Elongation measurement using 1-dimensional image correlation method

NASA Astrophysics Data System (ADS)

Phongwisit, Phachara; Kamoldilok, Surachart; Buranasiri, Prathan

2016-11-01

Aim of this paper was to study, setup, and calibrate an elongation measurement by using 1- Dimensional Image Correlation method (1-DIC). To confirm our method and setup correctness, we need calibration with other methods. In this paper, we used a small spring as a sample to find a result in terms of spring constant. With a fundamental of Image Correlation method, images of formed and deformed samples were compared to understand the difference between deformed process. By comparing the location of reference point on both image's pixel, the spring's elongation were calculated. Then, the results have been compared with the spring constants, which were found from Hooke's law. The percentage of 5 percent error has been found. This DIC method, then, would be applied to measure the elongation of some different kinds of small fiber samples.

Image stitching and image reconstruction of intestines captured using radial imaging capsule endoscope

NASA Astrophysics Data System (ADS)

Ou-Yang, Mang; Jeng, Wei-De; Wu, Yin-Yi; Dung, Lan-Rong; Wu, Hsien-Ming; Weng, Ping-Kuo; Huang, Ker-Jer; Chiu, Luan-Jiau

2012-05-01

This study investigates image processing using the radial imaging capsule endoscope (RICE) system. First, an experimental environment is established in which a simulated object has a shape that is similar to a cylinder, such that a triaxial platform can be used to push the RICE into the sample and capture radial images. Then four algorithms (mean absolute error, mean square error, Pearson correlation coefficient, and deformation processing) are used to stitch the images together. The Pearson correlation coefficient method is the most effective algorithm because it yields the highest peak signal-to-noise ratio, higher than 80.69 compared to the original image. Furthermore, a living animal experiment is carried out. Finally, the Pearson correlation coefficient method and vector deformation processing are used to stitch the images that were captured in the living animal experiment. This method is very attractive because unlike the other methods, in which two lenses are required to reconstruct the geometrical image, RICE uses only one lens and one mirror.

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.

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.

Field methods to measure surface displacement and strain with the Video Image Correlation method

NASA Technical Reports Server (NTRS)

Maddux, Gary A.; Horton, Charles M.; Mcneill, Stephen R.; Lansing, Matthew D.

1994-01-01

The objective of this project was to develop methods and application procedures to measure displacement and strain fields during the structural testing of aerospace components using paint speckle in conjunction with the Video Image Correlation (VIC) system.

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 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.

Microseismic reverse time migration with a multi-cross-correlation staining algorithm for fracture imaging

NASA Astrophysics Data System (ADS)

Yuan, Congcong; Jia, Xiaofeng; Liu, Shishuo; Zhang, Jie

2018-02-01

Accurate characterization of hydraulic fracturing zones is currently becoming increasingly important in production optimization, since hydraulic fracturing may increase the porosity and permeability of the reservoir significantly. Recently, the feasibility of the reverse time migration (RTM) method has been studied for the application in imaging fractures during borehole microseismic monitoring. However, strong low-frequency migration noise, poorly illuminated areas, and the low signal to noise ratio (SNR) data can degrade the imaging results. To improve the quality of the images, we propose a multi-cross-correlation staining algorithm to incorporate into the microseismic reverse time migration for imaging fractures using scattered data. Under the modified RTM method, our results are revealed in two images: one is the improved RTM image using the multi-cross-correlation condition, and the other is an image of the target region using the generalized staining algorithm. The numerical examples show that, compared with the conventional RTM, our method can significantly improve the spatial resolution of images, especially for the image of target region.

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.

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.

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

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

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.

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

Radar correlated imaging for extended target by the combination of negative exponential restraint and total variation

NASA Astrophysics Data System (ADS)

Qian, Tingting; Wang, Lianlian; Lu, Guanghua

2017-07-01

Radar correlated imaging (RCI) introduces the optical correlated imaging technology to traditional microwave imaging, which has raised widespread concern recently. Conventional RCI methods neglect the structural information of complex extended target, which makes the quality of recovery result not really perfect, thus a novel combination of negative exponential restraint and total variation (NER-TV) algorithm for extended target imaging is proposed in this paper. The sparsity is measured by a sequential order one negative exponential function, then the 2D total variation technique is introduced to design a novel optimization problem for extended target imaging. And the proven alternating direction method of multipliers is applied to solve the new problem. Experimental results show that the proposed algorithm could realize high resolution imaging efficiently for extended target.

Extracting flat-field images from scene-based image sequences using phase correlation

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

Caron, James N., E-mail: Caron@RSImd.com; Montes, Marcos J.; Obermark, Jerome L.

Flat-field image processing is an essential step in producing high-quality and radiometrically calibrated images. Flat-fielding corrects for variations in the gain of focal plane array electronics and unequal illumination from the system optics. Typically, a flat-field image is captured by imaging a radiometrically uniform surface. The flat-field image is normalized and removed from the images. There are circumstances, such as with remote sensing, where a flat-field image cannot be acquired in this manner. For these cases, we developed a phase-correlation method that allows the extraction of an effective flat-field image from a sequence of scene-based displaced images. The method usesmore » sub-pixel phase correlation image registration to align the sequence to estimate the static scene. The scene is removed from sequence producing a sequence of misaligned flat-field images. An average flat-field image is derived from the realigned flat-field sequence.« less

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.

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.

[Comparative research on the NIR and MIR micro-imaging of two similar plastic materials].

PubMed

Wang, Dong; Ma, Zhi-Hong; Zhao, Liu; Pan, Li-Gang; Li, Xiao-Ting; Wang, Ji-Hua

2011-09-01

The NIR/MIR micro-imaging can supply not only the information of spectra, but also the information of spacial distribution of the sample, which is superior to the traditional NIR/MIR spectroscopy analysis. In the present paper, polyethylene and parafilm, with similar appearances, were regarded as the research objects, of which the NIR/MIR micro-imaging was collected. Chemical imaging (CI) and compare correlation imaging were carried out for the two materials respectively to discuss the imaging methods of the two materials. The result indicated that the differentiation of the CI values of the two materials in the NIR/MIR CI for material II was 0.004 8 and 0.254 8 respectively, while those in the NIR/MIR CI for material I were 0.002 6 and 0.326 5, respectively. Clear CI was acquired, and the two materials could be differentiated. The result of the compare correlation imagings indicated that the compare correlation imagings, in which the NIR/MIR spectra of the two materials were regarded as reference spectra respectively, can differentiate the two materials remarkably with clear imagings. In the compare correlation imagings of MIR micro-imaging, the difference of the correlation coefficients between the two materials' MIR spectra and the reference spectrum was more than 0.12, which showed a better imaging result; while a tiny difference of the correlation coefficients between the two materials' NIR spectra and the reference spectrum could be employed to show a clear imaging result for NIR compare correlation imaging so as to differentiate the two materials. This thesis, to some extent, can supply the reference to not only the rapid discrimination of the safety of the packaging material for agri-food, but also the imaging methods for NIR/MIR micro-imaging to differentiate the different materials.

Spatiotemporal image correlation analysis of blood flow in branched vessel networks of zebrafish embryos

NASA Astrophysics Data System (ADS)

Ceffa, Nicolo G.; Cesana, Ilaria; Collini, Maddalena; D'Alfonso, Laura; Carra, Silvia; Cotelli, Franco; Sironi, Laura; Chirico, Giuseppe

2017-10-01

Ramification of blood circulation is relevant in a number of physiological and pathological conditions. The oxygen exchange occurs largely in the capillary bed, and the cancer progression is closely linked to the angiogenesis around the tumor mass. Optical microscopy has made impressive improvements in in vivo imaging and dynamic studies based on correlation analysis of time stacks of images. Here, we develop and test advanced methods that allow mapping the flow fields in branched vessel networks at the resolution of 10 to 20 μm. The methods, based on the application of spatiotemporal image correlation spectroscopy and its extension to cross-correlation analysis, are applied here to the case of early stage embryos of zebrafish.

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.

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.

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.

Cross Correlation versus Normalized Mutual Information on Image Registration

NASA Technical Reports Server (NTRS)

Tan, Bin; Tilton, James C.; Lin, Guoqing

2016-01-01

This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

Method and apparatus for the simultaneous display and correlation of independently generated images

DOEpatents

Vaitekunas, Jeffrey J.; Roberts, Ronald A.

1991-01-01

An apparatus and method for location by location correlation of multiple images from Non-Destructive Evaluation (NDE) and other sources. Multiple images of a material specimen are displayed on one or more monitors of an interactive graphics system. Specimen landmarks are located in each image and mapping functions from a reference image to each other image are calcuated using the landmark locations. A location selected by positioning a cursor in the reference image is mapped to the other images and location identifiers are simultaneously displayed in those images. Movement of the cursor in the reference image causes simultaneous movement of the location identifiers in the other images to positions corresponding to the location of the reference image cursor.

Simulation of speckle patterns with pre-defined correlation distributions.

PubMed

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S

2016-03-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques.

Simulation of speckle patterns with pre-defined correlation distributions

PubMed Central

Song, Lipei; Zhou, Zhen; Wang, Xueyan; Zhao, Xing; Elson, Daniel S.

2016-01-01

We put forward a method to easily generate a single or a sequence of fully developed speckle patterns with pre-defined correlation distribution by utilizing the principle of coherent imaging. The few-to-one mapping between the input correlation matrix and the correlation distribution between simulated speckle patterns is realized and there is a simple square relationship between the values of these two correlation coefficient sets. This method is demonstrated both theoretically and experimentally. The square relationship enables easy conversion from any desired correlation distribution. Since the input correlation distribution can be defined by a digital matrix or a gray-scale image acquired experimentally, this method provides a convenient way to simulate real speckle-related experiments and to evaluate data processing techniques. PMID:27231589

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers

NASA Astrophysics Data System (ADS)

Haring, Martijn T.; Liv, Nalan; Zonnevylle, A. Christiaan; Narvaez, Angela C.; Voortman, Lenard M.; Kruit, Pieter; Hoogenboom, Jacob P.

2017-03-01

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample.

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers.

PubMed

Haring, Martijn T; Liv, Nalan; Zonnevylle, A Christiaan; Narvaez, Angela C; Voortman, Lenard M; Kruit, Pieter; Hoogenboom, Jacob P

2017-03-02

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample.

Automated sub-5 nm image registration in integrated correlative fluorescence and electron microscopy using cathodoluminescence pointers

PubMed Central

Haring, Martijn T.; Liv, Nalan; Zonnevylle, A. Christiaan; Narvaez, Angela C.; Voortman, Lenard M.; Kruit, Pieter; Hoogenboom, Jacob P.

2017-01-01

In the biological sciences, data from fluorescence and electron microscopy is correlated to allow fluorescence biomolecule identification within the cellular ultrastructure and/or ultrastructural analysis following live-cell imaging. High-accuracy (sub-100 nm) image overlay requires the addition of fiducial markers, which makes overlay accuracy dependent on the number of fiducials present in the region of interest. Here, we report an automated method for light-electron image overlay at high accuracy, i.e. below 5 nm. Our method relies on direct visualization of the electron beam position in the fluorescence detection channel using cathodoluminescence pointers. We show that image overlay using cathodoluminescence pointers corrects for image distortions, is independent of user interpretation, and does not require fiducials, allowing image correlation with molecular precision anywhere on a sample. PMID:28252673

Hadamard multimode optical imaging transceiver

DOEpatents

Cooke, Bradly J; Guenther, David C; Tiee, Joe J; Kellum, Mervyn J; Olivas, Nicholas L; Weisse-Bernstein, Nina R; Judd, Stephen L; Braun, Thomas R

2012-10-30

Disclosed is a method and system for simultaneously acquiring and producing results for multiple image modes using a common sensor without optical filtering, scanning, or other moving parts. The system and method utilize the Walsh-Hadamard correlation detection process (e.g., functions/matrix) to provide an all-binary structure that permits seamless bridging between analog and digital domains. An embodiment may capture an incoming optical signal at an optical aperture, convert the optical signal to an electrical signal, pass the electrical signal through a Low-Noise Amplifier (LNA) to create an LNA signal, pass the LNA signal through one or more correlators where each correlator has a corresponding Walsh-Hadamard (WH) binary basis function, calculate a correlation output coefficient for each correlator as a function of the corresponding WH binary basis function in accordance with Walsh-Hadamard mathematical principles, digitize each of the correlation output coefficient by passing each correlation output coefficient through an Analog-to-Digital Converter (ADC), and performing image mode processing on the digitized correlation output coefficients as desired to produce one or more image modes. Some, but not all, potential image modes include: multi-channel access, temporal, range, three-dimensional, and synthetic aperture.

Method for localizing and isolating an errant process step

DOEpatents

Tobin, Jr., Kenneth W.; Karnowski, Thomas P.; Ferrell, Regina K.

2003-01-01

A method for localizing and isolating an errant process includes the steps of retrieving from a defect image database a selection of images each image having image content similar to image content extracted from a query image depicting a defect, each image in the selection having corresponding defect characterization data. A conditional probability distribution of the defect having occurred in a particular process step is derived from the defect characterization data. A process step as a highest probable source of the defect according to the derived conditional probability distribution is then identified. A method for process step defect identification includes the steps of characterizing anomalies in a product, the anomalies detected by an imaging system. A query image of a product defect is then acquired. A particular characterized anomaly is then correlated with the query image. An errant process step is then associated with the correlated image.

Value of three-dimensional volume rendering images in the assessment of the centrality index for preoperative planning in patients with renal masses.

PubMed

Sofia, C; Magno, C; Silipigni, S; Cantisani, V; Mucciardi, G; Sottile, F; Inferrera, A; Mazziotti, S; Ascenti, G

2017-01-01

To evaluate the precision of the centrality index (CI) measurement on three-dimensional (3D) volume rendering technique (VRT) images in patients with renal masses, compared to its standard measurement on axial images. Sixty-five patients with renal lesions underwent contrast-enhanced multidetector (MD) computed tomography (CT) for preoperative imaging. Two readers calculated the CI on two-dimensional axial images and on VRT images, measuring it in the plane that the tumour and centre of the kidney were lying in. Correlation and agreement of interobserver measurements and inter-method results were calculated using intraclass correlation (ICC) coefficients and the Bland-Altman method. Time saving was also calculated. The correlation coefficients were r=0.99 (p<0.05) and r=0.99 (p<0.05) for both the CI on axial and VRT images, with an ICC of 0.99, and 0.99, respectively. Correlation between the two methods of measuring the CI on VRT and axial CT images was r=0.99 (p<0.05). The two methods showed a mean difference of -0.03 (SD 0.13). Mean time saving per each examination with VRT was 45.5%. The present study showed that VRT and axial images produce almost identical values of CI, with the advantages of greater ease of execution and a time saving of almost 50% for 3D VRT images. In addition, VRT provides an integrated perspective that can better assist surgeons in clinical decision making and in operative planning, suggesting this technique as a possible standard method for CI measurement. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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.

Lossless Compression of JPEG Coded Photo Collections.

PubMed

Wu, Hao; Sun, Xiaoyan; Yang, Jingyu; Zeng, Wenjun; Wu, Feng

2016-04-06

The explosion of digital photos has posed a significant challenge to photo storage and transmission for both personal devices and cloud platforms. In this paper, we propose a novel lossless compression method to further reduce the size of a set of JPEG coded correlated images without any loss of information. The proposed method jointly removes inter/intra image redundancy in the feature, spatial, and frequency domains. For each collection, we first organize the images into a pseudo video by minimizing the global prediction cost in the feature domain. We then present a hybrid disparity compensation method to better exploit both the global and local correlations among the images in the spatial domain. Furthermore, the redundancy between each compensated signal and the corresponding target image is adaptively reduced in the frequency domain. Experimental results demonstrate the effectiveness of the proposed lossless compression method. Compared to the JPEG coded image collections, our method achieves average bit savings of more than 31%.

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.

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.

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

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.

Prediction of subacute infarct size in acute middle cerebral artery stroke: comparison of perfusion-weighted imaging and apparent diffusion coefficient maps.

PubMed

Drier, Aurélie; Tourdias, Thomas; Attal, Yohan; Sibon, Igor; Mutlu, Gurkan; Lehéricy, Stéphane; Samson, Yves; Chiras, Jacques; Dormont, Didier; Orgogozo, Jean-Marc; Dousset, Vincent; Rosso, Charlotte

2012-11-01

To compare perfusion-weighted (PW) imaging and apparent diffusion coefficient (ADC) maps in prediction of infarct size and growth in patients with acute middle cerebral artery infarct. This study was approved by the local institutional review board. Written informed consent was obtained from all 80 patients. Subsequent infarct volume and growth on follow-up magnetic resonance (MR) images obtained within 6 days were compared with the predictions based on PW images by using a time-to-peak threshold greater than 4 seconds and ADC maps obtained less than 12 hours after middle cerebral artery infarct. ADC- and PW imaging-predicted infarct growth areas and infarct volumes were correlated with subsequent infarct growth and follow-up diffusion-weighted (DW) imaging volumes. The impact of MR imaging time delay on the correlation coefficient between the predicted and subsequent infarct volumes and individual predictions of infarct growth by using receiver operating characteristic curves were assessed. The infarct volume measurements were highly reproducible (concordance correlation coefficient [CCC] of 0.965 and 95% confidence interval [CI]: 0.949, 0.976 for acute DW imaging; CCC of 0.995 and 95% CI: 0.993, 0.997 for subacute DW imaging). The subsequent infarct volume correlated (P<.0001) with ADC- (ρ=0.853) and PW imaging- (ρ=0.669) predicted volumes. The correlation was higher for ADC-predicted volume than for PW imaging-predicted volume (P<.005), but not when the analysis was restricted to patients without recanalization (P=.07). The infarct growth correlated (P<.0001) with PW imaging-DW imaging mismatch (ρ=0.470) and ADC-DW imaging mismatch (ρ=0.438), without significant differences between both methods (P=.71). The correlations were similar among time delays with ADC-predicted volumes but decreased with PW imaging-based volumes beyond the therapeutic window. Accuracies of ADC- and PW imaging-based predictions of infarct growth in an individual prediction were similar (area under the receiver operating characteristic curve [AUC] of 0.698 and 95% CI: 0.585, 0.796 vs AUC of 0.749 and 95% CI: 0.640, 0.839; P=.48). The ADC-based method was as accurate as the PW imaging-based method for evaluating infarct growth and size in the subacute phase. © RSNA, 2012

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.

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.

Dynamic contrast-enhanced MR imaging of the rectum: Correlations between single-section and whole-tumor histogram analyses.

PubMed

Choi, M H; Oh, S N; Park, G E; Yeo, D-M; Jung, S E

2018-05-10

To evaluate the interobserver and intermethod correlations of histogram metrics of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters acquired by multiple readers using the single-section and whole-tumor volume methods. Four DCE parameters (K trans , K ep , V e , V p ) were evaluated in 45 patients (31 men and 14 women; mean age, 61±11 years [range, 29-83 years]) with locally advanced rectal cancer using pre-chemoradiotherapy (CRT) MRI. Ten histogram metrics were extracted using two methods of lesion selection performed by three radiologists: the whole-tumor volume method for the whole tumor on axial section-by-section images and the single-section method for the entire area of the tumor on one axial image. The interobserver and intermethod correlations were evaluated using the intraclass correlation coefficients (ICCs). The ICCs showed excellent interobserver and intermethod correlations in most of histogram metrics of the DCE parameters. The ICCs among the three readers were > 0.7 (P<0.001) for all histogram metrics, except for the minimum and maximum. The intermethod correlations for most of the histogram metrics were excellent for each radiologist, regardless of the differences in the radiologists' experience. The interobserver and intermethod correlations for most of the histogram metrics of the DCE parameters are excellent in rectal cancer. Therefore, the single-section method may be a potential alternative to the whole-tumor volume method using pre-CRT MRI, despite the fact that the high agreement between the two methods cannot be extrapolated to post-CRT MRI. Copyright © 2018 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

Noise correlation in PET, CT, SPECT and PET/CT data evaluated using autocorrelation function: a phantom study on data, reconstructed using FBP and OSEM.

PubMed

Razifar, Pasha; Sandström, Mattias; Schnieder, Harald; Långström, Bengt; Maripuu, Enn; Bengtsson, Ewert; Bergström, Mats

2005-08-25

Positron Emission Tomography (PET), Computed Tomography (CT), PET/CT and Single Photon Emission Tomography (SPECT) are non-invasive imaging tools used for creating two dimensional (2D) cross section images of three dimensional (3D) objects. PET and SPECT have the potential of providing functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules, whereas CT visualizes X-ray density in tissues in the body. PET/CT provides fused images representing both functional and anatomical information with better precision in localization than PET alone. Images generated by these types of techniques are generally noisy, thereby impairing the imaging potential and affecting the precision in quantitative values derived from the images. It is crucial to explore and understand the properties of noise in these imaging techniques. Here we used autocorrelation function (ACF) specifically to describe noise correlation and its non-isotropic behaviour in experimentally generated images of PET, CT, PET/CT and SPECT. Experiments were performed using phantoms with different shapes. In PET and PET/CT studies, data were acquired in 2D acquisition mode and reconstructed by both analytical filter back projection (FBP) and iterative, ordered subsets expectation maximisation (OSEM) methods. In the PET/CT studies, different magnitudes of X-ray dose in the transmission were employed by using different mA settings for the X-ray tube. In the CT studies, data were acquired using different slice thickness with and without applied dose reduction function and the images were reconstructed by FBP. SPECT studies were performed in 2D, reconstructed using FBP and OSEM, using post 3D filtering. ACF images were generated from the primary images, and profiles across the ACF images were used to describe the noise correlation in different directions. The variance of noise across the images was visualised as images and with profiles across these images. The most important finding was that the pattern of noise correlation is rotation symmetric or isotropic, independent of object shape in PET and PET/CT images reconstructed using the iterative method. This is, however, not the case in FBP images when the shape of phantom is not circular. Also CT images reconstructed using FBP show the same non-isotropic pattern independent of slice thickness and utilization of care dose function. SPECT images show an isotropic correlation of the noise independent of object shape or applied reconstruction algorithm. Noise in PET/CT images was identical independent of the applied X-ray dose in the transmission part (CT), indicating that the noise from transmission with the applied doses does not propagate into the PET images showing that the noise from the emission part is dominant. The results indicate that in human studies it is possible to utilize a low dose in transmission part while maintaining the noise behaviour and the quality of the images. The combined effect of noise correlation for asymmetric objects and a varying noise variance across the image field significantly complicates the interpretation of the images when statistical methods are used, such as with statistical estimates of precision in average values, use of statistical parametric mapping methods and principal component analysis. Hence it is recommended that iterative reconstruction methods are used for such applications. However, it is possible to calculate the noise analytically in images reconstructed by FBP, while it is not possible to do the same calculation in images reconstructed by iterative methods. Therefore for performing statistical methods of analysis which depend on knowing the noise, FBP would be preferred.

Quantitative comparison and reproducibility of pathologist scoring and digital image analysis of estrogen receptor β2 immunohistochemistry in prostate cancer.

PubMed

Rizzardi, Anthony E; Zhang, Xiaotun; Vogel, Rachel Isaksson; Kolb, Suzanne; Geybels, Milan S; Leung, Yuet-Kin; Henriksen, Jonathan C; Ho, Shuk-Mei; Kwak, Julianna; Stanford, Janet L; Schmechel, Stephen C

2016-07-11

Digital image analysis offers advantages over traditional pathologist visual scoring of immunohistochemistry, although few studies examining the correlation and reproducibility of these methods have been performed in prostate cancer. We evaluated the correlation between digital image analysis (continuous variable data) and pathologist visual scoring (quasi-continuous variable data), reproducibility of each method, and association of digital image analysis methods with outcomes using prostate cancer tissue microarrays (TMAs) stained for estrogen receptor-β2 (ERβ2). Prostate cancer TMAs were digitized and evaluated by pathologist visual scoring versus digital image analysis for ERβ2 staining within tumor epithelium. Two independent analysis runs were performed to evaluate reproducibility. Image analysis data were evaluated for associations with recurrence-free survival and disease specific survival following radical prostatectomy. We observed weak/moderate Spearman correlation between digital image analysis and pathologist visual scores of tumor nuclei (Analysis Run A: 0.42, Analysis Run B: 0.41), and moderate/strong correlation between digital image analysis and pathologist visual scores of tumor cytoplasm (Analysis Run A: 0.70, Analysis Run B: 0.69). For the reproducibility analysis, there was high Spearman correlation between pathologist visual scores generated for individual TMA spots across Analysis Runs A and B (Nuclei: 0.84, Cytoplasm: 0.83), and very high correlation between digital image analysis for individual TMA spots across Analysis Runs A and B (Nuclei: 0.99, Cytoplasm: 0.99). Further, ERβ2 staining was significantly associated with increased risk of prostate cancer-specific mortality (PCSM) when quantified by cytoplasmic digital image analysis (HR 2.16, 95 % CI 1.02-4.57, p = 0.045), nuclear image analysis (HR 2.67, 95 % CI 1.20-5.96, p = 0.016), and total malignant epithelial area analysis (HR 5.10, 95 % CI 1.70-15.34, p = 0.004). After adjusting for clinicopathologic factors, only total malignant epithelial area ERβ2 staining was significantly associated with PCSM (HR 4.08, 95 % CI 1.37-12.15, p = 0.012). Digital methods of immunohistochemical quantification are more reproducible than pathologist visual scoring in prostate cancer, suggesting that digital methods are preferable and especially warranted for studies involving large sample sizes.

Digital Correlation In Laser-Speckle Velocimetry

NASA Technical Reports Server (NTRS)

Gilbert, John A.; Mathys, Donald R.

1992-01-01

Periodic recording helps to eliminate spurious results. Improved digital-correlation process extracts velocity field of two-dimensional flow from laser-speckle images of seed particles distributed sparsely in flow. Method which involves digital correlation of images recorded at unequal intervals, completely automated and has potential to be fastest yet.

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

Parallel image logical operations using cross correlation

NASA Technical Reports Server (NTRS)

Strong, J. P., III

1972-01-01

Methods are presented for counting areas in an image in a parallel manner using noncoherent optical techniques. The techniques presented include the Levialdi algorithm for counting, optical techniques for binary operations, and cross-correlation.

Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography

NASA Astrophysics Data System (ADS)

Kazantsev, Daniil; Jørgensen, Jakob S.; Andersen, Martin S.; Lionheart, William R. B.; Lee, Peter D.; Withers, Philip J.

2018-06-01

Rapid developments in photon-counting and energy-discriminating detectors have the potential to provide an additional spectral dimension to conventional x-ray grayscale imaging. Reconstructed spectroscopic tomographic data can be used to distinguish individual materials by characteristic absorption peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually correlated it can be advantageous to exploit this additional knowledge. In this paper, we propose a novel method which jointly reconstructs all energy channels while imposing a strong structural correlation. The core of the proposed algorithm is to employ a variational framework of parallel level sets to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction techniques including channel-wise total variation and correlative total nuclear variation regularization. Realistic simulation experiments demonstrate the performance improvements achievable by using correlative regularization methods.

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.

Application of abstract harmonic analysis to the high-speed recognition of images

NASA Technical Reports Server (NTRS)

Usikov, D. A.

1979-01-01

Methods are constructed for rapidly computing correlation functions using the theory of abstract harmonic analysis. The theory developed includes as a particular case the familiar Fourier transform method for a correlation function which makes it possible to find images which are independent of their translation in the plane. Two examples of the application of the general theory described are the search for images, independent of their rotation and scale, and the search for images which are independent of their translations and rotations in the plane.

Correlation between hippocampal volumes and medial temporal lobe atrophy in patients with Alzheimer's disease

PubMed Central

Dhikav, Vikas; Duraiswamy, Sharmila; Anand, Kuljeet Singh

2017-01-01

Introduction: Hippocampus undergoes atrophy in patients with Alzheimer's disease (AD). Calculation of hippocampal volumes can be done by a variety of methods using T1-weighted images of magnetic resonance imaging (MRI) of the brain. Medial temporal lobes atrophy (MTL) can be rated visually using T1-weighted MRI brain images. The present study was done to see if any correlation existed between hippocampal volumes and visual rating scores of the MTL using Scheltens Visual Rating Method. Materials and Methods: We screened 84 subjects presented to the Department of Neurology of a Tertiary Care Hospital and enrolled forty subjects meeting the National Institute of Neurological and Communicative Disorders and Stroke, AD related Disease Association criteria. Selected patients underwent MRI brain and T1-weighted images in a plane perpendicular to long axis of hippocampus were obtained. Hippocampal volumes were calculated manually using a standard protocol. The calculated hippocampal volumes were correlated with Scheltens Visual Rating Method for Rating MTL. A total of 32 cognitively normal age-matched subjects were selected to see the same correlation in the healthy subjects as well. Sensitivity and specificity of both methods was calculated and compared. Results: There was an insignificant correlation between the hippocampal volumes and MTL rating scores in cognitively normal elderly (n = 32; Pearson Correlation coefficient = 0.16, P > 0.05). In the AD Group, there was a moderately strong correlation between measured hippocampal volumes and MTL Rating (Pearson's correlation coefficient = −0.54; P < 0.05. There was a moderately strong correlation between hippocampal volume and Mini-Mental Status Examination in the AD group. Manual delineation was superior compared to the visual method (P < 0.05). Conclusions: Good correlation was present between manual hippocampal volume measurements and MTL scores. Sensitivity and specificity of manual measurement of hippocampus was higher compared to visual rating scores for MTL in patients with AD. PMID:28298839

A Generalized Method of Image Analysis from an Intercorrelation Matrix which May Be Singular.

ERIC Educational Resources Information Center

Yanai, Haruo; Mukherjee, Bishwa Nath

1987-01-01

This generalized image analysis method is applicable to singular and non-singular correlation matrices (CMs). Using the orthogonal projector and a weaker generalized inverse matrix, image and anti-image covariance matrices can be derived from a singular CM. (SLD)

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.

Reconstruction of coded aperture images

NASA Technical Reports Server (NTRS)

Bielefeld, Michael J.; Yin, Lo I.

1987-01-01

Balanced correlation method and the Maximum Entropy Method (MEM) were implemented to reconstruct a laboratory X-ray source as imaged by a Uniformly Redundant Array (URA) system. Although the MEM method has advantages over the balanced correlation method, it is computationally time consuming because of the iterative nature of its solution. Massively Parallel Processing, with its parallel array structure is ideally suited for such computations. These preliminary results indicate that it is possible to use the MEM method in future coded-aperture experiments with the help of the MPP.

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.

Cross-correlation photothermal optical coherence tomography with high effective resolution.

PubMed

Tang, Peijun; Liu, Shaojie; Chen, Junbo; Yuan, Zhiling; Xie, Bingkai; Zhou, Jianhua; Tang, Zhilie

2017-12-01

We developed a cross-correlation photothermal optical coherence tomography (CC-PTOCT) system for photothermal imaging with high lateral and axial resolution. The CC-PTOCT system consists of a phase-sensitive OCT system, a modulated pumping laser, and a digital cross-correlator. The pumping laser was used to induce the photothermal effect in the sample, causing a slight phase modulation of the OCT signals. A spatial phase differentiation method was employed to reduce phase accumulation. The noise brought by the phase differentiation method and the strong background noise were suppressed efficiently by the cross-correlator, which was utilized to extract the photothermal signals from the modulated signals. Combining the cross-correlation technique with spatial phase differentiation can improve both lateral and axial resolution of the PTOCT imaging system. Clear photothermal images of blood capillaries of a mouse ear in vivo were successfully obtained with high lateral and axial resolution. The experimental results demonstrated that this system can enhance the effective transverse resolution, effective depth resolution, and contrast of the PTOCT image effectively, aiding the ongoing development of the accurate 3D functional imaging.

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.

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

Measurement of the velocity of neutral fragments by the "correlated ion and neutral time of flight" method combined with "velocity-map imaging"

NASA Astrophysics Data System (ADS)

Berthias, F.; Feketeová, L.; Della Negra, R.; Dupasquier, T.; Fillol, R.; Abdoul-Carime, H.; Farizon, B.; Farizon, M.; Märk, T. D.

2017-08-01

In the challenging field of imaging molecular dynamics, a novel method has been developed and implemented that allows the measurement of the velocity of neutral fragments produced in collision induced dissociation experiments on an event-by-event basis. This has been made possible by combining a correlated ion and neutral time of flight method with a velocity map imaging technique. This new method relies on a multiparametric correlated detection of the neutral and charged fragments from collision induced dissociation on one single detector. Its implementation on the DIAM device (Device for irradiation of biomolecular clusters) (Dispositif d'Irradiation d'Agrégats bioMoléculaires) allowed us to measure the velocity distribution of water molecules evaporated from collision induced dissociation of mass- and energy-selected protonated water clusters.

On the mode I fracture analysis of cracked Brazilian disc using a digital image correlation method

NASA Astrophysics Data System (ADS)

Abshirini, Mohammad; Soltani, Nasser; Marashizadeh, Parisa

2016-03-01

Mode I of fracture of centrally cracked Brazilian disc was investigated experimentally using a digital image correlation (DIC) method. Experiments were performed on PMMA polymers subjected to diametric-compression load. The displacement fields were determined by a correlation between the reference and the deformed images captured before and during loading. The stress intensity factors were calculated by displacement fields using William's equation and the least square algorithm. The parameters involved in the accuracy of SIF calculation such as number of terms in William's equation and the region of analysis around the crack were discussed. The DIC results were compared with the numerical results available in literature and a very good agreement between them was observed. By extending the tests up to the critical state, mode I fracture toughness was determined by analyzing the image of specimen captured at the moment before fracture. The results showed that the digital image correlation was a reliable technique for the calculation of the fracture toughness of brittle materials.

Cluster signal-to-noise analysis for evaluation of the information content in an image.

PubMed

Weerawanich, Warangkana; Shimizu, Mayumi; Takeshita, Yohei; Okamura, Kazutoshi; Yoshida, Shoko; Yoshiura, Kazunori

2018-01-01

(1) To develop an observer-free method of analysing image quality related to the observer performance in the detection task and (2) to analyse observer behaviour patterns in the detection of small mass changes in cone-beam CT images. 13 observers detected holes in a Teflon phantom in cone-beam CT images. Using the same images, we developed a new method, cluster signal-to-noise analysis, to detect the holes by applying various cut-off values using ImageJ and reconstructing cluster signal-to-noise curves. We then evaluated the correlation between cluster signal-to-noise analysis and the observer performance test. We measured the background noise in each image to evaluate the relationship with false positive rates (FPRs) of the observers. Correlations between mean FPRs and intra- and interobserver variations were also evaluated. Moreover, we calculated true positive rates (TPRs) and accuracies from background noise and evaluated their correlations with TPRs from observers. Cluster signal-to-noise curves were derived in cluster signal-to-noise analysis. They yield the detection of signals (true holes) related to noise (false holes). This method correlated highly with the observer performance test (R 2 = 0.9296). In noisy images, increasing background noise resulted in higher FPRs and larger intra- and interobserver variations. TPRs and accuracies calculated from background noise had high correlation with actual TPRs from observers; R 2 was 0.9244 and 0.9338, respectively. Cluster signal-to-noise analysis can simulate the detection performance of observers and thus replace the observer performance test in the evaluation of image quality. Erroneous decision-making increased with increasing background noise.

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.

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.

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.

Cardiac magnetic resonance analysis of right ventricular function: comparison of quantification in the short-axis and 4-chamber planes.

PubMed

Souto Bayarri, M; Masip Capdevila, L; Remuiñan Pereira, C; Suárez-Cuenca, J J; Martínez Monzonís, A; Couto Pérez, M I; Carreira Villamor, J M

2015-01-01

To compare the methods of right ventricle segmentation in the short-axis and 4-chamber planes in cardiac magnetic resonance imaging and to correlate the findings with those of the tricuspid annular plane systolic excursion (TAPSE) method in echocardiography. We used a 1.5T MRI scanner to study 26 patients with diverse cardiovascular diseases. In all MRI studies, we obtained cine-mode images from the base to the apex in both the short-axis and 4-chamber planes using steady-state free precession sequences and 6mm thick slices. In all patients, we quantified the end-diastolic volume, end-systolic volume, and the ejection fraction of the right ventricle. On the same day as the cardiac magnetic resonance imaging study, 14 patients also underwent echocardiography with TAPSE calculation of right ventricular function. No statistically significant differences were found in the volumes and function of the right ventricle calculated using the 2 segmentation methods. The correlation between the volume estimations by the two segmentation methods was excellent (r=0,95); the correlation for the ejection fraction was slightly lower (r=0,8). The correlation between the cardiac magnetic resonance imaging estimate of right ventricular ejection fraction and TAPSE was very low (r=0,2, P<.01). Both ventricular segmentation methods quantify right ventricular function adequately. The correlation with the echocardiographic method is low. Copyright © 2012 SERAM. Published by Elsevier España, S.L.U. All rights reserved.

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%.

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 .

Motion tracking in MR-guided liver therapy by using navigator echoes and projection profile matching.

PubMed

Tokuda, Junichi; Morikawa, Shigehiro; Dohi, Takeyoshi; Hata, Nobuhiko

2004-01-01

Image registration in magnetic resonance (MR) image-guided liver therapy enhances surgical guidance by fusing preoperative multimodality images with intraoperative images, or by fusing intramodality images to correlate serial intraoperative images to monitor the effect of therapy. The objective of this paper is to describe the application of navigator echo and projection profile matching to fast two-dimensional image registration for MR-guided liver therapy. We obtain navigator echoes along the read-out and phase-encoding directions by using modified gradient echo imaging. This registration is made possible by masking out the liver profile from the image and performing profile matching with cross-correlation or mutual information as similarity measures. The set of experiments include a phantom study with a 2.0-T experimental MR scanner, and a volunteer and a clinical study with a 0.5-T open-configuration MR scanner, and these evaluate the accuracy and effectiveness of this method for liver therapy. Both the phantom and volunteer study indicate that this method can perform registration in 34 ms with root-mean-square error of 1.6 mm when the given misalignment of a liver is 30 mm. The clinical studies demonstrate that the method can track liver motion of up to approximately 40 mm. Matching profiles with cross-correlation information perform better than with mutual information in terms of robustness and speed. The proposed image registration method has potential clinical impact on and advantages for MR-guided liver therapy.

Correlation between hippocampal volumes and medial temporal lobe atrophy in patients with Alzheimer's disease.

PubMed

Dhikav, Vikas; Duraiswamy, Sharmila; Anand, Kuljeet Singh

2017-01-01

Hippocampus undergoes atrophy in patients with Alzheimer's disease (AD). Calculation of hippocampal volumes can be done by a variety of methods using T1-weighted images of magnetic resonance imaging (MRI) of the brain. Medial temporal lobes atrophy (MTL) can be rated visually using T1-weighted MRI brain images. The present study was done to see if any correlation existed between hippocampal volumes and visual rating scores of the MTL using Scheltens Visual Rating Method. We screened 84 subjects presented to the Department of Neurology of a Tertiary Care Hospital and enrolled forty subjects meeting the National Institute of Neurological and Communicative Disorders and Stroke, AD related Disease Association criteria. Selected patients underwent MRI brain and T1-weighted images in a plane perpendicular to long axis of hippocampus were obtained. Hippocampal volumes were calculated manually using a standard protocol. The calculated hippocampal volumes were correlated with Scheltens Visual Rating Method for Rating MTL. A total of 32 cognitively normal age-matched subjects were selected to see the same correlation in the healthy subjects as well. Sensitivity and specificity of both methods was calculated and compared. There was an insignificant correlation between the hippocampal volumes and MTL rating scores in cognitively normal elderly ( n = 32; Pearson Correlation coefficient = 0.16, P > 0.05). In the AD Group, there was a moderately strong correlation between measured hippocampal volumes and MTL Rating (Pearson's correlation coefficient = -0.54; P < 0.05. There was a moderately strong correlation between hippocampal volume and Mini-Mental Status Examination in the AD group. Manual delineation was superior compared to the visual method ( P < 0.05). Good correlation was present between manual hippocampal volume measurements and MTL scores. Sensitivity and specificity of manual measurement of hippocampus was higher compared to visual rating scores for MTL in patients with AD.

A modified anomaly detection method for capsule endoscopy images using non-linear color conversion and Higher-order Local Auto-Correlation (HLAC).

PubMed

Hu, Erzhong; Nosato, Hirokazu; Sakanashi, Hidenori; Murakawa, Masahiro

2013-01-01

Capsule endoscopy is a patient-friendly endoscopy broadly utilized in gastrointestinal examination. However, the efficacy of diagnosis is restricted by the large quantity of images. This paper presents a modified anomaly detection method, by which both known and unknown anomalies in capsule endoscopy images of small intestine are expected to be detected. To achieve this goal, this paper introduces feature extraction using a non-linear color conversion and Higher-order Local Auto Correlation (HLAC) Features, and makes use of image partition and subspace method for anomaly detection. Experiments are implemented among several major anomalies with combinations of proposed techniques. As the result, the proposed method achieved 91.7% and 100% detection accuracy for swelling and bleeding respectively, so that the effectiveness of proposed method is demonstrated.

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: A postmortem study

PubMed Central

Ding, Huanjun; Johnson, Travis; Lin, Muqing; Le, Huy Q.; Ducote, Justin L.; Su, Min-Ying; Molloi, Sabee

2013-01-01

Purpose: Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. Methods: T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left–right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. Results: The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left–right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left–right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. Conclusions: The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications. PMID:24320536

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.

Filling the gap: adding super-resolution to array tomography for correlated ultrastructural and molecular identification of electrical synapses at the C. elegans connectome.

PubMed

Markert, Sebastian Matthias; Britz, Sebastian; Proppert, Sven; Lang, Marietta; Witvliet, Daniel; Mulcahy, Ben; Sauer, Markus; Zhen, Mei; Bessereau, Jean-Louis; Stigloher, Christian

2016-10-01

Correlating molecular labeling at the ultrastructural level with high confidence remains challenging. Array tomography (AT) allows for a combination of fluorescence and electron microscopy (EM) to visualize subcellular protein localization on serial EM sections. Here, we describe an application for AT that combines near-native tissue preservation via high-pressure freezing and freeze substitution with super-resolution light microscopy and high-resolution scanning electron microscopy (SEM) analysis on the same section. We established protocols that combine SEM with structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM). We devised a method for easy, precise, and unbiased correlation of EM images and super-resolution imaging data using endogenous cellular landmarks and freely available image processing software. We demonstrate that these methods allow us to identify and label gap junctions in Caenorhabditis elegans with precision and confidence, and imaging of even smaller structures is feasible. With the emergence of connectomics, these methods will allow us to fill in the gap-acquiring the correlated ultrastructural and molecular identity of electrical synapses.

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

Estimation bias from using nonlinear Fourier plane correlators for sub-pixel image shift measurement and implications for the binary joint transform correlator

NASA Astrophysics Data System (ADS)

Grycewicz, Thomas J.; Florio, Christopher J.; Franz, Geoffrey A.; Robinson, Ross E.

2007-09-01

When using Fourier plane digital algorithms or an optical correlator to measure the correlation between digital images, interpolation by center-of-mass or quadratic estimation techniques can be used to estimate image displacement to the sub-pixel level. However, this can lead to a bias in the correlation measurement. This bias shifts the sub-pixel output measurement to be closer to the nearest pixel center than the actual location. The paper investigates the bias in the outputs of both digital and optical correlators, and proposes methods to minimize this effect. We use digital studies and optical implementations of the joint transform correlator to demonstrate optical registration with accuracies better than 0.1 pixels. We use both simulations of image shift and movies of a moving target as inputs. We demonstrate bias error for both center-of-mass and quadratic interpolation, and discuss the reasons that this bias is present. Finally, we suggest measures to reduce or eliminate the bias effects. We show that when sub-pixel bias is present, it can be eliminated by modifying the interpolation method. By removing the bias error, we improve registration accuracy by thirty percent.

Correlative Stochastic Optical Reconstruction Microscopy and Electron Microscopy

PubMed Central

Kim, Doory; Deerinck, Thomas J.; Sigal, Yaron M.; Babcock, Hazen P.; Ellisman, Mark H.; Zhuang, Xiaowei

2015-01-01

Correlative fluorescence light microscopy and electron microscopy allows the imaging of spatial distributions of specific biomolecules in the context of cellular ultrastructure. Recent development of super-resolution fluorescence microscopy allows the location of molecules to be determined with nanometer-scale spatial resolution. However, correlative super-resolution fluorescence microscopy and electron microscopy (EM) still remains challenging because the optimal specimen preparation and imaging conditions for super-resolution fluorescence microscopy and EM are often not compatible. Here, we have developed several experiment protocols for correlative stochastic optical reconstruction microscopy (STORM) and EM methods, both for un-embedded samples by applying EM-specific sample preparations after STORM imaging and for embedded and sectioned samples by optimizing the fluorescence under EM fixation, staining and embedding conditions. We demonstrated these methods using a variety of cellular targets. PMID:25874453

New method for identifying features of an image on a digital video display

NASA Astrophysics Data System (ADS)

Doyle, Michael D.

1991-04-01

The MetaMap process extends the concept of direct manipulation human-computer interfaces to new limits. Its specific capabilities include the correlation of discrete image elements to relevant text information and the correlation of these image features to other images as well as to program control mechanisms. The correlation is accomplished through reprogramming of both the color map and the image so that discrete image elements comprise unique sets of color indices. This process allows the correlation to be accomplished with very efficient data storage and program execution times. Image databases adapted to this process become object-oriented as a result. Very sophisticated interrelationships can be set up between images text and program control mechanisms using this process. An application of this interfacing process to the design of an interactive atlas of medical histology as well as other possible applications are described. The MetaMap process is protected by U. S. patent #4

Joint Transform Correlation for face tracking: elderly fall detection application

NASA Astrophysics Data System (ADS)

Katz, Philippe; Aron, Michael; Alfalou, Ayman

2013-03-01

In this paper, an iterative tracking algorithm based on a non-linear JTC (Joint Transform Correlator) architecture and enhanced by a digital image processing method is proposed and validated. This algorithm is based on the computation of a correlation plane where the reference image is updated at each frame. For that purpose, we use the JTC technique in real time to track a patient (target image) in a room fitted with a video camera. The correlation plane is used to localize the target image in the current video frame (frame i). Then, the reference image to be exploited in the next frame (frame i+1) is updated according to the previous one (frame i). In an effort to validate our algorithm, our work is divided into two parts: (i) a large study based on different sequences with several situations and different JTC parameters is achieved in order to quantify their effects on the tracking performances (decimation, non-linearity coefficient, size of the correlation plane, size of the region of interest...). (ii) the tracking algorithm is integrated into an application of elderly fall detection. The first reference image is a face detected by means of Haar descriptors, and then localized into the new video image thanks to our tracking method. In order to avoid a bad update of the reference frame, a method based on a comparison of image intensity histograms is proposed and integrated in our algorithm. This step ensures a robust tracking of the reference frame. This article focuses on face tracking step optimisation and evalutation. A supplementary step of fall detection, based on vertical acceleration and position, will be added and studied in further work.

Self-image of the Patients with Head and Neck Cancer: A Mixed Method Research

PubMed Central

Nayak, Shalini G; Pai, Mamatha Shivananda; George, Linu Sara

2016-01-01

Aim: The aim of the study was to assess the self-image of the patients with head and neck cancers (HNCs) by using a mixed method research. Subjects and Methods: A mixed method approach and triangulation design was used with the aim of assessing the self-image of the patients with HNCs. Data was gathered by using self-administered self-image scale and structured interview. Nested sampling technique was adopted. Sample size for quantitative approach was 54 and data saturation was achieved with seven subjects for qualitative approach. Institutional Ethical Committee clearance was obtained. Results: The results of the study showed that 30 (56%) subjects had positive self-image and 24 (44%) had negative self-image. There was a moderate positive correlation between body image and integrity (r = 0.430, P = 0.001), weak positive correlation between body image and self-esteem (r = 0.270, P = 0.049), and no correlation between self-esteem and integrity (r = 0.203, P = 0.141). The participants also scored maximum (24/24) in the areas of body image and self-esteem. Similar findings were also observed in the phenomenological approach. The themes evolved were immaterial of outer appearance and desire of good health to all. Conclusion: The illness is long-term and impacts the individual 24 h a day. Understanding patients’ self-concept and living experiences of patients with HNC is important for the health care professionals to improve the care. PMID:27559264

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.

Correlating objective and subjective evaluation of texture appearance with applications to camera phone imaging

NASA Astrophysics Data System (ADS)

Phillips, Jonathan B.; Coppola, Stephen M.; Jin, Elaine W.; Chen, Ying; Clark, James H.; Mauer, Timothy A.

2009-01-01

Texture appearance is an important component of photographic image quality as well as object recognition. Noise cleaning algorithms are used to decrease sensor noise of digital images, but can hinder texture elements in the process. The Camera Phone Image Quality (CPIQ) initiative of the International Imaging Industry Association (I3A) is developing metrics to quantify texture appearance. Objective and subjective experimental results of the texture metric development are presented in this paper. Eight levels of noise cleaning were applied to ten photographic scenes that included texture elements such as faces, landscapes, architecture, and foliage. Four companies (Aptina Imaging, LLC, Hewlett-Packard, Eastman Kodak Company, and Vista Point Technologies) have performed psychophysical evaluations of overall image quality using one of two methods of evaluation. Both methods presented paired comparisons of images on thin film transistor liquid crystal displays (TFT-LCD), but the display pixel pitch and viewing distance differed. CPIQ has also been developing objective texture metrics and targets that were used to analyze the same eight levels of noise cleaning. The correlation of the subjective and objective test results indicates that texture perception can be modeled with an objective metric. The two methods of psychophysical evaluation exhibited high correlation despite the differences in methodology.

Correlates of Intellectual Ability with Morphology of the Hippocampus and Amygdala in Healthy Adults

ERIC Educational Resources Information Center

Amat, Jose A.; Bansal, Ravi; Whiteman, Ronald; Haggerty, Rita; Royal, Jason; Peterson, Bradley S.

2008-01-01

Several prior imaging studies of healthy adults have correlated volumes of the hippocampus and amygdala with measures of general intelligence (IQ), with variable results. In this study, we assessed correlations between volumes of the hippocampus and amygdala and full-scale IQ scores (FSIQ) using a method of image analysis that permits detailed…

Incoherent Diffractive Imaging via Intensity Correlations of Hard X Rays

NASA Astrophysics Data System (ADS)

Classen, Anton; Ayyer, Kartik; Chapman, Henry N.; Röhlsberger, Ralf; von Zanthier, Joachim

2017-08-01

Established x-ray diffraction methods allow for high-resolution structure determination of crystals, crystallized protein structures, or even single molecules. While these techniques rely on coherent scattering, incoherent processes like fluorescence emission—often the predominant scattering mechanism—are generally considered detrimental for imaging applications. Here, we show that intensity correlations of incoherently scattered x-ray radiation can be used to image the full 3D arrangement of the scattering atoms with significantly higher resolution compared to conventional coherent diffraction imaging and crystallography, including additional three-dimensional information in Fourier space for a single sample orientation. We present a number of properties of incoherent diffractive imaging that are conceptually superior to those of coherent methods.

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.

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

Improved Discrete Approximation of Laplacian of Gaussian

NASA Technical Reports Server (NTRS)

Shuler, Robert L., Jr.

2004-01-01

An improved method of computing a discrete approximation of the Laplacian of a Gaussian convolution of an image has been devised. The primary advantage of the method is that without substantially degrading the accuracy of the end result, it reduces the amount of information that must be processed and thus reduces the amount of circuitry needed to perform the Laplacian-of- Gaussian (LOG) operation. Some background information is necessary to place the method in context. The method is intended for application to the LOG part of a process of real-time digital filtering of digitized video data that represent brightnesses in pixels in a square array. The particular filtering process of interest is one that converts pixel brightnesses to binary form, thereby reducing the amount of information that must be performed in subsequent correlation processing (e.g., correlations between images in a stereoscopic pair for determining distances or correlations between successive frames of the same image for detecting motions). The Laplacian is often included in the filtering process because it emphasizes edges and textures, while the Gaussian is often included because it smooths out noise that might not be consistent between left and right images or between successive frames of the same image.

Time reversal imaging and cross-correlations techniques by normal mode theory

NASA Astrophysics Data System (ADS)

Montagner, J.; Fink, M.; Capdeville, Y.; Phung, H.; Larmat, C.

2007-12-01

Time-reversal methods were successfully applied in the past to acoustic waves in many fields such as medical imaging, underwater acoustics, non destructive testing and recently to seismic waves in seismology for earthquake imaging. The increasing power of computers and numerical methods (such as spectral element methods) enables one to simulate more and more accurately the propagation of seismic waves in heterogeneous media and to develop new applications, in particular time reversal in the three-dimensional Earth. Generalizing the scalar approach of Draeger and Fink (1999), the theoretical understanding of time-reversal method can be addressed for the 3D- elastic Earth by using normal mode theory. It is shown how to relate time- reversal methods on one hand, with auto-correlation of seismograms for source imaging and on the other hand, with cross-correlation between receivers for structural imaging and retrieving Green function. The loss of information will be discussed. In the case of source imaging, automatic location in time and space of earthquakes and unknown sources is obtained by time reversal technique. In the case of big earthquakes such as the Sumatra-Andaman earthquake of december 2004, we were able to reconstruct the spatio-temporal history of the rupture. We present here some new applications at the global scale of these techniques on synthetic tests and on real data.

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

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.

Quantitative analysis of tympanic membrane perforation: a simple and reliable method.

PubMed

Ibekwe, T S; Adeosun, A A; Nwaorgu, O G

2009-01-01

Accurate assessment of the features of tympanic membrane perforation, especially size, site, duration and aetiology, is important, as it enables optimum management. To describe a simple, cheap and effective method of quantitatively analysing tympanic membrane perforations. The system described comprises a video-otoscope (capable of generating still and video images of the tympanic membrane), adapted via a universal serial bus box to a computer screen, with images analysed using the Image J geometrical analysis software package. The reproducibility of results and their correlation with conventional otoscopic methods of estimation were tested statistically with the paired t-test and correlational tests, using the Statistical Package for the Social Sciences version 11 software. The following equation was generated: P/T x 100 per cent = percentage perforation, where P is the area (in pixels2) of the tympanic membrane perforation and T is the total area (in pixels2) for the entire tympanic membrane (including the perforation). Illustrations are shown. Comparison of blinded data on tympanic membrane perforation area obtained independently from assessments by two trained otologists, of comparative years of experience, using the video-otoscopy system described, showed similar findings, with strong correlations devoid of inter-observer error (p = 0.000, r = 1). Comparison with conventional otoscopic assessment also indicated significant correlation, comparing results for two trained otologists, but some inter-observer variation was present (p = 0.000, r = 0.896). Correlation between the two methods for each of the otologists was also highly significant (p = 0.000). A computer-adapted video-otoscope, with images analysed by Image J software, represents a cheap, reliable, technology-driven, clinical method of quantitative analysis of tympanic membrane perforations and injuries.

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.

Quality evaluation of no-reference MR images using multidirectional filters and image statistics.

PubMed

Jang, Jinseong; Bang, Kihun; Jang, Hanbyol; Hwang, Dosik

2018-09-01

This study aimed to develop a fully automatic, no-reference image-quality assessment (IQA) method for MR images. New quality-aware features were obtained by applying multidirectional filters to MR images and examining the feature statistics. A histogram of these features was then fitted to a generalized Gaussian distribution function for which the shape parameters yielded different values depending on the type of distortion in the MR image. Standard feature statistics were established through a training process based on high-quality MR images without distortion. Subsequently, the feature statistics of a test MR image were calculated and compared with the standards. The quality score was calculated as the difference between the shape parameters of the test image and the undistorted standard images. The proposed IQA method showed a >0.99 correlation with the conventional full-reference assessment methods; accordingly, this proposed method yielded the best performance among no-reference IQA methods for images containing six types of synthetic, MR-specific distortions. In addition, for authentically distorted images, the proposed method yielded the highest correlation with subjective assessments by human observers, thus demonstrating its superior performance over other no-reference IQAs. Our proposed IQA was designed to consider MR-specific features and outperformed other no-reference IQAs designed mainly for photographic images. Magn Reson Med 80:914-924, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Breast density quantification using magnetic resonance imaging (MRI) with bias field correction: a postmortem study.

PubMed

Ding, Huanjun; Johnson, Travis; Lin, Muqing; Le, Huy Q; Ducote, Justin L; Su, Min-Ying; Molloi, Sabee

2013-12-01

Quantification of breast density based on three-dimensional breast MRI may provide useful information for the early detection of breast cancer. However, the field inhomogeneity can severely challenge the computerized image segmentation process. In this work, the effect of the bias field in breast density quantification has been investigated with a postmortem study. T1-weighted images of 20 pairs of postmortem breasts were acquired on a 1.5 T breast MRI scanner. Two computer-assisted algorithms were used to quantify the volumetric breast density. First, standard fuzzy c-means (FCM) clustering was used on raw images with the bias field present. Then, the coherent local intensity clustering (CLIC) method estimated and corrected the bias field during the iterative tissue segmentation process. Finally, FCM clustering was performed on the bias-field-corrected images produced by CLIC method. The left-right correlation for breasts in the same pair was studied for both segmentation algorithms to evaluate the precision of the tissue classification. Finally, the breast densities measured with the three methods were compared to the gold standard tissue compositions obtained from chemical analysis. The linear correlation coefficient, Pearson's r, was used to evaluate the two image segmentation algorithms and the effect of bias field. The CLIC method successfully corrected the intensity inhomogeneity induced by the bias field. In left-right comparisons, the CLIC method significantly improved the slope and the correlation coefficient of the linear fitting for the glandular volume estimation. The left-right breast density correlation was also increased from 0.93 to 0.98. When compared with the percent fibroglandular volume (%FGV) from chemical analysis, results after bias field correction from both the CLIC the FCM algorithms showed improved linear correlation. As a result, the Pearson's r increased from 0.86 to 0.92 with the bias field correction. The investigated CLIC method significantly increased the precision and accuracy of breast density quantification using breast MRI images by effectively correcting the bias field. It is expected that a fully automated computerized algorithm for breast density quantification may have great potential in clinical MRI applications.

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

Li, B; Southern Medical University, Guangzhou, Guangdong; Shen, C

Purpose: Multi-energy computed tomography (MECT) is an emerging application in medical imaging due to its ability of material differentiation and potential for molecular imaging. In MECT, image correlations at different spatial and channels exist. It is desirable to incorporate these correlations in reconstruction to improve image quality. For this purpose, this study proposes a MECT reconstruction technique that employes spatial spectral non-local means (ssNLM) regularization. Methods: We consider a kVp-switching scanning method in which source energy is rapidly switched during data acquisition. For each energy channel, this yields projection data acquired at a number of angles, whereas projection angles amongmore » channels are different. We formulate the reconstruction task as an optimziation problem. A least square term enfores data fidelity. A ssNLM term is used as regularization to encourage similarities among image patches at different spatial locations and channels. When comparing image patches at different channels, intensity difference were corrected by a transformation estimated via histogram equalization during the reconstruction process. Results: We tested our method in a simulation study with a NCAT phantom and an experimental study with a Gammex phantom. For comparison purpose, we also performed reconstructions using conjugate-gradient least square (CGLS) method and conventional NLM method that only considers spatial correlation in an image. ssNLM is able to better suppress streak artifacts. The streaks are along different projection directions in images at different channels. ssNLM discourages this dissimilarity and hence removes them. True image structures are preserved in this process. Measurements in regions of interests yield 1.1 to 3.2 and 1.5 to 1.8 times higher contrast to noise ratio than the NLM approach. Improvements over CGLS is even more profound due to lack of regularization in the CGLS method and hence amplified noise. Conclusion: The proposed ssNLM method for kVp-switching MECT reconstruction can achieve high quality MECT images.« less

TH-E-17A-07: Improved Cine Four-Dimensional Computed Tomography (4D CT) Acquisition and Processing Method

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

Castillo, S; Castillo, R; Castillo, E

2014-06-15

Purpose: Artifacts arising from the 4D CT acquisition and post-processing methods add systematic uncertainty to the treatment planning process. We propose an alternate cine 4D CT acquisition and post-processing method to consistently reduce artifacts, and explore patient parameters indicative of image quality. Methods: In an IRB-approved protocol, 18 patients with primary thoracic malignancies received a standard cine 4D CT acquisition followed by an oversampling 4D CT that doubled the number of images acquired. A second cohort of 10 patients received the clinical 4D CT plus 3 oversampling scans for intra-fraction reproducibility. The clinical acquisitions were processed by the standard phasemore » sorting method. The oversampling acquisitions were processed using Dijkstras algorithm to optimize an artifact metric over available image data. Image quality was evaluated with a one-way mixed ANOVA model using a correlation-based artifact metric calculated from the final 4D CT image sets. Spearman correlations and a linear mixed model tested the association between breathing parameters, patient characteristics, and image quality. Results: The oversampling 4D CT scans reduced artifact presence significantly by 27% and 28%, for the first cohort and second cohort respectively. From cohort 2, the inter-replicate deviation for the oversampling method was within approximately 13% of the cross scan average at the 0.05 significance level. Artifact presence for both clinical and oversampling methods was significantly correlated with breathing period (ρ=0.407, p-value<0.032 clinical, ρ=0.296, p-value<0.041 oversampling). Artifact presence in the oversampling method was significantly correlated with amount of data acquired, (ρ=-0.335, p-value<0.02) indicating decreased artifact presence with increased breathing cycles per scan location. Conclusion: The 4D CT oversampling acquisition with optimized sorting reduced artifact presence significantly and reproducibly compared to the phase-sorted clinical acquisition.« less

Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images

PubMed Central

Gutmann, Michael U.; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation. PMID:24533049

Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.

PubMed

Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.

Application of nonlinear phenomena induced by focused ultrasound to bone imaging.

PubMed

Callé, Samuel; Remenieras, Jean-Pierre; Bou Matar, Olivier; Defontaine, Marielle; Patat, Frederic

2003-03-01

A tissue deformability image is obtained with the vibroacoustography imaging method using mechanical low-frequency (LF) excitation. This ultrasonic excitation is created locally by means of a focused annular array emitting two primary beams at two close frequencies, f(1) and f(2) (f(2) = f(1) + f(LF)). The LF acoustic emission resulting from the vibration of the medium is detected by a sensitive hydrophone and then used to form the image. This noninvasive imaging method was demonstrated in this study to be suitable for bone imaging, with x and y transverse resolutions less than 300 micro m. Two bone sites susceptible to demineralization were tested: the calcaneus and the neck of the femur. The vibroacoustic method provides valuable ultrasonic images regarding the structure and the elastic properties of bone tissue. Correlation was made between vibroacoustic bone images, performed in vitro, and images acquired by other imaging methods (i.e., bone ultrasound attenuation and x-ray computerized tomography (CT)). Moreover, the amplitudes of vibroacoustic signals radiating from phosphocalcic ceramic samples (bone substitute) of different porosity were evaluated. The good correlation between these results and the description of our images and the quality of vibroacoustic images indicate that bone decalcification could be detected using vibroacoustography.

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.

Self-image of the Patients with Head and Neck Cancer: A Mixed Method Research.

PubMed

Nayak, Shalini G; Pai, Mamatha Shivananda; George, Linu Sara

2016-01-01

The aim of the study was to assess the self-image of the patients with head and neck cancers (HNCs) by using a mixed method research. A mixed method approach and triangulation design was used with the aim of assessing the self-image of the patients with HNCs. Data was gathered by using self-administered self-image scale and structured interview. Nested sampling technique was adopted. Sample size for quantitative approach was 54 and data saturation was achieved with seven subjects for qualitative approach. Institutional Ethical Committee clearance was obtained. The results of the study showed that 30 (56%) subjects had positive self-image and 24 (44%) had negative self-image. There was a moderate positive correlation between body image and integrity (r = 0.430, P = 0.001), weak positive correlation between body image and self-esteem (r = 0.270, P = 0.049), and no correlation between self-esteem and integrity (r = 0.203, P = 0.141). The participants also scored maximum (24/24) in the areas of body image and self-esteem. Similar findings were also observed in the phenomenological approach. The themes evolved were immaterial of outer appearance and desire of good health to all. The illness is long-term and impacts the individual 24 h a day. Understanding patients' self-concept and living experiences of patients with HNC is important for the health care professionals to improve the care.

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.

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.

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.

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

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.

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.

Optical Flow for Flight and Wind Tunnel Background Oriented Schlieren Imaging

NASA Technical Reports Server (NTRS)

Smith, Nathanial T.; Heineck, James T.; Schairer, Edward T.

2017-01-01

Background oriented Schlieren images have historically been generated by calculating the observed pixel displacement between a wind-on and wind-o image pair using normalized cross-correlation. This work uses optical flow to solve the displacement fields which generate the Schlieren images. A well established method used in the computer vision community, optical flow is the apparent motion in an image sequence due to brightness changes. The regularization method of Horn and Schunck is used to create Schlieren images using two data sets: a supersonic jet plume shock interaction from the NASA Ames Unitary Plan Wind Tunnel, and a transonic flight test of a T-38 aircraft using a naturally occurring background, performed in conjunction with NASA Ames and Armstrong Research Centers. Results are presented and contrasted with those using normalized cross-correlation. The optical flow Schlieren images are found to provided significantly more detail. We apply the method to historical data sets to demonstrate the broad applicability and limitations of the technique.

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

Optical joint correlator for real-time image tracking and retinal surgery

NASA Technical Reports Server (NTRS)

Juday, Richard D. (Inventor)

1991-01-01

A method for tracking an object in a sequence of images is described. Such sequence of images may, for example, be a sequence of television frames. The object in the current frame is correlated with the object in the previous frame to obtain the relative location of the object in the two frames. An optical joint transform correlator apparatus is provided to carry out the process. Such joint transform correlator apparatus forms the basis for laser eye surgical apparatus where an image of the fundus of an eyeball is stabilized and forms the basis for the correlator apparatus to track the position of the eyeball caused by involuntary movement. With knowledge of the eyeball position, a surgical laser can be precisely pointed toward a position on the retina.

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.

Determining the Number of Components from the Matrix of Partial Correlations

ERIC Educational Resources Information Center

Velicer, Wayne F.

1976-01-01

A method is presented for determining the number of components to retain in a principal components or image components analysis which utilizes a matrix of partial correlations. Advantages and uses of the method are discussed and a comparison of the proposed method with existing methods is presented. (JKS)

Statistical image reconstruction from correlated data with applications to PET

PubMed Central

Alessio, Adam; Sauer, Ken; Kinahan, Paul

2008-01-01

Most statistical reconstruction methods for emission tomography are designed for data modeled as conditionally independent Poisson variates. In reality, due to scanner detectors, electronics and data processing, correlations are introduced into the data resulting in dependent variates. In general, these correlations are ignored because they are difficult to measure and lead to computationally challenging statistical reconstruction algorithms. This work addresses the second concern, seeking to simplify the reconstruction of correlated data and provide a more precise image estimate than the conventional independent methods. In general, correlated variates have a large non-diagonal covariance matrix that is computationally challenging to use as a weighting term in a reconstruction algorithm. This work proposes two methods to simplify the use of a non-diagonal covariance matrix as the weighting term by (a) limiting the number of dimensions in which the correlations are modeled and (b) adopting flexible, yet computationally tractable, models for correlation structure. We apply and test these methods with simple simulated PET data and data processed with the Fourier rebinning algorithm which include the one-dimensional correlations in the axial direction and the two-dimensional correlations in the transaxial directions. The methods are incorporated into a penalized weighted least-squares 2D reconstruction and compared with a conventional maximum a posteriori approach. PMID:17921576

Correlating Intravital Multi-Photon Microscopy to 3D Electron Microscopy of Invading Tumor Cells Using Anatomical Reference Points

PubMed Central

Karreman, Matthia A.; Mercier, Luc; Schieber, Nicole L.; Shibue, Tsukasa; Schwab, Yannick; Goetz, Jacky G.

2014-01-01

Correlative microscopy combines the advantages of both light and electron microscopy to enable imaging of rare and transient events at high resolution. Performing correlative microscopy in complex and bulky samples such as an entire living organism is a time-consuming and error-prone task. Here, we investigate correlative methods that rely on the use of artificial and endogenous structural features of the sample as reference points for correlating intravital fluorescence microscopy and electron microscopy. To investigate tumor cell behavior in vivo with ultrastructural accuracy, a reliable approach is needed to retrieve single tumor cells imaged deep within the tissue. For this purpose, fluorescently labeled tumor cells were subcutaneously injected into a mouse ear and imaged using two-photon-excitation microscopy. Using near-infrared branding, the position of the imaged area within the sample was labeled at the skin level, allowing for its precise recollection. Following sample preparation for electron microscopy, concerted usage of the artificial branding and anatomical landmarks enables targeting and approaching the cells of interest while serial sectioning through the specimen. We describe here three procedures showing how three-dimensional (3D) mapping of structural features in the tissue can be exploited to accurately correlate between the two imaging modalities, without having to rely on the use of artificially introduced markers of the region of interest. The methods employed here facilitate the link between intravital and nanoscale imaging of invasive tumor cells, enabling correlating function to structure in the study of tumor invasion and metastasis. PMID:25479106

Proceedings of the Third Annual Symposium on Mathematical Pattern Recognition and Image Analysis

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.

1985-01-01

Topics addressed include: multivariate spline method; normal mixture analysis applied to remote sensing; image data analysis; classifications in spatially correlated environments; probability density functions; graphical nonparametric methods; subpixel registration analysis; hypothesis integration in image understanding systems; rectification of satellite scanner imagery; spatial variation in remotely sensed images; smooth multidimensional interpolation; and optimal frequency domain textural edge detection filters.

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.

TU-D-209-03: Alignment of the Patient Graphic Model Using Fluoroscopic Images for Skin Dose Mapping

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

Oines, A; Oines, A; Kilian-Meneghin, J

2016-06-15

Purpose: The Dose Tracking System (DTS) was developed to provide realtime feedback of skin dose and dose rate during interventional fluoroscopic procedures. A color map on a 3D graphic of the patient represents the cumulative dose distribution on the skin. Automated image correlation algorithms are described which use the fluoroscopic procedure images to align and scale the patient graphic for more accurate dose mapping. Methods: Currently, the DTS employs manual patient graphic selection and alignment. To improve the accuracy of dose mapping and automate the software, various methods are explored to extract information about the beam location and patient morphologymore » from the procedure images. To match patient anatomy with a reference projection image, preprocessing is first used, including edge enhancement, edge detection, and contour detection. Template matching algorithms from OpenCV are then employed to find the location of the beam. Once a match is found, the reference graphic is scaled and rotated to fit the patient, using image registration correlation functions in Matlab. The algorithm runs correlation functions for all points and maps all correlation confidences to a surface map. The highest point of correlation is used for alignment and scaling. The transformation data is saved for later model scaling. Results: Anatomic recognition is used to find matching features between model and image and image registration correlation provides for alignment and scaling at any rotation angle with less than onesecond runtime, and at noise levels in excess of 150% of those found in normal procedures. Conclusion: The algorithm provides the necessary scaling and alignment tools to improve the accuracy of dose distribution mapping on the patient graphic with the DTS. Partial support from NIH Grant R01-EB002873 and Toshiba Medical Systems Corp.« less

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.

Improvement in the measurement error of the specific binding ratio in dopamine transporter SPECT imaging due to exclusion of the cerebrospinal fluid fraction using the threshold of voxel RI count.

PubMed

Mizumura, Sunao; Nishikawa, Kazuhiro; Murata, Akihiro; Yoshimura, Kosei; Ishii, Nobutomo; Kokubo, Tadashi; Morooka, Miyako; Kajiyama, Akiko; Terahara, Atsuro

2018-05-01

In Japan, the Southampton method for dopamine transporter (DAT) SPECT is widely used to quantitatively evaluate striatal radioactivity. The specific binding ratio (SBR) is the ratio of specific to non-specific binding observed after placing pentagonal striatal voxels of interest (VOIs) as references. Although the method can reduce the partial volume effect, the SBR may fluctuate due to the presence of low-count areas of cerebrospinal fluid (CSF), caused by brain atrophy, in the striatal VOIs. We examined the effect of the exclusion of low-count VOIs on SBR measurement. We retrospectively reviewed DAT imaging of 36 patients with parkinsonian syndromes performed after injection of 123 I-FP-CIT. SPECT data were reconstructed using three conditions. We defined the CSF area in each SPECT image after segmenting the brain tissues. A merged image of gray and white matter images was constructed from each patient's magnetic resonance imaging (MRI) to create an idealized brain image that excluded the CSF fraction (MRI-mask method). We calculated the SBR and asymmetric index (AI) in the MRI-mask method for each reconstruction condition. We then calculated the mean and standard deviation (SD) of voxel RI counts in the reference VOI without the striatal VOIs in each image, and determined the SBR by excluding the low-count pixels (threshold method) using five thresholds: mean-0.0SD, mean-0.5SD, mean-1.0SD, mean-1.5SD, and mean-2.0SD. We also calculated the AIs from the SBRs measured using the threshold method. We examined the correlation among the SBRs of the threshold method, between the uncorrected SBRs and the SBRs of the MRI-mask method, and between the uncorrected AIs and the AIs of the MRI-mask method. The intraclass correlation coefficient indicated an extremely high correlation among the SBRs and among the AIs of the MRI-mask and threshold methods at thresholds between mean-2.0D and mean-1.0SD, regardless of the reconstruction correction. The differences among the SBRs and the AIs of the two methods were smallest at thresholds between man-2.0SD and mean-1.0SD. The SBR calculated using the threshold method was highly correlated with the MRI-SBR. These results suggest that the CSF correction of the threshold method is effective for the calculation of idealized SBR and AI values.

Spatiotemporal image correlation spectroscopy (STICS) theory, verification, and application to protein velocity mapping in living CHO cells.

PubMed

Hebert, Benedict; Costantino, Santiago; Wiseman, Paul W

2005-05-01

We introduce a new extension of image correlation spectroscopy (ICS) and image cross-correlation spectroscopy (ICCS) that relies on complete analysis of both the temporal and spatial correlation lags for intensity fluctuations from a laser-scanning microscopy image series. This new approach allows measurement of both diffusion coefficients and velocity vectors (magnitude and direction) for fluorescently labeled membrane proteins in living cells through monitoring of the time evolution of the full space-time correlation function. By using filtering in Fourier space to remove frequencies associated with immobile components, we are able to measure the protein transport even in the presence of a large fraction (>90%) of immobile species. We present the background theory, computer simulations, and analysis of measurements on fluorescent microspheres to demonstrate proof of principle, capabilities, and limitations of the method. We demonstrate mapping of flow vectors for mixed samples containing fluorescent microspheres with different emission wavelengths using space time image cross-correlation. We also present results from two-photon laser-scanning microscopy studies of alpha-actinin/enhanced green fluorescent protein fusion constructs at the basal membrane of living CHO cells. Using space-time image correlation spectroscopy (STICS), we are able to measure protein fluxes with magnitudes of mum/min from retracting lamellar regions and protrusions for adherent cells. We also demonstrate the measurement of correlated directed flows (magnitudes of mum/min) and diffusion of interacting alpha5 integrin/enhanced cyan fluorescent protein and alpha-actinin/enhanced yellow fluorescent protein within living CHO cells. The STICS method permits us to generate complete transport maps of proteins within subregions of the basal membrane even if the protein concentration is too high to perform single particle tracking measurements.

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.

Ultrasonography of the biliary tract - up to date. The importance of correlation between imaging methods and patients' signs and symptoms.

PubMed

Badea, Radu; Zaro, Răzvan; Tanțău, Marcel; Chiorean, Liliana

2015-09-01

Ultrasonography is generally accepted and performed as a first choice imaging technique in patients with jaundice. The method allows the discrimination between cholestatic and mechanical jaundice. The existing procedures are multiple: gray scale, Doppler, i.v. contrast enhancement, elastography, tridimensional ultrasonography, each of these with different contribution to the positive and differential diagnosis regarding the nature of the jaundice. The final diagnosis is a multimodal one and the efficiency is dependent on the level of the available technology, the examiner's experience, the degree and modality of integration of the data within the clinical context, as well as on the portfolio of available imaging procedures. This review shows the main ultrasonographic methods consecrated in the evaluation of the biliary tree. It also underlines the integrated character of the procedures, as well as the necessity to correlate with other imaging methods and the clinical situation.

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

Bubble structure evaluation method of sponge cake by using image morphology

NASA Astrophysics Data System (ADS)

Kato, Kunihito; Yamamoto, Kazuhiko; Nonaka, Masahiko; Katsuta, Yukiyo; Kasamatsu, Chinatsu

2007-01-01

Nowadays, many evaluation methods for food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that have been used for the quality evaluation recently. The goal of our research is structure evaluation of sponge cake by using the image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner, because the depth of field of this type scanner is very shallow. Therefore the bubble region of the surface has low gray scale value, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. The input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

Information theoretic approach for assessing image fidelity in photon-counting arrays.

PubMed

Narravula, Srikanth R; Hayat, Majeed M; Javidi, Bahram

2010-02-01

The method of photon-counting integral imaging has been introduced recently for three-dimensional object sensing, visualization, recognition and classification of scenes under photon-starved conditions. This paper presents an information-theoretic model for the photon-counting imaging (PCI) method, thereby providing a rigorous foundation for the merits of PCI in terms of image fidelity. This, in turn, can facilitate our understanding of the demonstrated success of photon-counting integral imaging in compressive imaging and classification. The mutual information between the source and photon-counted images is derived in a Markov random field setting and normalized by the source-image's entropy, yielding a fidelity metric that is between zero and unity, which respectively corresponds to complete loss of information and full preservation of information. Calculations suggest that the PCI fidelity metric increases with spatial correlation in source image, from which we infer that the PCI method is particularly effective for source images with high spatial correlation; the metric also increases with the reduction in photon-number uncertainty. As an application to the theory, an image-classification problem is considered showing a congruous relationship between the fidelity metric and classifier's performance.

Class of near-perfect coded apertures

NASA Technical Reports Server (NTRS)

Cannon, T. M.; Fenimore, E. E.

1977-01-01

Coded aperture imaging of gamma ray sources has long promised an improvement in the sensitivity of various detector systems. The promise has remained largely unfulfilled, however, for either one of two reasons. First, the encoding/decoding method produces artifacts, which even in the absence of quantum noise, restrict the quality of the reconstructed image. This is true of most correlation-type methods. Second, if the decoding procedure is of the deconvolution variety, small terms in the transfer function of the aperture can lead to excessive noise in the reconstructed image. It is proposed to circumvent both of these problems by use of a uniformly redundant array (URA) as the coded aperture in conjunction with a special correlation decoding method.

Correlation Functions Quantify Super-Resolution Images and Estimate Apparent Clustering Due to Over-Counting

PubMed Central

Veatch, Sarah L.; Machta, Benjamin B.; Shelby, Sarah A.; Chiang, Ethan N.; Holowka, David A.; Baird, Barbara A.

2012-01-01

We present an analytical method using correlation functions to quantify clustering in super-resolution fluorescence localization images and electron microscopy images of static surfaces in two dimensions. We use this method to quantify how over-counting of labeled molecules contributes to apparent self-clustering and to calculate the effective lateral resolution of an image. This treatment applies to distributions of proteins and lipids in cell membranes, where there is significant interest in using electron microscopy and super-resolution fluorescence localization techniques to probe membrane heterogeneity. When images are quantified using pair auto-correlation functions, the magnitude of apparent clustering arising from over-counting varies inversely with the surface density of labeled molecules and does not depend on the number of times an average molecule is counted. In contrast, we demonstrate that over-counting does not give rise to apparent co-clustering in double label experiments when pair cross-correlation functions are measured. We apply our analytical method to quantify the distribution of the IgE receptor (FcεRI) on the plasma membranes of chemically fixed RBL-2H3 mast cells from images acquired using stochastic optical reconstruction microscopy (STORM/dSTORM) and scanning electron microscopy (SEM). We find that apparent clustering of FcεRI-bound IgE is dominated by over-counting labels on individual complexes when IgE is directly conjugated to organic fluorophores. We verify this observation by measuring pair cross-correlation functions between two distinguishably labeled pools of IgE-FcεRI on the cell surface using both imaging methods. After correcting for over-counting, we observe weak but significant self-clustering of IgE-FcεRI in fluorescence localization measurements, and no residual self-clustering as detected with SEM. We also apply this method to quantify IgE-FcεRI redistribution after deliberate clustering by crosslinking with two distinct trivalent ligands of defined architectures, and we evaluate contributions from both over-counting of labels and redistribution of proteins. PMID:22384026

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures.

PubMed

Colen, Rivka; Foster, Ian; Gatenby, Robert; Giger, Mary Ellen; Gillies, Robert; Gutman, David; Heller, Matthew; Jain, Rajan; Madabhushi, Anant; Madhavan, Subha; Napel, Sandy; Rao, Arvind; Saltz, Joel; Tatum, James; Verhaak, Roeland; Whitman, Gary

2014-10-01

The National Cancer Institute (NCI) Cancer Imaging Program organized two related workshops on June 26-27, 2013, entitled "Correlating Imaging Phenotypes with Genomics Signatures Research" and "Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems." The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.

Submaximal delayed-onset muscle soreness: correlations between MR imaging findings and clinical measures

NASA Technical Reports Server (NTRS)

Evans, G. F.; Haller, R. G.; Wyrick, P. S.; Parkey, R. W.; Fleckenstein, J. L.; Blomqvist, C. G. (Principal Investigator)

1998-01-01

PURPOSE: To assess correlations between muscle edema on magnetic resonance (MR) images and clinical indexes of muscle injury in delayed-onset muscle soreness (DOMS) produced by submaximal exercise protocols. MATERIALS AND METHODS: Sixteen subjects performed 36 elbow flexions ("biceps curls") at one of two submaximal workloads that emphasized eccentric contractions. Changes in MR imaging findings, plasma levels of creatine kinase, and pain scores were correlated. RESULTS: Both exercise protocols produced DOMS in all subjects. The best correlation was between change in creatine kinase level and volume of muscle edema on MR images, regardless of the workload. Correlations tended to be better with the easier exercise protocol. CONCLUSION: Whereas many previous studies of DOMS focused on intense exercise protocols to ensure positive results, the present investigation showed that submaximal workloads are adequate to produce DOMS and that correlations between conventionally measured indexes of injury may be enhanced at lighter exercise intensities.

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.

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.

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.

3D temporal subtraction on multislice CT images using nonlinear warping technique

NASA Astrophysics Data System (ADS)

Ishida, Takayuki; Katsuragawa, Shigehiko; Kawashita, Ikuo; Kim, Hyounseop; Itai, Yoshinori; Awai, Kazuo; Li, Qiang; Doi, Kunio

2007-03-01

The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval changes between previous and current multislice CT images based on a nonlinear image warping technique. Our method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our computerized method includes global and local image matching techniques for accurate registration of current and previous CT images. For global image matching, we selected the corresponding previous section image for each current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred previous CT image. For local image matching, we applied the 3D template matching technique with translation and rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT images.

Time reversal imaging, Inverse problems and Adjoint Tomography}

NASA Astrophysics Data System (ADS)

Montagner, J.; Larmat, C. S.; Capdeville, Y.; Kawakatsu, H.; Fink, M.

2010-12-01

With the increasing power of computers and numerical techniques (such as spectral element methods), it is possible to address a new class of seismological problems. The propagation of seismic waves in heterogeneous media is simulated more and more accurately and new applications developed, in particular time reversal methods and adjoint tomography in the three-dimensional Earth. Since the pioneering work of J. Claerbout, theorized by A. Tarantola, many similarities were found between time-reversal methods, cross-correlations techniques, inverse problems and adjoint tomography. By using normal mode theory, we generalize the scalar approach of Draeger and Fink (1999) and Lobkis and Weaver (2001) to the 3D- elastic Earth, for theoretically understanding time-reversal method on global scale. It is shown how to relate time-reversal methods on one hand, with auto-correlations of seismograms for source imaging and on the other hand, with cross-correlations between receivers for structural imaging and retrieving Green function. Time-reversal methods were successfully applied in the past to acoustic waves in many fields such as medical imaging, underwater acoustics, non destructive testing and to seismic waves in seismology for earthquake imaging. In the case of source imaging, time reversal techniques make it possible an automatic location in time and space as well as the retrieval of focal mechanism of earthquakes or unknown environmental sources . We present here some applications at the global scale of these techniques on synthetic tests and on real data, such as Sumatra-Andaman (Dec. 2004), Haiti (Jan. 2010), as well as glacial earthquakes and seismic hum.

Tracking Image Correlation: Combining Single-Particle Tracking and Image Correlation

PubMed Central

Dupont, A.; Stirnnagel, K.; Lindemann, D.; Lamb, D.C.

2013-01-01

The interactions and coordination of biomolecules are crucial for most cellular functions. The observation of protein interactions in live cells may provide a better understanding of the underlying mechanisms. After fluorescent labeling of the interacting partners and live-cell microscopy, the colocalization is generally analyzed by quantitative global methods. Recent studies have addressed questions regarding the individual colocalization of moving biomolecules, usually by using single-particle tracking (SPT) and comparing the fluorescent intensities in both color channels. Here, we introduce a new method that combines SPT and correlation methods to obtain a dynamical 3D colocalization analysis along single trajectories of dual-colored particles. After 3D tracking, the colocalization is computed at each particle’s position via the local 3D image cross correlation of the two detection channels. For every particle analyzed, the output consists of the 3D trajectory, the time-resolved 3D colocalization information, and the fluorescence intensity in both channels. In addition, the cross-correlation analysis shows the 3D relative movement of the two fluorescent labels with an accuracy of 30 nm. We apply this method to the tracking of viral fusion events in live cells and demonstrate its capacity to obtain the time-resolved colocalization status of single particles in dense and noisy environments. PMID:23746509

High speed imaging for assessment of impact damage in natural fibre biocomposites

NASA Astrophysics Data System (ADS)

Ramakrishnan, Karthik Ram; Corn, Stephane; Le Moigne, Nicolas; Ienny, Patrick; Leger, Romain; Slangen, Pierre R.

2017-06-01

The use of Digital Image Correlation has been generally limited to the estimation of mechanical properties and fracture behaviour at low to moderate strain rates. High speed cameras dedicated to ballistic testing are often used to measure the initial and residual velocities of the projectile but rarely for damage assessment. The evaluation of impact damage is frequently achieved post-impact using visual inspection, ultrasonic C-scan or other NDI methods. Ultra-high speed cameras and developments in image processing have made possible the measurement of surface deformations and stresses in real time during dynamic cracking. In this paper, a method is presented to correlate the force- displacement data from the sensors to the slow motion tracking of the transient failure cracks using real-time high speed imaging. Natural fibre reinforced composites made of flax fibres and polypropylene matrix was chosen for the study. The creation of macro-cracks during the impact results in the loss of stiffness and a corresponding drop in the force history. However, optical instrumentation shows that the initiation of damage is not always evident and so the assessment of damage requires the use of a local approach. Digital Image Correlation is used to study the strain history of the composite and to identify the initiation and progression of damage. The effect of fly-speckled texture on strain measurement by image correlation is also studied. The developed method can be used for the evaluation of impact damage for different composite materials.

Introduction of Total Variation Regularization into Filtered Backprojection Algorithm

NASA Astrophysics Data System (ADS)

Raczyński, L.; Wiślicki, W.; Klimaszewski, K.; Krzemień, W.; Kowalski, P.; Shopa, R. Y.; Białas, P.; Curceanu, C.; Czerwiński, E.; Dulski, K.; Gajos, A.; Głowacz, B.; Gorgol, M.; Hiesmayr, B.; Jasińska, B.; Kisielewska-Kamińska, D.; Korcyl, G.; Kozik, T.; Krawczyk, N.; Kubicz, E.; Mohammed, M.; Pawlik-Niedźwiecka, M.; Niedźwiecki, S.; Pałka, M.; Rudy, Z.; Sharma, N. G.; Sharma, S.; Silarski, M.; Skurzok, M.; Wieczorek, A.; Zgardzińska, B.; Zieliński, M.; Moskal, P.

In this paper we extend the state-of-the-art filtered backprojection (FBP) method with application of the concept of Total Variation regularization. We compare the performance of the new algorithm with the most common form of regularizing in the FBP image reconstruction via apodizing functions. The methods are validated in terms of cross-correlation coefficient between reconstructed and real image of radioactive tracer distribution using standard Derenzo-type phantom. We demonstrate that the proposed approach results in higher cross-correlation values with respect to the standard FBP method.

Quantitative evaluation method of the bubble structure of sponge cake by using morphology image processing

NASA Astrophysics Data System (ADS)

Tatebe, Hironobu; Kato, Kunihito; Yamamoto, Kazuhiko; Katsuta, Yukio; Nonaka, Masahiko

2005-12-01

Now a day, many evaluation methods for the food industry by using image processing are proposed. These methods are becoming new evaluation method besides the sensory test and the solid-state measurement that are using for the quality evaluation. An advantage of the image processing is to be able to evaluate objectively. The goal of our research is structure evaluation of sponge cake by using image processing. In this paper, we propose a feature extraction method of the bobble structure in the sponge cake. Analysis of the bubble structure is one of the important properties to understand characteristics of the cake from the image. In order to take the cake image, first we cut cakes and measured that's surface by using the CIS scanner. Because the depth of field of this type scanner is very shallow, the bubble region of the surface has low gray scale values, and it has a feature that is blur. We extracted bubble regions from the surface images based on these features. First, input image is binarized, and the feature of bubble is extracted by the morphology analysis. In order to evaluate the result of feature extraction, we compared correlation with "Size of the bubble" of the sensory test result. From a result, the bubble extraction by using morphology analysis gives good correlation. It is shown that our method is as well as the subjectivity evaluation.

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

Displacement measurement with nanoscale resolution using a coded micro-mark and digital image correlation

NASA Astrophysics Data System (ADS)

Huang, Wei; Ma, Chengfu; Chen, Yuhang

2014-12-01

A method for simple and reliable displacement measurement with nanoscale resolution is proposed. The measurement is realized by combining a common optical microscopy imaging of a specially coded nonperiodic microstructure, namely two-dimensional zero-reference mark (2-D ZRM), and subsequent correlation analysis of the obtained image sequence. The autocorrelation peak contrast of the ZRM code is maximized with well-developed artificial intelligence algorithms, which enables robust and accurate displacement determination. To improve the resolution, subpixel image correlation analysis is employed. Finally, we experimentally demonstrate the quasi-static and dynamic displacement characterization ability of a micro 2-D ZRM.

A new phase-correlation-based iris matching for degraded images.

PubMed

Krichen, Emine; Garcia-Salicetti, Sonia; Dorizzi, Bernadette

2009-08-01

In this paper, we present a new phase-correlation-based iris matching approach in order to deal with degradations in iris images due to unconstrained acquisition procedures. Our matching system is a fusion of global and local Gabor phase-correlation schemes. The main originality of our local approach is that we do not only consider the correlation peak amplitudes but also their locations in different regions of the images. Results on several degraded databases, namely, the CASIA-BIOSECURE and Iris Challenge Evaluation 2005 databases, show the improvement of our method compared to two available reference systems, Masek and Open Source for Iris (OSRIS), in verification mode.

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

Correlative cryo-fluorescence light microscopy and cryo-electron tomography of Streptomyces.

PubMed

Koning, Roman I; Celler, Katherine; Willemse, Joost; Bos, Erik; van Wezel, Gilles P; Koster, Abraham J

2014-01-01

Light microscopy and electron microscopy are complementary techniques that in a correlative approach enable identification and targeting of fluorescently labeled structures in situ for three-dimensional imaging at nanometer resolution. Correlative imaging allows electron microscopic images to be positioned in a broader temporal and spatial context. We employed cryo-correlative light and electron microscopy (cryo-CLEM), combining cryo-fluorescence light microscopy and cryo-electron tomography, on vitrified Streptomyces bacteria to study cell division. Streptomycetes are mycelial bacteria that grow as long hyphae and reproduce via sporulation. On solid media, Streptomyces subsequently form distinct aerial mycelia where cell division leads to the formation of unigenomic spores which separate and disperse to form new colonies. In liquid media, only vegetative hyphae are present divided by noncell separating crosswalls. Their multicellular life style makes them exciting model systems for the study of bacterial development and cell division. Complex intracellular structures have been visualized with transmission electron microscopy. Here, we describe the methods for cryo-CLEM that we applied for studying Streptomyces. These methods include cell growth, fluorescent labeling, cryo-fixation by vitrification, cryo-light microscopy using a Linkam cryo-stage, image overlay and relocation, cryo-electron tomography using a Titan Krios, and tomographic reconstruction. Additionally, methods for segmentation, volume rendering, and visualization of the correlative data are described. © 2014 Elsevier Inc. All rights reserved.

3D digital image correlation methods for full-field vibration measurement

NASA Astrophysics Data System (ADS)

Helfrick, Mark N.; Niezrecki, Christopher; Avitabile, Peter; Schmidt, Timothy

2011-04-01

In the area of modal test/analysis/correlation, significant effort has been expended over the past twenty years in order to make reduced models and to expand test data for correlation and eventual updating of the finite element models. This has been restricted by vibration measurements which are traditionally limited to the location of relatively few applied sensors. Advances in computers and digital imaging technology have allowed 3D digital image correlation (DIC) methods to measure the shape and deformation of a vibrating structure. This technique allows for full-field measurement of structural response, thus providing a wealth of simultaneous test data. This paper presents some preliminary results for the test/analysis/correlation of data measured using the DIC approach along with traditional accelerometers and a scanning laser vibrometer for comparison to a finite element model. The results indicate that all three approaches correlated well with the finite element model and provide validation for the DIC approach for full-field vibration measurement. Some of the advantages and limitations of the technique are presented and discussed.

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.

Histological correlation of 7 T multi-parametric MRI performed in ex-vivo Achilles tendon.

PubMed

Juras, Vladimir; Apprich, Sebastian; Pressl, Christina; Zbyn, Stefan; Szomolanyi, Pavol; Domayer, Stephan; Hofstaetter, Jochen G; Trattnig, Siegfried

2013-05-01

The goal of this in vitro validation study was to investigate the feasibility of biochemical MRI techniques, such as sodium imaging, T₂ mapping, fast imaging with steady state precession (FISP), and reversed FISP (PSIF), as potential markers for collagen, glycosaminoglycan and water content in the Achilles tendon. Five fresh cadaver ankles acquired from a local anatomy department were used in the study. To acquire a sodium signal from the Achilles tendon, a 3D-gradient-echo sequence, optimized for sodium imaging, was used with TE=7.71 ms and TR=17 ms. The T₂ relaxation times were obtained using a multi-echo, spin-echo technique with a repetition time (TR) of 1200 ms and six echo times. A 3D, partially balanced, steady-state gradient echo pulse sequence was used to acquire FISP and PSIF images, with TR/TE=6.96/2.46 ms. MRI parameters were correlated with each other, as well as with histologically assessed glycosaminoglycan and water content in cadaver Achilles tendons. The highest relevant Pearson correlation coefficient was found between sodium SNR and glycosaminoglycan content (r=0.71, p=0.007). Relatively high correlation was found between the PSIF signal and T2 values (r=0.51, p=0.036), and between the FISP signal and T₂ values (r=0.56, p=0.047). Other correlations were found to be below the moderate level. This study demonstrated the feasibility of progressive biochemical MRI methods for the imaging of the AT. A GAG-specific, contrast-free method (sodium imaging), as well as collagen- and water-sensitive methods (T₂ mapping, FISP, PSIF), may be used in fast-relaxing tissues, such as tendons, in reasonable scan times. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Correlated displacement-T2 MRI by means of a Pulsed Field Gradient-Multi Spin Echo Method.

PubMed

Windt, Carel W; Vergeldt, Frank J; Van As, Henk

2007-04-01

A method for correlated displacement-T2 imaging is presented. A Pulsed Field Gradient-Multi Spin Echo (PFG-MSE) sequence is used to record T2 resolved propagators on a voxel-by-voxel basis, making it possible to perform single voxel correlated displacement-T2 analyses. In spatially heterogeneous media the method thus gives access to sub-voxel information about displacement and T2 relaxation. The sequence is demonstrated using a number of flow conducting model systems: a tube with flowing water of variable intrinsic T2's, mixing fluids of different T2's in an "X"-shaped connector, and an intact living plant. PFG-MSE can be applied to yield information about the relation between flow, pore size and exchange behavior, and can aid volume flow quantification by making it possible to correct for T2 relaxation during the displacement labeling period Delta in PFG displacement imaging methods. Correlated displacement-T2 imaging can be of special interest for a number of research subjects, such as the flow of liquids and mixtures of liquids or liquids and solids moving through microscopic conduits of different sizes (e.g., plants, porous media, bioreactors, biomats).

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

Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

PubMed

Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Richards, Michael S; Rubin, Jonathan M

2007-09-01

We compared the diagnostic potential of using correlation coefficient images versus elastograms from 2-dimensional (2D) freehand elastography to characterize breast cysts. In this preliminary study, which was approved by the Institutional Review Board and compliant with the Health Insurance Portability and Accountability Act, we imaged 4 consecutive human subjects (4 cysts, 1 biopsy-verified benign breast parenchyma) with freehand 2D elastography. Data were processed offline with conventional 2D phase-sensitive speckle-tracking algorithms. The correlation coefficient in the cyst and surrounding tissue was calculated, and appearances of the cysts in the correlation coefficient images and elastograms were compared. The correlation coefficient in the cysts was considerably lower (14%-37%) than in the surrounding tissue because of the lack of sufficient speckle in the cysts, as well as the prominence of random noise, reverberations, and clutter, which decorrelated quickly. Thus, the cysts were visible in all correlation coefficient images. In contrast, the elastograms associated with these cysts each had different elastographic patterns. The solid mass in this study did not have the same high decorrelation rate as the cysts, having a correlation coefficient only 2.1% lower than that of surrounding tissue. Correlation coefficient images may produce a more direct, reliable, and consistent method for characterizing cysts than elastograms.

Intensity correlation imaging with sunlight-like source

NASA Astrophysics Data System (ADS)

Wang, Wentao; Tang, Zhiguo; Zheng, Huaibin; Chen, Hui; Yuan, Yuan; Liu, Jinbin; Liu, Yanyan; Xu, Zhuo

2018-05-01

We show a method of intensity correlation imaging of targets illuminated by a sunlight-like source both theoretically and experimentally. With a Faraday anomalous dispersion optical filter (FADOF), we have modulated the coherence time of a thermal source up to 0.167 ns. And we carried out measurements of temporal and spatial correlations, respectively, with an intensity interferometer setup. By skillfully using the even Fourier fitting on the very sparse sampling data, the images of targets are successfully reconstructed from the low signal-noise-ratio(SNR) interference pattern by applying an iterative phase retrieval algorithm. The resulting imaging quality is as well as the one obtained by the theoretical fitting. The realization of such a case will bring this technique closer to geostationary satellite imaging illuminated by sunlight.

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.

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

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

Estimation of uncertainty bounds for individual particle image velocimetry measurements from cross-correlation peak ratio

NASA Astrophysics Data System (ADS)

Charonko, John J.; Vlachos, Pavlos P.

2013-06-01

Numerous studies have established firmly that particle image velocimetry (PIV) is a robust method for non-invasive, quantitative measurements of fluid velocity, and that when carefully conducted, typical measurements can accurately detect displacements in digital images with a resolution well below a single pixel (in some cases well below a hundredth of a pixel). However, to date, these estimates have only been able to provide guidance on the expected error for an average measurement under specific image quality and flow conditions. This paper demonstrates a new method for estimating the uncertainty bounds to within a given confidence interval for a specific, individual measurement. Here, cross-correlation peak ratio, the ratio of primary to secondary peak height, is shown to correlate strongly with the range of observed error values for a given measurement, regardless of flow condition or image quality. This relationship is significantly stronger for phase-only generalized cross-correlation PIV processing, while the standard correlation approach showed weaker performance. Using an analytical model of the relationship derived from synthetic data sets, the uncertainty bounds at a 95% confidence interval are then computed for several artificial and experimental flow fields, and the resulting errors are shown to match closely to the predicted uncertainties. While this method stops short of being able to predict the true error for a given measurement, knowledge of the uncertainty level for a PIV experiment should provide great benefits when applying the results of PIV analysis to engineering design studies and computational fluid dynamics validation efforts. Moreover, this approach is exceptionally simple to implement and requires negligible additional computational cost.

An improved schlieren method for measurement and automatic reconstruction of the far-field focal spot

PubMed Central

Wang, Zhengzhou; Hu, Bingliang; Yin, Qinye

2017-01-01

The schlieren method of measuring far-field focal spots offers many advantages at the Shenguang III laser facility such as low cost and automatic laser-path collimation. However, current methods of far-field focal spot measurement often suffer from low precision and efficiency when the final focal spot is merged manually, thereby reducing the accuracy of reconstruction. In this paper, we introduce an improved schlieren method to construct the high dynamic-range image of far-field focal spots and improve the reconstruction accuracy and efficiency. First, a detection method based on weak light beam sampling and magnification imaging was designed; images of the main and side lobes of the focused laser irradiance in the far field were obtained using two scientific CCD cameras. Second, using a self-correlation template matching algorithm, a circle the same size as the schlieren ball was dug from the main lobe cutting image and used to change the relative region of the main lobe cutting image within a 100×100 pixel region. The position that had the largest correlation coefficient between the side lobe cutting image and the main lobe cutting image when a circle was dug was identified as the best matching point. Finally, the least squares method was used to fit the center of the side lobe schlieren small ball, and the error was less than 1 pixel. The experimental results show that this method enables the accurate, high-dynamic-range measurement of a far-field focal spot and automatic image reconstruction. Because the best matching point is obtained through image processing rather than traditional reconstruction methods based on manual splicing, this method is less sensitive to the efficiency of focal-spot reconstruction and thus offers better experimental precision. PMID:28207758

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.

Digital photography provides a fast, reliable, and noninvasive method to estimate anthocyanin pigment concentration in reproductive and vegetative plant tissues.

PubMed

Del Valle, José C; Gallardo-López, Antonio; Buide, Mª Luisa; Whittall, Justen B; Narbona, Eduardo

2018-03-01

Anthocyanin pigments have become a model trait for evolutionary ecology as they often provide adaptive benefits for plants. Anthocyanins have been traditionally quantified biochemically or more recently using spectral reflectance. However, both methods require destructive sampling and can be labor intensive and challenging with small samples. Recent advances in digital photography and image processing make it the method of choice for measuring color in the wild. Here, we use digital images as a quick, noninvasive method to estimate relative anthocyanin concentrations in species exhibiting color variation. Using a consumer-level digital camera and a free image processing toolbox, we extracted RGB values from digital images to generate color indices. We tested petals, stems, pedicels, and calyces of six species, which contain different types of anthocyanin pigments and exhibit different pigmentation patterns. Color indices were assessed by their correlation to biochemically determined anthocyanin concentrations. For comparison, we also calculated color indices from spectral reflectance and tested the correlation with anthocyanin concentration. Indices perform differently depending on the nature of the color variation. For both digital images and spectral reflectance, the most accurate estimates of anthocyanin concentration emerge from anthocyanin content-chroma ratio, anthocyanin content-chroma basic, and strength of green indices. Color indices derived from both digital images and spectral reflectance strongly correlate with biochemically determined anthocyanin concentration; however, the estimates from digital images performed better than spectral reflectance in terms of r 2 and normalized root-mean-square error. This was particularly noticeable in a species with striped petals, but in the case of striped calyces, both methods showed a comparable relationship with anthocyanin concentration. Using digital images brings new opportunities to accurately quantify the anthocyanin concentrations in both floral and vegetative tissues. This method is efficient, completely noninvasive, applicable to both uniform and patterned color, and works with samples of any size.

Semi-quantitative methods yield greater inter- and intraobserver agreement than subjective methods for interpreting 99m technetium-hydroxymethylene-diphosphonate uptake in equine thoracic processi spinosi.

PubMed

van Zadelhoff, Claudia; Ehrle, Anna; Merle, Roswitha; Jahn, Werner; Lischer, Christoph

2018-05-09

Scintigraphy is a standard diagnostic method for evaluating horses with back pain due to suspected thoracic processus spinosus pathology. Lesion detection is based on subjective or semi-quantitative assessments of increased uptake. This retrospective, analytical study is aimed to compare semi-quantitative and subjective methods in the evaluation of scintigraphic images of the processi spinosi in the equine thoracic spine. Scintigraphic images of 20 Warmblood horses, presented for assessment of orthopedic conditions between 2014 and 2016, were included in the study. Randomized, blinded image evaluation was performed by 11 veterinarians using subjective and semi-quantitative methods. Subjective grading was performed for the analysis of red-green-blue and grayscale scintigraphic images, which were presented in full-size or as masked images. For the semi-quantitative assessment, observers placed regions of interest over each processus spinosus. The uptake ratio of each processus spinosus in comparison to a reference region of interest was determined. Subsequently, a modified semi-quantitative calculation was developed whereby only the highest counts-per-pixel for a specified number of pixels was processed. Inter- and intraobserver agreement was calculated using intraclass correlation coefficients. Inter- and intraobserver intraclass correlation coefficients were 41.65% and 71.39%, respectively, for the subjective image assessment. Additionally, a correlation between intraobserver agreement, experience, and grayscale images was identified. The inter- and intraobserver agreement was significantly increased when using semi-quantitative analysis (97.35% and 98.36%, respectively) or the modified semi-quantitative calculation (98.61% and 98.82%, respectively). The proposed modified semi-quantitative technique showed a higher inter- and intraobserver agreement when compared to other methods, which makes it a useful tool for the analysis of scintigraphic images. The association of the findings from this study with clinical and radiological examinations requires further investigation. © 2018 American College of Veterinary Radiology.

Seeing and Reading Red: Hue and Color-word Correlation in Images and Attendant Text on the WWW

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

Newsam, S

2004-07-12

This work represents an initial investigation into determining whether correlations actually exist between metadata and content descriptors in multimedia datasets. We provide a quantitative method for evaluating whether the hue of images on the WWW is correlated with the occurrence of color-words in metadata such as URLs, image names, and attendant text. It turns out that such a correlation does exist: the likelihood that a particular color appears in an image whose URL, name, and/or attendant text contains the corresponding color-word is generally at least twice the likelihood that the color appears in a randomly chosen image on the WWW.more » While this finding might not be significant in and of itself, it represents an initial step towards quantitatively establishing that other, perhaps more useful correlations exist. These correlations form the basis for exciting novel approaches that leverage semi-supervised datasets, such as the WWW, to overcome the semantic gap that has hampered progress in multimedia information retrieval for some time now.« less

Total focusing method with correlation processing of antenna array signals

NASA Astrophysics Data System (ADS)

Kozhemyak, O. A.; Bortalevich, S. I.; Loginov, E. L.; Shinyakov, Y. A.; Sukhorukov, M. P.

2018-03-01

The article proposes a method of preliminary correlation processing of a complete set of antenna array signals used in the image reconstruction algorithm. The results of experimental studies of 3D reconstruction of various reflectors using and without correlation processing are presented in the article. Software ‘IDealSystem3D’ by IDeal-Technologies was used for experiments. Copper wires of different diameters located in a water bath were used as a reflector. The use of correlation processing makes it possible to obtain more accurate reconstruction of the image of the reflectors and to increase the signal-to-noise ratio. The experimental results were processed using an original program. This program allows varying the parameters of the antenna array and sampling frequency.

Adaptive multiple super fast simulated annealing for stochastic microstructure reconstruction

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

Ryu, Seun; Lin, Guang; Sun, Xin

2013-01-01

Fast image reconstruction from statistical information is critical in image fusion from multimodality chemical imaging instrumentation to create high resolution image with large domain. Stochastic methods have been used widely in image reconstruction from two point correlation function. The main challenge is to increase the efficiency of reconstruction. A novel simulated annealing method is proposed for fast solution of image reconstruction. Combining the advantage of very fast cooling schedules, dynamic adaption and parallelization, the new simulation annealing algorithm increases the efficiencies by several orders of magnitude, making the large domain image fusion feasible.

Correlation of the clinical and physical image quality in chest radiography for average adults with a computed radiography imaging system

PubMed Central

Wood, T J; Beavis, A W; Saunderson, J R

2013-01-01

Objective: The purpose of this study was to examine the correlation between the quality of visually graded patient (clinical) chest images and a quantitative assessment of chest phantom (physical) images acquired with a computed radiography (CR) imaging system. Methods: The results of a previously published study, in which four experienced image evaluators graded computer-simulated postero-anterior chest images using a visual grading analysis scoring (VGAS) scheme, were used for the clinical image quality measurement. Contrast-to-noise ratio (CNR) and effective dose efficiency (eDE) were used as physical image quality metrics measured in a uniform chest phantom. Although optimal values of these physical metrics for chest radiography were not derived in this work, their correlation with VGAS in images acquired without an antiscatter grid across the diagnostic range of X-ray tube voltages was determined using Pearson’s correlation coefficient. Results: Clinical and physical image quality metrics increased with decreasing tube voltage. Statistically significant correlations between VGAS and CNR (R=0.87, p<0.033) and eDE (R=0.77, p<0.008) were observed. Conclusion: Medical physics experts may use the physical image quality metrics described here in quality assurance programmes and optimisation studies with a degree of confidence that they reflect the clinical image quality in chest CR images acquired without an antiscatter grid. Advances in knowledge: A statistically significant correlation has been found between the clinical and physical image quality in CR chest imaging. The results support the value of using CNR and eDE in the evaluation of quality in clinical thorax radiography. PMID:23568362

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.

The preferred magnetic resonance imaging planes in quantifying visceral adipose tissue and evaluating cardiovascular risk.

PubMed

Liu, K H; Chan, Y L; Chan, J C N; Chan, W B; Kong, M O; Poon, M Y

2005-09-01

Magnetic Resonance Imaging (MRI) is a well-accepted non-invasive method in the quantification of visceral adipose tissue. However, a standard method of measurement has not yet been universally agreed. The objectives of the present study were 2-fold, firstly, to identify the imaging plane in the Chinese population which gives the best correlation with total visceral adipose tissue volume and cardiovascular risk factors; and secondly to compare the correlations between single-slice and multiple-slice approach with cardiovascular risk factors. Thirty-seven Chinese subjects with no known medical history underwent MRI examination for quantifying total visceral adipose tissue volume. The visceral adipose tissue area at five axial imaging levels within abdomen and pelvis were determined. All subjects had blood pressure measured and fasting blood taken for analysis of cardiovascular risk factors. Framingham risk score for each subject was calculated. The imaging plane at the level of 'lower costal margin' (LCM) in both men and women had the highest correlation with total visceral adipose tissue volume (r = 0.97 and 0.99 respectively). The visceral adipose tissue area at specific imaging levels showed higher correlations with various cardiovascular risk factors and Framingham risk score than total visceral adipose tissue volume. The visceral adipose tissue area at 'umbilicus' (UMB) level in men (r = 0.88) and LCM level in women (r = 0.70) showed the best correlation with Framingham risk score. The imaging plane at the level of LCM is preferred for reflecting total visceral adipose tissue volume in Chinese subjects. For investigating the association of cardiovascular risk with visceral adipose tissue in MRI-obesity research, the single-slice approach is superior to the multiple-slice approach, with the level of UMB in men and LCM in women as the preferred imaging planes.

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

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.

Could digital imaging be an alternative for digital colorimeters?

PubMed

Caglar, Alper; Yamanel, Kivanc; Gulsahi, Kamran; Bagis, Bora; Ozcan, Mutlu

2010-12-01

This study evaluated the colour parameters of composite and ceramic shade guides determined using a colorimeter and digital imaging method with illuminants at different colour temperatures. Two different resin composite shade guides, namely Charisma (Heraeus Kulzer) and Premise (Kerr Corporation), and two different ceramic shade guides, Vita Lumin Vacuum (VITA Zahnfabrik) and Noritake (Noritake Co.), were evaluated at three different colour temperatures (2,700 K, 2,700-6,500 K, and 6500 K) of illuminants. Ten shade tabs were selected (A1, A2, A3, A3,5, A4, B1, B2, B3, C2 and C3) from each shade guide. CIE Lab values were obtained using digital imaging and a colorimeter (ShadeEye NCC Dental Chroma Meter, Shofu Inc.). The data were analysed using two-way ANOVA, and Pearson's correlation. While mean L* values of both composite and ceramic shade guides were not affected from the colour temperature, L* values obtained with the colorimeter showed significantly lower values than those of the digital imaging (p < 0.01). At combined 2,700-6500 K colour temperature, the means of a* values obtained from colorimeter and digital imaging did not show significant differences (p > 0.05). For both composite and ceramic shade guides, L* and b* values obtained from colorimeter and digital imaging method presented a high level of correlation. High-level correlations were also acquired for a* values in all shade guides except for the Charisma composite shade guide. Digital imaging method could be an alternative for the colorimeters unless the proper object-camera distance, digital camera settings and suitable illumination conditions could be supplied. However, variations in shade guides, especially for composites, may affect the correlation.

Potency backprojection

NASA Astrophysics Data System (ADS)

Okuwaki, R.; Kasahara, A.; Yagi, Y.

2017-12-01

The backprojection (BP) method has been one of the powerful tools of tracking seismic-wave sources of the large/mega earthquakes. The BP method projects waveforms onto a possible source point by stacking them with the theoretical-travel-time shifts between the source point and the stations. Following the BP method, the hybrid backprojection (HBP) method was developed to enhance depth-resolution of projected images and mitigate the dummy imaging of the depth phases, which are shortcomings of the BP method, by stacking cross-correlation functions of the observed waveforms and theoretically calculated Green's functions (GFs). The signal-intensity of the BP/HBP image at a source point is related to how much of observed waveforms was radiated from that point. Since the amplitude of the GF associated with the slip-rate increases with depth as the rigidity increases with depth, the intensity of the BP/HBP image inherently has depth dependence. To make a direct comparison of the BP/HBP image with the corresponding slip distribution inferred from a waveform inversion, and discuss the rupture properties along the fault drawn from the waveforms in high- and low-frequencies with the BP/HBP methods and the waveform inversion, respectively, it is desirable to have the variants of BP/HBP methods that directly image the potency-rate-density distribution. Here we propose new formulations of the BP/HBP methods, which image the distribution of the potency-rate density by introducing alternative normalizing factors in the conventional formulations. For the BP method, the observed waveform is normalized with the maximum amplitude of P-phase of the corresponding GF. For the HBP method, we normalize the cross-correlation function with the squared-sum of the GF. The normalized waveforms or the cross-correlation functions are then stacked for all the stations to enhance the signal to noise ratio. We will present performance-tests of the new formulations by using synthetic waveforms and the real data of the Mw 8.3 2015 Illapel Chile earthquake, and further discuss the limitations of the new BP/HBP methods proposed in this study when they are used for exploring the rupture properties of the earthquakes.

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.

Non-isotropic noise correlation in PET data reconstructed by FBP but not by OSEM demonstrated using auto-correlation function.

PubMed

Razifar, Pasha; Lubberink, Mark; Schneider, Harald; Långström, Bengt; Bengtsson, Ewert; Bergström, Mats

2005-05-13

BACKGROUND: Positron emission tomography (PET) is a powerful imaging technique with the potential of obtaining functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules in a biological system, both in vitro and in vivo. PET images can be used directly or after kinetic modelling to extract quantitative values of a desired physiological, biochemical or pharmacological entity. Because such images are generally noisy, it is essential to understand how noise affects the derived quantitative values. A pre-requisite for this understanding is that the properties of noise such as variance (magnitude) and texture (correlation) are known. METHODS: In this paper we explored the pattern of noise correlation in experimentally generated PET images, with emphasis on the angular dependence of correlation, using the autocorrelation function (ACF). Experimental PET data were acquired in 2D and 3D acquisition mode and reconstructed by analytical filtered back projection (FBP) and iterative ordered subsets expectation maximisation (OSEM) methods. The 3D data was rebinned to a 2D dataset using FOurier REbinning (FORE) followed by 2D reconstruction using either FBP or OSEM. In synthetic images we compared the ACF results with those from covariance matrix. The results were illustrated as 1D profiles and also visualized as 2D ACF images. RESULTS: We found that the autocorrelation images from PET data obtained after FBP were not fully rotationally symmetric or isotropic if the object deviated from a uniform cylindrical radioactivity distribution. In contrast, similar autocorrelation images obtained after OSEM reconstruction were isotropic even when the phantom was not circular. Simulations indicated that the noise autocorrelation is non-isotropic in images created by FBP when the level of noise in projections is angularly variable. Comparison between 1D cross profiles on autocorrelation images obtained by FBP reconstruction and covariance matrices produced almost identical results in a simulation study. CONCLUSION: With asymmetric radioactivity distribution in PET, reconstruction using FBP, in contrast to OSEM, generates images in which the noise correlation is non-isotropic when the noise magnitude is angular dependent, such as in objects with asymmetric radioactivity distribution. In this respect, iterative reconstruction is superior since it creates isotropic noise correlations in the images.

Longitudinal Imaging of Cancer Cell Metastases in Two Preclinical Models: A Correlation of Noninvasive Imaging to Histopathology

PubMed Central

Adiseshaiah, Pavan P.; Patel, Nimit L.; Ileva, Lilia V.; Kalen, Joseph D.; Haines, Diana C.; McNeil, Scott E.

2014-01-01

Metastatic spread is the leading cause of death from cancer. Early detection of cancer at primary and metastatic sites by noninvasive imaging modalities would be beneficial for both therapeutic intervention and disease management. Noninvasive imaging modalities such as bioluminescence (optical), positron emission tomography (PET)/X-ray computed tomography (CT), and magnetic resonance imaging (MRI) can provide complementary information and accurately measure tumor growth as confirmed by histopathology. Methods. We validated two metastatic tumor models, MDA-MD-231-Luc and B16-F10-Luc intravenously injected, and 4T1-Luc cells orthotopically implanted into the mammary fat pad. Longitudinal whole body bioluminescence imaging (BLI) evaluated metastasis, and tumor burden of the melanoma cell line (B16-F10-Luc) was correlated with (PET)/CT and MRI. In addition, ex vivo imaging evaluated metastasis in relevant organs and histopathological analysis was used to confirm imaging. Results. BLI revealed successful colonization of cancer cells in both metastatic tumor models over a 4-week period. Furthermore, lung metastasis of B16-F10-Luc cells imaged by PET/CT at week four showed a strong correlation (R 2 = 0.9) with histopathology. The presence and degree of metastasis as determined by imaging correlated (R 2 = 0.7) well with histopathology findings. Conclusions. We validated two metastatic tumor models by longitudinal noninvasive imaging with good histopathology correlation. PMID:24724022

Evaluation of Fiber Reinforced Cement Using Digital Image Correlation

PubMed Central

Melenka, Garrett W.; Carey, Jason P.

2015-01-01

The effect of short fiber reinforcements on the mechanical properties of cement has been examined using a splitting tensile – digital image correlation (DIC) measurement method. Three short fiber reinforcement materials have been used in this study: fiberglass, nylon, and polypropylene. The method outlined provides a simple experimental setup that can be used to evaluate the ultimate tensile strength of brittle materials as well as measure the full field strain across the surface of the splitting tensile test cylindrical specimen. Since the DIC measurement technique is a contact free measurement this method can be used to assess sample failure. PMID:26039590

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.

Correlative cryogenic tomography of cells using light and soft x-rays

PubMed Central

Smith, Elizabeth A.; Cinquin, Bertrand P.; Do, Myan; McDermott, Gerry; Le Gros, Mark A.; Larabell, Carolyn A.

2013-01-01

Correlated imaging is the process of imaging a specimen with two complementary modalities, and then combining the two data sets to create a highly informative, composite view. A recent implementation of this concept has been the combination of soft x-ray tomography (SXT) with fluorescence cryogenic microscopy (FCM). SXT-FCM is used to visualize cells that are held in a near-native, cryo-preserved state. The resultant images are, therefore, highly representative of both the cellular architecture and molecular organization in vivo. SXT quantitatively visualizes the cell and sub-cellular structures; FCM images the spatial distribution of fluorescently labeled molecules. Here, we review the characteristics of SXT-FCM, and briefly discuss how this method compares with existing correlative imaging techniques. We also describe how the incorporation of a cryo-rotation stage into a cryogenic fluorescence microscope allows acquisition of fluorescence cryogenic tomography (FCT) data. FCT is optimally suited to correlation with SXT, since both techniques image the specimen in 3-D, potentially with similar, isotropic spatial resolution. PMID:24355261

Analysis of gene expression levels in individual bacterial cells without image segmentation

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

Kwak, In Hae; Son, Minjun; Hagen, Stephen J., E-mail: sjhagen@ufl.edu

2012-05-11

Highlights: Black-Right-Pointing-Pointer We present a method for extracting gene expression data from images of bacterial cells. Black-Right-Pointing-Pointer The method does not employ cell segmentation and does not require high magnification. Black-Right-Pointing-Pointer Fluorescence and phase contrast images of the cells are correlated through the physics of phase contrast. Black-Right-Pointing-Pointer We demonstrate the method by characterizing noisy expression of comX in Streptococcus mutans. -- Abstract: Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on amore » segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly.« less

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.

Computer-aided analysis with Image J for quantitatively assessing psoriatic lesion area.

PubMed

Sun, Z; Wang, Y; Ji, S; Wang, K; Zhao, Y

2015-11-01

Body surface area is important in determining the severity of psoriasis. However, objective, reliable, and practical method is still in need for this purpose. We performed a computer image analysis (CIA) of psoriatic area using the image J freeware to determine whether this method could be used for objective evaluation of psoriatic area. Fifteen psoriasis patients were randomized to be treated with adalimumab or placebo in a clinical trial. At each visit, the psoriasis area of each body site was estimated by two physicians (E-method), and standard photographs were taken. The psoriasis area in the pictures was assessed with CIA using semi-automatic threshold selection (T-method), or manual selection (M-method, gold standard). The results assessed by the three methods were analyzed with reliability and affecting factors evaluated. Both T- and E-method correlated strongly with M-method, and T-method had a slightly stronger correlation with M-method. Both T- and E-methods had a good consistency between the evaluators. All the three methods were able to detect the change in the psoriatic area after treatment, while the E-method tends to overestimate. The CIA with image J freeware is reliable and practicable in quantitatively assessing the lesional of psoriasis area. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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.

Technical Note: Method to correlate whole-specimen histopathology of radical prostatectomy with diagnostic MR imaging

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

McGrath, Deirdre M., E-mail: d.mcgrath@sheffield.ac.uk; Lee, Jenny; Foltz, Warren D.

Purpose: Validation of MRI-guided tumor boundary delineation for targeted prostate cancer therapy is achieved via correlation with gold-standard histopathology of radical prostatectomy specimens. Challenges to accurate correlation include matching the pathology sectioning plane with the in vivo imaging slice plane and correction for the deformation that occurs between in vivo imaging and histology. A methodology is presented for matching of the histological sectioning angle and position to the in vivo imaging slices. Methods: Patients (n = 4) with biochemical failure following external beam radiotherapy underwent diagnostic MRI to confirm localized recurrence of prostate cancer, followed by salvage radical prostatectomy. High-resolutionmore » 3-D MRI of the ex vivo specimens was acquired to determine the pathology sectioning angle that best matched the in vivo imaging slice plane, using matching anatomical features and implanted fiducials. A novel sectioning device was developed to guide sectioning at the correct angle, and to assist the insertion of reference dye marks to aid in histopathology reconstruction. Results: The percentage difference in the positioning of the urethra in the ex vivo pathology sections compared to the positioning in in vivo images was reduced from 34% to 7% through slicing at the best match angle. Reference dye marks were generated, which were visible in ex vivo imaging, in the tissue sections before and after processing, and in histology sections. Conclusions: The method achieved an almost fivefold reduction in the slice-matching error and is readily implementable in combination with standard MRI technology. The technique will be employed to generate datasets for correlation of whole-specimen prostate histopathology with in vivo diagnostic MRI using 3-D deformable registration, allowing assessment of the sensitivity and specificity of MRI parameters for prostate cancer. Although developed specifically for prostate, the method is readily adaptable to other types of whole tissue specimen, such as mastectomy or liver resection.« less

[Study on objectively evaluating skin aging according to areas of skin texture].

PubMed

Shan, Gaixin; Gan, Ping; He, Ling; Sun, Lu; Li, Qiannan; Jiang, Zheng; He, Xiangqian

2015-02-01

Skin aging principles play important roles in skin disease diagnosis, the evaluation of skin cosmetic effect, forensic identification and age identification in sports competition, etc. This paper proposes a new method to evaluate the skin aging objectively and quantitatively by skin texture area. Firstly, the enlarged skin image was acquired. Then, the skin texture image was segmented by using the iterative threshold method, and the skin ridge image was extracted according to the watershed algorithm. Finally, the skin ridge areas of the skin texture were extracted. The experiment data showed that the average areas of skin ridges, of both men and women, had a good correlation with age (the correlation coefficient r of male was 0.938, and the correlation coefficient r of female was 0.922), and skin texture area and age regression curve showed that the skin texture area increased with age. Therefore, it is effective to evaluate skin aging objectively by the new method presented in this paper.

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.

Quantitative correlational study of microbubble-enhanced ultrasound imaging and magnetic resonance imaging of glioma and early response to radiotherapy in a rat model

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

Yang, Chen; Lee, Dong-Hoon; Zhang, Kai

Purpose: Radiotherapy remains a major treatment method for malignant tumors. Magnetic resonance imaging (MRI) is the standard modality for assessing glioma treatment response in the clinic. Compared to MRI, ultrasound imaging is low-cost and portable and can be used during intraoperative procedures. The purpose of this study was to quantitatively compare contrast-enhanced ultrasound (CEUS) imaging and MRI of irradiated gliomas in rats and to determine which quantitative ultrasound imaging parameters can be used for the assessment of early response to radiation in glioma. Methods: Thirteen nude rats with U87 glioma were used. A small thinned skull window preparation was performedmore » to facilitate ultrasound imaging and mimic intraoperative procedures. Both CEUS and MRI with structural, functional, and molecular imaging parameters were performed at preradiation and at 1 day and 4 days postradiation. Statistical analysis was performed to determine the correlations between MRI and CEUS parameters and the changes between pre- and postradiation imaging. Results: Area under the curve (AUC) in CEUS showed significant difference between preradiation and 4 days postradiation, along with four MRI parameters, T{sub 2}, apparent diffusion coefficient, cerebral blood flow, and amide proton transfer-weighted (APTw) (all p < 0.05). The APTw signal was correlated with three CEUS parameters, rise time (r = − 0.527, p < 0.05), time to peak (r = − 0.501, p < 0.05), and perfusion index (r = 458, p < 0.05). Cerebral blood flow was correlated with rise time (r = − 0.589, p < 0.01) and time to peak (r = − 0.543, p < 0.05). Conclusions: MRI can be used for the assessment of radiotherapy treatment response and CEUS with AUC as a new technique and can also be one of the assessment methods for early response to radiation in glioma.« less

Data processing device test apparatus and method therefor

DOEpatents

Wilcox, Richard Jacob; Mulig, Jason D.; Eppes, David; Bruce, Michael R.; Bruce, Victoria J.; Ring, Rosalinda M.; Cole, Jr., Edward I.; Tangyunyong, Paiboon; Hawkins, Charles F.; Louie, Arnold Y.

2003-04-08

A method and apparatus mechanism for testing data processing devices are implemented. The test mechanism isolates critical paths by correlating a scanning microscope image with a selected speed path failure. A trigger signal having a preselected value is generated at the start of each pattern vector. The sweep of the scanning microscope is controlled by a computer, which also receives and processes the image signals returned from the microscope. The value of the trigger signal is correlated with a set of pattern lines being driven on the DUT. The trigger is either asserted or negated depending the detection of a pattern line failure and the particular line that failed. In response to the detection of the particular speed path failure being characterized, and the trigger signal, the control computer overlays a mask on the image of the device under test (DUT). The overlaid image provides a visual correlation of the failure with the structural elements of the DUT at the level of resolution of the microscope itself.

Combined iterative reconstruction and image-domain decomposition for dual energy CT using total-variation regularization

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

Dong, Xue; Niu, Tianye; Zhu, Lei, E-mail: leizhu@gatech.edu

2014-05-15

Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical propertiesmore » of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan©600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.« less

Two-level image authentication by two-step phase-shifting interferometry and compressive sensing

NASA Astrophysics Data System (ADS)

Zhang, Xue; Meng, Xiangfeng; Yin, Yongkai; Yang, Xiulun; Wang, Yurong; Li, Xianye; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2018-01-01

A two-level image authentication method is proposed; the method is based on two-step phase-shifting interferometry, double random phase encoding, and compressive sensing (CS) theory, by which the certification image can be encoded into two interferograms. Through discrete wavelet transform (DWT), sparseness processing, Arnold transform, and data compression, two compressed signals can be generated and delivered to two different participants of the authentication system. Only the participant who possesses the first compressed signal attempts to pass the low-level authentication. The application of Orthogonal Match Pursuit CS algorithm reconstruction, inverse Arnold transform, inverse DWT, two-step phase-shifting wavefront reconstruction, and inverse Fresnel transform can result in the output of a remarkable peak in the central location of the nonlinear correlation coefficient distributions of the recovered image and the standard certification image. Then, the other participant, who possesses the second compressed signal, is authorized to carry out the high-level authentication. Therefore, both compressed signals are collected to reconstruct the original meaningful certification image with a high correlation coefficient. Theoretical analysis and numerical simulations verify the feasibility of the proposed method.

Application of digital image correlation for long-distance bridge deflection measurement

NASA Astrophysics Data System (ADS)

Tian, Long; Pan, Bing; Cai, Youfa; Liang, Hui; Zhao, Yan

2013-06-01

Due to its advantages of non-contact, full-field and high-resolution measurement, digital image correlation (DIC) method has gained wide acceptance and found numerous applications in the field of experimental mechanics. In this paper, the application of DIC for real-time long-distance bridge deflection detection in outdoor environments is studied. Bridge deflection measurement using DIC in outdoor environments is more challenging than regular DIC measurements performed under laboratory conditions. First, much more image noise due to variations in ambient light will be presented in the images recorded in outdoor environments. Second, how to select the target area becomes a key factor because long-distance imaging results in a large field of view of the test object. Finally, the image acquisition speed of the camera must be high enough (larger than 100 fps) to capture the real-time dynamic motion of a bridge. In this work, the above challenging issues are addressed and several improvements were made to DIC method. The applicability was demonstrated by real experiments. Experimental results indicate that the DIC method has great potentials in motion measurement in various large building structures.

Live CLEM imaging to analyze nuclear structures at high resolution.

PubMed

Haraguchi, Tokuko; Osakada, Hiroko; Koujin, Takako

2015-01-01

Fluorescence microscopy (FM) and electron microscopy (EM) are powerful tools for observing molecular components in cells. FM can provide temporal information about cellular proteins and structures in living cells. EM provides nanometer resolution images of cellular structures in fixed cells. We have combined FM and EM to develop a new method of correlative light and electron microscopy (CLEM), called "Live CLEM." In this method, the dynamic behavior of specific molecules of interest is first observed in living cells using fluorescence microscopy (FM) and then cellular structures in the same cell are observed using electron microscopy (EM). Following image acquisition, FM and EM images are compared to enable the fluorescent images to be correlated with the high-resolution images of cellular structures obtained using EM. As this method enables analysis of dynamic events involving specific molecules of interest in the context of specific cellular structures at high resolution, it is useful for the study of nuclear structures including nuclear bodies. Here we describe Live CLEM that can be applied to the study of nuclear structures in mammalian cells.

Improved Serial Sectioning Techniques for Correlative Light-Electron Microscopy Mapping of Human Langerhans Islets

PubMed Central

Saitoh, Sei; Ohno, Nobuhiko; Saitoh, Yurika; Terada, Nobuo; Shimo, Satoshi; Aida, Kaoru; Fujii, Hideki; Kobayashi, Tetsuro; Ohno, Shinichi

2018-01-01

Combined analysis of immunostaining for various biological molecules coupled with investigations of ultrastructural features of individual cells is a powerful approach for studies of cellular functions in normal and pathological conditions. However, weak antigenicity of tissues fixed by conventional methods poses a problem for immunoassays. This study introduces a method of correlative light and electron microscopy imaging of the same endocrine cells of compact and diffuse islets from human pancreatic tissue specimens. The method utilizes serial sections obtained from Epon-embedded specimens fixed with glutaraldehyde and osmium tetroxide. Double-immunofluorescence staining of thick Epon sections for endocrine hormones (insulin and glucagon) and regenerating islet-derived gene 1 α (REG1α) was performed following the removal of Epoxy resin with sodium ethoxide, antigen retrieval by autoclaving, and de-osmification treatment with hydrogen peroxide. The immunofluorescence images of endocrine cells were superimposed with the electron microscopy images of the same cells obtained from serial ultrathin sections. Immunofluorescence images showed well-preserved secretory granules in endocrine cells, whereas electron microscopy observations demonstrated corresponding secretory granules and intracellular organelles in the same cells. In conclusion, the correlative imaging approach developed by us may be useful for examining ultrastructural features in combination with immunolocalisation of endocrine hormones in the same human pancreatic islets. PMID:29622846

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.

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.

A high-order time-accurate interrogation method for time-resolved PIV

NASA Astrophysics Data System (ADS)

Lynch, Kyle; Scarano, Fulvio

2013-03-01

A novel method is introduced for increasing the accuracy and extending the dynamic range of time-resolved particle image velocimetry (PIV). The approach extends the concept of particle tracking velocimetry by multiple frames to the pattern tracking by cross-correlation analysis as employed in PIV. The working principle is based on tracking the patterned fluid element, within a chosen interrogation window, along its individual trajectory throughout an image sequence. In contrast to image-pair interrogation methods, the fluid trajectory correlation concept deals with variable velocity along curved trajectories and non-zero tangential acceleration during the observed time interval. As a result, the velocity magnitude and its direction are allowed to evolve in a nonlinear fashion along the fluid element trajectory. The continuum deformation (namely spatial derivatives of the velocity vector) is accounted for by adopting local image deformation. The principle offers important reductions of the measurement error based on three main points: by enlarging the temporal measurement interval, the relative error becomes reduced; secondly, the random and peak-locking errors are reduced by the use of least-squares polynomial fits to individual trajectories; finally, the introduction of high-order (nonlinear) fitting functions provides the basis for reducing the truncation error. Lastly, the instantaneous velocity is evaluated as the temporal derivative of the polynomial representation of the fluid parcel position in time. The principal features of this algorithm are compared with a single-pair iterative image deformation method. Synthetic image sequences are considered with steady flow (translation, shear and rotation) illustrating the increase of measurement precision. An experimental data set obtained by time-resolved PIV measurements of a circular jet is used to verify the robustness of the method on image sequences affected by camera noise and three-dimensional motions. In both cases, it is demonstrated that the measurement time interval can be significantly extended without compromising the correlation signal-to-noise ratio and with no increase of the truncation error. The increase of velocity dynamic range scales more than linearly with the number of frames included for the analysis, which supersedes by one order of magnitude the pair correlation by window deformation. The main factors influencing the performance of the method are discussed, namely the number of images composing the sequence and the polynomial order chosen to represent the motion throughout the trajectory.

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.

Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

NASA Astrophysics Data System (ADS)

Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

2016-04-01

Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the displacement fields. Displacement fields derived from both approaches are then combined and provide a better understanding of the landslide kinematics.

[Evaluation of dental plaque by quantitative digital image analysis system].

PubMed

Huang, Z; Luan, Q X

2016-04-18

To analyze the plaque staining image by using image analysis software, to verify the maneuverability, practicability and repeatability of this technique, and to evaluate the influence of different plaque stains. In the study, 30 volunteers were enrolled from the new dental students of Peking University Health Science Center in accordance with the inclusion criteria. The digital images of the anterior teeth were acquired after plaque stained according to filming standardization.The image analysis was performed using Image Pro Plus 7.0, and the Quigley-Hein plaque indexes of the anterior teeth were evaluated. The plaque stain area percentage and the corresponding dental plaque index were highly correlated,and the Spearman correlation coefficient was 0.776 (P<0.01). Intraclass correlation coefficients of the tooth area and plaque area which two researchers used the software to calculate were 0.956 and 0.930 (P<0.01).The Bland-Altman analysis chart showed only a few spots outside the 95% consistency boundaries. The different plaque stains image analysis results showed that the difference of the tooth area measurements was not significant, while the difference of the plaque area measurements significant (P<0.01). This method is easy in operation and control,highly related to the calculated percentage of plaque area and traditional plaque index, and has good reproducibility.The different plaque staining method has little effect on image segmentation results.The sensitive plaque stain for image analysis is suggested.

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.

New semi-quantitative 123I-MIBG estimation method compared with scoring system in follow-up of advanced neuroblastoma: utility of total MIBG retention ratio versus scoring method.

PubMed

Sano, Yuko; Okuyama, Chio; Iehara, Tomoko; Matsushima, Shigenori; Yamada, Kei; Hosoi, Hajime; Nishimura, Tsunehiko

2012-07-01

The purpose of this study is to evaluate a new semi-quantitative estimation method using (123)I-MIBG retention ratio to assess response to chemotherapy for advanced neuroblastoma. Thirteen children with advanced neuroblastoma (International Neuroblastoma Risk Group Staging System: stage M) were examined for a total of 51 studies with (123)I-MIBG scintigraphy (before and during chemotherapy). We proposed a new semi-quantitative method using MIBG retention ratio (count obtained with delayed image/count obtained with early image with decay correction) to estimate MIBG accumulation. We analyzed total (123)I-MIBG retention ratio (TMRR: total body count obtained with delayed image/total body count obtained with early image with decay correction) and compared with a scoring method in terms of correlation with tumor markers. TMRR showed significantly higher correlations with urinary catecholamine metabolites before chemotherapy (VMA: r(2) = 0.45, P < 0.05, HVA: r(2) = 0.627, P < 0.01) than MIBG score (VMA: r(2) = 0.19, P = 0.082, HVA: r(2) = 0.25, P = 0.137). There were relatively good correlations between serial change of TMRR and those of urinary catecholamine metabolites (VMA: r(2) = 0.274, P < 0.001, HVA: r(2) = 0.448, P < 0.0001) compared with serial change of MIBG score and those of tumor markers (VMA: r(2) = 0.01, P = 0.537, HVA: 0.084, P = 0.697) during chemotherapy for advanced neuroblastoma. TMRR could be a useful semi-quantitative method for estimating early response to chemotherapy of advanced neuroblastoma because of its high correlation with urine catecholamine metabolites.

Blind image quality assessment based on aesthetic and statistical quality-aware features

NASA Astrophysics Data System (ADS)

Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi

2017-07-01

The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.

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

Reconstruction of implanted marker trajectories from cone-beam CT projection images using interdimensional correlation modeling

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

Chung, Hyekyun

Purpose: Cone-beam CT (CBCT) is a widely used imaging modality for image-guided radiotherapy. Most vendors provide CBCT systems that are mounted on a linac gantry. Thus, CBCT can be used to estimate the actual 3-dimensional (3D) position of moving respiratory targets in the thoracic/abdominal region using 2D projection images. The authors have developed a method for estimating the 3D trajectory of respiratory-induced target motion from CBCT projection images using interdimensional correlation modeling. Methods: Because the superior–inferior (SI) motion of a target can be easily analyzed on projection images of a gantry-mounted CBCT system, the authors investigated the interdimensional correlation ofmore » the SI motion with left–right and anterior–posterior (AP) movements while the gantry is rotating. A simple linear model and a state-augmented model were implemented and applied to the interdimensional correlation analysis, and their performance was compared. The parameters of the interdimensional correlation models were determined by least-square estimation of the 2D error between the actual and estimated projected target position. The method was validated using 160 3D tumor trajectories from 46 thoracic/abdominal cancer patients obtained during CyberKnife treatment. The authors’ simulations assumed two application scenarios: (1) retrospective estimation for the purpose of moving tumor setup used just after volumetric matching with CBCT; and (2) on-the-fly estimation for the purpose of real-time target position estimation during gating or tracking delivery, either for full-rotation volumetric-modulated arc therapy (VMAT) in 60 s or a stationary six-field intensity-modulated radiation therapy (IMRT) with a beam delivery time of 20 s. Results: For the retrospective CBCT simulations, the mean 3D root-mean-square error (RMSE) for all 4893 trajectory segments was 0.41 mm (simple linear model) and 0.35 mm (state-augmented model). In the on-the-fly simulations, prior projections over more than 60° appear to be necessary for reliable estimations. The mean 3D RMSE during beam delivery after the simple linear model had established with a prior 90° projection data was 0.42 mm for VMAT and 0.45 mm for IMRT. Conclusions: The proposed method does not require any internal/external correlation or statistical modeling to estimate the target trajectory and can be used for both retrospective image-guided radiotherapy with CBCT projection images and real-time target position monitoring for respiratory gating or tracking.« less

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

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.

Directly imaging steeply-dipping fault zones in geothermal fields with multicomponent seismic data

DOE PAGES

Chen, Ting; Huang, Lianjie

2015-07-30

For characterizing geothermal systems, it is important to have clear images of steeply-dipping fault zones because they may confine the boundaries of geothermal reservoirs and influence hydrothermal flow. Elastic reverse-time migration (ERTM) is the most promising tool for subsurface imaging with multicomponent seismic data. However, conventional ERTM usually generates significant artifacts caused by the cross correlation of undesired wavefields and the polarity reversal of shear waves. In addition, it is difficult for conventional ERTM to directly image steeply-dipping fault zones. We develop a new ERTM imaging method in this paper to reduce these artifacts and directly image steeply-dipping fault zones.more » In our new ERTM method, forward-propagated source wavefields and backward-propagated receiver wavefields are decomposed into compressional (P) and shear (S) components. Furthermore, each component of these wavefields is separated into left- and right-going, or downgoing and upgoing waves. The cross correlation imaging condition is applied to the separated wavefields along opposite propagation directions. For converted waves (P-to-S or S-to-P), the polarity correction is applied to the separated wavefields based on the analysis of Poynting vectors. Numerical imaging examples of synthetic seismic data demonstrate that our new ERTM method produces high-resolution images of steeply-dipping fault zones.« less

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.

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.

Full field study of strain distribution near the crack tip in the fracture of solid propellants via large strain digital image correlation and optical microscopy

NASA Astrophysics Data System (ADS)

Gonzalez, Javier

A full field method for visualizing deformation around the crack tip in a fracture process with large strains is developed. A digital image correlation program (DIC) is used to incrementally compute strains and displacements between two consecutive images of a deformation process. Values of strain and displacements for consecutive deformations are added, this way solving convergence problems in the DIC algorithm when large deformations are investigated. The method developed is used to investigate the strain distribution within 1 mm of the crack tip in a particulate composite solid (propellant) using microscopic visualization of the deformation process.

PIV-DCNN: cascaded deep convolutional neural networks for particle image velocimetry

NASA Astrophysics Data System (ADS)

Lee, Yong; Yang, Hua; Yin, Zhouping

2017-12-01

Velocity estimation (extracting the displacement vector information) from the particle image pairs is of critical importance for particle image velocimetry. This problem is mostly transformed into finding the sub-pixel peak in a correlation map. To address the original displacement extraction problem, we propose a different evaluation scheme (PIV-DCNN) with four-level regression deep convolutional neural networks. At each level, the networks are trained to predict a vector from two input image patches. The low-level network is skilled at large displacement estimation and the high- level networks are devoted to improving the accuracy. Outlier replacement and symmetric window offset operation glue the well- functioning networks in a cascaded manner. Through comparison with the standard PIV methods (one-pass cross-correlation method, three-pass window deformation), the practicability of the proposed PIV-DCNN is verified by the application to a diversity of synthetic and experimental PIV images.

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.

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

Identification of seedling cabbages and weeds using hyperspectral imaging

USDA-ARS?s Scientific Manuscript database

Target detectionis one of research focues for precision chemical application. This study developed a method to identify seedling cabbages and weeds using hyperspectral spectral imaging. In processing the image data, with ENVI software, after dimension reduction, noise reduction, de-correlation for h...

Phi-s correlation and dynamic time warping - Two methods for tracking ice floes in SAR images

NASA Technical Reports Server (NTRS)

Mcconnell, Ross; Kober, Wolfgang; Kwok, Ronald; Curlander, John C.; Pang, Shirley S.

1991-01-01

The authors present two algorithms for performing shape matching on ice floe boundaries in SAR (synthetic aperture radar) images. These algorithms quickly produce a set of ice motion and rotation vectors that can be used to guide a pixel value correlator. The algorithms match a shape descriptor known as the Phi-s curve. The first algorithm uses normalized correlation to match the Phi-s curves, while the second uses dynamic programming to compute an elastic match that better accommodates ice floe deformation. Some empirical data on the performance of the algorithms on Seasat SAR images are presented.

Diffuse optical correlation tomography of cerebral blood flow during cortical spreading depression in rat brain

NASA Astrophysics Data System (ADS)

Zhou, Chao; Yu, Guoqiang; Furuya, Daisuke; Greenberg, Joel; Yodh, Arjun; Durduran, Turgut

2006-02-01

Diffuse optical correlation methods were adapted for three-dimensional (3D) tomography of cerebral blood flow (CBF) in small animal models. The image reconstruction was optimized using a noise model for diffuse correlation tomography which enabled better data selection and regularization. The tomographic approach was demonstrated with simulated data and during in-vivo cortical spreading depression (CSD) in rat brain. Three-dimensional images of CBF were obtained through intact skull in tissues(~4mm) deep below the cortex.

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.

Surface rupture and slip distribution of the 2016 Mw7.8 Kaikoura earthquake (New Zealand) from optical satellite image correlation using MicMac

NASA Astrophysics Data System (ADS)

Champenois, Johann; Klinger, Yann; Grandin, Raphaël; Satriano, Claudio; Baize, Stéphane; Delorme, Arthur; Scotti, Oona

2017-04-01

Remote sensing techniques, like optical satellite image correlation, are very efficient methods to localize and quantify surface displacements due to earthquakes. In this study, we use the french sub-pixel correlator MicMac (Multi Images Correspondances par Méthodes Automatiques de Corrélation). This free open-source software, developed by IGN, was recently adapted to process satellite images. This correlator uses regularization, and that provides good results especially in near-fault area with a high spatial resolution. We use co-seismic pair of ortho-images to measure the horizontal displacement field during the recent 2016 Mw7.8 Kaikoura earthquake. Optical satellite images from different satellites are processed (Sentinel-2A, Landsat8, etc.) to present a dense map of the surface ruptures and to analyze high density slip distribution along all major ruptures. We also provide a detail pattern of deformation along these main surface ruptures. Moreover, 2D displacement from optical correlation is compared to co-seismic measurements from GPS, static displacement from accelerometric records, geodetic marks and field investigations. Last but not least, we investigate the reconstruction of 3D displacement from combining InSAR, GPS and optic.

A new method of derived equatorial plasma bubbles motion by tracing OI 630 nm emission all-sky images

NASA Astrophysics Data System (ADS)

Li, M.; Yu, T.; Chunliang, X.; Zuo, X.; Liu, Z.

2017-12-01

A new method for estimating the equatorial plasma bubbles (EPBs) motions from airglow emission all-sky images is presented in this paper. This method, which is called 'cloud-derived wind technology' and widely used in satellite observation of wind, could reasonable derive zonal and meridional velocity vectors of EPBs drifts by tracking a series of successive airglow 630.0 nm emission images. Airglow emission images data are available from an all sky airglow camera in Hainan Fuke (19.5°N, 109.2°E) supported by China Meridional Project, which can receive the 630.0nm emission from the ionosphere F region at low-latitudes to observe plasma bubbles. A series of pretreatment technology, e.g. image enhancement, orientation correction, image projection are utilized to preprocess the raw observation. Then the regions of plasma bubble extracted from the images are divided into several small tracing windows and each tracing window can find a target window in the searching area in following image, which is considered as the position tracing window moved to. According to this, velocities in each window are calculated by using the technology of cloud-derived wind. When applying the cloud-derived wind technology, the maximum correlation coefficient (MCC) and the histogram of gradient (HOG) methods to find the target window, which mean to find the maximum correlation and the minimum euclidean distance between two gradient histograms in respectively, are investigated and compared in detail. The maximum correlation method is fianlly adopted in this study to analyze the velocity of plasma bubbles because of its better performance than HOG. All-sky images from Hainan Fuke, between August 2014 and October 2014, are analyzed to investigate the plasma bubble drift velocities using MCC method. The data at different local time at 9 nights are studied and find that zonal drift velocity in different latitude at different local time ranges from 50 m/s to 180 m/s and there is a peak value at about 20°N. For comparison and validation, EPBs motions obtained from three traditional methods are also investigated and compared with MC method. The advantages and disadvantages of using cloud-derived wind technology to calculate EPB drift velocity are discussed.

Orthographic Stereo Correlator on the Terrain Model for Apollo Metric Images

NASA Technical Reports Server (NTRS)

Kim, Taemin; Husmann, Kyle; Moratto, Zachary; Nefian, Ara V.

2011-01-01

A stereo correlation method on the object domain is proposed to generate the accurate and dense Digital Elevation Models (DEMs) from lunar orbital imagery. The NASA Ames Intelligent Robotics Group (IRG) aims to produce high-quality terrain reconstructions of the Moon from Apollo Metric Camera (AMC) data. In particular, IRG makes use of a stereo vision process, the Ames Stereo Pipeline (ASP), to automatically generate DEMs from consecutive AMC image pairs. Given camera parameters of an image pair from bundle adjustment in ASP, a correlation window is defined on the terrain with the predefined surface normal of a post rather than image domain. The squared error of back-projected images on the local terrain is minimized with respect to the post elevation. This single dimensional optimization is solved efficiently and improves the accuracy of the elevation estimate.

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.

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.

Quantitative correlational study of microbubble-enhanced ultrasound imaging and magnetic resonance imaging of glioma and early response to radiotherapy in a rat model.

PubMed

Yang, Chen; Lee, Dong-Hoon; Mangraviti, Antonella; Su, Lin; Zhang, Kai; Zhang, Yin; Zhang, Bin; Li, Wenxiao; Tyler, Betty; Wong, John; Wang, Ken Kang-Hsin; Velarde, Esteban; Zhou, Jinyuan; Ding, Kai

2015-08-01

Radiotherapy remains a major treatment method for malignant tumors. Magnetic resonance imaging (MRI) is the standard modality for assessing glioma treatment response in the clinic. Compared to MRI, ultrasound imaging is low-cost and portable and can be used during intraoperative procedures. The purpose of this study was to quantitatively compare contrast-enhanced ultrasound (CEUS) imaging and MRI of irradiated gliomas in rats and to determine which quantitative ultrasound imaging parameters can be used for the assessment of early response to radiation in glioma. Thirteen nude rats with U87 glioma were used. A small thinned skull window preparation was performed to facilitate ultrasound imaging and mimic intraoperative procedures. Both CEUS and MRI with structural, functional, and molecular imaging parameters were performed at preradiation and at 1 day and 4 days postradiation. Statistical analysis was performed to determine the correlations between MRI and CEUS parameters and the changes between pre- and postradiation imaging. Area under the curve (AUC) in CEUS showed significant difference between preradiation and 4 days postradiation, along with four MRI parameters, T2, apparent diffusion coefficient, cerebral blood flow, and amide proton transfer-weighted (APTw) (all p < 0.05). The APTw signal was correlated with three CEUS parameters, rise time (r = - 0.527, p < 0.05), time to peak (r = - 0.501, p < 0.05), and perfusion index (r = 458, p < 0.05). Cerebral blood flow was correlated with rise time (r = - 0.589, p < 0.01) and time to peak (r = - 0.543, p < 0.05). MRI can be used for the assessment of radiotherapy treatment response and CEUS with AUC as a new technique and can also be one of the assessment methods for early response to radiation in glioma.

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.

Dimensions of Attention Associated With the Microstructure of Corona Radiata White Matter.

PubMed

Stave, Elise A; De Bellis, Michael D; Hooper, Steven R; Woolley, Donald P; Chang, Suk Ki; Chen, Steven D

2017-04-01

Mirsky proposed a model of attention that included these dimensions: focus/execute, sustain, stabilize, encode, and shift. The neural correlates of these dimensions were investigated within corona radiata subregions in healthy youth. Diffusion tensor imaging and neuropsychological assessments were conducted in 79 healthy, right-handed youth aged 4-17 years. Diffusion tensor imaging maps were analyzed using standardized parcellation methods. Partial Pearson correlations between neuropsychological standardized scores, representing these attention dimensions, and diffusion tensor imaging measures of corona radiata subregions were calculated after adjusting for gender and IQ. Significant correlations were found between the focus/execute, sustain, stabilize, and shift dimensions and imaging metrics in hypothesized corona radiata subregions. Results suggest that greater microstructural white matter integrity of the corona radiata is partly associated with attention across 4 attention dimensions. Findings suggest that white matter microstructure of the corona radiata is a neural correlate of several, but not all, attention dimensions.

Dimensions of Attention Associated with the Microstructure of Corona Radiata White Matter

PubMed Central

Stave, Elise A.; Hooper, Stephen R.; Woolley, Donald P.; Chang, Suk Ki; Chen, Steven D.

2016-01-01

Mirsky proposed a model of attention that included these dimensions: focus/execute, sustain, stabilize, encode, and shift. The neural correlates of these dimensions were investigated within corona radiate subregions in healthy youth. Diffusion tensor imaging and neuropsychological assessments were conducted in 79 healthy, right-handed youth aged 4–17 years. Diffusion tensor imaging maps were analyzed using standardized parcellation methods. Partial Pearson correlations between neuropsychological standardized scores, representing these attention dimensions, and diffusion tensor imaging measures of corona radiate subregions were calculated after adjusting for gender and IQ. Significant correlations were found between the focus/execute, sustain, stabilize and shift dimensions and imaging metrics in hypothesized corona radiate subregions. Results suggest that greater microstructural white matter integrity of the corona radiata is partly associated with attention across four attention dimensions. Findings suggest that white matter microstructure of the corona radiata is a neural correlate of several, but not all, attention dimensions. PMID:28090797

Correlation estimation and performance optimization for distributed image compression

NASA Astrophysics Data System (ADS)

He, Zhihai; Cao, Lei; Cheng, Hui

2006-01-01

Correlation estimation plays a critical role in resource allocation and rate control for distributed data compression. A Wyner-Ziv encoder for distributed image compression is often considered as a lossy source encoder followed by a lossless Slepian-Wolf encoder. The source encoder consists of spatial transform, quantization, and bit plane extraction. In this work, we find that Gray code, which has been extensively used in digital modulation, is able to significantly improve the correlation between the source data and its side information. Theoretically, we analyze the behavior of Gray code within the context of distributed image compression. Using this theoretical model, we are able to efficiently allocate the bit budget and determine the code rate of the Slepian-Wolf encoder. Our experimental results demonstrate that the Gray code, coupled with accurate correlation estimation and rate control, significantly improves the picture quality, by up to 4 dB, over the existing methods for distributed image compression.

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.

High-resolution nerve ultrasound and magnetic resonance neurography as complementary neuroimaging tools for chronic inflammatory demyelinating polyneuropathy

PubMed Central

Pitarokoili, Kalliopi; Kronlage, Moritz; Bäumer, Philip; Schwarz, Daniel; Gold, Ralf; Bendszus, Martin; Yoon, Min-Suk

2018-01-01

Background: We present a clinical, electrophysiological, sonographical and magnetic resonance neurography (MRN) study examining the complementary role of two neuroimaging methods of the peripheral nervous system for patients with chronic inflammatory demyelinating polyneuropathy (CIDP). Furthermore, we explore the significance of cross-sectional area (CSA) increase through correlations with MRN markers of nerve integrity. Methods: A total of 108 nerve segments on the median, ulnar, radial, tibial and fibular nerve, as well as the lumbar and cervical plexus of 18 CIDP patients were examined with high-resonance nerve ultrasound (HRUS) and MRN additionally to the nerve conduction studies. Results: We observed a fair degree of correlation of the CSA values for all nerves/nerve segments between the two methods, with a low random error in Bland–Altman analysis (bias = HRUS-CSA − MRN-CSA, −0.61 to −3.26 mm). CSA in HRUS correlated with the nerve T2-weighted (nT2) signal increase as well as with diffusion tensor imaging parameters such as fractional anisotropy, a marker of microstructural integrity. HRUS-CSA of the interscalene brachial plexus correlated significantly with the MRN-CSA and nT2 signal of the L5 and S1 roots of the lumbar plexus. Conclusions: HRUS allows for reliable CSA imaging of all peripheral nerves and the cervical plexus, and CSA correlates with markers of nerve integrity. Imaging of proximal segments as well as the estimation of nerve integrity require MRN as a complementary method. PMID:29552093

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.

Compact hybrid optoelectrical unit for image processing and recognition

NASA Astrophysics Data System (ADS)

Cheng, Gang; Jin, Guofan; Wu, Minxian; Liu, Haisong; He, Qingsheng; Yuan, ShiFu

1998-07-01

In this paper a compact opto-electric unit (CHOEU) for digital image processing and recognition is proposed. The central part of CHOEU is an incoherent optical correlator, which is realized with a SHARP QA-1200 8.4 inch active matrix TFT liquid crystal display panel which is used as two real-time spatial light modulators for both the input image and reference template. CHOEU can do two main processing works. One is digital filtering; the other is object matching. Using CHOEU an edge-detection operator is realized to extract the edges from the input images. Then the reprocessed images are sent into the object recognition unit for identifying the important targets. A novel template- matching method is proposed for gray-tome image recognition. A positive and negative cycle-encoding method is introduced to realize the absolute difference measurement pixel- matching on a correlator structure simply. The system has god fault-tolerance ability for rotation distortion, Gaussian noise disturbance or information losing. The experiments are given at the end of this paper.

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.

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 Rotor Tip Vortex Tracing Algorithm for Image Post-Processing

NASA Technical Reports Server (NTRS)

Overmeyer, Austin D.

2015-01-01

A neurite tracing algorithm, originally developed for medical image processing, was used to trace the location of the rotor tip vortex in density gradient flow visualization images. The tracing algorithm was applied to several representative test images to form case studies. The accuracy of the tracing algorithm was compared to two current methods including a manual point and click method and a cross-correlation template method. It is shown that the neurite tracing algorithm can reduce the post-processing time to trace the vortex by a factor of 10 to 15 without compromising the accuracy of the tip vortex location compared to other methods presented in literature.

Correlative cryogenic tomography of cells using light and soft x-rays.

PubMed

Smith, Elizabeth A; Cinquin, Bertrand P; Do, Myan; McDermott, Gerry; Le Gros, Mark A; Larabell, Carolyn A

2014-08-01

Correlated imaging is the process of imaging a specimen with two complementary modalities, and then combining the two data sets to create a highly informative, composite view. A recent implementation of this concept has been the combination of soft x-ray tomography (SXT) with fluorescence cryogenic microscopy (FCM). SXT-FCM is used to visualize cells that are held in a near-native, cryopreserved. The resultant images are, therefore, highly representative of both the cellular architecture and molecular organization in vivo. SXT quantitatively visualizes the cell and sub-cellular structures; FCM images the spatial distribution of fluorescently labeled molecules. Here, we review the characteristics of SXT-FCM, and briefly discuss how this method compares with existing correlative imaging techniques. We also describe how the incorporation of a cryo-rotation stage into a cryogenic fluorescence microscope allows acquisition of fluorescence cryogenic tomography (FCT) data. FCT is optimally suited for correlation with SXT, since both techniques image the specimen in 3-D, potentially with similar, isotropic spatial resolution. © 2013 Elsevier B.V. All rights reserved.

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.

Cyclopentadienyl Rhenium (Technetium) Tricarbonyl Complexes Integrated in Estrogen Receptor Ligands for ER+ Tumor Imaging

DTIC Science & Technology

2006-10-01

determined by imaging correlate well with those determined by immunoassay methods on surgical biopsies. Because of the short half-life of fluorine -18, this...immunoassay methods on surgical biopsies. Currently, the most effective ER imaging agent is a fluorine -18 labeled estrogen. However, because of the short...substituent to the central pentacycle, including nucleophilic addition of organometallic reagents, addition of electrophiles to the cyclopentadiene

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.

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.

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

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.

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.

Image quality evaluation of full reference algorithm

NASA Astrophysics Data System (ADS)

He, Nannan; Xie, Kai; Li, Tong; Ye, Yushan

2018-03-01

Image quality evaluation is a classic research topic, the goal is to design the algorithm, given the subjective feelings consistent with the evaluation value. This paper mainly introduces several typical reference methods of Mean Squared Error(MSE), Peak Signal to Noise Rate(PSNR), Structural Similarity Image Metric(SSIM) and feature similarity(FSIM) of objective evaluation methods. The different evaluation methods are tested by Matlab, and the advantages and disadvantages of these methods are obtained by analyzing and comparing them.MSE and PSNR are simple, but they are not considered to introduce HVS characteristics into image quality evaluation. The evaluation result is not ideal. SSIM has a good correlation and simple calculation ,because it is considered to the human visual effect into image quality evaluation,However the SSIM method is based on a hypothesis,The evaluation result is limited. The FSIM method can be used for test of gray image and color image test, and the result is better. Experimental results show that the new image quality evaluation algorithm based on FSIM is more accurate.

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

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.

High-accuracy and real-time 3D positioning, tracking system for medical imaging applications based on 3D digital image correlation

NASA Astrophysics Data System (ADS)

Xue, Yuan; Cheng, Teng; Xu, Xiaohai; Gao, Zeren; Li, Qianqian; Liu, Xiaojing; Wang, Xing; Song, Rui; Ju, Xiangyang; Zhang, Qingchuan

2017-01-01

This paper presents a system for positioning markers and tracking the pose of a rigid object with 6 degrees of freedom in real-time using 3D digital image correlation, with two examples for medical imaging applications. Traditional DIC method was improved to meet the requirements of the real-time by simplifying the computations of integral pixel search. Experiments were carried out and the results indicated that the new method improved the computational efficiency by about 4-10 times in comparison with the traditional DIC method. The system was aimed for orthognathic surgery navigation in order to track the maxilla segment after LeFort I osteotomy. Experiments showed noise for the static point was at the level of 10-3 mm and the measurement accuracy was 0.009 mm. The system was demonstrated on skin surface shape evaluation of a hand for finger stretching exercises, which indicated a great potential on tracking muscle and skin movements.

Digital double random amplitude image encryption method based on the symmetry property of the parametric discrete Fourier transform

NASA Astrophysics Data System (ADS)

Bekkouche, Toufik; Bouguezel, Saad

2018-03-01

We propose a real-to-real image encryption method. It is a double random amplitude encryption method based on the parametric discrete Fourier transform coupled with chaotic maps to perform the scrambling. The main idea behind this method is the introduction of a complex-to-real conversion by exploiting the inherent symmetry property of the transform in the case of real-valued sequences. This conversion allows the encrypted image to be real-valued instead of being a complex-valued image as in all existing double random phase encryption methods. The advantage is to store or transmit only one image instead of two images (real and imaginary parts). Computer simulation results and comparisons with the existing double random amplitude encryption methods are provided for peak signal-to-noise ratio, correlation coefficient, histogram analysis, and key sensitivity.

Flow-gated radial phase-contrast imaging in the presence of weak flow.

PubMed

Peng, Hsu-Hsia; Huang, Teng-Yi; Wang, Fu-Nien; Chung, Hsiao-Wen

2013-01-01

To implement a flow-gating method to acquire phase-contrast (PC) images of carotid arteries without use of an electrocardiography (ECG) signal to synchronize the acquisition of imaging data with pulsatile arterial flow. The flow-gating method was realized through radial scanning and sophisticated post-processing methods including downsampling, complex difference, and correlation analysis to improve the evaluation of flow-gating times in radial phase-contrast scans. Quantitatively comparable results (R = 0.92-0.96, n = 9) of flow-related parameters, including mean velocity, mean flow rate, and flow volume, with conventional ECG-gated imaging demonstrated that the proposed method is highly feasible. The radial flow-gating PC imaging method is applicable in carotid arteries. The proposed flow-gating method can potentially avoid the setting up of ECG-related equipment for brain imaging. This technique has potential use in patients with arrhythmia or weak ECG signals.

Hyperspectral Image Denoising Using a Nonlocal Spectral Spatial Principal Component Analysis

NASA Astrophysics Data System (ADS)

Li, D.; Xu, L.; Peng, J.; Ma, J.

2018-04-01

Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.

Novel methods of imaging and analysis for the thermoregulatory sweat test.

PubMed

Carroll, Michael Sean; Reed, David W; Kuntz, Nancy L; Weese-Mayer, Debra Ellyn

2018-06-07

The thermoregulatory sweat test (TST) can be central to the identification and management of disorders affecting sudomotor function and small sensory and autonomic nerve fibers, but the cumbersome nature of the standard testing protocol has prevented its widespread adoption. A high resolution, quantitative, clean and simple assay of sweating could significantly improve identification and management of these disorders. Images from 89 clinical TSTs were analyzed retrospectively using two novel techniques. First, using the standard indicator powder, skin surface sweat distributions were determined algorithmically for each patient. Second, a fundamentally novel method using thermal imaging of forced evaporative cooling was evaluated through comparison with the standard technique. Correlation and receiver operating characteristic analyses were used to determine the degree of match between these methods, and the potential limits of thermal imaging were examined through cumulative analysis of all studied patients. Algorithmic encoding of sweating and non-sweating regions produces a more objective analysis for clinical decision making. Additionally, results from the forced cooling method correspond well with those from indicator powder imaging, with a correlation across spatial regions of -0.78 (CI: -0.84 to -0.71). The method works similarly across body regions, and frame-by-frame analysis suggests the ability to identify sweating regions within about 1 second of imaging. While algorithmic encoding can enhance the standard sweat testing protocol, thermal imaging with forced evaporative cooling can dramatically improve the TST by making it less time-consuming and more patient-friendly than the current approach.

Developing and evaluating a target-background similarity metric for camouflage detection.

PubMed

Lin, Chiuhsiang Joe; Chang, Chi-Chan; Liu, Bor-Shong

2014-01-01

Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.

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

Left ventricular mass and hypertrophy by echocardiography and cardiac magnetic resonance: The Multi-Ethnic Study of Atherosclerosis

PubMed Central

Armstrong, Anderson C.; Gjesdal, Ola; Almeida, André; Nacif, Marcelo; Wu, Colin; Bluemke, David A.; Brumback, Lyndia; Lima, João A. C.

2013-01-01

BACKGROUND Left ventricular mass (LVM) and hypertrophy (LVH) are important parameters, but their use is surrounded by controversies. We compare LVM by echocardiography and cardiac magnetic resonance (CMR), investigating reproducibility aspects and the effect of echocardiography image quality. We also compare indexing methods within and between imaging modalities for classification of LVH and cardiovascular risk. METHODS MESA enrolled 880 participants in Baltimore City; 146 had echocardiograms and CMR on the same day. LVM was then assessed using standard techniques. Echocardiography image quality was rated (good/limited) according to the parasternal view. LVH was defined after indexing LVM to body surface area, height1.7, height2.7, or by the predicted LVM from a reference group. Participants were classified for cardiovascular risk according to Framingham score. Pearson’s correlation, Bland-Altman plots, percent agreement, and kappa coefficient assessed agreement within and between modalities. RESULTS LVM by echocardiography (140 ± 40 g) and by CMR were correlated (r = 0.8, p < 0.001) regardless of the echocardiography image quality. The reproducibility profile had strong correlations and agreement for both modalities. Image quality groups had similar characteristics; those with good images compared to CMR slightly superiorly. The prevalence of LVH tended to be higher with higher cardiovascular risk. The agreement for LVH between imaging modalities ranged from 77% to 98% and the kappa coefficient from 0.10 to 0.76. CONCLUSIONS Echocardiography has a reliable performance for LVM assessment and classification of LVH, with limited influence of image quality. Echocardiography and CMR differ in the assessment of LVH, and additional differences rise from the indexing methods. PMID:23930739

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

Accurate and simple method for quantification of hepatic fat content using magnetic resonance imaging: a prospective study in biopsy-proven nonalcoholic fatty liver disease.

PubMed

Hatta, Tomoko; Fujinaga, Yasunari; Kadoya, Masumi; Ueda, Hitoshi; Murayama, Hiroaki; Kurozumi, Masahiro; Ueda, Kazuhiko; Komatsu, Michiharu; Nagaya, Tadanobu; Joshita, Satoru; Kodama, Ryo; Tanaka, Eiji; Uehara, Tsuyoshi; Sano, Kenji; Tanaka, Naoki

2010-12-01

To assess the degree of hepatic fat content, simple and noninvasive methods with high objectivity and reproducibility are required. Magnetic resonance imaging (MRI) is one such candidate, although its accuracy remains unclear. We aimed to validate an MRI method for quantifying hepatic fat content by calibrating MRI reading with a phantom and comparing MRI measurements in human subjects with estimates of liver fat content in liver biopsy specimens. The MRI method was performed by a combination of MRI calibration using a phantom and double-echo chemical shift gradient-echo sequence (double-echo fast low-angle shot sequence) that has been widely used on a 1.5-T scanner. Liver fat content in patients with nonalcoholic fatty liver disease (NAFLD, n = 26) was derived from a calibration curve generated by scanning the phantom. Liver fat was also estimated by optical image analysis. The correlation between the MRI measurements and liver histology findings was examined prospectively. Magnetic resonance imaging measurements showed a strong correlation with liver fat content estimated from the results of light microscopic examination (correlation coefficient 0.91, P < 0.001) regardless of the degree of hepatic steatosis. Moreover, the severity of lobular inflammation or fibrosis did not influence the MRI measurements. This MRI method is simple and noninvasive, has excellent ability to quantify hepatic fat content even in NAFLD patients with mild steatosis or advanced fibrosis, and can be performed easily without special devices.

Optical imaging through turbid media with a degenerate four-wave mixing correlation time gate

DOEpatents

Sappey, Andrew D.

1998-04-14

Optical imaging through turbid media is demonstrated using a degenerate four-wave mixing correlation time gate. An apparatus and method for detecting ballistic and/or snake light while rejecting unwanted diffusive light for imaging structures within highly scattering media are described. Degenerate four-wave mixing (DFWM) of a doubled YAG laser in rhodamine 590 is used to provide an ultrafast correlation time gate to discriminate against light that has undergone multiple scattering and therefore has lost memory of the structures within the scattering medium. Images have been obtained of a test cross-hair pattern through highly turbid suspensions of whole milk in water that are opaque to the naked eye, which demonstrates the utility of DFWM for imaging through turbid media. Use of DFWM as an ultrafast time gate for the detection of ballistic and/or snake light in optical mammography is discussed.

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

Evaluation of Existing Image Matching Methods for Deriving Glacier Surface Displacements Globally from Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Heid, T.; Kääb, A.

2011-12-01

Automatic matching of images from two different times is a method that is often used to derive glacier surface velocity. Nearly global repeat coverage of the Earth's surface by optical satellite sensors now opens the possibility for global-scale mapping and monitoring of glacier flow with a number of applications in, for example, glacier physics, glacier-related climate change and impact assessment, and glacier hazard management. The purpose of this study is to compare and evaluate different existing image matching methods for glacier flow determination over large scales. The study compares six different matching methods: normalized cross-correlation (NCC), the phase correlation algorithm used in the COSI-Corr software, and four other Fourier methods with different normalizations. We compare the methods over five regions of the world with different representative glacier characteristics: Karakoram, the European Alps, Alaska, Pine Island (Antarctica) and southwest Greenland. Landsat images are chosen for matching because they expand back to 1972, they cover large areas, and at the same time their spatial resolution is as good as 15 m for images after 1999 (ETM+ pan). Cross-correlation on orientation images (CCF-O) outperforms the three similar Fourier methods, both in areas with high and low visual contrast. NCC experiences problems in areas with low visual contrast, areas with thin clouds or changing snow conditions between the images. CCF-O has problems on narrow outlet glaciers where small window sizes (about 16 pixels by 16 pixels or smaller) are needed, and it also obtains fewer correct matches than COSI-Corr in areas with low visual contrast. COSI-Corr has problems on narrow outlet glaciers and it obtains fewer correct matches compared to CCF-O when thin clouds cover the surface, or if one of the images contains snow dunes. In total, we consider CCF-O and COSI-Corr to be the two most robust matching methods for global-scale mapping and monitoring of glacier velocities. If combining CCF-O with locally adaptive template sizes and by filtering the matching results automatically by comparing the displacement matrix to its low pass filtered version, the matching process can be automated to a large degree. This allows the derivation of glacier velocities with minimal (but not without!) user interaction and hence also opens up the possibility of global-scale mapping and monitoring of glacier flow.

Comparison of forward- and back-projection in vivo EPID dosimetry for VMAT treatment of the prostate

NASA Astrophysics Data System (ADS)

Bedford, James L.; Hanson, Ian M.; Hansen, Vibeke N.

2018-01-01

In the forward-projection method of portal dosimetry for volumetric modulated arc therapy (VMAT), the integrated signal at the electronic portal imaging device (EPID) is predicted at the time of treatment planning, against which the measured integrated image is compared. In the back-projection method, the measured signal at each gantry angle is back-projected through the patient CT scan to give a measure of total dose to the patient. This study aims to investigate the practical agreement between the two types of EPID dosimetry for prostate radiotherapy. The AutoBeam treatment planning system produced VMAT plans together with corresponding predicted portal images, and a total of 46 sets of gantry-resolved portal images were acquired in 13 patients using an iViewGT portal imager. For the forward-projection method, each acquisition of gantry-resolved images was combined into a single integrated image and compared with the predicted image. For the back-projection method, iViewDose was used to calculate the dose distribution in the patient for comparison with the planned dose. A gamma index for 3% and 3 mm was used for both methods. The results were investigated by delivering the same plans to a phantom and repeating some of the deliveries with deliberately introduced errors. The strongest agreement between forward- and back-projection methods is seen in the isocentric intensity/dose difference, with moderate agreement in the mean gamma. The strongest correlation is observed within a given patient, with less correlation between patients, the latter representing the accuracy of prediction of the two methods. The error study shows that each of the two methods has its own distinct sensitivity to errors, but that overall the response is similar. The forward- and back-projection EPID dosimetry methods show moderate agreement in this series of prostate VMAT patients, indicating that both methods can contribute to the verification of dose delivered to the patient.

TU-A-12A-02: Novel Lung Ventilation Imaging with Single Energy CT After Single Inhalation of Xenon: Comparison with SPECT Ventilation Images

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

Negahdar, M; Yamamoto, T; Shultz, D

Purpose: We propose a novel lung functional imaging method to determine the spatial distribution of xenon (Xe) gas in a single inhalation as a measure of regional ventilation. We compare Xe-CT ventilation to single-photon emission CT (SPECT) ventilation, which is the current clinical reference. Regional lung ventilation information may be useful for the diagnosis and monitoring of pulmonary diseases such as COPD, radiotherapy planning, and assessing the progression of toxicity after radiation therapy. Methods: In an IRB-approved clinical study, Xe-CT and SPECT ventilation scans were acquired for three patients including one patient with severe emphysema and two lung cancer patientsmore » treated with radiotherapy. For Xe- CT, we acquired two breath-hold single energy CT images of the entire lung with inspiration of 100% O2 and a mixture of 70% Xe and 30% O2, respectively. A video biofeedback system was used to achieve reproducible breath-holds. We used deformable image registration to align the breathhold images with each other to accurately subtract them, producing a map of the distribution of Xe as a surrogate of lung ventilation. We divided each lung into twelve parts and correlated the Hounsfield unit (HU) enhancement at each part with the SPECT ventilation count of the corresponding part of the lung. Results: The mean of the Pearson linear correlation coefficient values between the Xe-CT and ventilation SPECT count for all three patients were 0.62 (p<0.01). The Xe-CT image had a higher resolution than SPECT, and did not show central airway deposition artifacts that were present in the SPECT image. Conclusion: We developed a rapid, safe, clinically practical, and potentially widely accessible method for regional lung functional imaging. We demonstrated strong correlations between the Xe-CT ventilation image and SPECT ventilation image as the clinical reference. This ongoing study will investigate more patients to confirm this finding.« less

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.

Palmprint Recognition Across Different Devices.

PubMed

Jia, Wei; Hu, Rong-Xiang; Gui, Jie; Zhao, Yang; Ren, Xiao-Ming

2012-01-01

In this paper, the problem of Palmprint Recognition Across Different Devices (PRADD) is investigated, which has not been well studied so far. Since there is no publicly available PRADD image database, we created a non-contact PRADD image database containing 12,000 grayscale captured from 100 subjects using three devices, i.e., one digital camera and two smart-phones. Due to the non-contact image acquisition used, rotation and scale changes between different images captured from a same palm are inevitable. We propose a robust method to calculate the palm width, which can be effectively used for scale normalization of palmprints. On this PRADD image database, we evaluate the recognition performance of three different methods, i.e., subspace learning method, correlation method, and orientation coding based method, respectively. Experiments results show that orientation coding based methods achieved promising recognition performance for PRADD.

Palmprint Recognition across Different Devices

PubMed Central

Jia, Wei; Hu, Rong-Xiang; Gui, Jie; Zhao, Yang; Ren, Xiao-Ming

2012-01-01

In this paper, the problem of Palmprint Recognition Across Different Devices (PRADD) is investigated, which has not been well studied so far. Since there is no publicly available PRADD image database, we created a non-contact PRADD image database containing 12,000 grayscale captured from 100 subjects using three devices, i.e., one digital camera and two smart-phones. Due to the non-contact image acquisition used, rotation and scale changes between different images captured from a same palm are inevitable. We propose a robust method to calculate the palm width, which can be effectively used for scale normalization of palmprints. On this PRADD image database, we evaluate the recognition performance of three different methods, i.e., subspace learning method, correlation method, and orientation coding based method, respectively. Experiments results show that orientation coding based methods achieved promising recognition performance for PRADD. PMID:22969380

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.

Arterial input function derived from pairwise correlations between PET-image voxels.

PubMed

Schain, Martin; Benjaminsson, Simon; Varnäs, Katarina; Forsberg, Anton; Halldin, Christer; Lansner, Anders; Farde, Lars; Varrone, Andrea

2013-07-01

A metabolite corrected arterial input function is a prerequisite for quantification of positron emission tomography (PET) data by compartmental analysis. This quantitative approach is also necessary for radioligands without suitable reference regions in brain. The measurement is laborious and requires cannulation of a peripheral artery, a procedure that can be associated with patient discomfort and potential adverse events. A non invasive procedure for obtaining the arterial input function is thus preferable. In this study, we present a novel method to obtain image-derived input functions (IDIFs). The method is based on calculation of the Pearson correlation coefficient between the time-activity curves of voxel pairs in the PET image to localize voxels displaying blood-like behavior. The method was evaluated using data obtained in human studies with the radioligands [(11)C]flumazenil and [(11)C]AZ10419369, and its performance was compared with three previously published methods. The distribution volumes (VT) obtained using IDIFs were compared with those obtained using traditional arterial measurements. Overall, the agreement in VT was good (∼3% difference) for input functions obtained using the pairwise correlation approach. This approach performed similarly or even better than the other methods, and could be considered in applied clinical studies. Applications to other radioligands are needed for further verification.

Fully automatic and reference-marker-free image stitching method for full-spine and full-leg imaging with computed radiography

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Foos, David H.; Doran, James; Rogers, Michael K.

2004-05-01

Full-leg and full-spine imaging with standard computed radiography (CR) systems requires several cassettes/storage phosphor screens to be placed in a staggered arrangement and exposed simultaneously to achieve an increased imaging area. A method has been developed that can automatically and accurately stitch the acquired sub-images without relying on any external reference markers. It can detect and correct the order, orientation, and overlap arrangement of the subimages for stitching. The automatic determination of the order, orientation, and overlap arrangement of the sub-images consists of (1) constructing a hypothesis list that includes all cassette/screen arrangements, (2) refining hypotheses based on a set of rules derived from imaging physics, (3) correlating each consecutive sub-image pair in each hypothesis and establishing an overall figure-of-merit, (4) selecting the hypothesis of maximum figure-of-merit. The stitching process requires the CR reader to over scan each CR screen so that the screen edges are completely visible in the acquired sub-images. The rotational displacement and vertical displacement between two consecutive sub-images are calculated by matching the orientation and location of the screen edge in the front image and its corresponding shadow in the back image. The horizontal displacement is estimated by maximizing the correlation function between the two image sections in the overlap region. Accordingly, the two images are stitched together. This process is repeated for the newly stitched composite image and the next consecutive sub-image until a full-image composite is created. The method has been evaluated in both phantom experiments and clinical studies. The standard deviation of image misregistration is below one image pixel.

Visualizing ex vivo radiofrequency and microwave ablation zones using electrode vibration elastography

PubMed Central

DeWall, Ryan J.; Varghese, Tomy; Brace, Chris L.

2012-01-01

Purpose: Electrode vibration elastography is a new shear wave imaging technique that can be used to visualize thermal ablation zones. Prior work has shown the ability of electrode vibration elastography to delineate radiofrequency ablations; however, there has been no previous study of delineation of microwave ablations or radiological–pathological correlations using multiple observers. Methods: Radiofrequency and microwave ablations were formed in ex vivo bovine liver tissue. Their visualization was compared on shear wave velocity and maximum displacement images. Ablation dimensions were compared to gross pathology. Elastographic imaging and gross pathology overlap and interobserver variability were quantified using similarity measures. Results: Elastographic imaging correlated with gross pathology. Correlation of area estimates was better in radiofrequency than in microwave ablations, with Pearson coefficients of 0.79 and 0.54 on shear wave velocity images and 0.90 and 0.70 on maximum displacement images for radiofrequency and microwave ablations, respectively. The absolute relative difference in area between elastographic imaging and gross pathology was 18.9% and 22.9% on shear wave velocity images and 16.0% and 23.1% on maximum displacement images for radiofrequency and microwave ablations, respectively. Conclusions: Statistically significant radiological–pathological correlation was observed in this study, but correlation coefficients were lower than other modulus imaging techniques, most notably in microwave ablations. Observers provided similar delineations for most thermal ablations. These results suggest that electrode vibration elastography is capable of imaging thermal ablations, but refinement of the technique may be necessary before it can be used to monitor thermal ablation procedures clinically. PMID:23127063

Effect of random phase mask on input plane in photorefractive authentic memory with two-wave encryption method

NASA Astrophysics Data System (ADS)

Mita, Akifumi; Okamoto, Atsushi; Funakoshi, Hisatoshi

2004-06-01

We have proposed an all-optical authentic memory with the two-wave encryption method. In the recording process, the image data are encrypted to a white noise by the random phase masks added on the input beam with the image data and the reference beam. Only reading beam with the phase-conjugated distribution of the reference beam can decrypt the encrypted data. If the encrypted data are read out with an incorrect phase distribution, the output data are transformed into a white noise. Moreover, during read out, reconstructions of the encrypted data interfere destructively resulting in zero intensity. Therefore our memory has a merit that we can detect unlawful accesses easily by measuring the output beam intensity. In our encryption method, the random phase mask on the input plane plays important roles in transforming the input image into a white noise and prohibiting to decrypt a white noise to the input image by the blind deconvolution method. Without this mask, when unauthorized users observe the output beam by using CCD in the readout with the plane wave, the completely same intensity distribution as that of Fourier transform of the input image is obtained. Therefore the encrypted image will be decrypted easily by using the blind deconvolution method. However in using this mask, even if unauthorized users observe the output beam using the same method, the encrypted image cannot be decrypted because the observed intensity distribution is dispersed at random by this mask. Thus it can be said the robustness is increased by this mask. In this report, we compare two correlation coefficients, which represents the degree of a white noise of the output image, between the output image and the input image in using this mask or not. We show that the robustness of this encryption method is increased as the correlation coefficient is improved from 0.3 to 0.1 by using this mask.

On dealing with multiple correlation peaks in PIV

NASA Astrophysics Data System (ADS)

Masullo, A.; Theunissen, R.

2018-05-01

A novel algorithm to analyse PIV images in the presence of strong in-plane displacement gradients and reduce sub-grid filtering is proposed in this paper. Interrogation windows subjected to strong in-plane displacement gradients often produce correlation maps presenting multiple peaks. Standard multi-grid procedures discard such ambiguous correlation windows using a signal to noise (SNR) filter. The proposed algorithm improves the standard multi-grid algorithm allowing the detection of splintered peaks in a correlation map through an automatic threshold, producing multiple displacement vectors for each correlation area. Vector locations are chosen by translating images according to the peak displacements and by selecting the areas with the strongest match. The method is assessed on synthetic images of a boundary layer of varying intensity and a sinusoidal displacement field of changing wavelength. An experimental case of a flow exhibiting strong velocity gradients is also provided to show the improvements brought by this technique.

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

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.

Reproducibility of dynamically represented acoustic lung images from healthy individuals

PubMed Central

Maher, T M; Gat, M; Allen, D; Devaraj, A; Wells, A U; Geddes, D M

2008-01-01

Background and aim: Acoustic lung imaging offers a unique method for visualising the lung. This study was designed to demonstrate reproducibility of acoustic lung images recorded from healthy individuals at different time points and to assess intra- and inter-rater agreement in the assessment of dynamically represented acoustic lung images. Methods: Recordings from 29 healthy volunteers were made on three separate occasions using vibration response imaging. Reproducibility was measured using quantitative, computerised assessment of vibration energy. Dynamically represented acoustic lung images were scored by six blinded raters. Results: Quantitative measurement of acoustic recordings was highly reproducible with an intraclass correlation score of 0.86 (very good agreement). Intraclass correlations for inter-rater agreement and reproducibility were 0.61 (good agreement) and 0.86 (very good agreement), respectively. There was no significant difference found between the six raters at any time point. Raters ranged from 88% to 95% in their ability to identically evaluate the different features of the same image presented to them blinded on two separate occasions. Conclusion: Acoustic lung imaging is reproducible in healthy individuals. Graphic representation of lung images can be interpreted with a high degree of accuracy by the same and by different reviewers. PMID:18024534

Cerebella segmentation on MR images of pediatric patients with medulloblastoma

NASA Astrophysics Data System (ADS)

Shan, Zu Y.; Ji, Qing; Glass, John; Gajjar, Amar; Reddick, Wilburn E.

2005-04-01

In this study, an automated method has been developed to identify the cerebellum from T1-weighted MR brain images of patients with medulloblastoma. A new objective function that is similar to Gibbs free energy in classic physics was defined; and the brain structure delineation was viewed as a process of minimizing Gibbs free energy. We used a rigid-body registration and an active contour (snake) method to minimize the Gibbs free energy in this study. The method was applied to 20 patient data sets to generate cerebellum images and volumetric results. The generated cerebellum images were compared with two manually drawn results. Strong correlations were found between the automatically and manually generated volumetric results, the correlation coefficients with each of manual results were 0.971 and 0.974, respectively. The average Jaccard similarities with each of two manual results were 0.89 and 0.88, respectively. The average Kappa indexes with each of two manual results were 0.94 and 0.93, respectively. These results showed this method was both robust and accurate for cerebellum segmentation. The method may be applied to various research and clinical investigation in which cerebellum segmentation and quantitative MR measurement of cerebellum are needed.

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.

Left atrial volume assessment in atrial fibrillation using multimodality imaging: a comparison of echocardiography, invasive three-dimensional CARTO and cardiac magnetic resonance imaging.

PubMed

Rabbat, Mark G; Wilber, David; Thomas, Kevin; Malick, Owais; Bashir, Atif; Agrawal, Anoop; Biswas, Santanu; Sanagala, Thriveni; Syed, Mushabbar A

2015-06-01

Left atrial size in atrial fibrillation is a strong predictor of successful ablation and cardiovascular events. Cardiac magnetic resonance multislice method (CMR-MSM) is the current gold standard for left atrial volume (LAV) assessment but is time consuming. We investigated whether LAV with more rapid area-length method by echocardiography (Echo-AL) or cardiac magnetic resonance (CMR-AL) and invasive measurement by 3D-CARTO mapping during ablation correlate with the CMR-MSM. We studied 250 consecutive patients prior to atrial fibrillation ablation. CMR images were acquired on 3T scanner to measure LAV by MSM and biplane area-length method. Standard echocardiography views were used to calculate LAV by biplane area-length method. LAV during ablation was measured by 3D-CARTO mapping. LAV was compared using intra-class correlation (ICC), Pearson's correlation and Bland-Altman plots. CMR-MSM was used as the reference standard. Mean LAV using CMR-MSM was 112.7 ± 36.7 ml. CMR-AL method overestimated LAV by 13.3 ± 21.8 ml (11.2%, p < 0.005) whereas 3D-CARTO and Echo-AL underestimated LAV by 8.3 ± 22.6 and 24.0 ± 27.6 ml respectively (8.7% and 20.0% respectively, p < 0.005). There was no significant difference between paroxysmal and persistent atrial fibrillation. CMR-AL and 3D-CARTO correlated and agreed well with CMR-MSM (r = 0.87 and 0.74, ICC = 0.80 and 0.77 respectively). However, Echo-AL had poor correlation and agreement with CMR-MSM (r = 0.66 and ICC = 0.48). Bland-Altman plots confirmed these findings. CMR-AL method may be used as an alternative to CMR-MSM, as it is non-invasive, rapid, and correlates well with CMR-MSM. LAV by different modalities should not be used interchangeably.

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.

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.

Characterization of microcracks by application of digital image correlation to SPM images

NASA Astrophysics Data System (ADS)

Keller, Juergen; Gollhardt, Astrid; Vogel, Dietmar; Michel, Bernd

2004-07-01

With the development of micro- and nanotechnological products such as sensors, MEMS/NEMS and their broad application in a variety of market segments new reliability issues will arise. The increasing interface-to-volume ratio in highly integrated systems and nanoparticle filled materials and unsolved questions of size effect of nanomaterials are challenges for experimental reliability evaluation. To fulfill this needs the authors developed the nanoDAC method (nano Deformation Analysis by Correlation), which allows the determination and evaluation of 2D displacement fields based on scanning probe microscopy (SPM) data. In-situ SPM scans of the analyzed object are carried out at different thermo-mechanical load states. The obtained topography-, phase- or error-images are compared utilizing grayscale cross correlation algorithms. This allows the tracking of local image patterns of the analyzed surface structure. The measurement results of the nanoDAC method are full-field displacement and strain fields. Due to the application of SPM equipment deformations in the micro-, nanometer range can be easily detected. The method can be performed on bulk materials, thin films and on devices i.e microelectronic components, sensors or MEMS/NEMS. Furthermore, the characterization and evaluation of micro- and nanocracks or defects in bulk materials, thin layers and at material interfaces can be carried out.

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.

Using 3 Tesla magnetic resonance imaging in the pre-operative evaluation of tongue carcinoma.

PubMed

Moreno, K F; Cornelius, R S; Lucas, F V; Meinzen-Derr, J; Patil, Y J

2017-09-01

This study aimed to evaluate the role of 3 Tesla magnetic resonance imaging in predicting tongue tumour thickness via direct and reconstructed measures, and their correlations with corresponding histological measures, nodal metastasis and extracapsular spread. A prospective study was conducted of 25 patients with histologically proven squamous cell carcinoma of the tongue and pre-operative 3 Tesla magnetic resonance imaging from 2009 to 2012. Correlations between 3 Tesla magnetic resonance imaging and histological measures of tongue tumour thickness were assessed using the Pearson correlation coefficient: r values were 0.84 (p < 0.0001) and 0.81 (p < 0.0001) for direct and reconstructed measurements, respectively. For magnetic resonance imaging, direct measures of tumour thickness (mean ± standard deviation, 18.2 ± 7.3 mm) did not significantly differ from the reconstructed measures (mean ± standard deviation, 17.9 ± 7.2 mm; r = 0.879). Moreover, 3 Tesla magnetic resonance imaging had 83 per cent sensitivity, 82 per cent specificity, 82 per cent accuracy and a 90 per cent negative predictive value for detecting cervical lymph node metastasis. In this cohort, 3 Tesla magnetic resonance imaging measures of tumour thickness correlated highly with the corresponding histological measures. Further, 3 Tesla magnetic resonance imaging was an effective method of detecting malignant adenopathy with extracapsular spread.

Measurement of installation deformation of the acetabulum during prosthetic replacement of a hip joint using digital image correlation

NASA Astrophysics Data System (ADS)

Lei, Dong; Bai, Pengxiang; Zhu, Feipeng

2018-01-01

Nowadays, acetabulum prosthesis replacement is widely used in clinical medicine. However, there is no efficient way to evaluate the implantation effect of the prosthesis. Based on a modern photomechanics technique called digital image correlation (DIC), the evaluation method of the installation effect of the acetabulum was established during a prosthetic replacement of a hip joint. The DIC method determines strain field by comparing the speckle images between the undeformed sample and the deformed counterpart. Three groups of experiments were carried out to verify the feasibility of the DIC method on the acetabulum installation deformation test. Experimental results indicate that the installation deformation of acetabulum generally includes elastic deformation (corresponding to the principal strain of about 1.2%) and plastic deformation. When the installation angle is ideal, the plastic deformation can be effectively reduced, which could prolong the service life of acetabulum prostheses.

Measuring and imaging diffusion with multiple scan speed image correlation spectroscopy.

PubMed

Gröner, Nadine; Capoulade, Jérémie; Cremer, Christoph; Wachsmuth, Malte

2010-09-27

The intracellular mobility of biomolecules is determined by transport and diffusion as well as molecular interactions and is crucial for many processes in living cells. Methods of fluorescence microscopy like confocal laser scanning microscopy (CLSM) can be used to characterize the intracellular distribution of fluorescently labeled biomolecules. Fluorescence correlation spectroscopy (FCS) is used to describe diffusion, transport and photo-physical processes quantitatively. As an alternative to FCS, spatially resolved measurements of mobilities can be implemented using a CLSM by utilizing the spatio-temporal information inscribed into the image by the scan process, referred to as raster image correlation spectroscopy (RICS). Here we present and discuss an extended approach, multiple scan speed image correlation spectroscopy (msICS), which benefits from the advantages of RICS, i.e. the use of widely available instrumentation and the extraction of spatially resolved mobility information, without the need of a priori knowledge of diffusion properties. In addition, msICS covers a broad dynamic range, generates correlation data comparable to FCS measurements, and allows to derive two-dimensional maps of diffusion coefficients. We show the applicability of msICS to fluorophores in solution and to free EGFP in living cells.

Spot auto-focusing and spot auto-stigmation methods with high-definition auto-correlation function in high-resolution TEM.

PubMed

Isakozawa, Shigeto; Fuse, Taishi; Amano, Junpei; Baba, Norio

2018-04-01

As alternatives to the diffractogram-based method in high-resolution transmission electron microscopy, a spot auto-focusing (AF) method and a spot auto-stigmation (AS) method are presented with a unique high-definition auto-correlation function (HD-ACF). The HD-ACF clearly resolves the ACF central peak region in small amorphous-thin-film images, reflecting the phase contrast transfer function. At a 300-k magnification for a 120-kV transmission electron microscope, the smallest areas used are 64 × 64 pixels (~3 nm2) for the AF and 256 × 256 pixels for the AS. A useful advantage of these methods is that the AF function has an allowable accuracy even for a low s/n (~1.0) image. A reference database on the defocus dependency of the HD-ACF by the pre-acquisition of through-focus amorphous-thin-film images must be prepared to use these methods. This can be very beneficial because the specimens are not limited to approximations of weak phase objects but can be extended to objects outside such approximations.

An interdimensional correlation framework for real-time estimation of six degree of freedom target motion using a single x-ray imager during radiotherapy

NASA Astrophysics Data System (ADS)

Nguyen, D. T.; Bertholet, J.; Kim, J.-H.; O'Brien, R.; Booth, J. T.; Poulsen, P. R.; Keall, P. J.

2018-01-01

Increasing evidence suggests that intrafraction tumour motion monitoring needs to include both 3D translations and 3D rotations. Presently, methods to estimate the rotation motion require the 3D translation of the target to be known first. However, ideally, translation and rotation should be estimated concurrently. We present the first method to directly estimate six-degree-of-freedom (6DoF) motion from the target’s projection on a single rotating x-ray imager in real-time. This novel method is based on the linear correlations between the superior-inferior translations and the motion in the other five degrees-of-freedom. The accuracy of the method was evaluated in silico with 81 liver tumour motion traces from 19 patients with three implanted markers. The ground-truth motion was estimated using the current gold standard method where each marker’s 3D position was first estimated using a Gaussian probability method, and the 6DoF motion was then estimated from the 3D positions using an iterative method. The 3D position of each marker was projected onto a gantry-mounted imager with an imaging rate of 11 Hz. After an initial 110° gantry rotation (200 images), a correlation model between the superior-inferior translations and the five other DoFs was built using a least square method. The correlation model was then updated after each subsequent frame to estimate 6DoF motion in real-time. The proposed algorithm had an accuracy (±precision) of  -0.03  ±  0.32 mm, -0.01  ±  0.13 mm and 0.03  ±  0.52 mm for translations in the left-right (LR), superior-inferior (SI) and anterior-posterior (AP) directions respectively; and, 0.07  ±  1.18°, 0.07  ±  1.00° and 0.06  ±  1.32° for rotations around the LR, SI and AP axes respectively on the dataset. The first method to directly estimate real-time 6DoF target motion from segmented marker positions on a 2D imager was devised. The algorithm was evaluated using 81 motion traces from 19 liver patients and was found to have sub-mm and sub-degree accuracy.

Correlation Characterization of Particles in Volume Based on Peak-to-Basement Ratio

PubMed Central

Vovk, Tatiana A.; Petrov, Nikolay V.

2017-01-01

We propose a new express method of the correlation characterization of the particles suspended in the volume of optically transparent medium. It utilizes inline digital holography technique for obtaining two images of the adjacent layers from the investigated volume with subsequent matching of the cross-correlation function peak-to-basement ratio calculated for these images. After preliminary calibration via numerical simulation, the proposed method allows one to quickly distinguish parameters of the particle distribution and evaluate their concentration. The experimental verification was carried out for the two types of physical suspensions. Our method can be applied in environmental and biological research, which includes analyzing tools in flow cytometry devices, express characterization of particles and biological cells in air and water media, and various technical tasks, e.g. the study of scattering objects or rapid determination of cutting tool conditions in mechanisms. PMID:28252020

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.

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.

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.

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

Quantifying riverine surface currents from time sequences of thermal infrared imagery

USGS Publications Warehouse

Puleo, J.A.; McKenna, T.E.; Holland, K.T.; Calantoni, J.

2012-01-01

River surface currents are quantified from thermal and visible band imagery using two methods. One method utilizes time stacks of pixel intensity to estimate the streamwise velocity at multiple locations. The other method uses particle image velocimetry to solve for optimal two-dimensional pixel displacements between successive frames. Field validation was carried out on the Wolf River, a small coastal plain river near Landon, Mississippi, United States, on 26-27 May 2010 by collecting imagery in association with in situ velocities sampled using electromagnetic current meters deployed 0.1 m below the river surface. Comparisons are made between mean in situ velocities and image-derived velocities from 23 thermal and 6 visible-band image sequences (5 min length) during daylight and darkness conditions. The thermal signal was a small apparent temperature contrast induced by turbulent mixing of a thin layer of cooler water near the river surface with underlying warmer water. The visible-band signal was foam on the water surface. For thermal imagery, streamwise velocities derived from the pixel time stack and particle image velocimetry technique were generally highly correlated to mean streamwise current meter velocities during darkness (r 2 typically greater than 0.9) and early morning daylight (r 2 typically greater than 0.83). Streamwise velocities from the pixel time stack technique had high correlation for visible-band imagery during early morning daylight hours with respect to mean current meter velocities (r 2 > 0.86). Streamwise velocities for the particle image velocimetry technique for visible-band imagery had weaker correlations with only three out of six correlations performed having an r 2 exceeding 0.6. Copyright 2012 by the American Geophysical Union.

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.

An algorithm for spatial heirarchy clustering

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Velasco, F. R. D.

1981-01-01

A method for utilizing both spectral and spatial redundancy in compacting and preclassifying images is presented. In multispectral satellite images, a high correlation exists between neighboring image points which tend to occupy dense and restricted regions of the feature space. The image is divided into windows of the same size where the clustering is made. The classes obtained in several neighboring windows are clustered, and then again successively clustered until only one region corresponding to the whole image is obtained. By employing this algorithm only a few points are considered in each clustering, thus reducing computational effort. The method is illustrated as applied to LANDSAT images.

Feasibility of Computed Tomography-Guided Methods for Spatial Normalization of Dopamine Transporter Positron Emission Tomography Image

PubMed Central

Kim, Jin Su; Cho, Hanna; Choi, Jae Yong; Lee, Seung Ha; Ryu, Young Hoon; Lyoo, Chul Hyoung; Lee, Myung Sik

2015-01-01

Background Spatial normalization is a prerequisite step for analyzing positron emission tomography (PET) images both by using volume-of-interest (VOI) template and voxel-based analysis. Magnetic resonance (MR) or ligand-specific PET templates are currently used for spatial normalization of PET images. We used computed tomography (CT) images acquired with PET/CT scanner for the spatial normalization for [18F]-N-3-fluoropropyl-2-betacarboxymethoxy-3-beta-(4-iodophenyl) nortropane (FP-CIT) PET images and compared target-to-cerebellar standardized uptake value ratio (SUVR) values with those obtained from MR- or PET-guided spatial normalization method in healthy controls and patients with Parkinson’s disease (PD). Methods We included 71 healthy controls and 56 patients with PD who underwent [18F]-FP-CIT PET scans with a PET/CT scanner and T1-weighted MR scans. Spatial normalization of MR images was done with a conventional spatial normalization tool (cvMR) and with DARTEL toolbox (dtMR) in statistical parametric mapping software. The CT images were modified in two ways, skull-stripping (ssCT) and intensity transformation (itCT). We normalized PET images with cvMR-, dtMR-, ssCT-, itCT-, and PET-guided methods by using specific templates for each modality and measured striatal SUVR with a VOI template. The SUVR values measured with FreeSurfer-generated VOIs (FSVOI) overlaid on original PET images were also used as a gold standard for comparison. Results The SUVR values derived from all four structure-guided spatial normalization methods were highly correlated with those measured with FSVOI (P < 0.0001). Putaminal SUVR values were highly effective for discriminating PD patients from controls. However, the PET-guided method excessively overestimated striatal SUVR values in the PD patients by more than 30% in caudate and putamen, and thereby spoiled the linearity between the striatal SUVR values in all subjects and showed lower disease discrimination ability. Two CT-guided methods showed comparable capability with the MR-guided methods in separating PD patients from controls and showed better correlation between putaminal SUVR values and the parkinsonian motor severity than the PET-guided method. Conclusion CT-guided spatial normalization methods provided reliable striatal SUVR values comparable to those obtained with MR-guided methods. CT-guided methods can be useful for analyzing dopamine transporter PET images when MR images are unavailable. PMID:26147749

Scanning electron microscopy of bone.

PubMed

Boyde, Alan

2012-01-01

This chapter described methods for Scanning Electron Microscopical imaging of bone and bone cells. Backscattered electron (BSE) imaging is by far the most useful in the bone field, followed by secondary electrons (SE) and the energy dispersive X-ray (EDX) analytical modes. This chapter considers preparing and imaging samples of unembedded bone having 3D detail in a 3D surface, topography-free, polished or micromilled, resin-embedded block surfaces, and resin casts of space in bone matrix. The chapter considers methods for fixation, drying, looking at undersides of bone cells, and coating. Maceration with alkaline bacterial pronase, hypochlorite, hydrogen peroxide, and sodium or potassium hydroxide to remove cells and unmineralised matrix is described in detail. Attention is given especially to methods for 3D BSE SEM imaging of bone samples and recommendations for the types of resin embedding of bone for BSE imaging are given. Correlated confocal and SEM imaging of PMMA-embedded bone requires the use of glycerol to coverslip. Cathodoluminescence (CL) mode SEM imaging is an alternative for visualising fluorescent mineralising front labels such as calcein and tetracyclines. Making spatial casts from PMMA or other resin embedded samples is an important use of this material. Correlation with other imaging means, including microradiography and microtomography is important. Shipping wet bone samples between labs is best done in glycerol. Environmental SEM (ESEM, controlled vacuum mode) is valuable in eliminating -"charging" problems which are common with complex, cancellous bone samples.

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.

An AST-ELM Method for Eliminating the Influence of Charging Phenomenon on ECT.

PubMed

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2017-12-09

Electrical capacitance tomography (ECT) is a promising imaging technology of permittivity distributions in multiphase flow. To reduce the effect of charging phenomenon on ECT measurement, an improved extreme learning machine method combined with adaptive soft-thresholding (AST-ELM) is presented and studied for image reconstruction. This method can provide a nonlinear mapping model between the capacitance values and medium distributions by using machine learning but not an electromagnetic-sensitive mechanism. Both simulation and experimental tests are carried out to validate the performance of the presented method, and reconstructed images are evaluated by relative error and correlation coefficient. The results have illustrated that the image reconstruction accuracy by the proposed AST-ELM method has greatly improved than that by the conventional methods under the condition with charging object.

An AST-ELM Method for Eliminating the Influence of Charging Phenomenon on ECT

PubMed Central

Wang, Xiaoxin; Hu, Hongli; Jia, Huiqin; Tang, Kaihao

2017-01-01

Electrical capacitance tomography (ECT) is a promising imaging technology of permittivity distributions in multiphase flow. To reduce the effect of charging phenomenon on ECT measurement, an improved extreme learning machine method combined with adaptive soft-thresholding (AST-ELM) is presented and studied for image reconstruction. This method can provide a nonlinear mapping model between the capacitance values and medium distributions by using machine learning but not an electromagnetic-sensitive mechanism. Both simulation and experimental tests are carried out to validate the performance of the presented method, and reconstructed images are evaluated by relative error and correlation coefficient. The results have illustrated that the image reconstruction accuracy by the proposed AST-ELM method has greatly improved than that by the conventional methods under the condition with charging object. PMID:29232850

A spatially adaptive total variation regularization method for electrical resistance tomography

NASA Astrophysics Data System (ADS)

Song, Xizi; Xu, Yanbin; Dong, Feng

2015-12-01

The total variation (TV) regularization method has been used to solve the ill-posed inverse problem of electrical resistance tomography (ERT), owing to its good ability to preserve edges. However, the quality of the reconstructed images, especially in the flat region, is often degraded by noise. To optimize the regularization term and the regularization factor according to the spatial feature and to improve the resolution of reconstructed images, a spatially adaptive total variation (SATV) regularization method is proposed. A kind of effective spatial feature indicator named difference curvature is used to identify which region is a flat or edge region. According to different spatial features, the SATV regularization method can automatically adjust both the regularization term and regularization factor. At edge regions, the regularization term is approximate to the TV functional to preserve the edges; in flat regions, it is approximate to the first-order Tikhonov (FOT) functional to make the solution stable. Meanwhile, the adaptive regularization factor determined by the spatial feature is used to constrain the regularization strength of the SATV regularization method for different regions. Besides, a numerical scheme is adopted for the implementation of the second derivatives of difference curvature to improve the numerical stability. Several reconstruction image metrics are used to quantitatively evaluate the performance of the reconstructed results. Both simulation and experimental results indicate that, compared with the TV (mean relative error 0.288, mean correlation coefficient 0.627) and FOT (mean relative error 0.295, mean correlation coefficient 0.638) regularization methods, the proposed SATV (mean relative error 0.259, mean correlation coefficient 0.738) regularization method can endure a relatively high level of noise and improve the resolution of reconstructed images.

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

Assessing the skeletal age from a hand radiograph: automating the Tanner-Whitehouse method

NASA Astrophysics Data System (ADS)

Niemeijer, Meindert; van Ginneken, Bram; Maas, Casper A.; Beek, Frederik J. A.; Viergever, Max A.

2003-05-01

The skeletal maturity of children is usually assessed from a standard radiograph of the left hand and wrist. An established clinical method to determine the skeletal maturity is the Tanner-Whitehouse (TW2) method. This method divides the skeletal development into several stages (labelled A, B, ...,I). We are developing an automated system based on this method. In this work we focus on assigning a stage to one region of interest (ROI), the middle phalanx of the third finger. We classify each ROI as follows. A number of ROIs which have been assigned a certain stage by a radiologist are used to construct a mean image for that stage. For a new input ROI, landmarks are detected by using an Active Shape Model. These are used to align the mean images with the input image. Subsequently the correlation between each transformed mean stage image and the input is calculated. The input ROI can be assigned to the stage with the highest correlation directly, or the values can be used as features in a classifier. The method was tested on 71 cases ranging from stage E to I. The ROI was staged correctly in 73.2% of all cases and in 97.2% of all incorrectly staged cases the error was not more than one stage.

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

Correlation peak analysis applied to a sequence of images using two different filters for eye tracking model

NASA Astrophysics Data System (ADS)

Patrón, Verónica A.; Álvarez Borrego, Josué; Coronel Beltrán, Ángel

2015-09-01

Eye tracking has many useful applications that range from biometrics to face recognition and human-computer interaction. The analysis of the characteristics of the eyes has become one of the methods to accomplish the location of the eyes and the tracking of the point of gaze. Characteristics such as the contrast between the iris and the sclera, the shape, and distribution of colors and dark/light zones in the area are the starting point for these analyses. In this work, the focus will be on the contrast between the iris and the sclera, performing a correlation in the frequency domain. The images are acquired with an ordinary camera, which with were taken images of thirty-one volunteers. The reference image is an image of the subjects looking to a point in front of them at 0° angle. Then sequences of images are taken with the subject looking at different angles. These images are processed in MATLAB, obtaining the maximum correlation peak for each image, using two different filters. Each filter were analyzed and then one was selected, which is the filter that gives the best performance in terms of the utility of the data, which is displayed in graphs that shows the decay of the correlation peak as the eye moves progressively at different angle. This data will be used to obtain a mathematical model or function that establishes a relationship between the angle of vision (AOV) and the maximum correlation peak (MCP). This model will be tested using different input images from other subject not contained in the initial database, being able to predict angle of vision using the maximum correlation peak data.

A method of extracting speed-dependent vector correlations from 2 + 1 REMPI ion images.

PubMed

Wei, Wei; Wallace, Colin J; Grubb, Michael P; North, Simon W

2017-07-07

We present analytical expressions for extracting Dixon's bipolar moments in the semi-classical limit from experimental anisotropy parameters of sliced or reconstructed non-sliced images. The current method focuses on images generated by 2 + 1 REMPI (Resonance Enhanced Multi-photon Ionization) and is a necessary extension of our previously published 1 + 1 REMPI equations. Two approaches for applying the new equations, direct inversion and forward convolution, are presented. As demonstration of the new method, bipolar moments were extracted from images of carbonyl sulfide (OCS) photodissociation at 230 nm and NO 2 photodissociation at 355 nm, and the results are consistent with previous publications.

Abdominal multi-organ CT segmentation using organ correlation graph and prediction-based shape and location priors.

PubMed

Okada, Toshiyuki; Linguraru, Marius George; Hori, Masatoshi; Summers, Ronald M; Tomiyama, Noriyuki; Sato, Yoshinobu

2013-01-01

The paper addresses the automated segmentation of multiple organs in upper abdominal CT data. We propose a framework of multi-organ segmentation which is adaptable to any imaging conditions without using intensity information in manually traced training data. The features of the framework are as follows: (1) the organ correlation graph (OCG) is introduced, which encodes the spatial correlations among organs inherent in human anatomy; (2) the patient-specific organ shape and location priors obtained using OCG enable the estimation of intensity priors from only target data and optionally a number of untraced CT data of the same imaging condition as the target data. The proposed methods were evaluated through segmentation of eight abdominal organs (liver, spleen, left and right kidney, pancreas, gallbladder, aorta, and inferior vena cava) from 86 CT data obtained by four imaging conditions at two hospitals. The performance was comparable to the state-of-the-art method using intensity priors constructed from manually traced data.

A method to estimate the effect of deformable image registration uncertainties on daily dose mapping

PubMed Central

Murphy, Martin J.; Salguero, Francisco J.; Siebers, Jeffrey V.; Staub, David; Vaman, Constantin

2012-01-01

Purpose: To develop a statistical sampling procedure for spatially-correlated uncertainties in deformable image registration and then use it to demonstrate their effect on daily dose mapping. Methods: Sequential daily CT studies are acquired to map anatomical variations prior to fractionated external beam radiotherapy. The CTs are deformably registered to the planning CT to obtain displacement vector fields (DVFs). The DVFs are used to accumulate the dose delivered each day onto the planning CT. Each DVF has spatially-correlated uncertainties associated with it. Principal components analysis (PCA) is applied to measured DVF error maps to produce decorrelated principal component modes of the errors. The modes are sampled independently and reconstructed to produce synthetic registration error maps. The synthetic error maps are convolved with dose mapped via deformable registration to model the resulting uncertainty in the dose mapping. The results are compared to the dose mapping uncertainty that would result from uncorrelated DVF errors that vary randomly from voxel to voxel. Results: The error sampling method is shown to produce synthetic DVF error maps that are statistically indistinguishable from the observed error maps. Spatially-correlated DVF uncertainties modeled by our procedure produce patterns of dose mapping error that are different from that due to randomly distributed uncertainties. Conclusions: Deformable image registration uncertainties have complex spatial distributions. The authors have developed and tested a method to decorrelate the spatial uncertainties and make statistical samples of highly correlated error maps. The sample error maps can be used to investigate the effect of DVF uncertainties on daily dose mapping via deformable image registration. An initial demonstration of this methodology shows that dose mapping uncertainties can be sensitive to spatial patterns in the DVF uncertainties. PMID:22320766

Thresholding Based on Maximum Weighted Object Correlation for Rail Defect Detection

NASA Astrophysics Data System (ADS)

Li, Qingyong; Huang, Yaping; Liang, Zhengping; Luo, Siwei

Automatic thresholding is an important technique for rail defect detection, but traditional methods are not competent enough to fit the characteristics of this application. This paper proposes the Maximum Weighted Object Correlation (MWOC) thresholding method, fitting the features that rail images are unimodal and defect proportion is small. MWOC selects a threshold by optimizing the product of object correlation and the weight term that expresses the proportion of thresholded defects. Our experimental results demonstrate that MWOC achieves misclassification error of 0.85%, and outperforms the other well-established thresholding methods, including Otsu, maximum correlation thresholding, maximum entropy thresholding and valley-emphasis method, for the application of rail defect detection.

In vitro Cell Viability by CellProfiler® Software as Equivalent to MTT Assay.

PubMed

Gasparini, Luciana S; Macedo, Nayana D; Pimentel, Elisângela F; Fronza, Marcio; Junior, Valdemar L; Borges, Warley S; Cole, Eduardo R; Andrade, Tadeu U; Endringer, Denise C; Lenz, Dominik

2017-07-01

This study evaluated in vitro cell viability by the colorimetric MTT stands for 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) assay compared to image analysis by CellProfiler ® software. Hepatoma (Hepa-1c1c7) and fibroblast (L929) cells were exposed to isolated substances, camptothecin, lycorine, tazettine, albomaculine, 3-epimacronine, trispheridine, galanthine and Padina gymnospora , Sargassum sp. methanolic extract, and Habranthus itaobinus Ravenna ethyl acetate in different concentrations. After MTT assay, cells were stained with Panotic dye kit. Cell images were obtained with an inverted microscope equipped with a digital camera. The images were analyzed by CellProfiler ® . No cytotoxicity at the highest concentration analyzed for 3-epimacronine, albomaculine, galanthine, trispheridine, P. gymnospora extract and Sargassum sp. extract where detected. Tazettine offered cytotoxicity only against the Hepa1c1c7 cell line. Lycorine, camptothecin, and H. itaobinus extract exhibited cytotoxic effects in both cell lines. The viability methods tested were correlated demonstrated by Bland-Atman test with normal distribution with mean difference between the two methods close to zero, bias value 3.0263. The error was within the limits of the confidence intervals and these values had a narrow difference. The correlation between the two methods was demonstrated by the linear regression plotted as R 2 . CellProfiler ® image analysis presented similar results to the MTT assay in the identification of viable cells, and image analysis may assist part of biological analysis procedures. The presented methodology is inexpensive and reproducible. In vitro cell viability assessment with MTT (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) assay may be replaced by image analysis by CellProfiler ® . The viability methods tested were correlated demonstrated by Bland-Atman test with normal distribution with mean difference between the two methods close to zero, bias value 3.0263. The correlation between the two methods was demonstrated by the linear regression plotted as R2. Abbreviations: HPLC: High pressure liquid chromatography MTT: (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide) (3-(4, 5-dimethylthiazolyl-2)-2, 5-diphenyltetrazolium bromide).

Noninvasive measurement of pharmacokinetics by near-infrared fluorescence imaging in the eye of mice

NASA Astrophysics Data System (ADS)

Dobosz, Michael; Strobel, Steffen; Stubenrauch, Kay-Gunnar; Osl, Franz; Scheuer, Werner

2014-01-01

Purpose: For generating preclinical pharmacokinetics (PKs) of compounds, blood is drawn at different time points and levels are quantified by different analytical methods. In order to receive statistically meaningful data, 3 to 5 animals are used for each time point to get serum peak-level and half-life of the compound. Both characteristics are determined by data interpolation, which may influence the accuracy of these values. We provide a method that allows continuous monitoring of blood levels noninvasively by measuring the fluorescence intensity of labeled compounds in the eye and other body regions of anesthetized mice. Procedures: The method evaluation was performed with four different fluorescent compounds: (i) indocyanine green, a nontargeting dye; (ii) OsteoSense750, a bone targeting agent; (iii) tumor targeting Trastuzumab-Alexa750; and (iv) its F(-alxea750 fragment. The latter was used for a direct comparison between fluorescence imaging and classical blood analysis using enzyme-linked immunosorbent assay (ELISA). Results: We found an excellent correlation between blood levels measured by noninvasive eye imaging with the results generated by classical methods. A strong correlation between eye imaging and ELISA was demonstrated for the F( fragment. Whole body imaging revealed a compound accumulation in the expected regions (e.g., liver, bone). Conclusions: The combination of eye and whole body fluorescence imaging enables the simultaneous measurement of blood PKs and biodistribution of fluorescent-labeled compounds.

Lactate Chemical Exchange Saturation Transfer (LATEST) Imaging in vivo A Biomarker for LDH Activity.

PubMed

DeBrosse, Catherine; Nanga, Ravi Prakash Reddy; Bagga, Puneet; Nath, Kavindra; Haris, Mohammad; Marincola, Francesco; Schnall, Mitchell D; Hariharan, Hari; Reddy, Ravinder

2016-01-22

Non-invasive imaging of lactate is of enormous significance in cancer and metabolic disorders where glycolysis dominates. Here, for the first time, we describe a chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) method (LATEST), based on the exchange between lactate hydroxyl proton and bulk water protons to image lactate with high spatial resolution. We demonstrate the feasibility of imaging lactate with LATEST in lactate phantoms under physiological conditions, in a mouse model of lymphoma tumors, and in skeletal muscle of healthy human subjects pre- and post-exercise. The method is validated by measuring LATEST changes in lymphoma tumors pre- and post-infusion of pyruvate and correlating them with lactate determined from multiple quantum filtered proton magnetic resonance spectroscopy (SEL-MQC (1)H-MRS). Similarly, dynamic LATEST changes in exercising human skeletal muscle are correlated with lactate determined from SEL-MQC (1)H-MRS. The LATEST method does not involve injection of radioactive isotopes or labeled metabolites. It has over two orders of magnitude higher sensitivity compared to conventional (1)H-MRS. It is anticipated that this technique will have a wide range of applications including diagnosis and evaluation of therapeutic response of cancer, diabetes, cardiac, and musculoskeletal diseases. The advantages of LATEST over existing methods and its potential challenges are discussed.

Lactate Chemical Exchange Saturation Transfer (LATEST) Imaging in vivo A Biomarker for LDH Activity

PubMed Central

DeBrosse, Catherine; Nanga, Ravi Prakash Reddy; Bagga, Puneet; Nath, Kavindra; Haris, Mohammad; Marincola, Francesco; Schnall, Mitchell D.; Hariharan, Hari; Reddy, Ravinder

2016-01-01

Non-invasive imaging of lactate is of enormous significance in cancer and metabolic disorders where glycolysis dominates. Here, for the first time, we describe a chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) method (LATEST), based on the exchange between lactate hydroxyl proton and bulk water protons to image lactate with high spatial resolution. We demonstrate the feasibility of imaging lactate with LATEST in lactate phantoms under physiological conditions, in a mouse model of lymphoma tumors, and in skeletal muscle of healthy human subjects pre- and post-exercise. The method is validated by measuring LATEST changes in lymphoma tumors pre- and post-infusion of pyruvate and correlating them with lactate determined from multiple quantum filtered proton magnetic resonance spectroscopy (SEL-MQC 1H-MRS). Similarly, dynamic LATEST changes in exercising human skeletal muscle are correlated with lactate determined from SEL-MQC 1H-MRS. The LATEST method does not involve injection of radioactive isotopes or labeled metabolites. It has over two orders of magnitude higher sensitivity compared to conventional 1H-MRS. It is anticipated that this technique will have a wide range of applications including diagnosis and evaluation of therapeutic response of cancer, diabetes, cardiac, and musculoskeletal diseases. The advantages of LATEST over existing methods and its potential challenges are discussed. PMID:26794265

Correlation between automatic detection of malaria on thin film and experts' parasitaemia scores

NASA Astrophysics Data System (ADS)

Sunarko, Budi; Williams, Simon; Prescott, William R.; Byker, Scott M.; Bottema, Murk J.

2017-03-01

An algorithm was developed to diagnose the presence of malaria and to estimate the depth of infection by automatically counting individual normal and infected erythrocytes in images of thin blood smears. During the training stage, the parameters of the algorithm were optimized to maximize correlation with estimates of parasitaemia from expert human observers. The correlation was tested on a set of 1590 images from seven thin film blood smears. The correlation between the results from the algorithm and expert human readers was r = 0.836. Results indicate that reliable estimates of parasitaemia may be achieved by computational image analysis methods applied to images of thin film smears. Meanwhile, compared to biological experiments, the algorithm fitted well the three high parasitaemia slides and a mid-level parasitaemia slide, and overestimated the three low parasitaemia slides. To improve the parasitaemia estimation, the sources of the overestimation were identified. Emphasis is laid on the importance of further research in order to identify parasites independently of their erythrocyte hosts

Multi-camera digital image correlation method with distributed fields of view

NASA Astrophysics Data System (ADS)

Malowany, Krzysztof; Malesa, Marcin; Kowaluk, Tomasz; Kujawinska, Malgorzata

2017-11-01

A multi-camera digital image correlation (DIC) method and system for measurements of large engineering objects with distributed, non-overlapping areas of interest are described. The data obtained with individual 3D DIC systems are stitched by an algorithm which utilizes the positions of fiducial markers determined simultaneously by Stereo-DIC units and laser tracker. The proposed calibration method enables reliable determination of transformations between local (3D DIC) and global coordinate systems. The applicability of the method was proven during in-situ measurements of a hall made of arch-shaped (18 m span) self-supporting metal-plates. The proposed method is highly recommended for 3D measurements of shape and displacements of large and complex engineering objects made from multiple directions and it provides the suitable accuracy of data for further advanced structural integrity analysis of such objects.

The impact of cine EPID image acquisition frame rate on markerless soft-tissue tracking

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

Yip, Stephen, E-mail: syip@lroc.harvard.edu; Rottmann, Joerg; Berbeco, Ross

2014-06-15

Purpose: Although reduction of the cine electronic portal imaging device (EPID) acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor autotracking results. The impact of motion blurring and image noise on the tracking performance was investigated. Methods: Phantom and patient images were acquired at a frame rate of 12.87 Hz with an amorphous silicon portal imager (AS1000, Varian Medical Systems, Palo Alto, CA). The maximum frame rate of 12.87 Hz is imposed by the EPID. Low frame rate images were obtained bymore » continuous frame averaging. A previously validated tracking algorithm was employed for autotracking. The difference between the programmed and autotracked positions of a Las Vegas phantom moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at 11 field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise are correlated with δ using Pearson correlation coefficient (R). Results: For both phantom and patient studies, the autotracking errors increased at frame rates lower than 4.29 Hz. Above 4.29 Hz, changes in errors were negligible withδ < 1.60 mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R = 0.94) and patient studies (R = 0.72). Moderate to poor correlation was found between image noise and tracking error with R −0.58 and −0.19 for both studies, respectively. Conclusions: Cine EPID image acquisition at the frame rate of at least 4.29 Hz is recommended. Motion blurring in the images with frame rates below 4.29 Hz can significantly reduce the accuracy of autotracking.« less

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

Fluorescence imaging of tryptophan and collagen cross-links to evaluate wound closure ex vivo

NASA Astrophysics Data System (ADS)

Wang, Ying; Ortega-Martinez, Antonio; Farinelli, Bill; Anderson, R. R.; Franco, Walfre

2016-02-01

Wound size is a key parameter in monitoring healing. Current methods to measure wound size are often subjective, time-consuming and marginally invasive. Recently, we developed a non-invasive, non-contact, fast and simple but robust fluorescence imaging (u-FEI) method to monitor the healing of skin wounds. This method exploits the fluorescence of native molecules to tissue as functional and structural markers. The objective of the present study is to demonstrate the feasibility of using variations in the fluorescence intensity of tryptophan and cross-links of collagen to evaluate proliferation of keratinocyte cells and quantitate size of wound during healing, respectively. Circular dermal wounds were created in ex vivo human skin and cultured in different media. Two serial fluorescence images of tryptophan and collagen cross-links were acquired every two days. Histology and immunohistology were used to validate correlation between fluorescence and epithelialization. Images of collagen cross-links show fluorescence of the exposed dermis and, hence, are a measure of wound area. Images of tryptophan show higher fluorescence intensity of proliferating keratinocytes forming new epithelium, as compared to surrounding keratinocytes not involved in epithelialization. These images are complementary since collagen cross-links report on structure while tryptophan reports on function. HE and immunohistology show that tryptophan fluorescence correlates with newly formed epidermis. We have established a fluorescence imaging method for studying epithelialization processes during wound healing in a skin organ culture model, our approach has the potential to provide a non-invasive, non-contact, quick, objective and direct method for quantitative measurements in wound healing in vivo.

Feasibility of Computed Tomography-Guided Methods for Spatial Normalization of Dopamine Transporter Positron Emission Tomography Image.

PubMed

Kim, Jin Su; Cho, Hanna; Choi, Jae Yong; Lee, Seung Ha; Ryu, Young Hoon; Lyoo, Chul Hyoung; Lee, Myung Sik

2015-01-01

Spatial normalization is a prerequisite step for analyzing positron emission tomography (PET) images both by using volume-of-interest (VOI) template and voxel-based analysis. Magnetic resonance (MR) or ligand-specific PET templates are currently used for spatial normalization of PET images. We used computed tomography (CT) images acquired with PET/CT scanner for the spatial normalization for [18F]-N-3-fluoropropyl-2-betacarboxymethoxy-3-beta-(4-iodophenyl) nortropane (FP-CIT) PET images and compared target-to-cerebellar standardized uptake value ratio (SUVR) values with those obtained from MR- or PET-guided spatial normalization method in healthy controls and patients with Parkinson's disease (PD). We included 71 healthy controls and 56 patients with PD who underwent [18F]-FP-CIT PET scans with a PET/CT scanner and T1-weighted MR scans. Spatial normalization of MR images was done with a conventional spatial normalization tool (cvMR) and with DARTEL toolbox (dtMR) in statistical parametric mapping software. The CT images were modified in two ways, skull-stripping (ssCT) and intensity transformation (itCT). We normalized PET images with cvMR-, dtMR-, ssCT-, itCT-, and PET-guided methods by using specific templates for each modality and measured striatal SUVR with a VOI template. The SUVR values measured with FreeSurfer-generated VOIs (FSVOI) overlaid on original PET images were also used as a gold standard for comparison. The SUVR values derived from all four structure-guided spatial normalization methods were highly correlated with those measured with FSVOI (P < 0.0001). Putaminal SUVR values were highly effective for discriminating PD patients from controls. However, the PET-guided method excessively overestimated striatal SUVR values in the PD patients by more than 30% in caudate and putamen, and thereby spoiled the linearity between the striatal SUVR values in all subjects and showed lower disease discrimination ability. Two CT-guided methods showed comparable capability with the MR-guided methods in separating PD patients from controls and showed better correlation between putaminal SUVR values and the parkinsonian motor severity than the PET-guided method. CT-guided spatial normalization methods provided reliable striatal SUVR values comparable to those obtained with MR-guided methods. CT-guided methods can be useful for analyzing dopamine transporter PET images when MR images are unavailable.

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.

WE-FG-207B-05: Iterative Reconstruction Via Prior Image Constrained Total Generalized Variation for Spectral CT

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

Niu, S; Zhang, Y; Ma, J

Purpose: To investigate iterative reconstruction via prior image constrained total generalized variation (PICTGV) for spectral computed tomography (CT) using fewer projections while achieving greater image quality. Methods: The proposed PICTGV method is formulated as an optimization problem, which balances the data fidelity and prior image constrained total generalized variation of reconstructed images in one framework. The PICTGV method is based on structure correlations among images in the energy domain and high-quality images to guide the reconstruction of energy-specific images. In PICTGV method, the high-quality image is reconstructed from all detector-collected X-ray signals and is referred as the broad-spectrum image. Distinctmore » from the existing reconstruction methods applied on the images with first order derivative, the higher order derivative of the images is incorporated into the PICTGV method. An alternating optimization algorithm is used to minimize the PICTGV objective function. We evaluate the performance of PICTGV on noise and artifacts suppressing using phantom studies and compare the method with the conventional filtered back-projection method as well as TGV based method without prior image. Results: On the digital phantom, the proposed method outperforms the existing TGV method in terms of the noise reduction, artifacts suppression, and edge detail preservation. Compared to that obtained by the TGV based method without prior image, the relative root mean square error in the images reconstructed by the proposed method is reduced by over 20%. Conclusion: The authors propose an iterative reconstruction via prior image constrained total generalize variation for spectral CT. Also, we have developed an alternating optimization algorithm and numerically demonstrated the merits of our approach. Results show that the proposed PICTGV method outperforms the TGV method for spectral CT.« less

Penalized weighted least-squares approach for low-dose x-ray computed tomography

NASA Astrophysics Data System (ADS)

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

2006-03-01

The noise of low-dose computed tomography (CT) sinogram follows approximately a Gaussian distribution with nonlinear dependence between the sample mean and variance. The noise is statistically uncorrelated among detector bins at any view angle. However the correlation coefficient matrix of data signal indicates a strong signal correlation among neighboring views. Based on above observations, Karhunen-Loeve (KL) transform can be used to de-correlate the signal among the neighboring views. In each KL component, a penalized weighted least-squares (PWLS) objective function can be constructed and optimal sinogram can be estimated by minimizing the objective function, followed by filtered backprojection (FBP) for CT image reconstruction. In this work, we compared the KL-PWLS method with an iterative image reconstruction algorithm, which uses the Gauss-Seidel iterative calculation to minimize the PWLS objective function in image domain. We also compared the KL-PWLS with an iterative sinogram smoothing algorithm, which uses the iterated conditional mode calculation to minimize the PWLS objective function in sinogram space, followed by FBP for image reconstruction. Phantom experiments show a comparable performance of these three PWLS methods in suppressing the noise-induced artifacts and preserving resolution in reconstructed images. Computer simulation concurs with the phantom experiments in terms of noise-resolution tradeoff and detectability in low contrast environment. The KL-PWLS noise reduction may have the advantage in computation for low-dose CT imaging, especially for dynamic high-resolution studies.

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%.

Iterative nonlinear joint transform correlation for the detection of objects in cluttered scenes

NASA Astrophysics Data System (ADS)

Haist, Tobias; Tiziani, Hans J.

1999-03-01

An iterative correlation technique with digital image processing in the feedback loop for the detection of small objects in cluttered scenes is proposed. A scanning aperture is combined with the method in order to improve the immunity against noise and clutter. Multiple reference objects or different views of one object are processed in parallel. We demonstrate the method by detecting a noisy and distorted face in a crowd with a nonlinear joint transform correlator.

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.

Correlating the ground truth of mammographic histology with the success or failure of imaging.

PubMed

Tot, Tibor

2005-02-01

Detailed and systematic mammographic-pathologic correlation is essential for evaluation of the advantages and disadvantages of mammography as an imaging method as well as for establishing the role of additional methods or alternatives. Two- and three-dimensional large section histopathology represents an ideal tool for this correlation. This kind of interdisciplinary approach ("mammographic histology") is slowly but irrevocably becoming accepted as the new golden standard in diagnosing breast abnormalities. In this review, upon summarizing the theoretical background and our practical experience in routine diagnostic use of these advantageous techniques, we report on the accuracy of the preoperative radiological diagnosis. As compared to the final diagnostic outcome, stellate lesions on the mammogram and microcalcifications of casting type indicate malignancy with very high accuracy while predicting malignancy in cases of powdery and crushed stone type microcalcifications is problematic. The extent of the disease is regularly underestimated on the mammogram by the radiologist. Combining different radiological signs, and comparing repeated static images taken in regular intervals in screening or postoperative follow-up, the mammographer may type and grade the lesions properly in a considerable number of cases. Regular mammographic-pathologic correlation may increase the specificity and sensitivity of mammographic diagnosis. This correlation is essential for establishing the proper pre- and postoperative histological diagnosis, too.

Gradient-Modulated SWIFT

PubMed Central

Zhang, Jinjin; Idiyatullin, Djaudat; Corum, Curtis A.; Kobayashi, Naoharu; Garwood, Michael

2017-01-01

Purpose Methods designed to image fast-relaxing spins, such as sweep imaging with Fourier transformation (SWIFT), often utilize high excitation bandwidth and duty cycle, and in some applications the optimal flip angle cannot be used without exceeding safe specific absorption rate (SAR) levels. The aim is to reduce SAR and increase the flexibility of SWIFT by applying time-varying gradient-modulation (GM). The modified sequence is called GM-SWIFT. Theory and Methods The method known as gradient-modulated offset independent adiabaticity was used to modulate the radiofrequency (RF) pulse and gradients. An expanded correlation algorithm was developed for GM-SWIFT to correct the phase and scale effects. Simulations and phantom and in vivo human experiments were performed to verify the correlation algorithm and to evaluate imaging performance. Results GM-SWIFT reduces SAR, RF amplitude, and acquisition time by up to 90%, 70%, and 45%, respectively, while maintaining image quality. The choice of GM parameter influences the lower limit of short T2* sensitivity, which can be exploited to suppress unwanted image haze from unresolvable ultrashort T2* signals originating from plastic materials in the coil housing and fixatives. Conclusions GM-SWIFT reduces peak and total RF power requirements and provides additional flexibility for optimizing SAR, RF amplitude, scan time, and image quality. PMID:25800547

Mapping biomass for a northern forest ecosystem using multi-frequency SAR data

NASA Technical Reports Server (NTRS)

Ranson, K. J.; Sun, Guoqing

1992-01-01

Image processing methods for mapping standing biomass for a forest in Maine, using NASA/JPL airborne synthetic aperture radar (AIRSAR) polarimeter data, are presented. By examining the dependence of backscattering on standing biomass, it is determined that the ratio of HV backscattering from a longer wavelength (P- or L-band) to a shorter wavelength (C) is a good combination for mapping total biomass. This ratio enhances the correlation of the image signature to the standing biomass and compensates for a major part of the variations in backscattering attributed to radar incidence angle. The image processing methods used include image calibration, ratioing, filtering, and segmentation. The image segmentation algorithm uses both means and variances of the image, and it is combined with the image filtering process. Preliminary assessment of the resultant biomass maps suggests that this is a promising method.

Accurate and fiducial-marker-free correction for three-dimensional chromatic shift in biological fluorescence microscopy.

PubMed

Matsuda, Atsushi; Schermelleh, Lothar; Hirano, Yasuhiro; Haraguchi, Tokuko; Hiraoka, Yasushi

2018-05-15

Correction of chromatic shift is necessary for precise registration of multicolor fluorescence images of biological specimens. New emerging technologies in fluorescence microscopy with increasing spatial resolution and penetration depth have prompted the need for more accurate methods to correct chromatic aberration. However, the amount of chromatic shift of the region of interest in biological samples often deviates from the theoretical prediction because of unknown dispersion in the biological samples. To measure and correct chromatic shift in biological samples, we developed a quadrisection phase correlation approach to computationally calculate translation, rotation, and magnification from reference images. Furthermore, to account for local chromatic shifts, images are split into smaller elements, for which the phase correlation between channels is measured individually and corrected accordingly. We implemented this method in an easy-to-use open-source software package, called Chromagnon, that is able to correct shifts with a 3D accuracy of approximately 15 nm. Applying this software, we quantified the level of uncertainty in chromatic shift correction, depending on the imaging modality used, and for different existing calibration methods, along with the proposed one. Finally, we provide guidelines to choose the optimal chromatic shift registration method for any given situation.

a method of gravity and seismic sequential inversion and its GPU implementation

NASA Astrophysics Data System (ADS)

Liu, G.; Meng, X.

2011-12-01

In this abstract, we introduce a gravity and seismic sequential inversion method to invert for density and velocity together. For the gravity inversion, we use an iterative method based on correlation imaging algorithm; for the seismic inversion, we use the full waveform inversion. The link between the density and velocity is an empirical formula called Gardner equation, for large volumes of data, we use the GPU to accelerate the computation. For the gravity inversion method , we introduce a method based on correlation imaging algorithm,it is also a interative method, first we calculate the correlation imaging of the observed gravity anomaly, it is some value between -1 and +1, then we multiply this value with a little density ,this value become the initial density model. We get a forward reuslt with this initial model and also calculate the correaltion imaging of the misfit of observed data and the forward data, also multiply the correaltion imaging result a little density and add it to the initial model, then do the same procedure above , at last ,we can get a inversion density model. For the seismic inveron method ,we use a mothod base on the linearity of acoustic wave equation written in the frequency domain,with a intial velociy model, we can get a good velocity result. In the sequential inversion of gravity and seismic , we need a link formula to convert between density and velocity ,in our method , we use the Gardner equation. Driven by the insatiable market demand for real time, high-definition 3D images, the programmable NVIDIA Graphic Processing Unit (GPU) as co-processor of CPU has been developed for high performance computing. Compute Unified Device Architecture (CUDA) is a parallel programming model and software environment provided by NVIDIA designed to overcome the challenge of using traditional general purpose GPU while maintaining a low learn curve for programmers familiar with standard programming languages such as C. In our inversion processing, we use the GPU to accelerate our gravity and seismic inversion. Taking the gravity inversion as an example, its kernels are gravity forward simulation and correlation imaging, after the parallelization in GPU, in 3D case,the inversion module, the original five CPU loops are reduced to three,the forward module the original five CPU loops are reduced to two. Acknowledgments We acknowledge the financial support of Sinoprobe project (201011039 and 201011049-03), the Fundamental Research Funds for the Central Universities (2010ZY26 and 2011PY0183), the National Natural Science Foundation of China (41074095) and the Open Project of State Key Laboratory of Geological Processes and Mineral Resources (GPMR0945).

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.

Digital pathology: elementary, rapid and reliable automated image analysis.

PubMed

Bouzin, Caroline; Saini, Monika L; Khaing, Kyi-Kyi; Ambroise, Jérôme; Marbaix, Etienne; Grégoire, Vincent; Bol, Vanesa

2016-05-01

Slide digitalization has brought pathology to a new era, including powerful image analysis possibilities. However, while being a powerful prognostic tool, immunostaining automated analysis on digital images is still not implemented worldwide in routine clinical practice. Digitalized biopsy sections from two independent cohorts of patients, immunostained for membrane or nuclear markers, were quantified with two automated methods. The first was based on stained cell counting through tissue segmentation, while the second relied upon stained area proportion within tissue sections. Different steps of image preparation, such as automated tissue detection, folds exclusion and scanning magnification, were also assessed and validated. Quantification of either stained cells or the stained area was found to be correlated highly for all tested markers. Both methods were also correlated with visual scoring performed by a pathologist. For an equivalent reliability, quantification of the stained area is, however, faster and easier to fine-tune and is therefore more compatible with time constraints for prognosis. This work provides an incentive for the implementation of automated immunostaining analysis with a stained area method in routine laboratory practice. © 2015 John Wiley & Sons Ltd.

Bilateral filtering using the full noise covariance matrix applied to x-ray phase-contrast computed tomography.

PubMed

Allner, S; Koehler, T; Fehringer, A; Birnbacher, L; Willner, M; Pfeiffer, F; Noël, P B

2016-05-21

The purpose of this work is to develop an image-based de-noising algorithm that exploits complementary information and noise statistics from multi-modal images, as they emerge in x-ray tomography techniques, for instance grating-based phase-contrast CT and spectral CT. Among the noise reduction methods, image-based de-noising is one popular approach and the so-called bilateral filter is a well known algorithm for edge-preserving filtering. We developed a generalization of the bilateral filter for the case where the imaging system provides two or more perfectly aligned images. The proposed generalization is statistically motivated and takes the full second order noise statistics of these images into account. In particular, it includes a noise correlation between the images and spatial noise correlation within the same image. The novel generalized three-dimensional bilateral filter is applied to the attenuation and phase images created with filtered backprojection reconstructions from grating-based phase-contrast tomography. In comparison to established bilateral filters, we obtain improved noise reduction and at the same time a better preservation of edges in the images on the examples of a simulated soft-tissue phantom, a human cerebellum and a human artery sample. The applied full noise covariance is determined via cross-correlation of the image noise. The filter results yield an improved feature recovery based on enhanced noise suppression and edge preservation as shown here on the example of attenuation and phase images captured with grating-based phase-contrast computed tomography. This is supported by quantitative image analysis. Without being bound to phase-contrast imaging, this generalized filter is applicable to any kind of noise-afflicted image data with or without noise correlation. Therefore, it can be utilized in various imaging applications and fields.

SU-F-J-77: Variations in the Displacement Vector Fields Calculated by Different Deformable Image Registration Algorithms Used in Helical, Axial and Cone-Beam CT Images of a Mobile

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

Ali, I; Jaskowiak, J; Ahmad, S

Purpose: To investigate quantitatively the displacement-vector-fields (DVF) obtained from different deformable image registration algorithms (DIR) in helical (HCT), axial (ACT) and cone-beam CT (CBCT) to register CT images of a mobile phantom and its correlation with motion amplitudes and frequencies. Methods: HCT, ACT and CBCT are used to image a mobile phantom which includes three targets with different sizes that are manufactured from water-equivalent material and embedded in low density foam. The phantom is moved with controlled motion patterns where a range of motion amplitudes (0–40mm) and frequencies (0.125–0.5Hz) are used. The CT images obtained from scanning of the mobilemore » phantom are registered with the stationary CT-images using four deformable image registration algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from DIRART software. Results: The DVF calculated by the different algorithms correlate well with the motion amplitudes that are applied on the mobile phantom where maximal DVF increase linearly with the motion amplitudes of the mobile phantom in CBCT. Similarly in HCT, DVF increase linearly with motion amplitude, however, its correlation is weaker than CBCT. In ACT, the DVF’s do not correlate well with the motion amplitudes where motion induces strong image artifacts and DIR algorithms are not able to deform the ACT image of the mobile targets to the stationary targets. Three DIR-algorithms produce comparable values and patterns of the DVF for certain CT imaging modality. However, DVF from fast-demons deviated strongly from other algorithms at large motion amplitudes. Conclusion: In CBCT and HCT, the DVF correlate well with the motion amplitude of the mobile phantom. However, in ACT, DVF do not correlate with motion amplitudes. Correlations of DVF with motion amplitude as in CBCT and HCT imaging techniques can provide information about unknown motion parameters of the mobile organs in real patients as demonstrated in this phantom visibility study.« less

SU-E-J-112: The Impact of Cine EPID Image Acquisition Frame Rate On Markerless Soft-Tissue Tracking

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

Yip, S; Rottmann, J; Berbeco, R

2014-06-01

Purpose: Although reduction of the cine EPID acquisition frame rate through multiple frame averaging may reduce hardware memory burden and decrease image noise, it can hinder the continuity of soft-tissue motion leading to poor auto-tracking results. The impact of motion blurring and image noise on the tracking performance was investigated. Methods: Phantom and patient images were acquired at a frame rate of 12.87Hz on an AS1000 portal imager. Low frame rate images were obtained by continuous frame averaging. A previously validated tracking algorithm was employed for auto-tracking. The difference between the programmed and auto-tracked positions of a Las Vegas phantommore » moving in the superior-inferior direction defined the tracking error (δ). Motion blurring was assessed by measuring the area change of the circle with the greatest depth. Additionally, lung tumors on 1747 frames acquired at eleven field angles from four radiotherapy patients are manually and automatically tracked with varying frame averaging. δ was defined by the position difference of the two tracking methods. Image noise was defined as the standard deviation of the background intensity. Motion blurring and image noise were correlated with δ using Pearson correlation coefficient (R). Results: For both phantom and patient studies, the auto-tracking errors increased at frame rates lower than 4.29Hz. Above 4.29Hz, changes in errors were negligible with δ<1.60mm. Motion blurring and image noise were observed to increase and decrease with frame averaging, respectively. Motion blurring and tracking errors were significantly correlated for the phantom (R=0.94) and patient studies (R=0.72). Moderate to poor correlation was found between image noise and tracking error with R -0.58 and -0.19 for both studies, respectively. Conclusion: An image acquisition frame rate of at least 4.29Hz is recommended for cine EPID tracking. Motion blurring in images with frame rates below 4.39Hz can substantially reduce the accuracy of auto-tracking. This work is supported in part by the Varian Medical Systems, Inc.« less

Assessment of functional liver reserve: old and new in 99mTc-sulfur colloid scintigraphy.

PubMed

Matesan, Manuela M; Bowen, Stephen R; Chapman, Tobias R; Miyaoka, Robert S; Velez, James W; Wanner, Michele F; Nyflot, Matthew J; Apisarnthanarax, Smith; Vesselle, Hubert J

2017-07-01

A semiquantitative assessment of hepatic reticuloendothelial system function using colloidal particles scintigraphy has been proposed previously as a surrogate for liver function evaluation. In this article, we present an updated method for the overall assessment of technetium-99m (Tc)-sulfur colloid (SC) biodistribution that combines information from planar and attenuation-corrected Tc-SC single-photon emission computed tomography (SPECT) images. The imaging protocol described here was developed as an easy-to-implement method to assess overall and regional liver function changes associated with chronic liver disease. Thirty patients with chronic liver disease and primary liver cancers underwent Tc-SC whole-body planar imaging and upper-abdomen SPECT/computed tomography (CT) imaging before external beam radiation therapy. Liver plus spleen and bone marrow counts as a fraction of whole-body total counts were calculated from SC planar imaging. Attenuation correction Tc-SC images were rigidly coregistered with treatment planning CT images that contained liver and spleen regions-of-interest. Ratios of total liver counts to total spleen counts were obtained from the aligned Tc-SC SPECT and CT images, and were subsequently used to separate liver plus spleen counts obtained on the planar images. This hybrid SPECT/CT and planar scintigraphy approach yielded an updated estimation of whole-body SC distribution. These biodistribution estimates were compared with historical data for reference. Statistical associations of Tc-SC biodistribution to liver function parameters and liver disease scoring systems (Child-Pugh) were evaluated by Spearman rank correlation. Percentages of Tc-SC uptake ranged from 19.3 to 77.3% for the liver; 3.4 to 40.7% for the spleen; and 19.0 to 56.7% for the bone marrow. Spearman's correlation coefficient showed a significant statistical association between Child-Pugh score and bone marrow uptake at 0.55 (P≤0.05), liver uptake at 0.71 (P≤0.001), spleen uptake at 0.56 (P≤0.05), and spleen plus bone marrow uptake at 0.71 (P≤0.001). There was also a good correlation of SC uptake percentages with individual quantitative liver function components such as albumin and total bilirubin, and qualitative liver function components (varices, portal hypertension, ascites). For albumin: r=0.64 (P<0.001) compared with liver uptake percentage from the whole-body counts, r=0.49 (P<0.001) compared with splenic uptake percentage, and r=0.45 (P≤0.05) compared with bone marrow uptake percentage. We describe a novel liver function quantitative assessment method that combines whole-body planar images and SPECT/CT attenuation-corrected images of Tc-SC distribution. Attenuation-corrected SC images provide valuable regional liver function information, which is a unique feature compared with other imaging methods available. The results of our study indicate that the Tc-SC uptake by the liver, spleen, and bone marrow correlates with liver function parameters in patients with diffuse liver disease and the correlation with liver disease severity is slightly better for liver uptake percentages than for individual values of bone marrow and spleen uptake percentages.

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.

Assessment of β-zone peripapillary atrophy by optical coherence tomography and scanning laser ophthalmoscopy imaging in glaucoma patients

PubMed Central

Seidensticker, Florian; Reznicek, Lukas; Mann, Thomas; Hübert, Irene; Kampik, Anselm; Ulbig, Michael; Hirneiss, Christoph; Neubauer, Aljoscha S; Kernt, Marcus

2014-01-01

Purpose To assess β-zone peripapillary atrophy (β-PPA) using spectral domain optical coherence tomography (SD-OCT), scanning laser ophthalmoscopy (SLO), and fundus auto-fluorescence (FAF) imaging in patients with primary open-angle glaucoma with advanced glaucomatous visual field defects. Methods A consecutive, prospective series of 82 study eyes with primary open-angle glaucoma were included in this study. All study participants underwent a full ophthalmic examination followed by SD-OCT, wide-field SLO, and FAF imaging of the optic nerve head and the peripapillary region. Results Eighty-four glaucomatous eyes were included in our prospective study. Correlation analyses for horizontally and vertically obtained β-PPA for all three imaging modalities (color SLO, FAF, and SD-OCT) revealed highest correlations between FAF and color SLO (Pearson correlation coefficient: 0.904 [P<0.001] for horizontal β-PPA and 0.786 [P<0.001] for vertical β-PPA). Bland–Altman plotting revealed highest agreements between color SLO and FAF, with −2.1 pixels ±1.96 standard deviation (SD) for horizontal β-PPA, SD: 10.5 pixels and 2.4 pixels ±1.96 SD for vertical β-PPA. Conclusion β-PPA can be assessed using en-face SLO and cross-sectional SD-OCT imaging. Correlation analyses revealed highest correlations between color SLO and FAF imaging, while correlations between SLO and SD-OCT were weak. A more precise structural definition of β-PPA is needed. PMID:25061270

Evaluation of random errors in Williams’ series coefficients obtained with digital image correlation

NASA Astrophysics Data System (ADS)

Lychak, Oleh V.; Holyns'kiy, Ivan S.

2016-03-01

The use of the Williams’ series parameters for fracture analysis requires valid information about their error values. The aim of this investigation is the development of the method for estimation of the standard deviation of random errors of the Williams’ series parameters, obtained from the measured components of the stress field. Also, the criteria for choosing the optimal number of terms in the truncated Williams’ series for derivation of their parameters with minimal errors is proposed. The method was used for the evaluation of the Williams’ parameters, obtained from the data, and measured by the digital image correlation technique for testing a three-point bending specimen.

Marine Targets Classification in PolInSAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong; Ren, Lin

2014-11-01

In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then, A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

Marine Targets Classification in PolInSAR Data

NASA Astrophysics Data System (ADS)

Chen, Peng; Yang, Jingsong; Ren, Lin

2014-11-01

In this paper, marine stationary targets and moving targets are studied by Pol-In-SAR data of Radarsat-2. A new method of stationary targets detection is proposed. The method get the correlation coefficient image of the In-SAR data, and using the histogram of correlation coefficient image. Then , A Constant False Alarm Rate (CFAR) algorithm and The Probabilistic Neural Network model are imported to detect stationary targets. To find the moving targets, Azimuth Ambiguity is show as an important feature. We use the length of azimuth ambiguity to get the target's moving direction and speed. Make further efforts, Targets classification is studied by rebuild the surface elevation of marine targets.

Remote sensing of drought and salinity stressed turfgrass

NASA Astrophysics Data System (ADS)

Ikemura, Yoshiaki

The ability to detect early signs of stress in turfgrass stands using a rapid, inexpensive, and nondestructive method would be a valuable management tool. Studies were conducted to determine if digital image analysis and spectroradiometric readings obtained from drought- and salinity-stressed turfgrasses accurately reflected the varying degrees of stress and correlated strongly with visual ratings, relative water content (RWC) and leaf osmolality, standard methods for measuring stress in plants. Greenhouse drought and salinity experiments were conducted on hybrid bluegrass [Poa arachnifera (Torn.) x pratensis (L.)] cv. Reveille and bermudagrass [Cynodon dactylon (L.)] cv. Princess 77. Increasing drought and salinity stress led to decreased RWC, increased leaf osmolality, and decreased visual ratings for both species. Percent green cover and hue values obtained from digital image analysis, and Normalized Difference Vegetation Index (NDVI), calculated from spectroradiometric readings, were moderately to highly correlated with visual ratings, RWC, and leaf osmolality. Similarly, in a field validation study conducted on hybrid bluegrass, spectral reflectance ratios were moderately to highly correlated with visual ratings. In addition, percent green cover obtained from digital image analysis was strongly correlated with most of the spectral ratios, particularly the ratio of fluorescence peaks (r = -0.88 to -0.99), modified triangular vegetation index (MTVI) (r = 0.82 to 0.98), and NDVI (r = 0.84 to 0.99), suggesting that spectral reflectance and digital image analysis are equally effective at detecting changes in color brought on by stress. The two methods differed in their ability to distinguish between drought salinity stress. Hue values obtained from digital image analysis responded differently to increasing drought stress than to increasing salinity stress. Whereas the onset of drought stress was reflected by increased hue values followed by a decrease in values as drought stress increased, there was no increase in hue values at the onset of salinity stress. Thus, changes in hue could be a key to distinguish drought and salinity stress. Both digital image analysis and spectroradiometry effectively detected drought and salinity stress and may have applications in turfgrass management as rapid and quantitative methods to determine drought and salinity stress in turf.

Developing and Evaluating a Target-Background Similarity Metric for Camouflage Detection

PubMed Central

Lin, Chiuhsiang Joe; Chang, Chi-Chan; Liu, Bor-Shong

2014-01-01

Background Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. Methodology In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. Significance The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results. PMID:24498310

The study on the parallel processing based time series correlation analysis of RBC membrane flickering in quantitative phase imaging

NASA Astrophysics Data System (ADS)

Lee, Minsuk; Won, Youngjae; Park, Byungjun; Lee, Seungrag

2017-02-01

Not only static characteristics but also dynamic characteristics of the red blood cell (RBC) contains useful information for the blood diagnosis. Quantitative phase imaging (QPI) can capture sample images with subnanometer scale depth resolution and millisecond scale temporal resolution. Various researches have been used QPI for the RBC diagnosis, and recently many researches has been developed to decrease the process time of RBC information extraction using QPI by the parallel computing algorithm, however previous studies are interested in the static parameters such as morphology of the cells or simple dynamic parameters such as root mean square (RMS) of the membrane fluctuations. Previously, we presented a practical blood test method using the time series correlation analysis of RBC membrane flickering with QPI. However, this method has shown that there is a limit to the clinical application because of the long computation time. In this study, we present an accelerated time series correlation analysis of RBC membrane flickering using the parallel computing algorithm. This method showed consistent fractal scaling exponent results of the surrounding medium and the normal RBC with our previous research.

Full-direct method for imaging pharmacokinetic parameters in dynamic fluorescence molecular tomography

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

Zhang, Guanglei, E-mail: guangleizhang@bjtu.edu.cn; Department of Biomedical Engineering, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044; Pu, Huangsheng

2015-02-23

Images of pharmacokinetic parameters (also known as parametric images) in dynamic fluorescence molecular tomography (FMT) can provide three-dimensional metabolic information for biological studies and drug development. However, the ill-posed nature of FMT and the high temporal variation of fluorophore concentration together make it difficult to obtain accurate parametric images in small animals in vivo. In this letter, we present a method to directly reconstruct the parametric images from the boundary measurements based on hybrid FMT/X-ray computed tomography (XCT) system. This method can not only utilize structural priors obtained from the XCT system to mitigate the ill-posedness of FMT but alsomore » make full use of the temporal correlations of boundary measurements to model the high temporal variation of fluorophore concentration. The results of numerical simulation and mouse experiment demonstrate that the proposed method leads to significant improvements in the reconstruction quality of parametric images.« less

Can multi-slice or navigator-gated R2* MRI replace single-slice breath-hold acquisition for hepatic iron quantification?

PubMed

Loeffler, Ralf B; McCarville, M Beth; Wagstaff, Anne W; Smeltzer, Matthew P; Krafft, Axel J; Song, Ruitian; Hankins, Jane S; Hillenbrand, Claudia M

2017-01-01

Liver R2* values calculated from multi-gradient echo (mGRE) magnetic resonance images (MRI) are strongly correlated with hepatic iron concentration (HIC) as shown in several independently derived biopsy calibration studies. These calibrations were established for axial single-slice breath-hold imaging at the location of the portal vein. Scanning in multi-slice mode makes the exam more efficient, since whole-liver coverage can be achieved with two breath-holds and the optimal slice can be selected afterward. Navigator echoes remove the need for breath-holds and allow use in sedated patients. To evaluate if the existing biopsy calibrations can be applied to multi-slice and navigator-controlled mGRE imaging in children with hepatic iron overload, by testing if there is a bias-free correlation between single-slice R2* and multi-slice or multi-slice navigator controlled R2*. This study included MRI data from 71 patients with transfusional iron overload, who received an MRI exam to estimate HIC using gradient echo sequences. Patient scans contained 2 or 3 of the following imaging methods used for analysis: single-slice images (n = 71), multi-slice images (n = 69) and navigator-controlled images (n = 17). Small and large blood corrected region of interests were selected on axial images of the liver to obtain R2* values for all data sets. Bland-Altman and linear regression analysis were used to compare R2* values from single-slice images to those of multi-slice images and navigator-controlled images. Bland-Altman analysis showed that all imaging method comparisons were strongly associated with each other and had high correlation coefficients (0.98 ≤ r ≤ 1.00) with P-values ≤0.0001. Linear regression yielded slopes that were close to 1. We found that navigator-gated or breath-held multi-slice R2* MRI for HIC determination measures R2* values comparable to the biopsy-validated single-slice, single breath-hold scan. We conclude that these three R2* methods can be interchangeably used in existing R2*-HIC calibrations.

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 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.

Mapping soil deformation around plant roots using in vivo 4D X-ray Computed Tomography and Digital Volume Correlation.

PubMed

Keyes, S D; Gillard, F; Soper, N; Mavrogordato, M N; Sinclair, I; Roose, T

2016-06-14

The mechanical impedance of soils inhibits the growth of plant roots, often being the most significant physical limitation to root system development. Non-invasive imaging techniques have recently been used to investigate the development of root system architecture over time, but the relationship with soil deformation is usually neglected. Correlative mapping approaches parameterised using 2D and 3D image data have recently gained prominence for quantifying physical deformation in composite materials including fibre-reinforced polymers and trabecular bone. Digital Image Correlation (DIC) and Digital Volume Correlation (DVC) are computational techniques which use the inherent material texture of surfaces and volumes, captured using imaging techniques, to map full-field deformation components in samples during physical loading. Here we develop an experimental assay and methodology for four-dimensional, in vivo X-ray Computed Tomography (XCT) and apply a Digital Volume Correlation (DVC) approach to the data to quantify deformation. The method is validated for a field-derived soil under conditions of uniaxial compression, and a calibration study is used to quantify thresholds of displacement and strain measurement. The validated and calibrated approach is then demonstrated for an in vivo test case in which an extending maize root in field-derived soil was imaged hourly using XCT over a growth period of 19h. This allowed full-field soil deformation data and 3D root tip dynamics to be quantified in parallel for the first time. This fusion of methods paves the way for comparative studies of contrasting soils and plant genotypes, improving our understanding of the fundamental mechanical processes which influence root system development. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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

Single-pixel imaging by Hadamard transform and its application for hyperspectral imaging

NASA Astrophysics Data System (ADS)

Mizutani, Yasuhiro; Shibuya, Kyuki; Taguchi, Hiroki; Iwata, Tetsuo; Takaya, Yasuhiro; Yasui, Takeshi

2016-10-01

In this paper, we report on comparisons of single-pixel imagings using Hadamard Transform (HT) and the ghost imaging (GI) in the view point of the visibility under weak light conditions. For comparing the two methods, we have discussed about qualities of images based on experimental results and numerical analysis. To detect images by the TH method, we have illuminated the Hadamard-pattern mask and calculated by orthogonal transform. On the other hand, the GH method can detect images by illuminating random patterns and a correlation measurement. For comparing two methods under weak light intensity, we have controlled illuminated intensities of a DMD projector about 0.1 in signal-to-noise ratio. Though a process speed of the HT image was faster then an image via the GI, the GI method has an advantage of detection under weak light condition. An essential difference between the HT and the GI method is discussed about reconstruction process. Finally, we also show a typical application of the single-pixel imaging such as hyperspectral images by using dual-optical frequency combs. An optical setup consists of two fiber lasers, spatial light modulated for generating patten illumination, and a single pixel detector. We are successful to detect hyperspectrul images in a range from 1545 to 1555 nm at 0.01nm resolution.

X-ray phase contrast tomography by tracking near field speckle

PubMed Central

Wang, Hongchang; Berujon, Sebastien; Herzen, Julia; Atwood, Robert; Laundy, David; Hipp, Alexander; Sawhney, Kawal

2015-01-01

X-ray imaging techniques that capture variations in the x-ray phase can yield higher contrast images with lower x-ray dose than is possible with conventional absorption radiography. However, the extraction of phase information is often more difficult than the extraction of absorption information and requires a more sophisticated experimental arrangement. We here report a method for three-dimensional (3D) X-ray phase contrast computed tomography (CT) which gives quantitative volumetric information on the real part of the refractive index. The method is based on the recently developed X-ray speckle tracking technique in which the displacement of near field speckle is tracked using a digital image correlation algorithm. In addition to differential phase contrast projection images, the method allows the dark-field images to be simultaneously extracted. After reconstruction, compared to conventional absorption CT images, the 3D phase CT images show greatly enhanced contrast. This new imaging method has advantages compared to other X-ray imaging methods in simplicity of experimental arrangement, speed of measurement and relative insensitivity to beam movements. These features make the technique an attractive candidate for material imaging such as in-vivo imaging of biological systems containing soft tissue. PMID:25735237

A novel spinal kinematic analysis using X-ray imaging and vicon motion analysis: a case study.

PubMed

Noh, Dong K; Lee, Nam G; You, Joshua H

2014-01-01

This study highlights a novel spinal kinematic analysis method and the feasibility of X-ray imaging measurements to accurately assess thoracic spine motion. The advanced X-ray Nash-Moe method and analysis were used to compute the segmental range of motion in thoracic vertebra pedicles in vivo. This Nash-Moe X-ray imaging method was compared with a standardized method using the Vicon 3-dimensional motion capture system. Linear regression analysis showed an excellent and significant correlation between the two methods (R2 = 0.99, p < 0.05), suggesting that the analysis of spinal segmental range of motion using X-ray imaging measurements was accurate and comparable to the conventional 3-dimensional motion analysis system. Clinically, this novel finding is compelling evidence demonstrating that measurements with X-ray imaging are useful to accurately decipher pathological spinal alignment and movement impairments in idiopathic scoliosis (IS).

A multispectral photon-counting double random phase encoding scheme for image authentication.

PubMed

Yi, Faliu; Moon, Inkyu; Lee, Yeon H

2014-05-20

In this paper, we propose a new method for color image-based authentication that combines multispectral photon-counting imaging (MPCI) and double random phase encoding (DRPE) schemes. The sparsely distributed information from MPCI and the stationary white noise signal from DRPE make intruder attacks difficult. In this authentication method, the original multispectral RGB color image is down-sampled into a Bayer image. The three types of color samples (red, green and blue color) in the Bayer image are encrypted with DRPE and the amplitude part of the resulting image is photon counted. The corresponding phase information that has nonzero amplitude after photon counting is then kept for decryption. Experimental results show that the retrieved images from the proposed method do not visually resemble their original counterparts. Nevertheless, the original color image can be efficiently verified with statistical nonlinear correlations. Our experimental results also show that different interpolation algorithms applied to Bayer images result in different verification effects for multispectral RGB color images.

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

Advantages of indium-tin oxide-coated glass slides in correlative scanning electron microscopy applications of uncoated cultured cells.

PubMed

Pluk, H; Stokes, D J; Lich, B; Wieringa, B; Fransen, J

2009-03-01

A method of direct visualization by correlative scanning electron microscopy (SEM) and fluorescence light microscopy of cell structures of tissue cultured cells grown on conductive glass slides is described. We show that by growing cells on indium-tin oxide (ITO)-coated glass slides, secondary electron (SE) and backscatter electron (BSE) images of uncoated cells can be obtained in high-vacuum SEM without charging artefacts. Interestingly, we observed that BSE imaging is influenced by both accelerating voltage and ITO coating thickness. By combining SE and BSE imaging with fluorescence light microscopy imaging, we were able to reveal detailed features of actin cytoskeletal and mitochondrial structures in mouse embryonic fibroblasts. We propose that the application of ITO glass as a substrate for cell culture can easily be extended and offers new opportunities for correlative light and electron microscopy studies of adherently growing cells.

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.

Carbon nanotube based respiratory gated micro-CT imaging of a murine model of lung tumors with optical imaging correlation

NASA Astrophysics Data System (ADS)

Burk, Laurel M.; Lee, Yueh Z.; Heathcote, Samuel; Wang, Ko-han; Kim, William Y.; Lu, Jianping; Zhou, Otto

2011-03-01

Current optical imaging techniques can successfully measure tumor load in murine models of lung carcinoma but lack structural detail. We demonstrate that respiratory gated micro-CT imaging of such models gives information about structure and correlates with tumor load measurements by optical methods. Four mice with multifocal, Kras-induced tumors expressing firefly luciferase were imaged against four controls using both optical imaging and respiratory gated micro-CT. CT images of anesthetized animals were acquired with a custom CNT-based system using 30 ms x-ray pulses during peak inspiration; respiration motion was tracked with a pressure sensor beneath each animal's abdomen. Optical imaging based on the Luc+ signal correlating with tumor load was performed on a Xenogen IVIS Kinetix. Micro-CT images were post-processed using Osirix, measuring lung volume with region growing. Diameters of the largest three tumors were measured. Relationships between tumor size, lung volumes, and optical signal were compared. CT images and optical signals were obtained for all animals at two time points. In all lobes of the Kras+ mice in all images, tumors were visible; the smallest to be readily identified measured approximately 300 microns diameter. CT-derived tumor volumes and optical signals related linearly, with r=0.94 for all animals. When derived for only tumor bearing animals, r=0.3. The trend of each individual animal's optical signal tracked correctly based on the CT volumes. Interestingly, lung volumes also correlated positively with optical imaging data and tumor volume burden, suggesting active remodeling.

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.

The Correlation Between a Short-term Conventional Electroencephalography in the First Day of Life and Brain Magnetic Resonance Imaging in Newborns Undergoing Hypothermia for Hypoxic-Ischemic Encephalopathy.

PubMed

Obeid, Rawad; Sogawa, Yoshimi; Gedela, Satyanarayana; Naik, Monica; Lee, Vince; Telesco, Richard; Wisnowski, Jessica; Magill, Christine; Painter, Michael J; Panigrahy, Ashok

2017-02-01

Electroencephalograph recorded in the first day of life in newborns treated with hypothermia for hypoxic-ischemic encephalopathy could be utilized as a predictive tool for the severity of brain injury on magnetic resonance imaging and mortality. We analyzed newborns who were admitted for therapeutic hypothermia due to hypoxic-ischemic encephalopathy. All enrolled infants underwent encephalography within the first 24 hours of life and underwent brain magnetic resonance imaging after rewarming. All encephalographs were independently reviewed for background amplitude, continuity, and variability. Brain injury determined by magnetic resonance imaging was scored using methods described by Bonifacio et al. Forty-one newborns were included in the study. Each encephalograph variable correlated significantly with the severity of injury on brain magnetic resonance imaging (P < 0.001 for each). The overall encephalograph severity estimated as mild, moderate, and severe also correlated with injury (P < 0.001). Each encephalograph variable correlated with mortality (P < 0.001 for each) and also the overall encephalograph severity (P < 0.001). Severity of electrographic findings on encephalograph in the first day of life during therapeutic hypothermia for hypoxic-ischemic encephalopathy correlated with the extent of injury on brain magnetic resonance imaging. This information may be useful for families and aid guide clinical decision making. Copyright © 2017 Elsevier Inc. All rights reserved.

Recovery of the sub-basal nerve plexus and superficial nerve terminals after corneal epithelial injury in mice.

PubMed

Downie, Laura E; Naranjo Golborne, Cecilia; Chen, Merry; Ho, Ngoc; Hoac, Cam; Liyanapathirana, Dasun; Luo, Carol; Wu, Ruo Bing; Chinnery, Holly R

2018-06-01

Our aim was to compare regeneration of the sub-basal nerve plexus (SBNP) and superficial nerve terminals (SNT) following corneal epithelial injury. We also sought to compare agreement when quantifying nerve parameters using different image analysis techniques. Anesthetized, female C57BL/6 mice received central 1-mm corneal epithelial abrasions. Four-weeks post-injury, eyes were enucleated and processed for PGP9.5 to visualize the corneal nerves using wholemount immunofluorescence staining and confocal microscopy. The percentage area of the SBNP and SNT were quantified using: ImageJ automated thresholds, ImageJ manual thresholds and manual tracings in NeuronJ. Nerve sum length was quantified using NeuronJ and Imaris. Agreement between methods was considered with Bland-Altman analyses. Four-weeks post-injury, the sum length of nerve fibers in the SBNP, but not the SNT, was reduced compared with naïve eyes. In the periphery, but not central cornea, of both naïve and injured eyes, nerve fiber lengths in the SBNP and SNT were strongly correlated. For quantifying SBNP nerve axon area, all image analysis methods were highly correlated. In the SNT, there was poor correlation between manual methods and auto-thresholding, with a trend towards underestimating nerve fiber area using auto-thresholding when higher proportions of nerve fibers were present. In conclusion, four weeks after superficial corneal injury, there is differential recovery of epithelial nerve axons; SBNP sum length is reduced, however the sum length of SNTs is similar to naïve eyes. Care should be taken when selecting image analysis methods to compare nerve parameters in different depths of the corneal epithelium due to differences in background autofluorescence. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Four-dimensional ultrasonography of the fetal heart using color Doppler spatiotemporal image correlation.

PubMed

Gonçalves, Luís F; Romero, Roberto; Espinoza, Jimmy; Lee, Wesley; Treadwell, Marjorie; Chintala, Kavitha; Brandl, Helmut; Chaiworapongsa, Tinnakorn

2004-04-01

To describe clinical and research applications of 4-dimensional imaging of the fetal heart using color Doppler spatiotemporal image correlation. Forty-four volume data sets were acquired by color Doppler spatiotemporal image correlation. Seven subjects were examined: 4 fetuses without abnormalities, 1 fetus with ventriculomegaly and a hypoplastic cerebellum but normal cardiac anatomy, and 2 fetuses with cardiac anomalies detected by fetal echocardiography (1 case of a ventricular septal defect associated with trisomy 21 and 1 case of a double-inlet right ventricle with a 46,XX karyotype). The median gestational age at the time of examination was 21 3/7 weeks (range, 19 5/7-34 0/7 weeks). Volume data sets were reviewed offline by multiplanar display and volume-rendering methods. Representative images and online video clips illustrating the diagnostic potential of this technology are presented. Color Doppler spatiotemporal image correlation allowed multiplanar visualization of ventricular septal defects, multiplanar display and volume rendering of tricuspid regurgitation, volume rendering of the outflow tracts by color and power Doppler ultrasonography (both in a normal case and in a case of a double-inlet right ventricle with a double-outlet right ventricle), and visualization of venous streams at the level of the foramen ovale. Color Doppler spatiotemporal image correlation has the potential to simplify visualization of the outflow tracts and improve the evaluation of the location and extent of ventricular septal defects. Other applications include 3-dimensional evaluation of regurgitation jets and venous streams at the level of the foramen ovale.

A flexible and robust approach for segmenting cell nuclei from 2D microscopy images using supervised learning and template matching

PubMed Central

Chen, Cheng; Wang, Wei; Ozolek, John A.; Rohde, Gustavo K.

2013-01-01

We describe a new supervised learning-based template matching approach for segmenting cell nuclei from microscopy images. The method uses examples selected by a user for building a statistical model which captures the texture and shape variations of the nuclear structures from a given dataset to be segmented. Segmentation of subsequent, unlabeled, images is then performed by finding the model instance that best matches (in the normalized cross correlation sense) local neighborhood in the input image. We demonstrate the application of our method to segmenting nuclei from a variety of imaging modalities, and quantitatively compare our results to several other methods. Quantitative results using both simulated and real image data show that, while certain methods may work well for certain imaging modalities, our software is able to obtain high accuracy across several imaging modalities studied. Results also demonstrate that, relative to several existing methods, the template-based method we propose presents increased robustness in the sense of better handling variations in illumination, variations in texture from different imaging modalities, providing more smooth and accurate segmentation borders, as well as handling better cluttered nuclei. PMID:23568787

Velocity landscape correlation resolves multiple flowing protein populations from fluorescence image time series.

PubMed

Pandžić, Elvis; Abu-Arish, Asmahan; Whan, Renee M; Hanrahan, John W; Wiseman, Paul W

2018-02-16

Molecular, vesicular and organellar flows are of fundamental importance for the delivery of nutrients and essential components used in cellular functions such as motility and division. With recent advances in fluorescence/super-resolution microscopy modalities we can resolve the movements of these objects at higher spatio-temporal resolutions and with better sensitivity. Previously, spatio-temporal image correlation spectroscopy has been applied to map molecular flows by correlation analysis of fluorescence fluctuations in image series. However, an underlying assumption of this approach is that the sampled time windows contain one dominant flowing component. Although this was true for most of the cases analyzed earlier, in some situations two or more different flowing populations can be present in the same spatio-temporal window. We introduce an approach, termed velocity landscape correlation (VLC), which detects and extracts multiple flow components present in a sampled image region via an extension of the correlation analysis of fluorescence intensity fluctuations. First we demonstrate theoretically how this approach works, test the performance of the method with a range of computer simulated image series with varying flow dynamics. Finally we apply VLC to study variable fluxing of STIM1 proteins on microtubules connected to the plasma membrane of Cystic Fibrosis Bronchial Epithelial (CFBE) cells. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Methods for the analysis of ordinal response data in medical image quality assessment.

PubMed

Keeble, Claire; Baxter, Paul D; Gislason-Lee, Amber J; Treadgold, Laura A; Davies, Andrew G

2016-07-01

The assessment of image quality in medical imaging often requires observers to rate images for some metric or detectability task. These subjective results are used in optimization, radiation dose reduction or system comparison studies and may be compared to objective measures from a computer vision algorithm performing the same task. One popular scoring approach is to use a Likert scale, then assign consecutive numbers to the categories. The mean of these response values is then taken and used for comparison with the objective or second subjective response. Agreement is often assessed using correlation coefficients. We highlight a number of weaknesses in this common approach, including inappropriate analyses of ordinal data and the inability to properly account for correlations caused by repeated images or observers. We suggest alternative data collection and analysis techniques such as amendments to the scale and multilevel proportional odds models. We detail the suitability of each approach depending upon the data structure and demonstrate each method using a medical imaging example. Whilst others have raised some of these issues, we evaluated the entire study from data collection to analysis, suggested sources for software and further reading, and provided a checklist plus flowchart for use with any ordinal data. We hope that raised awareness of the limitations of the current approaches will encourage greater method consideration and the utilization of a more appropriate analysis. More accurate comparisons between measures in medical imaging will lead to a more robust contribution to the imaging literature and ultimately improved patient care.

Rapid Automated Quantification of Cerebral Leukoaraiosis on CT Images: A Multicenter Validation Study.

PubMed

Chen, Liang; Carlton Jones, Anoma Lalani; Mair, Grant; Patel, Rajiv; Gontsarova, Anastasia; Ganesalingam, Jeban; Math, Nikhil; Dawson, Angela; Aweid, Basaam; Cohen, David; Mehta, Amrish; Wardlaw, Joanna; Rueckert, Daniel; Bentley, Paul

2018-05-15

Purpose To validate a random forest method for segmenting cerebral white matter lesions (WMLs) on computed tomographic (CT) images in a multicenter cohort of patients with acute ischemic stroke, by comparison with fluid-attenuated recovery (FLAIR) magnetic resonance (MR) images and expert consensus. Materials and Methods A retrospective sample of 1082 acute ischemic stroke cases was obtained that was composed of unselected patients who were treated with thrombolysis or who were undergoing contemporaneous MR imaging and CT, and a subset of International Stroke Thrombolysis-3 trial participants. Automated delineations of WML on images were validated relative to experts' manual tracings on CT images, and co-registered FLAIR MR imaging, and ratings were performed by using two conventional ordinal scales. Analyses included correlations between CT and MR imaging volumes, and agreements between automated and expert ratings. Results Automated WML volumes correlated strongly with expert-delineated WML volumes at MR imaging and CT (r 2 = 0.85 and 0.71 respectively; P < .001). Spatial-similarity of automated maps, relative to WML MR imaging, was not significantly different to that of expert WML tracings on CT images. Individual expert WML volumes at CT correlated well with each other (r 2 = 0.85), but varied widely (range, 91% of mean estimate; median estimate, 11 mL; range of estimated ranges, 0.2-68 mL). Agreements (κ) between automated ratings and consensus ratings were 0.60 (Wahlund system) and 0.64 (van Swieten system) compared with agreements between individual pairs of experts of 0.51 and 0.67, respectively, for the two rating systems (P < .01 for Wahlund system comparison of agreements). Accuracy was unaffected by established infarction, acute ischemic changes, or atrophy (P > .05). Automated preprocessing failure rate was 4%; rating errors occurred in a further 4%. Total automated processing time averaged 109 seconds (range, 79-140 seconds). Conclusion An automated method for quantifying CT cerebral white matter lesions achieves a similar accuracy to experts in unselected and multicenter cohorts. © RSNA, 2018 Online supplemental material is available for this article.

WE-D-BRA-03: Four-Dimensional Dose Reconstruction Through Retrospective Phase Determination Using Cine Images of Electronic Portal Imaging Device

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

Yoon, J; Jung, J; Yi, B

2015-06-15

Purpose: To test a method to reconstruct a four-dimensional (4D) dose distribution using the correlation of pre-calculated 4D electronic portal imaging device (EPID) images and measured cine-EPID images. Methods: 1. A phantom designed to simulate a tumor in lung (a polystyrene block with 3.0 cm diameter embedded in cork) was placed on a sinusoidally moving platform with 2 cm amplitude and 4 sec/cycle. Ten-phase 4D CT images were acquired for treatment planning and dose reconstruction. A 6MV photon beam was irradiated on the phantom with static (field size=5×8.5 cm{sup 2}) and dynamic fields (sliding windows, 10×10 cm{sup 2}, X1 MLCmore » closing in parallel with the tumor movement). 2. 4D and 3D doses were calculated forwardly on PTV (1 cm margin). 3. Dose images on EPID under the fields were calculated for 10 phases. 4. Cine EPID images were acquired during irradiation. 5. Their acquisition times were correlated to the phases of the phantom at which irradiation occurred by inter-comparing calculated “reference” EPID images with measured images (2D gamma comparison). For the dynamic beam, the tumor was hidden under MLCs during a portion of irradiation time; the correlation performed when the tumor was visible was extrapolated. 6. Dose for each phase was reconstructed on the 4D CT images and summed over all phases. The summation was compared with forwardly calculated 4D and 3D dose distributions. Monte Carlo methods were used for all calculations. Results: For the open and dynamic beams, the 4D reconstructed doses showed the pass rates of 92.7 % and 100 %, respectively, at the isocenter plane given 3% / 3 mm criteria. The better agreement of the dynamic beam was from its dose gradient which blurred the otherwise sharp difference between forward and reconstructed doses. This also contributed slightly better agreement in DVH of PTV. Conclusion: The feasibility of 4D reconstruction was demonstrated.« less

Attitude-correlated frames approach for a star sensor to improve attitude accuracy under highly dynamic conditions.

PubMed

Ma, Liheng; Zhan, Dejun; Jiang, Guangwen; Fu, Sihua; Jia, Hui; Wang, Xingshu; Huang, Zongsheng; Zheng, Jiaxing; Hu, Feng; Wu, Wei; Qin, Shiqiao

2015-09-01

The attitude accuracy of a star sensor decreases rapidly when star images become motion-blurred under dynamic conditions. Existing techniques concentrate on a single frame of star images to solve this problem and improvements are obtained to a certain extent. An attitude-correlated frames (ACF) approach, which concentrates on the features of the attitude transforms of the adjacent star image frames, is proposed to improve upon the existing techniques. The attitude transforms between different star image frames are measured by the strap-down gyro unit precisely. With the ACF method, a much larger star image frame is obtained through the combination of adjacent frames. As a result, the degradation of attitude accuracy caused by motion-blurring are compensated for. The improvement of the attitude accuracy is approximately proportional to the square root of the number of correlated star image frames. Simulations and experimental results indicate that the ACF approach is effective in removing random noises and improving the attitude determination accuracy of the star sensor under highly dynamic conditions.

Correlative 3D imaging of Whole Mammalian Cells with Light and Electron Microscopy

PubMed Central

Murphy, Gavin E.; Narayan, Kedar; Lowekamp, Bradley C.; Hartnell, Lisa M.; Heymann, Jurgen A. W.; Fu, Jing; Subramaniam, Sriram

2011-01-01

We report methodological advances that extend the current capabilities of ion-abrasion scanning electron microscopy (IA–SEM), also known as focused ion beam scanning electron microscopy, a newly emerging technology for high resolution imaging of large biological specimens in 3D. We establish protocols that enable the routine generation of 3D image stacks of entire plastic-embedded mammalian cells by IA-SEM at resolutions of ~10 to 20 nm at high contrast and with minimal artifacts from the focused ion beam. We build on these advances by describing a detailed approach for carrying out correlative live confocal microscopy and IA–SEM on the same cells. Finally, we demonstrate that by combining correlative imaging with newly developed tools for automated image processing, small 100 nm-sized entities such as HIV-1 or gold beads can be localized in SEM image stacks of whole mammalian cells. We anticipate that these methods will add to the arsenal of tools available for investigating mechanisms underlying host-pathogen interactions, and more generally, the 3D subcellular architecture of mammalian cells and tissues. PMID:21907806

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.

Similarity regularized sparse group lasso for cup to disc ratio computation.

PubMed

Cheng, Jun; Zhang, Zhuo; Tao, Dacheng; Wong, Damon Wing Kee; Liu, Jiang; Baskaran, Mani; Aung, Tin; Wong, Tien Yin

2017-08-01

Automatic cup to disc ratio (CDR) computation from color fundus images has shown to be promising for glaucoma detection. Over the past decade, many algorithms have been proposed. In this paper, we first review the recent work in the area and then present a novel similarity-regularized sparse group lasso method for automated CDR estimation. The proposed method reconstructs the testing disc image based on a set of reference disc images by integrating the similarity between testing and the reference disc images with the sparse group lasso constraints. The reconstruction coefficients are then used to estimate the CDR of the testing image. The proposed method has been validated using 650 images with manually annotated CDRs. Experimental results show an average CDR error of 0.0616 and a correlation coefficient of 0.7, outperforming other methods. The areas under curve in the diagnostic test reach 0.843 and 0.837 when manual and automatically segmented discs are used respectively, better than other methods as well.

Simultaneous AFM and fluorescence imaging: A method for aligning an AFM-tip with an excitation beam using a 2D galvanometer

NASA Astrophysics Data System (ADS)

Moores, A. N.; Cadby, A. J.

2018-02-01

Correlative fluorescence and atomic force microscopy (AFM) imaging is a highly attractive technique for use in biological imaging, enabling force and mechanical measurements of particular structures whose locations are known due to the specificity of fluorescence imaging. The ability to perform these two measurements simultaneously (rather than consecutively with post-processing correlation) is highly valuable because it would allow the mechanical properties of a structure to be tracked over time as changes in the sample occur. We present an instrument which allows simultaneous AFM and fluorescence imaging by aligning an incident fluorescence excitation beam with an AFM-tip. Alignment was performed by calibrating a 2D galvanometer present in the excitation beam path and using it to reposition the incident beam. Two programs were developed (one manual and one automated) which correlate sample features between the AFM and fluorescence images, calculating the distance required to translate the incident beam towards the AFM-tip. Using this method, we were able to obtain beam-tip alignment (and therefore field-of-view alignment) from an offset of >15 μm to within one micron in two iterations of the program. With the program running alongside data acquisition for real-time feedback between AFM and optical images, this offset was maintained over a time period of several hours. Not only does this eliminate the need to image large areas with both techniques to ensure that fields-of-view overlap, but it also raises the possibility of using this instrument for tip-enhanced fluorescence applications, a technique in which super-resolution images have previously been achieved.

Application of a Simplified Method for Estimating Perfusion Derived from Diffusion-Weighted MR Imaging in Glioma Grading.

PubMed

Cao, Mengqiu; Suo, Shiteng; Han, Xu; Jin, Ke; Sun, Yawen; Wang, Yao; Ding, Weina; Qu, Jianxun; Zhang, Xiaohua; Zhou, Yan

2017-01-01

Purpose : To evaluate the feasibility of a simplified method based on diffusion-weighted imaging (DWI) acquired with three b -values to measure tissue perfusion linked to microcirculation, to validate it against from perfusion-related parameters derived from intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging, and to investigate its utility to differentiate low- from high-grade gliomas. Materials and Methods : The prospective study was approved by the local institutional review board and written informed consent was obtained from all patients. From May 2016 and May 2017, 50 patients confirmed with glioma were assessed with multi- b -value DWI and DCE MR imaging at 3.0 T. Besides conventional apparent diffusion coefficient (ADC 0,1000 ) map, perfusion-related parametric maps for IVIM-derived perfusion fraction ( f ) and pseudodiffusion coefficient (D*), DCE MR imaging-derived pharmacokinetic metrics, including K trans , v e and v p , as well as a metric named simplified perfusion fraction (SPF), were generated. Correlation between perfusion-related parameters was analyzed by using the Spearman rank correlation. All imaging parameters were compared between the low-grade ( n = 19) and high-grade ( n = 31) groups by using the Mann-Whitney U test. The diagnostic performance for tumor grading was evaluated with receiver operating characteristic (ROC) analysis. Results : SPF showed strong correlation with IVIM-derived f and D* ( ρ = 0.732 and 0.716, respectively; both P < 0.001). Compared with f , SPF was more correlated with DCE MR imaging-derived K trans ( ρ = 0.607; P < 0.001) and v p ( ρ = 0.397; P = 0.004). Among all parameters, SPF achieved the highest accuracy for differentiating low- from high-grade gliomas, with an area under the ROC curve value of 0.942, which was significantly higher than that of ADC 0,1000 ( P = 0.004). By using SPF as a discriminative index, the diagnostic sensitivity and specificity were 87.1% and 94.7%, respectively, at the optimal cut-off value of 19.26%. Conclusion : The simplified method to measure tissue perfusion based on DWI by using three b -values may be helpful to differentiate low- from high-grade gliomas. SPF may serve as a valuable alternative to measure tumor perfusion in gliomas in a noninvasive, convenient and efficient way.

Monitoring the progression of erosive tooth wear (ETW) using BEWE index in casts and their 3D images: A retrospective longitudinal study.

PubMed

Marro, Francisca; De Lat, Liesa; Martens, Luc; Jacquet, Wolfgang; Bottenberg, Peter

2018-04-13

To determine if the Basic erosive tooth wear index (BEWE index) is able to assess and monitor ETW changes in two consecutive cast models, and detect methodological differences when using the corresponding 3D image replicas. A total of 480 pre-treatment and 2-year post-treatment orthodontic models (n = 240 cast models and n = 240 3D image replicas) from 120 adolescents treated between 2002 and 2013 at the Gent Dental Clinic, Belgium, were scored using the BEWE index. For data analysis only posterior sextants were considered, and inter-method differences were evaluated using Wilcoxon Signed Rank test, Kappa values and Mc Nemar tests (p < 0.05). Correlations between methods were determined using Kendall tau correlation test. Significant changes of ETW were detected between two consecutive models when BEWE index was used to score cast models or their 3D image replicas (p < 0.001). A strong significant correlation (τb: 0.74; p < 0.001) was shown between both methods However, 3D image-BEWE index combination showed a higher probability for detecting initial surface changes, and scored significantly higher than casts (p < 0.001). Incidence and progression of ETW using 3D images was 13.3% (n = 16) and 60.9% (n = 56) respectively, with two subjects developing BEWE = 3 in at least one tooth surface. BEWE index is a suitable tool for the scoring of ETW lesions in 3D images and cast. The combination of both digital 3D records and index, can be used for the monitoring of ETW in a longitudinal approach. The higher sensibility of BEWE index when scoring 3D images might improve the early diagnosis of ETW lesions. The BEWE index combined with digital 3D records of oral conditions might improve the practitioner performance with respect to early diagnosis, monitoring and managing ETW. Copyright © 2018 Elsevier Ltd. All rights reserved.

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

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.

Ultrafast image-based dynamic light scattering for nanoparticle sizing

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

Zhou, Wu; Zhang, Jie; Liu, Lili

An ultrafast sizing method for nanoparticles is proposed, called as UIDLS (Ultrafast Image-based Dynamic Light Scattering). This method makes use of the intensity fluctuation of scattered light from nanoparticles in Brownian motion, which is similar to the conventional DLS method. The difference in the experimental system is that the scattered light by nanoparticles is received by an image sensor instead of a photomultiplier tube. A novel data processing algorithm is proposed to directly get correlation coefficient between two images at a certain time interval (from microseconds to milliseconds) by employing a two-dimensional image correlation algorithm. This coefficient has been provedmore » to be a monotonic function of the particle diameter. Samples of standard latex particles (79/100/352/482/948 nm) were measured for validation of the proposed method. The measurement accuracy of higher than 90% was found with standard deviations less than 3%. A sample of nanosilver particle with nominal size of 20 ± 2 nm and a sample of polymethyl methacrylate emulsion with unknown size were also tested using UIDLS method. The measured results were 23.2 ± 3.0 nm and 246.1 ± 6.3 nm, respectively, which is substantially consistent with the transmission electron microscope results. Since the time for acquisition of two successive images has been reduced to less than 1 ms and the data processing time in about 10 ms, the total measuring time can be dramatically reduced from hundreds seconds to tens of milliseconds, which provides the potential for real-time and in situ nanoparticle sizing.« less

3D SAPIV particle field reconstruction method based on adaptive threshold.

PubMed

Qu, Xiangju; Song, Yang; Jin, Ying; Li, Zhenhua; Wang, Xuezhen; Guo, ZhenYan; Ji, Yunjing; He, Anzhi

2018-03-01

Particle image velocimetry (PIV) is a necessary flow field diagnostic technique that provides instantaneous velocimetry information non-intrusively. Three-dimensional (3D) PIV methods can supply the full understanding of a 3D structure, the complete stress tensor, and the vorticity vector in the complex flows. In synthetic aperture particle image velocimetry (SAPIV), the flow field can be measured with large particle intensities from the same direction by different cameras. During SAPIV particle reconstruction, particles are commonly reconstructed by manually setting a threshold to filter out unfocused particles in the refocused images. In this paper, the particle intensity distribution in refocused images is analyzed, and a SAPIV particle field reconstruction method based on an adaptive threshold is presented. By using the adaptive threshold to filter the 3D measurement volume integrally, the three-dimensional location information of the focused particles can be reconstructed. The cross correlations between images captured from cameras and images projected by the reconstructed particle field are calculated for different threshold values. The optimal threshold is determined by cubic curve fitting and is defined as the threshold value that causes the correlation coefficient to reach its maximum. The numerical simulation of a 16-camera array and a particle field at two adjacent time events quantitatively evaluates the performance of the proposed method. An experimental system consisting of a camera array of 16 cameras was used to reconstruct the four adjacent frames in a vortex flow field. The results show that the proposed reconstruction method can effectively reconstruct the 3D particle fields.

Computer Vision for Artificially Intelligent Robotic Systems

NASA Astrophysics Data System (ADS)

Ma, Chialo; Ma, Yung-Lung

1987-04-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts -- position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed bye the main control unit. In Pulse-Echo Signal Process Unit, we ultilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by u law coding method, and this data together with delay time T, angle information OH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Model, we use a narrow beam transducer and it's input voltage is 50V p-p. A RobOt equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Improved Performance Characteristics For Indium Antimonide Photovoltaic Detector Arrays Using A FET-Switched Multiplexing Technique

NASA Astrophysics Data System (ADS)

Ma, Yung-Lung; Ma, Chialo

1987-03-01

In this paper An Acoustic Imaging Recognition System (AIRS) will be introduced which is installed on an Intelligent Robotic System and can recognize different type of Hand tools' by Dynamic pattern recognition. The dynamic pattern recognition is approached by look up table method in this case, the method can save a lot of calculation time and it is practicable. The Acoustic Imaging Recognition System (AIRS) is consist of four parts _ position control unit, pulse-echo signal processing unit, pattern recognition unit and main control unit. The position control of AIRS can rotate an angle of ±5 degree Horizental and Vertical seperately, the purpose of rotation is to find the maximum reflection intensity area, from the distance, angles and intensity of the target we can decide the characteristic of this target, of course all the decision is target, of course all the decision is processed by the main control unit. In Pulse-Echo Signal Process Unit, we utilize the correlation method, to overcome the limitation of short burst of ultrasonic, because the Correlation system can transmit large time bandwidth signals and obtain their resolution and increased intensity through pulse compression in the correlation receiver. The output of correlator is sampled and transfer into digital data by p law coding method, and this data together with delay time T, angle information eH, eV will be sent into main control unit for further analysis. The recognition process in this paper, we use dynamic look up table method, in this method at first we shall set up serval recognition pattern table and then the new pattern scanned by Transducer array will be devided into serval stages and compare with the sampling table. The comparison is implemented by dynamic programing and Markovian process. All the hardware control signals, such as optimum delay time for correlator receiver, horizental and vertical rotation angle for transducer plate, are controlled by the Main Control Unit, the Main Control Unit also handles the pattern recognition process. The distance from the target to the transducer plate is limitted by the power and beam angle of transducer elements, in this AIRS Models, we use a narrow beam transducer and it's input voltage is 50V p-p. A Robot equipped with AIRS can not only measure the distance from the target but also recognize a three dimensional image of target from the image lab of Robot memory. Indexitems, Accoustic System, Supersonic transducer, Dynamic programming, Look-up-table, Image process, pattern Recognition, Quad Tree, Quadappoach.

Application of automatic threshold in dynamic target recognition with low contrast

NASA Astrophysics Data System (ADS)

Miao, Hua; Guo, Xiaoming; Chen, Yu

2014-11-01

Hybrid photoelectric joint transform correlator can realize automatic real-time recognition with high precision through the combination of optical devices and electronic devices. When recognizing targets with low contrast using photoelectric joint transform correlator, because of the difference of attitude, brightness and grayscale between target and template, only four to five frames of dynamic targets can be recognized without any processing. CCD camera is used to capture the dynamic target images and the capturing speed of CCD is 25 frames per second. Automatic threshold has many advantages like fast processing speed, effectively shielding noise interference, enhancing diffraction energy of useful information and better reserving outline of target and template, so this method plays a very important role in target recognition with optical correlation method. However, the automatic obtained threshold by program can not achieve the best recognition results for dynamic targets. The reason is that outline information is broken to some extent. Optimal threshold is obtained by manual intervention in most cases. Aiming at the characteristics of dynamic targets, the processing program of improved automatic threshold is finished by multiplying OTSU threshold of target and template by scale coefficient of the processed image, and combining with mathematical morphology. The optimal threshold can be achieved automatically by improved automatic threshold processing for dynamic low contrast target images. The recognition rate of dynamic targets is improved through decreased background noise effect and increased correlation information. A series of dynamic tank images with the speed about 70 km/h are adapted as target images. The 1st frame of this series of tanks can correlate only with the 3rd frame without any processing. Through OTSU threshold, the 80th frame can be recognized. By automatic threshold processing of the joint images, this number can be increased to 89 frames. Experimental results show that the improved automatic threshold processing has special application value for the recognition of dynamic target with low contrast.

In Vivo High-Frequency, Contrast-Enhanced Ultrasonography of Uveal Melanoma in Mice: Imaging Features and Histopathologic Correlations

PubMed Central

Zhang, Qing; Yang, Hua; Kang, Shin J.; Wang, Yanggan; Wang, Geoffrey D.; Coulthard, Tonya

2011-01-01

Purpose. To evaluate the usefulness of in vivo imaging of uveal melanoma in mice using high-frequency contrast-enhanced ultrasound (HF-CE-US) with 2D or 3D modes and to correlate the sonographic findings with histopathologic characteristics. Methods. Fourteen 12-week-old C57BL6 mice were inoculated into their right eyes with aliquots of 5 × 105/2.5 μL B16LS9 melanoma cells and were randomly assigned to either of two groups. At 7 days after inoculation, tumor-bearing eyes in group 1 (n = 8) were imaged using HF-CE-US to determine the 2D tumor size and relative blood volume; eyes in group 2 (n = 6) were imaged by 3D microbubble contrast-enhanced ultrasound, and the tumor volume was determined. Histologic tumor burden was quantified in enucleated eyes by image processing software, and microvascular density was determined by counting von Willebrand factor-positive vascular channels. Ultrasound images were evaluated and compared with histopathologic findings. Results. Using HF-CE-US, melanomas were visualized as relatively hyperechoic regions. The intraobserver variability of sonographic measurements was 9.65% ± 7.89%, and the coefficient of variation for multiple measurements was 7.33% ± 5.71%. The correlation coefficient of sonographic volume or size and histologic area was 0.71 (P = 0.11) and 0.79 (P = 0.32). The relative blood volume within the tumor demonstrated sonographically correlated significantly with histologic tumor vascularity (r = 0.83; P < 0.001). Conclusions. There was a positive linear correlation between sonographic tumor measurements and histologic tumor burden in the mouse ocular melanoma model. Contrast-enhanced intensity corresponded with microvascular density and blood volume. HF-CE-US is a real-time, noninvasive, reliable method for in vivo evaluation of experimental intraocular melanoma tumor area and relative blood volume. PMID:21245408

Full-frame, high-speed 3D shape and deformation measurements using stereo-digital image correlation and a single color high-speed camera

NASA Astrophysics Data System (ADS)

Yu, Liping; Pan, Bing

2017-08-01

Full-frame, high-speed 3D shape and deformation measurement using stereo-digital image correlation (stereo-DIC) technique and a single high-speed color camera is proposed. With the aid of a skillfully designed pseudo stereo-imaging apparatus, color images of a test object surface, composed of blue and red channel images from two different optical paths, are recorded by a high-speed color CMOS camera. The recorded color images can be separated into red and blue channel sub-images using a simple but effective color crosstalk correction method. These separated blue and red channel sub-images are processed by regular stereo-DIC method to retrieve full-field 3D shape and deformation on the test object surface. Compared with existing two-camera high-speed stereo-DIC or four-mirror-adapter-assisted singe-camera high-speed stereo-DIC, the proposed single-camera high-speed stereo-DIC technique offers prominent advantages of full-frame measurements using a single high-speed camera but without sacrificing its spatial resolution. Two real experiments, including shape measurement of a curved surface and vibration measurement of a Chinese double-side drum, demonstrated the effectiveness and accuracy of the proposed technique.

Image enhancement by spectral-error correction for dual-energy computed tomography.

PubMed

Park, Kyung-Kook; Oh, Chang-Hyun; Akay, Metin

2011-01-01

Dual-energy CT (DECT) was reintroduced recently to use the additional spectral information of X-ray attenuation and aims for accurate density measurement and material differentiation. However, the spectral information lies in the difference between low and high energy images or measurements, so that it is difficult to acquire accurate spectral information due to amplification of high pixel noise in the resulting difference image. In this work, an image enhancement technique for DECT is proposed, based on the fact that the attenuation of a higher density material decreases more rapidly as X-ray energy increases. We define as spectral error the case when a pixel pair of low and high energy images deviates far from the expected attenuation trend. After analyzing the spectral-error sources of DECT images, we propose a DECT image enhancement method, which consists of three steps: water-reference offset correction, spectral-error correction, and anti-correlated noise reduction. It is the main idea of this work that makes spectral errors distributed like random noise over the true attenuation and suppressed by the well-known anti-correlated noise reduction. The proposed method suppressed noise of liver lesions and improved contrast between liver lesions and liver parenchyma in DECT contrast-enhanced abdominal images and their two-material decomposition.

Registration of 3D fetal neurosonography and MRI☆

PubMed Central

Kuklisova-Murgasova, Maria; Cifor, Amalia; Napolitano, Raffaele; Papageorghiou, Aris; Quaghebeur, Gerardine; Rutherford, Mary A.; Hajnal, Joseph V.; Noble, J. Alison; Schnabel, Julia A.

2013-01-01

We propose a method for registration of 3D fetal brain ultrasound with a reconstructed magnetic resonance fetal brain volume. This method, for the first time, allows the alignment of models of the fetal brain built from magnetic resonance images with 3D fetal brain ultrasound, opening possibilities to develop new, prior information based image analysis methods for 3D fetal neurosonography. The reconstructed magnetic resonance volume is first segmented using a probabilistic atlas and a pseudo ultrasound image volume is simulated from the segmentation. This pseudo ultrasound image is then affinely aligned with clinical ultrasound fetal brain volumes using a robust block-matching approach that can deal with intensity artefacts and missing features in the ultrasound images. A qualitative and quantitative evaluation demonstrates good performance of the method for our application, in comparison with other tested approaches. The intensity average of 27 ultrasound images co-aligned with the pseudo ultrasound template shows good correlation with anatomy of the fetal brain as seen in the reconstructed magnetic resonance image. PMID:23969169

Generating Artificial Reference Images for Open Loop Correlation Wavefront Sensors

NASA Astrophysics Data System (ADS)

Townson, M. J.; Love, G. D.; Saunter, C. D.

2018-05-01

Shack-Hartmann wavefront sensors for both solar and laser guide star adaptive optics (with elongated spots) need to observe extended objects. Correlation techniques have been successfully employed to measure the wavefront gradient in solar adaptive optics systems and have been proposed for laser guide star systems. In this paper we describe a method for synthesising reference images for correlation Shack-Hartmann wavefront sensors with a larger field of view than individual sub-apertures. We then show how these supersized reference images can increase the performance of correlation wavefront sensors in regimes where large relative shifts are induced between sub-apertures, such as those observed in open-loop wavefront sensors. The technique we describe requires no external knowledge outside of the wavefront-sensor images, making it available as an entirely "software" upgrade to an existing adaptive optics system. For solar adaptive optics we show the supersized reference images extend the magnitude of shifts which can be accurately measured from 12% to 50% of the field of view of a sub-aperture and in laser guide star wavefront sensors the magnitude of centroids that can be accurately measured is increased from 12% to 25% of the total field of view of the sub-aperture.

Estimating GATE rainfall with geosynchronous satellite images

NASA Technical Reports Server (NTRS)

Stout, J. E.; Martin, D. W.; Sikdar, D. N.

1979-01-01

A method of estimating GATE rainfall from either visible or infrared images of geosynchronous satellites is described. Rain is estimated from cumulonimbus cloud area by the equation R = a sub 0 A + a sub 1 dA/dt, where R is volumetric rainfall, A cloud area, t time, and a sub 0 and a sub 1 are constants. Rainfall, calculated from 5.3 cm ship radar, and cloud area are measured from clouds in the tropical North Atlantic. The constants a sub 0 and a sub 1 are fit to these measurements by the least-squares method. Hourly estimates by the infrared version of this technique correlate well (correlation coefficient of 0.84) with rain totals derived from composited radar for an area of 100,000 sq km. The accuracy of this method is described and compared to that of another technique using geosynchronous satellite images. It is concluded that this technique provides useful estimates of tropical oceanic rainfall on a convective scale.

Airplane wing deformation and flight flutter detection method by using three-dimensional speckle image correlation technology.

PubMed

Wu, Jun; Yu, Zhijing; Wang, Tao; Zhuge, Jingchang; Ji, Yue; Xue, Bin

2017-06-01

Airplane wing deformation is an important element of aerodynamic characteristics, structure design, and fatigue analysis for aircraft manufacturing, as well as a main test content of certification regarding flutter for airplanes. This paper presents a novel real-time detection method for wing deformation and flight flutter detection by using three-dimensional speckle image correlation technology. Speckle patterns whose positions are determined through the vibration characteristic of the aircraft are coated on the wing; then the speckle patterns are imaged by CCD cameras which are mounted inside the aircraft cabin. In order to reduce the computation, a matching technique based on Geodetic Systems Incorporated coded points combined with the classical epipolar constraint is proposed, and a displacement vector map for the aircraft wing can be obtained through comparing the coordinates of speckle points before and after deformation. Finally, verification experiments containing static and dynamic tests by using an aircraft wing model demonstrate the accuracy and effectiveness of the proposed method.

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.

k-Space Image Correlation Spectroscopy: A Method for Accurate Transport Measurements Independent of Fluorophore Photophysics

PubMed Central

Kolin, David L.; Ronis, David; Wiseman, Paul W.

2006-01-01

We present the theory and application of reciprocal space image correlation spectroscopy (kICS). This technique measures the number density, diffusion coefficient, and velocity of fluorescently labeled macromolecules in a cell membrane imaged on a confocal, two-photon, or total internal reflection fluorescence microscope. In contrast to r-space correlation techniques, we show kICS can recover accurate dynamics even in the presence of complex fluorophore photobleaching and/or “blinking”. Furthermore, these quantities can be calculated without nonlinear curve fitting, or any knowledge of the beam radius of the exciting laser. The number densities calculated by kICS are less sensitive to spatial inhomogeneity of the fluorophore distribution than densities measured using image correlation spectroscopy. We use simulations as a proof-of-principle to show that number densities and transport coefficients can be extracted using this technique. We present calibration measurements with fluorescent microspheres imaged on a confocal microscope, which recover Stokes-Einstein diffusion coefficients, and flow velocities that agree with single particle tracking measurements. We also show the application of kICS to measurements of the transport dynamics of α5-integrin/enhanced green fluorescent protein constructs in a transfected CHO cell imaged on a total internal reflection fluorescence microscope using charge-coupled device area detection. PMID:16861272

Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease

PubMed Central

Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B.; Torres, Vicente E.; Yu, Alan S.L.; Mrug, Michal; Bennett, William M.; Flessner, Michael F.; Landsittel, Doug P.

2016-01-01

Background and objectives Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Design, setting, participants, & measurements Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2–weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Results Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable. Conclusions We have developed a fully automated method for segmentation of kidneys from abdominal magnetic resonance images in patients with autosomal dominant polycystic kidney disease with varying kidney volumes. The performance of the automated method was in good agreement with that of manual method. PMID:26797708

Automated Segmentation of Kidneys from MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease.

PubMed

Kim, Youngwoo; Ge, Yinghui; Tao, Cheng; Zhu, Jianbing; Chapman, Arlene B; Torres, Vicente E; Yu, Alan S L; Mrug, Michal; Bennett, William M; Flessner, Michael F; Landsittel, Doug P; Bae, Kyongtae T

2016-04-07

Our study developed a fully automated method for segmentation and volumetric measurements of kidneys from magnetic resonance images in patients with autosomal dominant polycystic kidney disease and assessed the performance of the automated method with the reference manual segmentation method. Study patients were selected from the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease. At the enrollment of the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease Study in 2000, patients with autosomal dominant polycystic kidney disease were between 15 and 46 years of age with relatively preserved GFRs. Our fully automated segmentation method was on the basis of a spatial prior probability map of the location of kidneys in abdominal magnetic resonance images and regional mapping with total variation regularization and propagated shape constraints that were formulated into a level set framework. T2-weighted magnetic resonance image sets of 120 kidneys were selected from 60 patients with autosomal dominant polycystic kidney disease and divided into the training and test datasets. The performance of the automated method in reference to the manual method was assessed by means of two metrics: Dice similarity coefficient and intraclass correlation coefficient of segmented kidney volume. The training and test sets were swapped for crossvalidation and reanalyzed. Successful segmentation of kidneys was performed with the automated method in all test patients. The segmented kidney volumes ranged from 177.2 to 2634 ml (mean, 885.4±569.7 ml). The mean Dice similarity coefficient ±SD between the automated and manual methods was 0.88±0.08. The mean correlation coefficient between the two segmentation methods for the segmented volume measurements was 0.97 (P<0.001 for each crossvalidation set). The results from the crossvalidation sets were highly comparable. We have developed a fully automated method for segmentation of kidneys from abdominal magnetic resonance images in patients with autosomal dominant polycystic kidney disease with varying kidney volumes. The performance of the automated method was in good agreement with that of manual method. Copyright © 2016 by the American Society of Nephrology.

Postoperative MRI Evaluation of a Radiofrequency Cordotomy Lesion for Intractable Cancer Pain

PubMed Central

Vedantam, A.; Hou, P.; Chi, T.L.; Hess, K.R; Dougherty, P.M.; Bruera, E.; Viswanathan, A.

2017-01-01

BACKGROUND AND PURPOSE There are limited data on the use of postoperative imaging to evaluate the cordotomy lesion. We aimed to describe the cordotomy lesion by using postoperative MR imaging in patients after percutaneous cordotomy for intractable cancer pain. MATERIALS AND METHODS Postoperative MR imaging and clinical outcomes were prospectively obtained for 10 patients after percutaneous cordotomy for intractable cancer pain. Area, signal intensity, and location of the lesion were recorded. Clinical outcomes were measured by using the Visual Analog Scale and the Brief Pain Inventory–Short Form, and correlations with MR imaging metrics were evaluated. RESULTS Ten patients (5 men, 5 women; mean age, 58.5 ± 9.6 years) were included in this study. The cordotomy lesion was hyperintense with central hypointense foci on T2-weighted MR imaging, and it was centered in the anterolateral quadrant at the C1–C2 level. The mean percentage of total cord area lesioned was 24.9% ± 7.9%, and most lesions were centered in the dorsolateral region of the anterolateral quadrant (66% of the anterolateral quadrant). The number of pial penetrations correlated with the percentage of total cord area that was lesioned (r = 0.78; 95% CI, 0.44–0.89; P = .008) and the length of T2-weighted hyperintensity (r = 0.85; 95% CI, 0.54–0.89; P = .002). No significant correlations were found between early clinical outcomes and quantitative MR imaging metrics. CONCLUSIONS We describe qualitative and quantitative characteristics of a cordotomy lesion on early postoperative MR imaging. The size and length of the lesion on MR imaging correlate with the number of pial penetrations. Larger studies are needed to further investigate the clinical correlates of MR imaging metrics after percutaneous cordotomy. PMID:28209581

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

Accuracy evaluation of optical distortion calibration by digital image correlation

NASA Astrophysics Data System (ADS)

Gao, Zeren; Zhang, Qingchuan; Su, Yong; Wu, Shangquan

2017-11-01

Due to its convenience of operation, the camera calibration algorithm, which is based on the plane template, is widely used in image measurement, computer vision and other fields. How to select a suitable distortion model is always a problem to be solved. Therefore, there is an urgent need for an experimental evaluation of the accuracy of camera distortion calibrations. This paper presents an experimental method for evaluating camera distortion calibration accuracy, which is easy to implement, has high precision, and is suitable for a variety of commonly used lens. First, we use the digital image correlation method to calculate the in-plane rigid body displacement field of an image displayed on a liquid crystal display before and after translation, as captured with a camera. Next, we use a calibration board to calibrate the camera to obtain calibration parameters which are used to correct calculation points of the image before and after deformation. The displacement field before and after correction is compared to analyze the distortion calibration results. Experiments were carried out to evaluate the performance of two commonly used industrial camera lenses for four commonly used distortion models.

Visualizing excipient composition and homogeneity of Compound Liquorice Tablets by near-infrared chemical imaging

NASA Astrophysics Data System (ADS)

Wu, Zhisheng; Tao, Ou; Cheng, Wei; Yu, Lu; Shi, Xinyuan; Qiao, Yanjiang

2012-02-01

This study demonstrated that near-infrared chemical imaging (NIR-CI) was a promising technology for visualizing the spatial distribution and homogeneity of Compound Liquorice Tablets. The starch distribution (indirectly, plant extraction) could be spatially determined using basic analysis of correlation between analytes (BACRA) method. The correlation coefficients between starch spectrum and spectrum of each sample were greater than 0.95. Depending on the accurate determination of starch distribution, a method to determine homogeneous distribution was proposed by histogram graph. The result demonstrated that starch distribution in sample 3 was relatively heterogeneous according to four statistical parameters. Furthermore, the agglomerates domain in each tablet was detected using score image layers of principal component analysis (PCA) method. Finally, a novel method named Standard Deviation of Macropixel Texture (SDMT) was introduced to detect agglomerates and heterogeneity based on binary image. Every binary image was divided into different sizes length of macropixel and the number of zero values in each macropixel was counted to calculate standard deviation. Additionally, a curve fitting graph was plotted on the relationship between standard deviation and the size length of macropixel. The result demonstrated the inter-tablet heterogeneity of both starch and total compounds distribution, simultaneously, the similarity of starch distribution and the inconsistency of total compounds distribution among intra-tablet were signified according to the value of slope and intercept parameters in the curve.

Multimodality medical image database for temporal lobe epilepsy

NASA Astrophysics Data System (ADS)

Siadat, Mohammad-Reza; Soltanian-Zadeh, Hamid; Fotouhi, Farshad A.; Elisevich, Kost

2003-05-01

This paper presents the development of a human brain multi-modality 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 and FLAIR MRI and ictal/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 non-verbal Wechsler 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 matches the neurosurgeons 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.

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.

A CCA+ICA based model for multi-task brain imaging data fusion and its application to schizophrenia.

PubMed

Sui, Jing; Adali, Tülay; Pearlson, Godfrey; Yang, Honghui; Sponheim, Scott R; White, Tonya; Calhoun, Vince D

2010-05-15

Collection of multiple-task brain imaging data from the same subject has now become common practice in medical imaging studies. In this paper, we propose a simple yet effective model, "CCA+ICA", as a powerful tool for multi-task data fusion. This joint blind source separation (BSS) model takes advantage of two multivariate methods: canonical correlation analysis and independent component analysis, to achieve both high estimation accuracy and to provide the correct connection between two datasets in which sources can have either common or distinct between-dataset correlation. In both simulated and real fMRI applications, we compare the proposed scheme with other joint BSS models and examine the different modeling assumptions. The contrast images of two tasks: sensorimotor (SM) and Sternberg working memory (SB), derived from a general linear model (GLM), were chosen to contribute real multi-task fMRI data, both of which were collected from 50 schizophrenia patients and 50 healthy controls. When examining the relationship with duration of illness, CCA+ICA revealed a significant negative correlation with temporal lobe activation. Furthermore, CCA+ICA located sensorimotor cortex as the group-discriminative regions for both tasks and identified the superior temporal gyrus in SM and prefrontal cortex in SB as task-specific group-discriminative brain networks. In summary, we compared the new approach to some competitive methods with different assumptions, and found consistent results regarding each of their hypotheses on connecting the two tasks. Such an approach fills a gap in existing multivariate methods for identifying biomarkers from brain imaging data.

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.

Physically motivated global alignment method for electron tomography

DOE PAGES

Sanders, Toby; Prange, Micah; Akatay, Cem; ...

2015-04-08

Electron tomography is widely used for nanoscale determination of 3-D structures in many areas of science. Determining the 3-D structure of a sample from electron tomography involves three major steps: acquisition of sequence of 2-D projection images of the sample with the electron microscope, alignment of the images to a common coordinate system, and 3-D reconstruction and segmentation of the sample from the aligned image data. The resolution of the 3-D reconstruction is directly influenced by the accuracy of the alignment, and therefore, it is crucial to have a robust and dependable alignment method. In this paper, we develop amore » new alignment method which avoids the use of markers and instead traces the computed paths of many identifiable ‘local’ center-of-mass points as the sample is rotated. Compared with traditional correlation schemes, the alignment method presented here is resistant to cumulative error observed from correlation techniques, has very rigorous mathematical justification, and is very robust since many points and paths are used, all of which inevitably improves the quality of the reconstruction and confidence in the scientific results.« less

A novel method for repeatedly generating speckle patterns used in digital image correlation

NASA Astrophysics Data System (ADS)

Zhang, Juan; Sweedy, Ahmed; Gitzhofer, François; Baroud, Gamal

2018-01-01

Speckle patterns play a key role in Digital Image Correlation (DIC) measurement, and generating an optimal speckle pattern has been the goal for decades now. The usual method of generating a speckle pattern is by manually spraying the paint on the specimen. However, this makes it difficult to reproduce the optimal pattern for maintaining identical testing conditions and achieving consistent DIC results. This study proposed and evaluated a novel method using an atomization system to repeatedly generate speckle patterns. To verify the repeatability of the speckle patterns generated by this system, simulation and experimental studies were systematically performed. The results from both studies showed that the speckle patterns and, accordingly, the DIC measurements become highly accurate and repeatable using the proposed atomization system.

Mingus Discontinuous Multiphysics

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

Pat Notz, Dan Turner

Mingus provides hybrid coupled local/non-local mechanics analysis capabilities that extend several traditional methods to applications with inherent discontinuities. Its primary features include adaptations of solid mechanics, fluid dynamics and digital image correlation that naturally accommodate dijointed data or irregular solution fields by assimilating a variety of discretizations (such as control volume finite elements, peridynamics and meshless control point clouds). The goal of this software is to provide an analysis framework form multiphysics engineering problems with an integrated image correlation capability that can be used for experimental validation and model

Psychophysical Reverse Correlation with Multiple Response Alternatives

ERIC Educational Resources Information Center

Dai, Huanping; Micheyl, Christophe

2010-01-01

Psychophysical reverse-correlation methods such as the "classification image" technique provide a unique tool to uncover the internal representations and decision strategies of individual participants in perceptual tasks. Over the past 30 years, these techniques have gained increasing popularity among both visual and auditory psychophysicists.…

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…

Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images.

PubMed

Rajan, Jeny; Veraart, Jelle; Van Audekerke, Johan; Verhoye, Marleen; Sijbers, Jan

2012-12-01

Effective denoising is vital for proper analysis and accurate quantitative measurements from magnetic resonance (MR) images. Even though many methods were proposed to denoise MR images, only few deal with the estimation of true signal from MR images acquired with phased-array coils. If the magnitude data from phased array coils are reconstructed as the root sum of squares, in the absence of noise correlations and subsampling, the data is assumed to follow a non central-χ distribution. However, when the k-space is subsampled to increase the acquisition speed (as in GRAPPA like methods), noise becomes spatially varying. In this note, we propose a method to denoise multiple-coil acquired MR images. Both the non central-χ distribution and the spatially varying nature of the noise is taken into account in the proposed method. Experiments were conducted on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. Copyright © 2012 Elsevier Inc. All rights reserved.

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).

Germinal center texture entropy as possible indicator of humoral immune response: immunophysiology viewpoint.

PubMed

Pantic, Igor; Pantic, Senka

2012-10-01

In this article, we present the results indicating that spleen germinal center (GC) texture entropy determined by gray-level co-occurrence matrix (GLCM) method is related to humoral immune response. Spleen tissue was obtained from eight outbred male short-haired guinea pigs previously immunized by sheep red blood cells (SRBC). A total of 312 images from 39 germinal centers (156 GC light zone images and 156 GC dark zone images) were acquired and analyzed by GLCM method. Angular second moment, contrast, correlation, entropy, and inverse difference moment were calculated for each image. Humoral immune response to SRBC was measured using T cell-dependent antibody response (TDAR) assay. Statistically highly significant negative correlation was detected between light zone entropy and the number of TDAR plaque-forming cells (r (s) = -0.86, p < 0.01). The entropy decreased as the plaque-forming cells increased and vice versa. A statistically significant negative correlation was also detected between dark zone entropy values and the number of plaque-forming cells (r (s) = -0.69, p < 0.05). Germinal center texture entropy may be a powerful indicator of humoral immune response. This study is one of the first to point out the potential scientific value of GLCM image texture analysis in lymphoid tissue cytoarchitecture evaluation. Lymphoid tissue texture analysis could become an important and affordable addition to the conventional immunophysiology techniques.

What is the influence of self-image and perceived parenting role expectations on adolescent fathers' perceived role performance?

PubMed

Jones

2000-05-01

Background: "Adolescent pregnancy is one of the most pressing, persistent, and poignant problems facing society" (Yoos, 1987, p. 247). Manitoba's teen pregnancy rates are among the highest in Canada. Yet, little is known about adolescent fathers and their parenting involvement. The purpose of this descriptive correlational study was to explore variables which may influence teen fathers' participation in parenting.Methods: A convenience sample of 30 adolescent fathers, whose partners were attending an Adolescent Prenatal Clinic, completed two questionnaires: Offer Self-Image-Revised, and Perceived Parenting Role Performance. Guided by family role theory, four hypotheses were examined utilizing a quantitative research method.Results: Data analysis revealed that 30% of these respondents had a low to very low self-image. Pearson's correlation coefficient, which facilitated hypotheses testing, failed to validate a relationship between teen fathers' perceived role performance and self-image, and perceived parenting role expectations. Nevertheless, a moderate negative correlation was noted between teen fathers' self-image and their perceived parenting role expectations (r = -.35, p <.05).Conclusions: These findings contradict the philosophy of family role theory. Results of this study indicated that teen fathers want to be involved in parenting. However, unrealistic expectations and the inability to combine the developmental tasks of adolescence with the responsibilities of fatherhood increase their vulnerability to parenting failure.

Correlates of mammographic density in B-mode ultrasound and real time elastography.

PubMed

Jud, Sebastian Michael; Häberle, Lothar; Fasching, Peter A; Heusinger, Katharina; Hack, Carolin; Faschingbauer, Florian; Uder, Michael; Wittenberg, Thomas; Wagner, Florian; Meier-Meitinger, Martina; Schulz-Wendtland, Rüdiger; Beckmann, Matthias W; Adamietz, Boris R

2012-07-01

The aim of our study involved the assessment of B-mode imaging and elastography with regard to their ability to predict mammographic density (MD) without X-rays. Women, who underwent routine mammography, were prospectively examined with additional B-mode ultrasound and elastography. MD was assessed quantitatively with a computer-assisted method (Madena). The B-mode and elastography images were assessed by histograms with equally sized gray-level intervals. Regression models were built and cross validated to examine the ability to predict MD. The results of this study showed that B-mode imaging and elastography were able to predict MD. B-mode seemed to give a more accurate prediction. R for B-mode image and elastography were 0.67 and 0.44, respectively. Areas in the B-mode images that correlated with mammographic dense areas were either dark gray or of intermediate gray levels. Concerning elastography only the gray levels that represent extremely stiff tissue correlated positively with MD. In conclusion, ultrasound seems to be able to predict MD. Easy and cheap utilization of regular breast ultrasound machines encourages the use of ultrasound in larger case-control studies to validate this method as a breast cancer risk predictor. Furthermore, the application of ultrasound for breast tissue characterization could enable comprehensive research concerning breast cancer risk and breast density in young and pregnant women.

Normalized gradient fields cross-correlation for automated detection of prostate in magnetic resonance images

NASA Astrophysics Data System (ADS)

Fotin, Sergei V.; Yin, Yin; Periaswamy, Senthil; Kunz, Justin; Haldankar, Hrishikesh; Muradyan, Naira; Cornud, François; Turkbey, Baris; Choyke, Peter L.

2012-02-01

Fully automated prostate segmentation helps to address several problems in prostate cancer diagnosis and treatment: it can assist in objective evaluation of multiparametric MR imagery, provides a prostate contour for MR-ultrasound (or CT) image fusion for computer-assisted image-guided biopsy or therapy planning, may facilitate reporting and enables direct prostate volume calculation. Among the challenges in automated analysis of MR images of the prostate are the variations of overall image intensities across scanners, the presence of nonuniform multiplicative bias field within scans and differences in acquisition setup. Furthermore, images acquired with the presence of an endorectal coil suffer from localized high-intensity artifacts at the posterior part of the prostate. In this work, a three-dimensional method for fast automated prostate detection based on normalized gradient fields cross-correlation, insensitive to intensity variations and coil-induced artifacts, is presented and evaluated. The components of the method, offline template learning and the localization algorithm, are described in detail. The method was validated on a dataset of 522 T2-weighted MR images acquired at the National Cancer Institute, USA that was split in two halves for development and testing. In addition, second dataset of 29 MR exams from Centre d'Imagerie Médicale Tourville, France were used to test the algorithm. The 95% confidence intervals for the mean Euclidean distance between automatically and manually identified prostate centroids were 4.06 +/- 0.33 mm and 3.10 +/- 0.43 mm for the first and second test datasets respectively. Moreover, the algorithm provided the centroid within the true prostate volume in 100% of images from both datasets. Obtained results demonstrate high utility of the detection method for a fully automated prostate segmentation.

A Registration Method Based on Contour Point Cloud for 3D Whole-Body PET and CT Images

PubMed Central

Yang, Qiyao; Wang, Zhiguo; Zhang, Guoxu

2017-01-01

The PET and CT fusion image, combining the anatomical and functional information, has important clinical meaning. An effective registration of PET and CT images is the basis of image fusion. This paper presents a multithread registration method based on contour point cloud for 3D whole-body PET and CT images. Firstly, a geometric feature-based segmentation (GFS) method and a dynamic threshold denoising (DTD) method are creatively proposed to preprocess CT and PET images, respectively. Next, a new automated trunk slices extraction method is presented for extracting feature point clouds. Finally, the multithread Iterative Closet Point is adopted to drive an affine transform. We compare our method with a multiresolution registration method based on Mattes Mutual Information on 13 pairs (246~286 slices per pair) of 3D whole-body PET and CT data. Experimental results demonstrate the registration effectiveness of our method with lower negative normalization correlation (NC = −0.933) on feature images and less Euclidean distance error (ED = 2.826) on landmark points, outperforming the source data (NC = −0.496, ED = 25.847) and the compared method (NC = −0.614, ED = 16.085). Moreover, our method is about ten times faster than the compared one. PMID:28316979

Quantification of Fibrosis and Osteosclerosis in Myeloproliferative Neoplasms: A Computer-Assisted Image Study

PubMed Central

Teman, Carolin J.; Wilson, Andrew R.; Perkins, Sherrie L.; Hickman, Kimberly; Prchal, Josef T.; Salama, Mohamed E.

2010-01-01

Evaluation of bone marrow fibrosis and osteosclerosis in myeloproliferative neoplasms (MPN) is subject to interobserver inconsistency. Performance data for currently utilized fibrosis grading systems are lacking, and classification scales for osteosclerosis do not exist. Digital imaging can serve as a quantification method for fibrosis and osteosclerosis. We used digital imaging techniques for trabecular area assessment and reticulin-fiber quantification. Patients with all Philadelphia negative MPN subtypes had higher trabecular volume than controls (p ≤0.0015). Results suggest that the degree of osteosclerosis helps differentiate primary myelofibrosis from other MPN. Numerical quantification of fibrosis highly correlated with subjective scores, and interobserver correlation was satisfactory. Digital imaging provides accurate quantification for osteosclerosis and fibrosis. PMID:20122729

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

Nondestructive, fast, and cost-effective image processing method for roughness measurement of randomly rough metallic surfaces.

PubMed

Ghodrati, Sajjad; Kandi, Saeideh Gorji; Mohseni, Mohsen

2018-06-01

In recent years, various surface roughness measurement methods have been proposed as alternatives to the commonly used stylus profilometry, which is a low-speed, destructive, expensive but precise method. In this study, a novel method, called "image profilometry," has been introduced for nondestructive, fast, and low-cost surface roughness measurement of randomly rough metallic samples based on image processing and machine vision. The impacts of influential parameters such as image resolution and filtering approach for elimination of the long wavelength surface undulations on the accuracy of the image profilometry results have been comprehensively investigated. Ten surface roughness parameters were measured for the samples using both the stylus and image profilometry. Based on the results, the best image resolution was 800 dpi, and the most practical filtering method was Gaussian convolution+cutoff. In these conditions, the best and worst correlation coefficients (R 2 ) between the stylus and image profilometry results were 0.9892 and 0.9313, respectively. Our results indicated that the image profilometry predicted the stylus profilometry results with high accuracy. Consequently, it could be a viable alternative to the stylus profilometry, particularly in online applications.

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.

Quantitative optical scanning tests of complex microcircuits

NASA Technical Reports Server (NTRS)

Erickson, J. J.

1980-01-01

An approach for the development of the optical scanner as a screening inspection instrument for microcircuits involves comparing the quantitative differences in photoresponse images and then correlating them with electrical parameter differences in test devices. The existing optical scanner was modified so that the photoresponse data could be recorded and subsequently digitized. A method was devised for applying digital image processing techniques to the digitized photoresponse data in order to quantitatively compare the data. Electrical tests were performed and photoresponse images were recorded before and following life test intervals on two groups of test devices. Correlations were made between differences or changes in the electrical parameters of the test devices.

Using Spatial Correlations of SPDC Sources for Increasing the Signal to Noise Ratio in Images

NASA Astrophysics Data System (ADS)

Ruíz, A. I.; Caudillo, R.; Velázquez, V. M.; Barrios, E.

2017-05-01

We experimentally show that, by using spatial correlations of photon pairs produced by Spontaneous Parametric Down-Conversion, it is possible to increase the Signal to Noise Ratio in images of objects illuminated with those photons; in comparison, objects illuminated with light from a laser present a minor ratio. Our simple experimental set-up was capable to produce an average improvement in signal to noise ratio of 11dB of Parametric Down-Converted light over laser light. This simple method can be easily implemented for obtaining high contrast images of faint objects and for transmitting information with low noise.

Thermal expansion coefficient determination of polylactic acid using digital image correlation

NASA Astrophysics Data System (ADS)

Botean, Adrian-Ioan

2018-02-01

This paper aims determining the linear thermal expansion coefficient (CTE) of polylactic acid (PLA) using an optical method for measuring deformations called digital image correlation method (DIC). Because PLA is often used in making many pieces with 3D printing technology, it is opportune to know this coefficient to obtain a higher degree of precision in the construction of parts and to monitor deformations when these parts are subjected to a thermal gradient. Are used two PLA discs with 20 and 40% degree of filling. In parallel with this approach was determined the linear thermal expansion coefficient (CTE) for the copper cylinder on the surface of which are placed the two discs of PLA.

A novel Kalman filter based video image processing scheme for two-photon fluorescence microscopy

NASA Astrophysics Data System (ADS)

Sun, Wenqing; Huang, Xia; Li, Chunqiang; Xiao, Chuan; Qian, Wei

2016-03-01

Two-photon fluorescence microscopy (TPFM) is a perfect optical imaging equipment to monitor the interaction between fast moving viruses and hosts. However, due to strong unavoidable background noises from the culture, videos obtained by this technique are too noisy to elaborate this fast infection process without video image processing. In this study, we developed a novel scheme to eliminate background noises, recover background bacteria images and improve video qualities. In our scheme, we modified and implemented the following methods for both host and virus videos: correlation method, round identification method, tree-structured nonlinear filters, Kalman filters, and cell tracking method. After these procedures, most of noises were eliminated and host images were recovered with their moving directions and speed highlighted in the videos. From the analysis of the processed videos, 93% bacteria and 98% viruses were correctly detected in each frame on average.

Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems.

PubMed

Meza, Pablo; Machuca, Guillermo; Torres, Sergio; Martin, Cesar San; Vera, Esteban

2015-07-20

In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the nonuniformity noise sources. We derive an iterative optimization algorithm based on a gradient descent minimization strategy. Results from infrared image sequences corrupted with simulated and real fixed-pattern noise show a competitive performance compared with state-of-the-art methods. A qualitative analysis on the experimental results obtained with images from a variety of infrared cameras indicates that the proposed method provides super-resolution images with significantly less fixed-pattern noise.

Jitter Correction

NASA Technical Reports Server (NTRS)

Waegell, Mordecai J.; Palacios, David M.

2011-01-01

Jitter_Correct.m is a MATLAB function that automatically measures and corrects inter-frame jitter in an image sequence to a user-specified precision. In addition, the algorithm dynamically adjusts the image sample size to increase the accuracy of the measurement. The Jitter_Correct.m function takes an image sequence with unknown frame-to-frame jitter and computes the translations of each frame (column and row, in pixels) relative to a chosen reference frame with sub-pixel accuracy. The translations are measured using a Cross Correlation Fourier transformation method in which the relative phase of the two transformed images is fit to a plane. The measured translations are then used to correct the inter-frame jitter of the image sequence. The function also dynamically expands the image sample size over which the cross-correlation is measured to increase the accuracy of the measurement. This increases the robustness of the measurement to variable magnitudes of inter-frame jitter

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

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.

Left ventricular mass and hypertrophy by echocardiography and cardiac magnetic resonance: the multi-ethnic study of atherosclerosis.

PubMed

Armstrong, Anderson C; Gjesdal, Ola; Almeida, André; Nacif, Marcelo; Wu, Colin; Bluemke, David A; Brumback, Lyndia; Lima, João A C

2014-01-01

Left ventricular mass (LVM) and hypertrophy (LVH) are important parameters, but their use is surrounded by controversies. We compare LVM by echocardiography and cardiac magnetic resonance (CMR), investigating reproducibility aspects and the effect of echocardiography image quality. We also compare indexing methods within and between imaging modalities for classification of LVH and cardiovascular risk. Multi-Ethnic Study of Atherosclerosis enrolled 880 participants in Baltimore city, 146 had echocardiograms and CMR on the same day. LVM was then assessed using standard techniques. Echocardiography image quality was rated (good/limited) according to the parasternal view. LVH was defined after indexing LVM to body surface area, height(1.7) , height(2.7) , or by the predicted LVM from a reference group. Participants were classified for cardiovascular risk according to Framingham score. Pearson's correlation, Bland-Altman plots, percent agreement, and kappa coefficient assessed agreement within and between modalities. Left ventricular mass by echocardiography (140 ± 40 g) and by CMR were correlated (r = 0.8, P < 0.001) regardless of the echocardiography image quality. The reproducibility profile had strong correlations and agreement for both modalities. Image quality groups had similar characteristics; those with good images compared to CMR slightly superiorly. The prevalence of LVH tended to be higher with higher cardiovascular risk. The agreement for LVH between imaging modalities ranged from 77% to 98% and the kappa coefficient from 0.10 to 0.76. Echocardiography has a reliable performance for LVM assessment and classification of LVH, with limited influence of image quality. Echocardiography and CMR differ in the assessment of LVH, and additional differences rise from the indexing methods. © 2013. This article is a U.S. Government work and is in the public domain in the USA.

Assessment of mitral regurgitation in dogs: comparison of results of echocardiography with magnetic resonance imaging.

PubMed

Sargent, J; Connolly, D J; Watts, V; Mõtsküla, P; Volk, H A; Lamb, C R; Fuentes, V Luis

2015-11-01

Echocardiography is used routinely to assess mitral regurgitation severity, but echocardiographic measures of mitral regurgitation in dogs have not been compared with other quantitative methods. The study aim was to compare echocardiographic measures of mitral regurgitation with cardiac magnetic resonance imaging-derived mitral regurgitant fraction in small-breed dogs. Dogs with myxomatous mitral valve disease scheduled for magnetic resonance imaging assessment of neurological disease were recruited. Correlations were tested between cardiac magnetic resonance imaging-derived mitral regurgitant fraction and the following echocardiographic measures: vena contracta/aortic diameter, transmitral E-wave velocity, amplitude of mitral prolapse/aortic diameter, diastolic left ventricular diameter:aortic diameter, left atrium:aortic diameter, mitral regurgitation jet area ratio and regurgitant fraction calculated using the proximal isovelocity surface area method. Measurement of cardiac magnetic resonance imaging-derived mitral regurgitant fraction was attempted in 21 dogs. Twelve consecutive, complete studies were obtained and 10 dogs were included in the final analysis: vena contracta/aortic diameter (r = 0 · 89, p = 0 · 001) and E-wave velocity (r = 0 · 86, p = 0 · 001) had the strongest correlations with cardiac magnetic resonance imaging-derived mitral regurgitant fraction. E velocity had superior repeatability and could be measured in all dogs. The presence of multiple jets precluded vena contracta/aortic diameter measurement in one dog. Measurement of cardiac magnetic resonance imaging-derived mitral regurgitant fraction is feasible but technically demanding. The echocardiographic measures that correlated most closely with cardiac magnetic resonance imaging-derived mitral regurgitant fraction were vena contracta/aortic diameter and E-wave velocity. © 2015 British Small Animal Veterinary Association.

Measurement Consistency from Magnetic Resonance Images

PubMed Central

Chung, Dongjun; Chung, Moo K.; Durtschi, Reid B.; Lindell, R. Gentry; Vorperian, Houri K.

2010-01-01

Rationale and Objectives In quantifying medical images, length-based measurements are still obtained manually. Due to possible human error, a measurement protocol is required to guarantee the consistency of measurements. In this paper, we review various statistical techniques that can be used in determining measurement consistency. The focus is on detecting a possible measurement bias and determining the robustness of the procedures to outliers. Materials and Methods We review correlation analysis, linear regression, Bland-Altman method, paired t-test, and analysis of variance (ANOVA). These techniques were applied to measurements, obtained by two raters, of head and neck structures from magnetic resonance images (MRI). Results The correlation analysis and the linear regression were shown to be insufficient for detecting measurement inconsistency. They are also very sensitive to outliers. The widely used Bland-Altman method is a visualization technique so it lacks the numerical quantification. The paired t-test tends to be sensitive to small measurement bias. On the other hand, ANOVA performs well even under small measurement bias. Conclusion In almost all cases, using only one method is insufficient and it is recommended to use several methods simultaneously. In general, ANOVA performs the best. PMID:18790405

Multiple-image authentication with a cascaded multilevel architecture based on amplitude field random sampling and phase information multiplexing.

PubMed

Fan, Desheng; Meng, Xiangfeng; Wang, Yurong; Yang, Xiulun; Pan, Xuemei; Peng, Xiang; He, Wenqi; Dong, Guoyan; Chen, Hongyi

2015-04-10

A multiple-image authentication method with a cascaded multilevel architecture in the Fresnel domain is proposed, in which a synthetic encoded complex amplitude is first fabricated, and its real amplitude component is generated by iterative amplitude encoding, random sampling, and space multiplexing for the low-level certification images, while the phase component of the synthetic encoded complex amplitude is constructed by iterative phase information encoding and multiplexing for the high-level certification images. Then the synthetic encoded complex amplitude is iteratively encoded into two phase-type ciphertexts located in two different transform planes. During high-level authentication, when the two phase-type ciphertexts and the high-level decryption key are presented to the system and then the Fresnel transform is carried out, a meaningful image with good quality and a high correlation coefficient with the original certification image can be recovered in the output plane. Similar to the procedure of high-level authentication, in the case of low-level authentication with the aid of a low-level decryption key, no significant or meaningful information is retrieved, but it can result in a remarkable peak output in the nonlinear correlation coefficient of the output image and the corresponding original certification image. Therefore, the method realizes different levels of accessibility to the original certification image for different authority levels with the same cascaded multilevel architecture.

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

Digital image analysis to quantify carbide networks in ultrahigh carbon steels

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

Hecht, Matthew D.; Webler, Bryan A.; Picard, Yoosuf N., E-mail: ypicard@cmu.edu

A method has been developed and demonstrated to quantify the degree of carbide network connectivity in ultrahigh carbon steels through digital image processing and analysis of experimental micrographs. It was shown that the network connectivity and carbon content can be correlated to toughness for various ultrahigh carbon steel specimens. The image analysis approach first involved segmenting the carbide network and pearlite matrix into binary contrast representations via a grayscale intensity thresholding operation. Next, the carbide network pixels were skeletonized and parceled into braches and nodes, allowing the determination of a connectivity index for the carbide network. Intermediate image processing stepsmore » to remove noise and fill voids in the network are also detailed. The connectivity indexes of scanning electron micrographs were consistent in both secondary and backscattered electron imaging modes, as well as across two different (50 × and 100 ×) magnifications. Results from ultrahigh carbon steels reported here along with other results from the literature generally showed lower connectivity indexes correlated with higher Charpy impact energy (toughness). A deviation from this trend was observed at higher connectivity indexes, consistent with a percolation threshold for crack propagation across the carbide network. - Highlights: • A method for carbide network analysis in steels is proposed and demonstrated. • ImageJ method extracts a network connectivity index from micrographs. • Connectivity index consistent in different imaging conditions and magnifications. • Impact energy may plateau when a critical network connectivity is exceeded.« less

The Webcam system: a simple, automated, computer-based video system for quantitative measurement of movement in nonhuman primates.

PubMed

Togasaki, Daniel M; Hsu, Albert; Samant, Meghana; Farzan, Bijan; DeLanney, Louis E; Langston, J William; Di Monte, Donato A; Quik, Maryka

2005-06-30

Investigations using models of neurologic disease frequently involve quantifying animal motor activity. We developed a simple method for measuring motor activity using a computer-based video system (the Webcam system) consisting of an inexpensive video camera connected to a personal computer running customized software. Images of the animals are captured at half-second intervals and movement is quantified as the number of pixel changes between consecutive images. The Webcam system allows measurement of motor activity of the animals in their home cages, without devices affixed to their bodies. Webcam quantification of movement was validated by correlation with measures simultaneously obtained by two other methods: measurement of locomotion by interruption of infrared beams; and measurement of general motor activity using portable accelerometers. In untreated squirrel monkeys, correlations of Webcam and locomotor activity exceeded 0.79, and correlations with general activity counts exceeded 0.65. Webcam activity decreased after the monkeys were rendered parkinsonian by treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), but the correlations with the other measures of motor activity were maintained. Webcam activity also correlated with clinical ratings of parkinsonism. These results indicate that the Webcam system is reliable under both untreated and experimental conditions and is an excellent method for quantifying motor activity in animals.

Improving Signal-to-Noise Ratio in Scanning Transmission Electron Microscopy Energy-Dispersive X-Ray (STEM-EDX) Spectrum Images Using Single-Atomic-Column Cross-Correlation Averaging.

PubMed

Jeong, Jong Seok; Mkhoyan, K Andre

2016-06-01

Acquiring an atomic-resolution compositional map of crystalline specimens has become routine practice, thus opening possibilities for extracting subatomic information from such maps. A key challenge for achieving subatomic precision is the improvement of signal-to-noise ratio (SNR) of compositional maps. Here, we report a simple and reliable solution for achieving high-SNR energy-dispersive X-ray (EDX) spectroscopy spectrum images for individual atomic columns. The method is based on standard cross-correlation aided by averaging of single-column EDX maps with modifications in the reference image. It produces EDX maps with minimal specimen drift, beam drift, and scan distortions. Step-by-step procedures to determine a self-consistent reference map with a discussion on the reliability, stability, and limitations of the method are presented here.

Cherenkov imaging method for rapid optimization of clinical treatment geometry in total skin electron beam therapy

PubMed Central

Zhang, Rongxiao; Gladstone, David J.; Williams, Benjamin B.; Glaser, Adam K.; Pogue, Brian W.; Jarvis, Lesley A.

2016-01-01

Purpose: A method was developed utilizing Cherenkov imaging for rapid and thorough determination of the two gantry angles that produce the most uniform treatment plane during dual-field total skin electron beam therapy (TSET). Methods: Cherenkov imaging was implemented to gather 2D measurements of relative surface dose from 6 MeV electron beams on a white polyethylene sheet. An intensified charge-coupled device camera time-gated to the Linac was used for Cherenkov emission imaging at sixty-two different gantry angles (1° increments, from 239.5° to 300.5°). Following a modified Stanford TSET technique, which uses two fields per patient position for full body coverage, composite images were created as the sum of two beam images on the sheet; each angle pair was evaluated for minimum variation across the patient region of interest. Cherenkov versus dose correlation was verified with ionization chamber measurements. The process was repeated at source to surface distance (SSD) = 441, 370.5, and 300 cm to determine optimal angle spread for varying room geometries. In addition, three patients receiving TSET using a modified Stanford six-dual field technique with 6 MeV electron beams at SSD = 441 cm were imaged during treatment. Results: As in previous studies, Cherenkov intensity was shown to directly correlate with dose for homogenous flat phantoms (R2 = 0.93), making Cherenkov imaging an appropriate candidate to assess and optimize TSET setup geometry. This method provided dense 2D images allowing 1891 possible treatment geometries to be comprehensively analyzed from one data set of 62 single images. Gantry angles historically used for TSET at their institution were 255.5° and 284.5° at SSD = 441 cm; however, the angles optimized for maximum homogeneity were found to be 252.5° and 287.5° (+6° increase in angle spread). Ionization chamber measurements confirmed improvement in dose homogeneity across the treatment field from a range of 24.4% at the initial angles, to only 9.8% with the angles optimized. A linear relationship between angle spread and SSD was observed, ranging from 35° at 441 cm, to 39° at 300 cm, with no significant variation in percent-depth dose at midline (R2 = 0.998). For patient studies, factors influencing in vivo correlation between Cherenkov intensity and measured surface dose are still being investigated. Conclusions: Cherenkov intensity correlates to relative dose measured at depth of maximum dose in a uniform, flat phantom. Imaging of phantoms can thus be used to analyze and optimize TSET treatment geometry more extensively and rapidly than thermoluminescent dosimeters or ionization chambers. This work suggests that there could be an expanded role for Cherenkov imaging as a tool to efficiently improve treatment protocols and as a potential verification tool for routine monitoring of unique patient treatments. PMID:26843259

Cherenkov imaging method for rapid optimization of clinical treatment geometry in total skin electron beam therapy

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

Andreozzi, Jacqueline M., E-mail: Jacqueline.M.Andreozzi.th@dartmouth.edu, E-mail: Lesley.A.Jarvis@hitchcock.org; Glaser, Adam K.; Zhang, Rongxiao

2016-02-15

Purpose: A method was developed utilizing Cherenkov imaging for rapid and thorough determination of the two gantry angles that produce the most uniform treatment plane during dual-field total skin electron beam therapy (TSET). Methods: Cherenkov imaging was implemented to gather 2D measurements of relative surface dose from 6 MeV electron beams on a white polyethylene sheet. An intensified charge-coupled device camera time-gated to the Linac was used for Cherenkov emission imaging at sixty-two different gantry angles (1° increments, from 239.5° to 300.5°). Following a modified Stanford TSET technique, which uses two fields per patient position for full body coverage, compositemore » images were created as the sum of two beam images on the sheet; each angle pair was evaluated for minimum variation across the patient region of interest. Cherenkov versus dose correlation was verified with ionization chamber measurements. The process was repeated at source to surface distance (SSD) = 441, 370.5, and 300 cm to determine optimal angle spread for varying room geometries. In addition, three patients receiving TSET using a modified Stanford six-dual field technique with 6 MeV electron beams at SSD = 441 cm were imaged during treatment. Results: As in previous studies, Cherenkov intensity was shown to directly correlate with dose for homogenous flat phantoms (R{sup 2} = 0.93), making Cherenkov imaging an appropriate candidate to assess and optimize TSET setup geometry. This method provided dense 2D images allowing 1891 possible treatment geometries to be comprehensively analyzed from one data set of 62 single images. Gantry angles historically used for TSET at their institution were 255.5° and 284.5° at SSD = 441 cm; however, the angles optimized for maximum homogeneity were found to be 252.5° and 287.5° (+6° increase in angle spread). Ionization chamber measurements confirmed improvement in dose homogeneity across the treatment field from a range of 24.4% at the initial angles, to only 9.8% with the angles optimized. A linear relationship between angle spread and SSD was observed, ranging from 35° at 441 cm, to 39° at 300 cm, with no significant variation in percent-depth dose at midline (R{sup 2} = 0.998). For patient studies, factors influencing in vivo correlation between Cherenkov intensity and measured surface dose are still being investigated. Conclusions: Cherenkov intensity correlates to relative dose measured at depth of maximum dose in a uniform, flat phantom. Imaging of phantoms can thus be used to analyze and optimize TSET treatment geometry more extensively and rapidly than thermoluminescent dosimeters or ionization chambers. This work suggests that there could be an expanded role for Cherenkov imaging as a tool to efficiently improve treatment protocols and as a potential verification tool for routine monitoring of unique patient treatments.« less

Respiratory motion compensation algorithm of ultrasound hepatic perfusion data acquired in free-breathing

NASA Astrophysics Data System (ADS)

Wu, Kaizhi; Zhang, Xuming; Chen, Guangxie; Weng, Fei; Ding, Mingyue

2013-10-01

Images acquired in free breathing using contrast enhanced ultrasound exhibit a periodic motion that needs to be compensated for if a further accurate quantification of the hepatic perfusion analysis is to be executed. In this work, we present an algorithm to compensate the respiratory motion by effectively combining the PCA (Principal Component Analysis) method and block matching method. The respiratory kinetics of the ultrasound hepatic perfusion image sequences was firstly extracted using the PCA method. Then, the optimal phase of the obtained respiratory kinetics was detected after normalizing the motion amplitude and determining the image subsequences of the original image sequences. The image subsequences were registered by the block matching method using cross-correlation as the similarity. Finally, the motion-compensated contrast images can be acquired by using the position mapping and the algorithm was evaluated by comparing the TICs extracted from the original image sequences and compensated image subsequences. Quantitative comparisons demonstrated that the average fitting error estimated of ROIs (region of interest) was reduced from 10.9278 +/- 6.2756 to 5.1644 +/- 3.3431 after compensating.

Image denoising by exploring external and internal correlations.

PubMed

Yue, Huanjing; Sun, Xiaoyan; Yang, Jingyu; Wu, Feng

2015-06-01

Single image denoising suffers from limited data collection within a noisy image. In this paper, we propose a novel image denoising scheme, which explores both internal and external correlations with the help of web images. For each noisy patch, we build internal and external data cubes by finding similar patches from the noisy and web images, respectively. We then propose reducing noise by a two-stage strategy using different filtering approaches. In the first stage, since the noisy patch may lead to inaccurate patch selection, we propose a graph based optimization method to improve patch matching accuracy in external denoising. The internal denoising is frequency truncation on internal cubes. By combining the internal and external denoising patches, we obtain a preliminary denoising result. In the second stage, we propose reducing noise by filtering of external and internal cubes, respectively, on transform domain. In this stage, the preliminary denoising result not only enhances the patch matching accuracy but also provides reliable estimates of filtering parameters. The final denoising image is obtained by fusing the external and internal filtering results. Experimental results show that our method constantly outperforms state-of-the-art denoising schemes in both subjective and objective quality measurements, e.g., it achieves >2 dB gain compared with BM3D at a wide range of noise levels.

The analysis of image feature robustness using cometcloud

PubMed Central

Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

2012-01-01

The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval. PMID:23248759

Rapid Extraction of Landslide and Spatial Distribution Analysis after Jiuzhaigou Ms7.0 Earthquake Based on Uav Images

NASA Astrophysics Data System (ADS)

Jiao, Q. S.; Luo, Y.; Shen, W. H.; Li, Q.; Wang, X.

2018-04-01

Jiuzhaigou earthquake led to the collapse of the mountains and formed lots of landslides in Jiuzhaigou scenic spot and surrounding roads which caused road blockage and serious ecological damage. Due to the urgency of the rescue, the authors carried unmanned aerial vehicle (UAV) and entered the disaster area as early as August 9 to obtain the aerial images near the epicenter. On the basis of summarizing the earthquake landslides characteristics in aerial images, by using the object-oriented analysis method, landslides image objects were obtained by multi-scale segmentation, and the feature rule set of each level was automatically built by SEaTH (Separability and Thresholds) algorithm to realize the rapid landslide extraction. Compared with visual interpretation, object-oriented automatic landslides extraction method achieved an accuracy of 94.3 %. The spatial distribution of the earthquake landslide had a significant positive correlation with slope and relief and had a negative correlation with the roughness, but no obvious correlation with the aspect. The relationship between the landslide and the aspect was not found and the probable reason may be that the distance between the study area and the seismogenic fault was too far away. This work provided technical support for the earthquake field emergency, earthquake landslide prediction and disaster loss assessment.

Digital Image Correlation from Commercial to FOS Software: a Mature Technique for Full-Field Displacement Measurements

NASA Astrophysics Data System (ADS)

Belloni, V.; Ravanelli, R.; Nascetti, A.; Di Rita, M.; Mattei, D.; Crespi, M.

2018-05-01

In the last few decades, there has been a growing interest in studying non-contact methods for full-field displacement and strain measurement. Among such techniques, Digital Image Correlation (DIC) has received particular attention, thanks to its ability to provide these information by comparing digital images of a sample surface before and after deformation. The method is now commonly adopted in the field of civil, mechanical and aerospace engineering and different companies and some research groups implemented 2D and 3D DIC software. In this work a review on DIC software status is given at first. Moreover, a free and open source 2D DIC software is presented, named py2DIC and developed in Python at the Geodesy and Geomatics Division of DICEA of the University of Rome "La Sapienza"; its potentialities were evaluated by processing the images captured during tensile tests performed in the Structural Engineering Lab of the University of Rome "La Sapienza" and comparing them to those obtained using the commercial software Vic-2D developed by Correlated Solutions Inc, USA. The agreement of these results at one hundredth of millimetre level demonstrate the possibility to use this open source software as a valuable 2D DIC tool to measure full-field displacements on the investigated sample surface.

Statistical framework and noise sensitivity of the amplitude radial correlation contrast method.

PubMed

Kipervaser, Zeev Gideon; Pelled, Galit; Goelman, Gadi

2007-09-01

A statistical framework for the amplitude radial correlation contrast (RCC) method, which integrates a conventional pixel threshold approach with cluster-size statistics, is presented. The RCC method uses functional MRI (fMRI) data to group neighboring voxels in terms of their degree of temporal cross correlation and compares coherences in different brain states (e.g., stimulation OFF vs. ON). By defining the RCC correlation map as the difference between two RCC images, the map distribution of two OFF states is shown to be normal, enabling the definition of the pixel cutoff. The empirical cluster-size null distribution obtained after the application of the pixel cutoff is used to define a cluster-size cutoff that allows 5% false positives. Assuming that the fMRI signal equals the task-induced response plus noise, an analytical expression of amplitude-RCC dependency on noise is obtained and used to define the pixel threshold. In vivo and ex vivo data obtained during rat forepaw electric stimulation are used to fine-tune this threshold. Calculating the spatial coherences within in vivo and ex vivo images shows enhanced coherence in the in vivo data, but no dependency on the anesthesia method, magnetic field strength, or depth of anesthesia, strengthening the generality of the proposed cutoffs. Copyright (c) 2007 Wiley-Liss, Inc.

Correlation time and diffusion coefficient imaging: application to a granular flow system.

PubMed

Caprihan, A; Seymour, J D

2000-05-01

A parametric method for spatially resolved measurements for velocity autocorrelation functions, R(u)(tau) = , expressed as a sum of exponentials, is presented. The method is applied to a granular flow system of 2-mm oil-filled spheres rotated in a half-filled horizontal cylinder, which is an Ornstein-Uhlenbeck process with velocity autocorrelation function R(u)(tau) = e(- ||tau ||/tau(c)), where tau(c) is the correlation time and D = tau(c) is the diffusion coefficient. The pulsed-field-gradient NMR method consists of applying three different gradient pulse sequences of varying motion sensitivity to distinguish the range of correlation times present for particle motion. Time-dependent apparent diffusion coefficients are measured for these three sequences and tau(c) and D are then calculated from the apparent diffusion coefficient images. For the cylinder rotation rate of 2.3 rad/s, the axial diffusion coefficient at the top center of the free surface was 5.5 x 10(-6) m(2)/s, the correlation time was 3 ms, and the velocity fluctuation or granular temperature was 1.8 x 10(-3) m(2)/s(2). This method is also applicable to study transport in systems involving turbulence and porous media flows. Copyright 2000 Academic Press.

Cross-correlation analysis of pulse wave propagation in arteries: in vitro validation and in vivo feasibility.

PubMed

Nauleau, Pierre; Apostolakis, Iason; McGarry, Matthew; Konofagou, Elisa

2018-05-29

The stiffness of the arteries is known to be an indicator of the progression of various cardiovascular diseases. Clinically, the pulse wave velocity (PWV) is used as a surrogate for arterial stiffness. Pulse wave imaging (PWI) is a non-invasive, ultrasound-based imaging technique capable of mapping the motion of the vessel walls, allowing the local assessment of arterial properties. Conventionally, a distinctive feature of the displacement wave (e.g. the 50% upstroke) is tracked across the map to estimate the PWV. However, the presence of reflections, such as those generated at the carotid bifurcation, can bias the PWV estimation. In this paper, we propose a two-step cross-correlation based method to characterize arteries using the information available in the PWI spatio-temporal map. First, the area under the cross-correlation curve is proposed as an index for locating the regions of different properties. Second, a local peak of the cross-correlation function is tracked to obtain a less biased estimate of the PWV. Three series of experiments were conducted in phantoms to evaluate the capabilities of the proposed method compared with the conventional method. In the ideal case of a homogeneous phantom, the two methods performed similarly and correctly estimated the PWV. In the presence of reflections, the proposed method provided a more accurate estimate than conventional processing: e.g. for the soft phantom, biases of  -0.27 and -0.71 m · s -1 were observed. In a third series of experiments, the correlation-based method was able to locate two regions of different properties with an error smaller than 1 mm. It also provided more accurate PWV estimates than conventional processing (biases:  -0.12 versus -0.26 m · s -1 ). Finally, the in vivo feasibility of the proposed method was demonstrated in eleven healthy subjects. The results indicate that the correlation-based method might be less precise in vivo but more accurate than the conventional method.

Effect of the image resolution on the statistical descriptors of heterogeneous media.

PubMed

Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

2018-02-01

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

Effect of the image resolution on the statistical descriptors of heterogeneous media

NASA Astrophysics Data System (ADS)

Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

2018-02-01

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

Single shot imaging through turbid medium and around corner using coherent light

NASA Astrophysics Data System (ADS)

Li, Guowei; Li, Dayan; Situ, Guohai

2018-01-01

Optical imaging through turbid media and around corner is a difficult challenge. Even a very thin layer of a turbid media, which randomly scatters the probe light, can appear opaque and hide any objects behind it. Despite many recent advances, no current method can image the object behind turbid media with single record using coherent laser illumination. Here we report a method that allows non-invasive single-shot optical imaging through turbid media and around corner via speckle correlation. Instead of being as an obstacle in forming diffractionlimited images, speckle actually can be a carrier that encodes sufficient information to imaging through visually opaque layers. Optical imaging through turbid media and around corner is experimentally demonstrated using traditional imaging system with the aid of iterative phase retrieval algorithm. Our method require neither scan of illumination nor two-arm interferometry or long-time exposure in acquisition, which has new implications in optical sensing through common obscurants such as fog, smoke and haze.

Innovative approach for in-vivo ablation validation on multimodal images

NASA Astrophysics Data System (ADS)

Shahin, O.; Karagkounis, G.; Carnegie, D.; Schlaefer, A.; Boctor, E.

2014-03-01

Radiofrequency ablation (RFA) is an important therapeutic procedure for small hepatic tumors. To make sure that the target tumor is effectively treated, RFA monitoring is essential. While several imaging modalities can observe the ablation procedure, it is not clear how ablated lesions on the images correspond to actual necroses. This uncertainty contributes to the high local recurrence rates (up to 55%) after radiofrequency ablative therapy. This study investigates a novel approach to correlate images of ablated lesions with actual necroses. We mapped both intraoperative images of the lesion and a slice through the actual necrosis in a common reference frame. An electromagnetic tracking system was used to accurately match lesion slices from different imaging modalities. To minimize the liver deformation effect, the tracking reference frame was defined inside the tissue by anchoring an electromagnetic sensor adjacent to the lesion. A validation test was performed using a phantom and proved that the end-to-end accuracy of the approach was within 2mm. In an in-vivo experiment, intraoperative magnetic resonance imaging (MRI) and ultrasound (US) ablation images were correlated to gross and histopathology. The results indicate that the proposed method can accurately correlate invivo ablations on different modalities. Ultimately, this will improve the interpretation of the ablation monitoring and reduce the recurrence rates associated with RFA.

In Vivo High-Frequency Contrast-Enhanced Ultrasonography of Choroidal Melanoma in Rabbits: Imaging Features and Histopathologic Correlations

PubMed Central

Kang, Shin J.; Zhang, Qing; Patel, Samirkumar R.; Berezovsky, Damian; Yang, Hua; Wang, Yanggan; Grossniklaus, Hans E.

2013-01-01

Purpose To evaluate the utility of in vivo imaging of rabbit model of choroidal melanoma utilizing high-frequency contrast-enhanced ultrasound (HF-CE-US) with 2-or 3-dimensional modes, and to correlate the sonographic findings with histopathologic characteristics. Methods Five New Zealand white rabbits which were immunosuppressed with daily cyclosporin A were inoculated into their right eyes with aliquots of 1.5×106 / 50 µL of 92.1 human uveal melanoma cells cultured in RPMI. At week 4, the tumor-bearing eyes were imaged using high-frequency ultrasound with microbubble contrast agent to determine the 2-dimensional tumor size and relative blood volume and by 3-dimensional mode to determine tumor volume. Histologic tumor burden was quantified in enucleated eyes by ImageJ software, and microvascular density (MVD) was determined by counting vascular channels in PAS without hematoxylin sections. Results Utilizing HF-CE-US, melanomas were visualized as relatively hyperechoic regions in the images. The correlation coefficients of sonographic size or volume compared with histologic area were 0.72 and 0.70, respectively. The sonographic tumor relative blood volume correlated with the histologic tumor vascularity (R2=0.92, P=0.04) Conclusions There is a positive correlation between in vivo sonographic tumor volume/size and histologic tumor size in our rabbit choroidal melanoma model. HF-CE-US corresponds to microvascular density and blood volume. PMID:23645822

Contrast Enhanced Maximum Intensity Projection Ultrasound Imaging for Assessing Angiogenesis in Murine Glioma and Breast Tumor Models: A Comparative Study

PubMed Central

Forsberg, Flemming; Ro, Raymond J.; Fox, Traci B; Liu, Ji-Bin; Chiou, See-Ying; Potoczek, Magdalena; Goldberg, Barry B

2010-01-01

The purpose of this study was to prospectively compare noninvasive, quantitative measures of vascularity obtained from 4 contrast enhanced ultrasound (US) techniques to 4 invasive immunohistochemical markers of tumor angiogenesis in a large group of murine xenografts. Glioma (C6) or breast cancer (NMU) cells were implanted in 144 rats. The contrast agent Optison (GE Healthcare, Princeton, NJ) was injected in a tail vein (dose: 0.4ml/kg). Power Doppler imaging (PDI), pulse-subtraction harmonic imaging (PSHI), flash-echo imaging (FEI), and Microflow imaging (MFI; a technique creating maximum intensity projection images over time) was performed with an Aplio scanner (Toshiba America Medical Systems, Tustin, CA) and a 7.5 MHz linear array. Fractional tumor neovascularity was calculated from digital clips of contrast US, while the relative area stained was calculated from specimens. Results were compared using a factorial, repeated measures ANOVA, linear regression and z-tests. The tortuous morphology of tumor neovessels was visualized better with MFI than with the other US modes. Cell line, implantation method and contrast US imaging technique were significant parameters in the ANOVA model (p<0.05). The strongest correlation determined by linear regression in the C6 model was between PSHI and percent area stained with CD31 (r=0.37, p<0.0001). In the NMU model the strongest correlation was between FEI and COX-2 (r=0.46, p<0.0001). There were no statistically significant differences between correlations obtained with the various US methods (p>0.05). In conclusion, the largest study of contrast US of murine xenografts to date has been conducted and quantitative contrast enhanced US measures of tumor neovascularity in glioma and breast cancer xenograft models appear to provide a noninvasive marker for angiogenesis; although the best method for monitoring angiogenesis was not conclusively established. PMID:21144542

Constraints as a destriping tool for Hires images

NASA Technical Reports Server (NTRS)

Cao, YU; Prince, Thomas A.

1994-01-01

Images produced from the Maximum Correlation Method sometimes suffer from visible striping artifacts, especially for areas of extended sources. Possible causes are different baseline levels and calibration errors in the detectors. We incorporated these factors into the MCM algorithm, and tested the effects of different constraints on the output image. The result shows significant visual improvement over the standard MCM Method. In some areas the new images show intelligible structures that are otherwise corrupted by striping artifacts, and the removal of these artifacts could enhance performance of object classification algorithms. The constraints were also tested on low surface brightness areas, and were found to be effective in reducing the noise level.

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.

Refraction-based X-ray Computed Tomography for Biomedical Purpose Using Dark Field Imaging Method

NASA Astrophysics Data System (ADS)

Sunaguchi, Naoki; Yuasa, Tetsuya; Huo, Qingkai; Ichihara, Shu; Ando, Masami

We have proposed a tomographic x-ray imaging system using DFI (dark field imaging) optics along with a data-processing method to extract information on refraction from the measured intensities, and a reconstruction algorithm to reconstruct a refractive-index field from the projections generated from the extracted refraction information. The DFI imaging system consists of a tandem optical system of Bragg- and Laue-case crystals, a positioning device system for a sample, and two CCD (charge coupled device) cameras. Then, we developed a software code to simulate the data-acquisition, data-processing, and reconstruction methods to investigate the feasibility of the proposed methods. Finally, in order to demonstrate its efficacy, we imaged a sample with DCIS (ductal carcinoma in situ) excised from a breast cancer patient using a system constructed at the vertical wiggler beamline BL-14C in KEK-PF. Its CT images depicted a variety of fine histological structures, such as milk ducts, duct walls, secretions, adipose and fibrous tissue. They correlate well with histological sections.

A systematic desaturation method for images from the Atmospheric Imaging Assembly in the Solar Dynamics Observatory.

NASA Astrophysics Data System (ADS)

Torre, Gabriele; Schwartz, Richard; Piana, Michele; Massone, Anna Maria; Benvenuto, Federico

2016-05-01

The fine spatial resolution of the SDO AIA CCD's is often destroyed by the charge in saturated pixels overflowing into a swath of neighboring cells during fast rising solar flares. Automated exposure control can only mitigate this issue to a degree and it has other deleterious effects. Our method addresses the desaturation problem for AIA images as an image reconstruction problem in which the information content of the diffraction fringes, generated by the interaction between the incoming radiation and the hardware of the spacecraft, is exploited to recover the true image intensities within the primary saturated core of the image. This methodology takes advantage of some well defined techniques like cross-correlation and the Expectation Maximization method to invert the direct relation between the diffraction fringes intensities and the true flux intensities. During this talk a complete overview on the structure of the method will be provided, besides some reliability tests obtained by its application against synthetic and real data.

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...

Robust fluoroscopic respiratory gating for lung cancer radiotherapy without implanted fiducial markers

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Sharp, Greg C.; Alexander, Brian; Jiang, Steve B.

2007-02-01

For gated lung cancer radiotherapy, it is difficult to generate accurate gating signals due to the large uncertainties when using external surrogates and the risk of pneumothorax when using implanted fiducial markers. We have previously investigated and demonstrated the feasibility of generating gating signals using the correlation scores between the reference template image and the fluoroscopic images acquired during the treatment. In this paper, we present an in-depth study, aiming at the improvement of robustness of the algorithm and its validation using multiple sets of patient data. Three different template generating and matching methods have been developed and evaluated: (1) single template method, (2) multiple template method, and (3) template clustering method. Using the fluoroscopic data acquired during patient setup before each fraction of treatment, reference templates are built that represent the tumour position and shape in the gating window, which is assumed to be at the end-of-exhale phase. For the single template method, all the setup images within the gating window are averaged to generate a composite template. For the multiple template method, each setup image in the gating window is considered as a reference template and used to generate an ensemble of correlation scores. All the scores are then combined to generate the gating signal. For the template clustering method, clustering (grouping of similar objects together) is performed to reduce the large number of reference templates into a few representative ones. Each of these methods has been evaluated against the reference gating signal as manually determined by a radiation oncologist. Five patient datasets were used for evaluation. In each case, gated treatments were simulated at both 35% and 50% duty cycles. False positive, negative and total error rates were computed. Experiments show that the single template method is sensitive to noise; the multiple template and clustering methods are more robust to noise due to the smoothing effect of aggregation of correlation scores; and the clustering method results in the best performance in terms of computational efficiency and accuracy.

Subresolution Displacements in Finite Difference Simulations of Ultrasound Propagation and Imaging.

PubMed

Pinton, Gianmarco F

2017-03-01

Time domain finite difference simulations are used extensively to simulate wave propagation. They approximate the wave field on a discrete domain with a grid spacing that is typically on the order of a tenth of a wavelength. The smallest displacements that can be modeled by this type of simulation are thus limited to discrete values that are integer multiples of the grid spacing. This paper presents a method to represent continuous and subresolution displacements by varying the impedance of individual elements in a multielement scatterer. It is demonstrated that this method removes the limitations imposed by the discrete grid spacing by generating a continuum of displacements as measured by the backscattered signal. The method is first validated on an ideal perfect correlation case with a single scatterer. It is subsequently applied to a more complex case with a field of scatterers that model an acoustic radiation force-induced displacement used in ultrasound elasticity imaging. A custom finite difference simulation tool is used to simulate propagation from ultrasound imaging pulses in the scatterer field. These simulated transmit-receive events are then beamformed into images, which are tracked with a correlation-based algorithm to determine the displacement. A linear predictive model is developed to analytically describe the relationship between element impedance and backscattered phase shift. The error between model and simulation is λ/ 1364 , where λ is the acoustical wavelength. An iterative method is also presented that reduces the simulation error to λ/ 5556 over one iteration. The proposed technique therefore offers a computationally efficient method to model continuous subresolution displacements of a scattering medium in ultrasound imaging. This method has applications that include ultrasound elastography, blood flow, and motion tracking. This method also extends generally to finite difference simulations of wave propagation, such as electromagnetic or seismic waves.

Correlation Between Contrast Time-Density Time on Digital Subtraction Angiography and Flow: An in Vitro Study.

PubMed

Brunozzi, Denise; Shakur, Sophia F; Ismail, Rahim; Linninger, Andreas; Hsu, Chih-Yang; Charbel, Fady T; Alaraj, Ali

2018-02-01

Digital subtraction angiography (DSA) provides an excellent anatomic characterization of cerebral vasculature, but hemodynamic assessment is often qualitative and subjective. Various clinical algorithms have been produced to semiquantify flow from the data obtained from DSA, but few have tested them against reliable flow values. An arched flow model was created and injected with contrast material. Seventeen injections were acquired in anterior-posterior and lateral DSA projections, and 4 injections were acquired in oblique projection. Image intensity change over the angiogram cycle of each DSA run was analyzed through a custom MATLAB code. Time-density plots obtained were divided into 3 components (time-density times, TDTs): TDT 10%-100% (time needed for contrast material to change image intensity from 10% to 100%), TDT 100%-10% (time needed for contrast material to change image intensity from 100% to 10%), and TDT 25%-25% (time needed for contrast material to change from 25% image intensity to 25%). Time-density index (TDI) was defined as model cross-sectional area to TDT ratio, and it was measured against different flow rates. TDI 10%-100% , TDI 100%-10% , and TDI 25%-25% all correlated significantly with flow (P < 0.001). TDI 10%-100% , TDI 100%-10% , and TDI 25%-25% showed, respectively, a correlation coefficient of 0.91, 0.91, and 0.97 in the anterior-posterior DSA projections (P < 0.001). In the lateral DSA projection, TDI 100%-10% showed a weaker correlation (r = 0.57; P = 0.03). Also in the oblique DSA projection, TDIs correlated significantly with flow. TDI on DSA correlates significantly with flow. Although in vitro studies might overlook conditions that occur in patients, this method appears to correlate with the flow and could offer a semiquantitative method to evaluate the cerebral blood flow. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

Compression of hyper-spectral images using an accelerated nonnegative tensor decomposition

NASA Astrophysics Data System (ADS)

Li, Jin; Liu, Zilong

2017-12-01

Nonnegative tensor Tucker decomposition (NTD) in a transform domain (e.g., 2D-DWT, etc) has been used in the compression of hyper-spectral images because it can remove redundancies between spectrum bands and also exploit spatial correlations of each band. However, the use of a NTD has a very high computational cost. In this paper, we propose a low complexity NTD-based compression method of hyper-spectral images. This method is based on a pair-wise multilevel grouping approach for the NTD to overcome its high computational cost. The proposed method has a low complexity under a slight decrease of the coding performance compared to conventional NTD. We experimentally confirm this method, which indicates that this method has the less processing time and keeps a better coding performance than the case that the NTD is not used. The proposed approach has a potential application in the loss compression of hyper-spectral or multi-spectral images

Comparing synthetic imagery with real imagery for visible signature analysis: human observer results

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.; Richards, Noel; Madden, Christopher S.; Winter, Neal; Wheaton, Vivienne C.

2017-10-01

Synthetic imagery could potentially enhance visible signature analysis by providing a wider range of target images in differing environmental conditions than would be feasible to collect in field trials. Achieving this requires a method for generating synthetic imagery that is both verified to be realistic and produces the same visible signature analysis results as real images. Is target detectability as measured by image metrics the same for real images and synthetic images of the same scene? Is target detectability as measured by human observer trials the same for real images and synthetic images of the same scene, and how realistic do the synthetic images need to be? In this paper we present the results of a small scale exploratory study on the second question: a photosimulation experiment conducted using digital photographs and synthetic images generated of the same scene. Two sets of synthetic images were created: a high fidelity set created using an image generation tool, E-on Vue, and a low fidelity set created using a gaming engine, Unity 3D. The target detection results obtained using digital photographs were compared with those obtained using the two sets of synthetic images. There was a moderate correlation between the high fidelity synthetic image set and the real images in both the probability of correct detection (Pd: PCC = 0.58, SCC = 0.57) and mean search time (MST: PCC = 0.63, SCC = 0.61). There was no correlation between the low fidelity synthetic image set and the real images for the Pd, but a moderate correlation for MST (PCC = 0.67, SCC = 0.55).

Influence of the quality of intraoperative fluoroscopic images on the spatial positioning accuracy of a CAOS system.

PubMed

Wang, Junqiang; Wang, Yu; Zhu, Gang; Chen, Xiangqian; Zhao, Xiangrui; Qiao, Huiting; Fan, Yubo

2018-06-01

Spatial positioning accuracy is a key issue in a computer-assisted orthopaedic surgery (CAOS) system. Since intraoperative fluoroscopic images are one of the most important input data to the CAOS system, the quality of these images should have a significant influence on the accuracy of the CAOS system. But the regularities and mechanism of the influence of the quality of intraoperative images on the accuracy of a CAOS system have yet to be studied. Two typical spatial positioning methods - a C-arm calibration-based method and a bi-planar positioning method - are used to study the influence of different image quality parameters, such as resolution, distortion, contrast and signal-to-noise ratio, on positioning accuracy. The error propagation rules of image error in different spatial positioning methods are analyzed by the Monte Carlo method. Correlation analysis showed that resolution and distortion had a significant influence on spatial positioning accuracy. In addition the C-arm calibration-based method was more sensitive to image distortion, while the bi-planar positioning method was more susceptible to image resolution. The image contrast and signal-to-noise ratio have no significant influence on the spatial positioning accuracy. The result of Monte Carlo analysis proved that generally the bi-planar positioning method was more sensitive to image quality than the C-arm calibration-based method. The quality of intraoperative fluoroscopic images is a key issue in the spatial positioning accuracy of a CAOS system. Although the 2 typical positioning methods have very similar mathematical principles, they showed different sensitivities to different image quality parameters. The result of this research may help to create a realistic standard for intraoperative fluoroscopic images for CAOS systems. Copyright © 2018 John Wiley & Sons, Ltd.

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.

Design and Development of the Terrain Information Extraction System

DTIC Science & Technology

1990-09-04

system successfully demonstrated relief measurement and orthophoto production, automated feature extraction has remained "the major problem of today’s...the hierarchical relaxation correlation method developed by Helava Associates, Inc. and digital orthophoto production. To achieve this high accuracy...image memory transfer rates will be achieved by using data blocks or "image tiles ." Further, an image fringe loading module will be implemented which

NDVI and Panchromatic Image Correlation Using Texture Analysis

DTIC Science & Technology

2010-03-01

6 Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm (From Perry...should help the classification methods to be able to classify kelp. Figure 5. Spectral reflectance of vegetation and soil from 0.4 to 1.1 mm...1988). Image processing software for imaging spectrometry analysis. Remote Sensing of Enviroment , 24: 201–210. Perry, C., & Lautenschlager, L. F

Directional sinogram interpolation for sparse angular acquisition in cone-beam computed tomography.

PubMed

Zhang, Hua; Sonke, Jan-Jakob

2013-01-01

Cone-beam (CB) computed tomography (CT) is widely used in the field of medical imaging for guidance. Inspired by Betram's directional interpolation (BDI) methods, directional sinogram interpolation (DSI) was implemented to generate more CB projections by optimized (iterative) double-orientation estimation in sinogram space and directional interpolation. A new CBCT was subsequently reconstructed with the Feldkamp algorithm using both the original and interpolated CB projections. The proposed method was evaluated on both phantom and clinical data, and image quality was assessed by correlation ratio (CR) between the interpolated image and a gold standard obtained from full measured projections. Additionally, streak artifact reduction and image blur were assessed. In a CBCT reconstructed by 40 acquired projections over an arc of 360 degree, streak artifacts dropped 20.7% and 6.7% in a thorax phantom, when our method was compared to linear interpolation (LI) and BDI methods. Meanwhile, image blur was assessed by a head-and-neck phantom, where image blur of DSI was 20.1% and 24.3% less than LI and BDI. When our method was compared to LI and DI methods, CR increased by 4.4% and 3.1%. Streak artifacts of sparsely acquired CBCT were decreased by our method and image blur induced by interpolation was constrained to below other interpolation methods.

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.

Development of CD3 cell quantitation algorithms for renal allograft biopsy rejection assessment utilizing open source image analysis software.

PubMed

Moon, Andres; Smith, Geoffrey H; Kong, Jun; Rogers, Thomas E; Ellis, Carla L; Farris, Alton B Brad

2018-02-01

Renal allograft rejection diagnosis depends on assessment of parameters such as interstitial inflammation; however, studies have shown interobserver variability regarding interstitial inflammation assessment. Since automated image analysis quantitation can be reproducible, we devised customized analysis methods for CD3+ T-cell staining density as a measure of rejection severity and compared them with established commercial methods along with visual assessment. Renal biopsy CD3 immunohistochemistry slides (n = 45), including renal allografts with various degrees of acute cellular rejection (ACR) were scanned for whole slide images (WSIs). Inflammation was quantitated in the WSIs using pathologist visual assessment, commercial algorithms (Aperio nuclear algorithm for CD3+ cells/mm 2 and Aperio positive pixel count algorithm), and customized open source algorithms developed in ImageJ with thresholding/positive pixel counting (custom CD3+%) and identification of pixels fulfilling "maxima" criteria for CD3 expression (custom CD3+ cells/mm 2 ). Based on visual inspections of "markup" images, CD3 quantitation algorithms produced adequate accuracy. Additionally, CD3 quantitation algorithms correlated between each other and also with visual assessment in a statistically significant manner (r = 0.44 to 0.94, p = 0.003 to < 0.0001). Methods for assessing inflammation suggested a progression through the tubulointerstitial ACR grades, with statistically different results in borderline versus other ACR types, in all but the custom methods. Assessment of CD3-stained slides using various open source image analysis algorithms presents salient correlations with established methods of CD3 quantitation. These analysis techniques are promising and highly customizable, providing a form of on-slide "flow cytometry" that can facilitate additional diagnostic accuracy in tissue-based assessments.

Denoising Algorithm for CFA Image Sensors Considering Inter-Channel Correlation.

PubMed

Lee, Min Seok; Park, Sang Wook; Kang, Moon Gi

2017-05-28

In this paper, a spatio-spectral-temporal filter considering an inter-channel correlation is proposed for the denoising of a color filter array (CFA) sequence acquired by CCD/CMOS image sensors. Owing to the alternating under-sampled grid of the CFA pattern, the inter-channel correlation must be considered in the direct denoising process. The proposed filter is applied in the spatial, spectral, and temporal domain, considering the spatio-tempo-spectral correlation. First, nonlocal means (NLM) spatial filtering with patch-based difference (PBD) refinement is performed by considering both the intra-channel correlation and inter-channel correlation to overcome the spatial resolution degradation occurring with the alternating under-sampled pattern. Second, a motion-compensated temporal filter that employs inter-channel correlated motion estimation and compensation is proposed to remove the noise in the temporal domain. Then, a motion adaptive detection value controls the ratio of the spatial filter and the temporal filter. The denoised CFA sequence can thus be obtained without motion artifacts. Experimental results for both simulated and real CFA sequences are presented with visual and numerical comparisons to several state-of-the-art denoising methods combined with a demosaicing method. Experimental results confirmed that the proposed frameworks outperformed the other techniques in terms of the objective criteria and subjective visual perception in CFA sequences.

Reconstruction of fluorescence molecular tomography with a cosinoidal level set method.

PubMed

Zhang, Xuanxuan; Cao, Xu; Zhu, Shouping

2017-06-27

Implicit shape-based reconstruction method in fluorescence molecular tomography (FMT) is capable of achieving higher image clarity than image-based reconstruction method. However, the implicit shape method suffers from a low convergence speed and performs unstably due to the utilization of gradient-based optimization methods. Moreover, the implicit shape method requires priori information about the number of targets. A shape-based reconstruction scheme of FMT with a cosinoidal level set method is proposed in this paper. The Heaviside function in the classical implicit shape method is replaced with a cosine function, and then the reconstruction can be accomplished with the Levenberg-Marquardt method rather than gradient-based methods. As a result, the priori information about the number of targets is not required anymore and the choice of step length is avoided. Numerical simulations and phantom experiments were carried out to validate the proposed method. Results of the proposed method show higher contrast to noise ratios and Pearson correlations than the implicit shape method and image-based reconstruction method. Moreover, the number of iterations required in the proposed method is much less than the implicit shape method. The proposed method performs more stably, provides a faster convergence speed than the implicit shape method, and achieves higher image clarity than the image-based reconstruction method.

Usefulness of the automatic quantitative estimation tool for cerebral blood flow: clinical assessment of the application software tool AQCEL.

PubMed

Momose, Mitsuhiro; Takaki, Akihiro; Matsushita, Tsuyoshi; Yanagisawa, Shin; Yano, Kesato; Miyasaka, Tadashi; Ogura, Yuka; Kadoya, Masumi

2011-01-01

AQCEL enables automatic reconstruction of single-photon emission computed tomogram (SPECT) without image degradation and quantitative analysis of cerebral blood flow (CBF) after the input of simple parameters. We ascertained the usefulness and quality of images obtained by the application software AQCEL in clinical practice. Twelve patients underwent brain perfusion SPECT using technetium-99m ethyl cysteinate dimer at rest and after acetazolamide (ACZ) loading. Images reconstructed using AQCEL were compared with those reconstructed using conventional filtered back projection (FBP) method for qualitative estimation. Two experienced nuclear medicine physicians interpreted the image quality using the following visual scores: 0, same; 1, slightly superior; 2, superior. For quantitative estimation, the mean CBF values of the normal hemisphere of the 12 patients using ACZ calculated by the AQCEL method were compared with those calculated by the conventional method. The CBF values of the 24 regions of the 3-dimensional stereotaxic region of interest template (3DSRT) calculated by the AQCEL method at rest and after ACZ loading were compared to those calculated by the conventional method. No significant qualitative difference was observed between the AQCEL and conventional FBP methods in the rest study. The average score by the AQCEL method was 0.25 ± 0.45 and that by the conventional method was 0.17 ± 0.39 (P = 0.34). There was a significant qualitative difference between the AQCEL and conventional methods in the ACZ loading study. The average score for AQCEL was 0.83 ± 0.58 and that for the conventional method was 0.08 ± 0.29 (P = 0.003). During quantitative estimation using ACZ, the mean CBF values of 12 patients calculated by the AQCEL method were 3-8% higher than those calculated by the conventional method. The square of the correlation coefficient between these methods was 0.995. While comparing the 24 3DSRT regions of 12 patients, the squares of the correlation coefficient between AQCEL and conventional methods were 0.973 and 0.986 for the normal and affected sides at rest, respectively, and 0.977 and 0.984 for the normal and affected sides after ACZ loading, respectively. The quality of images reconstructed using the application software AQCEL were superior to that obtained using conventional method after ACZ loading, and high correlations were shown in quantity at rest and after ACZ loading. This software can be applied to clinical practice and is a useful tool for improvement of reproducibility and throughput.

An automatic method for segmentation of fission tracks in epidote crystal photomicrographs

NASA Astrophysics Data System (ADS)

de Siqueira, Alexandre Fioravante; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Tello Saenz, Carlos Alberto; Job, Aldo Eloizo

2014-08-01

Manual identification of fission tracks has practical problems, such as variation due to observe-observation efficiency. An automatic processing method that could identify fission tracks in a photomicrograph could solve this problem and improve the speed of track counting. However, separation of nontrivial images is one of the most difficult tasks in image processing. Several commercial and free softwares are available, but these softwares are meant to be used in specific images. In this paper, an automatic method based on starlet wavelets is presented in order to separate fission tracks in mineral photomicrographs. Automatization is obtained by the Matthews correlation coefficient, and results are evaluated by precision, recall and accuracy. This technique is an improvement of a method aimed at segmentation of scanning electron microscopy images. This method is applied in photomicrographs of epidote phenocrystals, in which accuracy higher than 89% was obtained in fission track segmentation, even for difficult images. Algorithms corresponding to the proposed method are available for download. Using the method presented here, a user could easily determine fission tracks in photomicrographs of mineral samples.

SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

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

Jaskowiak, J; Ahmad, S; Ali, I

Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were usedmore » to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts increased significantly and that limited image quality and poor correlation between the motion amplitude and DVF was obtained.« less

Quantitation of spatially-localized proteins in tissue samples using MALDI-MRM imaging.

PubMed

Clemis, Elizabeth J; Smith, Derek S; Camenzind, Alexander G; Danell, Ryan M; Parker, Carol E; Borchers, Christoph H

2012-04-17

MALDI imaging allows the creation of a "molecular image" of a tissue slice. This image is reconstructed from the ion abundances in spectra obtained while rastering the laser over the tissue. These images can then be correlated with tissue histology to detect potential biomarkers of, for example, aberrant cell types. MALDI, however, is known to have problems with ion suppression, making it difficult to correlate measured ion abundance with concentration. It would be advantageous to have a method which could provide more accurate protein concentration measurements, particularly for screening applications or for precise comparisons between samples. In this paper, we report the development of a novel MALDI imaging method for the localization and accurate quantitation of proteins in tissues. This method involves optimization of in situ tryptic digestion, followed by reproducible and uniform deposition of an isotopically labeled standard peptide from a target protein onto the tissue, using an aerosol-generating device. Data is acquired by MALDI multiple reaction monitoring (MRM) mass spectrometry (MS), and accurate peptide quantitation is determined from the ratio of MRM transitions for the endogenous unlabeled proteolytic peptides to the corresponding transitions from the applied isotopically labeled standard peptides. In a parallel experiment, the quantity of the labeled peptide applied to the tissue was determined using a standard curve generated from MALDI time-of-flight (TOF) MS data. This external calibration curve was then used to determine the quantity of endogenous peptide in a given area. All standard curves generate by this method had coefficients of determination greater than 0.97. These proof-of-concept experiments using MALDI MRM-based imaging show the feasibility for the precise and accurate quantitation of tissue protein concentrations over 2 orders of magnitude, while maintaining the spatial localization information for the proteins.

Detection of illicit substances in fingerprints by infrared spectral imaging.

PubMed

Ng, Ping Hei Ronnie; Walker, Sarah; Tahtouh, Mark; Reedy, Brian

2009-08-01

FTIR and Raman spectral imaging can be used to simultaneously image a latent fingerprint and detect exogenous substances deposited within it. These substances might include drugs of abuse or traces of explosives or gunshot residue. In this work, spectral searching algorithms were tested for their efficacy in finding targeted substances deposited within fingerprints. "Reverse" library searching, where a large number of possibly poor-quality spectra from a spectral image are searched against a small number of high-quality reference spectra, poses problems for common search algorithms as they are usually implemented. Out of a range of algorithms which included conventional Euclidean distance searching, the spectral angle mapper (SAM) and correlation algorithms gave the best results when used with second-derivative image and reference spectra. All methods tested gave poorer performances with first derivative and undifferentiated spectra. In a search against a caffeine reference, the SAM and correlation methods were able to correctly rank a set of 40 confirmed but poor-quality caffeine spectra at the top of a dataset which also contained 4,096 spectra from an image of an uncontaminated latent fingerprint. These methods also successfully and individually detected aspirin, diazepam and caffeine that had been deposited together in another fingerprint, and they did not indicate any of these substances as a match in a search for another substance which was known not to be present. The SAM was used to successfully locate explosive components in fingerprints deposited on silicon windows. The potential of other spectral searching algorithms used in the field of remote sensing is considered, and the applicability of the methods tested in this work to other modes of spectral imaging is discussed.

Vaccine Images on Twitter: Analysis of What Images are Shared

PubMed Central

Dredze, Mark

2018-01-01

Background Visual imagery plays a key role in health communication; however, there is little understanding of what aspects of vaccine-related images make them effective communication aids. Twitter, a popular venue for discussions related to vaccination, provides numerous images that are shared with tweets. Objective The objectives of this study were to understand how images are used in vaccine-related tweets and provide guidance with respect to the characteristics of vaccine-related images that correlate with the higher likelihood of being retweeted. Methods We collected more than one million vaccine image messages from Twitter and characterized various properties of these images using automated image analytics. We fit a logistic regression model to predict whether or not a vaccine image tweet was retweeted, thus identifying characteristics that correlate with a higher likelihood of being shared. For comparison, we built similar models for the sharing of vaccine news on Facebook and for general image tweets. Results Most vaccine-related images are duplicates (125,916/237,478; 53.02%) or taken from other sources, not necessarily created by the author of the tweet. Almost half of the images contain embedded text, and many include images of people and syringes. The visual content is highly correlated with a tweet’s textual topics. Vaccine image tweets are twice as likely to be shared as nonimage tweets. The sentiment of an image and the objects shown in the image were the predictive factors in determining whether an image was retweeted. Conclusions We are the first to study vaccine images on Twitter. Our findings suggest future directions for the study and use of vaccine imagery and may inform communication strategies around vaccination. Furthermore, our study demonstrates an effective study methodology for image analysis. PMID:29615386