered by applying forces throughout each deforming image to maximize the JRD between it and a target image (from a control subject). The 3D fluid registration was regularized using the linearized Cauchy–Navier operator. Fine-scale volumetric differences between diagnostic groups were mapped. Regions were identified where brain atrophy correlated with clinical measures. Results Severe atrophy (~15–20% deficit) was detected bilaterally in the primary and association sensorimotor areas. Atrophy of these regions, particularly in the white matter, correlated with cognitive impairment (P=0.033) and CD4+ T-lymphocyte depletion (P=0.005). Conclusion TBM facilitates 3D visualization of AIDS neuropathology in living patients scanned with MRI. Severe atrophy in frontoparietal and striatal areas may underlie early cognitive dysfunction in AIDS patients, and may signal the imminent onset of AIDS dementia complex. PMID:17035049

Protocol for Biomarker Ratio Imaging Microscopy with Specific Application to Ductal Carcinoma In situ of the Breast

PubMed Central

Clark, Andrea J.; Petty, Howard R.

2016-01-01

This protocol describes the methods and steps involved in performing biomarker ratio imaging microscopy (BRIM) using formalin fixed paraffin-embedded (FFPE) samples of human breast tissue. The technique is based on the acquisition of two fluorescence images of the same microscopic field using two biomarkers and immunohistochemical tools. The biomarkers are selected such that one biomarker correlates with breast cancer aggressiveness while the second biomarker anti-correlates with aggressiveness. When the former image is divided by the latter image, a computed ratio image is formed that reflects the aggressiveness of tumor cells while increasing contrast and eliminating path-length and other artifacts from the image. For example, the aggressiveness of epithelial cells may be assessed by computing ratio images of N-cadherin and E-cadherin images or CD44 and CD24 images, which specifically reflect the mesenchymal or stem cell nature of the constituent cells, respectively. This methodology is illustrated for tissue samples of ductal carcinoma in situ (DCIS) and invasive breast cancer. This tool should be useful in tissue studies of experimental cancer as well as the management of cancer patients. PMID:27857940

Planar dGEMRIC Maps May Aid Imaging Assessment of Cartilage Damage in Femoroacetabular Impingement.

PubMed

Bulat, Evgeny; Bixby, Sarah D; Siversson, Carl; Kalish, Leslie A; Warfield, Simon K; Kim, Young-Jo

2016-02-01

Three-dimensional (3-D) delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) helps quantify biochemical changes in articular cartilage that correlate with early-stage osteoarthritis. However, dGEMRIC analysis is performed slice by slice, limiting the potential of 3-D data to give an overall impression of cartilage biochemistry. We previously developed a computational algorithm to produce unfolded, or "planar," dGEMRIC maps of acetabular cartilage, but have neither assessed their application nor determined whether MRI-based grading of cartilage damage or dGEMRIC measurements predict intraoperative findings in hips with symptomatic femoroacetabular impingement (FAI). (1) Does imaging-based assessment of acetabular cartilage damage correlate with intraoperative findings in hips with symptomatic FAI? (2) Does the planar dGEMRIC map improve this correlation? (3) Does the planar map improve the correlation between the dGEMRIC index and MRI-based grading of cartilage damage in hips with symptomatic FAI? (4) Does the planar map improve imaging-based evaluation time for hips with symptomatic FAI? We retrospectively studied 47 hips of 45 patients with symptomatic FAI who underwent hip surgery between 2009 and 2013 and had a 1.5-T 3-D dGEMRIC scan within 6 months preoperatively. Our cohort included 25 males and 20 females with a mean ± SD age at surgery of 29 ± 11 years. Planar dGEMRIC maps were generated from isotropic, sagittal oblique TrueFISP and T1 sequences. A pediatric musculoskeletal radiologist with experience in hip MRI evaluated studies using radially reformatted sequences. For six acetabular subregions (anterior-peripheral [AP]; anterior-central [AC]; superior-peripheral [SP]; superior-central [SC]; posterior-peripheral [PP]; posterior-central [PC]), modified Outerbridge cartilage damage grades were recorded and region-of-interest T1 averages (the dGEMRIC index) were measured. Beck's intraoperative cartilage damage grades were compared with the Outerbridge grades and dGEMRIC indices. For a subset of 26 hips, 13 were reevaluated with the map and 13 without the map, and total evaluation times were recorded. There were no meaningful differences in the correlations obtained with versus without referencing the planar maps. Planar map-independent Outerbridge grades had a notable (p < 0.05) Spearman's rank correlation (ρ) with Beck's grades that was moderate in AP, SC, and PC (0.3 < ρ < 0.5) and strong in SP (ρ > 0.5). For map-dependent Outerbridge grades, ρ was moderate in AP, AC, and SC and strong in SP. Map-independent dGEMRIC indices had a ρ with Beck's grades that was moderate in AP and SC (-0.3 > ρ > -0.5) and strong in SP (ρ < -0.5). For map-dependent dGEMRIC indices, ρ was moderate in SC and strong in SP. Similarly, there were no meaningful, map-dependent differences in the correlations. When comparing Outerbridge grades and dGEMRIC indices, there were notable correlations across all subregions. Without the planar map, ρ was moderate in AC and PC and strong in AP, SP, SC, and PP. With the map, ρ was strong in all six subregions. In AC, there was a notable map-dependent improvement in this correlation (p < 0.001). Finally, referencing the planar dGEMRIC map during evaluation was associated with a decrease in mean evaluation time, from 207 ± 32 seconds to 152 ± 33 seconds (p = 0.001). Our work challenges the weak correlation between dGEMRIC and intraoperative findings of cartilage damage that was previously reported in hips with symptomatic FAI, suggesting that dGEMRIC has potential diagnostic use for this patient population. The planar dGEMRIC maps did not meaningfully alter the correlation of imaging-based evaluation of cartilage damage with intraoperative findings; however, they notably improved the correlation of dGEMRIC and MRI-based grading in AC, and their use incurred no additional time cost to imaging-based evaluation. Therefore, the planar maps may improve dGEMRIC's use as a continuous proxy for an otherwise discrete and simplified MRI-based grade of cartilage damage in hips with symptomatic FAI. Level III, diagnostic study.

Imaging, microscopic analysis, and modeling of a CdTe module degraded by heat and light

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnston, Steve; Albin, David; Hacke, Peter

Photoluminescence (PL), electroluminescence (EL), and dark lock-in thermography are collected during stressing of a CdTe module under one-Sun light at an elevated temperature of 100 degrees C. The PL imaging system is simple and economical. The PL images show differing degrees of degradation across the module and are less sensitive to effects of shunting and resistance that appear on the EL images. Regions of varying degradation are chosen based on avoiding pre-existing shunt defects. These regions are evaluated using time-of-flight secondary ion-mass spectrometry and Kelvin probe force microscopy. Reduced PL intensity correlates to increased Cu concentration at the front interface.more » Numerical modeling and measurements agree that the increased Cu concentration at the junction also correlates to a reduced space charge region.« less

Imaging, microscopic analysis, and modeling of a CdTe module degraded by heat and light

DOE PAGES

Johnston, Steve; Albin, David; Hacke, Peter; ...

2018-01-12

Photoluminescence (PL), electroluminescence (EL), and dark lock-in thermography are collected during stressing of a CdTe module under one-Sun light at an elevated temperature of 100 degrees C. The PL imaging system is simple and economical. The PL images show differing degrees of degradation across the module and are less sensitive to effects of shunting and resistance that appear on the EL images. Regions of varying degradation are chosen based on avoiding pre-existing shunt defects. These regions are evaluated using time-of-flight secondary ion-mass spectrometry and Kelvin probe force microscopy. Reduced PL intensity correlates to increased Cu concentration at the front interface.more » Numerical modeling and measurements agree that the increased Cu concentration at the junction also correlates to a reduced space charge region.« less

Chaotic CDMA watermarking algorithm for digital image in FRFT domain

NASA Astrophysics Data System (ADS)

Liu, Weizhong; Yang, Wentao; Feng, Zhuoming; Zou, Xuecheng

2007-11-01

A digital image-watermarking algorithm based on fractional Fourier transform (FRFT) domain is presented by utilizing chaotic CDMA technique in this paper. As a popular and typical transmission technique, CDMA has many advantages such as privacy, anti-jamming and low power spectral density, which can provide robustness against image distortions and malicious attempts to remove or tamper with the watermark. A super-hybrid chaotic map, with good auto-correlation and cross-correlation characteristics, is adopted to produce many quasi-orthogonal codes (QOC) that can replace the periodic PN-code used in traditional CDAM system. The watermarking data is divided into a lot of segments that correspond to different chaotic QOC respectively and are modulated into the CDMA watermarking data embedded into low-frequency amplitude coefficients of FRFT domain of the cover image. During watermark detection, each chaotic QOC extracts its corresponding watermarking segment by calculating correlation coefficients between chaotic QOC and watermarked data of the detected image. The CDMA technique not only can enhance the robustness of watermark but also can compress the data of the modulated watermark. Experimental results show that the watermarking algorithm has good performances in three aspects: better imperceptibility, anti-attack robustness and security.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

An MRI-Based Atlas for Correlation of Imaging and Pathologic Findings in Alzheimer's Disease.

PubMed

Raman, Mekala R; Schwarz, Christopher G; Murray, Melissa E; Lowe, Val J; Dickson, Dennis W; Jack, Clifford R; Kantarci, Kejal

2016-05-01

Pathologic diagnosis is the gold standard in evaluating imaging measures developed as biomarkers for pathologically defined disorders. A brain MRI atlas representing autopsy-sampled tissue can be used to directly compare imaging and pathology findings. Our objective was to develop a brain MRI atlas representing the cortical regions that are routinely sampled at autopsy for the diagnosis of Alzheimer's disease (AD). Subjects (n = 22; ages at death = 70-95) with a range of pathologies and antemortem 3T MRI were included. Histology slides from 8 cortical regions sampled from the left hemisphere at autopsy guided the localization of the atlas regions of interest (ROIs) on each subject's antemortem 3D T1 -weighted MRI. These ROIs were then registered to a common template and combined to form one ROI representing the volume of tissue that was sampled by the pathologists. A subset of the subjects (n = 4; ages at death = 79-95) had amyloid PET imaging. Density of β-amyloid immunostain was quantified from the autopsy-sampled regions in the 4 subjects using a custom-designed ImageScope algorithm. Median uptake values were calculated in each ROI on the amyloid-PET images. We found an association between β-amyloid plaque density in 8 ROIs of the 4 subjects (total ROI n = 32) and median PiB SUVR (r(2) = .64; P < .0001). In an atlas developed for imaging and pathologic correlation studies, we demonstrated that antemortem amyloid burden measured in the atlas ROIs on amyloid PET is strongly correlated with β-amyloid density measured on histology. This atlas can be used in imaging and pathologic correlation studies. © 2016 The Authors. Journal of Neuroimaging published by Wiley Periodicals, Inc. on behalf of American Society of Neuroimaging.

Pre-processing, registration and selection of adaptive optics corrected retinal images.

PubMed

Ramaswamy, Gomathy; Devaney, Nicholas

2013-07-01

In this paper, the aim is to demonstrate enhanced processing of sequences of fundus images obtained using a commercial AO flood illumination system. The purpose of the work is to (1) correct for uneven illumination at the retina (2) automatically select the best quality images and (3) precisely register the best images. Adaptive optics corrected retinal images are pre-processed to correct uneven illumination using different methods; subtracting or dividing by the average filtered image, homomorphic filtering and a wavelet based approach. These images are evaluated to measure the image quality using various parameters, including sharpness, variance, power spectrum kurtosis and contrast. We have carried out the registration in two stages; a coarse stage using cross-correlation followed by fine registration using two approaches; parabolic interpolation on the peak of the cross-correlation and maximum-likelihood estimation. The angle of rotation of the images is measured using a combination of peak tracking and Procrustes transformation. We have found that a wavelet approach (Daubechies 4 wavelet at 6th level decomposition) provides good illumination correction with clear improvement in image sharpness and contrast. The assessment of image quality using a 'Designer metric' works well when compared to visual evaluation, although it is highly correlated with other metrics. In image registration, sub-pixel translation measured using parabolic interpolation on the peak of the cross-correlation function and maximum-likelihood estimation are found to give very similar results (RMS difference 0.047 pixels). We have confirmed that correcting rotation of the images provides a significant improvement, especially at the edges of the image. We observed that selecting the better quality frames (e.g. best 75% images) for image registration gives improved resolution, at the expense of poorer signal-to-noise. The sharpness map of the registered and de-rotated images shows increased sharpness over most of the field of view. Adaptive optics assisted images of the cone photoreceptors can be better pre-processed using a wavelet approach. These images can be assessed for image quality using a 'Designer Metric'. Two-stage image registration including correcting for rotation significantly improves the final image contrast and sharpness. © 2013 The Authors Ophthalmic & Physiological Optics © 2013 The College of Optometrists.

Ischemic lesion volume determination on diffusion weighted images vs. apparent diffusion coefficient maps.

PubMed

Bråtane, Bernt Tore; Bastan, Birgul; Fisher, Marc; Bouley, James; Henninger, Nils

2009-07-07

Though diffusion weighted imaging (DWI) is frequently used for identifying the ischemic lesion in focal cerebral ischemia, the understanding of spatiotemporal evolution patterns observed with different analysis methods remains imprecise. DWI and calculated apparent diffusion coefficient (ADC) maps were serially obtained in rat stroke models (MCAO): permanent, 90 min, and 180 min temporary MCAO. Lesion volumes were analyzed in a blinded and randomized manner by 2 investigators using (i) a previously validated ADC threshold, (ii) visual determination of hypointense regions on ADC maps, and (iii) visual determination of hyperintense regions on DWI. Lesion volumes were correlated with 24 hour 2,3,5-triphenyltetrazoliumchloride (TTC)-derived infarct volumes. TTC-derived infarct volumes were not significantly different from the ADC and DWI-derived lesion volumes at the last imaging time points except for significantly smaller DWI lesions in the pMCAO model (p=0.02). Volumetric calculation based on TTC-derived infarct also correlated significantly stronger to volumetric calculation based on last imaging time point derived lesions on ADC maps than DWI (p<0.05). Following reperfusion, lesion volumes on the ADC maps significantly reduced but no change was observed on DWI. Visually determined lesion volumes on ADC maps and DWI by both investigators correlated significantly with threshold-derived lesion volumes on ADC maps with the former method demonstrating a stronger correlation. There was also a better interrater agreement for ADC map analysis than for DWI analysis. Ischemic lesion determination by ADC was more accurate in final infarct prediction, rater independent, and provided exclusive information on ischemic lesion reversibility.

Analysis of confidence level scores from an ROC study: comparison of three mammographic systems for detection of simulated calcifications

NASA Astrophysics Data System (ADS)

Lai, Chao-Jen; Shaw, Chris C.; Whitman, Gary J.; Yang, Wei T.; Dempsey, Peter J.

2005-04-01

The purpose of this study is to compare the detection performance of three different mammography systems: screen/film (SF) combination, a-Si/CsI flat-panel (FP-), and charge-coupled device (CCD-) based systems. A 5-cm thick 50% adipose/50% glandular breast tissue equivalent slab phantom was used to provide an uniform background. Calcium carbonate grains of three different size groups were used to simulate microcalcifications (MCs): 112-125, 125-140, and 140-150 μm overlapping with the uniform background. Calcification images were acquired with the three mammography systems. Digital images were printed on hardcopy films. All film images were displayed on a mammographic viewer and reviewed by 5 mammographers. The visibility of the MC was rated with a 5-point confidence rating scale for each detection task, including the negative controls. Scores were averaged over all readers for various detectors and size groups. Receiver operating characteristic (ROC) analysis was performed and the areas under the ROC curves (Az"s) were computed for various imaging conditions. The results shows that (1) the FP-based system performed significantly better than the SF and CCD-based systems for individual size groups using ROC analysis (2) the FP-based system also performed significantly better than the SF and CCD-based systems for individual size groups using averaged confidence scale, and (3) the results obtained from the Az"s were largely correlated with these from confidence level scores. However, the correlation varied slightly among different imaging conditions.

TU-AB-202-11: Tumor Segmentation by Fusion of Multi-Tracer PET Images Using Copula Based Statistical Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lapuyade-Lahorgue, J; Ruan, S; Li, H

Purpose: Multi-tracer PET imaging is getting more attention in radiotherapy by providing additional tumor volume information such as glucose and oxygenation. However, automatic PET-based tumor segmentation is still a very challenging problem. We propose a statistical fusion approach to joint segment the sub-area of tumors from the two tracers FDG and FMISO PET images. Methods: Non-standardized Gamma distributions are convenient to model intensity distributions in PET. As a serious correlation exists in multi-tracer PET images, we proposed a new fusion method based on copula which is capable to represent dependency between different tracers. The Hidden Markov Field (HMF) model ismore » used to represent spatial relationship between PET image voxels and statistical dynamics of intensities for each modality. Real PET images of five patients with FDG and FMISO are used to evaluate quantitatively and qualitatively our method. A comparison between individual and multi-tracer segmentations was conducted to show advantages of the proposed fusion method. Results: The segmentation results show that fusion with Gaussian copula can receive high Dice coefficient of 0.84 compared to that of 0.54 and 0.3 of monomodal segmentation results based on individual segmentation of FDG and FMISO PET images. In addition, high correlation coefficients (0.75 to 0.91) for the Gaussian copula for all five testing patients indicates the dependency between tumor regions in the multi-tracer PET images. Conclusion: This study shows that using multi-tracer PET imaging can efficiently improve the segmentation of tumor region where hypoxia and glucidic consumption are present at the same time. Introduction of copulas for modeling the dependency between two tracers can simultaneously take into account information from both tracers and deal with two pathological phenomena. Future work will be to consider other families of copula such as spherical and archimedian copulas, and to eliminate partial volume effect by considering dependency between neighboring voxels.« less

Dynamic CT imaging of volumetric changes in pulmonary nodules correlates with physical measurements of stiffness.

PubMed

Lartey, Frederick M; Rafat, Marjan; Negahdar, Mohammadreza; Malkovskiy, Andrey V; Dong, Xinzhe; Sun, Xiaoli; Li, Mei; Doyle, Timothy; Rajadas, Jayakumar; Graves, Edward E; Loo, Billy W; Maxim, Peter G

2017-02-01

A major challenge in CT screening for lung cancer is limited specificity when distinguishing between malignant and non-malignant pulmonary nodules (PN). Malignant nodules have different mechanical properties and tissue characteristics ('stiffness') from non-malignant nodules. This study seeks to improve CT specificity by demonstrating in rats that measurements of volumetric ratios in PNs with varying composition can be determined by respiratory-gated dynamic CT imaging and that these ratios correlate with direct physical measurements of PN stiffness. Respiratory-gated MicroCT images acquired at extreme tidal volumes of 9 rats with PNs from talc, matrigel and A549 human lung carcinoma were analyzed and their volumetric ratios (δ) derived. PN stiffness was determined by measuring the Young's modulus using atomic force microscopy (AFM) for each nodule excised immediately after MicroCT imaging. There was significant correlation (p=0.0002) between PN volumetric ratios determined by respiratory-gated CT imaging and the physical stiffness of the PNs determined from AFM measurements. We demonstrated proof of concept that PN volume changes measured non-invasively correlate with direct physical measurements of stiffness. These results may translate clinically into a means of improving the specificity of CT screening for lung cancer and/or improving individual prognostic assessments based on lung tumor stiffness. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

PubMed

Baños, Núria; Perez-Moreno, Alvaro; Migliorelli, Federico; Triginer, Laura; Cobo, Teresa; Bonet-Carne, Elisenda; Gratacos, Eduard; Palacio, Montse

2017-01-01

Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant. © 2016 S. Karger AG, Basel.

Correlative Imaging of Fluorescent Proteins in Resin-Embedded Plant Material1

PubMed Central

Bell, Karen; Mitchell, Steve; Paultre, Danae; Posch, Markus; Oparka, Karl

2013-01-01

Fluorescent proteins (FPs) were developed for live-cell imaging and have revolutionized cell biology. However, not all plant tissues are accessible to live imaging using confocal microscopy, necessitating alternative approaches for protein localization. An example is the phloem, a tissue embedded deep within plant organs and sensitive to damage. To facilitate accurate localization of FPs within recalcitrant tissues, we developed a simple method for retaining FPs after resin embedding. This method is based on low-temperature fixation and dehydration, followed by embedding in London Resin White, and avoids the need for cryosections. We show that a palette of FPs can be localized in plant tissues while retaining good structural cell preservation, and that the polymerized block face can be counterstained with cell wall probes. Using this method we have been able to image green fluorescent protein-labeled plasmodesmata to a depth of more than 40 μm beneath the resin surface. Using correlative light and electron microscopy of the phloem, we were able to locate the same FP-labeled sieve elements in semithin and ultrathin sections. Sections were amenable to antibody labeling, and allowed a combination of confocal and superresolution imaging (three-dimensional-structured illumination microscopy) on the same cells. These correlative imaging methods should find several uses in plant cell biology. PMID:23457228

Joint sparse coding based spatial pyramid matching for classification of color medical image.

PubMed

Shi, Jun; Li, Yi; Zhu, Jie; Sun, Haojie; Cai, Yin

2015-04-01

Although color medical images are important in clinical practice, they are usually converted to grayscale for further processing in pattern recognition, resulting in loss of rich color information. The sparse coding based linear spatial pyramid matching (ScSPM) and its variants are popular for grayscale image classification, but cannot extract color information. In this paper, we propose a joint sparse coding based SPM (JScSPM) method for the classification of color medical images. A joint dictionary can represent both the color information in each color channel and the correlation between channels. Consequently, the joint sparse codes calculated from a joint dictionary can carry color information, and therefore this method can easily transform a feature descriptor originally designed for grayscale images to a color descriptor. A color hepatocellular carcinoma histological image dataset was used to evaluate the performance of the proposed JScSPM algorithm. Experimental results show that JScSPM provides significant improvements as compared with the majority voting based ScSPM and the original ScSPM for color medical image classification. Copyright © 2014 Elsevier Ltd. All rights reserved.

SPIO-labeled Yttrium Microspheres for MR Imaging Quantification of Transcatheter Intrahepatic Delivery in a Rodent Model

PubMed Central

Li, Weiguo; Zhang, Zhuoli; Gordon, Andrew C.; Chen, Jeane; Nicolai, Jodi; Lewandowski, Robert J.; Omary, Reed A.

2016-01-01

Purpose To investigate the qualitative and quantitative impacts of labeling yttrium microspheres with increasing amounts of superparamagnetic iron oxide (SPIO) material for magnetic resonance (MR) imaging in phantom and rodent models. Materials and Methods Animal model studies were approved by the institutional Animal Care and Use Committee. The r2* relaxivity for each of four microsphere SPIO compositions was determined from 32 phantoms constructed with agarose gel and in eight concentrations from each of the four compositions. Intrahepatic transcatheter infusion procedures were performed in rats by using each of the four compositions before MR imaging to visualize distributions within the liver. For quantitative studies, doses of 5, 10, 15, or 20 mg 2% SPIO-labeled yttrium microspheres were infused into 24 rats (six rats per group). MR imaging R2* measurements were used to quantify the dose delivered to each liver. Pearson correlation, analysis of variance, and intraclass correlation analyses were performed to compare MR imaging measurements in phantoms and animal models. Results Increased r2* relaxivity was observed with incremental increases of SPIO microsphere content. R2* measurements of the 2% SPIO–labeled yttrium microsphere concentration were well correlated with known phantom concentrations (R2 = 1.00, P < .001) over a broader linear range than observed for the other three compositions. Microspheres were heterogeneously distributed within each liver; increasing microsphere SPIO content produced marked signal voids. R2*-based measurements of 2% SPIO–labeled yttrium microsphere delivery were well correlated with infused dose (intraclass correlation coefficient, 0.98; P < .001). Conclusion MR imaging R2* measurements of yttrium microspheres labeled with 2% SPIO can quantitatively depict in vivo intrahepatic biodistribution in a rat model. © RSNA, 2015 Online supplemental material is available for this article. PMID:26313619

Intracellular dynamics and fate of polystyrene nanoparticles in A549 Lung epithelial cells monitored by image (cross-) correlation spectroscopy and single particle tracking.

PubMed

Deville, Sarah; Penjweini, Rozhin; Smisdom, Nick; Notelaers, Kristof; Nelissen, Inge; Hooyberghs, Jef; Ameloot, Marcel

2015-10-01

Novel insights in nanoparticle (NP) uptake routes of cells, their intracellular trafficking and subcellular targeting can be obtained through the investigation of their temporal and spatial behavior. In this work, we present the application of image (cross-) correlation spectroscopy (IC(C)S) and single particle tracking (SPT) to monitor the intracellular dynamics of polystyrene (PS) NPs in the human lung carcinoma A549 cell line. The ensemble kinetic behavior of NPs inside the cell was characterized by temporal and spatiotemporal image correlation spectroscopy (TICS and STICS). Moreover, a more direct interpretation of the diffusion and flow detected in the NP motion was obtained by SPT by monitoring individual NPs. Both techniques demonstrate that the PS NP transport in A549 cells is mainly dependent on microtubule-assisted transport. By applying spatiotemporal image cross-correlation spectroscopy (STICCS), the correlated motions of NPs with the early endosomes, late endosomes and lysosomes are identified. PS NPs were equally distributed among the endolysosomal compartment during the time interval of the experiments. The cotransport of the NPs with the lysosomes is significantly larger compared to the other cell organelles. In the present study we show that the complementarity of ICS-based techniques and SPT enables a consistent elaborate model of the complex behavior of NPs inside biological systems. Copyright © 2015 Elsevier B.V. All rights reserved.

Speckle contrast diffuse correlation tomography of complex turbid medium flow

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Chong; Irwin, Daniel; Lin, Yu

2015-07-15

Purpose: Developed herein is a three-dimensional (3D) flow contrast imaging system leveraging advancements in the extension of laser speckle contrast imaging theories to deep tissues along with our recently developed finite-element diffuse correlation tomography (DCT) reconstruction scheme. This technique, termed speckle contrast diffuse correlation tomography (scDCT), enables incorporation of complex optical property heterogeneities and sample boundaries. When combined with a reflectance-based design, this system facilitates a rapid segue into flow contrast imaging of larger, in vivo applications such as humans. Methods: A highly sensitive CCD camera was integrated into a reflectance-based optical system. Four long-coherence laser source positions were coupledmore » to an optical switch for sequencing of tomographic data acquisition providing multiple projections through the sample. This system was investigated through incorporation of liquid and solid tissue-like phantoms exhibiting optical properties and flow characteristics typical of human tissues. Computer simulations were also performed for comparisons. A uniquely encountered smear correction algorithm was employed to correct point-source illumination contributions during image capture with the frame-transfer CCD and reflectance setup. Results: Measurements with scDCT on a homogeneous liquid phantom showed that speckle contrast-based deep flow indices were within 12% of those from standard DCT. Inclusion of a solid phantom submerged below the liquid phantom surface allowed for heterogeneity detection and validation. The heterogeneity was identified successfully by reconstructed 3D flow contrast tomography with scDCT. The heterogeneity center and dimensions and averaged relative flow (within 3%) and localization were in agreement with actuality and computer simulations, respectively. Conclusions: A custom cost-effective CCD-based reflectance 3D flow imaging system demonstrated rapid acquisition of dense boundary data and, with further studies, a high potential for translatability to real tissues with arbitrary boundaries. A requisite correction was also found for measurements in the fashion of scDCT to recover accurate speckle contrast of deep tissues.« less

Atomic-scale imaging of DNA using scanning tunnelling microscopy.

PubMed

Driscoll, R J; Youngquist, M G; Baldeschwieler, J D

1990-07-19

The scanning tunnelling microscope (STM) has been used to visualize DNA under water, under oil and in air. Images of single-stranded DNA have shown that submolecular resolution is possible. Here we describe atomic-resolution imaging of duplex DNA. Topographic STM images of uncoated duplex DNA on a graphite substrate obtained in ultra-high vacuum are presented that show double-helical structure, base pairs, and atomic-scale substructure. Experimental STM profiles show excellent correlation with atomic contours of the van der Waals surface of A-form DNA derived from X-ray crystallography. A comparison of variations in the barrier to quantum mechanical tunnelling (barrier-height) with atomic-scale topography shows correlation over the phosphate-sugar backbone but anticorrelation over the base pairs. This relationship may be due to the different chemical characteristics of parts of the molecule. Further investigation of this phenomenon should lead to a better understanding of the physics of imaging adsorbates with the STM and may prove useful in sequencing DNA. The improved resolution compared with previously published STM images of DNA may be attributable to ultra-high vacuum, high data-pixel density, slow scan rate, a fortuitously clean and sharp tip and/or a relatively dilute and extremely clean sample solution. This work demonstrates the potential of the STM for characterization of large biomolecular structures, but additional development will be required to make such high resolution imaging of DNA and other large molecules routine.

Hierarchical multivariate covariance analysis of metabolic connectivity

PubMed Central

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-01-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI). PMID:25294129

A New Method to Measure Crack Extension in Nuclear Graphite Based on Digital Image Correlation

DOE PAGES

Lai, Shigang; Shi, Li; Fok, Alex; ...

2017-01-01

Graphite components, used as moderators, reflectors, and core-support structures in a High-Temperature Gas-Cooled Reactor, play an important role in the safety of the reactor. Specifically, they provide channels for the fuel elements, control rods, and coolant flow. Fracture is the main failure mode for graphite, and breaching of the above channels by crack extension will seriously threaten the safety of a reactor. In this paper, a new method based on digital image correlation (DIC) is introduced for measuring crack extension in brittle materials. Cross-correlation of the displacements measured by DIC with a step function was employed to identify the advancingmore » crack tip in a graphite beam specimen under three-point bending. The load-crack extension curve, which is required for analyzing the R-curve and tension softening behaviors, was obtained for this material. Furthermore, a sensitivity analysis of the threshold value employed for the cross-correlation parameter in the crack identification process was conducted. Finally, the results were verified using the finite element method.« less

A New Method to Measure Crack Extension in Nuclear Graphite Based on Digital Image Correlation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lai, Shigang; Shi, Li; Fok, Alex

Graphite components, used as moderators, reflectors, and core-support structures in a High-Temperature Gas-Cooled Reactor, play an important role in the safety of the reactor. Specifically, they provide channels for the fuel elements, control rods, and coolant flow. Fracture is the main failure mode for graphite, and breaching of the above channels by crack extension will seriously threaten the safety of a reactor. In this paper, a new method based on digital image correlation (DIC) is introduced for measuring crack extension in brittle materials. Cross-correlation of the displacements measured by DIC with a step function was employed to identify the advancingmore » crack tip in a graphite beam specimen under three-point bending. The load-crack extension curve, which is required for analyzing the R-curve and tension softening behaviors, was obtained for this material. Furthermore, a sensitivity analysis of the threshold value employed for the cross-correlation parameter in the crack identification process was conducted. Finally, the results were verified using the finite element method.« less

Structural and functional brain changes in early- and mid-stage primary open-angle glaucoma using voxel-based morphometry and functional magnetic resonance imaging.

PubMed

Jiang, Ming-Ming; Zhou, Qing; Liu, Xiao-Yong; Shi, Chang-Zheng; Chen, Jian; Huang, Xiang-He

2017-03-01

To investigate structural and functional brain changes in patients with primary open-angle glaucoma (POAG) by using voxel-based morphometry based on diffeomorphic anatomical registration through exponentiated Lie algebra (VBM-DARTEL) and blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI), respectively.Thirteen patients diagnosed with POAG and 13 age- and sex-matched healthy controls were enrolled in the study. For each participant, high-resolution structural brain imaging and blood flow imaging were acquired on a 3.0-Tesla magnetic resonance imaging (MRI) scanner. Structural and functional changes between the POAG and control groups were analyzed. An analysis was carried out to identify correlations between structural and functional changes acquired in the previous analysis and the retinal nerve fiber layer (RNFL).Patients in the POAG group showed a significant (P < 0.001) volume increase in the midbrain, left brainstem, frontal gyrus, cerebellar vermis, left inferior parietal lobule, caudate nucleus, thalamus, precuneus, and Brodmann areas 7, 18, and 46. Moreover, significant (P < 0.001) BOLD signal changes were observed in the right supramarginal gyrus, frontal gyrus, superior frontal gyrus, left inferior parietal lobule, left cuneus, and left midcingulate area; many of these regions had high correlations with the RNFL.Patients with POAG undergo widespread and complex changes in cortical brain structure and blood flow. (ClinicalTrials.gov number: NCT02570867).

Development and Evaluation of Semiautomated Quantification of Lissamine Green Staining of the Bulbar Conjunctiva From Digital Images.

PubMed

Bunya, Vatinee Y; Chen, Min; Zheng, Yuanjie; Massaro-Giordano, Mina; Gee, James; Daniel, Ebenezer; O'Sullivan, Ryan; Smith, Eli; Stone, Richard A; Maguire, Maureen G

2017-10-01

Lissamine green (LG) staining of the conjunctiva is a key biomarker in evaluating ocular surface disease. The disease currently is assessed using relatively coarse subjective scales. Objective assessment would standardize comparisons over time and between clinicians. To develop a semiautomated, quantitative system to assess lissamine green staining of the bulbar conjunctiva on digital images. Using a standard photography protocol, 35 digital images of the conjunctiva of 11 patients with a diagnosis of dry eye disease based on characteristic signs and symptoms were obtained after topical administration of preservative-free LG, 1%, solution. Images were scored independently by 2 masked ophthalmologists in an academic medical center using the van Bijsterveld and National Eye Institute (NEI) scales. The region of interest was identified by manually marking 7 anatomic landmarks on the images. An objective measure was developed by segmenting the images, forming a vector of key attributes, and then performing a random forest regression. Subjective scores were correlated with the output from a computer algorithm using a cross-validation technique. The ranking of images from least to most staining was compared between the algorithm and the ophthalmologists. The study was conducted from April 26, 2012, through June 2, 2016. Correlation and level of agreement among computerized algorithm scores, van Bijsterveld scale clinical scores, and NEI scale clinical scores. The scores from the automated algorithm correlated well with the mean scores obtained from the gradings of 2 ophthalmologists for the 35 images using the van Bijsterveld scale (Spearman correlation coefficient, rs = 0.79), and moderately with the NEI scale (rs = 0.61) scores. For qualitative ranking of staining, the correlation between the automated algorithm and the 2 ophthalmologists was rs = 0.78 and rs = 0.83. The algorithm performed well when evaluating LG staining of the conjunctiva, as evidenced by good correlation with subjective gradings using 2 different grading scales. Future longitudinal studies are needed to assess the responsiveness of the algorithm to change of conjunctival staining over time.

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

A novel method for real-time edge-enhancement and its application to pattern recognition

NASA Astrophysics Data System (ADS)

Ge, Huayong; Bai, Enjian; Fan, Hong

2010-11-01

The coupling gain coefficient g is redefined and deduced based on coupling theory, the variant of coupling gain coefficient g for different ΓL and r is analyzed. A new optical system is proposed for image edge-enhancement. It recycles the back signal to amplify the edge signal, which has the advantages of high throughput efficiency and brightness. The optical system is designed and built, and the edge-enhanced image of hand bone is captured electronically by CCD camera. The principle of optical correlation is demonstrated, 3-D correlation distribution of letter H with and without edge-enhancement is simulated, the discrimination capability Iac and the full-width at half maximum intensity (FWHM) are compared for two kinds of correlators. The analysis shows that edge-enhancement preprocessing can improve the performance of correlator effectively.

Noise in x-ray grating-based phase-contrast imaging.

PubMed

Weber, Thomas; Bartl, Peter; Bayer, Florian; Durst, Jürgen; Haas, Wilhelm; Michel, Thilo; Ritter, André; Anton, Gisela

2011-07-01

Grating-based x-ray phase-contrast imaging is a fast developing new modality not only for medical imaging, but as well for other fields such as material sciences. While these many possible applications arise, the knowledge of the noise behavior is essential. In this work, the authors used a least squares fitting algorithm to calculate the noise behavior of the three quantities absorption, differential phase, and dark-field image. Further, the calculated error formula of the differential phase image was verified by measurements. Therefore, a Talbot interferometer was setup, using a microfocus x-ray tube as source and a Timepix detector for photon counting. Additionally, simulations regarding this topic were performed. It turned out that the variance of the reconstructed phase is only dependent of the total number of photons used to generate the phase image and the visibility of the experimental setup. These results could be evaluated in measurements as well as in simulations. Furthermore, the correlation between absorption and dark-field image was calculated. These results provide the understanding of the noise characteristics of grating-based phase-contrast imaging and will help to improve image quality.

A Hybrid Probabilistic Model for Unified Collaborative and Content-Based Image Tagging.

PubMed

Zhou, Ning; Cheung, William K; Qiu, Guoping; Xue, Xiangyang

2011-07-01

The increasing availability of large quantities of user contributed images with labels has provided opportunities to develop automatic tools to tag images to facilitate image search and retrieval. In this paper, we present a novel hybrid probabilistic model (HPM) which integrates low-level image features and high-level user provided tags to automatically tag images. For images without any tags, HPM predicts new tags based solely on the low-level image features. For images with user provided tags, HPM jointly exploits both the image features and the tags in a unified probabilistic framework to recommend additional tags to label the images. The HPM framework makes use of the tag-image association matrix (TIAM). However, since the number of images is usually very large and user-provided tags are diverse, TIAM is very sparse, thus making it difficult to reliably estimate tag-to-tag co-occurrence probabilities. We developed a collaborative filtering method based on nonnegative matrix factorization (NMF) for tackling this data sparsity issue. Also, an L1 norm kernel method is used to estimate the correlations between image features and semantic concepts. The effectiveness of the proposed approach has been evaluated using three databases containing 5,000 images with 371 tags, 31,695 images with 5,587 tags, and 269,648 images with 5,018 tags, respectively.

Status of use of lunar irradiance for on-orbit calibration

USGS Publications Warehouse

Stone, T.C.; Kieffer, H.H.; Anderson, J.M.; ,

2002-01-01

Routine observations of the Moon have been acquired by the Robotic Lunar Observatory (ROLO) for over four years. The ROLO instruments measure lunar radiance in 23 VNIR (Moon diameter ???500 pixels) and 9 SWIR (???250 pixels) passbands every month when the Moon is at phase angle less than 90 degrees. These are converted to exoatmospheric values at standard distances using an atmospheric extinction model based on observations of standard stars and a NIST-traceable absolute calibration source. Reduction of the stellar images also provides an independent pathway for absolute calibration. Comparison of stellar-based and lamp-based absolute calibrations of the lunar images currently shows unacceptably large differences. An analytic model of lunar irradiance as a function of phase angle and viewing geometry is derived from the calibrated lunar images. Residuals from models which fit hundreds of observations at each wavelength average less than 2%. Comparison with SeaWiFS observations over three years reveals a small quasi-periodic change in SeaWiFS responsivity that correlates with distance from the Sun for the first two years, then departs from this correlation.

A correlative and quantitative imaging approach enabling characterization of primary cell-cell communication: Case of human CD4+ T cell-macrophage immunological synapses.

PubMed

Kasprowicz, Richard; Rand, Emma; O'Toole, Peter J; Signoret, Nathalie

2018-05-22

Cell-to-cell communication engages signaling and spatiotemporal reorganization events driven by highly context-dependent and dynamic intercellular interactions, which are difficult to capture within heterogeneous primary cell cultures. Here, we present a straightforward correlative imaging approach utilizing commonly available instrumentation to sample large numbers of cell-cell interaction events, allowing qualitative and quantitative characterization of rare functioning cell-conjugates based on calcium signals. We applied this approach to examine a previously uncharacterized immunological synapse, investigating autologous human blood CD4 + T cells and monocyte-derived macrophages (MDMs) forming functional conjugates in vitro. Populations of signaling conjugates were visualized, tracked and analyzed by combining live imaging, calcium recording and multivariate statistical analysis. Correlative immunofluorescence was added to quantify endogenous molecular recruitments at the cell-cell junction. By analyzing a large number of rare conjugates, we were able to define calcium signatures associated with different states of CD4 + T cell-MDM interactions. Quantitative image analysis of immunostained conjugates detected the propensity of endogenous T cell surface markers and intracellular organelles to polarize towards cell-cell junctions with high and sustained calcium signaling profiles, hence defining immunological synapses. Overall, we developed a broadly applicable approach enabling detailed single cell- and population-based investigations of rare cell-cell communication events with primary cells.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, B; Fujita, A; Buch, K

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIsmore » over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast, subtle texture changes in addition to human observers.« less

Clinical Evaluation of positioning verification using digital tomosynthesis (DTS) based on bony anatomy and soft tissues for prostate image-guided radiation therapy (IGRT)

PubMed Central

Yoo, Sua; Wu, Q. Jackie; Godfrey, Devon; Yan, Hui; Ren, Lei; Das, Shiva; Lee, William R.; Yin, Fang-Fang

2008-01-01

Purpose To evaluate on-board digital tomosynthesis (DTS) for patient positioning in comparison with 2D-radiographs and 3D-CBCT. Methods and Materials A total of 92 image sessions from 9 prostate cancer patients were analyzed. An on-board image set was registered to a corresponding reference image set. Four pairs of image sets were used; DRR vs. on-board orthogonal paired radiograph for the 2D method, coronal-reference-DTS (RDTS) vs. on-board coronal-DTS for the coronal-DTS method, sagittal-RDTS vs. on-board sagittal-DTS for the sagittal-DTS method, and planning CT vs. CBCT for the CBCT method. Registration results were compared. Results The systematic errors in all methods were less than 1 mm/1°. When registering bony anatomy, the mean vector differences were 0.21±0.11 cm between 2D and CBCT, 0.11±0.08 cm between CBCT and coronal-DTS, and 0.14±0.07 cm between CBCT and sagittal-DTS. The correlation of CBCT to DTS was stronger (coefficients=0.92–0.95) than the correlation between 2D and CBCT or DTS (coefficients=0.81–0.83). When registering soft tissue, the mean vector differences were 0.18±0.11 cm between CBCT and coronal-DTS and 0.29±0.17 cm between CBCT and sagittal-DTS. The correlation coefficients of CBCT to sagittal-DTS and to coronal-DTS were 0.84 and 0.92, respectively. Conclusions DTS could provide equivalent results to CBCT when bony anatomy is used as landmarks for prostate IGRT. For soft tissue-based positioning verification, coronal-DTS produced equivalent results to CBCT and sagittal-DTS alone was insufficient. DTS could allow comparable soft tissue-based target localization with faster scanning time and less imaging dose compared to CBCT. PMID:19100923

Functional magnetic resonance imaging phase synchronization as a measure of dynamic functional connectivity.

PubMed

Glerean, Enrico; Salmi, Juha; Lahnakoski, Juha M; Jääskeläinen, Iiro P; Sams, Mikko

2012-01-01

Functional brain activity and connectivity have been studied by calculating intersubject and seed-based correlations of hemodynamic data acquired with functional magnetic resonance imaging (fMRI). To inspect temporal dynamics, these correlation measures have been calculated over sliding time windows with necessary restrictions on the length of the temporal window that compromises the temporal resolution. Here, we show that it is possible to increase temporal resolution by using instantaneous phase synchronization (PS) as a measure of dynamic (time-varying) functional connectivity. We applied PS on an fMRI dataset obtained while 12 healthy volunteers watched a feature film. Narrow frequency band (0.04-0.07 Hz) was used in the PS analysis to avoid artifactual results. We defined three metrics for computing time-varying functional connectivity and time-varying intersubject reliability based on estimation of instantaneous PS across the subjects: (1) seed-based PS, (2) intersubject PS, and (3) intersubject seed-based PS. Our findings show that these PS-based metrics yield results consistent with both seed-based correlation and intersubject correlation methods when inspected over the whole time series, but provide an important advantage of maximal single-TR temporal resolution. These metrics can be applied both in studies with complex naturalistic stimuli (e.g., watching a movie or listening to music in the MRI scanner) and more controlled (e.g., event-related or blocked design) paradigms. A MATLAB toolbox FUNPSY ( http://becs.aalto.fi/bml/software.html ) is openly available for using these metrics in fMRI data analysis.

Wavelet-based associative memory

NASA Astrophysics Data System (ADS)

Jones, Katharine J.

2004-04-01

Faces provide important characteristics of a person"s identification. In security checks, face recognition still remains the method in continuous use despite other approaches (i.e. fingerprints, voice recognition, pupil contraction, DNA scanners). With an associative memory, the output data is recalled directly using the input data. This can be achieved with a Nonlinear Holographic Associative Memory (NHAM). This approach can also distinguish between strongly correlated images and images that are partially or totally enclosed by others. Adaptive wavelet lifting has been used for Content-Based Image Retrieval. In this paper, adaptive wavelet lifting will be applied to face recognition to achieve an associative memory.

Quantifying white matter structural integrity with high-definition fiber tracking in traumatic brain injury.

PubMed

Presson, Nora; Krishnaswamy, Deepa; Wagener, Lauren; Bird, William; Jarbo, Kevin; Pathak, Sudhir; Puccio, Ava M; Borasso, Allison; Benso, Steven; Okonkwo, David O; Schneider, Walter

2015-03-01

There is an urgent, unmet demand for definitive biological diagnosis of traumatic brain injury (TBI) to pinpoint the location and extent of damage. We have developed High-Definition Fiber Tracking, a 3 T magnetic resonance imaging-based diffusion spectrum imaging and tractography analysis protocol, to quantify axonal injury in military and civilian TBI patients. A novel analytical methodology quantified white matter integrity in patients with TBI and healthy controls. Forty-one subjects (23 TBI, 18 controls) were scanned with the High-Definition Fiber Tracking diffusion spectrum imaging protocol. After reconstruction, segmentation was used to isolate bilateral hemisphere homologues of eight major tracts. Integrity of segmented tracts was estimated by calculating homologue correlation and tract coverage. Both groups showed high correlations for all tracts. TBI patients showed reduced homologue correlation and tract spread and increased outlier count (correlations>2.32 SD below control mean). On average, 6.5% of tracts in the TBI group were outliers with substantial variability among patients. Number and summed deviation of outlying tracts correlated with initial Glasgow Coma Scale score and 6-month Glasgow Outcome Scale-Extended score. The correlation metric used here can detect heterogeneous damage affecting a low proportion of tracts, presenting a potential mechanism for advancing TBI diagnosis. Reprint & Copyright © 2015 Association of Military Surgeons of the U.S.

A digital correlator upgrade for the Arcminute MicroKelvin Imager

NASA Astrophysics Data System (ADS)

Hickish, Jack; Razavi-Ghods, Nima; Perrott, Yvette C.; Titterington, David J.; Carey, Steve H.; Scott, Paul F.; Grainge, Keith J. B.; Scaife, Anna M. M.; Alexander, Paul; Saunders, Richard D. E.; Crofts, Mike; Javid, Kamran; Rumsey, Clare; Jin, Terry Z.; Ely, John A.; Shaw, Clive; Northrop, Ian G.; Pooley, Guy; D'Alessandro, Robert; Doherty, Peter; Willatt, Greg P.

2018-04-01

The Arcminute Microkelvin Imager (AMI) telescopes located at the Mullard Radio Astronomy Observatory near Cambridge have been significantly enhanced by the implementation of a new digital correlator with 1.2 MHz spectral resolution. This system has replaced a 750-MHz resolution analogue lag-based correlator, and was designed to mitigate the effects of radio frequency interference, particularly that from geostationary satellites which are visible from the AMI site when observing at low declinations. The upgraded instrument consists of 18 ROACH2 Field Programmable Gate Array platforms used to implement a pair of real-time FX correlators - one for each of AMI's two arrays. The new system separates the down-converted RF baseband signal from each AMI receiver into two sub-bands, each of which are filtered to a width of 2.3 GHz and digitized at 5-Gsps with 8 bits of precision. These digital data streams are filtered into 2048 frequency channels and cross-correlated using FPGA hardware, with a commercial 10 Gb Ethernet switch providing high-speed data interconnect. Images formed using data from the new digital correlator show over an order of magnitude improvement in dynamic range over the previous system. The ability to observe at low declinations has also been significantly improved.

Machine learning based detection of age-related macular degeneration (AMD) and diabetic macular edema (DME) from optical coherence tomography (OCT) images

PubMed Central

Wang, Yu; Zhang, Yaonan; Yao, Zhaomin; Zhao, Ruixue; Zhou, Fengfeng

2016-01-01

Non-lethal macular diseases greatly impact patients’ life quality, and will cause vision loss at the late stages. Visual inspection of the optical coherence tomography (OCT) images by the experienced clinicians is the main diagnosis technique. We proposed a computer-aided diagnosis (CAD) model to discriminate age-related macular degeneration (AMD), diabetic macular edema (DME) and healthy macula. The linear configuration pattern (LCP) based features of the OCT images were screened by the Correlation-based Feature Subset (CFS) selection algorithm. And the best model based on the sequential minimal optimization (SMO) algorithm achieved 99.3% in the overall accuracy for the three classes of samples. PMID:28018716

Ontology-aided feature correlation for multi-modal urban sensing

NASA Astrophysics Data System (ADS)

Misra, Archan; Lantra, Zaman; Jayarajah, Kasthuri

2016-05-01

The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

Three-dimensional mapping of microcircuit correlation structure

PubMed Central

Cotton, R. James; Froudarakis, Emmanouil; Storer, Patrick; Saggau, Peter; Tolias, Andreas S.

2013-01-01

Great progress has been made toward understanding the properties of single neurons, yet the principles underlying interactions between neurons remain poorly understood. Given that connectivity in the neocortex is locally dense through both horizontal and vertical connections, it is of particular importance to characterize the activity structure of local populations of neurons arranged in three dimensions. However, techniques for simultaneously measuring microcircuit activity are lacking. We developed an in vivo 3D high-speed, random-access two-photon microscope that is capable of simultaneous 3D motion tracking. This allows imaging from hundreds of neurons at several hundred Hz, while monitoring tissue movement. Given that motion will induce common artifacts across the population, accurate motion tracking is absolutely necessary for studying population activity with random-access based imaging methods. We demonstrate the potential of this imaging technique by measuring the correlation structure of large populations of nearby neurons in the mouse visual cortex, and find that the microcircuit correlation structure is stimulus-dependent. Three-dimensional random access multiphoton imaging with concurrent motion tracking provides a novel, powerful method to characterize the microcircuit activity in vivo. PMID:24133414

Near-infrared fluorescence imaging of experimentally collagen-induced arthritis in rats using the nonspecific dye tetrasulfocyanine in comparison with gadolinium-based contrast-enhanced magnetic resonance imaging, histology, and clinical score

NASA Astrophysics Data System (ADS)

Gemeinhardt, Ines; Puls, Dorothee; Gemeinhardt, Ole; Taupitz, Matthias; Wagner, Susanne; Schnorr, Beatrix; Licha, Kai; Schirner, Michael; Ebert, Bernd; Petzelt, Diethard; Macdonald, Rainer; Schnorr, Jörg

2012-10-01

Using 15 rats with collagen-induced arthritis (30 joints) and 7 control rats (14 joints), we correlated the intensity of near-infrared fluorescence (NIRF) of the nonspecific dye tetrasulfocyanine (TSC) with magnetic resonance imaging (MRI), histopathology, and clinical score. Fluorescence images were obtained in reflection geometry using a NIRF camera system. Normalized fluorescence intensity (INF) was determined after intravenous dye administration on different time points up to 120 min. Contrast-enhanced MRI using gadodiamide was performed after NIRF imaging. Analyses were performed in a blinded fashion. Histopathological and clinical scores were determined for each ankle joint. INF of moderate and high-grade arthritic joints were significantly higher (p<0.005) than the values of control and low-grade arthritic joints between 5 and 30 min after TSC-injection. This result correlated well with post-contrast MRI signal intensities at about 5 min after gadodiamide administration. Furthermore, INF and signal increase on contrast-enhanced MRI showed high correlation with clinical and histopathological scores. Sensitivities and specificities for detection of moderate and high-grade arthritic joints were slightly lower for NIRF imaging (89%/81%) than for MRI (100%/91%). NIRF imaging using TSC, which is characterized by slower plasma clearance compared to indocyanine green (ICG), has the potential to improve monitoring of inflamed joints.

A near-infrared fluorescence-based surgical navigation system imaging software for sentinel lymph node detection

NASA Astrophysics Data System (ADS)

Ye, Jinzuo; Chi, Chongwei; Zhang, Shuang; Ma, Xibo; Tian, Jie

2014-02-01

Sentinel lymph node (SLN) in vivo detection is vital in breast cancer surgery. A new near-infrared fluorescence-based surgical navigation system (SNS) imaging software, which has been developed by our research group, is presented for SLN detection surgery in this paper. The software is based on the fluorescence-based surgical navigation hardware system (SNHS) which has been developed in our lab, and is designed specifically for intraoperative imaging and postoperative data analysis. The surgical navigation imaging software consists of the following software modules, which mainly include the control module, the image grabbing module, the real-time display module, the data saving module and the image processing module. And some algorithms have been designed to achieve the performance of the software, for example, the image registration algorithm based on correlation matching. Some of the key features of the software include: setting the control parameters of the SNS; acquiring, display and storing the intraoperative imaging data in real-time automatically; analysis and processing of the saved image data. The developed software has been used to successfully detect the SLNs in 21 cases of breast cancer patients. In the near future, we plan to improve the software performance and it will be extensively used for clinical purpose.

[Present status and trend of heart fluid mechanics research based on medical image analysis].

PubMed

Gan, Jianhong; Yin, Lixue; Xie, Shenghua; Li, Wenhua; Lu, Jing; Luo, Anguo

2014-06-01

With introduction of current main methods for heart fluid mechanics researches, we studied the characteristics and weakness for three primary analysis methods based on magnetic resonance imaging, color Doppler ultrasound and grayscale ultrasound image, respectively. It is pointed out that particle image velocity (PIV), speckle tracking and block match have the same nature, and three algorithms all adopt block correlation. The further analysis shows that, with the development of information technology and sensor, the research for cardiac function and fluid mechanics will focus on energy transfer process of heart fluid, characteristics of Chamber wall related to blood fluid and Fluid-structure interaction in the future heart fluid mechanics fields.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hirvonen, Liisa M.; Le Marois, Alix; Suhling, Klaus, E-mail: klaus.suhling@kcl.ac.uk

We perform wide-field time-correlated single photon counting-based fluorescence lifetime imaging (FLIM) with a crossed delay line anode image intensifier, where the pulse propagation time yields the photon position. This microchannel plate-based detector was read out with conventional fast timing electronics and mounted on a fluorescence microscope with total internal reflection (TIR) illumination. The picosecond time resolution of this detection system combines low illumination intensity of microwatts with wide-field data collection. This is ideal for fluorescence lifetime imaging of cell membranes using TIR. We show that fluorescence lifetime images of living HeLa cells stained with membrane dye di-4-ANEPPDHQ exhibit a reducedmore » lifetime near the coverslip in TIR compared to epifluorescence FLIM.« less

Breast density estimation from high spectral and spatial resolution MRI

PubMed Central

Li, Hui; Weiss, William A.; Medved, Milica; Abe, Hiroyuki; Newstead, Gillian M.; Karczmar, Gregory S.; Giger, Maryellen L.

2016-01-01

Abstract. A three-dimensional breast density estimation method is presented for high spectral and spatial resolution (HiSS) MR imaging. Twenty-two patients were recruited (under an Institutional Review Board--approved Health Insurance Portability and Accountability Act-compliant protocol) for high-risk breast cancer screening. Each patient received standard-of-care clinical digital x-ray mammograms and MR scans, as well as HiSS scans. The algorithm for breast density estimation includes breast mask generating, breast skin removal, and breast percentage density calculation. The inter- and intra-user variabilities of the HiSS-based density estimation were determined using correlation analysis and limits of agreement. Correlation analysis was also performed between the HiSS-based density estimation and radiologists’ breast imaging-reporting and data system (BI-RADS) density ratings. A correlation coefficient of 0.91 (p<0.0001) was obtained between left and right breast density estimations. An interclass correlation coefficient of 0.99 (p<0.0001) indicated high reliability for the inter-user variability of the HiSS-based breast density estimations. A moderate correlation coefficient of 0.55 (p=0.0076) was observed between HiSS-based breast density estimations and radiologists’ BI-RADS. In summary, an objective density estimation method using HiSS spectral data from breast MRI was developed. The high reproducibility with low inter- and low intra-user variabilities shown in this preliminary study suggest that such a HiSS-based density metric may be potentially beneficial in programs requiring breast density such as in breast cancer risk assessment and monitoring effects of therapy. PMID:28042590

A Comparative Study of Random Patterns for Digital Image Correlation

NASA Astrophysics Data System (ADS)

Stoilov, G.; Kavardzhikov, V.; Pashkouleva, D.

2012-06-01

Digital Image Correlation (DIC) is a computer based image analysis technique utilizing random patterns, which finds applications in experimental mechanics of solids and structures. In this paper a comparative study of three simulated random patterns is done. One of them is generated according to a new algorithm, introduced by the authors. A criterion for quantitative evaluation of random patterns after the calculation of their autocorrelation functions is introduced. The patterns' deformations are simulated numerically and realized experimentally. The displacements are measured by using the DIC method. Tensile tests are performed after printing the generated random patterns on surfaces of standard iron sheet specimens. It is found that the new designed random pattern keeps relatively good quality until reaching 20% deformation.

Correlating subcortical interhemispheric connectivity and cortical hemispheric dominance in brain tumor patients: A repetitive navigated transcranial magnetic stimulation study.

PubMed

Sollmann, Nico; Ille, Sebastian; Tussis, Lorena; Maurer, Stefanie; Hauck, Theresa; Negwer, Chiara; Bauer, Jan S; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-02-01

The present study aims to investigate the relationship between transcallosal interhemispheric connectivity (IC) and hemispheric language lateralization by using a novel approach including repetitive navigated transcranial magnetic stimulation (rTMS), hemispheric dominance ratio (HDR) calculation, and rTMS-based diffusion tensor imaging fiber tracking (DTI FT). 31 patients with left-sided perisylvian brain lesions underwent diffusion tensor imaging (DTI) and rTMS language mapping. Cortical language-positive rTMS spots were used to calculate HDRs (HDR: quotient of the left-sided divided by right-sided naming error rates for corresponding left- and right-sided cortical regions) and to create regions of interest (ROIs) for DTI FT. Then, fibers connecting the rTMS-based ROIs of both hemispheres were tracked, and the correlation of IC to HDRs was calculated via Spearman's rank correlation coefficient (rs). Fibers connecting rTMS-based ROIs of both hemispheres were detected in 12 patients (38.7%). Within the patients in which IC was detected, the mean number of subcortical IC fibers ± standard deviation (SD) was 138.0 ± 346.5 (median: 7.5; range: 1-1,217 fibers). Regarding rs for the correlation of HDRs and fiber numbers of patients that showed IC, only moderate correlation was revealed. Our approach might be beneficial and technically feasible for further investigation of the relationship between IC and language lateralization. However, only moderate correlation was revealed in the present study. Copyright © 2015 Elsevier B.V. All rights reserved.

Improving Functional MRI Registration Using Whole-Brain Functional Correlation Tensors.

PubMed

Zhou, Yujia; Yap, Pew-Thian; Zhang, Han; Zhang, Lichi; Feng, Qianjin; Shen, Dinggang

2017-09-01

Population studies of brain function with resting-state functional magnetic resonance imaging (rs-fMRI) largely rely on the accurate inter-subject registration of functional areas. This is typically achieved through registration of the corresponding T1-weighted MR images with more structural details. However, accumulating evidence has suggested that such strategy cannot well-align functional regions which are not necessarily confined by the anatomical boundaries defined by the T1-weighted MR images. To mitigate this problem, various registration algorithms based directly on rs-fMRI data have been developed, most of which have utilized functional connectivity (FC) as features for registration. However, most of the FC-based registration methods usually extract the functional features only from the thin and highly curved cortical grey matter (GM), posing a great challenge in accurately estimating the whole-brain deformation field. In this paper, we demonstrate that the additional useful functional features can be extracted from brain regions beyond the GM, particularly, white-matter (WM) based on rs-fMRI, for improving the overall functional registration. Specifically, we quantify the local anisotropic correlation patterns of the blood oxygenation level-dependent (BOLD) signals, modeled by functional correlation tensors (FCTs), in both GM and WM. Functional registration is then performed based on multiple components of the whole-brain FCTs using a multichannel Large Deformation Diffeomorphic Metric Mapping (mLDDMM) algorithm. Experimental results show that our proposed method achieves superior functional registration performance, compared with other conventional registration methods.

Image-based ELISA on an activated polypropylene microtest plate--a spectrophotometer-free low cost assay technique.

PubMed

Parween, Shahila; Nahar, Pradip

2013-10-15

In this communication, we report ELISA technique on an activated polypropylene microtest plate (APPµTP) as an illustrative example of a low cost diagnostic assay. Activated test zone in APPµTP binds a capture biomolecule through covalent linkage thereby, eliminating non-specific binding often prevalent in absorption based techniques. Efficacy of APPµTP is demonstrated by detecting human immunoglobulin G (IgG), human immunoglobulin E (IgE) and Aspergillus fumigatus antibody in patient's sera. Detection is done by taking the image of the assay solution by a desktop scanner and analyzing the color of the image. Human IgE quantification by color saturation in the image-based assay shows excellent correlation with absorbance-based assay (Pearson correlation coefficient, r=0.992). Significance of the relationship is seen from its p value which is 4.087e-11. Performance of APPµTP is also checked with respect to microtiter plate and paper-based ELISA. APPµTP can quantify an analyte as precisely as in microtiter plate with insignificant non-specific binding, a necessary prerequisite for ELISA assay. In contrast, paper-ELISA shows high non-specific binding in control sera (false positive). Finally, we have carried out ELISA steps on APPµTP by ultrasound waves on a sonicator bath and the results show that even in 8 min, it can convincingly differentiate a test sample from a control sample. In short, spectrophotometer-free image-based miniaturized ELISA on APPµTP is precise, reliable, rapid, and sensitive and could be a good substitute for conventional immunoassay procedures widely used in clinical and research laboratories. Copyright © 2013 Elsevier B.V. All rights reserved.

Relevant Scatterers Characterization in SAR Images

NASA Astrophysics Data System (ADS)

Chaabouni, Houda; Datcu, Mihai

2006-11-01

Recognizing scenes in a single look meter resolution Synthetic Aperture Radar (SAR) images, requires the capability to identify relevant signal signatures in condition of variable image acquisition geometry, arbitrary objects poses and configurations. Among the methods to detect relevant scatterers in SAR images, we can mention the internal coherence. The SAR spectrum splitted in azimuth generates a series of images which preserve high coherence only for particular object scattering. The detection of relevant scatterers can be done by correlation study or Independent Component Analysis (ICA) methods. The present article deals with the state of the art for SAR internal correlation analysis and proposes further extensions using elements of inference based on information theory applied to complex valued signals. The set of azimuth looks images is analyzed using mutual information measures and an equivalent channel capacity is derived. The localization of the "target" requires analysis in a small image window, thus resulting in imprecise estimation of the second order statistics of the signal. For a better precision, a Hausdorff measure is introduced. The method is applied to detect and characterize relevant objects in urban areas.

Ghost imaging based on Pearson correlation coefficients

NASA Astrophysics Data System (ADS)

Yu, Wen-Kai; Yao, Xu-Ri; Liu, Xue-Feng; Li, Long-Zhen; Zhai, Guang-Jie

2015-05-01

Correspondence imaging is a new modality of ghost imaging, which can retrieve a positive/negative image by simple conditional averaging of the reference frames that correspond to relatively large/small values of the total intensity measured at the bucket detector. Here we propose and experimentally demonstrate a more rigorous and general approach in which a ghost image is retrieved by calculating a Pearson correlation coefficient between the bucket detector intensity and the brightness at a given pixel of the reference frames, and at the next pixel, and so on. Furthermore, we theoretically provide a statistical interpretation of these two imaging phenomena, and explain how the error depends on the sample size and what kind of distribution the error obeys. According to our analysis, the image signal-to-noise ratio can be greatly improved and the sampling number reduced by means of our new method. Project supported by the National Key Scientific Instrument and Equipment Development Project of China (Grant No. 2013YQ030595) and the National High Technology Research and Development Program of China (Grant No. 2013AA122902).

Efficient moving target analysis for inverse synthetic aperture radar images via joint speeded-up robust features and regular moment

NASA Astrophysics Data System (ADS)

Yang, Hongxin; Su, Fulin

2018-01-01

We propose a moving target analysis algorithm using speeded-up robust features (SURF) and regular moment in inverse synthetic aperture radar (ISAR) image sequences. In our study, we first extract interest points from ISAR image sequences by SURF. Different from traditional feature point extraction methods, SURF-based feature points are invariant to scattering intensity, target rotation, and image size. Then, we employ a bilateral feature registering model to match these feature points. The feature registering scheme can not only search the isotropic feature points to link the image sequences but also reduce the error matching pairs. After that, the target centroid is detected by regular moment. Consequently, a cost function based on correlation coefficient is adopted to analyze the motion information. Experimental results based on simulated and real data validate the effectiveness and practicability of the proposed method.

An image based information system - Architecture for correlating satellite and topological data bases

NASA Technical Reports Server (NTRS)

Bryant, N. A.; Zobrist, A. L.

1978-01-01

The paper describes the development of an image based information system and its use to process a Landsat thematic map showing land use or land cover in conjunction with a census tract polygon file to produce a tabulation of land use acreages per census tract. The system permits the efficient cross-tabulation of two or more geo-coded data sets, thereby setting the stage for the practical implementation of models of diffusion processes or cellular transformation. Characteristics of geographic information systems are considered, and functional requirements, such as data management, geocoding, image data management, and data analysis are discussed. The system is described, and the potentialities of its use are examined.

Imaging subsurface hydrothermal structure using a dense geophone array in Yellowstone

NASA Astrophysics Data System (ADS)

Wu, S. M.; Lin, F. C.; Farrell, J.; Smith, R. B.

2016-12-01

The recent development of ambient noise cross-correlation and the availability of large N seismic arrays allow for the study of detailed shallow crustal structure. In this study, we apply multi-component noise cross-correlation to explore shallow hydrothermal structure near Old Faithful geyser in Yellowstone National Park using a temporary geophone array. The array was composed of 133 three-component 5-Hz geophones and was deployed for two weeks during November 2015. The average station spacing is 50 meters and the full aperture of the array is around 1 km with good azimuthal and spatial coverage. The Upper Geyser Basin, where Old Faithful is located, has the largest concentration of geysers in the world. This unique active hydrothermal environment and hence the extremely inhomogeneous noise source distribution makes the construction of empirical Green's functions difficult based on the traditional noise cross-correlation method. In this presentation, we show examples of the constructed cross-correlation functions and demonstrate their spatial and temporal relationships with known hydrothermal activity. We also demonstrate how useful seismic signals can be extracted from these cross-correlation functions and used for subsurface imaging. In particular, we will discuss the existence of a recharge cavity beneath Old Faithful revealed by the noise cross-correlations. In addition, we also investigated the temporal structure variation based on time-lapse noise cross-correlations and these preliminary results will also be discussed.

A novel speckle pattern—Adaptive digital image correlation approach with robust strain calculation

NASA Astrophysics Data System (ADS)

Cofaru, Corneliu; Philips, Wilfried; Van Paepegem, Wim

2012-02-01

Digital image correlation (DIC) has seen widespread acceptance and usage as a non-contact method for the determination of full-field displacements and strains in experimental mechanics. The advances of imaging hardware in the last decades led to high resolution and speed cameras being more affordable than in the past making large amounts of data image available for typical DIC experimental scenarios. The work presented in this paper is aimed at maximizing both the accuracy and speed of DIC methods when employed with such images. A low-level framework for speckle image partitioning which replaces regularly shaped blocks with image-adaptive cells in the displacement calculation is introduced. The Newton-Raphson DIC method is modified to use the image pixels of the cells and to perform adaptive regularization to increase the spatial consistency of the displacements. Furthermore, a novel robust framework for strain calculation based also on the Newton-Raphson algorithm is introduced. The proposed methods are evaluated in five experimental scenarios, out of which four use numerically deformed images and one uses real experimental data. Results indicate that, as the desired strain density increases, significant computational gains can be obtained while maintaining or improving accuracy and rigid-body rotation sensitivity.

Neural correlates of long-term intense romantic love.

PubMed

Acevedo, Bianca P; Aron, Arthur; Fisher, Helen E; Brown, Lucy L

2012-02-01

The present study examined the neural correlates of long-term intense romantic love using functional magnetic resonance imaging (fMRI). Ten women and 7 men married an average of 21.4 years underwent fMRI while viewing facial images of their partner. Control images included a highly familiar acquaintance; a close, long-term friend; and a low-familiar person. Effects specific to the intensely loved, long-term partner were found in: (i) areas of the dopamine-rich reward and basal ganglia system, such as the ventral tegmental area (VTA) and dorsal striatum, consistent with results from early-stage romantic love studies; and (ii) several regions implicated in maternal attachment, such as the globus pallidus (GP), substantia nigra, Raphe nucleus, thalamus, insular cortex, anterior cingulate and posterior cingulate. Correlations of neural activity in regions of interest with widely used questionnaires showed: (i) VTA and caudate responses correlated with romantic love scores and inclusion of other in the self; (ii) GP responses correlated with friendship-based love scores; (iii) hypothalamus and posterior hippocampus responses correlated with sexual frequency; and (iv) caudate, septum/fornix, posterior cingulate and posterior hippocampus responses correlated with obsession. Overall, results suggest that for some individuals the reward-value associated with a long-term partner may be sustained, similar to new love, but also involves brain systems implicated in attachment and pair-bonding.

Neural correlates of long-term intense romantic love

PubMed Central

Aron, Arthur; Fisher, Helen E.; Brown, Lucy L.

2012-01-01

The present study examined the neural correlates of long-term intense romantic love using functional magnetic resonance imaging (fMRI). Ten women and 7 men married an average of 21.4 years underwent fMRI while viewing facial images of their partner. Control images included a highly familiar acquaintance; a close, long-term friend; and a low-familiar person. Effects specific to the intensely loved, long-term partner were found in: (i) areas of the dopamine-rich reward and basal ganglia system, such as the ventral tegmental area (VTA) and dorsal striatum, consistent with results from early-stage romantic love studies; and (ii) several regions implicated in maternal attachment, such as the globus pallidus (GP), substantia nigra, Raphe nucleus, thalamus, insular cortex, anterior cingulate and posterior cingulate. Correlations of neural activity in regions of interest with widely used questionnaires showed: (i) VTA and caudate responses correlated with romantic love scores and inclusion of other in the self; (ii) GP responses correlated with friendship-based love scores; (iii) hypothalamus and posterior hippocampus responses correlated with sexual frequency; and (iv) caudate, septum/fornix, posterior cingulate and posterior hippocampus responses correlated with obsession. Overall, results suggest that for some individuals the reward-value associated with a long-term partner may be sustained, similar to new love, but also involves brain systems implicated in attachment and pair-bonding. PMID:21208991

Atlas-based automatic measurements of the morphology of the tibiofemoral joint

NASA Astrophysics Data System (ADS)

Brehler, M.; Thawait, G.; Shyr, W.; Ramsay, J.; Siewerdsen, J. H.; Zbijewski, W.

2017-03-01

Purpose: Anatomical metrics of the tibiofemoral joint support assessment of joint stability and surgical planning. We propose an automated, atlas-based algorithm to streamline the measurements in 3D images of the joint and reduce userdependence of the metrics arising from manual identification of the anatomical landmarks. Methods: The method is initialized with coarse registrations of a set of atlas images to the fixed input image. The initial registrations are then refined separately for the tibia and femur and the best matching atlas is selected. Finally, the anatomical landmarks of the best matching atlas are transformed onto the input image by deforming a surface model of the atlas to fit the shape of the tibial plateau in the input image (a mesh-to-volume registration). We apply the method to weight-bearing volumetric images of the knee obtained from 23 subjects using an extremity cone-beam CT system. Results of the automated algorithm were compared to an expert radiologist for measurements of Static Alignment (SA), Medial Tibial Slope (MTS) and Lateral Tibial Slope (LTS). Results: Intra-reader variability as high as 10% for LTS and 7% for MTS (ratio of standard deviation to the mean in repeated measurements) was found for expert radiologist, illustrating the potential benefits of an automated approach in improving the precision of the metrics. The proposed method achieved excellent registration of the atlas mesh to the input volumes. The resulting automated measurements yielded high correlations with expert radiologist, as indicated by correlation coefficients of 0.72 for MTS, 0.8 for LTS, and 0.89 for SA. Conclusions: The automated method for measurement of anatomical metrics of the tibiofemoral joint achieves high correlation with expert radiologist without the need for time consuming and error prone manual selection of landmarks.

Atlas-based automatic measurements of the morphology of the tibiofemoral joint.

PubMed

Brehler, M; Thawait, G; Shyr, W; Ramsay, J; Siewerdsen, J H; Zbijewski, W

2017-02-11

Anatomical metrics of the tibiofemoral joint support assessment of joint stability and surgical planning. We propose an automated, atlas-based algorithm to streamline the measurements in 3D images of the joint and reduce user-dependence of the metrics arising from manual identification of the anatomical landmarks. The method is initialized with coarse registrations of a set of atlas images to the fixed input image. The initial registrations are then refined separately for the tibia and femur and the best matching atlas is selected. Finally, the anatomical landmarks of the best matching atlas are transformed onto the input image by deforming a surface model of the atlas to fit the shape of the tibial plateau in the input image (a mesh-to-volume registration). We apply the method to weight-bearing volumetric images of the knee obtained from 23 subjects using an extremity cone-beam CT system. Results of the automated algorithm were compared to an expert radiologist for measurements of Static Alignment (SA), Medial Tibial Slope (MTS) and Lateral Tibial Slope (LTS). Intra-reader variability as high as ~10% for LTS and 7% for MTS (ratio of standard deviation to the mean in repeated measurements) was found for expert radiologist, illustrating the potential benefits of an automated approach in improving the precision of the metrics. The proposed method achieved excellent registration of the atlas mesh to the input volumes. The resulting automated measurements yielded high correlations with expert radiologist, as indicated by correlation coefficients of 0.72 for MTS, 0.8 for LTS, and 0.89 for SA. The automated method for measurement of anatomical metrics of the tibiofemoral joint achieves high correlation with expert radiologist without the need for time consuming and error prone manual selection of landmarks.

High-b-value diffusion-weighted MR imaging for pretreatment prediction and early monitoring of tumor response to therapy in mice.

PubMed

Roth, Yiftach; Tichler, Thomas; Kostenich, Genady; Ruiz-Cabello, Jesus; Maier, Stephan E; Cohen, Jack S; Orenstein, Arie; Mardor, Yael

2004-09-01

To evaluate the use of diffusion-weighted magnetic resonance (MR) imaging with standard and high b values for pretreatment prediction and early detection of tumor response to various antineoplastic therapies in an animal model. Mice bearing C26 colon carcinoma tumors were treated with doxorubicin (n = 25) and with aminolevulinic acid-based photodynamic therapy (n = 23). Fourteen mice served as controls. Conventional T2-weighted fast spin-echo and diffusion-weighted MR images were acquired once before therapy and at 6, 24, and 48 hours after treatment. Pretreatment and early (1-2 days) posttreatment water diffusion parameters were calculated and compared with later changes in tumor volumes measured on conventional MR images by using the Pearson correlation test. In chemotherapy-treated tumors, a significant correlation (P <.002, r = 0.6) was observed between diffusion parameters that reflected tumor viability, measured prior to treatment, and changes in tumor volumes after therapy. This correlation implies that tumors with high pretreatment viability will respond better to chemotherapy than more necrotic tumors. In tumors treated with photodynamic therapy, no such correlation was found. Changes observed in water diffusion 1-2 days after treatment significantly correlated with later tumor growth rate for both therapies (P <.002, r = 0.54 for photodynamic therapy; P <.0003, r = 0.61 for chemotherapy). High-b-value diffusion-weighted MR imaging has potential use for the early detection of response to therapy and for predicting treatment outcome prior to initiation of chemotherapy. Copyright RSNA, 2004

Characterization and simulation of noise in PET images reconstructed with OSEM: Development of a method for the generation of synthetic images.

PubMed

Castro, P; Huerga, C; Chamorro, P; Garayoa, J; Roch, M; Pérez, L

2018-04-17

The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18 F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF. Copyright © 2018 Sociedad Española de Medicina Nuclear e Imagen Molecular. Publicado por Elsevier España, S.L.U. All rights reserved.

Application of 3D-MR image registration to monitor diseases around the knee joint.

PubMed

Takao, Masaki; Sugano, Nobuhiko; Nishii, Takashi; Miki, Hidenobu; Koyama, Tsuyoshi; Masumoto, Jun; Sato, Yoshinobu; Tamura, Shinichi; Yoshikawa, Hideki

2005-11-01

To estimate the accuracy and consistency of a method using a voxel-based MR image registration algorithm for precise monitoring of knee joint diseases. Rigid body transformation was calculated using a normalized cross-correlation (NCC) algorithm involving simple manual segmentation of the bone region based on its anatomical features. The accuracy of registration was evaluated using four phantoms, followed by a consistency test using MR data from the 11 patients with knee joint disease. The registration accuracy in the phantom experiment was 0.49+/-0.19 mm (SD) for the femur and 0.56+/-0.21 mm (SD) for the tibia. The consistency value in the experiment using clinical data was 0.69+/-0.25 mm (SD) for the femur and 0.77+/-0.37 mm (SD) for the tibia. These values were all smaller than a voxel (1.25 x 1.25 x 1.5 mm). The present method based on an NCC algorithm can be used to register serial MR images of the knee joint with error on the order of a sub-voxel. This method would be useful for precisely assessing therapeutic response and monitoring knee joint diseases; normalized cross-correlation; accuracy. J. Magn. Reson. Imaging 2005. (c) 2005 Wiley-Liss, Inc.

Correlated oxygen-sensing PLIM, cell metabolism FLIM and applications

NASA Astrophysics Data System (ADS)

Rück, A. C.; Kalinina, S.; Schäfer, P.; von Einem, B.; von Arnim, C.

2017-02-01

Correlated imaging of phosphorescence and fluorescence lifetime parameters of metabolic markers is a challenge for direct investigating mechanisms related to cell metabolism and oxygen tension. A large variety of clinical phenotypes is associated with mitochondrial defects accomplished with changes in cell metabolism. In many cases the hypoxic microenvironment of cancer cells shifts metabolism from oxidative phosphorylation (OXPHOS) to anaerobic or aerobic glycolysis, a process known as "Warburg" effect. Also during stem cell differentiation a switch in cell metabolism is observed. Mitochondrial dysfunction associated with hypoxia has been invoked in many complex disorders such as type 2 diabetes, Alzheimeŕs disease, cardiac ischemia/reperfusion injury, tissue inflammation and cancer. Cellular responses to oxygen tension have been studied extensively, optical imaging techniques based on time correlated single photon counting (TCSPC) to detect oxygen concentration and distribution are therefore of prominent interest. Moreover, they offer the possibility by inspecting fluorescence decay characteristics of intrinsic coenzymes to directly image metabolic pathways, whereas oxygen tension can be determined by considering the phosphorescence lifetime of a phosphorescent probe. The combination of both fluorescence lifetime imaging (FLIM) of coenzymes like NAD(P)H and FAD and phosphorescence lifetime (PLIM) of phosphorescent dyes could provide valuable information about correlation of metabolic pathways and oxygen tension.

Alpha trimmed correlation for touchless finger image mosaicing

NASA Astrophysics Data System (ADS)

Rao, Shishir P.; Rajendran, Rahul; Agaian, Sos S.; Mulawka, Marzena Mary Ann

2016-05-01

In this paper, a novel technique to mosaic multiview contactless finger images is presented. This technique makes use of different correlation methods, such as, the Alpha-trimmed correlation, Pearson's correlation [1], Kendall's correlation [2], and Spearman's correlation [2], to combine multiple views of the finger. The key contributions of the algorithm are: 1) stitches images more accurately, 2) provides better image fusion effects, 3) has better visual effect on the overall image, and 4) is more reliable. The extensive computer simulations show that the proposed method produces better or comparable stitched images than several state-of-the-art methods, such as those presented by Feng Liu [3], K Choi [4], H Choi [5], and G Parziale [6]. In addition, we also compare various correlation techniques with the correlation method mentioned in [3] and analyze the output. In the future, this method can be extended to obtain a 3D model of the finger using multiple views of the finger, and help in generating scenic panoramic images and underwater 360-degree panoramas.

A novel edge based embedding in medical images based on unique key generated using sudoku puzzle design.

PubMed

Santhi, B; Dheeptha, B

2016-01-01

The field of telemedicine has gained immense momentum, owing to the need for transmitting patients' information securely. This paper puts forth a unique method for embedding data in medical images. It is based on edge based embedding and XOR coding. The algorithm proposes a novel key generation technique by utilizing the design of a sudoku puzzle to enhance the security of the transmitted message. The edge blocks of the cover image alone, are utilized to embed the payloads. The least significant bit of the pixel values are changed by XOR coding depending on the data to be embedded and the key generated. Hence the distortion in the stego image is minimized and the information is retrieved accurately. Data is embedded in the RGB planes of the cover image, thus increasing its embedding capacity. Several measures including peak signal noise ratio (PSNR), mean square error (MSE), universal image quality index (UIQI) and correlation coefficient (R) are the image quality measures that have been used to analyze the quality of the stego image. It is evident from the results that the proposed technique outperforms the former methodologies.

Validation of multi-angle imaging spectroradiometer aerosol products in China

Treesearch

J. Liu; X. Xia; Z. Li; P. Wang; M. Min; WeiMin Hao; Y. Wang; J. Xin; X. Li; Y. Zheng; Z. Chen

2010-01-01

Based on AErosol RObotic NETwork and Chinese Sun Hazemeter Network data, the Multi-angle Imaging SpectroRadiometer (MISR) level 2 aerosol optical depth (AOD) products are evaluated in China. The MISR retrievals depict well the temporal aerosol trend in China with correlation coefficients exceeding 0.8 except for stations located in northeast China and at the...

Study of morphological changes in scattering and optically anisotropic medium through correlation images

NASA Astrophysics Data System (ADS)

Jain, Neha; Shukla, Prashant; Singh, Jai

2018-05-01

Correlation images are very useful in determining the morphological changes. We have investigated the correlation image analysis on depolarization and retardance matrices of polystyrene and gelatine samples respectively. We observed that that correlation images have a potential to show a significant variation with change in the concentration of samples (polystyrene and gelatine). For polystyrene microspheres the correlation value decreases with increasing scattering coefficient. In gelatine samples the correlation also decreases with sample concentration. This variation in correlation for retardance shows the change in a birefringence property of gelatine solution.

Neighborhood binary speckle pattern for deformation measurements insensitive to local illumination variation by digital image correlation.

PubMed

Zhao, Jian; Yang, Ping; Zhao, Yue

2017-06-01

Speckle pattern-based characteristics of digital image correlation (DIC) restrict its application in engineering fields and nonlaboratory environments, since serious decorrelation effect occurs due to localized sudden illumination variation. A simple and efficient speckle pattern adjusting and optimizing approach presented in this paper is aimed at providing a novel speckle pattern robust enough to resist local illumination variation. The new speckle pattern, called neighborhood binary speckle pattern, derived from original speckle pattern, is obtained by means of thresholding the pixels of a neighborhood at its central pixel value and considering the result as a binary number. The efficiency of the proposed speckle pattern is evaluated in six experimental scenarios. Experiment results indicate that the DIC measurements based on neighborhood binary speckle pattern are able to provide reliable and accurate results, even though local brightness and contrast of the deformed images have been seriously changed. It is expected that the new speckle pattern will have more potential value in engineering applications.

Semantic-gap-oriented active learning for multilabel image annotation.

PubMed

Tang, Jinhui; Zha, Zheng-Jun; Tao, Dacheng; Chua, Tat-Seng

2012-04-01

User interaction is an effective way to handle the semantic gap problem in image annotation. To minimize user effort in the interactions, many active learning methods were proposed. These methods treat the semantic concepts individually or correlatively. However, they still neglect the key motivation of user feedback: to tackle the semantic gap. The size of the semantic gap of each concept is an important factor that affects the performance of user feedback. User should pay more efforts to the concepts with large semantic gaps, and vice versa. In this paper, we propose a semantic-gap-oriented active learning method, which incorporates the semantic gap measure into the information-minimization-based sample selection strategy. The basic learning model used in the active learning framework is an extended multilabel version of the sparse-graph-based semisupervised learning method that incorporates the semantic correlation. Extensive experiments conducted on two benchmark image data sets demonstrated the importance of bringing the semantic gap measure into the active learning process.

Quantitative multiplex immunohistochemistry reveals myeloid-inflamed tumor-immune complexity associated with poor prognosis

PubMed Central

Tsujikawa, Takahiro; Kumar, Sushil; Borkar, Rohan N.; Azimi, Vahid; Thibault, Guillaume; Chang, Young Hwan; Balter, Ariel; Kawashima, Rie; Choe, Gina; Sauer, David; El Rassi, Edward; Clayburgh, Daniel R.; Kulesz-Martin, Molly F.; Lutz, Eric R.; Zheng, Lei; Jaffee, Elizabeth M.; Leyshock, Patrick; Margolin, Adam A.; Mori, Motomi; Gray, Joe W.; Flint, Paul W.; Coussens, Lisa M.

2017-01-01

SUMMARY Here we describe a multiplexed immunohistochemical platform, with computational image processing workflows including image cytometry, enabling simultaneous evaluation of 12 biomarkers in one formalin-fixed paraffin-embedded tissue section. To validate this platform, we used tissue microarrays containing 38 archival head and neck squamous cell carcinomas, and revealed differential immune profiles based on lymphoid and myeloid cell densities, correlating with human papilloma virus status and prognosis. Based on these results, we investigated 24 pancreatic ductal adenocarcinomas from patients who received neoadjuvant GVAX vaccination, and revealed that response to therapy correlated with degree of mono-myelocytic cell density, and percentages of CD8+ T cells expressing T cell exhaustion markers. These data highlight the utility of in situ immune monitoring for patient stratification, and provide digital image processing pipelines (https://github.com/multiplexIHC/cppipe) to the community for examining immune complexity in precious tissue sections, where phenotype and tissue architecture are preserved to thus improve biomarker discovery and assessment. PMID:28380359

Imaging model for the scintillator and its application to digital radiography image enhancement.

PubMed

Wang, Qian; Zhu, Yining; Li, Hongwei

2015-12-28

Digital Radiography (DR) images obtained by OCD-based (optical coupling detector) Micro-CT system usually suffer from low contrast. In this paper, a mathematical model is proposed to describe the image formation process in scintillator. By solving the correlative inverse problem, the quality of DR images is improved, i.e. higher contrast and spatial resolution. By analyzing the radiative transfer process of visible light in scintillator, scattering is recognized as the main factor leading to low contrast. Moreover, involved blurring effect is also concerned and described as point spread function (PSF). Based on these physical processes, the scintillator imaging model is then established. When solving the inverse problem, pre-correction to the intensity of x-rays, dark channel prior based haze removing technique, and an effective blind deblurring approach are employed. Experiments on a variety of DR images show that the proposed approach could improve the contrast of DR images dramatically as well as eliminate the blurring vision effectively. Compared with traditional contrast enhancement methods, such as CLAHE, our method could preserve the relative absorption values well.

Modified interferometric imaging condition for reverse-time migration

NASA Astrophysics Data System (ADS)

Guo, Xue-Bao; Liu, Hong; Shi, Ying

2018-01-01

For reverse-time migration, high-resolution imaging mainly depends on the accuracy of the velocity model and the imaging condition. In practice, however, the small-scale components of the velocity model cannot be estimated by tomographical methods; therefore, the wavefields are not accurately reconstructed from the background velocity, and the imaging process will generate artefacts. Some of the noise is due to cross-correlation of unrelated seismic events. Interferometric imaging condition suppresses imaging noise very effectively, especially the unknown random disturbance of the small-scale part. The conventional interferometric imaging condition is extended in this study to obtain a new imaging condition based on the pseudo-Wigner distribution function (WDF). Numerical examples show that the modified interferometric imaging condition improves imaging precision.

Study of image matching algorithm and sub-pixel fitting algorithm in target tracking

NASA Astrophysics Data System (ADS)

Yang, Ming-dong; Jia, Jianjun; Qiang, Jia; Wang, Jian-yu

2015-03-01

Image correlation matching is a tracking method that searched a region most approximate to the target template based on the correlation measure between two images. Because there is no need to segment the image, and the computation of this method is little. Image correlation matching is a basic method of target tracking. This paper mainly studies the image matching algorithm of gray scale image, which precision is at sub-pixel level. The matching algorithm used in this paper is SAD (Sum of Absolute Difference) method. This method excels in real-time systems because of its low computation complexity. The SAD method is introduced firstly and the most frequently used sub-pixel fitting algorithms are introduced at the meantime. These fitting algorithms can't be used in real-time systems because they are too complex. However, target tracking often requires high real-time performance, we put forward a fitting algorithm named paraboloidal fitting algorithm based on the consideration above, this algorithm is simple and realized easily in real-time system. The result of this algorithm is compared with that of surface fitting algorithm through image matching simulation. By comparison, the precision difference between these two algorithms is little, it's less than 0.01pixel. In order to research the influence of target rotation on precision of image matching, the experiment of camera rotation was carried on. The detector used in the camera is a CMOS detector. It is fixed to an arc pendulum table, take pictures when the camera rotated different angles. Choose a subarea in the original picture as the template, and search the best matching spot using image matching algorithm mentioned above. The result shows that the matching error is bigger when the target rotation angle is larger. It's an approximate linear relation. Finally, the influence of noise on matching precision was researched. Gaussian noise and pepper and salt noise were added in the image respectively, and the image was processed by mean filter and median filter, then image matching was processed. The result show that when the noise is little, mean filter and median filter can achieve a good result. But when the noise density of salt and pepper noise is bigger than 0.4, or the variance of Gaussian noise is bigger than 0.0015, the result of image matching will be wrong.

Contourlet domain multiband deblurring based on color correlation for fluid lens cameras.

PubMed

Tzeng, Jack; Liu, Chun-Chen; Nguyen, Truong Q

2010-10-01

Due to the novel fluid optics, unique image processing challenges are presented by the fluidic lens camera system. Developed for surgical applications, unique properties, such as no moving parts while zooming and better miniaturization than traditional glass optics, are advantages of the fluid lens. Despite these abilities, sharp color planes and blurred color planes are created by the nonuniform reaction of the liquid lens to different color wavelengths. Severe axial color aberrations are caused by this reaction. In order to deblur color images without estimating a point spread function, a contourlet filter bank system is proposed. Information from sharp color planes is used by this multiband deblurring method to improve blurred color planes. Compared to traditional Lucy-Richardson and Wiener deconvolution algorithms, significantly improved sharpness and reduced ghosting artifacts are produced by a previous wavelet-based method. Directional filtering is used by the proposed contourlet-based system to adjust to the contours of the image. An image is produced by the proposed method which has a similar level of sharpness to the previous wavelet-based method and has fewer ghosting artifacts. Conditions for when this algorithm will reduce the mean squared error are analyzed. While improving the blue color plane by using information from the green color plane is the primary focus of this paper, these methods could be adjusted to improve the red color plane. Many multiband systems such as global mapping, infrared imaging, and computer assisted surgery are natural extensions of this work. This information sharing algorithm is beneficial to any image set with high edge correlation. Improved results in the areas of deblurring, noise reduction, and resolution enhancement can be produced by the proposed algorithm.

Quantitative analysis of hyperpolarized 129Xe ventilation imaging in healthy volunteers and subjects with chronic obstructive pulmonary disease

PubMed Central

Virgincar, Rohan S.; Cleveland, Zackary I.; Kaushik, S. Sivaram; Freeman, Matthew S.; Nouls, John; Cofer, Gary P.; Martinez-Jimenez, Santiago; He, Mu; Kraft, Monica; Wolber, Jan; McAdams, H. Page; Driehuys, Bastiaan

2013-01-01

In this study, hyperpolarized (HP) 129Xe MR ventilation and 1H anatomical images were obtained from 3 subject groups: young healthy volunteers (HV), subjects with chronic obstructive pulmonary disease (COPD), and age-matched control subjects (AMC). Ventilation images were quantified by 2 methods: an expert reader-based ventilation defect score percentage (VDS%) and a semi-automatic segmentation-based ventilation defect percentage (VDP). Reader-based values were assigned by two experienced radiologists and resolved by consensus. In the semi-automatic analysis, 1H anatomical images and 129Xe ventilation images were both segmented following registration, to obtain the thoracic cavity volume (TCV) and ventilated volume (VV), respectively, which were then expressed as a ratio to obtain the VDP. Ventilation images were also characterized by generating signal intensity histograms from voxels within the TCV, and heterogeneity was analyzed using the coefficient of variation (CV). The reader-based VDS% correlated strongly with the semi-automatically generated VDP (r = 0.97, p < 0.0001), and with CV (r = 0.82, p < 0.0001). Both 129Xe ventilation defect scoring metrics readily separated the 3 groups from one another and correlated significantly with FEV1 (VDS%: r = -0.78, p = 0.0002; VDP: r = -0.79, p = 0.0003; CV: r = -0.66, p = 0.0059) and other pulmonary function tests. In the healthy subject groups (HV and AMC), the prevalence of ventilation defects also increased with age (VDS%: r = 0.61, p = 0.0002; VDP: r = 0.63, p = 0.0002). Moreover, ventilation histograms and their associated CVs distinguished between COPD subjects with similar ventilation defect scores but visibly different ventilation patterns. PMID:23065808

Whole-brain diffusion tensor imaging in correlation to visual-evoked potentials in multiple sclerosis: a tract-based spatial statistics analysis.

PubMed

Lobsien, D; Ettrich, B; Sotiriou, K; Classen, J; Then Bergh, F; Hoffmann, K-T

2014-01-01

Functional correlates of microstructural damage of the brain affected by MS are incompletely understood. The purpose of this study was to evaluate correlations of visual-evoked potentials with microstructural brain changes as determined by DTI in patients with demyelinating central nervous disease. Sixty-one patients with clinically isolated syndrome or MS were prospectively recruited. The mean P100 visual-evoked potential latencies of the right and left eyes of each patient were calculated and used for the analysis. For DTI acquisition, a single-shot echo-planar imaging pulse sequence with 80 diffusion directions was performed at 3T. Fractional anisotropy, radial diffusivity, and axial diffusivity were calculated and correlated with mean P100 visual-evoked potentials by tract-based spatial statistics. Significant negative correlations between mean P100 visual-evoked potentials and fractional anisotropy and significant positive correlations between mean P100 visual-evoked potentials and radial diffusivity were found widespread over the whole brain. The highest significance was found in the optic radiation, frontoparietal white matter, and corpus callosum. Significant positive correlations between mean P100 visual-evoked potentials and axial diffusivity were less widespread, notably sparing the optic radiation. Microstructural changes of the whole brain correlated significantly with mean P100 visual-evoked potentials. The distribution of the correlations showed clear differences among axial diffusivity, fractional anisotropy, and radial diffusivity, notably in the optic radiation. This finding suggests a stronger correlation of mean P100 visual-evoked potentials to demyelination than to axonal damage. © 2014 by American Journal of Neuroradiology.

Functional overestimation due to spatial smoothing of fMRI data.

PubMed

Liu, Peng; Calhoun, Vince; Chen, Zikuan

2017-11-01

Pearson correlation (simply correlation) is a basic technique for neuroimage function analysis. It has been observed that the spatial smoothing may cause functional overestimation, which however remains a lack of complete understanding. Herein, we present a theoretical explanation from the perspective of correlation scale invariance. For a task-evoked spatiotemporal functional dataset, we can extract the functional spatial map by calculating the temporal correlations (tcorr) of voxel timecourses against the task timecourse. From the relationship between image noise level (changed through spatial smoothing) and the tcorr map calculation, we show that the spatial smoothing causes a noise reduction, which in turn smooths the tcorr map and leads to a spatial expansion on neuroactivity blob estimation. Through numerical simulations and subject experiments, we show that the spatial smoothing of fMRI data may overestimate activation spots in the correlation functional map. Our results suggest a small spatial smoothing (with a smoothing kernel with a full width at half maximum (FWHM) of no more than two voxels) on fMRI data processing for correlation-based functional mapping COMPARISON WITH EXISTING METHODS: In extreme noiselessness, the correlation of scale-invariance property defines a meaningless binary tcorr map. In reality, a functional activity blob in a tcorr map is shaped due to the spoilage of image noise on correlative responses. We may reduce data noise level by smoothing processing, which poses a smoothing effect on correlation. This logic allows us to understand the noise dependence and the smoothing effect of correlation-based fMRI data analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

Multimedia human brain database system for surgical candidacy determination in temporal lobe epilepsy with content-based image retrieval

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-01-01

This paper presents the development of a human brain multimedia database for surgical candidacy determination in temporal lobe epilepsy. The focus of the paper is on content-based image management, navigation and retrieval. Several medical image-processing methods including our newly developed segmentation method are utilized for information extraction/correlation and indexing. The input data includes T1-, T2-Weighted MRI and FLAIR MRI and ictal and interictal SPECT modalities with associated clinical data and EEG data analysis. The database can answer queries regarding issues such as the correlation between the attribute X of the entity Y and the outcome of a temporal lobe epilepsy surgery. The entity Y can be a brain anatomical structure such as the hippocampus. The attribute X can be either a functionality feature of the anatomical structure Y, calculated with SPECT modalities, such as signal average, or a volumetric/morphological feature of the entity Y such as volume or average curvature. The outcome of the surgery can be any surgery assessment such as memory quotient. A determination is made regarding surgical candidacy by analysis of both textual and image data. The current database system suggests a surgical determination for the cases with relatively small hippocampus and high signal intensity average on FLAIR images within the hippocampus. This indication pretty much fits with the surgeons" expectations/observations. Moreover, as the database gets more populated with patient profiles and individual surgical outcomes, using data mining methods one may discover partially invisible correlations between the contents of different modalities of data and the outcome of the surgery.

Prediction of fracture profile using digital image correlation

NASA Astrophysics Data System (ADS)

Chaitanya, G. M. S. K.; Sasi, B.; Kumar, Anish; Babu Rao, C.; Purnachandra Rao, B.; Jayakumar, T.

2015-04-01

Digital Image Correlation (DIC) based full field strain mapping methodology is used for mapping strain on an aluminum sample subjected to tensile deformation. The local strains on the surface of the specimen are calculated at different strain intervals. Early localization of strain is observed at a total strain of 0.050ɛ; itself, whereas a visually apparent localization of strain is observed at a total strain of 0.088ɛ;. Orientation of the line of fracture (12.0°) is very close to the orientation of locus of strain maxima (11.6°) computed from the strain mapping at 0.063ɛ itself. These results show the efficacy of the DIC based method to predict the location as well as the profile of the fracture, at an early stage.

Diffuse shear wave imaging: toward passive elastography using low-frame rate spectral-domain optical coherence tomography

NASA Astrophysics Data System (ADS)

Nguyen, Thu-Mai; Zorgani, Ali; Lescanne, Maxime; Boccara, Claude; Fink, Mathias; Catheline, Stefan

2016-12-01

Optical coherence tomography (OCT) can map the stiffness of biological tissue by imaging mechanical perturbations (shear waves) propagating in the tissue. Most shear wave elastography (SWE) techniques rely on active shear sources to generate controlled displacements that are tracked at ultrafast imaging rates. Here, we propose a noise-correlation approach to retrieve stiffness information from the imaging of diffuse displacement fields using low-frame rate spectral-domain OCT. We demonstrated the method on tissue-mimicking phantoms and validated the results by comparison with classic ultrafast SWE. Then we investigated the in vivo feasibility on the eye of an anesthetized rat by applying noise correlation to naturally occurring displacements. The results suggest a great potential for passive elastography based on the detection of natural pulsatile motions using conventional spectral-domain OCT systems. This would facilitate the transfer of OCT-elastography to clinical practice, in particular, in ophthalmology or dermatology.

Diffuse shear wave imaging: toward passive elastography using low-frame rate spectral-domain optical coherence tomography.

PubMed

Nguyen, Thu-Mai; Zorgani, Ali; Lescanne, Maxime; Boccara, Claude; Fink, Mathias; Catheline, Stefan

2016-12-01

Optical coherence tomography (OCT) can map the stiffness of biological tissue by imaging mechanical perturbations (shear waves) propagating in the tissue. Most shear wave elastography (SWE) techniques rely on active shear sources to generate controlled displacements that are tracked at ultrafast imaging rates. Here, we propose a noise-correlation approach to retrieve stiffness information from the imaging of diffuse displacement fields using low-frame rate spectral-domain OCT. We demonstrated the method on tissue-mimicking phantoms and validated the results by comparison with classic ultrafast SWE. Then we investigated the in vivo feasibility on the eye of an anesthetized rat by applying noise correlation to naturally occurring displacements. The results suggest a great potential for passive elastography based on the detection of natural pulsatile motions using conventional spectral-domain OCT systems. This would facilitate the transfer of OCT-elastography to clinical practice, in particular, in ophthalmology or dermatology.

Nanoscale deformation analysis with high-resolution transmission electron microscopy and digital image correlation

DOE PAGES

Wang, Xueju; Pan, Zhipeng; Fan, Feifei; ...

2015-09-10

We present an application of the digital image correlation (DIC) method to high-resolution transmission electron microscopy (HRTEM) images for nanoscale deformation analysis. The combination of DIC and HRTEM offers both the ultrahigh spatial resolution and high displacement detection sensitivity that are not possible with other microscope-based DIC techniques. We demonstrate the accuracy and utility of the HRTEM-DIC technique through displacement and strain analysis on amorphous silicon. Two types of error sources resulting from the transmission electron microscopy (TEM) image noise and electromagnetic-lens distortions are quantitatively investigated via rigid-body translation experiments. The local and global DIC approaches are applied for themore » analysis of diffusion- and reaction-induced deformation fields in electrochemically lithiated amorphous silicon. As a result, the DIC technique coupled with HRTEM provides a new avenue for the deformation analysis of materials at the nanometer length scales.« less

Correlated Imaging – A Grand Challenge in Chemical Analysis

PubMed Central

Masyuko, Rachel; Lanni, Eric; Sweedler, Jonathan V.; Bohn, Paul W.

2013-01-01

Correlated chemical imaging is an emerging strategy for acquisition of images by combining information from multiplexed measurement platforms to track, visualize, and interpret in situ changes in the structure, organization, and activities of interesting chemical systems, frequently spanning multiple decades in space and time. Acquiring and correlating information from complementary imaging experiments has the potential to expose complex chemical behavior in ways that are simply not available from single methods applied in isolation, thereby greatly amplifying the information gathering power of imaging experiments. However, in order to correlate image information across platforms, a number of issues must be addressed. First, signals are obtained from disparate experiments with fundamentally different figures of merit, including pixel size, spatial resolution, dynamic range, and acquisition rates. In addition, images are often acquired on different instruments in different locations, so the sample must be registered spatially so that the same area of the sample landscape is addressed. The signals acquired must be correlated in both spatial and temporal domains, and the resulting information has to be presented in a way that is readily understood. These requirements pose special challenges for image cross-correlation that go well beyond those posed in single technique imaging approaches. The special opportunities and challenges that attend correlated imaging are explored by specific reference to correlated mass spectrometric and Raman imaging, a topic of substantial and growing interest. PMID:23431559

Fourier-Mellin moment-based intertwining map for image encryption

NASA Astrophysics Data System (ADS)

Kaur, Manjit; Kumar, Vijay

2018-03-01

In this paper, a robust image encryption technique that utilizes Fourier-Mellin moments and intertwining logistic map is proposed. Fourier-Mellin moment-based intertwining logistic map has been designed to overcome the issue of low sensitivity of an input image. Multi-objective Non-Dominated Sorting Genetic Algorithm (NSGA-II) based on Reinforcement Learning (MNSGA-RL) has been used to optimize the required parameters of intertwining logistic map. Fourier-Mellin moments are used to make the secret keys more secure. Thereafter, permutation and diffusion operations are carried out on input image using secret keys. The performance of proposed image encryption technique has been evaluated on five well-known benchmark images and also compared with seven well-known existing encryption techniques. The experimental results reveal that the proposed technique outperforms others in terms of entropy, correlation analysis, a unified average changing intensity and the number of changing pixel rate. The simulation results reveal that the proposed technique provides high level of security and robustness against various types of attacks.

Quantitative Rapid Assessment of Leukoaraiosis in CT : Comparison to Gold Standard MRI.

PubMed

Hanning, Uta; Sporns, Peter Bernhard; Schmidt, Rene; Niederstadt, Thomas; Minnerup, Jens; Bier, Georg; Knecht, Stefan; Kemmling, André

2017-10-20

The severity of white matter lesions (WML) is a risk factor of hemorrhage and predictor of clinical outcome after ischemic stroke; however, in contrast to magnetic resonance imaging (MRI) reliable quantification for this surrogate marker is limited for computed tomography (CT), the leading stroke imaging technique. We aimed to present and evaluate a CT-based automated rater-independent method for quantification of microangiopathic white matter changes. Patients with suspected minor stroke (National Institutes of Health Stroke scale, NIHSS < 4) were screened for the analysis of non-contrast computerized tomography (NCCT) at admission and compared to follow-up MRI. The MRI-based WML volume and visual Fazekas scores were assessed as the gold standard reference. We employed a recently published probabilistic brain segmentation algorithm for CT images to determine the tissue-specific density of WM space. All voxel-wise densities were quantified in WM space and weighted according to partial probabilistic WM content. The resulting mean weighted density of WM space in NCCT, the surrogate of WML, was correlated with reference to MRI-based WML parameters. The process of CT-based tissue-specific segmentation was reliable in 79 cases with varying severity of microangiopathy. Voxel-wise weighted density within WM spaces showed a noticeable correlation (r = -0.65) with MRI-based WML volume. Particularly in patients with moderate or severe lesion load according to the visual Fazekas score the algorithm provided reliable prediction of MRI-based WML volume. Automated observer-independent quantification of voxel-wise WM density in CT significantly correlates with microangiopathic WM disease in gold standard MRI. This rapid surrogate of white matter lesion load in CT may support objective WML assessment and therapeutic decision-making during acute stroke triage.

Efficient principal component analysis for multivariate 3D voxel-based mapping of brain functional imaging data sets as applied to FDG-PET and normal aging.

PubMed

Zuendorf, Gerhard; Kerrouche, Nacer; Herholz, Karl; Baron, Jean-Claude

2003-01-01

Principal component analysis (PCA) is a well-known technique for reduction of dimensionality of functional imaging data. PCA can be looked at as the projection of the original images onto a new orthogonal coordinate system with lower dimensions. The new axes explain the variance in the images in decreasing order of importance, showing correlations between brain regions. We used an efficient, stable and analytical method to work out the PCA of Positron Emission Tomography (PET) images of 74 normal subjects using [(18)F]fluoro-2-deoxy-D-glucose (FDG) as a tracer. Principal components (PCs) and their relation to age effects were investigated. Correlations between the projections of the images on the new axes and the age of the subjects were carried out. The first two PCs could be identified as being the only PCs significantly correlated to age. The first principal component, which explained 10% of the data set variance, was reduced only in subjects of age 55 or older and was related to loss of signal in and adjacent to ventricles and basal cisterns, reflecting expected age-related brain atrophy with enlarging CSF spaces. The second principal component, which accounted for 8% of the total variance, had high loadings from prefrontal, posterior parietal and posterior cingulate cortices and showed the strongest correlation with age (r = -0.56), entirely consistent with previously documented age-related declines in brain glucose utilization. Thus, our method showed that the effect of aging on brain metabolism has at least two independent dimensions. This method should have widespread applications in multivariate analysis of brain functional images. Copyright 2002 Wiley-Liss, Inc.

Imaging Signs in Spontaneous Intracranial Hypotension: Prevalence and Relationship to CSF Pressure.

PubMed

Kranz, P G; Tanpitukpongse, T P; Choudhury, K R; Amrhein, T J; Gray, L

2016-07-01

Patients with spontaneous intracranial hypotension often exhibit low CSF pressure and changes on brain MR imaging and/or evidence of CSF leak on myelography. We investigated whether individual imaging signs of spontaneous intracranial hypotension correlate with measured CSF pressure and how frequently these 2 markers of spontaneous intracranial hypotension were concordant. We performed a retrospective, cross-sectional study of 99 subjects with spontaneous intracranial hypotension. Prevalence of brain and myelographic imaging signs of spontaneous intracranial hypotension was recorded. CSF pressure among subjects with or without individual imaging signs was compared by using a 2-tailed t test and ANOVA. Concordance between low CSF pressure (≤6 cm H2O) and imaging was defined as the presence of the sign in a subject with low CSF pressure or absence of the sign when pressure was not low. Dural enhancement, brain sagging, and venous distension sign were present in 83%, 61%, and 75% of subjects, respectively, and myelographic evidence of CSF leak was seen in 55%. Marginal correlations between CSF pressure and brain sagging (P = .046) and the venous distension sign (P = .047) were found. Dural enhancement and myelographic evidence of leak were not significantly correlated with CSF pressure. Rates of concordance between imaging signs and low CSF pressure were generally low, ranging from 39% to 55%. Brain and myelographic signs of spontaneous intracranial hypotension correlate poorly with CSF pressure. These findings reinforce the need to base the diagnosis of spontaneous intracranial hypotension on multiple diagnostic criteria and suggest the presence of patient-specific variables that influence CSF pressure in these individuals. © 2016 by American Journal of Neuroradiology.

Polarization-multiplexing ghost imaging

NASA Astrophysics Data System (ADS)

Dongfeng, Shi; Jiamin, Zhang; Jian, Huang; Yingjian, Wang; Kee, Yuan; Kaifa, Cao; Chenbo, Xie; Dong, Liu; Wenyue, Zhu

2018-03-01

A novel technique for polarization-multiplexing ghost imaging is proposed to simultaneously obtain multiple polarimetric information by a single detector. Here, polarization-division multiplexing speckles are employed for object illumination. The light reflected from the objects is detected by a single-pixel detector. An iterative reconstruction method is used to restore the fused image containing the different polarimetric information by using the weighted sum of the multiplexed speckles based on the correlation coefficients obtained from the detected intensities. Next, clear images of the different polarimetric information are recovered by demultiplexing the fused image. The results clearly demonstrate that the proposed method is effective.

Quantitative imaging of peripheral trabecular bone microarchitecture using MDCT.

PubMed

Chen, Cheng; Zhang, Xiaoliu; Guo, Junfeng; Jin, Dakai; Letuchy, Elena M; Burns, Trudy L; Levy, Steven M; Hoffman, Eric A; Saha, Punam K

2018-01-01

Osteoporosis associated with reduced bone mineral density (BMD) and microarchitectural changes puts patients at an elevated risk of fracture. Modern multidetector row CT (MDCT) technology, producing high spatial resolution at increasingly lower dose radiation, is emerging as a viable modality for trabecular bone (Tb) imaging. Wide variation in CT scanners raises concerns of data uniformity in multisite and longitudinal studies. A comprehensive cadaveric study was performed to evaluate MDCT-derived Tb microarchitectural measures. A human pilot study was performed comparing continuity of Tb measures estimated from two MDCT scanners with significantly different image resolution features. Micro-CT imaging of cadaveric ankle specimens (n=25) was used to examine the validity of MDCT-derived Tb microarchitectural measures. Repeat scan reproducibility of MDCT-based Tb measures and their ability to predict mechanical properties were examined. To assess multiscanner data continuity of Tb measures, the distal tibias of 20 volunteers (age:26.2±4.5Y,10F) were scanned using the Siemens SOMATOM Definition Flash and the higher resolution Siemens SOMATOM Force scanners with an average 45-day time gap between scans. The correlation of Tb measures derived from the two scanners over 30% and 60% peel regions at the 4% to 8% of distal tibia was analyzed. MDCT-based Tb measures characterizing bone network area density, plate-rod microarchitecture, and transverse trabeculae showed good correlations (r∈0.85,0.92) with the gold standard micro-CT-derived values of matching Tb measures. However, other MDCT-derived Tb measures characterizing trabecular thickness and separation, erosion index, and structure model index produced weak correlation (r<0.8) with their micro-CT-derived values. Most MDCT Tb measures were found repeatable (ICC∈0.94,0.98). The Tb plate-width measure showed a strong correlation (r = 0.89) with experimental yield stress, while the transverse trabecular measure produced the highest correlation (r = 0.81) with Young's modulus. The data continuity experiment showed that, despite significant differences in image resolution between two scanners (10% MTF along xy-plane and z-direction - Flash: 16.2 and 17.9 lp/cm; Force: 24.8 and 21.0 lp/cm), most Tb measures had high Pearson correlations (r > 0.95) between values estimated from the two scanners. Relatively lower correlation coefficients were observed for the bone network area density (r = 0.91) and Tb separation (r = 0.93) measures. Most MDCT-derived Tb microarchitectural measures are reproducible and their values derived from two scanners strongly correlate with each other as well as with bone strength. This study has highlighted those MDCT-derived measures which show the greatest promise for characterization of bone network area density, plate-rod and transverse trabecular distributions with a good correlation (r ≥ 0.85) compared with their micro-CT-derived values. At the same time, other measures representing trabecular thickness and separation, erosion index, and structure model index produced weak correlations (r < 0.8) with their micro-CT-derived values, failing to accurately portray the projected trabecular microarchitectural features. Strong correlations of Tb measures estimated from two scanners suggest that image data from different scanners can be used successfully in multisite and longitudinal studies with linear calibration required for some measures. In summary, modern MDCT scanners are suitable for effective quantitative imaging of peripheral Tb microarchitecture if care is taken to focus on appropriate quantitative metrics. © 2017 American Association of Physicists in Medicine.

Cest Analysis: Automated Change Detection from Very-High Remote Sensing Images

NASA Astrophysics Data System (ADS)

Ehlers, M.; Klonus, S.; Jarmer, T.; Sofina, N.; Michel, U.; Reinartz, P.; Sirmacek, B.

2012-08-01

A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye) new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST) analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT) and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment) with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST) of the change algorithms is applied to calculate the probability of change for a particular location. CEST was tested with high-resolution satellite images of the crisis areas of Darfur (Sudan). CEST results are compared with a number of standard algorithms for automated change detection such as image difference, image ratioe, principal component analysis, delta cue technique and post classification change detection. The new combined method shows superior results averaging between 45% and 15% improvement in accuracy.

WE-AB-202-05: Validation of Lung Stress Maps for CT-Ventilation Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cazoulat, G; Jolly, S; Matuszak, M

Purpose: To date, lung CT-ventilation imaging has been based on quantification of local breathing-induced changes in Hounsfield Units (HU) or volume. This work investigates the use of a stress map resulting from a biomechanical deformable image registration (DIR) algorithm as a metric of the ventilation function. Method: Eight lung cancer patients presenting different kinds of ventilation defects were retrospectively analyzed. Additionally, to the 4DCT acquired for radiotherapy planning, five of them had PET and three had SPECT imaging following inhalation of Ga-68 and Tc-99m, respectively. For each patient, the inhale phase of the 4DCT was registered to the exhale phasemore » using Morfeus, a biomechanical DIR algorithm based on the determination of boundary conditions on the lung surfaces and vessel tree. To take into account the heterogeneity of the tissue stiffness in the stress map estimation, each tetrahedral element of the finite-element model was assigned a Young’s modulus ranging from 60kPa to 12MPa, as a function of the HU in the inhale CT. The node displacements and element stresses resulting from the numerical simulation were used to generate three CT-ventilation maps based on: (i) volume changes (Jacobian determinant), (ii) changes in HU, (iii) the maximum principal stress. The voxel-wise correlation between each CT-ventilation map and the PET or SPECT V image was computed in a lung mask. Results: For patients with PET, the mean (min-max) Spearman correlation coefficients r were: 0.33 (0.19–0.45), 0.36 (0.16–0.51) and 0.42 (0.21–0.59) considering the Jacobian, changes in HU and maximum principal stress, respectively. For patients with SPECT V, the mean r were: 0.12 (−0.12–0.43), 0.29 (0.22–0.45) and 0.33 (0.25–0.39). Conclusion: The maximum principal stress maps showed a stronger correlation with the ventilation images than the previously proposed Jacobian or change in HU maps. This metric thus appears promising for CT-ventilation imaging. This work was funded in part by NIH P01CA059827.« less

Correlation Time of Ocean Ambient Noise Intensity in San Diego Bay and Target Recognition in Acoustic Daylight Images

NASA Astrophysics Data System (ADS)

Wadsworth, Adam J.

A method for passively detecting and imaging underwater targets using ambient noise as the sole source of illumination (named acoustic daylight) was successfully implemented in the form of the Acoustic Daylight Ocean Noise Imaging System (ADONIS). In a series of imaging experiments conducted in San Diego Bay, where the dominant source of high-frequency ambient noise is snapping shrimp, a large quantity of ambient noise intensity data was collected with the ADONIS (Epifanio, 1997). In a subset of the experimental data sets, fluctuations of time-averaged ambient noise intensity exhibited a diurnal pattern consistent with the increase in frequency of shrimp snapping near dawn and dusk. The same subset of experimental data is revisited here and the correlation time is estimated and analysed for sequences of ambient noise data several minutes in length, with the aim of detecting possible periodicities or other trends in the fluctuation of the shrimp-dominated ambient noise field. Using videos formed from sequences of acoustic daylight images along with other experimental information, candidate segments of static-configuration ADONIS raw ambient noise data were isolated. For each segment, the normalized intensity auto-correlation closely resembled the delta function, the auto-correlation of white noise. No intensity fluctuation patterns at timescales smaller than a few minutes were discernible, suggesting that the shrimp do not communicate, synchronise, or exhibit any periodicities in their snapping. Also presented here is a ADONIS-specific target recognition algorithm based on principal component analysis, along with basic experimental results using a database of acoustic daylight images.

Technical Note: Detection of gas bubble leakage via correlation of water column multibeam images

NASA Astrophysics Data System (ADS)

Schneider von Deimling, J.; Papenberg, C.

2012-03-01

Hydroacoustic detection of natural gas release from the seafloor has been conducted in the past by using singlebeam echosounders. In contrast, modern multibeam swath mapping systems allow much wider coverage, higher resolution, and offer 3-D spatial correlation. Up to the present, the extremely high data rate hampers water column backscatter investigations and more sophisticated visualization and processing techniques are needed. Here, we present water column backscatter data acquired with a 50 kHz prototype multibeam system over a period of 75 seconds. Display types are of swath-images as well as of a "re-sorted" singlebeam presentation. Thus, individual and/or groups of gas bubbles rising from the 24 m deep seafloor clearly emerge in the acoustic images, making it possible to estimate rise velocities. A sophisticated processing scheme is introduced to identify those rising gas bubbles in the hydroacoustic data. We apply a cross-correlation technique adapted from particle imaging velocimetry (PIV) to the acoustic backscatter images. Temporal and spatial drift patterns of the bubbles are assessed and are shown to match very well to measured and theoretical rise patterns. The application of this processing to our field data gives clear results with respect to unambiguous bubble detection and remote bubble rise velocimetry. The method can identify and exclude the main source of misinterpretations, i.e. fish-mediated echoes. Although image-based cross-correlation techniques are well known in the field of fluid mechanics for high resolution and non-inversive current flow field analysis, we present the first application of this technique as an acoustic bubble detector.

A conceptual design for an exoplanet imager

NASA Astrophysics Data System (ADS)

Hyland, David C.; Winkeller, Jon; Mosher, Robert; Momin, Anif; Iglesias, Gerardo; Donnellan, Quentin; Stanley, Jerry; Myers, Storm; Whittington, William G.; Asazuma, Taro; Slagle, Kami; Newton, Lindsay; Bourgeois, Scott; Tejeda, Donny; Young, Brian; Shaver, Nick; Cooper, Jacob; Underwood, Dennis; Perkins, James; Morea, Nathan; Goodnight, Ryan; Colunga, Aaron; Peltier, Scott; Singleton, Zane; Brashear, John; McPherson, Ronald; Guillory, Winston; Patel, Sunil; Stovall, Rachel; Meyer, Ryall; Eberle, Patrick; Morrison, Cole; Mong, Chun Yu

2007-09-01

This paper reports the results of a design study for an exoplanet imaging system. The design team consisted of the students in the "Electromagnetic Sensing for Space-Bourne Imaging" class taught by the principal author in the Spring, 2005 semester. The design challenge was to devise a space system capable of forming 10X10 pixel images of terrestrial-class planets out to 10 parsecs, observing in the 9.0 to 17.0 microns range. It was presumed that this system would operate after the Terrestrial Planet Finder had been deployed and had identified a number of planetary systems for more detailed imaging. The design team evaluated a large number of tradeoffs, starting with the use of a single monolithic telescope, versus a truss-mounted sparse aperture, versus a formation of free-flying telescopes. Having selected the free-flyer option, the team studied a variety of sensing technologies, including amplitude interferometry, intensity correlation imaging (ICI, based on the Brown-Twiss effect and phase retrieval), heterodyne interferometry and direct electric field reconstruction. Intensity correlation imaging was found to have several advantages. It does not require combiner spacecraft, nor nanometer-level control of the relative positions, nor diffraction-limited optics. Orbit design, telescope design, spacecraft structural design, thermal management and communications architecture trades were also addressed. A six spacecraft design involving non-repeating baselines was selected. By varying the overall scale of the baselines it was found possible to unambiguously characterize an entire multi-planet system, to image the parent star and, for the largest base scales, to determine 10X10 pixel images of individual planets.

Resolution improvement in positron emission tomography using anatomical Magnetic Resonance Imaging.

PubMed

Chu, Yong; Su, Min-Ying; Mandelkern, Mark; Nalcioglu, Orhan

2006-08-01

An ideal imaging system should provide information with high-sensitivity, high spatial, and temporal resolution. Unfortunately, it is not possible to satisfy all of these desired features in a single modality. In this paper, we discuss methods to improve the spatial resolution in positron emission imaging (PET) using a priori information from Magnetic Resonance Imaging (MRI). Our approach uses an image restoration algorithm based on the maximization of mutual information (MMI), which has found significant success for optimizing multimodal image registration. The MMI criterion is used to estimate the parameters in the Sharpness-Constrained Wiener filter. The generated filter is then applied to restore PET images of a realistic digital brain phantom. The resulting restored images show improved resolution and better signal-to-noise ratio compared to the interpolated PET images. We conclude that a Sharpness-Constrained Wiener filter having parameters optimized from a MMI criterion may be useful for restoring spatial resolution in PET based on a priori information from correlated MRI.

Diffusion processes in tumors: A nuclear medicine approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Amaya, Helman, E-mail: haamayae@unal.edu.co

The number of counts used in nuclear medicine imaging techniques, only provides physical information about the desintegration of the nucleus present in the the radiotracer molecules that were uptaken in a particular anatomical region, but that information is not a real metabolic information. For this reason a mathematical method was used to find a correlation between number of counts and {sup 18}F-FDG mass concentration. This correlation allows a better interpretation of the results obtained in the study of diffusive processes in an agar phantom, and based on it, an image from the PETCETIX DICOM sample image set from OsiriX-viewer softwaremore » was processed. PET-CT gradient magnitude and Laplacian images could show direct information on diffusive processes for radiopharmaceuticals that enter into the cells by simple diffusion. In the case of the radiopharmaceutical {sup 18}F-FDG is necessary to include pharmacokinetic models, to make a correct interpretation of the gradient magnitude and Laplacian of counts images.« less

Imaging of supersonic flow over a double elliptic surface

NASA Astrophysics Data System (ADS)

Zhang, Qing-Hu; Yi, Shi-He; He, Lin; Zhu, Yang-Zhu; Chen, Zhi

2013-11-01

The coherent structures of flow over a double elliptic surface are experimentally investigated in a supersonic low-noise wind tunnel at Mach number 3 using nano-tracer planar laser scattering (NPLS) and particle image velocimetry (PIV) techniques. High spatiotemporal resolution images and velocity fields of both laminar and turbulent inflows over the test model are captured. Based on the time-correlation images, the spatial and temporal evolutionary characteristics of the coherent structures are investigated. The flow structures in the NPLS images are in good agreement with the velocity fluctuation fields by PIV. From statistically significant ensembles, spatial correlation analysis of both cases is performed to quantify the mean size and the orientation of coherent structures. The results indicate that the mean structure is elliptical in shape and the structural angles in the separated region of laminar inflow are slightly smaller than that of turbulent inflow. Moreover, the structural angles of both cases increase with their distance away from the wall.

Quantum imaging with incoherently scattered light from a free-electron laser

NASA Astrophysics Data System (ADS)

Schneider, Raimund; Mehringer, Thomas; Mercurio, Giuseppe; Wenthaus, Lukas; Classen, Anton; Brenner, Günter; Gorobtsov, Oleg; Benz, Adrian; Bhatti, Daniel; Bocklage, Lars; Fischer, Birgit; Lazarev, Sergey; Obukhov, Yuri; Schlage, Kai; Skopintsev, Petr; Wagner, Jochen; Waldmann, Felix; Willing, Svenja; Zaluzhnyy, Ivan; Wurth, Wilfried; Vartanyants, Ivan A.; Röhlsberger, Ralf; von Zanthier, Joachim

2018-02-01

The advent of accelerator-driven free-electron lasers (FEL) has opened new avenues for high-resolution structure determination via diffraction methods that go far beyond conventional X-ray crystallography methods. These techniques rely on coherent scattering processes that require the maintenance of first-order coherence of the radiation field throughout the imaging procedure. Here we show that higher-order degrees of coherence, displayed in the intensity correlations of incoherently scattered X-rays from an FEL, can be used to image two-dimensional objects with a spatial resolution close to or even below the Abbe limit. This constitutes a new approach towards structure determination based on incoherent processes, including fluorescence emission or wavefront distortions, generally considered detrimental for imaging applications. Our method is an extension of the landmark intensity correlation measurements of Hanbury Brown and Twiss to higher than second order, paving the way towards determination of structure and dynamics of matter in regimes where coherent imaging methods have intrinsic limitations.

Combining points and lines in rectifying satellite images

NASA Astrophysics Data System (ADS)

Elaksher, Ahmed F.

2017-09-01

The quick advance in remote sensing technologies established the potential to gather accurate and reliable information about the Earth surface using high resolution satellite images. Remote sensing satellite images of less than one-meter pixel size are currently used in large-scale mapping. Rigorous photogrammetric equations are usually used to describe the relationship between the image coordinates and ground coordinates. These equations require the knowledge of the exterior and interior orientation parameters of the image that might not be available. On the other hand, the parallel projection transformation could be used to represent the mathematical relationship between the image-space and objectspace coordinate systems and provides the required accuracy for large-scale mapping using fewer ground control features. This article investigates the differences between point-based and line-based parallel projection transformation models in rectifying satellite images with different resolutions. The point-based parallel projection transformation model and its extended form are presented and the corresponding line-based forms are developed. Results showed that the RMS computed using the point- or line-based transformation models are equivalent and satisfy the requirement for large-scale mapping. The differences between the transformation parameters computed using the point- and line-based transformation models are insignificant. The results showed high correlation between the differences in the ground elevation and the RMS.

A Generic and Efficient E-field Parallel Imaging Correlator for Next-Generation Radio Telescopes

NASA Astrophysics Data System (ADS)

Thyagarajan, Nithyanandan; Beardsley, Adam P.; Bowman, Judd D.; Morales, Miguel F.

2017-05-01

Modern radio telescopes are favouring densely packed array layouts with large numbers of antennas (NA ≳ 1000). Since the complexity of traditional correlators scales as O(N_A^2), there will be a steep cost for realizing the full imaging potential of these powerful instruments. Through our generic and efficient E-field Parallel Imaging Correlator (epic), we present the first software demonstration of a generalized direct imaging algorithm, namely the Modular Optimal Frequency Fourier imager. Not only does it bring down the cost for dense layouts to O(N_A log _2N_A) but can also image from irregular layouts and heterogeneous arrays of antennas. epic is highly modular, parallelizable, implemented in object-oriented python, and publicly available. We have verified the images produced to be equivalent to those from traditional techniques to within a precision set by gridding coarseness. We have also validated our implementation on data observed with the Long Wavelength Array (LWA1). We provide a detailed framework for imaging with heterogeneous arrays and show that epic robustly estimates the input sky model for such arrays. Antenna layouts with dense filling factors consisting of a large number of antennas such as LWA, the Square Kilometre Array, Hydrogen Epoch of Reionization Array, and Canadian Hydrogen Intensity Mapping Experiment will gain significant computational advantage by deploying an optimized version of epic. The algorithm is a strong candidate for instruments targeting transient searches of fast radio bursts as well as planetary and exoplanetary phenomena due to the availability of high-speed calibrated time-domain images and low output bandwidth relative to visibility-based systems.

Direct biomechanical modeling of trabecular bone using a nonlinear manifold-based volumetric representation

NASA Astrophysics Data System (ADS)

Jin, Dakai; Lu, Jia; Zhang, Xiaoliu; Chen, Cheng; Bai, ErWei; Saha, Punam K.

2017-03-01

Osteoporosis is associated with increased fracture risk. Recent advancement in the area of in vivo imaging allows segmentation of trabecular bone (TB) microstructures, which is a known key determinant of bone strength and fracture risk. An accurate biomechanical modelling of TB micro-architecture provides a comprehensive summary measure of bone strength and fracture risk. In this paper, a new direct TB biomechanical modelling method using nonlinear manifold-based volumetric reconstruction of trabecular network is presented. It is accomplished in two sequential modules. The first module reconstructs a nonlinear manifold-based volumetric representation of TB networks from three-dimensional digital images. Specifically, it starts with the fuzzy digital segmentation of a TB network, and computes its surface and curve skeletons. An individual trabecula is identified as a topological segment in the curve skeleton. Using geometric analysis, smoothing and optimization techniques, the algorithm generates smooth, curved, and continuous representations of individual trabeculae glued at their junctions. Also, the method generates a geometrically consistent TB volume at junctions. In the second module, a direct computational biomechanical stress-strain analysis is applied on the reconstructed TB volume to predict mechanical measures. The accuracy of the method was examined using micro-CT imaging of cadaveric distal tibia specimens (N = 12). A high linear correlation (r = 0.95) between TB volume computed using the new manifold-modelling algorithm and that directly derived from the voxel-based micro-CT images was observed. Young's modulus (YM) was computed using direct mechanical analysis on the TB manifold-model over a cubical volume of interest (VOI), and its correlation with the YM, computed using micro-CT based conventional finite-element analysis over the same VOI, was examined. A moderate linear correlation (r = 0.77) was observed between the two YM measures. This preliminary results show the accuracy of the new nonlinear manifold modelling algorithm for TB, and demonstrate the feasibility of a new direct mechanical strain-strain analysis on a nonlinear manifold model of a highly complex biological structure.

Application and evaluation of ISVR method in QuickBird image fusion

NASA Astrophysics Data System (ADS)

Cheng, Bo; Song, Xiaolu

2014-05-01

QuickBird satellite images are widely used in many fields, and applications have put forward high requirements for the integration of the spatial information and spectral information of the imagery. A fusion method for high resolution remote sensing images based on ISVR is identified in this study. The core principle of ISVS is taking the advantage of radicalization targeting to remove the effect of different gain and error of satellites' sensors. Transformed from DN to radiance, the multi-spectral image's energy is used to simulate the panchromatic band. The linear regression analysis is carried through the simulation process to find a new synthetically panchromatic image, which is highly linearly correlated to the original panchromatic image. In order to evaluate, test and compare the algorithm results, this paper used ISVR and other two different fusion methods to give a comparative study of the spatial information and spectral information, taking the average gradient and the correlation coefficient as an indicator. Experiments showed that this method could significantly improve the quality of fused image, especially in preserving spectral information, to maximize the spectral information of original multispectral images, while maintaining abundant spatial information.

Prediction of survival with multi-scale radiomic analysis in glioblastoma patients.

PubMed

Chaddad, Ahmad; Sabri, Siham; Niazi, Tamim; Abdulkarim, Bassam

2018-06-19

We propose a multiscale texture features based on Laplacian-of Gaussian (LoG) filter to predict progression free (PFS) and overall survival (OS) in patients newly diagnosed with glioblastoma (GBM). Experiments use the extracted features derived from 40 patients of GBM with T1-weighted imaging (T1-WI) and Fluid-attenuated inversion recovery (FLAIR) images that were segmented manually into areas of active tumor, necrosis, and edema. Multiscale texture features were extracted locally from each of these areas of interest using a LoG filter and the relation between features to OS and PFS was investigated using univariate (i.e., Spearman's rank correlation coefficient, log-rank test and Kaplan-Meier estimator) and multivariate analyses (i.e., Random Forest classifier). Three and seven features were statistically correlated with PFS and OS, respectively, with absolute correlation values between 0.32 and 0.36 and p < 0.05. Three features derived from active tumor regions only were associated with OS (p < 0.05) with hazard ratios (HR) of 2.9, 3, and 3.24, respectively. Combined features showed an AUC value of 85.37 and 85.54% for predicting the PFS and OS of GBM patients, respectively, using the random forest (RF) classifier. We presented a multiscale texture features to characterize the GBM regions and predict he PFS and OS. The efficiency achievable suggests that this technique can be developed into a GBM MR analysis system suitable for clinical use after a thorough validation involving more patients. Graphical abstract Scheme of the proposed model for characterizing the heterogeneity of GBM regions and predicting the overall survival and progression free survival of GBM patients. (1) Acquisition of pretreatment MRI images; (2) Affine registration of T1-WI image with its corresponding FLAIR images, and GBM subtype (phenotypes) labelling; (3) Extraction of nine texture features from the three texture scales fine, medium, and coarse derived from each of GBM regions; (4) Comparing heterogeneity between GBM regions by ANOVA test; Survival analysis using Univariate (Spearman rank correlation between features and survival (i.e., PFS and OS) based on each of the GBM regions, Kaplan-Meier estimator and log-rank test to predict the PFS and OS of patient groups that grouped based on median of feature), and multivariate (random forest model) for predicting the PFS and OS of patients groups that grouped based on median of PFS and OS.

TU-G-BRA-02: Can We Extract Lung Function Directly From 4D-CT Without Deformable Image Registration?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kipritidis, J; Woodruff, H; Counter, W

Purpose: Dynamic CT ventilation imaging (CT-VI) visualizes air volume changes in the lung by evaluating breathing-induced lung motion using deformable image registration (DIR). Dynamic CT-VI could enable functionally adaptive lung cancer radiation therapy, but its sensitivity to DIR parameters poses challenges for validation. We hypothesize that a direct metric using CT parameters derived from Hounsfield units (HU) alone can provide similar ventilation images without DIR. We compare the accuracy of Direct and Dynamic CT-VIs versus positron emission tomography (PET) images of inhaled {sup 68}Ga-labelled nanoparticles (‘Galligas’). Methods: 25 patients with lung cancer underwent Galligas 4D-PET/CT scans prior to radiation therapy.more » For each patient we produced three CT- VIs. (i) Our novel method, Direct CT-VI, models blood-gas exchange as the product of air and tissue density at each lung voxel based on time-averaged 4D-CT HU values. Dynamic CT-VIs were produced by evaluating: (ii) regional HU changes, and (iii) regional volume changes between the exhale and inhale 4D-CT phase images using a validated B-spline DIR method. We assessed the accuracy of each CT-VI by computing the voxel-wise Spearman correlation with free-breathing Galligas PET, and also performed a visual analysis. Results: Surprisingly, Direct CT-VIs exhibited better global correlation with Galligas PET than either of the dynamic CT-VIs. The (mean ± SD) correlations were (0.55 ± 0.16), (0.41 ± 0.22) and (0.29 ± 0.27) for Direct, Dynamic HU-based and Dynamic volume-based CT-VIs respectively. Visual comparison of Direct CT-VI to PET demonstrated similarity for emphysema defects and ventral-to-dorsal gradients, but inability to identify decreased ventilation distal to tumor-obstruction. Conclusion: Our data supports the hypothesis that Direct CT-VIs are as accurate as Dynamic CT-VIs in terms of global correlation with Galligas PET. Visual analysis, however, demonstrated that different CT-VI algorithms might have varying accuracy depending on the underlying cause of ventilation abnormality. This research was supported by a National Health and Medical Research Council (NHMRC) Australia Fellowship, an Cancer Institute New South Wales Early Career Fellowship 13-ECF-1/15 and NHMRC scholarship APP1038399. No commercial funding was received for this work.« less