Image-based corrosion recognition for ship steel structures

NASA Astrophysics Data System (ADS)

Ma, Yucong; Yang, Yang; Yao, Yuan; Li, Shengyuan; Zhao, Xuefeng

2018-03-01

Ship structures are subjected to corrosion inevitably in service. Existed image-based methods are influenced by the noises in images because they recognize corrosion by extracting features. In this paper, a novel method of image-based corrosion recognition for ship steel structures is proposed. The method utilizes convolutional neural networks (CNN) and will not be affected by noises in images. A CNN used to recognize corrosion was designed through fine-turning an existing CNN architecture and trained by datasets built using lots of images. Combining the trained CNN classifier with a sliding window technique, the corrosion zone in an image can be recognized.

Reducing Error Rates for Iris Image using higher Contrast in Normalization process

NASA Astrophysics Data System (ADS)

Aminu Ghali, Abdulrahman; Jamel, Sapiee; Abubakar Pindar, Zahraddeen; Hasssan Disina, Abdulkadir; Mat Daris, Mustafa

2017-08-01

Iris recognition system is the most secured, and faster means of identification and authentication. However, iris recognition system suffers a setback from blurring, low contrast and illumination due to low quality image which compromises the accuracy of the system. The acceptance or rejection rates of verified user depend solely on the quality of the image. In many cases, iris recognition system with low image contrast could falsely accept or reject user. Therefore this paper adopts Histogram Equalization Technique to address the problem of False Rejection Rate (FRR) and False Acceptance Rate (FAR) by enhancing the contrast of the iris image. A histogram equalization technique enhances the image quality and neutralizes the low contrast of the image at normalization stage. The experimental result shows that Histogram Equalization Technique has reduced FRR and FAR compared to the existing techniques.

Weighted image de-fogging using luminance dark prior

NASA Astrophysics Data System (ADS)

Kansal, Isha; Kasana, Singara Singh

2017-10-01

In this work, the weighted image de-fogging process based upon dark channel prior is modified by using luminance dark prior. Dark channel prior estimates the transmission by using three colour channels whereas luminance dark prior does the same by making use of only Y component of YUV colour space. For each pixel in a patch of ? size, the luminance dark prior uses ? pixels, rather than ? pixels used in DCP technique, which speeds up the de-fogging process. To estimate the transmission map, weighted approach based upon difference prior is used which mitigates halo artefacts at the time of transmission estimation. The major drawback of weighted technique is that it does not maintain the constancy of the transmission in a local patch even if there are no significant depth disruptions, due to which the de-fogged image looks over smooth and has low contrast. Apart from this, in some images, weighted transmission still carries less visible halo artefacts. Therefore, Gaussian filter is used to blur the estimated weighted transmission map which enhances the contrast of de-fogged images. In addition to this, a novel approach is proposed to remove the pixels belonging to bright light source(s) during the atmospheric light estimation process based upon histogram of YUV colour space. To show the effectiveness, the proposed technique is compared with existing techniques. This comparison shows that the proposed technique performs better than the existing techniques.

"Relative CIR": an image enhancement and visualization technique

USGS Publications Warehouse

Fleming, Michael D.

1993-01-01

Many techniques exist to spectrally and spatially enhance digital multispectral scanner data. One technique enhances an image while keeping the colors as they would appear in a color-infrared (CIR) image. This "relative CIR" technique generates an image that is both spectrally and spatially enhanced, while displaying a maximum range of colors. The technique enables an interpreter to visualize either spectral or land cover classes by their relative CIR characteristics. A relative CIR image is generated by developed spectral statistics for each class in the classifications and then, using a nonparametric approach for spectral enhancement, the means of the classes for each band are ranked. A 3 by 3 pixel smoothing filter is applied to the classification for spatial enhancement and the classes are mapped to the representative rank for each band. Practical applications of the technique include displaying an image classification product as a CIR image that was not derived directly from a spectral image, visualizing how a land cover classification would look as a CIR image, and displaying a spectral classification or intermediate product that will be used to label spectral classes.

Hyperspectral face recognition with spatiospectral information fusion and PLS regression.

PubMed

Uzair, Muhammad; Mahmood, Arif; Mian, Ajmal

2015-03-01

Hyperspectral imaging offers new opportunities for face recognition via improved discrimination along the spectral dimension. However, it poses new challenges, including low signal-to-noise ratio, interband misalignment, and high data dimensionality. Due to these challenges, the literature on hyperspectral face recognition is not only sparse but is limited to ad hoc dimensionality reduction techniques and lacks comprehensive evaluation. We propose a hyperspectral face recognition algorithm using a spatiospectral covariance for band fusion and partial least square regression for classification. Moreover, we extend 13 existing face recognition techniques, for the first time, to perform hyperspectral face recognition.We formulate hyperspectral face recognition as an image-set classification problem and evaluate the performance of seven state-of-the-art image-set classification techniques. We also test six state-of-the-art grayscale and RGB (color) face recognition algorithms after applying fusion techniques on hyperspectral images. Comparison with the 13 extended and five existing hyperspectral face recognition techniques on three standard data sets show that the proposed algorithm outperforms all by a significant margin. Finally, we perform band selection experiments to find the most discriminative bands in the visible and near infrared response spectrum.

A Comparison of the Multiscale Retinex With Other Image Enhancement Techniques

NASA Technical Reports Server (NTRS)

Rahman, Zia-Ur; Woodell, Glenn A.; Jobson, Daniel J.

1997-01-01

The multiscale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. A number of algorithms exist that provide one or more of these features, but not all. In this paper we compare the performance of the MSRCR with techniques that are widely used for image enhancement. Specifically, we compare the MSRCR with color adjustment methods such as gamma correction and gain/offset application, histogram modification techniques such as histogram equalization and manual histogram adjustment, and other more powerful techniques such as homomorphic filtering and 'burning and dodging'. The comparison is carried out by testing the suite of image enhancement methods on a set of diverse images. We find that though some of these techniques work well for some of these images, only the MSRCR performs universally well on the test set.

Peering beneath the surface: novel imaging techniques to noninvasively select gametes and embryos for ART.

PubMed

Jasensky, Joshua; Swain, Jason E

2013-10-01

Embryo imaging has long been a critical tool for in vitro fertilization laboratories, aiding in morphological assessment of embryos, which remains the primary tool for embryo selection. With the recent emergence of clinically applicable real-time imaging systems to assess embryo morphokinetics, a renewed interest has emerged regarding noninvasive methods to assess gamete and embryo development as a means of inferring quality. Several studies exist that utilize novel imaging techniques to visualize or quantify intracellular components of gametes and embryos with the intent of correlating localization of organelles or molecular constitution with quality or outcome. However, the safety of these approaches varies due to the potential detrimental impact of light exposure or other variables. Along with complexity of equipment and cost, these drawbacks currently limit clinical application of these novel microscopes and imaging techniques. However, as evidenced by clinical incorporation of some real-time imaging devices as well as use of polarized microscopy, some of these imaging approaches may prove to be useful. This review summarizes the existing literature on novel imaging approaches utilized to examine gametes and embryos. Refinement of some of these imaging systems may permit clinical application and serve as a means to offer new, noninvasive selection tools to improve outcomes for various assisted reproductive technology procedures.

Computing Challenges in Coded Mask Imaging

NASA Technical Reports Server (NTRS)

Skinner, Gerald

2009-01-01

This slide presaentation reviews the complications and challenges in developing computer systems for Coded Mask Imaging telescopes. The coded mask technique is used when there is no other way to create the telescope, (i.e., when there are wide fields of view, high energies for focusing or low energies for the Compton/Tracker Techniques and very good angular resolution.) The coded mask telescope is described, and the mask is reviewed. The coded Masks for the INTErnational Gamma-Ray Astrophysics Laboratory (INTEGRAL) instruments are shown, and a chart showing the types of position sensitive detectors used for the coded mask telescopes is also reviewed. Slides describe the mechanism of recovering an image from the masked pattern. The correlation with the mask pattern is described. The Matrix approach is reviewed, and other approaches to image reconstruction are described. Included in the presentation is a review of the Energetic X-ray Imaging Survey Telescope (EXIST) / High Energy Telescope (HET), with information about the mission, the operation of the telescope, comparison of the EXIST/HET with the SWIFT/BAT and details of the design of the EXIST/HET.

Image steganalysis using Artificial Bee Colony algorithm

NASA Astrophysics Data System (ADS)

Sajedi, Hedieh

2017-09-01

Steganography is the science of secure communication where the presence of the communication cannot be detected while steganalysis is the art of discovering the existence of the secret communication. Processing a huge amount of information takes extensive execution time and computational sources most of the time. As a result, it is needed to employ a phase of preprocessing, which can moderate the execution time and computational sources. In this paper, we propose a new feature-based blind steganalysis method for detecting stego images from the cover (clean) images with JPEG format. In this regard, we present a feature selection technique based on an improved Artificial Bee Colony (ABC). ABC algorithm is inspired by honeybees' social behaviour in their search for perfect food sources. In the proposed method, classifier performance and the dimension of the selected feature vector depend on using wrapper-based methods. The experiments are performed using two large data-sets of JPEG images. Experimental results demonstrate the effectiveness of the proposed steganalysis technique compared to the other existing techniques.

Image Analysis Technique for Material Behavior Evaluation in Civil Structures

PubMed Central

Moretti, Michele; Rossi, Gianluca

2017-01-01

The article presents a hybrid monitoring technique for the measurement of the deformation field. The goal is to obtain information about crack propagation in existing structures, for the purpose of monitoring their state of health. The measurement technique is based on the capture and analysis of a digital image set. Special markers were used on the surface of the structures that can be removed without damaging existing structures as the historical masonry. The digital image analysis was done using software specifically designed in Matlab to follow the tracking of the markers and determine the evolution of the deformation state. The method can be used in any type of structure but is particularly suitable when it is necessary not to damage the surface of structures. A series of experiments carried out on masonry walls of the Oliverian Museum (Pesaro, Italy) and Palazzo Silvi (Perugia, Italy) have allowed the validation of the procedure elaborated by comparing the results with those derived from traditional measuring techniques. PMID:28773129

Image Analysis Technique for Material Behavior Evaluation in Civil Structures.

PubMed

Speranzini, Emanuela; Marsili, Roberto; Moretti, Michele; Rossi, Gianluca

2017-07-08

The article presents a hybrid monitoring technique for the measurement of the deformation field. The goal is to obtain information about crack propagation in existing structures, for the purpose of monitoring their state of health. The measurement technique is based on the capture and analysis of a digital image set. Special markers were used on the surface of the structures that can be removed without damaging existing structures as the historical masonry. The digital image analysis was done using software specifically designed in Matlab to follow the tracking of the markers and determine the evolution of the deformation state. The method can be used in any type of structure but is particularly suitable when it is necessary not to damage the surface of structures. A series of experiments carried out on masonry walls of the Oliverian Museum (Pesaro, Italy) and Palazzo Silvi (Perugia, Italy) have allowed the validation of the procedure elaborated by comparing the results with those derived from traditional measuring techniques.

An automatic optimum kernel-size selection technique for edge enhancement

USGS Publications Warehouse

Chavez, Pat S.; Bauer, Brian P.

1982-01-01

Edge enhancement is a technique that can be considered, to a first order, a correction for the modulation transfer function of an imaging system. Digital imaging systems sample a continuous function at discrete intervals so that high-frequency information cannot be recorded at the same precision as lower frequency data. Because of this, fine detail or edge information in digital images is lost. Spatial filtering techniques can be used to enhance the fine detail information that does exist in the digital image, but the filter size is dependent on the type of area being processed. A technique has been developed by the authors that uses the horizontal first difference to automatically select the optimum kernel-size that should be used to enhance the edges that are contained in the image. 

Multimodal Image Registration through Simultaneous Segmentation.

PubMed

Aganj, Iman; Fischl, Bruce

2017-11-01

Multimodal image registration facilitates the combination of complementary information from images acquired with different modalities. Most existing methods require computation of the joint histogram of the images, while some perform joint segmentation and registration in alternate iterations. In this work, we introduce a new non-information-theoretical method for pairwise multimodal image registration, in which the error of segmentation - using both images - is considered as the registration cost function. We empirically evaluate our method via rigid registration of multi-contrast brain magnetic resonance images, and demonstrate an often higher registration accuracy in the results produced by the proposed technique, compared to those by several existing methods.

Photographic techniques for enhancing ERTS MSS data for geologic information

NASA Technical Reports Server (NTRS)

Yost, E.; Geluso, W.; Anderson, R.

1974-01-01

Satellite multispectral black-and-white photographic negatives of Luna County, New Mexico, obtained by ERTS on 15 August and 2 September 1973, were precisely reprocessed into positive images and analyzed in an additive color viewer. In addition, an isoluminous (uniform brightness) color rendition of the image was constructed. The isoluminous technique emphasizes subtle differences between multispectral bands by greatly enhancing the color of the superimposed composite of all bands and eliminating the effects of brightness caused by sloping terrain. Basaltic lava flows were more accurately displayed in the precision processed multispectral additive color ERTS renditions than on existing state geological maps. Malpais lava flows and small basaltic occurrences not appearing on existing geological maps were identified in ERTS multispectral color images.

Information-Adaptive Image Encoding and Restoration

NASA Technical Reports Server (NTRS)

Park, Stephen K.; Rahman, Zia-ur

1998-01-01

The multiscale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. A number of algorithms exist that provide one or more of these features, but not all. In this paper we compare the performance of the MSRCR with techniques that are widely used for image enhancement. Specifically, we compare the MSRCR with color adjustment methods such as gamma correction and gain/offset application, histogram modification techniques such as histogram equalization and manual histogram adjustment, and other more powerful techniques such as homomorphic filtering and 'burning and dodging'. The comparison is carried out by testing the suite of image enhancement methods on a set of diverse images. We find that though some of these techniques work well for some of these images, only the MSRCR performs universally well oil the test set.

Steganalysis for Audio Data

DTIC Science & Technology

2006-03-31

from existing image steganography and steganalysis techniques, the overall objective of Task (b) is to design and implement audio steganography in...general design of the VoIP steganography algorithm is based on known LSB hiding techniques (used for example in StegHide (http...system. Nasir Memon et. al. described a steganalyzer based on image quality metrics [AMS03]. Basically, the main idea to detect steganography by

Effective evaluation of privacy protection techniques in visible and thermal imagery

NASA Astrophysics Data System (ADS)

Nawaz, Tahir; Berg, Amanda; Ferryman, James; Ahlberg, Jörgen; Felsberg, Michael

2017-09-01

Privacy protection may be defined as replacing the original content in an image region with a (less intrusive) content having modified target appearance information to make it less recognizable by applying a privacy protection technique. Indeed, the development of privacy protection techniques also needs to be complemented with an established objective evaluation method to facilitate their assessment and comparison. Generally, existing evaluation methods rely on the use of subjective judgments or assume a specific target type in image data and use target detection and recognition accuracies to assess privacy protection. An annotation-free evaluation method that is neither subjective nor assumes a specific target type is proposed. It assesses two key aspects of privacy protection: "protection" and "utility." Protection is quantified as an appearance similarity, and utility is measured as a structural similarity between original and privacy-protected image regions. We performed an extensive experimentation using six challenging datasets (having 12 video sequences), including a new dataset (having six sequences) that contains visible and thermal imagery. The new dataset is made available online for the community. We demonstrate effectiveness of the proposed method by evaluating six image-based privacy protection techniques and also show comparisons of the proposed method over existing methods.

Performance of signal-to-noise ratio estimation for scanning electron microscope using autocorrelation Levinson-Durbin recursion model.

PubMed

Sim, K S; Lim, M S; Yeap, Z X

2016-07-01

A new technique to quantify signal-to-noise ratio (SNR) value of the scanning electron microscope (SEM) images is proposed. This technique is known as autocorrelation Levinson-Durbin recursion (ACLDR) model. To test the performance of this technique, the SEM image is corrupted with noise. The autocorrelation function of the original image and the noisy image are formed. The signal spectrum based on the autocorrelation function of image is formed. ACLDR is then used as an SNR estimator to quantify the signal spectrum of noisy image. The SNR values of the original image and the quantified image are calculated. The ACLDR is then compared with the three existing techniques, which are nearest neighbourhood, first-order linear interpolation and nearest neighbourhood combined with first-order linear interpolation. It is shown that ACLDR model is able to achieve higher accuracy in SNR estimation. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Fourier-Mellin moment-based intertwining map for image encryption

NASA Astrophysics Data System (ADS)

Kaur, Manjit; Kumar, Vijay

2018-03-01

In this paper, a robust image encryption technique that utilizes Fourier-Mellin moments and intertwining logistic map is proposed. Fourier-Mellin moment-based intertwining logistic map has been designed to overcome the issue of low sensitivity of an input image. Multi-objective Non-Dominated Sorting Genetic Algorithm (NSGA-II) based on Reinforcement Learning (MNSGA-RL) has been used to optimize the required parameters of intertwining logistic map. Fourier-Mellin moments are used to make the secret keys more secure. Thereafter, permutation and diffusion operations are carried out on input image using secret keys. The performance of proposed image encryption technique has been evaluated on five well-known benchmark images and also compared with seven well-known existing encryption techniques. The experimental results reveal that the proposed technique outperforms others in terms of entropy, correlation analysis, a unified average changing intensity and the number of changing pixel rate. The simulation results reveal that the proposed technique provides high level of security and robustness against various types of attacks.

Imaging Analysis of the Hard X-Ray Telescope ProtoEXIST2 and New Techniques for High-Resolution Coded-Aperture Telescopes

NASA Technical Reports Server (NTRS)

Hong, Jaesub; Allen, Branden; Grindlay, Jonathan; Barthelmy, Scott D.

2016-01-01

Wide-field (greater than or approximately equal to 100 degrees squared) hard X-ray coded-aperture telescopes with high angular resolution (greater than or approximately equal to 2 minutes) will enable a wide range of time domain astrophysics. For instance, transient sources such as gamma-ray bursts can be precisely localized without the assistance of secondary focusing X-ray telescopes to enable rapid followup studies. On the other hand, high angular resolution in coded-aperture imaging introduces a new challenge in handling the systematic uncertainty: the average photon count per pixel is often too small to establish a proper background pattern or model the systematic uncertainty in a timescale where the model remains invariant. We introduce two new techniques to improve detection sensitivity, which are designed for, but not limited to, a high-resolution coded-aperture system: a self-background modeling scheme which utilizes continuous scan or dithering operations, and a Poisson-statistics based probabilistic approach to evaluate the significance of source detection without subtraction in handling the background. We illustrate these new imaging analysis techniques in high resolution coded-aperture telescope using the data acquired by the wide-field hard X-ray telescope ProtoEXIST2 during a high-altitude balloon flight in fall 2012. We review the imaging sensitivity of ProtoEXIST2 during the flight, and demonstrate the performance of the new techniques using our balloon flight data in comparison with a simulated ideal Poisson background.

Image smoothing and enhancement via min/max curvature flow

NASA Astrophysics Data System (ADS)

Malladi, Ravikanth; Sethian, James A.

1996-03-01

We present a class of PDE-based algorithms suitable for a wide range of image processing applications. The techniques are applicable to both salt-and-pepper gray-scale noise and full- image continuous noise present in black and white images, gray-scale images, texture images and color images. At the core, the techniques rely on a level set formulation of evolving curves and surfaces and the viscosity in profile evolution. Essentially, the method consists of moving the isointensity contours in an image under curvature dependent speed laws to achieve enhancement. Compared to existing techniques, our approach has several distinct advantages. First, it contains only one enhancement parameter, which in most cases is automatically chosen. Second, the scheme automatically stops smoothing at some optimal point; continued application of the scheme produces no further change. Third, the method is one of the fastest possible schemes based on a curvature-controlled approach.

Magneto-optical imaging technique for hostile environments: The ghost imaging approach

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

Meda, A.; Caprile, A.; Avella, A.

2015-06-29

In this paper, we develop an approach to magneto optical imaging (MOI), applying a ghost imaging (GI) protocol to perform Faraday microscopy. MOI is of the utmost importance for the investigation of magnetic properties of material samples, through Weiss domains shape, dimension and dynamics analysis. Nevertheless, in some extreme conditions such as cryogenic temperatures or high magnetic field applications, there exists a lack of domain images due to the difficulty in creating an efficient imaging system in such environments. Here, we present an innovative MOI technique that separates the imaging optical path from the one illuminating the object. The techniquemore » is based on thermal light GI and exploits correlations between light beams to retrieve the image of magnetic domains. As a proof of principle, the proposed technique is applied to the Faraday magneto-optical observation of the remanence domain structure of an yttrium iron garnet sample.« less

Web image retrieval using an effective topic and content-based technique

NASA Astrophysics Data System (ADS)

Lee, Ching-Cheng; Prabhakara, Rashmi

2005-03-01

There has been an exponential growth in the amount of image data that is available on the World Wide Web since the early development of Internet. With such a large amount of information and image available and its usefulness, an effective image retrieval system is thus greatly needed. In this paper, we present an effective approach with both image matching and indexing techniques that improvise on existing integrated image retrieval methods. This technique follows a two-phase approach, integrating query by topic and query by example specification methods. In the first phase, The topic-based image retrieval is performed by using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. This technique consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. In the second phase, we use query by example specification to perform a low-level content-based image match in order to retrieve smaller and relatively closer results of the example image. From this, information related to the image feature is automatically extracted from the query image. The main objective of our approach is to develop a functional image search and indexing technique and to demonstrate that better retrieval results can be achieved.

Multi-material classification of dry recyclables from municipal solid waste based on thermal imaging.

PubMed

Gundupalli, Sathish Paulraj; Hait, Subrata; Thakur, Atul

2017-12-01

There has been a significant rise in municipal solid waste (MSW) generation in the last few decades due to rapid urbanization and industrialization. Due to the lack of source segregation practice, a need for automated segregation of recyclables from MSW exists in the developing countries. This paper reports a thermal imaging based system for classifying useful recyclables from simulated MSW sample. Experimental results have demonstrated the possibility to use thermal imaging technique for classification and a robotic system for sorting of recyclables in a single process step. The reported classification system yields an accuracy in the range of 85-96% and is comparable with the existing single-material recyclable classification techniques. We believe that the reported thermal imaging based system can emerge as a viable and inexpensive large-scale classification-cum-sorting technology in recycling plants for processing MSW in developing countries. Copyright © 2017 Elsevier Ltd. All rights reserved.

The pre-image problem for Laplacian Eigenmaps utilizing L 1 regularization with applications to data fusion

NASA Astrophysics Data System (ADS)

Cloninger, Alexander; Czaja, Wojciech; Doster, Timothy

2017-07-01

As the popularity of non-linear manifold learning techniques such as kernel PCA and Laplacian Eigenmaps grows, vast improvements have been seen in many areas of data processing, including heterogeneous data fusion and integration. One problem with the non-linear techniques, however, is the lack of an easily calculable pre-image. Existence of such pre-image would allow visualization of the fused data not only in the embedded space, but also in the original data space. The ability to make such comparisons can be crucial for data analysts and other subject matter experts who are the end users of novel mathematical algorithms. In this paper, we propose a pre-image algorithm for Laplacian Eigenmaps. Our method offers major improvements over existing techniques, which allow us to address the problem of noisy inputs and the issue of how to calculate the pre-image of a point outside the convex hull of training samples; both of which have been overlooked in previous studies in this field. We conclude by showing that our pre-image algorithm, combined with feature space rotations, allows us to recover occluded pixels of an imaging modality based off knowledge of that image measured by heterogeneous modalities. We demonstrate this data recovery on heterogeneous hyperspectral (HS) cameras, as well as by recovering LIDAR measurements from HS data.

Rapid 2D-to-3D conversion

NASA Astrophysics Data System (ADS)

Harman, Philip V.; Flack, Julien; Fox, Simon; Dowley, Mark

2002-05-01

The conversion of existing 2D images to 3D is proving commercially viable and fulfills the growing need for high quality stereoscopic images. This approach is particularly effective when creating content for the new generation of autostereoscopic displays that require multiple stereo images. The dominant technique for such content conversion is to develop a depth map for each frame of 2D material. The use of a depth map as part of the 2D to 3D conversion process has a number of desirable characteristics: 1. The resolution of the depth may be lower than that of the associated 2D image. 2. It can be highly compressed. 3. 2D compatibility is maintained. 4. Real time generation of stereo, or multiple stereo pairs, is possible. The main disadvantage has been the laborious nature of the manual conversion techniques used to create depth maps from existing 2D images, which results in a slow and costly process. An alternative, highly productive technique has been developed based upon the use of Machine Leaning Algorithm (MLAs). This paper describes the application of MLAs to the generation of depth maps and presents the results of the commercial application of this approach.

3D thermography imaging standardization technique for inflammation diagnosis

NASA Astrophysics Data System (ADS)

Ju, Xiangyang; Nebel, Jean-Christophe; Siebert, J. Paul

2005-01-01

We develop a 3D thermography imaging standardization technique to allow quantitative data analysis. Medical Digital Infrared Thermal Imaging is very sensitive and reliable mean of graphically mapping and display skin surface temperature. It allows doctors to visualise in colour and quantify temperature changes in skin surface. The spectrum of colours indicates both hot and cold responses which may co-exist if the pain associate with an inflammatory focus excites an increase in sympathetic activity. However, due to thermograph provides only qualitative diagnosis information, it has not gained acceptance in the medical and veterinary communities as a necessary or effective tool in inflammation and tumor detection. Here, our technique is based on the combination of visual 3D imaging technique and thermal imaging technique, which maps the 2D thermography images on to 3D anatomical model. Then we rectify the 3D thermogram into a view independent thermogram and conform it a standard shape template. The combination of these imaging facilities allows the generation of combined 3D and thermal data from which thermal signatures can be quantified.

Hybrid registration of PET/CT in thoracic region with pre-filtering PET sinogram

NASA Astrophysics Data System (ADS)

Mokri, S. S.; Saripan, M. I.; Marhaban, M. H.; Nordin, A. J.; Hashim, S.

2015-11-01

The integration of physiological (PET) and anatomical (CT) images in cancer delineation requires an accurate spatial registration technique. Although hybrid PET/CT scanner is used to co-register these images, significant misregistrations exist due to patient and respiratory/cardiac motions. This paper proposes a hybrid feature-intensity based registration technique for hybrid PET/CT scanner. First, simulated PET sinogram was filtered with a 3D hybrid mean-median before reconstructing the image. The features were then derived from the segmented structures (lung, heart and tumor) from both images. The registration was performed based on modified multi-modality demon registration with multiresolution scheme. Apart from visual observations improvements, the proposed registration technique increased the normalized mutual information index (NMI) between the PET/CT images after registration. All nine tested datasets show marked improvements in mutual information (MI) index than free form deformation (FFD) registration technique with the highest MI increase is 25%.

A Fourier-based compressed sensing technique for accelerated CT image reconstruction using first-order methods.

PubMed

Choi, Kihwan; Li, Ruijiang; Nam, Haewon; Xing, Lei

2014-06-21

As a solution to iterative CT image reconstruction, first-order methods are prominent for the large-scale capability and the fast convergence rate [Formula: see text]. In practice, the CT system matrix with a large condition number may lead to slow convergence speed despite the theoretically promising upper bound. The aim of this study is to develop a Fourier-based scaling technique to enhance the convergence speed of first-order methods applied to CT image reconstruction. Instead of working in the projection domain, we transform the projection data and construct a data fidelity model in Fourier space. Inspired by the filtered backprojection formalism, the data are appropriately weighted in Fourier space. We formulate an optimization problem based on weighted least-squares in the Fourier space and total-variation (TV) regularization in image space for parallel-beam, fan-beam and cone-beam CT geometry. To achieve the maximum computational speed, the optimization problem is solved using a fast iterative shrinkage-thresholding algorithm with backtracking line search and GPU implementation of projection/backprojection. The performance of the proposed algorithm is demonstrated through a series of digital simulation and experimental phantom studies. The results are compared with the existing TV regularized techniques based on statistics-based weighted least-squares as well as basic algebraic reconstruction technique. The proposed Fourier-based compressed sensing (CS) method significantly improves both the image quality and the convergence rate compared to the existing CS techniques.

Evaluation of a rule-based compositing technique for Landsat-5 TM and Landsat-7 ETM+ images

NASA Astrophysics Data System (ADS)

Lück, W.; van Niekerk, A.

2016-05-01

Image compositing is a multi-objective optimization process. Its goal is to produce a seamless cloud and artefact-free artificial image. This is achieved by aggregating image observations and by replacing poor and cloudy data with good observations from imagery acquired within the timeframe of interest. This compositing process aims to minimise the visual artefacts which could result from different radiometric properties, caused by atmospheric conditions, phenologic patterns and land cover changes. It has the following requirements: (1) image compositing must be cloud free, which requires the detection of clouds and shadows, and (2) the image composite must be seamless, minimizing artefacts and visible across inter image seams. This study proposes a new rule-based compositing technique (RBC) that combines the strengths of several existing methods. A quantitative and qualitative evaluation is made of the RBC technique by comparing it to the maximum NDVI (MaxNDVI), minimum red (MinRed) and maximum ratio (MaxRatio) compositing techniques. A total of 174 Landsat TM and ETM+ images, covering three study sites and three different timeframes for each site, are used in the evaluation. A new set of quantitative/qualitative evaluation techniques for compositing quality measurement was developed and showed that the RBC technique outperformed all other techniques, with MaxRatio, MaxNDVI, and MinRed techniques in order of performance from best to worst.

Applications of digital image processing techniques to problems of data registration and correlation

NASA Technical Reports Server (NTRS)

Green, W. B.

1978-01-01

An overview is presented of the evolution of the computer configuration at JPL's Image Processing Laboratory (IPL). The development of techniques for the geometric transformation of digital imagery is discussed and consideration is given to automated and semiautomated image registration, and the registration of imaging and nonimaging data. The increasing complexity of image processing tasks at IPL is illustrated with examples of various applications from the planetary program and earth resources activities. It is noted that the registration of existing geocoded data bases with Landsat imagery will continue to be important if the Landsat data is to be of genuine use to the user community.

Imaging fast electrical activity in the brain with electrical impedance tomography

PubMed Central

Aristovich, Kirill Y.; Packham, Brett C.; Koo, Hwan; Santos, Gustavo Sato dos; McEvoy, Andy; Holder, David S.

2016-01-01

Imaging of neuronal depolarization in the brain is a major goal in neuroscience, but no technique currently exists that could image neural activity over milliseconds throughout the whole brain. Electrical impedance tomography (EIT) is an emerging medical imaging technique which can produce tomographic images of impedance changes with non-invasive surface electrodes. We report EIT imaging of impedance changes in rat somatosensory cerebral cortex with a resolution of 2 ms and < 200 μm during evoked potentials using epicortical arrays with 30 electrodes. Images were validated with local field potential recordings and current source-sink density analysis. Our results demonstrate that EIT can image neural activity in a volume 7 × 5 × 2 mm in somatosensory cerebral cortex with reduced invasiveness, greater resolution and imaging volume than other methods. Modeling indicates similar resolutions are feasible throughout the entire brain so this technique, uniquely, has the potential to image functional connectivity of cortical and subcortical structures. PMID:26348559

Interference Mitigation Effects on Synthetic Aperture Radar Coherent Data Products

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

Musgrove, Cameron

For synthetic aperture radars radio frequency interference from sources external to the radar system and techniques to mitigate the interference can degrade the quality of the image products. Usually the radar system designer will try to balance the amount of mitigation for an acceptable amount of interference to optimize the image quality. This dissertation examines the effect of interference mitigation upon coherent data products of fine resolution, high frequency synthetic aperture radars using stretch processing. Novel interference mitigation techniques are introduced that operate on single or multiple apertures of data that increase average coherence compared to existing techniques. New metricsmore » are applied to evaluate multiple mitigation techniques for image quality and average coherence. The underlying mechanism for interference mitigation techniques that affect coherence is revealed.« less

Investigating existing medical CT segmentation techniques within automated baggage and package inspection

NASA Astrophysics Data System (ADS)

Megherbi, Najla; Breckon, Toby P.; Flitton, Greg T.

2013-10-01

3D Computed Tomography (CT) image segmentation is already well established tool in medical research and in routine daily clinical practice. However, such techniques have not been used in the context of 3D CT image segmentation for baggage and package security screening using CT imagery. CT systems are increasingly used in airports for security baggage examination. We propose in this contribution an investigation of the current 3D CT medical image segmentation methods for use in this new domain. Experimental results of 3D segmentation on real CT baggage security imagery using a range of techniques are presented and discussed.

Signal-to-noise ratio estimation on SEM images using cubic spline interpolation with Savitzky-Golay smoothing.

PubMed

Sim, K S; Kiani, M A; Nia, M E; Tso, C P

2014-01-01

A new technique based on cubic spline interpolation with Savitzky-Golay noise reduction filtering is designed to estimate signal-to-noise ratio of scanning electron microscopy (SEM) images. This approach is found to present better result when compared with two existing techniques: nearest neighbourhood and first-order interpolation. When applied to evaluate the quality of SEM images, noise can be eliminated efficiently with optimal choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Reducing charging effects in scanning electron microscope images by Rayleigh contrast stretching method (RCS).

PubMed

Wan Ismail, W Z; Sim, K S; Tso, C P; Ting, H Y

2011-01-01

To reduce undesirable charging effects in scanning electron microscope images, Rayleigh contrast stretching is developed and employed. First, re-scaling is performed on the input image histograms with Rayleigh algorithm. Then, contrast stretching or contrast adjustment is implemented to improve the images while reducing the contrast charging artifacts. This technique has been compared to some existing histogram equalization (HE) extension techniques: recursive sub-image HE, contrast stretching dynamic HE, multipeak HE and recursive mean separate HE. Other post processing methods, such as wavelet approach, spatial filtering, and exponential contrast stretching, are compared as well. Overall, the proposed method produces better image compensation in reducing charging artifacts. Copyright © 2011 Wiley Periodicals, Inc.

A study of the x-ray image quality improvement in the examination of the respiratory system based on the new image processing technique

NASA Astrophysics Data System (ADS)

Nagai, Yuichi; Kitagawa, Mayumi; Torii, Jun; Iwase, Takumi; Aso, Tomohiko; Ihara, Kanyu; Fujikawa, Mari; Takeuchi, Yumiko; Suzuki, Katsumi; Ishiguro, Takashi; Hara, Akio

2014-03-01

Recently, the double contrast technique in a gastrointestinal examination and the transbronchial lung biopsy in an examination for the respiratory system [1-3] have made a remarkable progress. Especially in the transbronchial lung biopsy, better quality of x-ray fluoroscopic images is requested because this examination is performed under a guidance of x-ray fluoroscopic images. On the other hand, various image processing methods [4] for x-ray fluoroscopic images have been developed as an x-ray system with a flat panel detector [5-7] is widely used. A recursive filtering is an effective method to reduce a random noise in x-ray fluoroscopic images. However it has a limitation for its effectiveness of a noise reduction in case of a moving object exists in x-ray fluoroscopic images because the recursive filtering is a noise reduction method by adding last few images. After recursive filtering a residual signal was produced if a moving object existed in x-ray images, and this residual signal disturbed a smooth procedure of the examinations. To improve this situation, new noise reduction method has been developed. The Adaptive Noise Reduction [ANR] is the brand-new noise reduction technique which can be reduced only a noise regardless of the moving object in x-ray fluoroscopic images. Therefore the ANR is a very suitable noise reduction method for the transbronchial lung biopsy under a guidance of x-ray fluoroscopic images because the residual signal caused of the moving object in x-ray fluoroscopic images is never produced after the ANR. In this paper, we will explain an advantage of the ANR by comparing of a performance between the ANR images and the conventional recursive filtering images.

Sensing Applied Load and Damage Effects in Composites with Nondestructive Techniques

DTIC Science & Technology

2017-05-01

evaluation (NDE) techniques. Evaluation using piezoelectrically induced guided waves, acoustic emission, thermography, and X-ray imaging were compared...nondestructive inspection to further understanding of the material itself and the capabilities of various nondestructive evaluation (NDE) techniques...materials because of their inherent differences. NDE techniques exist that can evaluate composite structures for damage including C-Scan

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.

Ultrasound appearances of Implanon implanted contraceptive devices.

PubMed

McNeill, G; Ward, E; Halpenny, D; Snow, A; Torreggiani, W

2009-01-01

Subdermal contraceptive devices represent a popular choice of contraception. Whilst often removed without the use of imaging, circumstances exist where imaging is required. Ultrasound is the modality of choice. The optimal technique and typical sonographic appearances are detailed in this article.

Simultaneous neutron and x-ray imaging of inertial confinement fusion experiments along a single line of sight at Omega.

PubMed

Danly, C R; Day, T H; Fittinghoff, D N; Herrmann, H; Izumi, N; Kim, Y H; Martinez, J I; Merrill, F E; Schmidt, D W; Simpson, R A; Volegov, P L; Wilde, C H

2015-04-01

Neutron and x-ray imaging provide critical information about the geometry and hydrodynamics of inertial confinement fusion implosions. However, existing diagnostics at Omega and the National Ignition Facility (NIF) cannot produce images in both neutrons and x-rays along the same line of sight. This leads to difficulty comparing these images, which capture different parts of the plasma geometry, for the asymmetric implosions seen in present experiments. Further, even when opposing port neutron and x-ray images are available, they use different detectors and cannot provide positive information about the relative positions of the neutron and x-ray sources. A technique has been demonstrated on implosions at Omega that can capture x-ray images along the same line of sight as the neutron images. The technique is described, and data from a set of experiments are presented, along with a discussion of techniques for coregistration of the various images. It is concluded that the technique is viable and could provide valuable information if implemented on NIF in the near future.

Simultaneous neutron and x-ray imaging of inertial confinement fusion experiments along a single line of sight at Omega

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

Danly, C. R.; Day, T. H.; Fittinghoff, D. N.

Neutron and x-ray imaging provide critical information about the geometry and hydrodynamics of inertial confinement fusion implosions. However, existing diagnostics at Omega and the National Ignition Facility (NIF) cannot produce images in both neutrons and x-rays along the same line of sight. This leads to difficulty comparing these images, which capture different parts of the plasma geometry, for the asymmetric implosions seen in present experiments. Further, even when opposing port neutron and x-ray images are available, they use different detectors and cannot provide positive information about the relative positions of the neutron and x-ray sources. A technique has been demonstratedmore » on implosions at Omega that can capture x-ray images along the same line of sight as the neutron images. Thus, the technique is described, and data from a set of experiments are presented, along with a discussion of techniques for coregistration of the various images. It is concluded that the technique is viable and could provide valuable information if implemented on NIF in the near future.« less

Simultaneous neutron and x-ray imaging of inertial confinement fusion experiments along a single line of sight at Omega

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

Danly, C. R.; Day, T. H.; Herrmann, H.

Neutron and x-ray imaging provide critical information about the geometry and hydrodynamics of inertial confinement fusion implosions. However, existing diagnostics at Omega and the National Ignition Facility (NIF) cannot produce images in both neutrons and x-rays along the same line of sight. This leads to difficulty comparing these images, which capture different parts of the plasma geometry, for the asymmetric implosions seen in present experiments. Further, even when opposing port neutron and x-ray images are available, they use different detectors and cannot provide positive information about the relative positions of the neutron and x-ray sources. A technique has been demonstratedmore » on implosions at Omega that can capture x-ray images along the same line of sight as the neutron images. The technique is described, and data from a set of experiments are presented, along with a discussion of techniques for coregistration of the various images. It is concluded that the technique is viable and could provide valuable information if implemented on NIF in the near future.« less

Simultaneous neutron and x-ray imaging of inertial confinement fusion experiments along a single line of sight at Omega

DOE PAGES

Danly, C. R.; Day, T. H.; Fittinghoff, D. N.; ...

2015-04-16

Neutron and x-ray imaging provide critical information about the geometry and hydrodynamics of inertial confinement fusion implosions. However, existing diagnostics at Omega and the National Ignition Facility (NIF) cannot produce images in both neutrons and x-rays along the same line of sight. This leads to difficulty comparing these images, which capture different parts of the plasma geometry, for the asymmetric implosions seen in present experiments. Further, even when opposing port neutron and x-ray images are available, they use different detectors and cannot provide positive information about the relative positions of the neutron and x-ray sources. A technique has been demonstratedmore » on implosions at Omega that can capture x-ray images along the same line of sight as the neutron images. Thus, the technique is described, and data from a set of experiments are presented, along with a discussion of techniques for coregistration of the various images. It is concluded that the technique is viable and could provide valuable information if implemented on NIF in the near future.« less

Full-color high-definition CGH reconstructing hybrid scenes of physical and virtual objects

NASA Astrophysics Data System (ADS)

Tsuchiyama, Yasuhiro; Matsushima, Kyoji; Nakahara, Sumio; Yamaguchi, Masahiro; Sakamoto, Yuji

2017-03-01

High-definition CGHs can reconstruct high-quality 3D images that are comparable to that in conventional optical holography. However, it was difficult to exhibit full-color images reconstructed by these high-definition CGHs, because three CGHs for RGB colors and a bulky image combiner were needed to produce full-color images. Recently, we reported a novel technique for full-color reconstruction using RGB color filters, which are similar to that used for liquid-crystal panels. This technique allows us to produce full-color high-definition CGHs composed of a single plate and place them on exhibition. By using the technique, we demonstrate full-color CGHs that reconstruct hybrid scenes comprised of real-existing physical objects and CG-modeled virtual objects in this paper. Here, the wave field of the physical object are obtained from dense multi-viewpoint images by employing the ray-sampling (RS) plane technique. In addition to the technique for full-color capturing and reconstruction of real object fields, the principle and simulation technique for full- color CGHs using RGB color filters are presented.

Pseudo-shading technique in the two-dimensional domain: a post-processing algorithm for enhancing the Z-buffer of a three-dimensional binary image.

PubMed

Tan, A C; Richards, R

1989-01-01

Three-dimensional (3D) medical graphics is becoming popular in clinical use on tomographic scanners. Research work in 3D reconstructive display of computerized tomography (CT) and magnetic resonance imaging (MRI) scans on conventional computers has produced many so-called pseudo-3D images. The quality of these images depends on the rendering algorithm, the coarseness of the digitized object, the number of grey levels and the image screen resolution. CT and MRI data are fundamentally voxel based and they produce images that are coarse because of the resolution of the data acquisition system. 3D images produced by the Z-buffer depth shading technique suffer loss of detail when complex objects with fine textural detail need to be displayed. Attempts have been made to improve the display of voxel objects, and existing techniques have shown the improvement possible using these post-processing algorithms. The improved rendering technique works on the Z-buffer image to generate a shaded image using a single light source in any direction. The effectiveness of the technique in generating a shaded image has been shown to be a useful means of presenting 3D information for clinical use.

Comparison of lossless compression techniques for prepress color images

NASA Astrophysics Data System (ADS)

Van Assche, Steven; Denecker, Koen N.; Philips, Wilfried R.; Lemahieu, Ignace L.

1998-12-01

In the pre-press industry color images have both a high spatial and a high color resolution. Such images require a considerable amount of storage space and impose long transmission times. Data compression is desired to reduce these storage and transmission problems. Because of the high quality requirements in the pre-press industry only lossless compression is acceptable. Most existing lossless compression schemes operate on gray-scale images. In this case the color components of color images must be compressed independently. However, higher compression ratios can be achieved by exploiting inter-color redundancies. In this paper we present a comparison of three state-of-the-art lossless compression techniques which exploit such color redundancies: IEP (Inter- color Error Prediction) and a KLT-based technique, which are both linear color decorrelation techniques, and Interframe CALIC, which uses a non-linear approach to color decorrelation. It is shown that these techniques are able to exploit color redundancies and that color decorrelation can be done effectively and efficiently. The linear color decorrelators provide a considerable coding gain (about 2 bpp) on some typical prepress images. The non-linear interframe CALIC predictor does not yield better results, but the full interframe CALIC technique does.

Geometric and shading correction for images of printed materials using boundary.

PubMed

Brown, Michael S; Tsoi, Yau-Chat

2006-06-01

A novel technique that uses boundary interpolation to correct geometric distortion and shading artifacts present in images of printed materials is presented. Unlike existing techniques, our algorithm can simultaneously correct a variety of geometric distortions, including skew, fold distortion, binder curl, and combinations of these. In addition, the same interpolation framework can be used to estimate the intrinsic illumination component of the distorted image to correct shading artifacts. We detail our algorithm for geometric and shading correction and demonstrate its usefulness on real-world and synthetic data.

Preliminary thermal imaging of cotton impurities

USDA-ARS?s Scientific Manuscript database

Discrepancies exist between the Advanced Fiber Information Systems (AFIS) seed coat nep measurements and the seed coat fragment count upon visual inspection. Various studies have indicated that the two techniques may not be sensing the same contaminants as seed coat entities. Thermal imaging is an...

Image feature detection and extraction techniques performance evaluation for development of panorama under different light conditions

NASA Astrophysics Data System (ADS)

Patil, Venkat P.; Gohatre, Umakant B.

2018-04-01

The technique of obtaining a wider field-of-view of an image to get high resolution integrated image is normally required for development of panorama of a photographic images or scene from a sequence of part of multiple views. There are various image stitching methods developed recently. For image stitching five basic steps are adopted stitching which are Feature detection and extraction, Image registration, computing homography, image warping and Blending. This paper provides review of some of the existing available image feature detection and extraction techniques and image stitching algorithms by categorizing them into several methods. For each category, the basic concepts are first described and later on the necessary modifications made to the fundamental concepts by different researchers are elaborated. This paper also highlights about the some of the fundamental techniques for the process of photographic image feature detection and extraction methods under various illumination conditions. The Importance of Image stitching is applicable in the various fields such as medical imaging, astrophotography and computer vision. For comparing performance evaluation of the techniques used for image features detection three methods are considered i.e. ORB, SURF, HESSIAN and time required for input images feature detection is measured. Results obtained finally concludes that for daylight condition, ORB algorithm found better due to the fact that less tome is required for more features extracted where as for images under night light condition it shows that SURF detector performs better than ORB/HESSIAN detectors.

Retinal Image Simulation of Subjective Refraction Techniques.

PubMed

Perches, Sara; Collados, M Victoria; Ares, Jorge

2016-01-01

Refraction techniques make it possible to determine the most appropriate sphero-cylindrical lens prescription to achieve the best possible visual quality. Among these techniques, subjective refraction (i.e., patient's response-guided refraction) is the most commonly used approach. In this context, this paper's main goal is to present a simulation software that implements in a virtual manner various subjective-refraction techniques--including Jackson's Cross-Cylinder test (JCC)--relying all on the observation of computer-generated retinal images. This software has also been used to evaluate visual quality when the JCC test is performed in multifocal-contact-lens wearers. The results reveal this software's usefulness to simulate the retinal image quality that a particular visual compensation provides. Moreover, it can help to gain a deeper insight and to improve existing refraction techniques and it can be used for simulated training.

Trigonometric Transforms for Image Reconstruction

DTIC Science & Technology

1998-06-01

applying trigo - nometric transforms to image reconstruction problems. Many existing linear image reconstruc- tion techniques rely on knowledge of...ancestors. The research performed for this dissertation represents the first time the symmetric convolution-multiplication property of trigo - nometric...Fourier domain. The traditional representation of these filters will be similar to new trigo - nometric transform versions derived in later chapters

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 novel methodology for querying web images

NASA Astrophysics Data System (ADS)

Prabhakara, Rashmi; Lee, Ching Cheng

2005-01-01

Ever since the advent of Internet, there has been an immense growth in the amount of image data that is available on the World Wide Web. With such a magnitude of image availability, an efficient and effective image retrieval system is required to make use of this information. This research presents an effective image matching and indexing technique that improvises on existing integrated image retrieval methods. The proposed technique follows a two-phase approach, integrating query by topic and query by example specification methods. The first phase consists of topic-based image retrieval using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. It consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. The second phase uses the query by example specification to perform a low-level content-based image match for the retrieval of smaller and relatively closer results of the example image. Information related to the image feature is automatically extracted from the query image by the image processing system. A technique that is not computationally intensive based on color feature is used to perform content-based matching of images. The main goal is to develop a functional image search and indexing system and to demonstrate that better retrieval results can be achieved with this proposed hybrid search technique.

A novel methodology for querying web images

NASA Astrophysics Data System (ADS)

Prabhakara, Rashmi; Lee, Ching Cheng

2004-12-01

Ever since the advent of Internet, there has been an immense growth in the amount of image data that is available on the World Wide Web. With such a magnitude of image availability, an efficient and effective image retrieval system is required to make use of this information. This research presents an effective image matching and indexing technique that improvises on existing integrated image retrieval methods. The proposed technique follows a two-phase approach, integrating query by topic and query by example specification methods. The first phase consists of topic-based image retrieval using an improved text information retrieval (IR) technique that makes use of the structured format of HTML documents. It consists of a focused crawler that not only provides for the user to enter the keyword for the topic-based search but also, the scope in which the user wants to find the images. The second phase uses the query by example specification to perform a low-level content-based image match for the retrieval of smaller and relatively closer results of the example image. Information related to the image feature is automatically extracted from the query image by the image processing system. A technique that is not computationally intensive based on color feature is used to perform content-based matching of images. The main goal is to develop a functional image search and indexing system and to demonstrate that better retrieval results can be achieved with this proposed hybrid search technique.

Histology image analysis for carcinoma detection and grading

PubMed Central

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

2012-01-01

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

A method for digital image registration using a mathematical programming technique

NASA Technical Reports Server (NTRS)

Yao, S. S.

1973-01-01

A new algorithm based on a nonlinear programming technique to correct the geometrical distortions of one digital image with respect to another is discussed. This algorithm promises to be superior to existing ones in that it is capable of treating localized differential scaling, translational and rotational errors over the whole image plane. A series of piece-wise 'rubber-sheet' approximations are used, constrained in such a manner that a smooth approximation over the entire image can be obtained. The theoretical derivation is included. The result of using the algorithm to register four channel S065 Apollo IX digitized photography over Imperial Valley, California, is discussed in detail.

Endometrial ablation: normal appearance and complications.

PubMed

Drylewicz, Monica R; Robinson, Kathryn; Siegel, Cary Lynn

2018-03-14

Global endometrial ablation is a commonly performed, minimally invasive technique aimed at improving/resolving abnormal uterine bleeding and menorrhagia in women. As non-resectoscopic techniques have come into existence, endometrial ablation performance continues to increase due to accessibility and decreased requirements for operating room time and advanced technical training. The increased utilization of this method translates into increased imaging of patients who have undergone the procedure. An understanding of the expected imaging appearances of endometrial ablation using different modalities is important for the abdominal radiologist. In addition, the frequent usage of the technique naturally comes with complications requiring appropriate imaging work-up. We review the expected appearance of the post-endometrial ablated uterus on multiple imaging modalities and demonstrate the more common and rare complications seen in the immediate post-procedural time period and remotely.

RECOVERY ACT: MULTIMODAL IMAGING FOR SOLAR CELL MICROCRACK DETECTION

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

Janice Hudgings; Lawrence Domash

2012-02-08

Undetected microcracks in solar cells are a principal cause of failure in service due to subsequent weather exposure, mechanical flexing or diurnal temperature cycles. Existing methods have not been able to detect cracks early enough in the production cycle to prevent inadvertent shipment to customers. This program, sponsored under the DOE Photovoltaic Supply Chain and Cross-Cutting Technologies program, studied the feasibility of quantifying surface micro-discontinuities by use of a novel technique, thermoreflectance imaging, to detect surface temperature gradients with very high spatial resolution, in combination with a suite of conventional imaging methods such as electroluminescence. The project carried out laboratorymore » tests together with computational image analyses using sample solar cells with known defects supplied by industry sources or DOE National Labs. Quantitative comparisons between the effectiveness of the new technique and conventional methods were determined in terms of the smallest detectable crack. Also the robustness of the new technique for reliable microcrack detection was determined at various stages of processing such as before and after antireflectance treatments. An overall assessment is that the new technique compares favorably with existing methods such as lock-in thermography or ultrasonics. The project was 100% completed in Sept, 2010. A detailed report of key findings from this program was published as: Q.Zhou, X.Hu, K.Al-Hemyari, K.McCarthy, L.Domash and J.Hudgings, High spatial resolution characterization of silicon solar cells using thermoreflectance imaging, J. Appl. Phys, 110, 053108 (2011).« less

Comparison of existing digital image analysis systems for the analysis of Thematic Mapper data

NASA Technical Reports Server (NTRS)

Likens, W. C.; Wrigley, R. C.

1984-01-01

Most existing image analysis systems were designed with the Landsat Multi-Spectral Scanner in mind, leaving open the question of whether or not these systems could adequately process Thematic Mapper data. In this report, both hardware and software systems have been evaluated for compatibility with TM data. Lack of spectral analysis capability was not found to be a problem, though techniques for spatial filtering and texture varied. Computer processing speed and data storage of currently existing mini-computer based systems may be less than adequate. Upgrading to more powerful hardware may be required for many TM applications.

Through-wall image enhancement using fuzzy and QR decomposition.

PubMed

Riaz, Muhammad Mohsin; Ghafoor, Abdul

2014-01-01

QR decomposition and fuzzy logic based scheme is proposed for through-wall image enhancement. QR decomposition is less complex compared to singular value decomposition. Fuzzy inference engine assigns weights to different overlapping subspaces. Quantitative measures and visual inspection are used to analyze existing and proposed techniques.

Color edges extraction using statistical features and automatic threshold technique: application to the breast cancer cells.

PubMed

Ben Chaabane, Salim; Fnaiech, Farhat

2014-01-23

Color image segmentation has been so far applied in many areas; hence, recently many different techniques have been developed and proposed. In the medical imaging area, the image segmentation may be helpful to provide assistance to doctor in order to follow-up the disease of a certain patient from the breast cancer processed images. The main objective of this work is to rebuild and also to enhance each cell from the three component images provided by an input image. Indeed, from an initial segmentation obtained using the statistical features and histogram threshold techniques, the resulting segmentation may represent accurately the non complete and pasted cells and enhance them. This allows real help to doctors, and consequently, these cells become clear and easy to be counted. A novel method for color edges extraction based on statistical features and automatic threshold is presented. The traditional edge detector, based on the first and the second order neighborhood, describing the relationship between the current pixel and its neighbors, is extended to the statistical domain. Hence, color edges in an image are obtained by combining the statistical features and the automatic threshold techniques. Finally, on the obtained color edges with specific primitive color, a combination rule is used to integrate the edge results over the three color components. Breast cancer cell images were used to evaluate the performance of the proposed method both quantitatively and qualitatively. Hence, a visual and a numerical assessment based on the probability of correct classification (PC), the false classification (Pf), and the classification accuracy (Sens(%)) are presented and compared with existing techniques. The proposed method shows its superiority in the detection of points which really belong to the cells, and also the facility of counting the number of the processed cells. Computer simulations highlight that the proposed method substantially enhances the segmented image with smaller error rates better than other existing algorithms under the same settings (patterns and parameters). Moreover, it provides high classification accuracy, reaching the rate of 97.94%. Additionally, the segmentation method may be extended to other medical imaging types having similar properties.

In vivo three-dimensional photoacoustic imaging of the renal vasculature in preclinical rodent models.

PubMed

Ogunlade, Olumide; Connell, John J; Huang, Jennifer L; Zhang, Edward; Lythgoe, Mark F; Long, David A; Beard, Paul

2018-06-01

Noninvasive imaging of the kidney vasculature in preclinical murine models is important for the assessment of renal development, studying diseases and evaluating new therapies but is challenging to achieve using existing imaging modalities. Photoacoustic imaging is a promising new technique that is particularly well suited to visualizing the vasculature and could provide an alternative to existing preclinical imaging methods for studying renal vascular anatomy and function. To investigate this, an all-optical Fabry-Perot-based photoacoustic scanner was used to image the abdominal region of mice. High-resolution three-dimensional, noninvasive, label-free photoacoustic images of the mouse kidney and renal vasculature were acquired in vivo. The scanner was also used to visualize and quantify differences in the vascular architecture of the kidney in vivo due to polycystic kidney disease. This study suggests that photoacoustic imaging could be utilized as a novel preclinical imaging tool for studying the biology of renal disease.

Advanced magneto-optical microscopy: Imaging from picoseconds to centimeters - imaging spin waves and temperature distributions (invited)

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

Urs, Necdet Onur; Mozooni, Babak; Kustov, Mikhail

2016-05-15

Recent developments in the observation of magnetic domains and domain walls by wide-field optical microscopy based on the magneto-optical Kerr, Faraday, Voigt, and Gradient effect are reviewed. Emphasis is given to the existence of higher order magneto-optical effects for advanced magnetic imaging. Fundamental concepts and advances in methodology are discussed that allow for imaging of magnetic domains on various length and time scales. Time-resolved imaging of electric field induced domain wall rotation is shown. Visualization of magnetization dynamics down to picosecond temporal resolution for the imaging of spin-waves and magneto-optical multi-effect domain imaging techniques for obtaining vectorial information are demonstrated.more » Beyond conventional domain imaging, the use of a magneto-optical indicator technique for local temperature sensing is shown.« less

Hybrid cardiac imaging with MR-CAT scan: a feasibility study.

PubMed

Hillenbrand, C; Sandstede, J; Pabst, T; Hahn, D; Haase, A; Jakob, P M

2000-06-01

We demonstrate the feasibility of a new versatile hybrid imaging concept, the combined acquisition technique (CAT), for cardiac imaging. The cardiac CAT approach, which combines new methodology with existing technology, essentially integrates fast low-angle shot (FLASH) and echoplanar imaging (EPI) modules in a sequential fashion, whereby each acquisition module is employed with independently optimized imaging parameters. One important CAT sequence optimization feature is the ability to use different bandwidths for different acquisition modules. Twelve healthy subjects were imaged using three cardiac CAT acquisition strategies: a) CAT was used to reduce breath-hold duration times while maintaining constant spatial resolution; b) CAT was used to increase spatial resolution in a given breath-hold time; and c) single-heart beat CAT imaging was performed. The results obtained demonstrate the feasibility of cardiac imaging using the CAT approach and the potential of this technique to accelerate the imaging process with almost conserved image quality. Copyright 2000 Wiley-Liss, Inc.

Comparison of sonochemiluminescence images using image analysis techniques and identification of acoustic pressure fields via simulation.

PubMed

Tiong, T Joyce; Chandesa, Tissa; Yap, Yeow Hong

2017-05-01

One common method to determine the existence of cavitational activity in power ultrasonics systems is by capturing images of sonoluminescence (SL) or sonochemiluminescence (SCL) in a dark environment. Conventionally, the light emitted from SL or SCL was detected based on the number of photons. Though this method is effective, it could not identify the sonochemical zones of an ultrasonic systems. SL/SCL images, on the other hand, enable identification of 'active' sonochemical zones. However, these images often provide just qualitative data as the harvesting of light intensity data from the images is tedious and require high resolution images. In this work, we propose a new image analysis technique using pseudo-colouring images to quantify the SCL zones based on the intensities of the SCL images and followed by comparison of the active SCL zones with COMSOL simulated acoustic pressure zones. Copyright © 2016 Elsevier B.V. All rights reserved.

Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images.

PubMed

Gandhamal, Akash; Talbar, Sanjay; Gajre, Suhas; Hani, Ahmad Fadzil M; Kumar, Dileep

2017-04-01

Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images. Copyright © 2017 Elsevier Ltd. All rights reserved.

High resolution remote sensing of densely urbanised regions: a case study of Hong Kong.

PubMed

Nichol, Janet E; Wong, Man Sing

2009-01-01

Data on the urban environment such as climate or air quality is usually collected at a few point monitoring stations distributed over a city. However, the synoptic viewpoint of satellites where a whole city is visible on a single image permits the collection of spatially comprehensive data at city-wide scale. In spite of rapid developments in remote sensing systems, deficiencies in image resolution and algorithm development still exist for applications such as air quality monitoring and urban heat island analysis. This paper describes state-of-the-art techniques for enhancing and maximising the spatial detail available from satellite images, and demonstrates their applications to the densely urbanised environment of Hong Kong. An Emissivity Modulation technique for spatial enhancement of thermal satellite images permits modelling of urban microclimate in combination with other urban structural parameters at local scale. For air quality monitoring, a Minimum Reflectance Technique (MRT) has been developed for MODIS 500 m images. The techniques described can promote the routine utilization of remotely sensed images for environmental monitoring in cities of the 21(st) century.

Nonlinear secret image sharing scheme.

PubMed

Shin, Sang-Ho; Lee, Gil-Je; Yoo, Kee-Young

2014-01-01

Over the past decade, most of secret image sharing schemes have been proposed by using Shamir's technique. It is based on a linear combination polynomial arithmetic. Although Shamir's technique based secret image sharing schemes are efficient and scalable for various environments, there exists a security threat such as Tompa-Woll attack. Renvall and Ding proposed a new secret sharing technique based on nonlinear combination polynomial arithmetic in order to solve this threat. It is hard to apply to the secret image sharing. In this paper, we propose a (t, n)-threshold nonlinear secret image sharing scheme with steganography concept. In order to achieve a suitable and secure secret image sharing scheme, we adapt a modified LSB embedding technique with XOR Boolean algebra operation, define a new variable m, and change a range of prime p in sharing procedure. In order to evaluate efficiency and security of proposed scheme, we use the embedding capacity and PSNR. As a result of it, average value of PSNR and embedding capacity are 44.78 (dB) and 1.74t⌈log2 m⌉ bit-per-pixel (bpp), respectively.

Nonlinear Secret Image Sharing Scheme

PubMed Central

Shin, Sang-Ho; Yoo, Kee-Young

2014-01-01

Over the past decade, most of secret image sharing schemes have been proposed by using Shamir's technique. It is based on a linear combination polynomial arithmetic. Although Shamir's technique based secret image sharing schemes are efficient and scalable for various environments, there exists a security threat such as Tompa-Woll attack. Renvall and Ding proposed a new secret sharing technique based on nonlinear combination polynomial arithmetic in order to solve this threat. It is hard to apply to the secret image sharing. In this paper, we propose a (t, n)-threshold nonlinear secret image sharing scheme with steganography concept. In order to achieve a suitable and secure secret image sharing scheme, we adapt a modified LSB embedding technique with XOR Boolean algebra operation, define a new variable m, and change a range of prime p in sharing procedure. In order to evaluate efficiency and security of proposed scheme, we use the embedding capacity and PSNR. As a result of it, average value of PSNR and embedding capacity are 44.78 (dB) and 1.74t⌈log2⁡m⌉ bit-per-pixel (bpp), respectively. PMID:25140334

High Resolution Remote Sensing of Densely Urbanised Regions: a Case Study of Hong Kong

PubMed Central

Nichol, Janet E.; Wong, Man Sing

2009-01-01

Data on the urban environment such as climate or air quality is usually collected at a few point monitoring stations distributed over a city. However, the synoptic viewpoint of satellites where a whole city is visible on a single image permits the collection of spatially comprehensive data at city-wide scale. In spite of rapid developments in remote sensing systems, deficiencies in image resolution and algorithm development still exist for applications such as air quality monitoring and urban heat island analysis. This paper describes state-of-the-art techniques for enhancing and maximising the spatial detail available from satellite images, and demonstrates their applications to the densely urbanised environment of Hong Kong. An Emissivity Modulation technique for spatial enhancement of thermal satellite images permits modelling of urban microclimate in combination with other urban structural parameters at local scale. For air quality monitoring, a Minimum Reflectance Technique (MRT) has been developed for MODIS 500 m images. The techniques described can promote the routine utilization of remotely sensed images for environmental monitoring in cities of the 21st century. PMID:22408549

Rank-based decompositions of morphological templates.

PubMed

Sussner, P; Ritter, G X

2000-01-01

Methods for matrix decomposition have found numerous applications in image processing, in particular for the problem of template decomposition. Since existing matrix decomposition techniques are mainly concerned with the linear domain, we consider it timely to investigate matrix decomposition techniques in the nonlinear domain with applications in image processing. The mathematical basis for these investigations is the new theory of rank within minimax algebra. Thus far, only minimax decompositions of rank 1 and rank 2 matrices into outer product expansions are known to the image processing community. We derive a heuristic algorithm for the decomposition of matrices having arbitrary rank.

An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

PubMed Central

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

PubMed

Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

2015-01-01

Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

Interpretation of ERTS-MSS images of a Savanna area in eastern Colombia

NASA Technical Reports Server (NTRS)

Elberson, G. W. W.

1973-01-01

The application of ERTS-1 imagery for extrapolating existing soil maps into unmapped areas of the Llanos Orientales of Colombia, South America is discussed. Interpretations of ERTS-1 data were made according to conventional photointerpretation techniques. Most units delineated in the existing reconnaissance soil map at a scale of 1:250,000 could be recognized and delineated in the ERTS image. The methods of interpretation are described and the results obtained for specific areas are analyzed.

Effect of spatial image support in detecting long-term vegetation change from satellite time-series

USDA-ARS?s Scientific Manuscript database

Context Arid rangelands have been severely degraded over the past century. Multi-temporal remote sensing techniques are ideally suited to detect significant changes in ecosystem state; however, considerable uncertainty exists regarding the effects of changing image resolution on their ability to de...

MRI artifact reduction and quality improvement in the upper abdomen with PROPELLER and prospective acquisition correction (PACE) technique.

PubMed

Hirokawa, Yuusuke; Isoda, Hiroyoshi; Maetani, Yoji S; Arizono, Shigeki; Shimada, Kotaro; Togashi, Kaori

2008-10-01

The purpose of this study was to evaluate the effectiveness of the periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER [BLADE in the MR systems from Siemens Medical Solutions]) with a respiratory compensation technique for motion correction, image noise reduction, improved sharpness of liver edge, and image quality of the upper abdomen. Twenty healthy adult volunteers with a mean age of 28 years (age range, 23-42 years) underwent upper abdominal MRI with a 1.5-T scanner. For each subject, fat-saturated T2-weighted turbo spin-echo (TSE) sequences with respiratory compensation (prospective acquisition correction [PACE]) were performed with and without the BLADE technique. Ghosting artifact, artifacts except ghosting artifact such as respiratory motion and bowel movement, sharpness of liver edge, image noise, and overall image quality were evaluated visually by three radiologists using a 5-point scale for qualitative analysis. The Wilcoxon's signed rank test was used to determine whether a significant difference existed between images with and without BLADE. A p value less than 0.05 was considered to be statistically significant. In the BLADE images, image artifacts, sharpness of liver edge, image noise, and overall image quality were significantly improved (p < 0.001). With the BLADE technique, T2-weighted TSE images of the upper abdomen could provide reduced image artifacts including ghosting artifact and image noise and provide better image quality.

Processing techniques for digital sonar images from GLORIA.

USGS Publications Warehouse

Chavez, P.S.

1986-01-01

Image processing techniques have been developed to handle data from one of the newest members of the remote sensing family of digital imaging systems. This paper discusses software to process data collected by the GLORIA (Geological Long Range Inclined Asdic) sonar imaging system, designed and built by the Institute of Oceanographic Sciences (IOS) in England, to correct for both geometric and radiometric distortions that exist in the original 'raw' data. Preprocessing algorithms that are GLORIA-specific include corrections for slant-range geometry, water column offset, aspect ratio distortion, changes in the ship's velocity, speckle noise, and shading problems caused by the power drop-off which occurs as a function of range.-from Author

Nanoscale Fresnel coherent diffraction imaging tomography using ptychography.

PubMed

Peterson, I; Abbey, B; Putkunz, C T; Vine, D J; van Riessen, G A; Cadenazzi, G A; Balaur, E; Ryan, R; Quiney, H M; McNulty, I; Peele, A G; Nugent, K A

2012-10-22

We demonstrate Fresnel Coherent Diffractive Imaging (FCDI) tomography in the X-ray regime. The method uses an incident X-ray illumination with known curvature in combination with ptychography to overcome existing problems in diffraction imaging. The resulting tomographic reconstruction represents a 3D map of the specimen's complex refractive index at nano-scale resolution. We use this technique to image a lithographically fabricated glass capillary, in which features down to 70nm are clearly resolved.

Improved localization accuracy in stochastic super-resolution fluorescence microscopy by K-factor image deshadowing

PubMed Central

Ilovitsh, Tali; Meiri, Amihai; Ebeling, Carl G.; Menon, Rajesh; Gerton, Jordan M.; Jorgensen, Erik M.; Zalevsky, Zeev

2013-01-01

Localization of a single fluorescent particle with sub-diffraction-limit accuracy is a key merit in localization microscopy. Existing methods such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) achieve localization accuracies of single emitters that can reach an order of magnitude lower than the conventional resolving capabilities of optical microscopy. However, these techniques require a sparse distribution of simultaneously activated fluorophores in the field of view, resulting in larger time needed for the construction of the full image. In this paper we present the use of a nonlinear image decomposition algorithm termed K-factor, which reduces an image into a nonlinear set of contrast-ordered decompositions whose joint product reassembles the original image. The K-factor technique, when implemented on raw data prior to localization, can improve the localization accuracy of standard existing methods, and also enable the localization of overlapping particles, allowing the use of increased fluorophore activation density, and thereby increased data collection speed. Numerical simulations of fluorescence data with random probe positions, and especially at high densities of activated fluorophores, demonstrate an improvement of up to 85% in the localization precision compared to single fitting techniques. Implementing the proposed concept on experimental data of cellular structures yielded a 37% improvement in resolution for the same super-resolution image acquisition time, and a decrease of 42% in the collection time of super-resolution data with the same resolution. PMID:24466491

Unconventional methods of imaging: computational microscopy and compact implementations

NASA Astrophysics Data System (ADS)

McLeod, Euan; Ozcan, Aydogan

2016-07-01

In the past two decades or so, there has been a renaissance of optical microscopy research and development. Much work has been done in an effort to improve the resolution and sensitivity of microscopes, while at the same time to introduce new imaging modalities, and make existing imaging systems more efficient and more accessible. In this review, we look at two particular aspects of this renaissance: computational imaging techniques and compact imaging platforms. In many cases, these aspects go hand-in-hand because the use of computational techniques can simplify the demands placed on optical hardware in obtaining a desired imaging performance. In the first main section, we cover lens-based computational imaging, in particular, light-field microscopy, structured illumination, synthetic aperture, Fourier ptychography, and compressive imaging. In the second main section, we review lensfree holographic on-chip imaging, including how images are reconstructed, phase recovery techniques, and integration with smart substrates for more advanced imaging tasks. In the third main section we describe how these and other microscopy modalities have been implemented in compact and field-portable devices, often based around smartphones. Finally, we conclude with some comments about opportunities and demand for better results, and where we believe the field is heading.

Nanomaterial characterization through image treatment, 3D reconstruction and AI techniques

NASA Astrophysics Data System (ADS)

Lopez de Uralde Huarte, Juan Jose

Nanotechnology is not only the science of the future, but it is indeed the science of today. It is used in all sectors, from health to energy, including information technologies and transport. For the present investigation, we have taken carbon black as a use case. This nanomaterial is mixed with a wide variety of materials to improve their properties, like abrasion resistance, tire and plastic wear or tinting strength in pigments. Nowadays, indirect methods of analysis, like oil absorption or nitrogen adsorption are the most common techniques of the nanomaterial industry. These procedures measure the change in the physical state while adding oil and nitrogen. In this way, the superficial area is estimated and related with the properties of the material. Nevertheless, we have chosen to improve the existent direct methods, which consist in analysing microscopy images of nanomaterials. We have made progress in the image processing treatments and in the extracted features. In fact, some of them have overcome the existing features in the literature. In addition, we have applied, for the first time in the literature, machine learning to aggregate categorization. In this way, we identify automatically their morphology, which will determine the final properties of the material that is mixed with. Finally, we have presented an aggregate reconstruction genetic algorithm that, with only two orthogonal images, provides more information than a tomography, which needs a lot of images. To summarize, we have improved the state of the art in direct analysing techniques, allowing in the near future the replacement of the current indirect techniques.

Dual PET and Near-Infrared Fluorescence Imaging Probes as Tools for Imaging in Oncology

PubMed Central

An, Fei-Fei; Chan, Mark; Kommidi, Harikrishna; Ting, Richard

2016-01-01

OBJECTIVE The purpose of this article is to summarize advances in PET fluorescence resolution, agent design, and preclinical imaging that make a growing case for clinical PET fluorescence imaging. CONCLUSION Existing SPECT, PET, fluorescence, and MRI contrast imaging techniques are already deeply integrated into the management of cancer, from initial diagnosis to the observation and management of metastases. Combined positron-emitting fluorescent contrast agents can convey new or substantial benefits that improve on these proven clinical contrast agents. PMID:27223168

Demonstration of a time-integrated short line of sight neutron imaging system for inertial confinement fusion

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

Simpson, R., E-mail: raspberry@lanl.gov; Danly, C.; Fatherley, V. E.

2015-12-15

The Neutron Imaging System (NIS) is an important diagnostic for understanding implosions of deuterium-tritium capsules at the National Ignition Facility. While the detectors for the existing system must be positioned 28 m from the source to produce sufficient imaging magnification and resolution, recent testing of a new short line of sight neutron imaging system has shown sufficient resolution to allow reconstruction of the source image with quality similar to that of the existing NIS on a 11.6 m line of sight. The new system used the existing pinhole aperture array and a stack of detectors composed of 2 mm thickmore » high-density polyethylene converter material followed by an image plate. In these detectors, neutrons enter the converter material and interact with protons, which recoil and deposit energy within the thin active layer of the image plate through ionization losses. The described system produces time-integrated images for all neutron energies passing through the pinhole. We present details of the measurement scheme for this novel technique to produce energy-integrated neutron images as well as source reconstruction results from recent experiments at NIF.« less

Blind technique using blocking artifacts and entropy of histograms for image tampering detection

NASA Astrophysics Data System (ADS)

Manu, V. T.; Mehtre, B. M.

2017-06-01

The tremendous technological advancements in recent times has enabled people to create, edit and circulate images easily than ever before. As a result of this, ensuring the integrity and authenticity of the images has become challenging. Malicious editing of images to deceive the viewer is referred to as image tampering. A widely used image tampering technique is image splicing or compositing, in which regions from different images are copied and pasted. In this paper, we propose a tamper detection method utilizing the blocking and blur artifacts which are the footprints of splicing. The classification of images as tampered or not, is done based on the standard deviations of the entropy histograms and block discrete cosine transformations. We can detect the exact boundaries of the tampered area in the image, if the image is classified as tampered. Experimental results on publicly available image tampering datasets show that the proposed method outperforms the existing methods in terms of accuracy.

Advanced Computer Image Generation Techniques Exploiting Perceptual Characteristics. Final Report.

ERIC Educational Resources Information Center

Stenger, Anthony J.; And Others

This study suggests and identifies computer image generation (CIG) algorithms for visual simulation that improve the training effectiveness of CIG simulators and identifies areas of basic research in visual perception that are significant for improving CIG technology. The first phase of the project entailed observing three existing CIG simulators.…

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images

PubMed Central

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-01-01

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. PMID:26007744

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

PubMed

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-05-22

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

A Bio Medical Waste Identification and Classification Algorithm Using Mltrp and Rvm.

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

We aimed to extract the histogram features for text analysis and, to classify the types of Bio Medical Waste (BMW) for garbage disposal and management. The given BMW was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. After that, the histogram features of the filtered image were extracted with the help of proposed Modified Local Tetra Pattern (MLTrP) technique. Finally, the Relevance Vector Machine (RVM) was used to classify the BMW into human body parts, plastics, cotton and liquids. The BMW image was collected from the garbage image dataset for analysis. The performance of the proposed BMW identification and classification system was evaluated in terms of sensitivity, specificity, classification rate and accuracy with the help of MATLAB. When compared to the existing techniques, the proposed techniques provided the better results. This work proposes a new texture analysis and classification technique for BMW management and disposal. It can be used in many real time applications such as hospital and healthcare management systems for proper BMW disposal.

Particle Streak Anemometry: A New Method for Proximal Flow Sensing from Aircraft

NASA Astrophysics Data System (ADS)

Nichols, T. W.

Accurate sensing of relative air flow direction from fixed-wing small unmanned aircraft (sUAS) is challenging with existing multi-hole pitot-static and vane systems. Sub-degree direction accuracy is generally not available on such systems and disturbances to the local flow field, induced by the airframe, introduce an additional error source. An optical imaging approach to make a relative air velocity measurement with high-directional accuracy is presented. Optical methods offer the capability to make a proximal measurement in undisturbed air outside of the local flow field without the need to place sensors on vulnerable probes extended ahead of the aircraft. Current imaging flow analysis techniques for laboratory use rely on relatively thin imaged volumes and sophisticated hardware and intensity thresholding in low-background conditions. A new method is derived and assessed using a particle streak imaging technique that can be implemented with low-cost commercial cameras and illumination systems, and can function in imaged volumes of arbitrary depth with complex background signal. The new technique, referred to as particle streak anemometry (PSA) (to differentiate from particle streak velocimetry which makes a field measurement rather than a single bulk flow measurement) utilizes a modified Canny Edge detection algorithm with a connected component analysis and principle component analysis to detect streak ends in complex imaging conditions. A linear solution for the air velocity direction is then implemented with a random sample consensus (RANSAC) solution approach. A single DOF non-linear, non-convex optimization problem is then solved for the air speed through an iterative approach. The technique was tested through simulation and wind tunnel tests yielding angular accuracies under 0.2 degrees, superior to the performance of existing commercial systems. Air speed error standard deviations varied from 1.6 to 2.2 m/s depending on the techniques of implementation. While air speed sensing is secondary to accurate flow direction measurement, the air speed results were in line with commercial pitot static systems at low speeds.

A dual-modal retinal imaging system with adaptive optics.

PubMed

Meadway, Alexander; Girkin, Christopher A; Zhang, Yuhua

2013-12-02

An adaptive optics scanning laser ophthalmoscope (AO-SLO) is adapted to provide optical coherence tomography (OCT) imaging. The AO-SLO function is unchanged. The system uses the same light source, scanning optics, and adaptive optics in both imaging modes. The result is a dual-modal system that can acquire retinal images in both en face and cross-section planes at the single cell level. A new spectral shaping method is developed to reduce the large sidelobes in the coherence profile of the OCT imaging when a non-ideal source is used with a minimal introduction of noise. The technique uses a combination of two existing digital techniques. The thickness and position of the traditionally named inner segment/outer segment junction are measured from individual photoreceptors. In-vivo images of healthy and diseased human retinas are demonstrated.

Texture functions in image analysis: A computationally efficient solution

NASA Technical Reports Server (NTRS)

Cox, S. C.; Rose, J. F.

1983-01-01

A computationally efficient means for calculating texture measurements from digital images by use of the co-occurrence technique is presented. The calculation of the statistical descriptors of image texture and a solution that circumvents the need for calculating and storing a co-occurrence matrix are discussed. The results show that existing efficient algorithms for calculating sums, sums of squares, and cross products can be used to compute complex co-occurrence relationships directly from the digital image input.

Two-dimensional photoacoustic imaging of femtosecond filament in water

NASA Astrophysics Data System (ADS)

Potemkin, F. V.; Mareev, E. I.; Rumiantsev, B. V.; Bychkov, A. S.; Karabutov, A. A.; Cherepetskaya, E. B.; Makarov, V. A.

2018-07-01

We report a first-of-its-kind optoacoustic tomography of a femtosecond filament in water. Using a broadband (~100 MHz) piezoelectric transducer and a back-projection reconstruction technique, a single filament profile was retrieved. Obtained pressure distribution induced by the femtosecond filament allowed us to identify the size of the core and the energy reservoir with spatial resolution better than 10 µm. The photoacoustic imaging provides direct measurements of the energy deposition into the medium under filamentation of ultrashort laser pulses that cannot be obtained by existing techniques. In combination with a relative simplicity and high accuracy, photoacoustic imaging can be considered as a breakthrough instrument for filamentation investigation.

The Commercial Challenges Of Pacs

NASA Astrophysics Data System (ADS)

Vanden Brink, John A.

1984-08-01

The increasing use of digital imaging techniques create a need for improved methods of digital processing, communication and archiving. However, the commercial opportunity is dependent on the resolution of a number of issues. These issues include proof that digital processes are more cost effective than present techniques, implementation of information system support in the imaging activity, implementation of industry standards, conversion of analog images to digital formats, definition of clinical needs, the implications of the purchase decision and technology requirements. In spite of these obstacles, a market is emerging, served by new and existing companies, that may become a $500 million market (U.S.) by 1990 for equipment and supplies.

Measurement of absolute regional lung air volumes from near-field x-ray speckles.

PubMed

Leong, Andrew F T; Paganin, David M; Hooper, Stuart B; Siew, Melissa L; Kitchen, Marcus J

2013-11-18

Propagation-based phase contrast x-ray (PBX) imaging yields high contrast images of the lung where airways that overlap in projection coherently scatter the x-rays, giving rise to a speckled intensity due to interference effects. Our previous works have shown that total and regional changes in lung air volumes can be accurately measured from two-dimensional (2D) absorption or phase contrast images when the subject is immersed in a water-filled container. In this paper we demonstrate how the phase contrast speckle patterns can be used to directly measure absolute regional lung air volumes from 2D PBX images without the need for a water-filled container. We justify this technique analytically and via simulation using the transport-of-intensity equation and calibrate the technique using our existing methods for measuring lung air volume. Finally, we show the full capabilities of this technique for measuring regional differences in lung aeration.

High dynamic range coding imaging system

NASA Astrophysics Data System (ADS)

Wu, Renfan; Huang, Yifan; Hou, Guangqi

2014-10-01

We present a high dynamic range (HDR) imaging system design scheme based on coded aperture technique. This scheme can help us obtain HDR images which have extended depth of field. We adopt Sparse coding algorithm to design coded patterns. Then we utilize the sensor unit to acquire coded images under different exposure settings. With the guide of the multiple exposure parameters, a series of low dynamic range (LDR) coded images are reconstructed. We use some existing algorithms to fuse and display a HDR image by those LDR images. We build an optical simulation model and get some simulation images to verify the novel system.

A Taxonomy of 3D Occluded Objects Recognition Techniques

NASA Astrophysics Data System (ADS)

Soleimanizadeh, Shiva; Mohamad, Dzulkifli; Saba, Tanzila; Al-ghamdi, Jarallah Saleh

2016-03-01

The overall performances of object recognition techniques under different condition (e.g., occlusion, viewpoint, and illumination) have been improved significantly in recent years. New applications and hardware are shifted towards digital photography, and digital media. This faces an increase in Internet usage requiring object recognition for certain applications; particularly occulded objects. However occlusion is still an issue unhandled, interlacing the relations between extracted feature points through image, research is going on to develop efficient techniques and easy to use algorithms that would help users to source images; this need to overcome problems and issues regarding occlusion. The aim of this research is to review recognition occluded objects algorithms and figure out their pros and cons to solve the occlusion problem features, which are extracted from occluded object to distinguish objects from other co-existing objects by determining the new techniques, which could differentiate the occluded fragment and sections inside an image.

Retinal Image Simulation of Subjective Refraction Techniques

PubMed Central

Perches, Sara; Collados, M. Victoria; Ares, Jorge

2016-01-01

Refraction techniques make it possible to determine the most appropriate sphero-cylindrical lens prescription to achieve the best possible visual quality. Among these techniques, subjective refraction (i.e., patient’s response-guided refraction) is the most commonly used approach. In this context, this paper’s main goal is to present a simulation software that implements in a virtual manner various subjective-refraction techniques—including Jackson’s Cross-Cylinder test (JCC)—relying all on the observation of computer-generated retinal images. This software has also been used to evaluate visual quality when the JCC test is performed in multifocal-contact-lens wearers. The results reveal this software’s usefulness to simulate the retinal image quality that a particular visual compensation provides. Moreover, it can help to gain a deeper insight and to improve existing refraction techniques and it can be used for simulated training. PMID:26938648

Artificial intelligence and signal processing for infrastructure assessment

NASA Astrophysics Data System (ADS)

Assaleh, Khaled; Shanableh, Tamer; Yehia, Sherif

2015-04-01

The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.

Automatic DNA Diagnosis for 1D Gel Electrophoresis Images using Bio-image Processing Technique.

PubMed

Intarapanich, Apichart; Kaewkamnerd, Saowaluck; Shaw, Philip J; Ukosakit, Kittipat; Tragoonrung, Somvong; Tongsima, Sissades

2015-01-01

DNA gel electrophoresis is a molecular biology technique for separating different sizes of DNA fragments. Applications of DNA gel electrophoresis include DNA fingerprinting (genetic diagnosis), size estimation of DNA, and DNA separation for Southern blotting. Accurate interpretation of DNA banding patterns from electrophoretic images can be laborious and error prone when a large number of bands are interrogated manually. Although many bio-imaging techniques have been proposed, none of them can fully automate the typing of DNA owing to the complexities of migration patterns typically obtained. We developed an image-processing tool that automatically calls genotypes from DNA gel electrophoresis images. The image processing workflow comprises three main steps: 1) lane segmentation, 2) extraction of DNA bands and 3) band genotyping classification. The tool was originally intended to facilitate large-scale genotyping analysis of sugarcane cultivars. We tested the proposed tool on 10 gel images (433 cultivars) obtained from polyacrylamide gel electrophoresis (PAGE) of PCR amplicons for detecting intron length polymorphisms (ILP) on one locus of the sugarcanes. These gel images demonstrated many challenges in automated lane/band segmentation in image processing including lane distortion, band deformity, high degree of noise in the background, and bands that are very close together (doublets). Using the proposed bio-imaging workflow, lanes and DNA bands contained within are properly segmented, even for adjacent bands with aberrant migration that cannot be separated by conventional techniques. The software, called GELect, automatically performs genotype calling on each lane by comparing with an all-banding reference, which was created by clustering the existing bands into the non-redundant set of reference bands. The automated genotype calling results were verified by independent manual typing by molecular biologists. This work presents an automated genotyping tool from DNA gel electrophoresis images, called GELect, which was written in Java and made available through the imageJ framework. With a novel automated image processing workflow, the tool can accurately segment lanes from a gel matrix, intelligently extract distorted and even doublet bands that are difficult to identify by existing image processing tools. Consequently, genotyping from DNA gel electrophoresis can be performed automatically allowing users to efficiently conduct large scale DNA fingerprinting via DNA gel electrophoresis. The software is freely available from http://www.biotec.or.th/gi/tools/gelect.

Imaging the inside of thick structures using cosmic rays

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

Guardincerri, E., E-mail: elenaguardincerri@lanl.gov; Durham, J. M.; Morris, C.

2016-01-15

The authors present here a new method to image reinforcement elements inside thick structures and the results of a demonstration measurement performed on a mock-up wall built at Los Alamos National Laboratory. The method, referred to as “multiple scattering muon radiography”, relies on the use of cosmic-ray muons as probes. The work described in this article was performed to prove the viability of the technique as a means to image the interior of the dome of Florence Cathedral Santa Maria del Fiore, one of the UNESCO World Heritage sites and among the highest profile buildings in existence. Its result showsmore » the effectiveness of the technique as a tool to radiograph thick structures and image denser object inside them.« less

Alignment Solution for CT Image Reconstruction using Fixed Point and Virtual Rotation Axis.

PubMed

Jun, Kyungtaek; Yoon, Seokhwan

2017-01-25

Since X-ray tomography is now widely adopted in many different areas, it becomes more crucial to find a robust routine of handling tomographic data to get better quality of reconstructions. Though there are several existing techniques, it seems helpful to have a more automated method to remove the possible errors that hinder clearer image reconstruction. Here, we proposed an alternative method and new algorithm using the sinogram and the fixed point. An advanced physical concept of Center of Attenuation (CA) was also introduced to figure out how this fixed point is applied to the reconstruction of image having errors we categorized in this article. Our technique showed a promising performance in restoring images having translation and vertical tilt errors.

Constrained Metric Learning by Permutation Inducing Isometries.

PubMed

Bosveld, Joel; Mahmood, Arif; Huynh, Du Q; Noakes, Lyle

2016-01-01

The choice of metric critically affects the performance of classification and clustering algorithms. Metric learning algorithms attempt to improve performance, by learning a more appropriate metric. Unfortunately, most of the current algorithms learn a distance function which is not invariant to rigid transformations of images. Therefore, the distances between two images and their rigidly transformed pair may differ, leading to inconsistent classification or clustering results. We propose to constrain the learned metric to be invariant to the geometry preserving transformations of images that induce permutations in the feature space. The constraint that these transformations are isometries of the metric ensures consistent results and improves accuracy. Our second contribution is a dimension reduction technique that is consistent with the isometry constraints. Our third contribution is the formulation of the isometry constrained logistic discriminant metric learning (IC-LDML) algorithm, by incorporating the isometry constraints within the objective function of the LDML algorithm. The proposed algorithm is compared with the existing techniques on the publicly available labeled faces in the wild, viewpoint-invariant pedestrian recognition, and Toy Cars data sets. The IC-LDML algorithm has outperformed existing techniques for the tasks of face recognition, person identification, and object classification by a significant margin.

Theory and applications of structured light single pixel imaging

NASA Astrophysics Data System (ADS)

Stokoe, Robert J.; Stockton, Patrick A.; Pezeshki, Ali; Bartels, Randy A.

2018-02-01

Many single-pixel imaging techniques have been developed in recent years. Though the methods of image acquisition vary considerably, the methods share unifying features that make general analysis possible. Furthermore, the methods developed thus far are based on intuitive processes that enable simple and physically-motivated reconstruction algorithms, however, this approach may not leverage the full potential of single-pixel imaging. We present a general theoretical framework of single-pixel imaging based on frame theory, which enables general, mathematically rigorous analysis. We apply our theoretical framework to existing single-pixel imaging techniques, as well as provide a foundation for developing more-advanced methods of image acquisition and reconstruction. The proposed frame theoretic framework for single-pixel imaging results in improved noise robustness, decrease in acquisition time, and can take advantage of special properties of the specimen under study. By building on this framework, new methods of imaging with a single element detector can be developed to realize the full potential associated with single-pixel imaging.

Mechanism of Chronic Pain in Rodent Brain Imaging

NASA Astrophysics Data System (ADS)

Chang, Pei-Ching

Chronic pain is a significant health problem that greatly impacts the quality of life of individuals and imparts high costs to society. Despite intense research effort in understanding of the mechanism of pain, chronic pain remains a clinical problem that has few effective therapies. The advent of human brain imaging research in recent years has changed the way that chronic pain is viewed. To further extend the use of human brain imaging techniques for better therapies, the adoption of imaging technique onto the animal pain models is essential, in which underlying brain mechanisms can be systematically studied using various combination of imaging and invasive techniques. The general goal of this thesis is to addresses how brain develops and maintains chronic pain in an animal model using fMRI. We demonstrate that nucleus accumbens, the central component of mesolimbic circuitry, is essential in development of chronic pain. To advance our imaging technique, we develop an innovative methodology to carry out fMRI in awake, conscious rat. Using this cutting-edge technique, we show that allodynia is assoicated with shift brain response toward neural circuits associated nucleus accumbens and prefrontal cortex that regulate affective and cognitive component of pain. Taken together, this thesis provides a deeper understanding of how brain mediates pain. It builds on the existing body of knowledge through maximizing the depth of insight into brain imaging of chronic pain.

Novel Fourier-based iterative reconstruction for sparse fan projection using alternating direction total variation minimization

NASA Astrophysics Data System (ADS)

Zhao, Jin; Han-Ming, Zhang; Bin, Yan; Lei, Li; Lin-Yuan, Wang; Ai-Long, Cai

2016-03-01

Sparse-view x-ray computed tomography (CT) imaging is an interesting topic in CT field and can efficiently decrease radiation dose. Compared with spatial reconstruction, a Fourier-based algorithm has advantages in reconstruction speed and memory usage. A novel Fourier-based iterative reconstruction technique that utilizes non-uniform fast Fourier transform (NUFFT) is presented in this work along with advanced total variation (TV) regularization for a fan sparse-view CT. The proposition of a selective matrix contributes to improve reconstruction quality. The new method employs the NUFFT and its adjoin to iterate back and forth between the Fourier and image space. The performance of the proposed algorithm is demonstrated through a series of digital simulations and experimental phantom studies. Results of the proposed algorithm are compared with those of existing TV-regularized techniques based on compressed sensing method, as well as basic algebraic reconstruction technique. Compared with the existing TV-regularized techniques, the proposed Fourier-based technique significantly improves convergence rate and reduces memory allocation, respectively. Projected supported by the National High Technology Research and Development Program of China (Grant No. 2012AA011603) and the National Natural Science Foundation of China (Grant No. 61372172).

Polarization-based and specular-reflection-based noncontact latent fingerprint imaging and lifting

NASA Astrophysics Data System (ADS)

Lin, Shih-Schön; Yemelyanov, Konstantin M.; Pugh, Edward N., Jr.; Engheta, Nader

2006-09-01

In forensic science the finger marks left unintentionally by people at a crime scene are referred to as latent fingerprints. Most existing techniques to detect and lift latent fingerprints require application of a certain material directly onto the exhibit. The chemical and physical processing applied to the fingerprint potentially degrades or prevents further forensic testing on the same evidence sample. Many existing methods also have deleterious side effects. We introduce a method to detect and extract latent fingerprint images without applying any powder or chemicals on the object. Our method is based on the optical phenomena of polarization and specular reflection together with the physiology of fingerprint formation. The recovered image quality is comparable to existing methods. In some cases, such as the sticky side of tape, our method shows unique advantages.

Classification of high dimensional multispectral image data

NASA Technical Reports Server (NTRS)

Hoffbeck, Joseph P.; Landgrebe, David A.

1993-01-01

A method for classifying high dimensional remote sensing data is described. The technique uses a radiometric adjustment to allow a human operator to identify and label training pixels by visually comparing the remotely sensed spectra to laboratory reflectance spectra. Training pixels for material without obvious spectral features are identified by traditional means. Features which are effective for discriminating between the classes are then derived from the original radiance data and used to classify the scene. This technique is applied to Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data taken over Cuprite, Nevada in 1992, and the results are compared to an existing geologic map. This technique performed well even with noisy data and the fact that some of the materials in the scene lack absorption features. No adjustment for the atmosphere or other scene variables was made to the data classified. While the experimental results compare favorably with an existing geologic map, the primary purpose of this research was to demonstrate the classification method, as compared to the geology of the Cuprite scene.

Automatic Tracking Of Remote Sensing Precipitation Data Using Genetic Algorithm Image Registration Based Automatic Morphing: September 1999 Storm Floyd Case Study

NASA Astrophysics Data System (ADS)

Chiu, L.; Vongsaard, J.; El-Ghazawi, T.; Weinman, J.; Yang, R.; Kafatos, M.

U Due to the poor temporal sampling by satellites, data gaps exist in satellite derived time series of precipitation. This poses a challenge for assimilating rain- fall data into forecast models. To yield a continuous time series, the classic image processing technique of digital image morphing has been used. However, the digital morphing technique was applied manually and that is time consuming. In order to avoid human intervention in the process, an automatic procedure for image morphing is needed for real-time operations. For this purpose, Genetic Algorithm Based Image Registration Automatic Morphing (GRAM) model was developed and tested in this paper. Specifically, automatic morphing technique was integrated with Genetic Algo- rithm and Feature Based Image Metamorphosis technique to fill in data gaps between satellite coverage. The technique was tested using NOWRAD data which are gener- ated from the network of NEXRAD radars. Time series of NOWRAD data from storm Floyd that occurred at the US eastern region on September 16, 1999 for 00:00, 01:00, 02:00,03:00, and 04:00am were used. The GRAM technique was applied to data col- lected at 00:00 and 04:00am. These images were also manually morphed. Images at 01:00, 02:00 and 03:00am were interpolated from the GRAM and manual morphing and compared with the original NOWRAD rainrates. The results show that the GRAM technique outperforms manual morphing. The correlation coefficients between the im- ages generated using manual morphing are 0.905, 0.900, and 0.905 for the images at 01:00, 02:00,and 03:00 am, while the corresponding correlation coefficients are 0.946, 0.911, and 0.913, respectively, based on the GRAM technique. Index terms ­ Remote Sensing, Image Registration, Hydrology, Genetic Algorithm, Morphing, NEXRAD

Simulating Building Fires for Movies

NASA Technical Reports Server (NTRS)

Rodriguez, Ricardo C.; Johnson, Randall P.

1987-01-01

Fire scenes for cinematography staged at relatively low cost in method that combines several existing techniques. Nearly realistic scenes, suitable for firefighter training, produced with little specialized equipment. Sequences of scenes set up quickly and easily, without compromising safety because model not burned. Images of fire, steam, and smoke superimposed on image of building to simulate burning of building.

Nonlinear Interferometric Vibrational Imaging (NIVI) with Novel Optical Sources

NASA Astrophysics Data System (ADS)

Boppart, Stephen A.; King, Matthew D.; Liu, Yuan; Tu, Haohua; Gruebele, Martin

Optical imaging is essential in medicine and in fundamental studies of biological systems. Although many existing imaging modalities can supply valuable information, not all are capable of label-free imaging with high-contrast and molecular specificity. The application of molecular or nanoparticle contrast agents may adversely influence the biological system under investigation. These substances also present ongoing concerns over toxicity or particle clearance, which must be properly addressed before their approval for in vivo human imaging. Hence there is an increasing appreciation for label-free imaging techniques. It is of primary importance to develop imaging techniques that can indiscriminately identify and quantify biochemical compositions to high degrees of sensitivity and specificity through only the intrinsic optical response of endogenous molecular species. The development and use of nonlinear interferometric vibrational imaging, which is based on the interferometric detection of optical signals from coherent anti-Stokes Raman scattering (CARS), along with novel optical sources, offers the potential for label-free molecular imaging.

Accelerated Microstructure Imaging via Convex Optimization (AMICO) from diffusion MRI data.

PubMed

Daducci, Alessandro; Canales-Rodríguez, Erick J; Zhang, Hui; Dyrby, Tim B; Alexander, Daniel C; Thiran, Jean-Philippe

2015-01-15

Microstructure imaging from diffusion magnetic resonance (MR) data represents an invaluable tool to study non-invasively the morphology of tissues and to provide a biological insight into their microstructural organization. In recent years, a variety of biophysical models have been proposed to associate particular patterns observed in the measured signal with specific microstructural properties of the neuronal tissue, such as axon diameter and fiber density. Despite very appealing results showing that the estimated microstructure indices agree very well with histological examinations, existing techniques require computationally very expensive non-linear procedures to fit the models to the data which, in practice, demand the use of powerful computer clusters for large-scale applications. In this work, we present a general framework for Accelerated Microstructure Imaging via Convex Optimization (AMICO) and show how to re-formulate this class of techniques as convenient linear systems which, then, can be efficiently solved using very fast algorithms. We demonstrate this linearization of the fitting problem for two specific models, i.e. ActiveAx and NODDI, providing a very attractive alternative for parameter estimation in those techniques; however, the AMICO framework is general and flexible enough to work also for the wider space of microstructure imaging methods. Results demonstrate that AMICO represents an effective means to accelerate the fit of existing techniques drastically (up to four orders of magnitude faster) while preserving accuracy and precision in the estimated model parameters (correlation above 0.9). We believe that the availability of such ultrafast algorithms will help to accelerate the spread of microstructure imaging to larger cohorts of patients and to study a wider spectrum of neurological disorders. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Automatic screening and classification of diabetic retinopathy and maculopathy using fuzzy image processing.

PubMed

Rahim, Sarni Suhaila; Palade, Vasile; Shuttleworth, James; Jayne, Chrisina

2016-12-01

Digital retinal imaging is a challenging screening method for which effective, robust and cost-effective approaches are still to be developed. Regular screening for diabetic retinopathy and diabetic maculopathy diseases is necessary in order to identify the group at risk of visual impairment. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images by employing fuzzy image processing techniques. The paper first introduces the existing systems for diabetic retinopathy screening, with an emphasis on the maculopathy detection methods. The proposed medical decision support system consists of four parts, namely: image acquisition, image preprocessing including four retinal structures localisation, feature extraction and the classification of diabetic retinopathy and maculopathy. A combination of fuzzy image processing techniques, the Circular Hough Transform and several feature extraction methods are implemented in the proposed system. The paper also presents a novel technique for the macula region localisation in order to detect the maculopathy. In addition to the proposed detection system, the paper highlights a novel online dataset and it presents the dataset collection, the expert diagnosis process and the advantages of our online database compared to other public eye fundus image databases for diabetic retinopathy purposes.

A quantitative damage imaging technique based on enhanced CCRTM for composite plates using 2D scan

NASA Astrophysics Data System (ADS)

He, Jiaze; Yuan, Fuh-Gwo

2016-10-01

A two-dimensional (2D) non-contact areal scan system was developed to image and quantify impact damage in a composite plate using an enhanced zero-lag cross-correlation reverse-time migration (E-CCRTM) technique. The system comprises a single piezoelectric wafer mounted on the composite plate and a laser Doppler vibrometer (LDV) for scanning a region in the vicinity of the PZT to capture the scattered wavefield. The proposed damage imaging technique takes into account the amplitude, phase, geometric spreading, and all of the frequency content of the Lamb waves propagating in the plate; thus, a reflectivity coefficients of the delamination is calculated and potentially related to damage severity. Comparisons are made in terms of damage imaging quality between 2D areal scans and 1D line scans as well as between the proposed and existing imaging conditions. The experimental results show that the 2D E-CCRTM performs robustly when imaging and quantifying impact damage in large-scale composites using a single PZT actuator with a nearby areal scan using LDV.

An enhanced CCRTM (E-CCRTM) damage imaging technique using a 2D areal scan for composite plates

NASA Astrophysics Data System (ADS)

He, Jiaze; Yuan, Fuh-Gwo

2016-04-01

A two-dimensional (2-D) non-contact areal scan system was developed to image and quantify impact damage in a composite plate using an enhanced zero-lag cross-correlation reverse-time migration (E-CCRTM) technique. The system comprises a single piezoelectric actuator mounted on the composite plate and a laser Doppler vibrometer (LDV) for scanning a region to capture the scattered wavefield in the vicinity of the PZT. The proposed damage imaging technique takes into account the amplitude, phase, geometric spreading, and all of the frequency content of the Lamb waves propagating in the plate; thus, the reflectivity coefficients of the delamination can be calculated and potentially related to damage severity. Comparisons are made in terms of damage imaging quality between 2-D areal scans and linear scans as well as between the proposed and existing imaging conditions. The experimental results show that the 2-D E-CCRTM performs robustly when imaging and quantifying impact damage in large-scale composites using a single PZT actuator with a nearby areal scan using LDV.

A promising diagnostic method: Terahertz pulsed imaging and spectroscopy

PubMed Central

Sun, Yiwen; Sy, Ming Yiu; Wang, Yi-Xiang J; Ahuja, Anil T; Zhang, Yuan-Ting; Pickwell-MacPherson, Emma

2011-01-01

The terahertz band lies between the microwave and infrared regions of the electromagnetic spectrum. This radiation has very low photon energy and thus it does not pose any ionization hazard for biological tissues. It is strongly attenuated by water and very sensitive to water content. Unique absorption spectra due to intermolecular vibrations in this region have been found in different biological materials. These unique features make terahertz imaging very attractive for medical applications in order to provide complimentary information to existing imaging techniques. There has been an increasing interest in terahertz imaging and spectroscopy of biologically related applications within the last few years and more and more terahertz spectra are being reported. This paper introduces terahertz technology and provides a short review of recent advances in terahertz imaging and spectroscopy techniques, and a number of applications such as molecular spectroscopy, tissue characterization and skin imaging are discussed. PMID:21512652

4-D OCT in Developmental Cardiology

NASA Astrophysics Data System (ADS)

Jenkins, Michael W.; Rollins, Andrew M.

Although strong evidence exists to suggest that altered cardiac function can lead to CHDs, few studies have investigated the influential role of cardiac function and biophysical forces on the development of the cardiovascular system due to a lack of proper in vivo imaging tools. 4-D imaging is needed to decipher the complex spatial and temporal patterns of biomechanical forces acting upon the heart. Numerous solutions over the past several years have demonstrated 4-D OCT imaging of the developing cardiovascular system. This chapter will focus on these solutions and explain their context in the evolution of 4-D OCT imaging. The first sections describe the relevant techniques (prospective gating, direct 4-D imaging, retrospective gating), while later sections focus on 4-D Doppler imaging and measurements of force implementing 4-D OCT Doppler. Finally, the techniques are summarized, and some possible future directions are discussed.

Spread spectrum image steganography.

PubMed

Marvel, L M; Boncelet, C R; Retter, C T

1999-01-01

In this paper, we present a new method of digital steganography, entitled spread spectrum image steganography (SSIS). Steganography, which means "covered writing" in Greek, is the science of communicating in a hidden manner. Following a discussion of steganographic communication theory and review of existing techniques, the new method, SSIS, is introduced. This system hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range. The hidden message can be recovered using appropriate keys without any knowledge of the original image. Image restoration, error-control coding, and techniques similar to spread spectrum are described, and the performance of the system is illustrated. A message embedded by this method can be in the form of text, imagery, or any other digital signal. Applications for such a data-hiding scheme include in-band captioning, covert communication, image tamperproofing, authentication, embedded control, and revision tracking.

An update of commercial infrared sensing and imaging instruments

NASA Technical Reports Server (NTRS)

Kaplan, Herbert

1989-01-01

A classification of infrared sensing instruments by type and application, listing commercially available instruments, from single point thermal probes to on-line control sensors, to high speed, high resolution imaging systems is given. A review of performance specifications follows, along with a discussion of typical thermographic display approaches utilized by various imager manufacturers. An update report on new instruments, new display techniques and newly introduced features of existing instruments is given.

Murine aggregation chimeras and wholemount imaging in airway stem cell biology.

PubMed

Rosewell, Ian R; Giangreco, Adam

2012-01-01

Local tissue stem cells are known to exist in mammalian lungs but their role in epithelial maintenance remains unclear. We therefore developed murine aggregation chimera and wholemount imaging techniques to assess the contribution of these cells to lung homeostasis and repair. In this chapter we provide further details regarding the generation of murine aggregation chimera mice and their subsequent use in wholemount lung imaging. We also describe methods related to the interpretation of this data that allows for quantitative assessment of airway stem cell activation versus quiescence. Using these techniques, it is possible to compare the growth and differentiation capacity of various lung epithelial cells in normal, repairing, and diseased states.

An underwater turbulence degraded image restoration algorithm

NASA Astrophysics Data System (ADS)

Furhad, Md. Hasan; Tahtali, Murat; Lambert, Andrew

2017-09-01

Underwater turbulence occurs due to random fluctuations of temperature and salinity in the water. These fluctuations are responsible for variations in water density, refractive index and attenuation. These impose random geometric distortions, spatio-temporal varying blur, limited range visibility and limited contrast on the acquired images. There are some restoration techniques developed to address this problem, such as image registration based, lucky region based and centroid-based image restoration algorithms. Although these methods demonstrate better results in terms of removing turbulence, they require computationally intensive image registration, higher CPU load and memory allocations. Thus, in this paper, a simple patch based dictionary learning algorithm is proposed to restore the image by alleviating the costly image registration step. Dictionary learning is a machine learning technique which builds a dictionary of non-zero atoms derived from the sparse representation of an image or signal. The image is divided into several patches and the sharp patches are detected from them. Next, dictionary learning is performed on these patches to estimate the restored image. Finally, an image deconvolution algorithm is employed on the estimated restored image to remove noise that still exists.

Cellular uptake and intracellular fate of engineered nanoparticles: a review on the application of imaging techniques.

PubMed

Tantra, Ratna; Knight, Alex

2011-09-01

The use of imaging tools to probe nanoparticle-cell interactions will be crucial to elucidating the mechanisms of nanoparticle-induced toxicity. Of particular interest are mechanisms associated with cell penetration, translocation and subsequent accumulation inside the cell, or in cellular compartments. The objective of the present paper is to review imaging techniques that have been previously used in order to assess such interactions, and new techniques with the potential to be useful in this area. In order to identify the most suitable techniques, they were evaluated and matched against a list of evaluation criteria. We conclude that limitations exist with all of the techniques and the ultimate choice will thus depend on the needs of end users, and their particular application. The state-of-the-art techniques appear to have the least limitations, despite the fact that they are not so well established and still far from being routine. For example, super-resolution microscopy techniques appear to have many advantages for understanding the details of the interactions between nanoparticles and cells. Future research should concentrate on further developing or improving such novel techniques, to include the development of standardized methods and appropriate reference materials.

Contemporary imaging of mild TBI: the journey toward diffusion tensor imaging to assess neuronal damage.

PubMed

Fox, W Christopher; Park, Min S; Belverud, Shawn; Klugh, Arnett; Rivet, Dennis; Tomlin, Jeffrey M

2013-04-01

To follow the progression of neuroimaging as a means of non-invasive evaluation of mild traumatic brain injury (mTBI) in order to provide recommendations based on reproducible, defined imaging findings. A comprehensive literature review and analysis of contemporary published articles was performed to study the progression of neuroimaging findings as a non-invasive 'biomarker' for mTBI. Multiple imaging modalities exist to support the evaluation of patients with mTBI, including ultrasound (US), computed tomography (CT), single photon emission computed tomography (SPECT), positron emission tomography (PET), and magnetic resonance imaging (MRI). These techniques continue to evolve with the development of fractional anisotropy (FA), fiber tractography (FT), and diffusion tensor imaging (DTI). Modern imaging techniques, when applied in the appropriate clinical setting, may serve as a valuable tool for diagnosis and management of patients with mTBI. An understanding of modern neuroanatomical imaging will enhance our ability to analyse injury and recognize the manifestations of mTBI.

TU-G-204-01: BEST IN PHYSICS (IMAGING): Dynamic CT Myocardial Perfusion Measurement and Its Comparison to Fractional Flow Reserve

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

Ziemer, B; Hubbard, L; Groves, E

2015-06-15

Purpose: To evaluate a first pass analysis (FPA) technique for CT perfusion measurement in a swine animal and its validation using fractional flow reserve (FFR) as a reference standard. Methods: Swine were placed under anesthesia and relevant physiologic parameters were continuously recorded. Intra-coronary adenosine was administered to induce maximum hyperemia. A pressure wire was advanced distal to the first diagonal branch of the left anterior descending (LAD) artery for FFR measurements and a balloon dilation catheter was inserted over the pressure wire into the proximal LAD to create varying levels of stenosis. Images were acquired with a 320-row wide volumemore » CT scanner. Three main coronary perfusion beds were delineated in the myocardium using arteries extracted from CT angiography images using a minimum energy hypothesis. The integrated density in the perfusion bed was used to calculate perfusion using the FPA technique. The perfusion in the LAD bed over a range of stenosis severity was measured. The measured fractional perfusion was compared to FFR and linear regression was performed. Results: The measured fractional perfusion using the FPA technique (P-FPA) and FFR were related as P-FPA = 1.06FFR – 0.06 (r{sup 2} = 0.86). The perfusion measurements were calculated with only three to five total CT volume scans, which drastically reduces the radiation dose as compared with the existing techniques requiring 15–20 volume scans. Conclusion: The measured perfusion using the first pass analysis technique showed good correlation with FFR measurements as a reference standard. The technique for perfusion measurement can potentially make a substantial reduction in radiation dose as compared with the existing techniques.« less

Visualization and characterization of engineered nanoparticles in complex environmental and food matrices using atmospheric scanning electron microscopy.

PubMed

Luo, P; Morrison, I; Dudkiewicz, A; Tiede, K; Boyes, E; O'Toole, P; Park, S; Boxall, A B

2013-04-01

Imaging and characterization of engineered nanoparticles (ENPs) in water, soils, sediment and food matrices is very important for research into the risks of ENPs to consumers and the environment. However, these analyses pose a significant challenge as most existing techniques require some form of sample manipulation prior to imaging and characterization, which can result in changes in the ENPs in a sample and in the introduction of analytical artefacts. This study therefore explored the application of a newly designed instrument, the atmospheric scanning electron microscope (ASEM), which allows the direct characterization of ENPs in liquid matrices and which therefore overcomes some of the limitations associated with existing imaging methods. ASEM was used to characterize the size distribution of a range of ENPs in a selection of environmental and food matrices, including supernatant of natural sediment, test medium used in ecotoxicology studies, bovine serum albumin and tomato soup under atmospheric conditions. The obtained imaging results were compared to results obtained using conventional imaging by transmission electron microscope (TEM) and SEM as well as to size distribution data derived from nanoparticle tracking analysis (NTA). ASEM analysis was found to be a complementary technique to existing methods that is able to visualize ENPs in complex liquid matrices and to provide ENP size information without extensive sample preparation. ASEM images can detect ENPs in liquids down to 30 nm and to a level of 1 mg L(-1) (9×10(8) particles mL(-1) , 50 nm Au ENPs). The results indicate ASEM is a highly complementary method to existing approaches for analyzing ENPs in complex media and that its use will allow those studying to study ENP behavior in situ, something that is currently extremely challenging to do. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Red fluorescent proteins: advanced imaging applications and future design.

PubMed

Shcherbakova, Daria M; Subach, Oksana M; Verkhusha, Vladislav V

2012-10-22

In the past few years a large series of the advanced red-shifted fluorescent proteins (RFPs) has been developed. These enhanced RFPs provide new possibilities to study biological processes at the levels ranging from single molecules to whole organisms. Herein the relationship between the properties of the RFPs of different phenotypes and their applications to various imaging techniques are described. Existing and emerging imaging approaches are discussed for conventional RFPs, far-red FPs, RFPs with a large Stokes shift, fluorescent timers, irreversibly photoactivatable and reversibly photoswitchable RFPs. Advantages and limitations of specific RFPs for each technique are presented. Recent progress in understanding the chemical transformations of red chromophores allows the future RFP phenotypes and their respective novel imaging applications to be foreseen. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Extraction and fusion of spectral parameters for face recognition

NASA Astrophysics Data System (ADS)

Boisier, B.; Billiot, B.; Abdessalem, Z.; Gouton, P.; Hardeberg, J. Y.

2011-03-01

Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately in order to extract the most appropriate information for face recognition. We also verify the consistency of several keypoints extraction techniques in the Near Infrared (NIR) and in the Visible Spectrum.

Propagation-based x-ray phase contrast imaging using an iterative phase diversity technique

NASA Astrophysics Data System (ADS)

Carroll, Aidan J.; van Riessen, Grant A.; Balaur, Eugeniu; Dolbnya, Igor P.; Tran, Giang N.; Peele, Andrew G.

2018-03-01

Through the use of a phase diversity technique, we demonstrate a near-field in-line x-ray phase contrast algorithm that provides improved object reconstruction when compared to our previous iterative methods for a homogeneous sample. Like our previous methods, the new technique uses the sample refractive index distribution during the reconstruction process. The technique complements existing monochromatic and polychromatic methods and is useful in situations where experimental phase contrast data is affected by noise.

Automatic phase aberration compensation for digital holographic microscopy based on deep learning background detection.

PubMed

Nguyen, Thanh; Bui, Vy; Lam, Van; Raub, Christopher B; Chang, Lin-Ching; Nehmetallah, George

2017-06-26

We propose a fully automatic technique to obtain aberration free quantitative phase imaging in digital holographic microscopy (DHM) based on deep learning. The traditional DHM solves the phase aberration compensation problem by manually detecting the background for quantitative measurement. This would be a drawback in real time implementation and for dynamic processes such as cell migration phenomena. A recent automatic aberration compensation approach using principle component analysis (PCA) in DHM avoids human intervention regardless of the cells' motion. However, it corrects spherical/elliptical aberration only and disregards the higher order aberrations. Traditional image segmentation techniques can be employed to spatially detect cell locations. Ideally, automatic image segmentation techniques make real time measurement possible. However, existing automatic unsupervised segmentation techniques have poor performance when applied to DHM phase images because of aberrations and speckle noise. In this paper, we propose a novel method that combines a supervised deep learning technique with convolutional neural network (CNN) and Zernike polynomial fitting (ZPF). The deep learning CNN is implemented to perform automatic background region detection that allows for ZPF to compute the self-conjugated phase to compensate for most aberrations.

Functional and morphological ultrasonic biomicroscopy for tissue engineers

NASA Astrophysics Data System (ADS)

Mallidi, S.; Aglyamov, S. R.; Karpiouk, A. B.; Park, S.; Emelianov, S. Y.

2006-03-01

Tissue engineering is an interdisciplinary field that combines various aspects of engineering and life sciences and aims to develop biological substitutes to restore, repair or maintain tissue function. Currently, the ability to have quantitative functional assays of engineered tissues is limited to existing invasive methods like biopsy. Hence, an imaging tool for non-invasive and simultaneous evaluation of the anatomical and functional properties of the engineered tissue is needed. In this paper we present an advanced in-vivo imaging technology - ultrasound biomicroscopy combined with complementary photoacoustic and elasticity imaging techniques, capable of accurate visualization of both structural and functional changes in engineered tissues, sequential monitoring of tissue adaptation and/or regeneration, and possible assistance of drug delivery and treatment planning. The combined imaging at microscopic resolution was evaluated on tissue mimicking phantoms imaged with 25 MHz single element focused transducer. The results of our study demonstrate that the ultrasonic, photoacoustic and elasticity images synergistically complement each other in detecting features otherwise imperceptible using the individual techniques. Finally, we illustrate the feasibility of the combined ultrasound, photoacoustic and elasticity imaging techniques in accurately assessing the morphological and functional changes occurring in engineered tissue.

Line-Constrained Camera Location Estimation in Multi-Image Stereomatching.

PubMed

Donné, Simon; Goossens, Bart; Philips, Wilfried

2017-08-23

Stereomatching is an effective way of acquiring dense depth information from a scene when active measurements are not possible. So-called lightfield methods take a snapshot from many camera locations along a defined trajectory (usually uniformly linear or on a regular grid-we will assume a linear trajectory) and use this information to compute accurate depth estimates. However, they require the locations for each of the snapshots to be known: the disparity of an object between images is related to both the distance of the camera to the object and the distance between the camera positions for both images. Existing solutions use sparse feature matching for camera location estimation. In this paper, we propose a novel method that uses dense correspondences to do the same, leveraging an existing depth estimation framework to also yield the camera locations along the line. We illustrate the effectiveness of the proposed technique for camera location estimation both visually for the rectification of epipolar plane images and quantitatively with its effect on the resulting depth estimation. Our proposed approach yields a valid alternative for sparse techniques, while still being executed in a reasonable time on a graphics card due to its highly parallelizable nature.

MRI technique for the snapshot imaging of quantitative velocity maps using RARE

NASA Astrophysics Data System (ADS)

Shiko, G.; Sederman, A. J.; Gladden, L. F.

2012-03-01

A quantitative PGSE-RARE pulse sequence was developed and successfully applied to the in situ dissolution of two pharmaceutical formulations dissolving over a range of timescales. The new technique was chosen over other existing fast velocity imaging techniques because it is T2 weighted, not T2∗ weighted, and is, therefore, robust for imaging time-varying interfaces and flow in magnetically heterogeneous systems. The complex signal was preserved intact by separating odd and even echoes to obtain two phase maps which are then averaged in post-processing. Initially, the validity of the technique was shown when imaging laminar flow in a pipe. Subsequently, the dissolution of two drugs was followed in situ, where the technique enables the imaging and quantification of changes in the form of the tablet and the flow field surrounding it at high spatial and temporal resolution. First, the complete 3D velocity field around an eroding salicylic acid tablet was acquired at a resolution of 98 × 49 μm2, within 20 min, and monitored over ˜13 h. The tablet was observed to experience a heterogeneous flow field and, hence a heterogeneous shear field, which resulted in the non-symmetric erosion of the tablet. Second, the dissolution of a fast dissolving immediate release tablet was followed using one-shot 2D velocity images acquired every 5.2 s at a resolution of 390 × 390 μm2. The quantitative nature of the technique and fast acquisition times provided invaluable information on the dissolution behaviour of this tablet, which had not been attainable previously with conventional quantitative MRI techniques.

From Phenomena to Objects: Segmentation of Fuzzy Objects and its Application to Oceanic Eddies

NASA Astrophysics Data System (ADS)

Wu, Qingling

A challenging image analysis problem that has received limited attention to date is the isolation of fuzzy objects---i.e. those with inherently indeterminate boundaries---from continuous field data. This dissertation seeks to bridge the gap between, on the one hand, the recognized need for Object-Based Image Analysis of fuzzy remotely sensed features, and on the other, the optimization of existing image segmentation techniques for the extraction of more discretely bounded features. Using mesoscale oceanic eddies as a case study of a fuzzy object class evident in Sea Surface Height Anomaly (SSHA) imagery, the dissertation demonstrates firstly, that the widely used region-growing and watershed segmentation techniques can be optimized and made comparable in the absence of ground truth data using the principle of parsimony. However, they both have significant shortcomings, with the region growing procedure creating contour polygons that do not follow the shape of eddies while the watershed technique frequently subdivides eddies or groups together separate eddy objects. Secondly, it was determined that these problems can be remedied by using a novel Non-Euclidian Voronoi (NEV) tessellation technique. NEV is effective in isolating the extrema associated with eddies in SSHA data while using a non-Euclidian cost-distance based procedure (based on cumulative gradients in ocean height) to define the boundaries between fuzzy objects. Using this procedure as the first stage in isolating candidate eddy objects, a novel "region-shrinking" multicriteria eddy identification algorithm was developed that includes consideration of shape and vorticity. Eddies identified by this region-shrinking technique compare favorably with those identified by existing techniques, while simplifying and improving existing automated eddy detection algorithms. However, it also tends to find a larger number of eddies as a result of its ability to separate what other techniques identify as connected eddies. The research presented here is of significance not only to eddy research in oceanography, but also to other areas of Earth System Science for which the automated detection of features lacking rigid boundary definitions is of importance.

Quantitative X-ray Differential Interference Contrast Microscopy

NASA Astrophysics Data System (ADS)

Nakamura, Takashi

Full-field soft x-ray microscopes are widely used in many fields of sciences. Advances in nanofabrication technology enabled short wavelength focusing elements with significantly improved spatial resolution. In the soft x-ray spectral region, samples as small as 12 nm can be resolved using micro zone-plates as the objective lens. In addition to conventional x-ray microscopy in which x-ray absorption difference provides the image contrast, phase contrast mechanisms such as differential phase contrast (DIC) and Zernike phase contrast have also been demonstrated These phase contrast imaging mechanisms are especially attractive at the x-ray wavelengths where phase contrast of most materials is typically 10 times stronger than the absorption contrast. With recent progresses in plasma-based x- ray sources and increasing accessibility to synchrotron user facilities, x-ray microscopes are quickly becoming standard measurement equipment in the laboratory. To further the usefulness of x-ray DIC microscopy this thesis explicitly addresses three known issues with this imaging modality by introducing new techniques and devices First, as opposed to its visible-light counterpart, no quantitative phase imaging technique exists for x-ray DIC microscopy. To address this issue, two nanoscale x-ray quantitative phase imaging techniques, using exclusive OR (XOR) patterns and zone-plate doublets, respectively, are proposed. Unlike existing x-ray quantitative phase imaging techniques such as Talbot interferometry and ptychography, no dedicated experimental setups or stringent illumination coherence are needed for quantitative phase retrieval. Second, to the best of our knowledge, no quantitative performance characterization of DIC microscopy exists to date. Therefore the imaging system's response to sample's spatial frequency is not known In order to gain in-depth understanding of this imaging modality, performance of x-ray DIC microscopy is quantified using modulation transfer function. A new illumination apparatus required for the transfer function analysis under partially coherent illumination is also proposed. Such a characterization is essential for a proper selection of DIC optics for various transparent samples under study. Finally, optical elements used for x-ray DIC microscopy are highly absorptive and high brilliance x-ray sources such as synchrotrons are generally needed for image contrast. To extend the use of x-ray DIC microscopy to a wider variety of applications, a high efficiency large numerical aperture optical element consisting of high reflective Bragg reflectors is proposed. Using Bragg reflectors, which have 70% ˜99% reflectivity at extreme ultraviolet and soft x-rays for all angles of glancing incidence, the first order focusing efficiency is expected to increase by ˜ 8 times compared to that of a typical Fresnel zone-plate. This thesis contributes to current nanoscale x-ray phase contrast imaging research and provides new insights for biological, material, and magnetic sciences

Image processing via level set curvature flow

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

Malladi, R.; Sethian, J.A.

We present a controlled image smoothing and enhancement method based on a curvature flow interpretation of the geometric heat equation. Compared to existing techniques, the model has several distinct advantages. (i) It contains just one enhancement parameter. (ii) The scheme naturally inherits a stopping criterion from the image; continued application of the scheme produces no further change. (iii) The method is one of the fastest possible schemes based on a curvature-controlled approach. 15 ref., 6 figs.

Phase estimation for magnetic resonance imaging near metal prostheses

NASA Astrophysics Data System (ADS)

Bones, Philip J.; King, Laura J.; Millane, Rick P.

2015-09-01

Magnetic resonance imaging (MRI) has the potential to be the best technique for assessing complications in patients with metal orthopedic implants. The presence of fat can obscure definition of the other soft tissues in MRI images, so fat suppression is often required. However, the performance of existing fat suppression techniques is inadequate near implants, due to very significant magnetic field perturbations induced by the metal. The three-point Dixon technique is potentially a method of choice as it is able to suppress fat in the presence of inhomogeneities, but the success of this technique depends on being able to accurately calculate the phase shift. This is generally done using phase unwrapping and/or iterative reconstruction algorithms. Most current phase unwrapping techniques assume that the phase function is slowly varying and phase differences between adjacent points are limited to less than π radians in magnitude. Much greater phase differences can be present near metal implants. We present our experience with two phase unwrapping techniques which have been adapted to use prior knowledge of the implant. The first method identifies phase discontinuities before recovering the phase along paths through the image. The second method employs a transform to find the least squares solution to the unwrapped phase. Simulation results indicate that the methods show promise.

Biometric feature embedding using robust steganography technique

NASA Astrophysics Data System (ADS)

Rashid, Rasber D.; Sellahewa, Harin; Jassim, Sabah A.

2013-05-01

This paper is concerned with robust steganographic techniques to hide and communicate biometric data in mobile media objects like images, over open networks. More specifically, the aim is to embed binarised features extracted using discrete wavelet transforms and local binary patterns of face images as a secret message in an image. The need for such techniques can arise in law enforcement, forensics, counter terrorism, internet/mobile banking and border control. What differentiates this problem from normal information hiding techniques is the added requirement that there should be minimal effect on face recognition accuracy. We propose an LSB-Witness embedding technique in which the secret message is already present in the LSB plane but instead of changing the cover image LSB values, the second LSB plane will be changed to stand as a witness/informer to the receiver during message recovery. Although this approach may affect the stego quality, it is eliminating the weakness of traditional LSB schemes that is exploited by steganalysis techniques for LSB, such as PoV and RS steganalysis, to detect the existence of secrete message. Experimental results show that the proposed method is robust against PoV and RS attacks compared to other variants of LSB. We also discussed variants of this approach and determine capacity requirements for embedding face biometric feature vectors while maintain accuracy of face recognition.

Generalized image contrast enhancement technique based on Heinemann contrast discrimination model

NASA Astrophysics Data System (ADS)

Liu, Hong; Nodine, Calvin F.

1994-03-01

This paper presents a generalized image contrast enhancement technique which equalizes perceived brightness based on the Heinemann contrast discrimination model. This is a modified algorithm which presents an improvement over the previous study by Mokrane in its mathematically proven existence of a unique solution and in its easily tunable parameterization. The model uses a log-log representation of contrast luminosity between targets and the surround in a fixed luminosity background setting. The algorithm consists of two nonlinear gray-scale mapping functions which have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear functions of gray scale distribution of the image, and can be uniquely determined once the previous three are given. Tests have been carried out to examine the effectiveness of the algorithm for increasing the overall contrast of images. It can be demonstrated that the generalized algorithm provides better contrast enhancement than histogram equalization. In fact, the histogram equalization technique is a special case of the proposed mapping.

Atherosclerosis imaging using 3D black blood TSE SPACE vs 2D TSE

PubMed Central

Wong, Stephanie K; Mobolaji-Iawal, Motunrayo; Arama, Leron; Cambe, Joy; Biso, Sylvia; Alie, Nadia; Fayad, Zahi A; Mani, Venkatesh

2014-01-01

AIM: To compare 3D Black Blood turbo spin echo (TSE) sampling perfection with application-optimized contrast using different flip angle evolution (SPACE) vs 2D TSE in evaluating atherosclerotic plaques in multiple vascular territories. METHODS: The carotid, aortic, and femoral arterial walls of 16 patients at risk for cardiovascular or atherosclerotic disease were studied using both 3D black blood magnetic resonance imaging SPACE and conventional 2D multi-contrast TSE sequences using a consolidated imaging approach in the same imaging session. Qualitative and quantitative analyses were performed on the images. Agreement of morphometric measurements between the two imaging sequences was assessed using a two-sample t-test, calculation of the intra-class correlation coefficient and by the method of linear regression and Bland-Altman analyses. RESULTS: No statistically significant qualitative differences were found between the 3D SPACE and 2D TSE techniques for images of the carotids and aorta. For images of the femoral arteries, however, there were statistically significant differences in all four qualitative scores between the two techniques. Using the current approach, 3D SPACE is suboptimal for femoral imaging. However, this may be due to coils not being optimized for femoral imaging. Quantitatively, in our study, higher mean total vessel area measurements for the 3D SPACE technique across all three vascular beds were observed. No significant differences in lumen area for both the right and left carotids were observed between the two techniques. Overall, a significant-correlation existed between measures obtained between the two approaches. CONCLUSION: Qualitative and quantitative measurements between 3D SPACE and 2D TSE techniques are comparable. 3D-SPACE may be a feasible approach in the evaluation of cardiovascular patients. PMID:24876923

Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue

NASA Astrophysics Data System (ADS)

Sawyer, Travis W.; Rice, Photini F. S.; Sawyer, David M.; Koevary, Jennifer W.; Barton, Jennifer K.

2018-02-01

Ovarian cancer has the lowest survival rate among all gynecologic cancers due to predominantly late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Optical coherence tomography (OCT) is an emerging technique that provides depthresolved, high-resolution images of biological tissue in real time and demonstrates great potential for imaging of ovarian tissue. Mouse models are crucial to quantitatively assess the diagnostic potential of OCT for ovarian cancer imaging; however, due to small organ size, the ovaries must rst be separated from the image background using the process of segmentation. Manual segmentation is time-intensive, as OCT yields three-dimensional data. Furthermore, speckle noise complicates OCT images, frustrating many processing techniques. While much work has investigated noise-reduction and automated segmentation for retinal OCT imaging, little has considered the application to the ovaries, which exhibit higher variance and inhomogeneity than the retina. To address these challenges, we evaluated a set of algorithms to segment OCT images of mouse ovaries. We examined ve preprocessing techniques and six segmentation algorithms. While all pre-processing methods improve segmentation, Gaussian filtering is most effective, showing an improvement of 32% +/- 1.2%. Of the segmentation algorithms, active contours performs best, segmenting with an accuracy of 0.948 +/- 0.012 compared with manual segmentation (1.0 being identical). Nonetheless, further optimization could lead to maximizing the performance for segmenting OCT images of the ovaries.

Significance of perceptually relevant image decolorization for scene classification

NASA Astrophysics Data System (ADS)

Viswanathan, Sowmya; Divakaran, Govind; Soman, Kutti Padanyl

2017-11-01

Color images contain luminance and chrominance components representing the intensity and color information, respectively. The objective of this paper is to show the significance of incorporating chrominance information to the task of scene classification. An improved color-to-grayscale image conversion algorithm that effectively incorporates chrominance information is proposed using the color-to-gray structure similarity index and singular value decomposition to improve the perceptual quality of the converted grayscale images. The experimental results based on an image quality assessment for image decolorization and its success rate (using the Cadik and COLOR250 datasets) show that the proposed image decolorization technique performs better than eight existing benchmark algorithms for image decolorization. In the second part of the paper, the effectiveness of incorporating the chrominance component for scene classification tasks is demonstrated using a deep belief network-based image classification system developed using dense scale-invariant feature transforms. The amount of chrominance information incorporated into the proposed image decolorization technique is confirmed with the improvement to the overall scene classification accuracy. Moreover, the overall scene classification performance improved by combining the models obtained using the proposed method and conventional decolorization methods.

Large-scale retrieval for medical image analytics: A comprehensive review.

PubMed

Li, Zhongyu; Zhang, Xiaofan; Müller, Henning; Zhang, Shaoting

2018-01-01

Over the past decades, medical image analytics was greatly facilitated by the explosion of digital imaging techniques, where huge amounts of medical images were produced with ever-increasing quality and diversity. However, conventional methods for analyzing medical images have achieved limited success, as they are not capable to tackle the huge amount of image data. In this paper, we review state-of-the-art approaches for large-scale medical image analysis, which are mainly based on recent advances in computer vision, machine learning and information retrieval. Specifically, we first present the general pipeline of large-scale retrieval, summarize the challenges/opportunities of medical image analytics on a large-scale. Then, we provide a comprehensive review of algorithms and techniques relevant to major processes in the pipeline, including feature representation, feature indexing, searching, etc. On the basis of existing work, we introduce the evaluation protocols and multiple applications of large-scale medical image retrieval, with a variety of exploratory and diagnostic scenarios. Finally, we discuss future directions of large-scale retrieval, which can further improve the performance of medical image analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments.

PubMed

Gorgolewski, Krzysztof J; Auer, Tibor; Calhoun, Vince D; Craddock, R Cameron; Das, Samir; Duff, Eugene P; Flandin, Guillaume; Ghosh, Satrajit S; Glatard, Tristan; Halchenko, Yaroslav O; Handwerker, Daniel A; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B Nolan; Nichols, Thomas E; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A; Varoquaux, Gaël; Poldrack, Russell A

2016-06-21

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations.

The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments

PubMed Central

Gorgolewski, Krzysztof J.; Auer, Tibor; Calhoun, Vince D.; Craddock, R. Cameron; Das, Samir; Duff, Eugene P.; Flandin, Guillaume; Ghosh, Satrajit S.; Glatard, Tristan; Halchenko, Yaroslav O.; Handwerker, Daniel A.; Hanke, Michael; Keator, David; Li, Xiangrui; Michael, Zachary; Maumet, Camille; Nichols, B. Nolan; Nichols, Thomas E.; Pellman, John; Poline, Jean-Baptiste; Rokem, Ariel; Schaefer, Gunnar; Sochat, Vanessa; Triplett, William; Turner, Jessica A.; Varoquaux, Gaël; Poldrack, Russell A.

2016-01-01

The development of magnetic resonance imaging (MRI) techniques has defined modern neuroimaging. Since its inception, tens of thousands of studies using techniques such as functional MRI and diffusion weighted imaging have allowed for the non-invasive study of the brain. Despite the fact that MRI is routinely used to obtain data for neuroscience research, there has been no widely adopted standard for organizing and describing the data collected in an imaging experiment. This renders sharing and reusing data (within or between labs) difficult if not impossible and unnecessarily complicates the application of automatic pipelines and quality assurance protocols. To solve this problem, we have developed the Brain Imaging Data Structure (BIDS), a standard for organizing and describing MRI datasets. The BIDS standard uses file formats compatible with existing software, unifies the majority of practices already common in the field, and captures the metadata necessary for most common data processing operations. PMID:27326542

Fundamental limits of reconstruction-based superresolution algorithms under local translation.

PubMed

Lin, Zhouchen; Shum, Heung-Yeung

2004-01-01

Superresolution is a technique that can produce images of a higher resolution than that of the originally captured ones. Nevertheless, improvement in resolution using such a technique is very limited in practice. This makes it significant to study the problem: "Do fundamental limits exist for superresolution?" In this paper, we focus on a major class of superresolution algorithms, called the reconstruction-based algorithms, which compute high-resolution images by simulating the image formation process. Assuming local translation among low-resolution images, this paper is the first attempt to determine the explicit limits of reconstruction-based algorithms, under both real and synthetic conditions. Based on the perturbation theory of linear systems, we obtain the superresolution limits from the conditioning analysis of the coefficient matrix. Moreover, we determine the number of low-resolution images that are sufficient to achieve the limit. Both real and synthetic experiments are carried out to verify our analysis.

A balloon-borne payload for imaging hard X-rays and gamma rays from solar flares

NASA Technical Reports Server (NTRS)

Crannell, Carol J.; Dennis, Brian R.; Orwig, Larry E.; Schmahl, Edward J.; Lang, Frederic L.; Starr, Richard; Norris, Jay P.; Greene, Michael E.; Hurford, Gordon J.; Johnson, W. N.

1991-01-01

Hard X-rays and gamma rays provide direct evidence of the roles of accelerated particles in solar flares. An approach that employs a spatial Fourier-transform technique for imaging the sources of these emissions is described, and the development of a balloon-borne imaging device based on this instrumental technique is presented. The detectors, together with the imaging optics, are sensitive to hard X-ray and gamma-ray emission in the energy-range from 20 to 700 keV. This payload, scheduled for its first flight in June 1992, will provide 11-arc second angular resolution and millisecond time resolution with a whole-sun field of view. For subsequent flights, the effective detector area can be increased by as much as a factor of four, and imaging optics with angular resolution as fine as 2 arcsec can be added to the existing gondola and metering structures.

Cell-based therapies and imaging in cardiology.

PubMed

Bengel, Frank M; Schachinger, Volker; Dimmeler, Stefanie

2005-12-01

Cell therapy for cardiac repair has emerged as one of the most exciting and promising developments in cardiovascular medicine. Evidence from experimental and clinical studies is increasing that this innovative treatment will influence clinical practice in the future. But open questions and controversies with regard to the basic mechanisms of this therapy continue to exist and emphasise the need for specific techniques to visualise the mechanisms and success of therapy in vivo. Several non-invasive imaging approaches which aim at tracking of transplanted cells in the heart have been introduced. Among these are direct labelling of cells with radionuclides or paramagnetic agents, and the use of reporter genes for imaging of cell transplantation and differentiation. Initial studies have suggested that these molecular imaging techniques have great potential. Integration of cell imaging into studies of cardiac cell therapy holds promise to facilitate further growth of the field towards a broadly clinically useful application.

Guided SAR image despeckling with probabilistic non local weights

NASA Astrophysics Data System (ADS)

Gokul, Jithin; Nair, Madhu S.; Rajan, Jeny

2017-12-01

SAR images are generally corrupted by granular disturbances called speckle, which makes visual analysis and detail extraction a difficult task. Non Local despeckling techniques with probabilistic similarity has been a recent trend in SAR despeckling. To achieve effective speckle suppression without compromising detail preservation, we propose an improvement for the existing Generalized Guided Filter with Bayesian Non-Local Means (GGF-BNLM) method. The proposed method (Guided SAR Image Despeckling with Probabilistic Non Local Weights) replaces parametric constants based on heuristics in GGF-BNLM method with dynamically derived values based on the image statistics for weight computation. Proposed changes make GGF-BNLM method adaptive and as a result, significant improvement is achieved in terms of performance. Experimental analysis on SAR images shows excellent speckle reduction without compromising feature preservation when compared to GGF-BNLM method. Results are also compared with other state-of-the-art and classic SAR depseckling techniques to demonstrate the effectiveness of the proposed method.

Zebra Crossing Spotter: Automatic Population of Spatial Databases for Increased Safety of Blind Travelers

PubMed Central

Ahmetovic, Dragan; Manduchi, Roberto; Coughlan, James M.; Mascetti, Sergio

2016-01-01

In this paper we propose a computer vision-based technique that mines existing spatial image databases for discovery of zebra crosswalks in urban settings. Knowing the location of crosswalks is critical for a blind person planning a trip that includes street crossing. By augmenting existing spatial databases (such as Google Maps or OpenStreetMap) with this information, a blind traveler may make more informed routing decisions, resulting in greater safety during independent travel. Our algorithm first searches for zebra crosswalks in satellite images; all candidates thus found are validated against spatially registered Google Street View images. This cascaded approach enables fast and reliable discovery and localization of zebra crosswalks in large image datasets. While fully automatic, our algorithm could also be complemented by a final crowdsourcing validation stage for increased accuracy. PMID:26824080

Application of the Indirect Immunoperoxidase Stain Technique to the Flagella of Azospirillum brasilense

PubMed Central

Hall, Patrick G.; Krieg, Noel R.

1984-01-01

An indirect immunoperoxidase stain was used to demonstrate by electron microscopy that an antigenic difference exists between the polar flagellum and the lateral flagella of Azospirillum brasilense ATCC 29145. Images PMID:16346482

High resolution spectroscopic mapping imaging applied in situ to multilayer structures for stratigraphic identification of painted art objects

NASA Astrophysics Data System (ADS)

Karagiannis, Georgios Th.

2016-04-01

The development of non-destructive techniques is a reality in the field of conservation science. These techniques are usually not so accurate, as the analytical micro-sampling techniques, however, the proper development of soft-computing techniques can improve their accuracy. In this work, we propose a real-time fast acquisition spectroscopic mapping imaging system that operates from the ultraviolet to mid infrared (UV/Vis/nIR/mIR) area of the electromagnetic spectrum and it is supported by a set of soft-computing methods to identify the materials that exist in a stratigraphic structure of paint layers. Particularly, the system acquires spectra in diffuse-reflectance mode, scanning in a Region-Of-Interest (ROI), and having wavelength range from 200 up to 5000 nm. Also, a fuzzy c-means clustering algorithm, i.e., the particular soft-computing algorithm, produces the mapping images. The evaluation of the method was tested on a byzantine painted icon.

Anisotropic polyvinyl alcohol hydrogel phantom for shear wave elastography in fibrous biological soft tissue: a multimodality characterization

NASA Astrophysics Data System (ADS)

Chatelin, Simon; Bernal, Miguel; Deffieux, Thomas; Papadacci, Clément; Flaud, Patrice; Nahas, Amir; Boccara, Claude; Gennisson, Jean-Luc; Tanter, Mickael; Pernot, Mathieu

2014-11-01

Shear wave elastography imaging techniques provide quantitative measurement of soft tissues elastic properties. Tendons, muscles and cerebral tissues are composed of fibers, which induce a strong anisotropic effect on the mechanical behavior. Currently, these tissues cannot be accurately represented by existing elastography phantoms. Recently, a novel approach for orthotropic hydrogel mimicking soft tissues has been developed (Millon et al 2006 J. Biomed. Mater. Res. B 305-11). The mechanical anisotropy is induced in a polyvinyl alcohol (PVA) cryogel by stretching the physical crosslinks of the polymeric chains while undergoing freeze/thaw cycles. In the present study we propose an original multimodality imaging characterization of this new transverse isotropic (TI) PVA hydrogel. Multiple properties were investigated using a large variety of techniques at different scales compared with an isotropic PVA hydrogel undergoing similar imaging and rheology protocols. The anisotropic mechanical (dynamic and static) properties were studied using supersonic shear wave imaging technique, full-field optical coherence tomography (FFOCT) strain imaging and classical linear rheometry using dynamic mechanical analysis. The anisotropic optical and ultrasonic spatial coherence properties were measured by FFOCT volumetric imaging and backscatter tensor imaging, respectively. Correlation of mechanical and optical properties demonstrates the complementarity of these techniques for the study of anisotropy on a multi-scale range as well as the potential of this TI phantom as fibrous tissue-mimicking phantom for shear wave elastographic applications.

Detecting perceptual groupings in textures by continuity considerations

NASA Technical Reports Server (NTRS)

Greene, Richard J.

1990-01-01

A generalization is presented for the second derivative of a Gaussian D(sup 2)G operator to apply to problems of perceptual organization involving textures. Extensions to other problems of perceptual organization are evident and a new research direction can be established. The technique presented is theoretically pleasing since it has the potential of unifying the entire area of image segmentation under the mathematical notion of continuity and presents a single algorithm to form perceptual groupings where many algorithms existed previously. The eventual impact on both the approach and technique of image processing segmentation operations could be significant.

High-Resolution Scanning Electron Microscopy and Immuno-Gold Labeling of the Nuclear Lamina and Nuclear Pore Complex.

PubMed

Goldberg, Martin W

2016-01-01

Scanning electron microscopy (SEM) is a technique used to image surfaces. Field emission SEMs (feSEMs) can resolve structures that are ~0.5-1.5 nm apart. FeSEM, therefore is a useful technique for imaging molecular structures that exist at surfaces such as membranes. The nuclear envelope consists of four membrane surfaces, all of which may be accessible for imaging. Imaging of the cytoplasmic face of the outer membrane gives information about ribosomes and cytoskeletal attachments, as well as details of the cytoplasmic peripheral components of the nuclear pore complex, and is the most easily accessed surface. The nucleoplasmic face of the inner membrane is easily accessible in some cells, such as amphibian oocytes, giving valuable details about the organization of the nuclear lamina and how it interacts with the nuclear pore complexes. The luminal faces of both membranes are difficult to access, but may be exposed by various fracturing techniques. Protocols are presented here for the preparation, labeling, and feSEM imaging of Xenopus laevis oocyte nuclear envelopes.

Automated simultaneous multiple feature classification of MTI data

NASA Astrophysics Data System (ADS)

Harvey, Neal R.; Theiler, James P.; Balick, Lee K.; Pope, Paul A.; Szymanski, John J.; Perkins, Simon J.; Porter, Reid B.; Brumby, Steven P.; Bloch, Jeffrey J.; David, Nancy A.; Galassi, Mark C.

2002-08-01

Los Alamos National Laboratory has developed and demonstrated a highly capable system, GENIE, for the two-class problem of detecting a single feature against a background of non-feature. In addition to the two-class case, however, a commonly encountered remote sensing task is the segmentation of multispectral image data into a larger number of distinct feature classes or land cover types. To this end we have extended our existing system to allow the simultaneous classification of multiple features/classes from multispectral data. The technique builds on previous work and its core continues to utilize a hybrid evolutionary-algorithm-based system capable of searching for image processing pipelines optimized for specific image feature extraction tasks. We describe the improvements made to the GENIE software to allow multiple-feature classification and describe the application of this system to the automatic simultaneous classification of multiple features from MTI image data. We show the application of the multiple-feature classification technique to the problem of classifying lava flows on Mauna Loa volcano, Hawaii, using MTI image data and compare the classification results with standard supervised multiple-feature classification techniques.

Generalized image contrast enhancement technique based on the Heinemann contrast discrimination model

NASA Astrophysics Data System (ADS)

Liu, Hong; Nodine, Calvin F.

1996-07-01

This paper presents a generalized image contrast enhancement technique, which equalizes the perceived brightness distribution based on the Heinemann contrast discrimination model. It is based on the mathematically proven existence of a unique solution to a nonlinear equation, and is formulated with easily tunable parameters. The model uses a two-step log-log representation of luminance contrast between targets and surround in a luminous background setting. The algorithm consists of two nonlinear gray scale mapping functions that have seven parameters, two of which are adjustable Heinemann constants. Another parameter is the background gray level. The remaining four parameters are nonlinear functions of the gray-level distribution of the given image, and can be uniquely determined once the previous three are set. Tests have been carried out to demonstrate the effectiveness of the algorithm for increasing the overall contrast of radiology images. The traditional histogram equalization can be reinterpreted as an image enhancement technique based on the knowledge of human contrast perception. In fact, it is a special case of the proposed algorithm.

Vision-based obstacle recognition system for automated lawn mower robot development

NASA Astrophysics Data System (ADS)

Mohd Zin, Zalhan; Ibrahim, Ratnawati

2011-06-01

Digital image processing techniques (DIP) have been widely used in various types of application recently. Classification and recognition of a specific object using vision system require some challenging tasks in the field of image processing and artificial intelligence. The ability and efficiency of vision system to capture and process the images is very important for any intelligent system such as autonomous robot. This paper gives attention to the development of a vision system that could contribute to the development of an automated vision based lawn mower robot. The works involve on the implementation of DIP techniques to detect and recognize three different types of obstacles that usually exist on a football field. The focus was given on the study on different types and sizes of obstacles, the development of vision based obstacle recognition system and the evaluation of the system's performance. Image processing techniques such as image filtering, segmentation, enhancement and edge detection have been applied in the system. The results have shown that the developed system is able to detect and recognize various types of obstacles on a football field with recognition rate of more 80%.

Radar image enhancement and simulation as an aid to interpretation and training

NASA Technical Reports Server (NTRS)

Frost, V. S.; Stiles, J. A.; Holtzman, J. C.; Dellwig, L. F.; Held, D. N.

1980-01-01

Greatly increased activity in the field of radar image applications in the coming years demands that techniques of radar image analysis, enhancement, and simulation be developed now. Since the statistical nature of radar imagery differs from that of photographic imagery, one finds that the required digital image processing algorithms (e.g., for improved viewing and feature extraction) differ from those currently existing. This paper addresses these problems and discusses work at the Remote Sensing Laboratory in image simulation and processing, especially for systems comparable to the formerly operational SEASAT synthetic aperture radar.

Multimodality cardiac imaging at IRCCS Policlinico San Donato: a new interdisciplinary vision.

PubMed

Lombardi, Massimo; Secchi, Francesco; Pluchinotta, Francesca R; Castelvecchio, Serenella; Montericcio, Vincenzo; Camporeale, Antonia; Bandera, Francesco

2016-04-28

Multimodality imaging is the efficient integration of various methods of cardiovascular imaging to improve the ability to diagnose, guide therapy, or predict outcome. This approach implies both the availability of different technologies in a single unit and the presence of dedicated staff with cardiologic and radiologic background and certified competence in more than one imaging technique. Interaction with clinical practice and existence of research programmes and educational activities are pivotal for the success of this model. The aim of this paper is to describe the multimodality cardiac imaging programme recently started at San Donato Hospital.

Novel technique for preoperative pedicle localization in spinal surgery with challenging anatomy.

PubMed

Young, Richard M; Prasad, Vikram; Wind, Joshua J; Olan, Wayne; Caputy, Anthony J

2014-04-01

Accurately localizing a spine level in the thoracic spine is often not easily achieved with the existing imaging modalities available in the operating room. The coordination of the preoperative imaging pathology with intraoperative imaging is even more difficult in patients with challenging anatomy. Using standard percutaneous techniques, the authors placed a radiopaque embolization coil into the pedicle of interest under biplanar fluoroscopy in 1 patient. Thoracic spine MRI along with scout MRI was then performed to confirm coil marker placement in relation to the actual spine pathology prior to surgical intervention. No complications were observed during placement of the radiopaque marker. Intraoperatively, the marker was immediately and easily visualized, leading to a confident identification of the correct thoracic spinal level. The preoperative placement of a radiopaque marker into the vertebral pedicle of the identified pathological level combined with postplacement MRI verification provides an advantage over previously proposed techniques in the literature.

Seamless stitching of tile scan microscope images.

PubMed

Legesse, F B; Chernavskaia, O; Heuke, S; Bocklitz, T; Meyer, T; Popp, J; Heintzmann, R

2015-06-01

For diagnostic purposes, optical imaging techniques need to obtain high-resolution images of extended biological specimens in reasonable time. The field of view of an objective lens, however, is often smaller than the sample size. To image the whole sample, laser scanning microscopes acquire tile scans that are stitched into larger mosaics. The appearance of such image mosaics is affected by visible edge artefacts that arise from various optical aberrations which manifest in grey level jumps across tile boundaries. In this contribution, a technique for stitching tiles into a seamless mosaic is presented. The stitching algorithm operates by equilibrating neighbouring edges and forcing the brightness at corners to a common value. The corrected image mosaics appear to be free from stitching artefacts and are, therefore, suited for further image analysis procedures. The contribution presents a novel method to seamlessly stitch tiles captured by a laser scanning microscope into a large mosaic. The motivation for the work is the failure of currently existing methods for stitching nonlinear, multimodal images captured by our microscopic setups. Our method eliminates the visible edge artefacts that appear between neighbouring tiles by taking into account the overall illumination differences among tiles in such mosaics. The algorithm first corrects the nonuniform brightness that exists within each of the tiles. It then compensates for grey level differences across tile boundaries by equilibrating neighbouring edges and forcing the brightness at the corners to a common value. After these artefacts have been removed further image analysis procedures can be applied on the microscopic images. Even though the solution presented here is tailored for the aforementioned specific case, it could be easily adapted to other contexts where image tiles are assembled into mosaics such as in astronomical or satellite photos. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Image reconstruction of dynamic infrared single-pixel imaging system

NASA Astrophysics Data System (ADS)

Tong, Qi; Jiang, Yilin; Wang, Haiyan; Guo, Limin

2018-03-01

Single-pixel imaging technique has recently received much attention. Most of the current single-pixel imaging is aimed at relatively static targets or the imaging system is fixed, which is limited by the number of measurements received through the single detector. In this paper, we proposed a novel dynamic compressive imaging method to solve the imaging problem, where exists imaging system motion behavior, for the infrared (IR) rosette scanning system. The relationship between adjacent target images and scene is analyzed under different system movement scenarios. These relationships are used to build dynamic compressive imaging models. Simulation results demonstrate that the proposed method can improve the reconstruction quality of IR image and enhance the contrast between the target and the background in the presence of system movement.

MISTICA: Minimum Spanning Tree-based Coarse Image Alignment for Microscopy Image Sequences

PubMed Central

Ray, Nilanjan; McArdle, Sara; Ley, Klaus; Acton, Scott T.

2016-01-01

Registration of an in vivo microscopy image sequence is necessary in many significant studies, including studies of atherosclerosis in large arteries and the heart. Significant cardiac and respiratory motion of the living subject, occasional spells of focal plane changes, drift in the field of view, and long image sequences are the principal roadblocks. The first step in such a registration process is the removal of translational and rotational motion. Next, a deformable registration can be performed. The focus of our study here is to remove the translation and/or rigid body motion that we refer to here as coarse alignment. The existing techniques for coarse alignment are unable to accommodate long sequences often consisting of periods of poor quality images (as quantified by a suitable perceptual measure). Many existing methods require the user to select an anchor image to which other images are registered. We propose a novel method for coarse image sequence alignment based on minimum weighted spanning trees (MISTICA) that overcomes these difficulties. The principal idea behind MISTICA is to re-order the images in shorter sequences, to demote nonconforming or poor quality images in the registration process, and to mitigate the error propagation. The anchor image is selected automatically making MISTICA completely automated. MISTICA is computationally efficient. It has a single tuning parameter that determines graph width, which can also be eliminated by way of additional computation. MISTICA outperforms existing alignment methods when applied to microscopy image sequences of mouse arteries. PMID:26415193

MISTICA: Minimum Spanning Tree-Based Coarse Image Alignment for Microscopy Image Sequences.

PubMed

Ray, Nilanjan; McArdle, Sara; Ley, Klaus; Acton, Scott T

2016-11-01

Registration of an in vivo microscopy image sequence is necessary in many significant studies, including studies of atherosclerosis in large arteries and the heart. Significant cardiac and respiratory motion of the living subject, occasional spells of focal plane changes, drift in the field of view, and long image sequences are the principal roadblocks. The first step in such a registration process is the removal of translational and rotational motion. Next, a deformable registration can be performed. The focus of our study here is to remove the translation and/or rigid body motion that we refer to here as coarse alignment. The existing techniques for coarse alignment are unable to accommodate long sequences often consisting of periods of poor quality images (as quantified by a suitable perceptual measure). Many existing methods require the user to select an anchor image to which other images are registered. We propose a novel method for coarse image sequence alignment based on minimum weighted spanning trees (MISTICA) that overcomes these difficulties. The principal idea behind MISTICA is to reorder the images in shorter sequences, to demote nonconforming or poor quality images in the registration process, and to mitigate the error propagation. The anchor image is selected automatically making MISTICA completely automated. MISTICA is computationally efficient. It has a single tuning parameter that determines graph width, which can also be eliminated by the way of additional computation. MISTICA outperforms existing alignment methods when applied to microscopy image sequences of mouse arteries.

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.

Acquisition and visualization techniques for narrow spectral color imaging.

PubMed

Neumann, László; García, Rafael; Basa, János; Hegedüs, Ramón

2013-06-01

This paper introduces a new approach in narrow-band imaging (NBI). Existing NBI techniques generate images by selecting discrete bands over the full visible spectrum or an even wider spectral range. In contrast, here we perform the sampling with filters covering a tight spectral window. This image acquisition method, named narrow spectral imaging, can be particularly useful when optical information is only available within a narrow spectral window, such as in the case of deep-water transmittance, which constitutes the principal motivation of this work. In this study we demonstrate the potential of the proposed photographic technique on nonunderwater scenes recorded under controlled conditions. To this end three multilayer narrow bandpass filters were employed, which transmit at 440, 456, and 470 nm bluish wavelengths, respectively. Since the differences among the images captured in such a narrow spectral window can be extremely small, both image acquisition and visualization require a novel approach. First, high-bit-depth images were acquired with multilayer narrow-band filters either placed in front of the illumination or mounted on the camera lens. Second, a color-mapping method is proposed, using which the input data can be transformed onto the entire display color gamut with a continuous and perceptually nearly uniform mapping, while ensuring optimally high information content for human perception.

A super resolution framework for low resolution document image OCR

NASA Astrophysics Data System (ADS)

Ma, Di; Agam, Gady

2013-01-01

Optical character recognition is widely used for converting document images into digital media. Existing OCR algorithms and tools produce good results from high resolution, good quality, document images. In this paper, we propose a machine learning based super resolution framework for low resolution document image OCR. Two main techniques are used in our proposed approach: a document page segmentation algorithm and a modified K-means clustering algorithm. Using this approach, by exploiting coherence in the document, we reconstruct from a low resolution document image a better resolution image and improve OCR results. Experimental results show substantial gain in low resolution documents such as the ones captured from video.

Developing stereo image based robot control system

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

Suprijadi,; Pambudi, I. R.; Woran, M.

Application of image processing is developed in various field and purposes. In the last decade, image based system increase rapidly with the increasing of hardware and microprocessor performance. Many fields of science and technology were used this methods especially in medicine and instrumentation. New technique on stereovision to give a 3-dimension image or movie is very interesting, but not many applications in control system. Stereo image has pixel disparity information that is not existed in single image. In this research, we proposed a new method in wheel robot control system using stereovision. The result shows robot automatically moves based onmore » stereovision captures.« less

The review on infrared image restoration techniques

NASA Astrophysics Data System (ADS)

Li, Sijian; Fan, Xiang; Zhu, Bin Cheng; Zheng, Dong

2016-11-01

The goal of infrared image restoration is to reconstruct an original scene from a degraded observation. The restoration process in the application of infrared wavelengths, however, still has numerous research possibilities. In order to give people a comprehensive knowledge of infrared image restoration, the degradation factors divided into two major categories of noise and blur. Many kinds of infrared image restoration method were overviewed. Mathematical background and theoretical basis of infrared image restoration technology, and the limitations or insufficiency of existing methods were discussed. After the survey, the direction and prospects of infrared image restoration technology for the future development were forecast and put forward.

Surface defect detection in tiling Industries using digital image processing methods: analysis and evaluation.

PubMed

Karimi, Mohammad H; Asemani, Davud

2014-05-01

Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Image Transmission through OFDM System under the Influence of AWGN Channel

NASA Astrophysics Data System (ADS)

Krishna, Dharavathu; Anuradha, M. S., Dr.

2017-08-01

OFDM system is one among the modern techniques which is most abundantly used in next generation wireless communication networks for transmitting many forms of digital data in efficient manner than compared with other existing traditional techniques. In this paper, one such kind of a digital data corresponding to a two dimensional (2D) gray-scale image is used to evaluate the functionality and overall performance of an OFDM system under the influence of modeled AWGN channel in MATLAB simulation environment. Within the OFDM system, different configurations of notable modulation techniques such as M-PSK and M-QAM are considered for evaluation of the system and necessary valid conclusions are made from the comparison of several observed MATLAB simulation results.

Computer image processing in marine resource exploration

NASA Technical Reports Server (NTRS)

Paluzzi, P. R.; Normark, W. R.; Hess, G. R.; Hess, H. D.; Cruickshank, M. J.

1976-01-01

Pictographic data or imagery is commonly used in marine exploration. Pre-existing image processing techniques (software) similar to those used on imagery obtained from unmanned planetary exploration were used to improve marine photography and side-scan sonar imagery. Features and details not visible by conventional photo processing methods were enhanced by filtering and noise removal on selected deep-sea photographs. Information gained near the periphery of photographs allows improved interpretation and facilitates construction of bottom mosaics where overlapping frames are available. Similar processing techniques were applied to side-scan sonar imagery, including corrections for slant range distortion, and along-track scale changes. The use of digital data processing and storage techniques greatly extends the quantity of information that can be handled, stored, and processed.

An assessment of multimodal imaging of subsurface text in mummy cartonnage using surrogate papyrus phantoms

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

Gibson, Adam; Piquette, Kathryn E.; Bergmann, Uwe

Ancient Egyptian mummies were often covered with an outer casing, panels and masks made from cartonnage: a lightweight material made from linen, plaster, and recycled papyrus held together with adhesive. Egyptologists, papyrologists, and historians aim to recover and read extant text on the papyrus contained within cartonnage layers, but some methods, such as dissolving mummy casings, are destructive. The use of an advanced range of different imaging modalities was investigated to test the feasibility of non-destructive approaches applied to multi-layered papyrus found in ancient Egyptian mummy cartonnage. Eight different techniques were compared by imaging four synthetic phantoms designed to providemore » robust, well-understood, yet relevant sample standards using modern papyrus and replica inks. The techniques include optical (multispectral imaging with reflection and transillumination, and optical coherence tomography), X-ray (X-ray fluorescence imaging, X-ray fluorescence spectroscopy, X-ray micro computed tomography and phase contrast X-ray) and terahertz-based approaches. Optical imaging techniques were able to detect inks on all four phantoms, but were unable to significantly penetrate papyrus. X-ray-based techniques were sensitive to iron-based inks with excellent penetration but were not able to detect carbon-based inks. However, using terahertz imaging, it was possible to detect carbon-based inks with good penetration but with less sensitivity to iron-based inks. The phantoms allowed reliable and repeatable tests to be made at multiple sites on three continents. Finally, the tests demonstrated that each imaging modality needs to be optimised for this particular application: it is, in general, not sufficient to repurpose an existing device without modification. Furthermore, it is likely that no single imaging technique will to be able to robustly detect and enable the reading of text within ancient Egyptian mummy cartonnage. However, by carefully selecting, optimising and combining techniques, text contained within these fragile and rare artefacts may eventually be open to non-destructive imaging, identification, and interpretation.« less

An assessment of multimodal imaging of subsurface text in mummy cartonnage using surrogate papyrus phantoms

DOE PAGES

Gibson, Adam; Piquette, Kathryn E.; Bergmann, Uwe; ...

2018-02-26

Ancient Egyptian mummies were often covered with an outer casing, panels and masks made from cartonnage: a lightweight material made from linen, plaster, and recycled papyrus held together with adhesive. Egyptologists, papyrologists, and historians aim to recover and read extant text on the papyrus contained within cartonnage layers, but some methods, such as dissolving mummy casings, are destructive. The use of an advanced range of different imaging modalities was investigated to test the feasibility of non-destructive approaches applied to multi-layered papyrus found in ancient Egyptian mummy cartonnage. Eight different techniques were compared by imaging four synthetic phantoms designed to providemore » robust, well-understood, yet relevant sample standards using modern papyrus and replica inks. The techniques include optical (multispectral imaging with reflection and transillumination, and optical coherence tomography), X-ray (X-ray fluorescence imaging, X-ray fluorescence spectroscopy, X-ray micro computed tomography and phase contrast X-ray) and terahertz-based approaches. Optical imaging techniques were able to detect inks on all four phantoms, but were unable to significantly penetrate papyrus. X-ray-based techniques were sensitive to iron-based inks with excellent penetration but were not able to detect carbon-based inks. However, using terahertz imaging, it was possible to detect carbon-based inks with good penetration but with less sensitivity to iron-based inks. The phantoms allowed reliable and repeatable tests to be made at multiple sites on three continents. Finally, the tests demonstrated that each imaging modality needs to be optimised for this particular application: it is, in general, not sufficient to repurpose an existing device without modification. Furthermore, it is likely that no single imaging technique will to be able to robustly detect and enable the reading of text within ancient Egyptian mummy cartonnage. However, by carefully selecting, optimising and combining techniques, text contained within these fragile and rare artefacts may eventually be open to non-destructive imaging, identification, and interpretation.« less

Graph-cut based discrete-valued image reconstruction.

PubMed

Tuysuzoglu, Ahmet; Karl, W Clem; Stojanovic, Ivana; Castañòn, David; Ünlü, M Selim

2015-05-01

Efficient graph-cut methods have been used with great success for labeling and denoising problems occurring in computer vision. Unfortunately, the presence of linear image mappings has prevented the use of these techniques in most discrete-amplitude image reconstruction problems. In this paper, we develop a graph-cut based framework for the direct solution of discrete amplitude linear image reconstruction problems cast as regularized energy function minimizations. We first analyze the structure of discrete linear inverse problem cost functions to show that the obstacle to the application of graph-cut methods to their solution is the variable mixing caused by the presence of the linear sensing operator. We then propose to use a surrogate energy functional that overcomes the challenges imposed by the sensing operator yet can be utilized efficiently in existing graph-cut frameworks. We use this surrogate energy functional to devise a monotonic iterative algorithm for the solution of discrete valued inverse problems. We first provide experiments using local convolutional operators and show the robustness of the proposed technique to noise and stability to changes in regularization parameter. Then we focus on nonlocal, tomographic examples where we consider limited-angle data problems. We compare our technique with state-of-the-art discrete and continuous image reconstruction techniques. Experiments show that the proposed method outperforms state-of-the-art techniques in challenging scenarios involving discrete valued unknowns.

Effectiveness of image features and similarity measures in cluster-based approaches for content-based image retrieval

NASA Astrophysics Data System (ADS)

Du, Hongbo; Al-Jubouri, Hanan; Sellahewa, Harin

2014-05-01

Content-based image retrieval is an automatic process of retrieving images according to image visual contents instead of textual annotations. It has many areas of application from automatic image annotation and archive, image classification and categorization to homeland security and law enforcement. The key issues affecting the performance of such retrieval systems include sensible image features that can effectively capture the right amount of visual contents and suitable similarity measures to find similar and relevant images ranked in a meaningful order. Many different approaches, methods and techniques have been developed as a result of very intensive research in the past two decades. Among many existing approaches, is a cluster-based approach where clustering methods are used to group local feature descriptors into homogeneous regions, and search is conducted by comparing the regions of the query image against those of the stored images. This paper serves as a review of works in this area. The paper will first summarize the existing work reported in the literature and then present the authors' own investigations in this field. The paper intends to highlight not only achievements made by recent research but also challenges and difficulties still remaining in this area.

MRI technique for the snapshot imaging of quantitative velocity maps using RARE.

PubMed

Shiko, G; Sederman, A J; Gladden, L F

2012-03-01

A quantitative PGSE-RARE pulse sequence was developed and successfully applied to the in situ dissolution of two pharmaceutical formulations dissolving over a range of timescales. The new technique was chosen over other existing fast velocity imaging techniques because it is T(2) weighted, not T(2)(∗) weighted, and is, therefore, robust for imaging time-varying interfaces and flow in magnetically heterogeneous systems. The complex signal was preserved intact by separating odd and even echoes to obtain two phase maps which are then averaged in post-processing. Initially, the validity of the technique was shown when imaging laminar flow in a pipe. Subsequently, the dissolution of two drugs was followed in situ, where the technique enables the imaging and quantification of changes in the form of the tablet and the flow field surrounding it at high spatial and temporal resolution. First, the complete 3D velocity field around an eroding salicylic acid tablet was acquired at a resolution of 98×49 μm(2), within 20 min, and monitored over ∼13 h. The tablet was observed to experience a heterogeneous flow field and, hence a heterogeneous shear field, which resulted in the non-symmetric erosion of the tablet. Second, the dissolution of a fast dissolving immediate release tablet was followed using one-shot 2D velocity images acquired every 5.2 s at a resolution of 390×390 μm(2). The quantitative nature of the technique and fast acquisition times provided invaluable information on the dissolution behaviour of this tablet, which had not been attainable previously with conventional quantitative MRI techniques. Copyright © 2012 Elsevier Inc. All rights reserved.

Enhanced light element imaging in atomic resolution scanning transmission electron microscopy.

PubMed

Findlay, S D; Kohno, Y; Cardamone, L A; Ikuhara, Y; Shibata, N

2014-01-01

We show that an imaging mode based on taking the difference between signals recorded from the bright field (forward scattering region) in atomic resolution scanning transmission electron microscopy provides an enhancement of the detectability of light elements over existing techniques. In some instances this is an enhancement of the visibility of the light element columns relative to heavy element columns. In all cases explored it is an enhancement in the signal-to-noise ratio of the image at the light column site. The image formation mechanisms are explained and the technique is compared with earlier approaches. Experimental data, supported by simulation, are presented for imaging the oxygen columns in LaAlO₃. Case studies looking at imaging hydrogen columns in YH₂ and lithium columns in Al₃Li are also explored through simulation, particularly with respect to the dependence on defocus, probe-forming aperture angle and detector collection aperture angles. © 2013 Elsevier B.V. All rights reserved.

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

Identifying the arterial input function from dynamic contrast-enhanced magnetic resonance images using an apex-seeking technique

NASA Astrophysics Data System (ADS)

Martel, Anne L.

2004-04-01

In order to extract quantitative information from dynamic contrast-enhanced MR images (DCE-MRI) it is usually necessary to identify an arterial input function. This is not a trivial problem if there are no major vessels present in the field of view. Most existing techniques rely on operator intervention or use various curve parameters to identify suitable pixels but these are often specific to the anatomical region or the acquisition method used. They also require the signal from several pixels to be averaged in order to improve the signal to noise ratio, however this introduces errors due to partial volume effects. We have described previously how factor analysis can be used to automatically separate arterial and venous components from DCE-MRI studies of the brain but although that method works well for single slice images through the brain when the blood brain barrier technique is intact, it runs into problems for multi-slice images with more complex dynamics. This paper will describe a factor analysis method that is more robust in such situations and is relatively insensitive to the number of physiological components present in the data set. The technique is very similar to that used to identify spectral end-members from multispectral remote sensing images.

Supervised restoration of degraded medical images using multiple-point geostatistics.

PubMed

Pham, Tuan D

2012-06-01

Reducing noise in medical images has been an important issue of research and development for medical diagnosis, patient treatment, and validation of biomedical hypotheses. Noise inherently exists in medical and biological images due to the acquisition and transmission in any imaging devices. Being different from image enhancement, the purpose of image restoration is the process of removing noise from a degraded image in order to recover as much as possible its original version. This paper presents a statistically supervised approach for medical image restoration using the concept of multiple-point geostatistics. Experimental results have shown the effectiveness of the proposed technique which has potential as a new methodology for medical and biological image processing. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Semantic photo synthesis

NASA Astrophysics Data System (ADS)

Johnson, Matthew; Brostow, G. J.; Shotton, J.; Kwatra, V.; Cipolla, R.

2007-02-01

Composite images are synthesized from existing photographs by artists who make concept art, e.g. storyboards for movies or architectural planning. Current techniques allow an artist to fabricate such an image by digitally splicing parts of stock photographs. While these images serve mainly to "quickly" convey how a scene should look, their production is laborious. We propose a technique that allows a person to design a new photograph with substantially less effort. This paper presents a method that generates a composite image when a user types in nouns, such as "boat" and "sand." The artist can optionally design an intended image by specifying other constraints. Our algorithm formulates the constraints as queries to search an automatically annotated image database. The desired photograph, not a collage, is then synthesized using graph-cut optimization, optionally allowing for further user interaction to edit or choose among alternative generated photos. Our results demonstrate our contributions of (1) a method of creating specific images with minimal human effort, and (2) a combined algorithm for automatically building an image library with semantic annotations from any photo collection.

QR images: optimized image embedding in QR codes.

PubMed

Garateguy, Gonzalo J; Arce, Gonzalo R; Lau, Daniel L; Villarreal, Ofelia P

2014-07-01

This paper introduces the concept of QR images, an automatic method to embed QR codes into color images with bounded probability of detection error. These embeddings are compatible with standard decoding applications and can be applied to any color image with full area coverage. The QR information bits are encoded into the luminance values of the image, taking advantage of the immunity of QR readers against local luminance disturbances. To mitigate the visual distortion of the QR image, the algorithm utilizes halftoning masks for the selection of modified pixels and nonlinear programming techniques to locally optimize luminance levels. A tractable model for the probability of error is developed and models of the human visual system are considered in the quality metric used to optimize the luminance levels of the QR image. To minimize the processing time, the optimization techniques proposed to consider the mechanics of a common binarization method and are designed to be amenable for parallel implementations. Experimental results show the graceful degradation of the decoding rate and the perceptual quality as a function the embedding parameters. A visual comparison between the proposed and existing methods is presented.

Thermography based prescreening software tool for veterinary clinics

NASA Astrophysics Data System (ADS)

Dahal, Rohini; Umbaugh, Scott E.; Mishra, Deependra; Lama, Norsang; Alvandipour, Mehrdad; Umbaugh, David; Marino, Dominic J.; Sackman, Joseph

2017-05-01

Under development is a clinical software tool which can be used in the veterinary clinics as a prescreening tool for these pathologies: anterior cruciate ligament (ACL) disease, bone cancer and feline hyperthyroidism. Currently, veterinary clinical practice uses several imaging techniques including radiology, computed tomography (CT), and magnetic resonance imaging (MRI). But, harmful radiation involved during imaging, expensive equipment setup, excessive time consumption and the need for a cooperative patient during imaging, are major drawbacks of these techniques. In veterinary procedures, it is very difficult for animals to remain still for the time periods necessary for standard imaging without resorting to sedation - which creates another set of complexities. Therefore, clinical application software integrated with a thermal imaging system and the algorithms with high sensitivity and specificity for these pathologies, can address the major drawbacks of the existing imaging techniques. A graphical user interface (GUI) has been created to allow ease of use for the clinical technician. The technician inputs an image, enters patient information, and selects the camera view associated with the image and the pathology to be diagnosed. The software will classify the image using an optimized classification algorithm that has been developed through thousands of experiments. Optimal image features are extracted and the feature vector is then used in conjunction with the stored image database for classification. Classification success rates as high as 88% for bone cancer, 75% for ACL and 90% for feline hyperthyroidism have been achieved. The software is currently undergoing preliminary clinical testing.

Image-guided techniques in renal and hepatic interventions.

PubMed

Najmaei, Nima; Mostafavi, Kamal; Shahbazi, Sahar; Azizian, Mahdi

2013-12-01

Development of new imaging technologies and advances in computing power have enabled the physicians to perform medical interventions on the basis of high-quality 3D and/or 4D visualization of the patient's organs. Preoperative imaging has been used for planning the surgery, whereas intraoperative imaging has been widely employed to provide visual feedback to a clinician when he or she is performing the procedure. In the past decade, such systems demonstrated great potential in image-guided minimally invasive procedures on different organs, such as brain, heart, liver and kidneys. This article focuses on image-guided interventions and surgery in renal and hepatic surgeries. A comprehensive search of existing electronic databases was completed for the period of 2000-2011. Each contribution was assessed by the authors for relevance and inclusion. The contributions were categorized on the basis of the type of operation/intervention, imaging modality and specific techniques such as image fusion and augmented reality, and organ motion tracking. As a result, detailed classification and comparative study of various contributions in image-guided renal and hepatic interventions are provided. In addition, the potential future directions have been sketched. With a detailed review of the literature, potential future trends in development of image-guided abdominal interventions are identified, namely, growing use of image fusion and augmented reality, computer-assisted and/or robot-assisted interventions, development of more accurate registration and navigation techniques, and growing applications of intraoperative magnetic resonance imaging. Copyright © 2012 John Wiley & Sons, Ltd.

Cellular image segmentation using n-agent cooperative game theory

NASA Astrophysics Data System (ADS)

Dimock, Ian B.; Wan, Justin W. L.

2016-03-01

Image segmentation is an important problem in computer vision and has significant applications in the segmentation of cellular images. Many different imaging techniques exist and produce a variety of image properties which pose difficulties to image segmentation routines. Bright-field images are particularly challenging because of the non-uniform shape of the cells, the low contrast between cells and background, and imaging artifacts such as halos and broken edges. Classical segmentation techniques often produce poor results on these challenging images. Previous attempts at bright-field imaging are often limited in scope to the images that they segment. In this paper, we introduce a new algorithm for automatically segmenting cellular images. The algorithm incorporates two game theoretic models which allow each pixel to act as an independent agent with the goal of selecting their best labelling strategy. In the non-cooperative model, the pixels choose strategies greedily based only on local information. In the cooperative model, the pixels can form coalitions, which select labelling strategies that benefit the entire group. Combining these two models produces a method which allows the pixels to balance both local and global information when selecting their label. With the addition of k-means and active contour techniques for initialization and post-processing purposes, we achieve a robust segmentation routine. The algorithm is applied to several cell image datasets including bright-field images, fluorescent images and simulated images. Experiments show that the algorithm produces good segmentation results across the variety of datasets which differ in cell density, cell shape, contrast, and noise levels.

Efficient volumetric estimation from plenoptic data

NASA Astrophysics Data System (ADS)

Anglin, Paul; Reeves, Stanley J.; Thurow, Brian S.

2013-03-01

The commercial release of the Lytro camera, and greater availability of plenoptic imaging systems in general, have given the image processing community cost-effective tools for light-field imaging. While this data is most commonly used to generate planar images at arbitrary focal depths, reconstruction of volumetric fields is also possible. Similarly, deconvolution is a technique that is conventionally used in planar image reconstruction, or deblurring, algorithms. However, when leveraged with the ability of a light-field camera to quickly reproduce multiple focal planes within an imaged volume, deconvolution offers a computationally efficient method of volumetric reconstruction. Related research has shown than light-field imaging systems in conjunction with tomographic reconstruction techniques are also capable of estimating the imaged volume and have been successfully applied to particle image velocimetry (PIV). However, while tomographic volumetric estimation through algorithms such as multiplicative algebraic reconstruction techniques (MART) have proven to be highly accurate, they are computationally intensive. In this paper, the reconstruction problem is shown to be solvable by deconvolution. Deconvolution offers significant improvement in computational efficiency through the use of fast Fourier transforms (FFTs) when compared to other tomographic methods. This work describes a deconvolution algorithm designed to reconstruct a 3-D particle field from simulated plenoptic data. A 3-D extension of existing 2-D FFT-based refocusing techniques is presented to further improve efficiency when computing object focal stacks and system point spread functions (PSF). Reconstruction artifacts are identified; their underlying source and methods of mitigation are explored where possible, and reconstructions of simulated particle fields are provided.

Real-time phase-contrast x-ray imaging: a new technique for the study of animal form and function

PubMed Central

Socha, John J; Westneat, Mark W; Harrison, Jon F; Waters, James S; Lee, Wah-Keat

2007-01-01

Background Despite advances in imaging techniques, real-time visualization of the structure and dynamics of tissues and organs inside small living animals has remained elusive. Recently, we have been using synchrotron x-rays to visualize the internal anatomy of millimeter-sized opaque, living animals. This technique takes advantage of partially-coherent x-rays and diffraction to enable clear visualization of internal soft tissue not viewable via conventional absorption radiography. However, because higher quality images require greater x-ray fluxes, there exists an inherent tradeoff between image quality and tissue damage. Results We evaluated the tradeoff between image quality and harm to the animal by determining the impact of targeted synchrotron x-rays on insect physiology, behavior and survival. Using 25 keV x-rays at a flux density of 80 μW/mm-2, high quality video-rate images can be obtained without major detrimental effects on the insects for multiple minutes, a duration sufficient for many physiological studies. At this setting, insects do not heat up. Additionally, we demonstrate the range of uses of synchrotron phase-contrast imaging by showing high-resolution images of internal anatomy and observations of labeled food movement during ingestion and digestion. Conclusion Synchrotron x-ray phase contrast imaging has the potential to revolutionize the study of physiology and internal biomechanics in small animals. This is the only generally applicable technique that has the necessary spatial and temporal resolutions, penetrating power, and sensitivity to soft tissue that is required to visualize the internal physiology of living animals on the scale from millimeters to microns. PMID:17331247

MO-C-BRCD-03: The Role of Informatics in Medical Physics and Vice Versa.

PubMed

Andriole, K

2012-06-01

Like Medical Physics, Imaging Informatics encompasses concepts touching every aspect of the imaging chain from image creation, acquisition, management and archival, to image processing, analysis, display and interpretation. The two disciplines are in fact quite complementary, with similar goals to improve the quality of care provided to patients using an evidence-based approach, to assure safety in the clinical and research environments, to facilitate efficiency in the workplace, and to accelerate knowledge discovery. Use-cases describing several areas of informatics activity will be given to illustrate current limitations that would benefit from medical physicist participation, and conversely areas in which informaticists may contribute to the solution. Topics to be discussed include radiation dose monitoring, process management and quality control, display technologies, business analytics techniques, and quantitative imaging. Quantitative imaging is increasingly becoming an essential part of biomedicalresearch as well as being incorporated into clinical diagnostic activities. Referring clinicians are asking for more objective information to be gleaned from the imaging tests that they order so that they may make the best clinical management decisions for their patients. Medical Physicists may be called upon to identify existing issues as well as develop, validate and implement new approaches and technologies to help move the field further toward quantitative imaging methods for the future. Biomedical imaging informatics tools and techniques such as standards, integration, data mining, cloud computing and new systems architectures, ontologies and lexicons, data visualization and navigation tools, and business analytics applications can be used to overcome some of the existing limitations. 1. Describe what is meant by Medical Imaging Informatics and understand why the medical physicist should care. 2. Identify existing limitations in information technologies with respect to Medical Physics, and conversely see how Informatics may assist the medical physicist in filling some of the current gaps in their activities. 3. Understand general informatics concepts and areas of investigation including imaging and workflow standards, systems integration, computing architectures, ontologies, data mining and business analytics, data visualization and human-computer interface tools, and the importance of quantitative imaging for the future of Medical Physics and Imaging Informatics. 4. Become familiar with on-going efforts to address current challenges facing future research into and clinical implementation of quantitative imaging applications. © 2012 American Association of Physicists in Medicine.

Scheimpflug with computational imaging to extend the depth of field of iris recognition systems

NASA Astrophysics Data System (ADS)

Sinharoy, Indranil

Despite the enormous success of iris recognition in close-range and well-regulated spaces for biometric authentication, it has hitherto failed to gain wide-scale adoption in less controlled, public environments. The problem arises from a limitation in imaging called the depth of field (DOF): the limited range of distances beyond which subjects appear blurry in the image. The loss of spatial details in the iris image outside the small DOF limits the iris image capture to a small volume-the capture volume. Existing techniques to extend the capture volume are usually expensive, computationally intensive, or afflicted by noise. Is there a way to combine the classical Scheimpflug principle with the modern computational imaging techniques to extend the capture volume? The solution we found is, surprisingly, simple; yet, it provides several key advantages over existing approaches. Our method, called Angular Focus Stacking (AFS), consists of capturing a set of images while rotating the lens, followed by registration, and blending of the in-focus regions from the images in the stack. The theoretical underpinnings of AFS arose from a pair of new and general imaging models we developed for Scheimpflug imaging that directly incorporates the pupil parameters. The model revealed that we could register the images in the stack analytically if we pivot the lens at the center of its entrance pupil, rendering the registration process exact. Additionally, we found that a specific lens design further reduces the complexity of image registration making AFS suitable for real-time performance. We have demonstrated up to an order of magnitude improvement in the axial capture volume over conventional image capture without sacrificing optical resolution and signal-to-noise ratio. The total time required for capturing the set of images for AFS is less than the time needed for a single-exposure, conventional image for the same DOF and brightness level. The net reduction in capture time can significantly relax the constraints on subject movement during iris acquisition, making it less restrictive.

Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique

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

Teramoto, Atsushi, E-mail: teramoto@fujita-hu.ac.jp; Fujita, Hiroshi; Yamamuro, Osamu

Purpose: Automated detection of solitary pulmonary nodules using positron emission tomography (PET) and computed tomography (CT) images shows good sensitivity; however, it is difficult to detect nodules in contact with normal organs, and additional efforts are needed so that the number of false positives (FPs) can be further reduced. In this paper, the authors propose an improved FP-reduction method for the detection of pulmonary nodules in PET/CT images by means of convolutional neural networks (CNNs). Methods: The overall scheme detects pulmonary nodules using both CT and PET images. In the CT images, a massive region is first detected using anmore » active contour filter, which is a type of contrast enhancement filter that has a deformable kernel shape. Subsequently, high-uptake regions detected by the PET images are merged with the regions detected by the CT images. FP candidates are eliminated using an ensemble method; it consists of two feature extractions, one by shape/metabolic feature analysis and the other by a CNN, followed by a two-step classifier, one step being rule based and the other being based on support vector machines. Results: The authors evaluated the detection performance using 104 PET/CT images collected by a cancer-screening program. The sensitivity in detecting candidates at an initial stage was 97.2%, with 72.8 FPs/case. After performing the proposed FP-reduction method, the sensitivity of detection was 90.1%, with 4.9 FPs/case; the proposed method eliminated approximately half the FPs existing in the previous study. Conclusions: An improved FP-reduction scheme using CNN technique has been developed for the detection of pulmonary nodules in PET/CT images. The authors’ ensemble FP-reduction method eliminated 93% of the FPs; their proposed method using CNN technique eliminates approximately half the FPs existing in the previous study. These results indicate that their method may be useful in the computer-aided detection of pulmonary nodules using PET/CT images.« less

A robust star identification algorithm with star shortlisting

NASA Astrophysics Data System (ADS)

Mehta, Deval Samirbhai; Chen, Shoushun; Low, Kay Soon

2018-05-01

A star tracker provides the most accurate attitude solution in terms of arc seconds compared to the other existing attitude sensors. When no prior attitude information is available, it operates in "Lost-In-Space (LIS)" mode. Star pattern recognition, also known as star identification algorithm, forms the most crucial part of a star tracker in the LIS mode. Recognition reliability and speed are the two most important parameters of a star pattern recognition technique. In this paper, a novel star identification algorithm with star ID shortlisting is proposed. Firstly, the star IDs are shortlisted based on worst-case patch mismatch, and later stars are identified in the image by an initial match confirmed with a running sequential angular match technique. The proposed idea is tested on 16,200 simulated star images having magnitude uncertainty, noise stars, positional deviation, and varying size of the field of view. The proposed idea is also benchmarked with the state-of-the-art star pattern recognition techniques. Finally, the real-time performance of the proposed technique is tested on the 3104 real star images captured by a star tracker SST-20S currently mounted on a satellite. The proposed technique can achieve an identification accuracy of 98% and takes only 8.2 ms for identification on real images. Simulation and real-time results depict that the proposed technique is highly robust and achieves a high speed of identification suitable for actual space applications.

Detection of changes in semi-natural grasslands by cross correlation analysis with WorldView-2 images and new Landsat 8 data.

PubMed

Tarantino, Cristina; Adamo, Maria; Lucas, Richard; Blonda, Palma

2016-03-15

Focusing on a Mediterranean Natura 2000 site in Italy, the effectiveness of the cross correlation analysis (CCA) technique for quantifying change in the area of semi-natural grasslands at different spatial resolutions (grain) was evaluated. In a fine scale analysis (2 m), inputs to the CCA were a) a semi-natural grasslands layer extracted from an existing validated land cover/land use (LC/LU) map (1:5000, time T 1 ) and b) a more recent single date very high resolution (VHR) WorldView-2 image (time T 2 ), with T 2  > T 1 . The changes identified through the CCA were compared against those detected by applying a traditional post-classification comparison (PCC) technique to the same reference T 1 map and an updated T 2 map obtained by a knowledge driven classification of four multi-seasonal Worldview-2 input images. Specific changes observed were those associated with agricultural intensification and fires. The study concluded that prior knowledge (spectral class signatures, awareness of local agricultural practices and pressures) was needed for the selection of the most appropriate image (in terms of seasonality) to be acquired at T 2 . CCA was also applied to the comparison of the existing T 1 map with recent high resolution (HR) Landsat 8 OLS images. The areas of change detected at VHR and HR were broadly similar with larger error values in HR change images.

UNDERWATER MAPPING USING GLORIA AND MIPS.

USGS Publications Warehouse

Chavez, Pat S.; Anderson, Jeffrey A.; Schoonmaker, James W.

1987-01-01

Advances in digital image processing of the (GLORIA) Geological Long-Range Induced Asdic) sidescan-sonar image data have made it technically and economically possible to map large areas of the ocean floor including the Exclusive Economic Zone. Software was written to correct both geometric and radiometric distortions that exist in the original raw GLORIA data. A digital mosaicking technique was developed enabling 2 degree by 2 degree quadrangles to be generated.

Uses of megavoltage digital tomosynthesis in radiotherapy

NASA Astrophysics Data System (ADS)

Sarkar, Vikren

With the advent of intensity modulated radiotherapy, radiation treatment plans are becoming more conformal to the tumor with the decreasing margins. It is therefore of prime importance that the patient be positioned correctly prior to treatment. Therefore, image guided treatment is necessary for intensity modulated radiotherapy plans to be implemented successfully. Current advanced imaging devices require costly hardware and software upgrade, and radiation imaging solutions, such as cone beam computed tomography, may introduce extra radiation dose to the patient in order to acquire better quality images. Thus, there is a need to extend current existing imaging device ability and functions while reducing cost and radiation dose. Existing electronic portal imaging devices can be used to generate computed tomography-like tomograms through projection images acquired over a small angle using the technique of cone-beam digital tomosynthesis. Since it uses a fraction of the images required for computed tomography reconstruction, use of this technique correspondingly delivers only a fraction of the imaging dose to the patient. Furthermore, cone-beam digital tomosynthesis can be offered as a software-only solution as long as a portal imaging device is available. In this study, the feasibility of performing digital tomosynthesis using individually-acquired megavoltage images from a charge coupled device-based electronic portal imaging device was investigated. Three digital tomosynthesis reconstruction algorithms, the shift-and-add, filtered back-projection, and simultaneous algebraic reconstruction technique, were compared considering the final image quality and radiation dose during imaging. A software platform, DART, was created using a combination of the Matlab and C++ languages. The platform allows for the registration of a reference Cone Beam Digital Tomosynthesis (CBDT) image against a daily acquired set to determine how to shift the patient prior to treatment. Finally, the software was extended to investigate if the digital tomosynthesis dataset could be used in an adaptive radiotherapy regimen through the use of the Pinnacle treatment planning software to recalculate dose delivered. The feasibility study showed that the megavoltage CBDT visually agreed with corresponding megavoltage computed tomography images. The comparative study showed that the best compromise between imaging quality and imaging dose is obtained when 11 projection images, acquired over an imaging angle of 40°, are used with the filtered back-projection algorithm. DART was successfully used to register reference and daily image sets to within 1 mm in-plane and 2.5 mm out of plane. The DART platform was also effectively used to generate updated files that the Pinnacle treatment planning system used to calculate updated dose in a rigidly shifted patient. These doses were then used to calculate a cumulative dose distribution that could be used by a physician as reference to decide when the treatment plan should be updated. In conclusion, this study showed that a software solution is possible to extend existing electronic portal imaging devices to function as cone-beam digital tomosynthesis devices and achieve daily requirement for image guided intensity modulated radiotherapy treatments. The DART platform also has the potential to be used as a part of adaptive radiotherapy solution.

Hyperspectral range imaging for transportation systems evaluation

NASA Astrophysics Data System (ADS)

Bridgelall, Raj; Rafert, J. B.; Atwood, Don; Tolliver, Denver D.

2016-04-01

Transportation agencies expend significant resources to inspect critical infrastructure such as roadways, railways, and pipelines. Regular inspections identify important defects and generate data to forecast maintenance needs. However, cost and practical limitations prevent the scaling of current inspection methods beyond relatively small portions of the network. Consequently, existing approaches fail to discover many high-risk defect formations. Remote sensing techniques offer the potential for more rapid and extensive non-destructive evaluations of the multimodal transportation infrastructure. However, optical occlusions and limitations in the spatial resolution of typical airborne and space-borne platforms limit their applicability. This research proposes hyperspectral image classification to isolate transportation infrastructure targets for high-resolution photogrammetric analysis. A plenoptic swarm of unmanned aircraft systems will capture images with centimeter-scale spatial resolution, large swaths, and polarization diversity. The light field solution will incorporate structure-from-motion techniques to reconstruct three-dimensional details of the isolated targets from sequences of two-dimensional images. A comparative analysis of existing low-power wireless communications standards suggests an application dependent tradeoff in selecting the best-suited link to coordinate swarming operations. This study further produced a taxonomy of specific roadway and railway defects, distress symptoms, and other anomalies that the proposed plenoptic swarm sensing system would identify and characterize to estimate risk levels.

Simultenious binary hash and features learning for image retrieval

NASA Astrophysics Data System (ADS)

Frantc, V. A.; Makov, S. V.; Voronin, V. V.; Marchuk, V. I.; Semenishchev, E. A.; Egiazarian, K. O.; Agaian, S.

2016-05-01

Content-based image retrieval systems have plenty of applications in modern world. The most important one is the image search by query image or by semantic description. Approaches to this problem are employed in personal photo-collection management systems, web-scale image search engines, medical systems, etc. Automatic analysis of large unlabeled image datasets is virtually impossible without satisfactory image-retrieval technique. It's the main reason why this kind of automatic image processing has attracted so much attention during recent years. Despite rather huge progress in the field, semantically meaningful image retrieval still remains a challenging task. The main issue here is the demand to provide reliable results in short amount of time. This paper addresses the problem by novel technique for simultaneous learning of global image features and binary hash codes. Our approach provide mapping of pixel-based image representation to hash-value space simultaneously trying to save as much of semantic image content as possible. We use deep learning methodology to generate image description with properties of similarity preservation and statistical independence. The main advantage of our approach in contrast to existing is ability to fine-tune retrieval procedure for very specific application which allow us to provide better results in comparison to general techniques. Presented in the paper framework for data- dependent image hashing is based on use two different kinds of neural networks: convolutional neural networks for image description and autoencoder for feature to hash space mapping. Experimental results confirmed that our approach has shown promising results in compare to other state-of-the-art methods.

Perceptual distortion analysis of color image VQ-based coding

NASA Astrophysics Data System (ADS)

Charrier, Christophe; Knoblauch, Kenneth; Cherifi, Hocine

1997-04-01

It is generally accepted that a RGB color image can be easily encoded by using a gray-scale compression technique on each of the three color planes. Such an approach, however, fails to take into account correlations existing between color planes and perceptual factors. We evaluated several linear and non-linear color spaces, some introduced by the CIE, compressed with the vector quantization technique for minimum perceptual distortion. To study these distortions, we measured contrast and luminance of the video framebuffer, to precisely control color. We then obtained psychophysical judgements to measure how well these methods work to minimize perceptual distortion in a variety of color space.

Making the PACS workstation a browser of image processing software: a feasibility study using inter-process communication techniques.

PubMed

Wang, Chunliang; Ritter, Felix; Smedby, Orjan

2010-07-01

To enhance the functional expandability of a picture archiving and communication systems (PACS) workstation and to facilitate the integration of third-part image-processing modules, we propose a browser-server style method. In the proposed solution, the PACS workstation shows the front-end user interface defined in an XML file while the image processing software is running in the background as a server. Inter-process communication (IPC) techniques allow an efficient exchange of image data, parameters, and user input between the PACS workstation and stand-alone image-processing software. Using a predefined communication protocol, the PACS workstation developer or image processing software developer does not need detailed information about the other system, but will still be able to achieve seamless integration between the two systems and the IPC procedure is totally transparent to the final user. A browser-server style solution was built between OsiriX (PACS workstation software) and MeVisLab (Image-Processing Software). Ten example image-processing modules were easily added to OsiriX by converting existing MeVisLab image processing networks. Image data transfer using shared memory added <10ms of processing time while the other IPC methods cost 1-5 s in our experiments. The browser-server style communication based on IPC techniques is an appealing method that allows PACS workstation developers and image processing software developers to cooperate while focusing on different interests.

Multi-MHz laser-scanning single-cell fluorescence microscopy by spatiotemporally encoded virtual source array

PubMed Central

Wu, Jianglai; Tang, Anson H. L.; Mok, Aaron T. Y.; Yan, Wenwei; Chan, Godfrey C. F.; Wong, Kenneth K. Y.; Tsia, Kevin K.

2017-01-01

Apart from the spatial resolution enhancement, scaling of temporal resolution, equivalently the imaging throughput, of fluorescence microscopy is of equal importance in advancing cell biology and clinical diagnostics. Yet, this attribute has mostly been overlooked because of the inherent speed limitation of existing imaging strategies. To address the challenge, we employ an all-optical laser-scanning mechanism, enabled by an array of reconfigurable spatiotemporally-encoded virtual sources, to demonstrate ultrafast fluorescence microscopy at line-scan rate as high as 8 MHz. We show that this technique enables high-throughput single-cell microfluidic fluorescence imaging at 75,000 cells/second and high-speed cellular 2D dynamical imaging at 3,000 frames per second, outperforming the state-of-the-art high-speed cameras and the gold-standard laser scanning strategies. Together with its wide compatibility to the existing imaging modalities, this technology could empower new forms of high-throughput and high-speed biological fluorescence microscopy that was once challenged. PMID:28966855

Glioma grading using cell nuclei morphologic features in digital pathology images

NASA Astrophysics Data System (ADS)

Reza, Syed M. S.; Iftekharuddin, Khan M.

2016-03-01

This work proposes a computationally efficient cell nuclei morphologic feature analysis technique to characterize the brain gliomas in tissue slide images. In this work, our contributions are two-fold: 1) obtain an optimized cell nuclei segmentation method based on the pros and cons of the existing techniques in literature, 2) extract representative features by k-mean clustering of nuclei morphologic features to include area, perimeter, eccentricity, and major axis length. This clustering based representative feature extraction avoids shortcomings of extensive tile [1] [2] and nuclear score [3] based methods for brain glioma grading in pathology images. Multilayer perceptron (MLP) is used to classify extracted features into two tumor types: glioblastoma multiforme (GBM) and low grade glioma (LGG). Quantitative scores such as precision, recall, and accuracy are obtained using 66 clinical patients' images from The Cancer Genome Atlas (TCGA) [4] dataset. On an average ~94% accuracy from 10 fold crossvalidation confirms the efficacy of the proposed method.

Authenticity techniques for PACS images and records

NASA Astrophysics Data System (ADS)

Wong, Stephen T. C.; Abundo, Marco; Huang, H. K.

1995-05-01

Along with the digital radiology environment supported by picture archiving and communication systems (PACS) comes a new problem: How to establish trust in multimedia medical data that exist only in the easily altered memory of a computer. Trust is characterized in terms of integrity and privacy of digital data. Two major self-enforcing techniques can be used to assure the authenticity of electronic images and text -- key-based cryptography and digital time stamping. Key-based cryptography associates the content of an image with the originator using one or two distinct keys and prevents alteration of the document by anyone other than the originator. A digital time stamping algorithm generates a characteristic `digital fingerprint' for the original document using a mathematical hash function, and checks that it has not been modified. This paper discusses these cryptographic algorithms and their appropriateness for a PACS environment. It also presents experimental results of cryptographic algorithms on several imaging modalities.

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

Full-color large-scaled computer-generated holograms for physical and non-physical objects

NASA Astrophysics Data System (ADS)

Matsushima, Kyoji; Tsuchiyama, Yasuhiro; Sonobe, Noriaki; Masuji, Shoya; Yamaguchi, Masahiro; Sakamoto, Yuji

2017-05-01

Several full-color high-definition CGHs are created for reconstructing 3D scenes including real-existing physical objects. The field of the physical objects are generated or captured by employing three techniques; 3D scanner, synthetic aperture digital holography, and multi-viewpoint images. Full-color reconstruction of high-definition CGHs is realized by RGB color filters. The optical reconstructions are presented for verifying these techniques.

Experimental Verification of Bayesian Planet Detection Algorithms with a Shaped Pupil Coronagraph

NASA Astrophysics Data System (ADS)

Savransky, D.; Groff, T. D.; Kasdin, N. J.

2010-10-01

We evaluate the feasibility of applying Bayesian detection techniques to discovering exoplanets using high contrast laboratory data with simulated planetary signals. Background images are generated at the Princeton High Contrast Imaging Lab (HCIL), with a coronagraphic system utilizing a shaped pupil and two deformable mirrors (DMs) in series. Estimates of the electric field at the science camera are used to correct for quasi-static speckle and produce symmetric high contrast dark regions in the image plane. Planetary signals are added in software, or via a physical star-planet simulator which adds a second off-axis point source before the coronagraph with a beam recombiner, calibrated to a fixed contrast level relative to the source. We produce a variety of images, with varying integration times and simulated planetary brightness. We then apply automated detection algorithms such as matched filtering to attempt to extract the planetary signals. This allows us to evaluate the efficiency of these techniques in detecting planets in a high noise regime and eliminating false positives, as well as to test existing algorithms for calculating the required integration times for these techniques to be applicable.

Using deep learning for content-based medical image retrieval

NASA Astrophysics Data System (ADS)

Sun, Qinpei; Yang, Yuanyuan; Sun, Jianyong; Yang, Zhiming; Zhang, Jianguo

2017-03-01

Content-Based medical image retrieval (CBMIR) is been highly active research area from past few years. The retrieval performance of a CBMIR system crucially depends on the feature representation, which have been extensively studied by researchers for decades. Although a variety of techniques have been proposed, it remains one of the most challenging problems in current CBMIR research, which is mainly due to the well-known "semantic gap" issue that exists between low-level image pixels captured by machines and high-level semantic concepts perceived by human[1]. Recent years have witnessed some important advances of new techniques in machine learning. One important breakthrough technique is known as "deep learning". Unlike conventional machine learning methods that are often using "shallow" architectures, deep learning mimics the human brain that is organized in a deep architecture and processes information through multiple stages of transformation and representation. This means that we do not need to spend enormous energy to extract features manually. In this presentation, we propose a novel framework which uses deep learning to retrieval the medical image to improve the accuracy and speed of a CBIR in integrated RIS/PACS.

Watermarking techniques for electronic delivery of remote sensing images

NASA Astrophysics Data System (ADS)

Barni, Mauro; Bartolini, Franco; Magli, Enrico; Olmo, Gabriella

2002-09-01

Earth observation missions have recently attracted a growing interest, mainly due to the large number of possible applications capable of exploiting remotely sensed data and images. Along with the increase of market potential, the need arises for the protection of the image products. Such a need is a very crucial one, because the Internet and other public/private networks have become preferred means of data exchange. A critical issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. A question that obviously arises is whether the requirements imposed by remote sensing imagery are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: assessment of the requirements imposed by remote sensing applications on watermark-based copyright protection, and modification of two well-established digital watermarking techniques to meet such constraints. More specifically, the concept of near-lossless watermarking is introduced and two possible algorithms matching such a requirement are presented. Experimental results are shown to measure the impact of watermark introduction on a typical remote sensing application, i.e., unsupervised image classification.

Stellar Echo Imaging of Exoplanets

NASA Technical Reports Server (NTRS)

Mann, Chris; Lerch, Kieran; Lucente, Mark; Meza-Galvan, Jesus; Mitchell, Dan; Ruedin, Josh; Williams, Spencer; Zollars, Byron

2016-01-01

All stars exhibit intensity fluctuations over several timescales, from nanoseconds to years. These intensity fluctuations echo off bodies and structures in the star system. We posit that it is possible to take advantage of these echoes to detect, and possibly image, Earth-scale exoplanets. Unlike direct imaging techniques, temporal measurements do not require fringe tracking, maintaining an optically-perfect baseline, or utilizing ultra-contrast coronagraphs. Unlike transit or radial velocity techniques, stellar echo detection is not constrained to any specific orbital inclination. Current results suggest that existing and emerging technology can already enable stellar echo techniques at flare stars, such as Proxima Centauri, including detection, spectroscopic interrogation, and possibly even continent-level imaging of exoplanets in a variety of orbits. Detection of Earth-like planets around Sun-like stars appears to be extremely challenging, but cannot be fully quantified without additional data on micro- and millisecond-scale intensity fluctuations of the Sun. We consider survey missions in the mold of Kepler and place preliminary constraints on the feasibility of producing 3D tomographic maps of other structures in star systems, such as accretion disks. In this report we discuss the theory, limitations, models, and future opportunities for stellar echo imaging.

Motion correction of PET brain images through deconvolution: II. Practical implementation and algorithm optimization

NASA Astrophysics Data System (ADS)

Raghunath, N.; Faber, T. L.; Suryanarayanan, S.; Votaw, J. R.

2009-02-01

Image quality is significantly degraded even by small amounts of patient motion in very high-resolution PET scanners. When patient motion is known, deconvolution methods can be used to correct the reconstructed image and reduce motion blur. This paper describes the implementation and optimization of an iterative deconvolution method that uses an ordered subset approach to make it practical and clinically viable. We performed ten separate FDG PET scans using the Hoffman brain phantom and simultaneously measured its motion using the Polaris Vicra tracking system (Northern Digital Inc., Ontario, Canada). The feasibility and effectiveness of the technique was studied by performing scans with different motion and deconvolution parameters. Deconvolution resulted in visually better images and significant improvement as quantified by the Universal Quality Index (UQI) and contrast measures. Finally, the technique was applied to human studies to demonstrate marked improvement. Thus, the deconvolution technique presented here appears promising as a valid alternative to existing motion correction methods for PET. It has the potential for deblurring an image from any modality if the causative motion is known and its effect can be represented in a system matrix.

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

Investigations of image fusion

NASA Astrophysics Data System (ADS)

Zhang, Zhong

1999-12-01

The objective of image fusion is to combine information from multiple images of the same scene. The result of image fusion is a single image which is more suitable for the purpose of human visual perception or further image processing tasks. In this thesis, a region-based fusion algorithm using the wavelet transform is proposed. The identification of important features in each image, such as edges and regions of interest, are used to guide the fusion process. The idea of multiscale grouping is also introduced and a generic image fusion framework based on multiscale decomposition is studied. The framework includes all of the existing multiscale-decomposition- based fusion approaches we found in the literature which did not assume a statistical model for the source images. Comparisons indicate that our framework includes some new approaches which outperform the existing approaches for the cases we consider. Registration must precede our fusion algorithms. So we proposed a hybrid scheme which uses both feature-based and intensity-based methods. The idea of robust estimation of optical flow from time- varying images is employed with a coarse-to-fine multi- resolution approach and feature-based registration to overcome some of the limitations of the intensity-based schemes. Experiments show that this approach is robust and efficient. Assessing image fusion performance in a real application is a complicated issue. In this dissertation, a mixture probability density function model is used in conjunction with the Expectation- Maximization algorithm to model histograms of edge intensity. Some new techniques are proposed for estimating the quality of a noisy image of a natural scene. Such quality measures can be used to guide the fusion. Finally, we study fusion of images obtained from several copies of a new type of camera developed for video surveillance. Our techniques increase the capability and reliability of the surveillance system and provide an easy way to obtain 3-D information of objects in the space monitored by the system.

Biochemical magnetic resonance imaging of knee articular cartilage: T1rho and T2 mapping as cartilage degeneration biomarkers.

PubMed

Le, Jenna; Peng, Qi; Sperling, Karen

2016-11-01

Osteoarthritis (OA) is a disease whose hallmark is the degeneration of articular cartilage. There is a worsening epidemic of OA in the United States today, with considerable economic costs. In order to develop more effective treatments for OA, noninvasive biomarkers that permit early diagnosis and treatment monitoring are necessary. T1rho and T2 mapping are two magnetic resonance imaging techniques that have shown great promise as noninvasive biomarkers of cartilage degeneration. Each of the two techniques is endowed with advantages and disadvantages: T1rho can discern earlier biochemical changes of OA than T2 mapping, while T2 mapping is more widely available and can be incorporated into existing imaging protocols in a more time-efficient manner than T1rho. Both techniques have been applied in numerous instances to study how cartilage is affected by OA risk factors, such as age and exercise. Additionally, both techniques have been repeatedly applied to the study of posttraumatic OA in patients with torn anterior cruciate ligaments. © 2016 New York Academy of Sciences.

Image interpolation by adaptive 2-D autoregressive modeling and soft-decision estimation.

PubMed

Zhang, Xiangjun; Wu, Xiaolin

2008-06-01

The challenge of image interpolation is to preserve spatial details. We propose a soft-decision interpolation technique that estimates missing pixels in groups rather than one at a time. The new technique learns and adapts to varying scene structures using a 2-D piecewise autoregressive model. The model parameters are estimated in a moving window in the input low-resolution image. The pixel structure dictated by the learnt model is enforced by the soft-decision estimation process onto a block of pixels, including both observed and estimated. The result is equivalent to that of a high-order adaptive nonseparable 2-D interpolation filter. This new image interpolation approach preserves spatial coherence of interpolated images better than the existing methods, and it produces the best results so far over a wide range of scenes in both PSNR measure and subjective visual quality. Edges and textures are well preserved, and common interpolation artifacts (blurring, ringing, jaggies, zippering, etc.) are greatly reduced.

An image segmentation method based on fuzzy C-means clustering and Cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Wang, Mingwei; Wan, Youchuan; Gao, Xianjun; Ye, Zhiwei; Chen, Maolin

2018-04-01

Image segmentation is a significant step in image analysis and machine vision. Many approaches have been presented in this topic; among them, fuzzy C-means (FCM) clustering is one of the most widely used methods for its high efficiency and ambiguity of images. However, the success of FCM could not be guaranteed because it easily traps into local optimal solution. Cuckoo search (CS) is a novel evolutionary algorithm, which has been tested on some optimization problems and proved to be high-efficiency. Therefore, a new segmentation technique using FCM and blending of CS algorithm is put forward in the paper. Further, the proposed method has been measured on several images and compared with other existing FCM techniques such as genetic algorithm (GA) based FCM and particle swarm optimization (PSO) based FCM in terms of fitness value. Experimental results indicate that the proposed method is robust, adaptive and exhibits the better performance than other methods involved in the paper.

A deep semantic mobile application for thyroid cytopathology

NASA Astrophysics Data System (ADS)

Kim, Edward; Corte-Real, Miguel; Baloch, Zubair

2016-03-01

Cytopathology is the study of disease at the cellular level and often used as a screening tool for cancer. Thyroid cytopathology is a branch of pathology that studies the diagnosis of thyroid lesions and diseases. A pathologist views cell images that may have high visual variance due to different anatomical structures and pathological characteristics. To assist the physician with identifying and searching through images, we propose a deep semantic mobile application. Our work augments recent advances in the digitization of pathology and machine learning techniques, where there are transformative opportunities for computers to assist pathologists. Our system uses a custom thyroid ontology that can be augmented with multimedia metadata extracted from images using deep machine learning techniques. We describe the utilization of a particular methodology, deep convolutional neural networks, to the application of cytopathology classification. Our method is able to leverage networks that have been trained on millions of generic images, to medical scenarios where only hundreds or thousands of images exist. We demonstrate the benefits of our framework through both quantitative and qualitative results.

Perfect blind restoration of images blurred by multiple filters: theory and efficient algorithms.

PubMed

Harikumar, G; Bresler, Y

1999-01-01

We address the problem of restoring an image from its noisy convolutions with two or more unknown finite impulse response (FIR) filters. We develop theoretical results about the existence and uniqueness of solutions, and show that under some generically true assumptions, both the filters and the image can be determined exactly in the absence of noise, and stably estimated in its presence. We present efficient algorithms to estimate the blur functions and their sizes. These algorithms are of two types, subspace-based and likelihood-based, and are extensions of techniques proposed for the solution of the multichannel blind deconvolution problem in one dimension. We present memory and computation-efficient techniques to handle the very large matrices arising in the two-dimensional (2-D) case. Once the blur functions are determined, they are used in a multichannel deconvolution step to reconstruct the unknown image. The theoretical and practical implications of edge effects, and "weakly exciting" images are examined. Finally, the algorithms are demonstrated on synthetic and real data.

Impervious surfaces mapping using high resolution satellite imagery

NASA Astrophysics Data System (ADS)

Shirmeen, Tahmina

In recent years, impervious surfaces have emerged not only as an indicator of the degree of urbanization, but also as an indicator of environmental quality. As impervious surface area increases, storm water runoff increases in velocity, quantity, temperature and pollution load. Any of these attributes can contribute to the degradation of natural hydrology and water quality. Various image processing techniques have been used to identify the impervious surfaces, however, most of the existing impervious surface mapping tools used moderate resolution imagery. In this project, the potential of standard image processing techniques to generate impervious surface data for change detection analysis using high-resolution satellite imagery was evaluated. The city of Oxford, MS was selected as the study site for this project. Standard image processing techniques, including Normalized Difference Vegetation Index (NDVI), Principal Component Analysis (PCA), a combination of NDVI and PCA, and image classification algorithms, were used to generate impervious surfaces from multispectral IKONOS and QuickBird imagery acquired in both leaf-on and leaf-off conditions. Accuracy assessments were performed, using truth data generated by manual classification, with Kappa statistics and Zonal statistics to select the most appropriate image processing techniques for impervious surface mapping. The performance of selected image processing techniques was enhanced by incorporating Soil Brightness Index (SBI) and Greenness Index (GI) derived from Tasseled Cap Transformed (TCT) IKONOS and QuickBird imagery. A time series of impervious surfaces for the time frame between 2001 and 2007 was made using the refined image processing techniques to analyze the changes in IS in Oxford. It was found that NDVI and the combined NDVI--PCA methods are the most suitable image processing techniques for mapping impervious surfaces in leaf-off and leaf-on conditions respectively, using high resolution multispectral imagery. It was also found that IS data generated by these techniques can be refined by removing the conflicting dry soil patches using SBI and GI obtained from TCT of the same imagery used for IS data generation. The change detection analysis of the IS time series shows that Oxford experienced the major changes in IS from the year 2001 to 2004 and 2006 to 2007.

Biology and therapy of fibromyalgia. Functional magnetic resonance imaging findings in fibromyalgia

PubMed Central

Williams, David A; Gracely, Richard H

2006-01-01

Techniques in neuroimaging such as functional magnetic resonance imaging (fMRI) have helped to provide insights into the role of supraspinal mechanisms in pain perception. This review focuses on studies that have applied fMRI in an attempt to gain a better understanding of the mechanisms involved in the processing of pain associated with fibromyalgia. This article provides an overview of the nociceptive system as it functions normally, reviews functional brain imaging methods, and integrates the existing literature utilizing fMRI to study central pain mechanisms in fibromyalgia. PMID:17254318

Colour Based Image Processing Method for Recognizing Ribbed Smoked Sheet Grade

NASA Astrophysics Data System (ADS)

Fibriani, Ike; Sumardi; Bayu Satriya, Alfredo; Budi Utomo, Satryo

2017-03-01

This research proposes a colour based image processing technique to recognize the Ribbed Smoked Sheet (RSS) grade so that the RSS sorting process can be faster and more accurate than the traditional one. The RSS sheet image captured by the camera is transformed into grayscale image to simplify the recognition of rust and mould on the RSS sheet. Then the grayscale image is transformed into binary image using threshold value which is obtained from the RSS 1 reference colour. The grade recognition is determined by counting the white pixel percentage. The result shows that the system has 88% of accuracy. Most faults exist on RSS 2 recognition. This is due to the illumination distribution which is not equal over the RSS image.

Review of photoacoustic flow imaging: its current state and its promises

PubMed Central

van den Berg, P.J.; Daoudi, K.; Steenbergen, W.

2015-01-01

Flow imaging is an important method for quantification in many medical imaging modalities, with applications ranging from estimating wall shear rate to detecting angiogenesis. Modalities like ultrasound and optical coherence tomography both offer flow imaging capabilities, but suffer from low contrast to red blood cells and are sensitive to clutter artefacts. Photoacoustic imaging (PAI) is a relatively new field, with a recent interest in flow imaging. The recent enthusiasm for PA flow imaging is due to its intrinsic contrast to haemoglobin, which offers a new spin on existing methods of flow imaging, and some unique approaches in addition. This review article will delve into the research on photoacoustic flow imaging, explain the principles behind the many techniques and comment on their individual advantages and disadvantages. PMID:26640771

Review of photoacoustic flow imaging: its current state and its promises.

PubMed

van den Berg, P J; Daoudi, K; Steenbergen, W

2015-09-01

Flow imaging is an important method for quantification in many medical imaging modalities, with applications ranging from estimating wall shear rate to detecting angiogenesis. Modalities like ultrasound and optical coherence tomography both offer flow imaging capabilities, but suffer from low contrast to red blood cells and are sensitive to clutter artefacts. Photoacoustic imaging (PAI) is a relatively new field, with a recent interest in flow imaging. The recent enthusiasm for PA flow imaging is due to its intrinsic contrast to haemoglobin, which offers a new spin on existing methods of flow imaging, and some unique approaches in addition. This review article will delve into the research on photoacoustic flow imaging, explain the principles behind the many techniques and comment on their individual advantages and disadvantages.

A novel fully automatic multilevel thresholding technique based on optimized intuitionistic fuzzy sets and tsallis entropy for MR brain tumor image segmentation.

PubMed

Kaur, Taranjit; Saini, Barjinder Singh; Gupta, Savita

2018-03-01

In the present paper, a hybrid multilevel thresholding technique that combines intuitionistic fuzzy sets and tsallis entropy has been proposed for the automatic delineation of the tumor from magnetic resonance images having vague boundaries and poor contrast. This novel technique takes into account both the image histogram and the uncertainty information for the computation of multiple thresholds. The benefit of the methodology is that it provides fast and improved segmentation for the complex tumorous images with imprecise gray levels. To further boost the computational speed, the mutation based particle swarm optimization is used that selects the most optimal threshold combination. The accuracy of the proposed segmentation approach has been validated on simulated, real low-grade glioma tumor volumes taken from MICCAI brain tumor segmentation (BRATS) challenge 2012 dataset and the clinical tumor images, so as to corroborate its generality and novelty. The designed technique achieves an average Dice overlap equal to 0.82010, 0.78610 and 0.94170 for three datasets. Further, a comparative analysis has also been made between the eight existing multilevel thresholding implementations so as to show the superiority of the designed technique. In comparison, the results indicate a mean improvement in Dice by an amount equal to 4.00% (p < 0.005), 9.60% (p < 0.005) and 3.58% (p < 0.005), respectively in contrast to the fuzzy tsallis approach.

In Vivo Imaging of Retinal Hypoxia in a Model of Oxygen-Induced Retinopathy.

PubMed

Uddin, Md Imam; Evans, Stephanie M; Craft, Jason R; Capozzi, Megan E; McCollum, Gary W; Yang, Rong; Marnett, Lawrence J; Uddin, Md Jashim; Jayagopal, Ashwath; Penn, John S

2016-08-05

Ischemia-induced hypoxia elicits retinal neovascularization and is a major component of several blinding retinopathies such as retinopathy of prematurity (ROP), diabetic retinopathy (DR) and retinal vein occlusion (RVO). Currently, noninvasive imaging techniques capable of detecting and monitoring retinal hypoxia in living systems do not exist. Such techniques would greatly clarify the role of hypoxia in experimental and human retinal neovascular pathogenesis. In this study, we developed and characterized HYPOX-4, a fluorescence-imaging probe capable of detecting retinal-hypoxia in living animals. HYPOX-4 dependent in vivo and ex vivo imaging of hypoxia was tested in a mouse model of oxygen-induced retinopathy (OIR). Predicted patterns of retinal hypoxia were imaged by HYPOX-4 dependent fluorescence activity in this animal model. In retinal cells and mouse retinal tissue, pimonidazole-adduct immunostaining confirmed the hypoxia selectivity of HYPOX-4. HYPOX-4 had no effect on retinal cell proliferation as indicated by BrdU assay and exhibited no acute toxicity in retinal tissue as indicated by TUNEL assay and electroretinography (ERG) analysis. Therefore, HYPOX-4 could potentially serve as the basis for in vivo fluorescence-based hypoxia-imaging techniques, providing a tool for investigators to understand the pathogenesis of ischemic retinopathies and for physicians to address unmet clinical needs.

In Vivo Imaging of Retinal Hypoxia in a Model of Oxygen-Induced Retinopathy

PubMed Central

Uddin, Md. Imam; Evans, Stephanie M.; Craft, Jason R.; Capozzi, Megan E.; McCollum, Gary W.; Yang, Rong; Marnett, Lawrence J.; Uddin, Md. Jashim; Jayagopal, Ashwath; Penn, John S.

2016-01-01

Ischemia-induced hypoxia elicits retinal neovascularization and is a major component of several blinding retinopathies such as retinopathy of prematurity (ROP), diabetic retinopathy (DR) and retinal vein occlusion (RVO). Currently, noninvasive imaging techniques capable of detecting and monitoring retinal hypoxia in living systems do not exist. Such techniques would greatly clarify the role of hypoxia in experimental and human retinal neovascular pathogenesis. In this study, we developed and characterized HYPOX-4, a fluorescence-imaging probe capable of detecting retinal-hypoxia in living animals. HYPOX-4 dependent in vivo and ex vivo imaging of hypoxia was tested in a mouse model of oxygen-induced retinopathy (OIR). Predicted patterns of retinal hypoxia were imaged by HYPOX-4 dependent fluorescence activity in this animal model. In retinal cells and mouse retinal tissue, pimonidazole-adduct immunostaining confirmed the hypoxia selectivity of HYPOX-4. HYPOX-4 had no effect on retinal cell proliferation as indicated by BrdU assay and exhibited no acute toxicity in retinal tissue as indicated by TUNEL assay and electroretinography (ERG) analysis. Therefore, HYPOX-4 could potentially serve as the basis for in vivo fluorescence-based hypoxia-imaging techniques, providing a tool for investigators to understand the pathogenesis of ischemic retinopathies and for physicians to address unmet clinical needs. PMID:27491345

Multivariate image analysis of laser-induced photothermal imaging used for detection of caries tooth

NASA Astrophysics Data System (ADS)

El-Sherif, Ashraf F.; Abdel Aziz, Wessam M.; El-Sharkawy, Yasser H.

2010-08-01

Time-resolved photothermal imaging has been investigated to characterize tooth for the purpose of discriminating between normal and caries areas of the hard tissue using thermal camera. Ultrasonic thermoelastic waves were generated in hard tissue by the absorption of fiber-coupled Q-switched Nd:YAG laser pulses operating at 1064 nm in conjunction with a laser-induced photothermal technique used to detect the thermal radiation waves for diagnosis of human tooth. The concepts behind the use of photo-thermal techniques for off-line detection of caries tooth features were presented by our group in earlier work. This paper illustrates the application of multivariate image analysis (MIA) techniques to detect the presence of caries tooth. MIA is used to rapidly detect the presence and quantity of common caries tooth features as they scanned by the high resolution color (RGB) thermal cameras. Multivariate principal component analysis is used to decompose the acquired three-channel tooth images into a two dimensional principal components (PC) space. Masking score point clusters in the score space and highlighting corresponding pixels in the image space of the two dominant PCs enables isolation of caries defect pixels based on contrast and color information. The technique provides a qualitative result that can be used for early stage caries tooth detection. The proposed technique can potentially be used on-line or real-time resolved to prescreen the existence of caries through vision based systems like real-time thermal camera. Experimental results on the large number of extracted teeth as well as one of the thermal image panoramas of the human teeth voltanteer are investigated and presented.

Rapid, topology-based particle tracking for high-resolution measurements of large complex 3D motion fields.

PubMed

Patel, Mohak; Leggett, Susan E; Landauer, Alexander K; Wong, Ian Y; Franck, Christian

2018-04-03

Spatiotemporal tracking of tracer particles or objects of interest can reveal localized behaviors in biological and physical systems. However, existing tracking algorithms are most effective for relatively low numbers of particles that undergo displacements smaller than their typical interparticle separation distance. Here, we demonstrate a single particle tracking algorithm to reconstruct large complex motion fields with large particle numbers, orders of magnitude larger than previously tractably resolvable, thus opening the door for attaining very high Nyquist spatial frequency motion recovery in the images. Our key innovations are feature vectors that encode nearest neighbor positions, a rigorous outlier removal scheme, and an iterative deformation warping scheme. We test this technique for its accuracy and computational efficacy using synthetically and experimentally generated 3D particle images, including non-affine deformation fields in soft materials, complex fluid flows, and cell-generated deformations. We augment this algorithm with additional particle information (e.g., color, size, or shape) to further enhance tracking accuracy for high gradient and large displacement fields. These applications demonstrate that this versatile technique can rapidly track unprecedented numbers of particles to resolve large and complex motion fields in 2D and 3D images, particularly when spatial correlations exist.

NMF-Based Image Quality Assessment Using Extreme Learning Machine.

PubMed

Wang, Shuigen; Deng, Chenwei; Lin, Weisi; Huang, Guang-Bin; Zhao, Baojun

2017-01-01

Numerous state-of-the-art perceptual image quality assessment (IQA) algorithms share a common two-stage process: distortion description followed by distortion effects pooling. As for the first stage, the distortion descriptors or measurements are expected to be effective representatives of human visual variations, while the second stage should well express the relationship among quality descriptors and the perceptual visual quality. However, most of the existing quality descriptors (e.g., luminance, contrast, and gradient) do not seem to be consistent with human perception, and the effects pooling is often done in ad-hoc ways. In this paper, we propose a novel full-reference IQA metric. It applies non-negative matrix factorization (NMF) to measure image degradations by making use of the parts-based representation of NMF. On the other hand, a new machine learning technique [extreme learning machine (ELM)] is employed to address the limitations of the existing pooling techniques. Compared with neural networks and support vector regression, ELM can achieve higher learning accuracy with faster learning speed. Extensive experimental results demonstrate that the proposed metric has better performance and lower computational complexity in comparison with the relevant state-of-the-art approaches.

Contour sensitive saliency and depth application in image retargeting

NASA Astrophysics Data System (ADS)

Lu, Hongju; Yue, Pengfei; Zhao, Yanhui; Liu, Rui; Fu, Yuanbin; Zheng, Yuanjie; Cui, Jia

2018-04-01

Image retargeting technique requires important information preservation and less edge distortion during increasing/decreasing image size. The major existed content-aware methods perform well. However, there are two problems should be improved: the slight distortion appeared at the object edges and the structure distortion in the nonsalient area. According to psychological theories, people evaluate image quality based on multi-level judgments and comparison between different areas, both image content and image structure. The paper proposes a new standard: the structure preserving in non-salient area. After observation and image analysis, blur (slight blur) is generally existed at the edge of objects. The blur feature is used to estimate the depth cue, named blur depth descriptor. It can be used in the process of saliency computation for balanced image retargeting result. In order to keep the structure information in nonsalient area, the salient edge map is presented in Seam Carving process, instead of field-based saliency computation. The derivative saliency from x- and y-direction can avoid the redundant energy seam around salient objects causing structure distortion. After the comparison experiments between classical approaches and ours, the feasibility of our algorithm is proved.

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes.

PubMed

Xie, Dong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

2017-01-01

In a general (k, n) scalable secret image sharing (SSIS) scheme, the secret image is shared by n participants and any k or more than k participants have the ability to reconstruct it. The scalability means that the amount of information in the reconstructed image scales in proportion to the number of the participants. In most existing SSIS schemes, the size of each image shadow is relatively large and the dealer does not has a flexible control strategy to adjust it to meet the demand of differen applications. Besides, almost all existing SSIS schemes are not applicable under noise circumstances. To address these deficiencies, in this paper we present a novel SSIS scheme based on a brand-new technique, called compressed sensing, which has been widely used in many fields such as image processing, wireless communication and medical imaging. Our scheme has the property of flexibility, which means that the dealer can achieve a compromise between the size of each shadow and the quality of the reconstructed image. In addition, our scheme has many other advantages, including smooth scalability, noise-resilient capability, and high security. The experimental results and the comparison with similar works demonstrate the feasibility and superiority of our scheme.

Empirical gradient threshold technique for automated segmentation across image modalities and cell lines.

PubMed

Chalfoun, J; Majurski, M; Peskin, A; Breen, C; Bajcsy, P; Brady, M

2015-10-01

New microscopy technologies are enabling image acquisition of terabyte-sized data sets consisting of hundreds of thousands of images. In order to retrieve and analyze the biological information in these large data sets, segmentation is needed to detect the regions containing cells or cell colonies. Our work with hundreds of large images (each 21,000×21,000 pixels) requires a segmentation method that: (1) yields high segmentation accuracy, (2) is applicable to multiple cell lines with various densities of cells and cell colonies, and several imaging modalities, (3) can process large data sets in a timely manner, (4) has a low memory footprint and (5) has a small number of user-set parameters that do not require adjustment during the segmentation of large image sets. None of the currently available segmentation methods meet all these requirements. Segmentation based on image gradient thresholding is fast and has a low memory footprint. However, existing techniques that automate the selection of the gradient image threshold do not work across image modalities, multiple cell lines, and a wide range of foreground/background densities (requirement 2) and all failed the requirement for robust parameters that do not require re-adjustment with time (requirement 5). We present a novel and empirically derived image gradient threshold selection method for separating foreground and background pixels in an image that meets all the requirements listed above. We quantify the difference between our approach and existing ones in terms of accuracy, execution speed, memory usage and number of adjustable parameters on a reference data set. This reference data set consists of 501 validation images with manually determined segmentations and image sizes ranging from 0.36 Megapixels to 850 Megapixels. It includes four different cell lines and two image modalities: phase contrast and fluorescent. Our new technique, called Empirical Gradient Threshold (EGT), is derived from this reference data set with a 10-fold cross-validation method. EGT segments cells or colonies with resulting Dice accuracy index measurements above 0.92 for all cross-validation data sets. EGT results has also been visually verified on a much larger data set that includes bright field and Differential Interference Contrast (DIC) images, 16 cell lines and 61 time-sequence data sets, for a total of 17,479 images. This method is implemented as an open-source plugin to ImageJ as well as a standalone executable that can be downloaded from the following link: https://isg.nist.gov/. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

Comparison of competing segmentation standards for X-ray computed topographic imaging using Lattice Boltzmann techniques

NASA Astrophysics Data System (ADS)

Larsen, J. D.; Schaap, M. G.

2013-12-01

Recent advances in computing technology and experimental techniques have made it possible to observe and characterize fluid dynamics at the micro-scale. Many computational methods exist that can adequately simulate fluid flow in porous media. Lattice Boltzmann methods provide the distinct advantage of tracking particles at the microscopic level and returning macroscopic observations. While experimental methods can accurately measure macroscopic fluid dynamics, computational efforts can be used to predict and gain insight into fluid dynamics by utilizing thin sections or computed micro-tomography (CMT) images of core sections. Although substantial effort have been made to advance non-invasive imaging methods such as CMT, fluid dynamics simulations, and microscale analysis, a true three dimensional image segmentation technique has not been developed until recently. Many competing segmentation techniques are utilized in industry and research settings with varying results. In this study lattice Boltzmann method is used to simulate stokes flow in a macroporous soil column. Two dimensional CMT images were used to reconstruct a three dimensional representation of the original sample. Six competing segmentation standards were used to binarize the CMT volumes which provide distinction between solid phase and pore space. The permeability of the reconstructed samples was calculated, with Darcy's Law, from lattice Boltzmann simulations of fluid flow in the samples. We compare simulated permeability from differing segmentation algorithms to experimental findings.

SU-E-J-02: 4D Digital Tomosynthesis Based On Algebraic Image Reconstruction and Total-Variation Minimization for the Improvement of Image Quality

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

Kim, D; Kang, S; Kim, T

2014-06-01

Purpose: In this paper, we implemented the four-dimensional (4D) digital tomosynthesis (DTS) imaging based on algebraic image reconstruction technique and total-variation minimization method in order to compensate the undersampled projection data and improve the image quality. Methods: The projection data were acquired as supposed the cone-beam computed tomography system in linear accelerator by the Monte Carlo simulation and the in-house 4D digital phantom generation program. We performed 4D DTS based upon simultaneous algebraic reconstruction technique (SART) among the iterative image reconstruction technique and total-variation minimization method (TVMM). To verify the effectiveness of this reconstruction algorithm, we performed systematic simulation studiesmore » to investigate the imaging performance. Results: The 4D DTS algorithm based upon the SART and TVMM seems to give better results than that based upon the existing method, or filtered-backprojection. Conclusion: The advanced image reconstruction algorithm for the 4D DTS would be useful to validate each intra-fraction motion during radiation therapy. In addition, it will be possible to give advantage to real-time imaging for the adaptive radiation therapy. This research was supported by Leading Foreign Research Institute Recruitment Program (Grant No.2009-00420) and Basic Atomic Energy Research Institute (BAERI); (Grant No. 2009-0078390) through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT and Future Planning (MSIP)« less

Dental magnetic resonance imaging: making the invisible visible.

PubMed

Idiyatullin, Djaudat; Corum, Curt; Moeller, Steen; Prasad, Hari S; Garwood, Michael; Nixdorf, Donald R

2011-06-01

Clinical dentistry is in need of noninvasive and accurate diagnostic methods to better evaluate dental pathosis. The purpose of this work was to assess the feasibility of a recently developed magnetic resonance imaging (MRI) technique, called SWeep Imaging with Fourier Transform (SWIFT), to visualize dental tissues. Three in vitro teeth, representing a limited range of clinical conditions of interest, imaged using a 9.4T system with scanning times ranging from 100 seconds to 25 minutes. In vivo imaging of a subject was performed using a 4T system with a 10-minute scanning time. SWIFT images were compared with traditional two-dimensional radiographs, three-dimensional cone-beam computed tomography (CBCT) scanning, gradient-echo MRI technique, and histological sections. A resolution of 100 μm was obtained from in vitro teeth. SWIFT also identified the presence and extent of dental caries and fine structures of the teeth, including cracks and accessory canals, which are not visible with existing clinical radiography techniques. Intraoral positioning of the radiofrequency coil produced initial images of multiple adjacent teeth at a resolution of 400 μm. SWIFT MRI offers simultaneous three-dimensional hard- and soft-tissue imaging of teeth without the use of ionizing radiation. Furthermore, it has the potential to image minute dental structures within clinically relevant scanning times. This technology has implications for endodontists because it offers a potential method to longitudinally evaluate teeth where pulp and root structures have been regenerated. Copyright © 2011 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Improved JPEG anti-forensics with better image visual quality and forensic undetectability.

PubMed

Singh, Gurinder; Singh, Kulbir

2017-08-01

There is an immediate need to validate the authenticity of digital images due to the availability of powerful image processing tools that can easily manipulate the digital image information without leaving any traces. The digital image forensics most often employs the tampering detectors based on JPEG compression. Therefore, to evaluate the competency of the JPEG forensic detectors, an anti-forensic technique is required. In this paper, two improved JPEG anti-forensic techniques are proposed to remove the blocking artifacts left by the JPEG compression in both spatial and DCT domain. In the proposed framework, the grainy noise left by the perceptual histogram smoothing in DCT domain can be reduced significantly by applying the proposed de-noising operation. Two types of denoising algorithms are proposed, one is based on the constrained minimization problem of total variation of energy and other on the normalized weighted function. Subsequently, an improved TV based deblocking operation is proposed to eliminate the blocking artifacts in the spatial domain. Then, a decalibration operation is applied to bring the processed image statistics back to its standard position. The experimental results show that the proposed anti-forensic approaches outperform the existing state-of-the-art techniques in achieving enhanced tradeoff between image visual quality and forensic undetectability, but with high computational cost. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Viewing zone duplication of multi-projection 3D display system using uniaxial crystal.

PubMed

Lee, Chang-Kun; Park, Soon-Gi; Moon, Seokil; Lee, Byoungho

2016-04-18

We propose a novel multiplexing technique for increasing the viewing zone of a multi-view based multi-projection 3D display system by employing double refraction in uniaxial crystal. When linearly polarized images from projector pass through the uniaxial crystal, two possible optical paths exist according to the polarization states of image. Therefore, the optical paths of the image could be changed, and the viewing zone is shifted in a lateral direction. The polarization modulation of the image from a single projection unit enables us to generate two viewing zones at different positions. For realizing full-color images at each viewing zone, a polarization-based temporal multiplexing technique is adopted with a conventional polarization switching device of liquid crystal (LC) display. Through experiments, a prototype of a ten-view multi-projection 3D display system presenting full-colored view images is implemented by combining five laser scanning projectors, an optically clear calcite (CaCO₃) crystal, and an LC polarization rotator. For each time sequence of temporal multiplexing, the luminance distribution of the proposed system is measured and analyzed.

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis.

PubMed

Downie, H F; Adu, M O; Schmidt, S; Otten, W; Dupuy, L X; White, P J; Valentine, T A

2015-07-01

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions. © 2014 John Wiley & Sons Ltd.

Identification of Low Coronal Sources of “Stealth” Coronal Mass Ejections Using New Image Processing Techniques

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

Alzate, Nathalia; Morgan, Huw, E-mail: naa19@aber.ac.uk

Coronal mass ejections (CMEs) are generally associated with low coronal signatures (LCSs), such as flares, filament eruptions, extreme ultraviolet (EUV) waves, or jets. A number of recent studies have reported the existence of stealth CMEs as events without LCSs, possibly due to observational limitations. Our study focuses on a set of 40 stealth CMEs identified from a study by D’Huys et al. New image processing techniques are applied to high-cadence, multi-instrument sets of images spanning the onset and propagation time of each of these CMEs to search for possible LCSs. Twenty-three of these events are identified as small, low-mass, unstructuredmore » blobs or puffs, often occurring in the aftermath of a large CME, but associated with LCSs such as small flares, jets, or filament eruptions. Of the larger CMEs, seven are associated with jets and eight with filament eruptions. Several of these filament eruptions are different from the standard model of an erupting filament/flux tube in that they are eruptions of large, faint flux tubes that seem to exist at large heights for a long time prior to their slow eruption. For two of these events, we see an eruption in Large Angle Spectrometric Coronagraph C2 images and the consequent changes at the bottom edge of the eruption in EUV images. All 40 events in our study are associated with some form of LCS. We conclude that stealth CMEs arise from observational and processing limitations.« less

A Software Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Donald J.; Martin, Richard E.; Seebo, Jeff P.; Trinh, Long B.; Walker, James L.; Winfree, William P.

2007-01-01

Ultrasonic, microwave, and terahertz nondestructive evaluation imaging systems generally require the acquisition of waveforms at each scan point to form an image. For such systems, signal and image processing methods are commonly needed to extract information from the waves and improve resolution of, and highlight, defects in the image. Since some similarity exists for all waveform-based NDE methods, it would seem a common software platform containing multiple signal and image processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. This presentation describes NASA Glenn Research Center's approach in developing a common software platform for processing waveform-based NDE signals and images. This platform is currently in use at NASA Glenn and at Lockheed Martin Michoud Assembly Facility for processing of pulsed terahertz and ultrasonic data. Highlights of the software operation will be given. A case study will be shown for use with terahertz data. The authors also request scientists and engineers who are interested in sharing customized signal and image processing algorithms to contribute to this effort by letting the authors code up and include these algorithms in future releases.

Mapping the local organization of cell membranes using excitation-polarization-resolved confocal fluorescence microscopy.

PubMed

Kress, Alla; Wang, Xiao; Ranchon, Hubert; Savatier, Julien; Rigneault, Hervé; Ferrand, Patrick; Brasselet, Sophie

2013-07-02

Fluorescence anisotropy and linear dichroism imaging have been widely used for imaging biomolecular orientational distributions in protein aggregates, fibrillar structures of cells, and cell membranes. However, these techniques do not give access to complete orientational order information in a whole image, because their use is limited to parts of the sample where the average orientation of molecules is known a priori. Fluorescence anisotropy is also highly sensitive to depolarization mechanisms such as those induced by fluorescence energy transfer. A fully excitation-polarization-resolved fluorescence microscopy imaging that relies on the use of a tunable incident polarization and a nonpolarized detection is able to circumvent these limitations. We have developed such a technique in confocal epifluorescence microscopy, giving access to new regions of study in the complex and heterogeneous molecular organization of cell membranes. Using this technique, we demonstrate morphological changes at the subdiffraction scale in labeled COS-7 cell membranes whose cytoskeleton is perturbed. Molecular orientational order is also seen to be affected by cholesterol depletion, reflecting the strong interplay between lipid-packing regions and their nearby cytoskeleton. This noninvasive optical technique can reveal local organization in cell membranes when used as a complement to existing methods such as generalized polarization. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Dynamic two-photon imaging of the immune response to Toxoplasma gondii infection.

PubMed

Luu, L; Coombes, J L

2015-03-01

Toxoplasma gondii is a highly successful parasite that can manipulate host immune responses to optimize its persistence and spread. As a result, a highly complex relationship exists between T. gondii and the immune system of the host. Advances in imaging techniques, and in particular, the application of two-photon microscopy to mouse infection models, have made it possible to directly visualize interactions between parasites and the host immune system as they occur in living tissues. Here, we will discuss how dynamic imaging techniques have provided unexpected new insight into (i) how immune responses are dynamically regulated by cells and structures in the local tissue environment, (ii) how protective responses to T. gondii are generated and (iii) how the parasite exploits the immune system for its own benefit. © 2014 John Wiley & Sons Ltd.

Image-guidance enables new methods for customizing cochlear implant stimulation strategies

PubMed Central

Noble, Jack H.; Labadie, Robert F.; Gifford, René H.; Dawant, Benoit M.

2013-01-01

Over the last 20 years, cochlear implants (CIs) have become what is arguably the most successful neural prosthesis to date. Despite this success, a significant number of CI recipients experience marginal hearing restoration, and, even among the best performers, restoration to normal fidelity is rare. In this article, we present image processing techniques that can be used to detect, for the first time, the positions of implanted CI electrodes and the nerves they stimulate for individual CI users. These techniques permit development of new, customized CI stimulation strategies. We present one such strategy and show that it leads to significant hearing improvement in an experiment conducted with 11 CI recipients. These results indicate that image-guidance can be used to improve hearing outcomes for many existing CI recipients without requiring additional surgical procedures. PMID:23529109

Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms

PubMed Central

Masood, Ammara; Al-Jumaily, Adel Ali

2013-01-01

Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique's performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided. PMID:24575126

Sparse 4D TomoSAR imaging in the presence of non-linear deformation

NASA Astrophysics Data System (ADS)

Khwaja, Ahmed Shaharyar; ćetin, Müjdat

2018-04-01

In this paper, we present a sparse four-dimensional tomographic synthetic aperture radar (4D TomoSAR) imaging scheme that can estimate elevation and linear as well as non-linear seasonal deformation rates of scatterers using the interferometric phase. Unlike existing sparse processing techniques that use fixed dictionaries based on a linear deformation model, we use a variable dictionary for the non-linear deformation in the form of seasonal sinusoidal deformation, in addition to the fixed dictionary for the linear deformation. We estimate the amplitude of the sinusoidal deformation using an optimization method and create the variable dictionary using the estimated amplitude. We show preliminary results using simulated data that demonstrate the soundness of our proposed technique for sparse 4D TomoSAR imaging in the presence of non-linear deformation.

Progress in terahertz nondestructive testing: A review

NASA Astrophysics Data System (ADS)

Zhong, Shuncong

2018-05-01

Terahertz (THz) waves, whose frequencies range between microwave and infrared, are part of the electromagnetic spectrum. A gap exists in THz literature because investigating THz waves is difficult due to the weak characteristics of the waves and the lack of suitable THz sources and detectors. Recently, THz nondestructive testing (NDT) technology has become an interesting topic. This review outlines several typical THz devices and systems and engineering applications of THz NDT techniques in composite materials, thermal barrier coatings, car paint films, marine protective coatings, and pharmaceutical tablet coatings. THz imaging has higher resolution but lower penetration than ultrasound imaging. This review presents the significance and advantages provided by the emerging THz NDT technique.

Estimating Number of People Using Calibrated Monocular Camera Based on Geometrical Analysis of Surface Area

NASA Astrophysics Data System (ADS)

Arai, Hiroyuki; Miyagawa, Isao; Koike, Hideki; Haseyama, Miki

We propose a novel technique for estimating the number of people in a video sequence; it has the advantages of being stable even in crowded situations and needing no ground-truth data. By analyzing the geometrical relationships between image pixels and their intersection volumes in the real world quantitatively, a foreground image directly indicates the number of people. Because foreground detection is possible even in crowded situations, the proposed method can be applied in such situations. Moreover, it can estimate the number of people in an a priori manner, so it needs no ground-truth data unlike existing feature-based estimation techniques. Experiments show the validity of the proposed method.

Adjustable lossless image compression based on a natural splitting of an image into drawing, shading, and fine-grained components

NASA Technical Reports Server (NTRS)

Novik, Dmitry A.; Tilton, James C.

1993-01-01

The compression, or efficient coding, of single band or multispectral still images is becoming an increasingly important topic. While lossy compression approaches can produce reconstructions that are visually close to the original, many scientific and engineering applications require exact (lossless) reconstructions. However, the most popular and efficient lossless compression techniques do not fully exploit the two-dimensional structural links existing in the image data. We describe here a general approach to lossless data compression that effectively exploits two-dimensional structural links of any length. After describing in detail two main variants on this scheme, we discuss experimental results.

Automation is an Effective Way to Improve Quality of Verification (Calibration) of Measuring Instruments

NASA Astrophysics Data System (ADS)

Golobokov, M.; Danilevich, S.

2018-04-01

In order to assess calibration reliability and automate such assessment, procedures for data collection and simulation study of thermal imager calibration procedure have been elaborated. The existing calibration techniques do not always provide high reliability. A new method for analyzing the existing calibration techniques and developing new efficient ones has been suggested and tested. A type of software has been studied that allows generating instrument calibration reports automatically, monitoring their proper configuration, processing measurement results and assessing instrument validity. The use of such software allows reducing man-hours spent on finalization of calibration data 2 to 5 times and eliminating a whole set of typical operator errors.

Fast Fourier transform-based Retinex and alpha-rooting color image enhancement

NASA Astrophysics Data System (ADS)

Grigoryan, Artyom M.; Agaian, Sos S.; Gonzales, Analysa M.

2015-05-01

Efficiency in terms of both accuracy and speed is highly important in any system, especially when it comes to image processing. The purpose of this paper is to improve an existing implementation of multi-scale retinex (MSR) by utilizing the fast Fourier transforms (FFT) within the illumination estimation step of the algorithm to improve the speed at which Gaussian blurring filters were applied to the original input image. In addition, alpha-rooting can be used as a separate technique to achieve a sharper image in order to fuse its results with those of the retinex algorithm for the sake of achieving the best image possible as shown by the values of the considered color image enhancement measure (EMEC).

GPU computing in medical physics: a review.

PubMed

Pratx, Guillem; Xing, Lei

2011-05-01

The graphics processing unit (GPU) has emerged as a competitive platform for computing massively parallel problems. Many computing applications in medical physics can be formulated as data-parallel tasks that exploit the capabilities of the GPU for reducing processing times. The authors review the basic principles of GPU computing as well as the main performance optimization techniques, and survey existing applications in three areas of medical physics, namely image reconstruction, dose calculation and treatment plan optimization, and image processing.

Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies.

PubMed

Koch, Lisa M; Rajchl, Martin; Bai, Wenjia; Baumgartner, Christian F; Tong, Tong; Passerat-Palmbach, Jonathan; Aljabar, Paul; Rueckert, Daniel

2017-08-22

Multi-atlas segmentation is a widely used tool in medical image analysis, providing robust and accurate results by learning from annotated atlas datasets. However, the availability of fully annotated atlas images for training is limited due to the time required for the labelling task. Segmentation methods requiring only a proportion of each atlas image to be labelled could therefore reduce the workload on expert raters tasked with annotating atlas images. To address this issue, we first re-examine the labelling problem common in many existing approaches and formulate its solution in terms of a Markov Random Field energy minimisation problem on a graph connecting atlases and the target image. This provides a unifying framework for multi-atlas segmentation. We then show how modifications in the graph configuration of the proposed framework enable the use of partially annotated atlas images and investigate different partial annotation strategies. The proposed method was evaluated on two Magnetic Resonance Imaging (MRI) datasets for hippocampal and cardiac segmentation. Experiments were performed aimed at (1) recreating existing segmentation techniques with the proposed framework and (2) demonstrating the potential of employing sparsely annotated atlas data for multi-atlas segmentation.

JIGSAW: Joint Inhomogeneity estimation via Global Segment Assembly for Water-fat separation.

PubMed

Lu, Wenmiao; Lu, Yi

2011-07-01

Water-fat separation in magnetic resonance imaging (MRI) is of great clinical importance, and the key to uniform water-fat separation lies in field map estimation. This work deals with three-point field map estimation, in which water and fat are modelled as two single-peak spectral lines, and field inhomogeneities shift the spectrum by an unknown amount. Due to the simplified spectrum modelling, there exists inherent ambiguity in forming field maps from multiple locally feasible field map values at each pixel. To resolve such ambiguity, spatial smoothness of field maps has been incorporated as a constraint of an optimization problem. However, there are two issues: the optimization problem is computationally intractable and even when it is solved exactly, it does not always separate water and fat images. Hence, robust field map estimation remains challenging in many clinically important imaging scenarios. This paper proposes a novel field map estimation technique called JIGSAW. It extends a loopy belief propagation (BP) algorithm to obtain an approximate solution to the optimization problem. The solution produces locally smooth segments and avoids error propagation associated with greedy methods. The locally smooth segments are then assembled into a globally consistent field map by exploiting the periodicity of the feasible field map values. In vivo results demonstrate that JIGSAW outperforms existing techniques and produces correct water-fat separation in challenging imaging scenarios.

a Novel Ihs-Ga Fusion Method Based on Enhancement Vegetated Area

NASA Astrophysics Data System (ADS)

Niazi, S.; Mokhtarzade, M.; Saeedzadeh, F.

2015-12-01

Pan sharpening methods aim to produce a more informative image containing the positive aspects of both source images. However, the pan sharpening process usually introduces some spectral and spatial distortions in the resulting fused image. The amount of these distortions varies highly depending on the pan sharpening technique as well as the type of data. Among the existing pan sharpening methods, the Intensity-Hue-Saturation (IHS) technique is the most widely used for its efficiency and high spatial resolution. When the IHS method is used for IKONOS or QuickBird imagery, there is a significant color distortion which is mainly due to the wavelengths range of the panchromatic image. Regarding the fact that in the green vegetated regions panchromatic gray values are much larger than the gray values of intensity image. A novel method is proposed which spatially adjusts the intensity image in vegetated areas. To do so the normalized difference vegetation index (NDVI) is used to identify vegetation areas where the green band is enhanced according to the red and NIR bands. In this way an intensity image is obtained in which the gray values are comparable to the panchromatic image. Beside the genetic optimization algorithm is used to find the optimum weight parameters in order to gain the best intensity image. Visual and statistical analysis proved the efficiency of the proposed method as it significantly improved the fusion quality in comparison to conventional IHS technique. The accuracy of the proposed pan sharpening technique was also evaluated in terms of different spatial and spectral metrics. In this study, 7 metrics (Correlation Coefficient, ERGAS, RASE, RMSE, SAM, SID and Spatial Coefficient) have been used in order to determine the quality of the pan-sharpened images. Experiments were conducted on two different data sets obtained by two different imaging sensors, IKONOS and QuickBird. The result of this showed that the evaluation metrics are more promising for our fused image in comparison to other pan sharpening methods.

Microwave imaging of spinning object using orbital angular momentum

NASA Astrophysics Data System (ADS)

Liu, Kang; Li, Xiang; Gao, Yue; Wang, Hongqiang; Cheng, Yongqiang

2017-09-01

The linear Doppler shift used for the detection of a spinning object becomes significantly weakened when the line of sight (LOS) is perpendicular to the object, which will result in the failure of detection. In this paper, a new detection and imaging technique for spinning objects is developed. The rotational Doppler phenomenon is observed by using the microwave carrying orbital angular momentum (OAM). To converge the radiation energy on the area where objects might exist, the generation method of OAM beams is proposed based on the frequency diversity principle, and the imaging model is derived accordingly. The detection method of the rotational Doppler shift and the imaging approach of the azimuthal profiles are proposed, which are verified by proof-of-concept experiments. Simulation and experimental results demonstrate that OAM beams can still be used to obtain the azimuthal profiles of spinning objects even when the LOS is perpendicular to the object. This work remedies the insufficiency in existing microwave sensing technology and offers a new solution to the object identification problem.

Three-dimensional spectral-spatial EPR imaging of free radicals in the heart: a technique for imaging tissue metabolism and oxygenation.

PubMed Central

Kuppusamy, P; Chzhan, M; Vij, K; Shteynbuk, M; Lefer, D J; Giannella, E; Zweier, J L

1994-01-01

It has been hypothesized that free radical metabolism and oxygenation in living organs and tissues such as the heart may vary over the spatially defined tissue structure. In an effort to study these spatially defined differences, we have developed electron paramagnetic resonance imaging instrumentation enabling the performance of three-dimensional spectral-spatial images of free radicals infused into the heart and large vessels. Using this instrumentation, high-quality three-dimensional spectral-spatial images of isolated perfused rat hearts and rabbit aortas are obtained. In the isolated aorta, it is shown that spatially and spectrally accurate images of the vessel lumen and wall could be obtained in this living vascular tissue. In the isolated rat heart, imaging experiments were performed to determine the kinetics of radical clearance at different spatial locations within the heart during myocardial ischemia. The kinetic data show the existence of regional and transmural differences in myocardial free radical clearance. It is further demonstrated that EPR imaging can be used to noninvasively measure spatially localized oxygen concentrations in the heart. Thus, the technique of spectral-spatial EPR imaging is shown to be a powerful tool in providing spatial information regarding the free radical distribution, metabolism, and tissue oxygenation in living biological organs and tissues. Images PMID:8159757

INVITED REVIEW--IMAGE REGISTRATION IN VETERINARY RADIATION ONCOLOGY: INDICATIONS, IMPLICATIONS, AND FUTURE ADVANCES.

PubMed

Feng, Yang; Lawrence, Jessica; Cheng, Kun; Montgomery, Dean; Forrest, Lisa; Mclaren, Duncan B; McLaughlin, Stephen; Argyle, David J; Nailon, William H

2016-01-01

The field of veterinary radiation therapy (RT) has gained substantial momentum in recent decades with significant advances in conformal treatment planning, image-guided radiation therapy (IGRT), and intensity-modulated (IMRT) techniques. At the root of these advancements lie improvements in tumor imaging, image alignment (registration), target volume delineation, and identification of critical structures. Image registration has been widely used to combine information from multimodality images such as computerized tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) to improve the accuracy of radiation delivery and reliably identify tumor-bearing areas. Many different techniques have been applied in image registration. This review provides an overview of medical image registration in RT and its applications in veterinary oncology. A summary of the most commonly used approaches in human and veterinary medicine is presented along with their current use in IGRT and adaptive radiation therapy (ART). It is important to realize that registration does not guarantee that target volumes, such as the gross tumor volume (GTV), are correctly identified on the image being registered, as limitations unique to registration algorithms exist. Research involving novel registration frameworks for automatic segmentation of tumor volumes is ongoing and comparative oncology programs offer a unique opportunity to test the efficacy of proposed algorithms. © 2016 American College of Veterinary Radiology.

Adaptive multifocus image fusion using block compressed sensing with smoothed projected Landweber integration in the wavelet domain.

PubMed

V S, Unni; Mishra, Deepak; Subrahmanyam, G R K S

2016-12-01

The need for image fusion in current image processing systems is increasing mainly due to the increased number and variety of image acquisition techniques. Image fusion is the process of combining substantial information from several sensors using mathematical techniques in order to create a single composite image that will be more comprehensive and thus more useful for a human operator or other computer vision tasks. This paper presents a new approach to multifocus image fusion based on sparse signal representation. Block-based compressive sensing integrated with a projection-driven compressive sensing (CS) recovery that encourages sparsity in the wavelet domain is used as a method to get the focused image from a set of out-of-focus images. Compression is achieved during the image acquisition process using a block compressive sensing method. An adaptive thresholding technique within the smoothed projected Landweber recovery process reconstructs high-resolution focused images from low-dimensional CS measurements of out-of-focus images. Discrete wavelet transform and dual-tree complex wavelet transform are used as the sparsifying basis for the proposed fusion. The main finding lies in the fact that sparsification enables a better selection of the fusion coefficients and hence better fusion. A Laplacian mixture model fit is done in the wavelet domain and estimation of the probability density function (pdf) parameters by expectation maximization leads us to the proper selection of the coefficients of the fused image. Using the proposed method compared with the fusion scheme without employing the projected Landweber (PL) scheme and the other existing CS-based fusion approaches, it is observed that with fewer samples itself, the proposed method outperforms other approaches.

Image-guided optical measurement of blood oxygen saturation within capillary vessels (Conference Presentation)

NASA Astrophysics Data System (ADS)

Akons, Kfir; Zeidan, Adel; Yeheskely-Hayon, Daniella; Minai, Limor; Yelin, Dvir

2016-03-01

Values of blood oxygenation levels are useful for assessing heart and lung conditions, and are frequently monitored during routine patient care. Independent measurement of the oxygen saturation in capillary blood, which is significantly different from that of arterial blood, is important for diagnosing tissue hypoxia and for increasing the accuracy of existing techniques that measure arterial oxygen saturation. Here, we developed a simple, non-invasive technique for measuring the reflected spectra from individual capillary vessels within a human lip, allowing local measurement of the blood oxygen saturation. The optical setup includes a spatially incoherent broadband light that was focused onto a specific vessel below the lip surface. Backscattered light was imaged by a camera for identifying a target vessel and pointing the illumination beam to its cross section. Scattered light from the vessel was then collected by a single-mode fiber and analyzed by a fast spectrometer. Spectra acquired from small capillary vessels within a volunteer lip showed the characteristic oxyhemoglobin absorption bands in real time and with a high signal-to-noise ratio. Measuring capillary oxygen saturation using this technique would potentially be more accurate compared to existing pulse oximetry techniques due to its insensitivity to the patient's skin color, pulse rate, motion, and medical condition. It could be used as a standalone endoscopic technique for measuring tissue hypoxia or in conjunction with conventional pulse oximetry for a more accurate measurement of oxygen transport in the body.

[Aging explosive detection using terahertz time-domain spectroscopy].

PubMed

Meng, Kun; Li, Ze-ren; Liu, Qiao

2011-05-01

Detecting the aging situation of stock explosive is essentially meaningful to the research on the capability, security and stability of explosive. Existing aging explosive detection techniques, such as scan microscope technique, Fourier transfer infrared spectrum technique, gas chromatogram mass spectrum technique and so on, are either not able to differentiate whether the explosive is aging or not, or not able to image the structure change of the molecule. In the present paper, using the density functional theory (DFT), the absorb spectrum changes after the explosive aging were calculated, from which we can clearly find the difference of spectrum between explosive molecule and aging ones in the terahertz band. The terahertz time-domain spectrum (THz-TDS) system as well as its frequency spectrum resolution and measured range are analyzed. Combined with the existing experimental results and the essential characters of the terahertz wave, the application of THz-TDS technique to the detection of aging explosive was demonstrated from the aspects of feasibility, veracity and practicability. On the base of that, the authors advance the new method of aging explosive detection using the terahertz time-domain spectrum technique.

Characterizing the Siple Coast Ice Stream System using Satellite Images, Improved Topography, and Integrated Aerogeophysical Measurements

NASA Technical Reports Server (NTRS)

Scambos, Ted

2003-01-01

A technique for improving elevation maps of the polar ice sheets has been developed using AVHRR images. The technique is based on 'photoclinometry' or 'shape from shading', a technique used in the past for mapping planetary surfaces where little elevation information was available. The fundamental idea behind photoclinometry is using the brightness of imaged areas to infer their surface slope in the sun-illuminated direction. Our version of the method relies on a calibration of the images based on an existing lower-resolution digital elevation model (DEM), and then using the images to improve the input DEM resolution to the scale of the image data. Most current DEMs covering the ice sheets are based on Radar altimetry data, and have an inherent resolution of 10 to 25 km at best - although the grid scale of the DEM is often finer. These DEMs are highly accurate (to less than 1 meter); but they report the mean elevation of a broad area, thus erasing smaller features of glaciological interest. AVHRR image data, when accurately geolocated and calibrated, provides surface slope measurements (based on the pixel brightness under known lighting conditions) every approximately 1.1 km. The limitations of the technique are noisiness in the image data, small variations in the albedo of the snow surface, and the integration technique used to create an elevation field from the image-derived slopes. Our study applied the technique to several ice sheet areas having some elevation data; Greenland, the Amery Ice Shelf, the Institute Ice Stream, and the Siple Coast. For the latter, the input data set was laser-altimetry data collected under NSF's SOAR Facility (Support Office for Aerogeophysical Research) over the onset area of the Siple Coast. Over the course of the grant, the technique was greatly improved and modified, significantly improving accuracy and reducing noise from the images. Several publications resulted from the work, and a follow-on proposal to NASA has been submitted to apply the same method to MODIS data using ICESat and other elevation input information. This follow-on grant will explore two applications that are facilitated by the improved surface morphology characterizations of the ice sheets: accumulation and temperature variations near small undulations in the ice.

Noise estimation for hyperspectral imagery using spectral unmixing and synthesis

NASA Astrophysics Data System (ADS)

Demirkesen, C.; Leloglu, Ugur M.

2014-10-01

Most hyperspectral image (HSI) processing algorithms assume a signal to noise ratio model in their formulation which makes them dependent on accurate noise estimation. Many techniques have been proposed to estimate the noise. A very comprehensive comparative study on the subject is done by Gao et al. [1]. In a nut-shell, most techniques are based on the idea of calculating standard deviation from assumed-to-be homogenous regions in the image. Some of these algorithms work on a regular grid parameterized with a window size w, while others make use of image segmentation in order to obtain homogenous regions. This study focuses not only to the statistics of the noise but to the estimation of the noise itself. A noise estimation technique motivated from a recent HSI de-noising approach [2] is proposed in this study. The denoising algorithm is based on estimation of the end-members and their fractional abundances using non-negative least squares method. The end-members are extracted using the well-known simplex volume optimization technique called NFINDR after manual selection of number of end-members and the image is reconstructed using the estimated endmembers and abundances. Actually, image de-noising and noise estimation are two sides of the same coin: Once we denoise an image, we can estimate the noise by calculating the difference of the de-noised image and the original noisy image. In this study, the noise is estimated as described above. To assess the accuracy of this method, the methodology in [1] is followed, i.e., synthetic images are created by mixing end-member spectra and noise. Since best performing method for noise estimation was spectral and spatial de-correlation (SSDC) originally proposed in [3], the proposed method is compared to SSDC. The results of the experiments conducted with synthetic HSIs suggest that the proposed noise estimation strategy outperforms the existing techniques in terms of mean and standard deviation of absolute error of the estimated noise. Finally, it is shown that the proposed technique demonstrated a robust behavior to the change of its single parameter, namely the number of end-members.

Misaligned Image Integration With Local Linear Model.

PubMed

Baba, Tatsuya; Matsuoka, Ryo; Shirai, Keiichiro; Okuda, Masahiro

2016-05-01

We present a new image integration technique for a flash and long-exposure image pair to capture a dark scene without incurring blurring or noisy artifacts. Most existing methods require well-aligned images for the integration, which is often a burdensome restriction in practical use. We address this issue by locally transferring the colors of the flash images using a small fraction of the corresponding pixels in the long-exposure images. We formulate the image integration as a convex optimization problem with the local linear model. The proposed method makes it possible to integrate the color of the long-exposure image with the detail of the flash image without causing any harmful effects to its contrast, where we do not need perfect alignment between the images by virtue of our new integration principle. We show that our method successfully outperforms the state of the art in the image integration and reference-based color transfer for challenging misaligned data sets.

Neuroimaging essentials in essential tremor: A systematic review

PubMed Central

Sharifi, Sarvi; Nederveen, Aart J.; Booij, Jan; van Rootselaar, Anne-Fleur

2014-01-01

Background Essential tremor is regarded to be a disease of the central nervous system. Neuroimaging is a rapidly growing field with potential benefits to both diagnostics and research. The exact role of imaging techniques with respect to essential tremor in research and clinical practice is not clear. A systematic review of the different imaging techniques in essential tremor is lacking in the literature. Methods We performed a systematic literature search combining the terms essential tremor and familial tremor with the following keywords: imaging, MRI, VBM, DWI, fMRI, PET and SPECT, both in abbreviated form as well as in full form. We summarize and discuss the quality and the external validity of each study and place the results in the context of existing knowledge regarding the pathophysiology of essential tremor. Results A total of 48 neuroimaging studies met our search criteria, roughly divided into 19 structural and 29 functional and metabolic studies. The quality of the studies varied, especially concerning inclusion criteria. Functional imaging studies indicated cerebellar hyperactivity during rest and during tremor. The studies also pointed to the involvement of the thalamus, the inferior olive and the red nucleus. Structural studies showed less consistent results. Discussion and conclusion Neuroimaging techniques in essential tremor give insight into the pathophysiology of essential tremor indicating the involvement of the cerebellum as the most consistent finding. GABAergic dysfunction might be a major premise in the pathophysiological hypotheses. Inconsistencies between studies can be partly explained by the inclusion of heterogeneous patient groups. Improvement of scientific research requires more stringent inclusion criteria and application of advanced analysis techniques. Also, the use of multimodal neuroimaging techniques is a promising development in movement disorders research. Currently, the role of imaging techniques in essential tremor in daily clinical practice is limited. PMID:25068111

Directional Histogram Ratio at Random Probes: A Local Thresholding Criterion for Capillary Images

PubMed Central

Lu, Na; Silva, Jharon; Gu, Yu; Gerber, Scott; Wu, Hulin; Gelbard, Harris; Dewhurst, Stephen; Miao, Hongyu

2013-01-01

With the development of micron-scale imaging techniques, capillaries can be conveniently visualized using methods such as two-photon and whole mount microscopy. However, the presence of background staining, leaky vessels and the diffusion of small fluorescent molecules can lead to significant complexity in image analysis and loss of information necessary to accurately quantify vascular metrics. One solution to this problem is the development of accurate thresholding algorithms that reliably distinguish blood vessels from surrounding tissue. Although various thresholding algorithms have been proposed, our results suggest that without appropriate pre- or post-processing, the existing approaches may fail to obtain satisfactory results for capillary images that include areas of contamination. In this study, we propose a novel local thresholding algorithm, called directional histogram ratio at random probes (DHR-RP). This method explicitly considers the geometric features of tube-like objects in conducting image binarization, and has a reliable performance in distinguishing small vessels from either clean or contaminated background. Experimental and simulation studies suggest that our DHR-RP algorithm is superior over existing thresholding methods. PMID:23525856

Watermarking-based protection of remote sensing images: requirements and possible solutions

NASA Astrophysics Data System (ADS)

Barni, Mauro; Bartolini, Franco; Cappellini, Vito; Magli, Enrico; Olmo, Gabriella

2001-12-01

Earth observation missions have recently attracted ag rowing interest form the scientific and industrial communities, mainly due to the large number of possible applications capable to exploit remotely sensed data and images. Along with the increase of market potential, the need arises for the protection of the image products from non-authorized use. Such a need is a very crucial one even because the Internet and other public/private networks have become preferred means of data exchange. A crucial issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. A question that obviously arises is whether the requirements imposed by remote sensing imagery are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: i) assessment of the requirements imposed by the characteristics of remotely sensed images on watermark-based copyright protection ii) analysis of the state-of-the-art, and performance evaluation of existing algorithms in terms of the requirements at the previous point.

Classification of rice grain varieties arranged in scattered and heap fashion using image processing

NASA Astrophysics Data System (ADS)

Bhat, Sudhanva; Panat, Sreedath; N, Arunachalam

2017-03-01

Inspection and classification of food grains is a manual process in many of the food grain processing industries. Automation of such a process is going to be beneficial for industries facing shortage of skilled workforce. Machine Vision techniques are some of the popular approaches for developing such automations. Most of the existing works on the topic deal with identification of the rice variety by analyzing images of well separated and isolated rice grains from which a lot of geometrical features can be extracted. This paper proposes techniques to estimate geometrical parameters from the images of scattered as well as heaped rice grains where the grain boundaries are not clearly identifiable. A methodology based on convexity is proposed to separate touching rice grains in the scattered rice grain images and get their geometrical parameters. And in case of heaped arrangement a Pixel-Distance Contribution Function is defined and is used to get points inside rice grains and then to find the boundary points of rice grains. These points are fit with the equation of an ellipse to estimate their lengths and breadths. The proposed techniques are applied on images of scattered and heaped rice grains of different varieties. It is shown that each variety gives a unique set of results.

Mapping of the surface rupture induced by the M 7.3 Kumamoto Earthquake along the Eastern segment of Futagawa fault using image correlation techniques

NASA Astrophysics Data System (ADS)

Ekhtari, N.; Glennie, C. L.; Fielding, E. J.; Liang, C.

2016-12-01

Near field surface deformation is vital to understanding the shallow fault physics of earthquakes but near-field deformation measurements are often sparse or not reliable. In this study, we use the Co-seismic Image Correlation (COSI-Corr) technique to map the near-field surface deformation caused by the M 7.3 April 16, 2016 Kumamoto Earthquake, Kyushu, Japan. The surface rupture around the Eastern segment of Futagawa fault is mapped using a pair of panchromatic 1.5 meter resolution SPOT 7 images. These images were acquired on January 16 and April 29, 2016 (3 months before and 13 days after the earthquake respectively) with close to nadir (less than 1.5 degree off nadir) viewing angle. The two images are ortho-rectified using SRTM Digital Elevation Model and further co-registered using tie points far away from the rupture field. Then the COSI-Corr technique is utilized to produce an estimated surface displacement map, and a horizontal displacement vector field is calculated which supplies a seamless estimate of near field displacement measurements along the Eastern segment of the Futagawa fault. The COSI-Corr estimated displacements are then compared to other existing displacement observations from InSAR, GPS and field observations.

Visiting the Gödel universe.

PubMed

Grave, Frank; Buser, Michael

2008-01-01

Visualization of general relativity illustrates aspects of Einstein's insights into the curved nature of space and time to the expert as well as the layperson. One of the most interesting models which came up with Einstein's theory was developed by Kurt Gödel in 1949. The Gödel universe is a valid solution of Einstein's field equations, making it a possible physical description of our universe. It offers remarkable features like the existence of an optical horizon beyond which time travel is possible. Although we know that our universe is not a Gödel universe, it is interesting to visualize physical aspects of a world model resulting from a theory which is highly confirmed in scientific history. Standard techniques to adopt an egocentric point of view in a relativistic world model have shortcomings with respect to the time needed to render an image as well as difficulties in applying a direct illumination model. In this paper we want to face both issues to reduce the gap between common visualization standards and relativistic visualization. We will introduce two techniques to speed up recalculation of images by means of preprocessing and lookup tables and to increase image quality through a special optimization applicable to the Gödel universe. The first technique allows the physicist to understand the different effects of general relativity faster and better by generating images from existing datasets interactively. By using the intrinsic symmetries of Gödel's spacetime which are expressed by the Killing vector field, we are able to reduce the necessary calculations to simple cases using the second technique. This even makes it feasible to account for a direct illumination model during the rendering process. Although the presented methods are applied to Gödel's universe, they can also be extended to other manifolds, for example light propagation in moving dielectric media. Therefore, other areas of research can benefit from these generic improvements.

Electromagnetic navigation technology for more precise electrode placement in the foramen ovale: a technical report.

PubMed

Van Buyten, Jean-Pierre; Smet, Iris; Van de Kelft, Erik

2009-07-01

Introduction. Interventional pain management techniques require precise positioning of needles or electrodes, therefore fluoroscopic control is mandatory. This imaging technique does however not visualize soft tissues such as blood vessels. Moreover, patient and physician are exposed to a considerable dose of radiation. Computed tomography (CT)-scans give a better view of soft tissues, but there use requires presence of a radiologist and has proven to be laborious and time consuming. Objectives. This study is to develop a technique using electromagnetic (EM) navigation as a guidance technique for interventional pain management, using CT and/or magnetic resonance (MRI) images uploaded on the navigation station. Methods. One of the best documented interventional procedures for the management of trigeminal neuralgia is percutaneous radiofrequency treatment of the Gasserian ganglion. EM navigation software for intracranial applications already exists. We developed a technique using a stylet with two magnetic coils suitable for EM navigation. The procedure is followed in real time on a computer screen where the patient's multislice CT-scan images and three-dimensional reconstruction of his face are uploaded. Virtual landmarks on the screen are matched with those on the patient's face, calculating the precision of the needle placement. Discussion. The experience with EM navigation acquired with the radiofrequency technique can be transferred to other interventional pain management techniques, for instance, for the placement of a neuromodulation electrode close to the Gasserian ganglion. Currently, research is ongoing to extend the software of the navigation station for spinal application, and to adapt neurostimulation hardware to the EM navigation technology. This technology will allow neuromodulation techniques to be performed without x-ray exposure for the patient and the physician, and this with the precision of CT/MR imaging guidance. © 2009 International Neuromodulation Society.

Optimization of oncological {sup 18}F-FDG PET/CT imaging based on a multiparameter analysis

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

Menezes, Vinicius O., E-mail: vinicius@radtec.com.br; Machado, Marcos A. D.; Queiroz, Cleiton C.

2016-02-15

Purpose: This paper describes a method to achieve consistent clinical image quality in {sup 18}F-FDG scans accounting for patient habitus, dose regimen, image acquisition, and processing techniques. Methods: Oncological PET/CT scan data for 58 subjects were evaluated retrospectively to derive analytical curves that predict image quality. Patient noise equivalent count rate and coefficient of variation (CV) were used as metrics in their analysis. Optimized acquisition protocols were identified and prospectively applied to 179 subjects. Results: The adoption of different schemes for three body mass ranges (<60 kg, 60–90 kg, >90 kg) allows improved image quality with both point spread functionmore » and ordered-subsets expectation maximization-3D reconstruction methods. The application of this methodology showed that CV improved significantly (p < 0.0001) in clinical practice. Conclusions: Consistent oncological PET/CT image quality on a high-performance scanner was achieved from an analysis of the relations existing between dose regimen, patient habitus, acquisition, and processing techniques. The proposed methodology may be used by PET/CT centers to develop protocols to standardize PET/CT imaging procedures and achieve better patient management and cost-effective operations.« less

Semiautomated confocal imaging of fungal pathogenesis on plants: Microscopic analysis of macroscopic specimens.

PubMed

Minker, Katharine R; Biedrzycki, Meredith L; Kolagunda, Abhishek; Rhein, Stephen; Perina, Fabiano J; Jacobs, Samuel S; Moore, Michael; Jamann, Tiffany M; Yang, Qin; Nelson, Rebecca; Balint-Kurti, Peter; Kambhamettu, Chandra; Wisser, Randall J; Caplan, Jeffrey L

2018-02-01

The study of phenotypic variation in plant pathogenesis provides fundamental information about the nature of disease resistance. Cellular mechanisms that alter pathogenesis can be elucidated with confocal microscopy; however, systematic phenotyping platforms-from sample processing to image analysis-to investigate this do not exist. We have developed a platform for 3D phenotyping of cellular features underlying variation in disease development by fluorescence-specific resolution of host and pathogen interactions across time (4D). A confocal microscopy phenotyping platform compatible with different maize-fungal pathosystems (fungi: Setosphaeria turcica, Cochliobolus heterostrophus, and Cercospora zeae-maydis) was developed. Protocols and techniques were standardized for sample fixation, optical clearing, species-specific combinatorial fluorescence staining, multisample imaging, and image processing for investigation at the macroscale. The sample preparation methods presented here overcome challenges to fluorescence imaging such as specimen thickness and topography as well as physiological characteristics of the samples such as tissue autofluorescence and presence of cuticle. The resulting imaging techniques provide interesting qualitative and quantitative information not possible with conventional light or electron 2D imaging. Microsc. Res. Tech., 81:141-152, 2018. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Automated processing of label-free Raman microscope images of macrophage cells with standardized regression for high-throughput analysis.

PubMed

Milewski, Robert J; Kumagai, Yutaro; Fujita, Katsumasa; Standley, Daron M; Smith, Nicholas I

2010-11-19

Macrophages represent the front lines of our immune system; they recognize and engulf pathogens or foreign particles thus initiating the immune response. Imaging macrophages presents unique challenges, as most optical techniques require labeling or staining of the cellular compartments in order to resolve organelles, and such stains or labels have the potential to perturb the cell, particularly in cases where incomplete information exists regarding the precise cellular reaction under observation. Label-free imaging techniques such as Raman microscopy are thus valuable tools for studying the transformations that occur in immune cells upon activation, both on the molecular and organelle levels. Due to extremely low signal levels, however, Raman microscopy requires sophisticated image processing techniques for noise reduction and signal extraction. To date, efficient, automated algorithms for resolving sub-cellular features in noisy, multi-dimensional image sets have not been explored extensively. We show that hybrid z-score normalization and standard regression (Z-LSR) can highlight the spectral differences within the cell and provide image contrast dependent on spectral content. In contrast to typical Raman imaging processing methods using multivariate analysis, such as single value decomposition (SVD), our implementation of the Z-LSR method can operate nearly in real-time. In spite of its computational simplicity, Z-LSR can automatically remove background and bias in the signal, improve the resolution of spatially distributed spectral differences and enable sub-cellular features to be resolved in Raman microscopy images of mouse macrophage cells. Significantly, the Z-LSR processed images automatically exhibited subcellular architectures whereas SVD, in general, requires human assistance in selecting the components of interest. The computational efficiency of Z-LSR enables automated resolution of sub-cellular features in large Raman microscopy data sets without compromise in image quality or information loss in associated spectra. These results motivate further use of label free microscopy techniques in real-time imaging of live immune cells.

Copyright protection of remote sensing imagery by means of digital watermarking

NASA Astrophysics Data System (ADS)

Barni, Mauro; Bartolini, Franco; Cappellini, Vito; Magli, Enrico; Olmo, Gabriella; Zanini, R.

2001-12-01

The demand for remote sensing data has increased dramatically mainly due to the large number of possible applications capable to exploit remotely sensed data and images. As in many other fields, along with the increase of market potential and product diffusion, the need arises for some sort of protection of the image products from unauthorized use. Such a need is a very crucial one even because the Internet and other public/private networks have become preferred and effective means of data exchange. An important issue arising when dealing with digital image distribution is copyright protection. Such a problem has been largely addressed by resorting to watermarking technology. Before applying watermarking techniques developed for multimedia applications to remote sensing applications, it is important that the requirements imposed by remote sensing imagery are carefully analyzed to investigate whether they are compatible with existing watermarking techniques. On the basis of these motivations, the contribution of this work is twofold: (1) assessment of the requirements imposed by the characteristics of remotely sensed images on watermark-based copyright protection; (2) discussion of a case study where the performance of two popular, state-of-the-art watermarking techniques are evaluated by the light of the requirements at the previous point.

Exploiting range imagery: techniques and applications

NASA Astrophysics Data System (ADS)

Armbruster, Walter

2009-07-01

Practically no applications exist for which automatic processing of 2D intensity imagery can equal human visual perception. This is not the case for range imagery. The paper gives examples of 3D laser radar applications, for which automatic data processing can exceed human visual cognition capabilities and describes basic processing techniques for attaining these results. The examples are drawn from the fields of helicopter obstacle avoidance, object detection in surveillance applications, object recognition at high range, multi-object-tracking, and object re-identification in range image sequences. Processing times and recognition performances are summarized. The techniques used exploit the bijective continuity of the imaging process as well as its independence of object reflectivity, emissivity and illumination. This allows precise formulations of the probability distributions involved in figure-ground segmentation, feature-based object classification and model based object recognition. The probabilistic approach guarantees optimal solutions for single images and enables Bayesian learning in range image sequences. Finally, due to recent results in 3D-surface completion, no prior model libraries are required for recognizing and re-identifying objects of quite general object categories, opening the way to unsupervised learning and fully autonomous cognitive systems.

Optical control and diagnostics sensors for gas turbine machinery

NASA Astrophysics Data System (ADS)

Trolinger, James D.; Jenkins, Thomas P.; Heeg, Bauke

2012-10-01

There exists a vast range of optical techniques that have been under development for solving complex measurement problems related to gas-turbine machinery and phenomena. For instance, several optical techniques are ideally suited for studying fundamental combustion phenomena in laboratory environments. Yet other techniques hold significant promise for use as either on-line gas turbine control sensors, or as health monitoring diagnostics sensors. In this paper, we briefly summarize these and discuss, in more detail, some of the latter class of techniques, including phosphor thermometry, hyperspectral imaging and low coherence interferometry, which are particularly suited for control and diagnostics sensing on hot section components with ceramic thermal barrier coatings (TBCs).

TOPICAL REVIEW: Anatomical imaging for radiotherapy

NASA Astrophysics Data System (ADS)

Evans, Philip M.

2008-06-01

The goal of radiation therapy is to achieve maximal therapeutic benefit expressed in terms of a high probability of local control of disease with minimal side effects. Physically this often equates to the delivery of a high dose of radiation to the tumour or target region whilst maintaining an acceptably low dose to other tissues, particularly those adjacent to the target. Techniques such as intensity modulated radiotherapy (IMRT), stereotactic radiosurgery and computer planned brachytherapy provide the means to calculate the radiation dose delivery to achieve the desired dose distribution. Imaging is an essential tool in all state of the art planning and delivery techniques: (i) to enable planning of the desired treatment, (ii) to verify the treatment is delivered as planned and (iii) to follow-up treatment outcome to monitor that the treatment has had the desired effect. Clinical imaging techniques can be loosely classified into anatomic methods which measure the basic physical characteristics of tissue such as their density and biological imaging techniques which measure functional characteristics such as metabolism. In this review we consider anatomical imaging techniques. Biological imaging is considered in another article. Anatomical imaging is generally used for goals (i) and (ii) above. Computed tomography (CT) has been the mainstay of anatomical treatment planning for many years, enabling some delineation of soft tissue as well as radiation attenuation estimation for dose prediction. Magnetic resonance imaging is fast becoming widespread alongside CT, enabling superior soft-tissue visualization. Traditionally scanning for treatment planning has relied on the use of a single snapshot scan. Recent years have seen the development of techniques such as 4D CT and adaptive radiotherapy (ART). In 4D CT raw data are encoded with phase information and reconstructed to yield a set of scans detailing motion through the breathing, or cardiac, cycle. In ART a set of scans is taken on different days. Both allow planning to account for variability intrinsic to the patient. Treatment verification has been carried out using a variety of technologies including: MV portal imaging, kV portal/fluoroscopy, MVCT, conebeam kVCT, ultrasound and optical surface imaging. The various methods have their pros and cons. The four x-ray methods involve an extra radiation dose to normal tissue. The portal methods may not generally be used to visualize soft tissue, consequently they are often used in conjunction with implanted fiducial markers. The two CT-based methods allow measurement of inter-fraction variation only. Ultrasound allows soft-tissue measurement with zero dose but requires skilled interpretation, and there is evidence of systematic differences between ultrasound and other data sources, perhaps due to the effects of the probe pressure. Optical imaging also involves zero dose but requires good correlation between the target and the external measurement and thus is often used in conjunction with an x-ray method. The use of anatomical imaging in radiotherapy allows treatment uncertainties to be determined. These include errors between the mean position at treatment and that at planning (the systematic error) and the day-to-day variation in treatment set-up (the random error). Positional variations may also be categorized in terms of inter- and intra-fraction errors. Various empirical treatment margin formulae and intervention approaches exist to determine the optimum strategies for treatment in the presence of these known errors. Other methods exist to try to minimize error margins drastically including the currently available breath-hold techniques and the tracking methods which are largely in development. This paper will review anatomical imaging techniques in radiotherapy and how they are used to boost the therapeutic benefit of the treatment.

Hypoxia Imaging Endoscopy Equipped with Laser Light Source from Preclinical Live Animal Study to First-In-Human Subject Research

PubMed Central

Kaneko, Kazuhiro; Yamaguchi, Hiroshi; Saito, Takaaki; Yano, Tomonori; Oono, Yasuhiro; Ikematsu, Hiroaki; Nomura, Shogo; Sato, Akihiro; Kojima, Motohiro; Esumi, Hiroyasu; Ochiai, Atsushi

2014-01-01

A goal in next-generation endoscopy is to develop functional imaging techniques to open up new opportunities for cancer diagnosis. Although spatial and temporal information on hypoxia is crucial for understanding cancer physiology and expected to be useful for cancer diagnosis, existing techniques using fluorescent indicators have limitations due to low spatial resolution and invasive administration. To overcome these problems, we developed an imaging technology based on hemoglobin oxygen saturation in both the tumor and surrounding mucosa using a laser endoscope system, and conducted the first human subject research for patients with aero-digestive tract cancer. The oxygen saturation map overlapped the images of cancerous lesions and indicated highly heterogeneous features of oxygen supply in the tumor. The hypoxic region of the tumor surface was found in both early cancer and cancer precursors. This technology illustrates a novel aspect of cancer biology as a potential biomarker and can be widely utilized in cancer diagnosis. PMID:24915532

Diagnostic Evaluation of the Knee in the Office Setting Using Small-Bore Needle Arthroscopy.

PubMed

Patel, Karan A; Hartigan, David E; Makovicka, Justin L; Dulle, Donald L; Chhabra, Anikar

2018-01-01

Arthroscopy is currently the gold standard for diagnosing intra-articular knee pathology. Magnetic resonance imaging (MRI) can be a clinical adjunct for diagnosis; however, it is not without its shortcomings. Although highly accurate, even advanced imaging misdiagnoses the condition in 1 in 14 patients with regard to anterior cruciate ligament pathology. Previous studies have indicated that MRI fails to identify meniscal pathology when one exists in 1 of every 10 cases, and diagnoses pathology when pathology truly does not exist in 1 of every 5 patients. In-office arthroscopy offers an alternative to formal diagnostic arthroscopy, with reduced cost and risk of complications. This is a technique article that discusses the use of small-bore needle arthroscopy in the office setting.

DIFFUSION-WEIGHTED IMAGING OF THE LIVER: TECHNIQUES AND APPLICATIONS

PubMed Central

Lewis, Sara; Dyvorne, Hadrien; Cui, Yong; Taouli, Bachir

2014-01-01

SYNOPSIS Diffusion weighted MRI (DWI) is a technique that assesses the cellularity, tortuosity of the extracellular/extravascular space and cell membrane density based upon differences in water proton mobility in tissues. The strength of the diffusion weighting is reflected by the b-value. DWI using several b-values enables quantification of the apparent diffusion coefficient (ADC). DWI is increasingly employed in liver imaging for multiple reasons: it can add useful qualitative and quantitative information to conventional imaging sequences, it is acquired relatively quickly, it is easily incorporated into existing clinical protocols, and it is a non-contrast technique. DWI is useful for focal liver lesion detection and characterization, for the assessment of post-treatment tumor response and for evaluation of diffuse liver disease. ADC quantification can be used to characterize lesions as cystic/necrotic or solid and for predicting tumor response to therapy. Advanced diffusion methods such as IVIM (intravoxel incoherent motion) may have potential for detection, staging and evaluation of the progression of liver fibrosis and for liver lesion characterization. The lack of standardization of DWI technique including choice of b-values and sequence parameters has somewhat limited its widespread adoption. PMID:25086935

Mass Spectrometry Imaging of Complex Microbial Communities

PubMed Central

2016-01-01

Conspectus In the two decades since mass spectrometry imaging (MSI) was first applied to visualize the distribution of peptides across biological tissues and cells, the technique has become increasingly effective and reliable. MSI excels at providing complementary information to existing methods for molecular analysis—such as genomics, transcriptomics, and metabolomics—and stands apart from other chemical imaging modalities through its capability to generate information that is simultaneously multiplexed and chemically specific. Today a diverse family of MSI approaches are applied throughout the scientific community to study the distribution of proteins, peptides, and small-molecule metabolites across many biological models. The inherent strengths of MSI make the technique valuable for studying microbial systems. Many microbes reside in surface-attached multicellular and multispecies communities, such as biofilms and motile colonies, where they work together to harness surrounding nutrients, fend off hostile organisms, and shield one another from adverse environmental conditions. These processes, as well as many others essential for microbial survival, are mediated through the production and utilization of a diverse assortment of chemicals. Although bacterial cells are generally only a few microns in diameter, the ecologies they influence can encompass entire ecosystems, and the chemical changes that they bring about can occur over time scales ranging from milliseconds to decades. Because of their incredible complexity, our understanding of and influence over microbial systems requires detailed scientific evaluations that yield both chemical and spatial information. MSI is well-positioned to fulfill these requirements. With small adaptations to existing methods, the technique can be applied to study a wide variety of chemical interactions, including those that occur inside single-species microbial communities, between cohabitating microbes, and between microbes and their hosts. In recognition of this potential for scientific advancement, researchers have adapted MSI methodologies for the specific needs of the microbiology research community. As a result, workflows exist for imaging microbial systems with many of the common MSI ionization methods. Despite this progress, there is substantial room for improvements in instrumentation, sample preparation, and data interpretation. This Account provides a brief overview of the state of technology in microbial MSI, illuminates selected applications that demonstrate the potential of the technique, and highlights a series of development challenges that are needed to move the field forward. In the coming years, as microbial MSI becomes easier to use and more universally applicable, the technique will evolve into a fundamental tool widely applied throughout many divisions of science, medicine, and industry. PMID:28001363

Mass Spectrometry Imaging of Complex Microbial Communities.

PubMed

Dunham, Sage J B; Ellis, Joseph F; Li, Bin; Sweedler, Jonathan V

2017-01-17

In the two decades since mass spectrometry imaging (MSI) was first applied to visualize the distribution of peptides across biological tissues and cells, the technique has become increasingly effective and reliable. MSI excels at providing complementary information to existing methods for molecular analysis-such as genomics, transcriptomics, and metabolomics-and stands apart from other chemical imaging modalities through its capability to generate information that is simultaneously multiplexed and chemically specific. Today a diverse family of MSI approaches are applied throughout the scientific community to study the distribution of proteins, peptides, and small-molecule metabolites across many biological models. The inherent strengths of MSI make the technique valuable for studying microbial systems. Many microbes reside in surface-attached multicellular and multispecies communities, such as biofilms and motile colonies, where they work together to harness surrounding nutrients, fend off hostile organisms, and shield one another from adverse environmental conditions. These processes, as well as many others essential for microbial survival, are mediated through the production and utilization of a diverse assortment of chemicals. Although bacterial cells are generally only a few microns in diameter, the ecologies they influence can encompass entire ecosystems, and the chemical changes that they bring about can occur over time scales ranging from milliseconds to decades. Because of their incredible complexity, our understanding of and influence over microbial systems requires detailed scientific evaluations that yield both chemical and spatial information. MSI is well-positioned to fulfill these requirements. With small adaptations to existing methods, the technique can be applied to study a wide variety of chemical interactions, including those that occur inside single-species microbial communities, between cohabitating microbes, and between microbes and their hosts. In recognition of this potential for scientific advancement, researchers have adapted MSI methodologies for the specific needs of the microbiology research community. As a result, workflows exist for imaging microbial systems with many of the common MSI ionization methods. Despite this progress, there is substantial room for improvements in instrumentation, sample preparation, and data interpretation. This Account provides a brief overview of the state of technology in microbial MSI, illuminates selected applications that demonstrate the potential of the technique, and highlights a series of development challenges that are needed to move the field forward. In the coming years, as microbial MSI becomes easier to use and more universally applicable, the technique will evolve into a fundamental tool widely applied throughout many divisions of science, medicine, and industry.

Nonrigid registration of carotid ultrasound and MR images using a "twisting and bending" model

NASA Astrophysics Data System (ADS)

Nanayakkara, Nuwan D.; Chiu, Bernard; Samani, Abbas; Spence, J. David; Parraga, Grace; Samarabandu, Jagath; Fenster, Aaron

2008-03-01

Atherosclerosis at the carotid bifurcation resulting in cerebral emboli is a major cause of ischemic stroke. Most strokes associated with carotid atherosclerosis can be prevented by lifestyle/dietary changes and pharmacological treatments if identified early by monitoring carotid plaque changes. Plaque composition information from magnetic resonance (MR) carotid images and dynamic characteristics information from 3D ultrasound (US) are necessary for developing and validating US imaging tools to identify vulnerable carotid plaques. Combining these images requires nonrigid registration to correct the non-linear miss-alignments caused by relative twisting and bending in the neck due to different head positions during the two image acquisitions sessions. The high degree of freedom and large number of parameters associated with existing nonrigid image registration methods causes several problems including unnatural plaque morphology alteration, computational complexity, and low reliability. Our approach was to model the normal movement of the neck using a "twisting and bending model" with only six parameters for nonrigid registration. We evaluated our registration technique using intra-subject in-vivo 3D US and 3D MR carotid images acquired on the same day. We calculated the Mean Registration Error (MRE) between the segmented vessel surfaces in the target image and the registered image using a distance-based error metric after applying our "twisting bending model" based nonrigid registration algorithm. We achieved an average registration error of 1.33+/-0.41mm using our nonrigid registration technique. Visual inspection of segmented vessel surfaces also showed a substantial improvement of alignment with our non-rigid registration technique.

A Secure and Efficient Scalable Secret Image Sharing Scheme with Flexible Shadow Sizes

PubMed Central

Xie, Dong; Li, Lixiang; Peng, Haipeng; Yang, Yixian

2017-01-01

In a general (k, n) scalable secret image sharing (SSIS) scheme, the secret image is shared by n participants and any k or more than k participants have the ability to reconstruct it. The scalability means that the amount of information in the reconstructed image scales in proportion to the number of the participants. In most existing SSIS schemes, the size of each image shadow is relatively large and the dealer does not has a flexible control strategy to adjust it to meet the demand of differen applications. Besides, almost all existing SSIS schemes are not applicable under noise circumstances. To address these deficiencies, in this paper we present a novel SSIS scheme based on a brand-new technique, called compressed sensing, which has been widely used in many fields such as image processing, wireless communication and medical imaging. Our scheme has the property of flexibility, which means that the dealer can achieve a compromise between the size of each shadow and the quality of the reconstructed image. In addition, our scheme has many other advantages, including smooth scalability, noise-resilient capability, and high security. The experimental results and the comparison with similar works demonstrate the feasibility and superiority of our scheme. PMID:28072851

Electromechanical wave imaging for noninvasive mapping of the 3D electrical activation sequence in canines and humans in vivo

PubMed Central

Konofagou, Elisa E.; Provost, Jean

2014-01-01

Cardiovascular diseases rank as America’s primary killer, claiming the lives of over 41% of more than 2.4 million Americans. One of the main reasons for this high death toll is the severe lack of effective imaging techniques for screening, early detection and localization of an abnormality detected on the electrocardiogram (ECG). The two most widely used imaging techniques in the clinic are CT angiography and echocardiography with limitations in speed of application and reliability, respectively. It has been established that the mechanical and electrical properties of the myocardium change dramatically as a result of ischemia, infarction or arrhythmia; both at their onset and after survival. Despite these findings, no imaging technique currently exists that is routinely used in the clinic and can provide reliable, non-invasive, quantitative mapping of the regional, mechanical and electrical function of the myocardium. Electromechanical Wave Imaging (EWI) is an ultrasound-based technique that utilizes the electromechanical coupling and its associated resulting strain to infer to the underlying electrical function of the myocardium. The methodology of EWI is first described and its fundamental performance is presented. Subsequent in vivo canine and human applications are provided that demonstrate the applicability of Electromechanical Wave Imaging in differentiating between sinus rhythm and induced pacing schemes as well as mapping arrhythmias. Preliminary validation with catheter mapping is also provided and transthoracic electromechanical mapping in all four chambers of the human heart is also presented demonstrating the potential of this novel methodology to noninvasively infer to both the normal and pathological electrical conduction of the heart. PMID:22284425

A methodology for automated CPA extraction using liver biopsy image analysis and machine learning techniques.

PubMed

Tsipouras, Markos G; Giannakeas, Nikolaos; Tzallas, Alexandros T; Tsianou, Zoe E; Manousou, Pinelopi; Hall, Andrew; Tsoulos, Ioannis; Tsianos, Epameinondas

2017-03-01

Collagen proportional area (CPA) extraction in liver biopsy images provides the degree of fibrosis expansion in liver tissue, which is the most characteristic histological alteration in hepatitis C virus (HCV). Assessment of the fibrotic tissue is currently based on semiquantitative staging scores such as Ishak and Metavir. Since its introduction as a fibrotic tissue assessment technique, CPA calculation based on image analysis techniques has proven to be more accurate than semiquantitative scores. However, CPA has yet to reach everyday clinical practice, since the lack of standardized and robust methods for computerized image analysis for CPA assessment have proven to be a major limitation. The current work introduces a three-stage fully automated methodology for CPA extraction based on machine learning techniques. Specifically, clustering algorithms have been employed for background-tissue separation, as well as for fibrosis detection in liver tissue regions, in the first and the third stage of the methodology, respectively. Due to the existence of several types of tissue regions in the image (such as blood clots, muscle tissue, structural collagen, etc.), classification algorithms have been employed to identify liver tissue regions and exclude all other non-liver tissue regions from CPA computation. For the evaluation of the methodology, 79 liver biopsy images have been employed, obtaining 1.31% mean absolute CPA error, with 0.923 concordance correlation coefficient. The proposed methodology is designed to (i) avoid manual threshold-based and region selection processes, widely used in similar approaches presented in the literature, and (ii) minimize CPA calculation time. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Nanoscale chemical imaging by photoinduced force microscopy

PubMed Central

Nowak, Derek; Morrison, William; Wickramasinghe, H. Kumar; Jahng, Junghoon; Potma, Eric; Wan, Lei; Ruiz, Ricardo; Albrecht, Thomas R.; Schmidt, Kristin; Frommer, Jane; Sanders, Daniel P.; Park, Sung

2016-01-01

Correlating spatial chemical information with the morphology of closely packed nanostructures remains a challenge for the scientific community. For example, supramolecular self-assembly, which provides a powerful and low-cost way to create nanoscale patterns and engineered nanostructures, is not easily interrogated in real space via existing nondestructive techniques based on optics or electrons. A novel scanning probe technique called infrared photoinduced force microscopy (IR PiFM) directly measures the photoinduced polarizability of the sample in the near field by detecting the time-integrated force between the tip and the sample. By imaging at multiple IR wavelengths corresponding to absorption peaks of different chemical species, PiFM has demonstrated the ability to spatially map nm-scale patterns of the individual chemical components of two different types of self-assembled block copolymer films. With chemical-specific nanometer-scale imaging, PiFM provides a powerful new analytical method for deepening our understanding of nanomaterials. PMID:27051870

Combining total internal reflection sum frequency spectroscopy spectral imaging and confocal fluorescence microscopy.

PubMed

Allgeyer, Edward S; Sterling, Sarah M; Gunewardene, Mudalige S; Hess, Samuel T; Neivandt, David J; Mason, Michael D

2015-01-27

Understanding surface and interfacial lateral organization in material and biological systems is critical in nearly every field of science. The continued development of tools and techniques viable for elucidation of interfacial and surface information is therefore necessary to address new questions and further current investigations. Sum frequency spectroscopy (SFS) is a label-free, nonlinear optical technique with inherent surface specificity that can yield critical organizational information on interfacial species. Unfortunately, SFS provides no spatial information on a surface; small scale heterogeneities that may exist are averaged over the large areas typically probed. Over the past decade, this has begun to be addressed with the advent of SFS microscopy. Here we detail the construction and function of a total internal reflection (TIR) SFS spectral and confocal fluorescence imaging microscope directly amenable to surface investigations. This instrument combines, for the first time, sample scanning TIR-SFS imaging with confocal fluorescence microscopy.

Computer assisted diagnostic system in tumor radiography.

PubMed

Faisal, Ahmed; Parveen, Sharmin; Badsha, Shahriar; Sarwar, Hasan; Reza, Ahmed Wasif

2013-06-01

An improved and efficient method is presented in this paper to achieve a better trade-off between noise removal and edge preservation, thereby detecting the tumor region of MRI brain images automatically. Compass operator has been used in the fourth order Partial Differential Equation (PDE) based denoising technique to preserve the anatomically significant information at the edges. A new morphological technique is also introduced for stripping skull region from the brain images, which consequently leading to the process of detecting tumor accurately. Finally, automatic seeded region growing segmentation based on an improved single seed point selection algorithm is applied to detect the tumor. The method is tested on publicly available MRI brain images and it gives an average PSNR (Peak Signal to Noise Ratio) of 36.49. The obtained results also show detection accuracy of 99.46%, which is a significant improvement than that of the existing results.

A novel data hiding scheme for block truncation coding compressed images using dynamic programming strategy

NASA Astrophysics Data System (ADS)

Chang, Ching-Chun; Liu, Yanjun; Nguyen, Son T.

2015-03-01

Data hiding is a technique that embeds information into digital cover data. This technique has been concentrated on the spatial uncompressed domain, and it is considered more challenging to perform in the compressed domain, i.e., vector quantization, JPEG, and block truncation coding (BTC). In this paper, we propose a new data hiding scheme for BTC-compressed images. In the proposed scheme, a dynamic programming strategy was used to search for the optimal solution of the bijective mapping function for LSB substitution. Then, according to the optimal solution, each mean value embeds three secret bits to obtain high hiding capacity with low distortion. The experimental results indicated that the proposed scheme obtained both higher hiding capacity and hiding efficiency than the other four existing schemes, while ensuring good visual quality of the stego-image. In addition, the proposed scheme achieved a low bit rate as original BTC algorithm.

User-guided segmentation for volumetric retinal optical coherence tomography images

PubMed Central

Yin, Xin; Chao, Jennifer R.; Wang, Ruikang K.

2014-01-01

Abstract. Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method. PMID:25147962

User-guided segmentation for volumetric retinal optical coherence tomography images.

PubMed

Yin, Xin; Chao, Jennifer R; Wang, Ruikang K

2014-08-01

Despite the existence of automatic segmentation techniques, trained graders still rely on manual segmentation to provide retinal layers and features from clinical optical coherence tomography (OCT) images for accurate measurements. To bridge the gap between this time-consuming need of manual segmentation and currently available automatic segmentation techniques, this paper proposes a user-guided segmentation method to perform the segmentation of retinal layers and features in OCT images. With this method, by interactively navigating three-dimensional (3-D) OCT images, the user first manually defines user-defined (or sketched) lines at regions where the retinal layers appear very irregular for which the automatic segmentation method often fails to provide satisfactory results. The algorithm is then guided by these sketched lines to trace the entire 3-D retinal layer and anatomical features by the use of novel layer and edge detectors that are based on robust likelihood estimation. The layer and edge boundaries are finally obtained to achieve segmentation. Segmentation of retinal layers in mouse and human OCT images demonstrates the reliability and efficiency of the proposed user-guided segmentation method.

Accurately estimating PSF with straight lines detected by Hough transform

NASA Astrophysics Data System (ADS)

Wang, Ruichen; Xu, Liangpeng; Fan, Chunxiao; Li, Yong

2018-04-01

This paper presents an approach to estimating point spread function (PSF) from low resolution (LR) images. Existing techniques usually rely on accurate detection of ending points of the profile normal to edges. In practice however, it is often a great challenge to accurately localize profiles of edges from a LR image, which hence leads to a poor PSF estimation of the lens taking the LR image. For precisely estimating the PSF, this paper proposes firstly estimating a 1-D PSF kernel with straight lines, and then robustly obtaining the 2-D PSF from the 1-D kernel by least squares techniques and random sample consensus. Canny operator is applied to the LR image for obtaining edges and then Hough transform is utilized to extract straight lines of all orientations. Estimating 1-D PSF kernel with straight lines effectively alleviates the influence of the inaccurate edge detection on PSF estimation. The proposed method is investigated on both natural and synthetic images for estimating PSF. Experimental results show that the proposed method outperforms the state-ofthe- art and does not rely on accurate edge detection.

Ultrasound speckle reduction based on fractional order differentiation.

PubMed

Shao, Dangguo; Zhou, Ting; Liu, Fan; Yi, Sanli; Xiang, Yan; Ma, Lei; Xiong, Xin; He, Jianfeng

2017-07-01

Ultrasound images show a granular pattern of noise known as speckle that diminishes their quality and results in difficulties in diagnosis. To preserve edges and features, this paper proposes a fractional differentiation-based image operator to reduce speckle in ultrasound. An image de-noising model based on fractional partial differential equations with balance relation between k (gradient modulus threshold that controls the conduction) and v (the order of fractional differentiation) was constructed by the effective combination of fractional calculus theory and a partial differential equation, and the numerical algorithm of it was achieved using a fractional differential mask operator. The proposed algorithm has better speckle reduction and structure preservation than the three existing methods [P-M model, the speckle reducing anisotropic diffusion (SRAD) technique, and the detail preserving anisotropic diffusion (DPAD) technique]. And it is significantly faster than bilateral filtering (BF) in producing virtually the same experimental results. Ultrasound phantom testing and in vivo imaging show that the proposed method can improve the quality of an ultrasound image in terms of tissue SNR, CNR, and FOM values.

Self-organized Evaluation of Dynamic Hand Gestures for Sign Language Recognition

NASA Astrophysics Data System (ADS)

Buciu, Ioan; Pitas, Ioannis

Two main theories exist with respect to face encoding and representation in the human visual system (HVS). The first one refers to the dense (holistic) representation of the face, where faces have "holon"-like appearance. The second one claims that a more appropriate face representation is given by a sparse code, where only a small fraction of the neural cells corresponding to face encoding is activated. Theoretical and experimental evidence suggest that the HVS performs face analysis (encoding, storing, face recognition, facial expression recognition) in a structured and hierarchical way, where both representations have their own contribution and goal. According to neuropsychological experiments, it seems that encoding for face recognition, relies on holistic image representation, while a sparse image representation is used for facial expression analysis and classification. From the computer vision perspective, the techniques developed for automatic face and facial expression recognition fall into the same two representation types. Like in Neuroscience, the techniques which perform better for face recognition yield a holistic image representation, while those techniques suitable for facial expression recognition use a sparse or local image representation. The proposed mathematical models of image formation and encoding try to simulate the efficient storing, organization and coding of data in the human cortex. This is equivalent with embedding constraints in the model design regarding dimensionality reduction, redundant information minimization, mutual information minimization, non-negativity constraints, class information, etc. The presented techniques are applied as a feature extraction step followed by a classification method, which also heavily influences the recognition results.

MO-DE-207A-10: One-Step CT Reconstruction for Metal Artifact Reduction by a Modification of Penalized Weighted Least-Squares (PWLS)

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

Kim, H; Chen, J

Purpose: Metal objects create severe artifacts in kilo-voltage (kV) CT image reconstructions due to the high attenuation coefficients of high atomic number objects. Most of the techniques devised to reduce this artifact utilize a two-step approach, which do not reliably yield the qualified reconstructed images. Thus, for accuracy and simplicity, this work presents a one-step reconstruction method based on a modified penalized weighted least-squares (PWLS) technique. Methods: Existing techniques for metal artifact reduction mostly adopt a two-step approach, which conduct additional reconstruction with the modified projection data from the initial reconstruction. This procedure does not consistently perform well due tomore » the uncertainties in manipulating the metal-contaminated projection data by thresholding and linear interpolation. This study proposes a one-step reconstruction process using a new PWLS operation with total-variation (TV) minimization, while not manipulating the projection. The PWLS for CT reconstruction has been investigated using a pre-defined weight, based on the variance of the projection datum at each detector bin. It works well when reconstructing CT images from metal-free projection data, which does not appropriately penalize metal-contaminated projection data. The proposed work defines the weight at each projection element under the assumption of a Poisson random variable. This small modification using element-wise penalization has a large impact in reducing metal artifacts. For evaluation, the proposed technique was assessed with two noisy, metal-contaminated digital phantoms, against the existing PWLS with TV minimization and the two-step approach. Result: The proposed PWLS with TV minimization greatly improved the metal artifact reduction, relative to the other techniques, by watching the results. Numerically, the new approach lowered the normalized root-mean-square error about 30 and 60% for the two cases, respectively, compared to the two-step method. Conclusion: A new PWLS operation shows promise for improving metal artifact reduction in CT imaging, as well as simplifying the reconstructing procedure.« less

A Support Vector Machine Approach for Truncated Fingerprint Image Detection from Sweeping Fingerprint Sensors

PubMed Central

Chen, Chi-Jim; Pai, Tun-Wen; Cheng, Mox

2015-01-01

A sweeping fingerprint sensor converts fingerprints on a row by row basis through image reconstruction techniques. However, a built fingerprint image might appear to be truncated and distorted when the finger was swept across a fingerprint sensor at a non-linear speed. If the truncated fingerprint images were enrolled as reference targets and collected by any automated fingerprint identification system (AFIS), successful prediction rates for fingerprint matching applications would be decreased significantly. In this paper, a novel and effective methodology with low time computational complexity was developed for detecting truncated fingerprints in a real time manner. Several filtering rules were implemented to validate existences of truncated fingerprints. In addition, a machine learning method of supported vector machine (SVM), based on the principle of structural risk minimization, was applied to reject pseudo truncated fingerprints containing similar characteristics of truncated ones. The experimental result has shown that an accuracy rate of 90.7% was achieved by successfully identifying truncated fingerprint images from testing images before AFIS enrollment procedures. The proposed effective and efficient methodology can be extensively applied to all existing fingerprint matching systems as a preliminary quality control prior to construction of fingerprint templates. PMID:25835186

Recent Design Development in Molecular Imaging for Breast Cancer Detection Using Nanometer CMOS Based Sensors.

PubMed

Nguyen, Dung C; Ma, Dongsheng Brian; Roveda, Janet M W

2012-01-01

As one of the key clinical imaging methods, the computed X-ray tomography can be further improved using new nanometer CMOS sensors. This will enhance the current technique's ability in terms of cancer detection size, position, and detection accuracy on the anatomical structures. The current paper reviewed designs of SOI-based CMOS sensors and their architectural design in mammography systems. Based on the existing experimental results, using the SOI technology can provide a low-noise (SNR around 87.8 db) and high-gain (30 v/v) CMOS imager. It is also expected that, together with the fast data acquisition designs, the new type of imagers may play important roles in the near-future high-dimensional images in additional to today's 2D imagers.

Leveraging simulation to evaluate system performance in presence of fixed pattern noise

NASA Astrophysics Data System (ADS)

Teaney, Brian P.

2017-05-01

The development of image simulation techniques which map the effects of a notional, modeled sensor system onto an existing image can be used to evaluate the image quality of camera systems prior to the development of prototype systems. In addition, image simulation or `virtual prototyping' can be utilized to reduce the time and expense associated with conducting extensive field trials. In this paper we examine the development of a perception study designed to assess the performance of the NVESD imager performance metrics as a function of fixed pattern noise. This paper discusses the development of the model theory and the implementation and execution of the perception study. In addition, other applications of the image simulation component including the evaluation of limiting resolution and other test targets is provided.

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids.

PubMed

Dahlberg, Jerry; Tkacik, Peter T; Mullany, Brigid; Fleischhauer, Eric; Shahinian, Hossein; Azimi, Farzad; Navare, Jayesh; Owen, Spencer; Bisel, Tucker; Martin, Tony; Sholar, Jodie; Keanini, Russell G

2017-12-04

An analog, macroscopic method for studying molecular-scale hydrodynamic processes in dense gases and liquids is described. The technique applies a standard fluid dynamic diagnostic, particle image velocimetry (PIV), to measure: i) velocities of individual particles (grains), extant on short, grain-collision time-scales, ii) velocities of systems of particles, on both short collision-time- and long, continuum-flow-time-scales, iii) collective hydrodynamic modes known to exist in dense molecular fluids, and iv) short- and long-time-scale velocity autocorrelation functions, central to understanding particle-scale dynamics in strongly interacting, dense fluid systems. The basic system is composed of an imaging system, light source, vibrational sensors, vibrational system with a known media, and PIV and analysis software. Required experimental measurements and an outline of the theoretical tools needed when using the analog technique to study molecular-scale hydrodynamic processes are highlighted. The proposed technique provides a relatively straightforward alternative to photonic and neutron beam scattering methods traditionally used in molecular hydrodynamic studies.

Biometric Authentication for Gender Classification Techniques: A Review

NASA Astrophysics Data System (ADS)

Mathivanan, P.; Poornima, K.

2017-12-01

One of the challenging biometric authentication applications is gender identification and age classification, which captures gait from far distance and analyze physical information of the subject such as gender, race and emotional state of the subject. It is found that most of the gender identification techniques have focused only with frontal pose of different human subject, image size and type of database used in the process. The study also classifies different feature extraction process such as, Principal Component Analysis (PCA) and Local Directional Pattern (LDP) that are used to extract the authentication features of a person. This paper aims to analyze different gender classification techniques that help in evaluating strength and weakness of existing gender identification algorithm. Therefore, it helps in developing a novel gender classification algorithm with less computation cost and more accuracy. In this paper, an overview and classification of different gender identification techniques are first presented and it is compared with other existing human identification system by means of their performance.

Classification of biological micro-objects using optical coherence tomography: in silico study

PubMed Central

Ossowski, Paweł; Wojtkowski, Maciej; Munro, Peter RT

2017-01-01

We report on the development of a technique for differentiating between biological micro-objects using a rigorous, full-wave model of OCT image formation. We model an existing experimental prototype which uses OCT to interrogate a microfluidic chip containing the blood cells. A full-wave model is required since the technique uses light back-scattered by a scattering substrate, rather than by the cells directly. The light back-scattered by the substrate is perturbed upon propagation through the cells, which flow between the substrate and imaging system’s objective lens. We present the key elements of the 3D, Maxwell equation-based computational model, the key findings of the computational study and a comparison with experimental results. PMID:28856039

Classification of biological micro-objects using optical coherence tomography: in silico study.

PubMed

Ossowski, Paweł; Wojtkowski, Maciej; Munro, Peter Rt

2017-08-01

We report on the development of a technique for differentiating between biological micro-objects using a rigorous, full-wave model of OCT image formation. We model an existing experimental prototype which uses OCT to interrogate a microfluidic chip containing the blood cells. A full-wave model is required since the technique uses light back-scattered by a scattering substrate, rather than by the cells directly. The light back-scattered by the substrate is perturbed upon propagation through the cells, which flow between the substrate and imaging system's objective lens. We present the key elements of the 3D, Maxwell equation-based computational model, the key findings of the computational study and a comparison with experimental results.

Mobile robot self-localization system using single webcam distance measurement technology in indoor environments.

PubMed

Li, I-Hsum; Chen, Ming-Chang; Wang, Wei-Yen; Su, Shun-Feng; Lai, To-Wen

2014-01-27

A single-webcam distance measurement technique for indoor robot localization is proposed in this paper. The proposed localization technique uses webcams that are available in an existing surveillance environment. The developed image-based distance measurement system (IBDMS) and parallel lines distance measurement system (PLDMS) have two merits. Firstly, only one webcam is required for estimating the distance. Secondly, the set-up of IBDMS and PLDMS is easy, which only one known-dimension rectangle pattern is needed, i.e., a ground tile. Some common and simple image processing techniques, i.e., background subtraction are used to capture the robot in real time. Thus, for the purposes of indoor robot localization, the proposed method does not need to use expensive high-resolution webcams and complicated pattern recognition methods but just few simple estimating formulas. From the experimental results, the proposed robot localization method is reliable and effective in an indoor environment.

Mobile Robot Self-Localization System Using Single Webcam Distance Measurement Technology in Indoor Environments

PubMed Central

Li, I-Hsum; Chen, Ming-Chang; Wang, Wei-Yen; Su, Shun-Feng; Lai, To-Wen

2014-01-01

A single-webcam distance measurement technique for indoor robot localization is proposed in this paper. The proposed localization technique uses webcams that are available in an existing surveillance environment. The developed image-based distance measurement system (IBDMS) and parallel lines distance measurement system (PLDMS) have two merits. Firstly, only one webcam is required for estimating the distance. Secondly, the set-up of IBDMS and PLDMS is easy, which only one known-dimension rectangle pattern is needed, i.e., a ground tile. Some common and simple image processing techniques, i.e., background subtraction are used to capture the robot in real time. Thus, for the purposes of indoor robot localization, the proposed method does not need to use expensive high-resolution webcams and complicated pattern recognition methods but just few simple estimating formulas. From the experimental results, the proposed robot localization method is reliable and effective in an indoor environment. PMID:24473282

Location-Driven Image Retrieval for Images Collected by a Mobile Robot

NASA Astrophysics Data System (ADS)

Tanaka, Kanji; Hirayama, Mitsuru; Okada, Nobuhiro; Kondo, Eiji

Mobile robot teleoperation is a method for a human user to interact with a mobile robot over time and distance. Successful teleoperation depends on how well images taken by the mobile robot are visualized to the user. To enhance the efficiency and flexibility of the visualization, an image retrieval system on such a robot’s image database would be very useful. The main difference of the robot’s image database from standard image databases is that various relevant images exist due to variety of viewing conditions. The main contribution of this paper is to propose an efficient retrieval approach, named location-driven approach, utilizing correlation between visual features and real world locations of images. Combining the location-driven approach with the conventional feature-driven approach, our goal can be viewed as finding an optimal classifier between relevant and irrelevant feature-location pairs. An active learning technique based on support vector machine is extended for this aim.

Image quality enhancement in low-light-level ghost imaging using modified compressive sensing method

NASA Astrophysics Data System (ADS)

Shi, Xiaohui; Huang, Xianwei; Nan, Suqin; Li, Hengxing; Bai, Yanfeng; Fu, Xiquan

2018-04-01

Detector noise has a significantly negative impact on ghost imaging at low light levels, especially for existing recovery algorithm. Based on the characteristics of the additive detector noise, a method named modified compressive sensing ghost imaging is proposed to reduce the background imposed by the randomly distributed detector noise at signal path. Experimental results show that, with an appropriate choice of threshold value, modified compressive sensing ghost imaging algorithm can dramatically enhance the contrast-to-noise ratio of the object reconstruction significantly compared with traditional ghost imaging and compressive sensing ghost imaging methods. The relationship between the contrast-to-noise ratio of the reconstruction image and the intensity ratio (namely, the average signal intensity to average noise intensity ratio) for the three reconstruction algorithms are also discussed. This noise suppression imaging technique will have great applications in remote-sensing and security areas.

A spectral k-means approach to bright-field cell image segmentation.

PubMed

Bradbury, Laura; Wan, Justin W L

2010-01-01

Automatic segmentation of bright-field cell images is important to cell biologists, but difficult to complete due to the complex nature of the cells in bright-field images (poor contrast, broken halo, missing boundaries). Standard approaches such as level set segmentation and active contours work well for fluorescent images where cells appear as round shape, but become less effective when optical artifacts such as halo exist in bright-field images. In this paper, we present a robust segmentation method which combines the spectral and k-means clustering techniques to locate cells in bright-field images. This approach models an image as a matrix graph and segment different regions of the image by computing the appropriate eigenvectors of the matrix graph and using the k-means algorithm. We illustrate the effectiveness of the method by segmentation results of C2C12 (muscle) cells in bright-field images.

A RONI Based Visible Watermarking Approach for Medical Image Authentication.

PubMed

Thanki, Rohit; Borra, Surekha; Dwivedi, Vedvyas; Borisagar, Komal

2017-08-09

Nowadays medical data in terms of image files are often exchanged between different hospitals for use in telemedicine and diagnosis. Visible watermarking being extensively used for Intellectual Property identification of such medical images, leads to serious issues if failed to identify proper regions for watermark insertion. In this paper, the Region of Non-Interest (RONI) based visible watermarking for medical image authentication is proposed. In this technique, to RONI of the cover medical image is first identified using Human Visual System (HVS) model. Later, watermark logo is visibly inserted into RONI of the cover medical image to get watermarked medical image. Finally, the watermarked medical image is compared with the original medical image for measurement of imperceptibility and authenticity of proposed scheme. The experimental results showed that this proposed scheme reduces the computational complexity and improves the PSNR when compared to many existing schemes.

High resolution x-ray microtomography of biological samples: Requirements and strategies for satisfying them

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

Loo, B.W. Jr.

High resolution x-ray microscopy has been made possible in recent years primarily by two new technologies: microfabricated diffractive lenses for soft x-rays with about 30-50 nm resolution, and high brightness synchrotron x-ray sources. X-ray microscopy occupies a special niche in the array of biological microscopic imaging methods. It extends the capabilities of existing techniques mainly in two areas: a previously unachievable combination of sub-visible resolution and multi-micrometer sample size, and new contrast mechanisms. Because of the soft x-ray wavelengths used in biological imaging (about 1-4 nm), XM is intermediate in resolution between visible light and electron microscopies. Similarly, the penetrationmore » depth of soft x-rays in biological materials is such that the ideal sample thickness for XM falls in the range of 0.25 - 10 {mu}m, between that of VLM and EM. XM is therefore valuable for imaging of intermediate level ultrastructure, requiring sub-visible resolutions, in intact cells and subcellular organelles, without artifacts produced by thin sectioning. Many of the contrast producing and sample preparation techniques developed for VLM and EM also work well with XM. These include, for example, molecule specific staining by antibodies with heavy metal or fluorescent labels attached, and sectioning of both frozen and plastic embedded tissue. However, there is also a contrast mechanism unique to XM that exists naturally because a number of elemental absorption edges lie in the wavelength range used. In particular, between the oxygen and carbon absorption edges (2.3 and 4.4 nm wavelength), organic molecules absorb photons much more strongly than does water, permitting element-specific imaging of cellular structure in aqueous media, with no artifically introduced contrast agents. For three-dimensional imaging applications requiring the capabilities of XM, an obvious extension of the technique would therefore be computerized x-ray microtomography (XMT).« less

Platform for Post-Processing Waveform-Based NDE

NASA Technical Reports Server (NTRS)

Roth, Don J.

2010-01-01

Signal- and image-processing methods are commonly needed to extract information from the waves, improve resolution of, and highlight defects in an image. Since some similarity exists for all waveform-based nondestructive evaluation (NDE) methods, it would seem that a common software platform containing multiple signal- and image-processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. NDE Wave & Image Processor Version 2.0 software provides a single, integrated signal- and image-processing and analysis environment for total NDE data processing and analysis. It brings some of the most useful algorithms developed for NDE over the past 20 years into a commercial-grade product. The software can import signal/spectroscopic data, image data, and image series data. This software offers the user hundreds of basic and advanced signal- and image-processing capabilities including esoteric 1D and 2D wavelet-based de-noising, de-trending, and filtering. Batch processing is included for signal- and image-processing capability so that an optimized sequence of processing operations can be applied to entire folders of signals, spectra, and images. Additionally, an extensive interactive model-based curve-fitting facility has been included to allow fitting of spectroscopy data such as from Raman spectroscopy. An extensive joint-time frequency module is included for analysis of non-stationary or transient data such as that from acoustic emission, vibration, or earthquake data.

Cardiovascular cine imaging and flow evaluation using Fast Interrupted Steady-State (FISS) magnetic resonance.

PubMed

Edelman, Robert R; Serhal, Ali; Pursnani, Amit; Pang, Jianing; Koktzoglou, Ioannis

2018-02-19

Existing cine imaging techniques rely on balanced steady-state free precession (bSSFP) or spoiled gradient-echo readouts, each of which has limitations. For instance, with bSSFP, artifacts occur from rapid through-plane flow and off-resonance effects. We hypothesized that a prototype cine technique, radial fast interrupted steady-state (FISS), could overcome these limitations. The technique was compared with standard cine bSSFP for cardiac function, coronary artery conspicuity, and aortic valve morphology. Given its advantageous properties, we further hypothesized that the cine FISS technique, in combination with arterial spin labeling (ASL), could provide an alternative to phase contrast for visualizing in-plane flow patterns within the aorta and branch vessels. The study was IRB-approved and subjects provided consent. Breath-hold cine FISS and bSSFP were acquired using similar imaging parameters. There was no significant difference in biplane left ventricular ejection fraction or cardiac image quality between the two techniques. Compared with cine bSSFP, cine FISS demonstrated a marked decrease in fat signal which improved conspicuity of the coronary arteries, while suppression of through-plane flow artifact on thin-slice cine FISS images improved visualization of the aortic valve. Banding artifacts in the subcutaneous tissues were reduced. In healthy subjects, dynamic flow patterns were well visualized in the aorta, coronary and renal arteries using cine FISS ASL, even when the slice was substantially thicker than the vessel diameter. Cine FISS demonstrates several benefits for cardiovascular imaging compared with cine bSSFP, including better suppression of fat signal and reduced artifacts from through-plane flow and off-resonance effects. The main drawback is a slight (~ 20%) decrease in temporal resolution. In addition, preliminary results suggest that cine FISS ASL provides a potential alternative to phase contrast techniques for in-plane flow quantification, while enabling an efficient, visually-appealing, semi-projective display of blood flow patterns throughout the course of an artery and its branches.

Automated prescription of oblique brain 3D magnetic resonance spectroscopic imaging.

PubMed

Ozhinsky, Eugene; Vigneron, Daniel B; Chang, Susan M; Nelson, Sarah J

2013-04-01

Two major difficulties encountered in implementing Magnetic Resonance Spectroscopic Imaging (MRSI) in a clinical setting are limited coverage and difficulty in prescription. The goal of this project was to automate completely the process of 3D PRESS MRSI prescription, including placement of the selection box, saturation bands and shim volume, while maximizing the coverage of the brain. The automated prescription technique included acquisition of an anatomical MRI image, optimization of the oblique selection box parameters, optimization of the placement of outer-volume suppression saturation bands, and loading of the calculated parameters into a customized 3D MRSI pulse sequence. To validate the technique and compare its performance with existing protocols, 3D MRSI data were acquired from six exams from three healthy volunteers. To assess the performance of the automated 3D MRSI prescription for patients with brain tumors, the data were collected from 16 exams from 8 subjects with gliomas. This technique demonstrated robust coverage of the tumor, high consistency of prescription and very good data quality within the T2 lesion. Copyright © 2012 Wiley Periodicals, Inc.

Lip boundary detection techniques using color and depth information

NASA Astrophysics Data System (ADS)

Kim, Gwang-Myung; Yoon, Sung H.; Kim, Jung H.; Hur, Gi Taek

2002-01-01

This paper presents our approach to using a stereo camera to obtain 3-D image data to be used to improve existing lip boundary detection techniques. We show that depth information as provided by our approach can be used to significantly improve boundary detection systems. Our system detects the face and mouth area in the image by using color, geometric location, and additional depth information for the face. Initially, color and depth information can be used to localize the face. Then we can determine the lip region from the intensity information and the detected eye locations. The system has successfully been used to extract approximate lip regions using RGB color information of the mouth area. Merely using color information is not robust because the quality of the results may vary depending on light conditions, background, and the human race. To overcome this problem, we used a stereo camera to obtain 3-D facial images. 3-D data constructed from the depth information along with color information can provide more accurate lip boundary detection results as compared to color only based techniques.

Emerging Network Storage Management Standards for Intelligent Data Storage Subsystems

NASA Technical Reports Server (NTRS)

Podio, Fernando; Vollrath, William; Williams, Joel; Kobler, Ben; Crouse, Don

1998-01-01

This paper discusses the need for intelligent storage devices and subsystems that can provide data integrity metadata, the content of the existing data integrity standard for optical disks and techniques and metadata to verify stored data on optical tapes developed by the Association for Information and Image Management (AIIM) Optical Tape Committee.

A perspective view of the plane mixing layer

NASA Technical Reports Server (NTRS)

Jimenez, J.; Cogollos, M.; Bernal, L. P.

1984-01-01

A three-dimensional model of the plane mixing layer is constructed by applying digital image processing and computer graphic techniques to laser fluorescent motion pictures of its transversal sections. A system of streamwise vortex pairs is shown to exist on top of the classical spanwise eddies. Its influence on mixing is examined.

Propagation phasor approach for holographic image reconstruction

PubMed Central

Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan

2016-01-01

To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears. PMID:26964671

Brain early infarct detection using gamma correction extreme-level eliminating with weighting distribution.

PubMed

Teh, V; Sim, K S; Wong, E K

2016-11-01

According to the statistic from World Health Organization (WHO), stroke is one of the major causes of death globally. Computed tomography (CT) scan is one of the main medical diagnosis system used for diagnosis of ischemic stroke. CT scan provides brain images in Digital Imaging and Communication in Medicine (DICOM) format. The presentation of CT brain images is mainly relied on the window setting (window center and window width), which converts an image from DICOM format into normal grayscale format. Nevertheless, the ordinary window parameter could not deliver a proper contrast on CT brain images for ischemic stroke detection. In this paper, a new proposed method namely gamma correction extreme-level eliminating with weighting distribution (GCELEWD) is implemented to improve the contrast on CT brain images. GCELEWD is capable of highlighting the hypodense region for diagnosis of ischemic stroke. The performance of this new proposed technique, GCELEWD, is compared with four of the existing contrast enhancement technique such as brightness preserving bi-histogram equalization (BBHE), dualistic sub-image histogram equalization (DSIHE), extreme-level eliminating histogram equalization (ELEHE), and adaptive gamma correction with weighting distribution (AGCWD). GCELEWD shows better visualization for ischemic stroke detection and higher values with image quality assessment (IQA) module. SCANNING 38:842-856, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Non-integer expansion embedding techniques for reversible image watermarking

NASA Astrophysics Data System (ADS)

Xiang, Shijun; Wang, Yi

2015-12-01

This work aims at reducing the embedding distortion of prediction-error expansion (PE)-based reversible watermarking. In the classical PE embedding method proposed by Thodi and Rodriguez, the predicted value is rounded to integer number for integer prediction-error expansion (IPE) embedding. The rounding operation makes a constraint on a predictor's performance. In this paper, we propose a non-integer PE (NIPE) embedding approach, which can proceed non-integer prediction errors for embedding data into an audio or image file by only expanding integer element of a prediction error while keeping its fractional element unchanged. The advantage of the NIPE embedding technique is that the NIPE technique can really bring a predictor into full play by estimating a sample/pixel in a noncausal way in a single pass since there is no rounding operation. A new noncausal image prediction method to estimate a pixel with four immediate pixels in a single pass is included in the proposed scheme. The proposed noncausal image predictor can provide better performance than Sachnev et al.'s noncausal double-set prediction method (where data prediction in two passes brings a distortion problem due to the fact that half of the pixels were predicted with the watermarked pixels). In comparison with existing several state-of-the-art works, experimental results have shown that the NIPE technique with the new noncausal prediction strategy can reduce the embedding distortion for the same embedding payload.

Dual-wavelength hybrid optoacoustic-ultrasound biomicroscopy for functional imaging of large-scale cerebral vascular networks.

PubMed

Rebling, Johannes; Estrada, Héctor; Gottschalk, Sven; Sela, Gali; Zwack, Michael; Wissmeyer, Georg; Ntziachristos, Vasilis; Razansky, Daniel

2018-04-19

A critical link exists between pathological changes of cerebral vasculature and diseases affecting brain function. Microscopic techniques have played an indispensable role in the study of neurovascular anatomy and functions. Yet, investigations are often hindered by suboptimal trade-offs between the spatiotemporal resolution, field-of-view (FOV) and type of contrast offered by the existing optical microscopy techniques. We present a hybrid dual-wavelength optoacoustic (OA) biomicroscope capable of rapid transcranial visualization of large-scale cerebral vascular networks. The system offers 3-dimensional views of the morphology and oxygenation status of the cerebral vasculature with single capillary resolution and a FOV exceeding 6 × 8 mm 2 , thus covering the entire cortical vasculature in mice. The large-scale OA imaging capacity is complemented by simultaneously acquired pulse-echo ultrasound (US) biomicroscopy scans of the mouse skull. The new approach holds great potential to provide better insights into cerebrovascular function and facilitate efficient studies into neurological and vascular abnormalities of the brain. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Rapid prototyping model for percutaneous nephrolithotomy training.

PubMed

Bruyère, Franck; Leroux, Cecile; Brunereau, Laurent; Lermusiaux, Patrick

2008-01-01

Rapid prototyping is a technique used for creating computer images in three dimensions more efficiently than classic techniques. Percutaneous nephrolithotomy (PCNL) is a popular method to remove kidney stones; however, broader use by the urologic community has been hampered by the morbidity associated with needle puncture to gain access to the renal calix (bleeding, pneumothorax, hydrothorax, inadvertent colon injury). A training model to improve technique and understanding of renal anatomy could improve complications related to renal puncture; however, no model currently exists for resident training. We created a training model using the rapid prototyping technique based on abdominal CT images of a patient scheduled to undergo PCNL. This allowed our staff and residents to train on the model before performing the operation. This model allowed anticipation of particular difficulties inherent to the patient's anatomy. After training, the procedure proceeded without complication, and the patient was discharged at postoperative day 1 without problems. We hypothesize that rapid prototyping could be useful for resident education, allowing the creation of numerous models for research and surgical training. In addition, we anticipate that experienced urologists could find this technique helpful in preparation for difficult PCNL operations.

Hyperspectral imaging for detection of arthritis: feasibility and prospects

NASA Astrophysics Data System (ADS)

Milanic, Matija; Paluchowski, Lukasz A.; Randeberg, Lise L.

2015-09-01

Rheumatoid arthritis (RA) is a disease that frequently leads to joint destruction. It has a high incidence rate worldwide, and the disease significantly reduces patients' quality of life. Detecting and treating inflammatory arthritis before structural damage to the joint has occurred is known to be essential for preventing patient disability and pain. Existing diagnostic technologies are expensive, time consuming, and require trained personnel to collect and interpret data. Optical techniques might be a fast, noninvasive alternative. Hyperspectral imaging (HSI) is a noncontact optical technique which provides both spectral and spatial information in one measurement. In this study, the feasibility of HSI in arthritis diagnostics was explored by numerical simulations and optimal imaging parameters were identified. Hyperspectral reflectance and transmission images of RA and normal human joint models were simulated using the Monte Carlo method. The spectral range was 600 to 1100 nm. Characteristic spatial patterns for RA joints and two spectral windows with transmission were identified. The study demonstrated that transmittance images of human joints could be used as one parameter for discrimination between arthritic and unaffected joints. The presented work shows that HSI is a promising imaging modality for the diagnostics and follow-up monitoring of arthritis in small joints.

Multiple hypothesis tracking for cluttered biological image sequences.

PubMed

Chenouard, Nicolas; Bloch, Isabelle; Olivo-Marin, Jean-Christophe

2013-11-01

In this paper, we present a method for simultaneously tracking thousands of targets in biological image sequences, which is of major importance in modern biology. The complexity and inherent randomness of the problem lead us to propose a unified probabilistic framework for tracking biological particles in microscope images. The framework includes realistic models of particle motion and existence and of fluorescence image features. For the track extraction process per se, the very cluttered conditions motivate the adoption of a multiframe approach that enforces tracking decision robustness to poor imaging conditions and to random target movements. We tackle the large-scale nature of the problem by adapting the multiple hypothesis tracking algorithm to the proposed framework, resulting in a method with a favorable tradeoff between the model complexity and the computational cost of the tracking procedure. When compared to the state-of-the-art tracking techniques for bioimaging, the proposed algorithm is shown to be the only method providing high-quality results despite the critically poor imaging conditions and the dense target presence. We thus demonstrate the benefits of advanced Bayesian tracking techniques for the accurate computational modeling of dynamical biological processes, which is promising for further developments in this domain.

Probabilistic images (PBIS): A concise image representation technique for multiple parameters

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

Wu, L.C.; Yeh, S.H.; Chen, Z.

1984-01-01

Based on m parametric images (PIs) derived from a dynamic series (DS), each pixel of DS is regarded as an m-dimensional vector. Given one set of normal samples (pixels) N and another of abnormal samples A, probability density functions (pdfs) of both sets are estimated. Any unknown sample is classified into N or A by calculating the probability of its being in the abnormal set using the Bayes' theorem. Instead of estimating the multivariate pdfs, a distance ratio transformation is introduced to map the m-dimensional sample space to one dimensional Euclidean space. Consequently, the image that localizes the regional abnormalitiesmore » is characterized by the probability of being abnormal. This leads to the new representation scheme of PBIs. Tc-99m HIDA study for detecting intrahepatic lithiasis (IL) was chosen as an example of constructing PBI from 3 parameters derived from DS and such a PBI was compared with those 3 PIs, namely, retention ratio image (RRI), peak time image (TNMAX) and excretion mean transit time image (EMTT). 32 normal subjects and 20 patients with proved IL were collected and analyzed. The resultant sensitivity and specificity of PBI were 97% and 98% respectively. They were superior to those of any of the 3 PIs: RRI (94/97), TMAX (86/88) and EMTT (94/97). Furthermore, the contrast of PBI was much better than that of any other image. This new image formation technique, based on multiple parameters, shows the functional abnormalities in a structural way. Its good contrast makes the interpretation easy. This technique is powerful compared to the existing parametric image method.« less

A sparsity-based iterative algorithm for reconstruction of micro-CT images from highly undersampled projection datasets obtained with a synchrotron X-ray source

NASA Astrophysics Data System (ADS)

Melli, S. Ali; Wahid, Khan A.; Babyn, Paul; Cooper, David M. L.; Gopi, Varun P.

2016-12-01

Synchrotron X-ray Micro Computed Tomography (Micro-CT) is an imaging technique which is increasingly used for non-invasive in vivo preclinical imaging. However, it often requires a large number of projections from many different angles to reconstruct high-quality images leading to significantly high radiation doses and long scan times. To utilize this imaging technique further for in vivo imaging, we need to design reconstruction algorithms that reduce the radiation dose and scan time without reduction of reconstructed image quality. This research is focused on using a combination of gradient-based Douglas-Rachford splitting and discrete wavelet packet shrinkage image denoising methods to design an algorithm for reconstruction of large-scale reduced-view synchrotron Micro-CT images with acceptable quality metrics. These quality metrics are computed by comparing the reconstructed images with a high-dose reference image reconstructed from 1800 equally spaced projections spanning 180°. Visual and quantitative-based performance assessment of a synthetic head phantom and a femoral cortical bone sample imaged in the biomedical imaging and therapy bending magnet beamline at the Canadian Light Source demonstrates that the proposed algorithm is superior to the existing reconstruction algorithms. Using the proposed reconstruction algorithm to reduce the number of projections in synchrotron Micro-CT is an effective way to reduce the overall radiation dose and scan time which improves in vivo imaging protocols.

Dynamic heart phantom with functional mitral and aortic valves

NASA Astrophysics Data System (ADS)

Vannelli, Claire; Moore, John; McLeod, Jonathan; Ceh, Dennis; Peters, Terry

2015-03-01

Cardiac valvular stenosis, prolapse and regurgitation are increasingly common conditions, particularly in an elderly population with limited potential for on-pump cardiac surgery. NeoChord©, MitraClipand numerous stent-based transcatheter aortic valve implantation (TAVI) devices provide an alternative to intrusive cardiac operations; performed while the heart is beating, these procedures require surgeons and cardiologists to learn new image-guidance based techniques. Developing these visual aids and protocols is a challenging task that benefits from sophisticated simulators. Existing models lack features needed to simulate off-pump valvular procedures: functional, dynamic valves, apical and vascular access, and user flexibility for different activation patterns such as variable heart rates and rapid pacing. We present a left ventricle phantom with these characteristics. The phantom can be used to simulate valvular repair and replacement procedures with magnetic tracking, augmented reality, fluoroscopy and ultrasound guidance. This tool serves as a platform to develop image-guidance and image processing techniques required for a range of minimally invasive cardiac interventions. The phantom mimics in vivo mitral and aortic valve motion, permitting realistic ultrasound images of these components to be acquired. It also has a physiological realistic left ventricular ejection fraction of 50%. Given its realistic imaging properties and non-biodegradable composition—silicone for tissue, water for blood—the system promises to reduce the number of animal trials required to develop image guidance applications for valvular repair and replacement. The phantom has been used in validation studies for both TAVI image-guidance techniques1, and image-based mitral valve tracking algorithms2.

A novel image registration approach via combining local features and geometric invariants

PubMed Central

Lu, Yan; Gao, Kun; Zhang, Tinghua; Xu, Tingfa

2018-01-01

Image registration is widely used in many fields, but the adaptability of the existing methods is limited. This work proposes a novel image registration method with high precision for various complex applications. In this framework, the registration problem is divided into two stages. First, we detect and describe scale-invariant feature points using modified computer vision-oriented fast and rotated brief (ORB) algorithm, and a simple method to increase the performance of feature points matching is proposed. Second, we develop a new local constraint of rough selection according to the feature distances. Evidence shows that the existing matching techniques based on image features are insufficient for the images with sparse image details. Then, we propose a novel matching algorithm via geometric constraints, and establish local feature descriptions based on geometric invariances for the selected feature points. Subsequently, a new price function is constructed to evaluate the similarities between points and obtain exact matching pairs. Finally, we employ the progressive sample consensus method to remove wrong matches and calculate the space transform parameters. Experimental results on various complex image datasets verify that the proposed method is more robust and significantly reduces the rate of false matches while retaining more high-quality feature points. PMID:29293595

GyneScan

PubMed Central

Acharya, U. Rajendra; Sree, S. Vinitha; Kulshreshtha, Sanjeev; Molinari, Filippo; Koh, Joel En Wei; Saba, Luca; Suri, Jasjit S.

2014-01-01

Ovarian cancer is the fifth highest cause of cancer in women and the leading cause of death from gynecological cancers. Accurate diagnosis of ovarian cancer from acquired images is dependent on the expertise and experience of ultrasonographers or physicians, and is therefore, associated with inter observer variabilities. Computer Aided Diagnostic (CAD) techniques use a number of different data mining techniques to automatically predict the presence or absence of cancer, and therefore, are more reliable and accurate. A review of published literature in the field of CAD based ovarian cancer detection indicates that many studies use ultrasound images as the base for analysis. The key objective of this work is to propose an effective adjunct CAD technique called GyneScan for ovarian tumor detection in ultrasound images. In our proposed data mining framework, we extract several texture features based on first order statistics, Gray Level Co-occurrence Matrix and run length matrix. The significant features selected using t-test are then used to train and test several supervised learning based classifiers such as Probabilistic Neural Networks (PNN), Support Vector Machine (SVM), Decision Tree (DT), k-Nearest Neighbor (KNN), and Naïve Bayes (NB). We evaluated the developed framework using 1300 benign and 1300 malignant images. Using 11 significant features in KNN/PNN classifiers, we were able to achieve 100% classification accuracy, sensitivity, specificity, and positive predictive value in detecting ovarian tumor. Even though more validation using larger databases would better establish the robustness of our technique, the preliminary results are promising. This technique could be used as a reliable adjunct method to existing imaging modalities to provide a more confident second opinion on the presence/absence of ovarian tumor. PMID:24325128

FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis.

PubMed

Wan, Yong; Otsuna, Hideo; Holman, Holly A; Bagley, Brig; Ito, Masayoshi; Lewis, A Kelsey; Colasanto, Mary; Kardon, Gabrielle; Ito, Kei; Hansen, Charles

2017-05-26

Image segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame. Existing tools built on volume visualization pipelines for single channel or red-green-blue (RGB) channels have become inadequate for the new challenges of fluorescence microscopy. For a three-dimensional atlas of the insect nervous system, hundreds of volume channels are rendered simultaneously, whereas fluorescence intensity values from each channel need to be preserved for versatile adjustment and analysis. Although several existing tools have incorporated support of multichannel data using various strategies, the lack of a flexible design has made true many-channel visualization and analysis unavailable. The most common practice for many-channel volume data presentation is still converting and rendering pseudosurfaces, which are inaccurate for both qualitative and quantitative evaluations. Here, we present an alternative design strategy that accommodates the visualization and analysis of about 100 volume channels, each of which can be interactively adjusted, selected, and segmented using freehand tools. Our multichannel visualization includes a multilevel streaming pipeline plus a triple-buffer compositing technique. Our method also preserves original fluorescence intensity values on graphics hardware, a crucial feature that allows graphics-processing-unit (GPU)-based processing for interactive data analysis, such as freehand segmentation. We have implemented the design strategies as a thorough restructuring of our original tool, FluoRender. The redesign of FluoRender not only maintains the existing multichannel capabilities for a greatly extended number of volume channels, but also enables new analysis functions for many-channel data from emerging biomedical-imaging techniques.

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.

Digital spiral-slit for bi-photon imaging

NASA Astrophysics Data System (ADS)

McLaren, Melanie; Forbes, Andrew

2017-04-01

Quantum ghost imaging using entangled photon pairs has become a popular field of investigation, highlighting the quantum correlation between the photon pairs. We introduce a technique using spatial light modulators encoded with digital holograms to recover both the amplitude and the phase of the digital object. Down-converted photon pairs are entangled in the orbital angular momentum basis, and are commonly measured using spiral phase holograms. Consequently, by encoding a spiral ring-slit hologram into the idler arm, and varying it radially we can simultaneously recover the phase and amplitude of the object in question. We demonstrate that a good correlation between the encoded field function and the reconstructed images exists.

Multichannel blind deconvolution of spatially misaligned images.

PubMed

Sroubek, Filip; Flusser, Jan

2005-07-01

Existing multichannel blind restoration techniques assume perfect spatial alignment of channels, correct estimation of blur size, and are prone to noise. We developed an alternating minimization scheme based on a maximum a posteriori estimation with a priori distribution of blurs derived from the multichannel framework and a priori distribution of original images defined by the variational integral. This stochastic approach enables us to recover the blurs and the original image from channels severely corrupted by noise. We observe that the exact knowledge of the blur size is not necessary, and we prove that translation misregistration up to a certain extent can be automatically removed in the restoration process.

Off-resonance suppression for multispectral MR imaging near metallic implants.

PubMed

den Harder, J Chiel; van Yperen, Gert H; Blume, Ulrike A; Bos, Clemens

2015-01-01

Metal artifact reduction in MRI within clinically feasible scan-times without through-plane aliasing. Existing metal artifact reduction techniques include view angle tilting (VAT), which resolves in-plane distortions, and multispectral imaging (MSI) techniques, such as slice encoding for metal artifact correction (SEMAC) and multi-acquisition with variable resonances image combination (MAVRIC), that further reduce image distortions, but significantly increase scan-time. Scan-time depends on anatomy size and anticipated total spectral content of the signal. Signals outside the anticipated spatial region may cause through-plane back-folding. Off-resonance suppression (ORS), using different gradient amplitudes for excitation and refocusing, is proposed to provide well-defined spatial-spectral selectivity in MSI to allow scan-time reduction and flexibility of scan-orientation. Comparisons of MSI techniques with and without ORS were made in phantom and volunteer experiments. Off-resonance suppressed SEMAC (ORS-SEMAC) and outer-region suppressed MAVRIC (ORS-MAVRIC) required limited through-plane phase encoding steps compared with original MSI. Whereas SEMAC (scan time: 5'46") and MAVRIC (4'12") suffered from through-plane aliasing, ORS-SEMAC and ORS-MAVRIC allowed alias-free imaging in the same scan-times. ORS can be used in MSI to limit the selected spatial-spectral region and contribute to metal artifact reduction in clinically feasible scan-times while avoiding slice aliasing. © 2014 Wiley Periodicals, Inc.

Photon-efficient super-resolution laser radar

NASA Astrophysics Data System (ADS)

Shin, Dongeek; Shapiro, Jeffrey H.; Goyal, Vivek K.

2017-08-01

The resolution achieved in photon-efficient active optical range imaging systems can be low due to non-idealities such as propagation through a diffuse scattering medium. We propose a constrained optimization-based frame- work to address extremes in scarcity of photons and blurring by a forward imaging kernel. We provide two algorithms for the resulting inverse problem: a greedy algorithm, inspired by sparse pursuit algorithms; and a convex optimization heuristic that incorporates image total variation regularization. We demonstrate that our framework outperforms existing deconvolution imaging techniques in terms of peak signal-to-noise ratio. Since our proposed method is able to super-resolve depth features using small numbers of photon counts, it can be useful for observing fine-scale phenomena in remote sensing through a scattering medium and through-the-skin biomedical imaging applications.

Interference Mitigation Effects on Synthetic Aperture Radar Coherent Data Products

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

Musgrove, Cameron

2014-05-01

For synthetic aperture radar image products interference can degrade the quality of the images while techniques to mitigate the interference also reduce the image quality. Usually the radar system designer will try to balance the amount of mitigation for the amount of interference to optimize the image quality. This may work well for many situations, but coherent data products derived from the image products are more sensitive than the human eye to distortions caused by interference and mitigation of interference. This dissertation examines the e ect that interference and mitigation of interference has upon coherent data products. An improvement tomore » the standard notch mitigation is introduced, called the equalization notch. Other methods are suggested to mitigation interference while improving the quality of coherent data products over existing methods.« less

Three-dimensional fluorescent microscopy via simultaneous illumination and detection at multiple planes.

PubMed

Ma, Qian; Khademhosseinieh, Bahar; Huang, Eric; Qian, Haoliang; Bakowski, Malina A; Troemel, Emily R; Liu, Zhaowei

2016-08-16

The conventional optical microscope is an inherently two-dimensional (2D) imaging tool. The objective lens, eyepiece and image sensor are all designed to capture light emitted from a 2D 'object plane'. Existing technologies, such as confocal or light sheet fluorescence microscopy have to utilize mechanical scanning, a time-multiplexing process, to capture a 3D image. In this paper, we present a 3D optical microscopy method based upon simultaneously illuminating and detecting multiple focal planes. This is implemented by adding two diffractive optical elements to modify the illumination and detection optics. We demonstrate that the image quality of this technique is comparable to conventional light sheet fluorescent microscopy with the advantage of the simultaneous imaging of multiple axial planes and reduced number of scans required to image the whole sample volume.

ACM-based automatic liver segmentation from 3-D CT images by combining multiple atlases and improved mean-shift techniques.

PubMed

Ji, Hongwei; He, Jiangping; Yang, Xin; Deklerck, Rudi; Cornelis, Jan

2013-05-01

In this paper, we present an autocontext model(ACM)-based automatic liver segmentation algorithm, which combines ACM, multiatlases, and mean-shift techniques to segment liver from 3-D CT images. Our algorithm is a learning-based method and can be divided into two stages. At the first stage, i.e., the training stage, ACM is performed to learn a sequence of classifiers in each atlas space (based on each atlas and other aligned atlases). With the use of multiple atlases, multiple sequences of ACM-based classifiers are obtained. At the second stage, i.e., the segmentation stage, the test image will be segmented in each atlas space by applying each sequence of ACM-based classifiers. The final segmentation result will be obtained by fusing segmentation results from all atlas spaces via a multiclassifier fusion technique. Specially, in order to speed up segmentation, given a test image, we first use an improved mean-shift algorithm to perform over-segmentation and then implement the region-based image labeling instead of the original inefficient pixel-based image labeling. The proposed method is evaluated on the datasets of MICCAI 2007 liver segmentation challenge. The experimental results show that the average volume overlap error and the average surface distance achieved by our method are 8.3% and 1.5 m, respectively, which are comparable to the results reported in the existing state-of-the-art work on liver segmentation.

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography

NASA Astrophysics Data System (ADS)

Allec, N.; Abbaszadeh, S.; Scott, C. C.; Lewin, J. M.; Karim, K. S.

2012-12-01

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

Including the effect of motion artifacts in noise and performance analysis of dual-energy contrast-enhanced mammography.

PubMed

Allec, N; Abbaszadeh, S; Scott, C C; Lewin, J M; Karim, K S

2012-12-21

In contrast-enhanced mammography (CEM), the dual-energy dual-exposure technique, which can leverage existing conventional mammography infrastructure, relies on acquiring the low- and high-energy images using two separate exposures. The finite time between image acquisition leads to motion artifacts in the combined image. Motion artifacts can lead to greater anatomical noise in the combined image due to increased mismatch of the background tissue in the images to be combined, however the impact has not yet been quantified. In this study we investigate a method to include motion artifacts in the dual-energy noise and performance analysis. The motion artifacts are included via an extended cascaded systems model. To validate the model, noise power spectra of a previous dual-energy clinical study are compared to that of the model. The ideal observer detectability is used to quantify the effect of motion artifacts on tumor detectability. It was found that the detectability can be significantly degraded when motion is present (e.g., detectability of 2.5 mm radius tumor decreased by approximately a factor of 2 for translation motion on the order of 1000 μm). The method presented may be used for a more comprehensive theoretical noise and performance analysis and fairer theoretical performance comparison between dual-exposure techniques, where motion artifacts are present, and single-exposure techniques, where low- and high-energy images are acquired simultaneously and motion artifacts are absent.

A compressed sensing X-ray camera with a multilayer architecture

NASA Astrophysics Data System (ADS)

Wang, Zhehui; Iaroshenko, O.; Li, S.; Liu, T.; Parab, N.; Chen, W. W.; Chu, P.; Kenyon, G. T.; Lipton, R.; Sun, K.-X.

2018-01-01

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.

Lifting scheme-based method for joint coding 3D stereo digital cinema with luminace correction and optimized prediction

NASA Astrophysics Data System (ADS)

Darazi, R.; Gouze, A.; Macq, B.

2009-01-01

Reproducing a natural and real scene as we see in the real world everyday is becoming more and more popular. Stereoscopic and multi-view techniques are used for this end. However due to the fact that more information are displayed requires supporting technologies such as digital compression to ensure the storage and transmission of the sequences. In this paper, a new scheme for stereo image coding is proposed. The original left and right images are jointly coded. The main idea is to optimally exploit the existing correlation between the two images. This is done by the design of an efficient transform that reduces the existing redundancy in the stereo image pair. This approach was inspired by Lifting Scheme (LS). The novelty in our work is that the prediction step is been replaced by an hybrid step that consists in disparity compensation followed by luminance correction and an optimized prediction step. The proposed scheme can be used for lossless and for lossy coding. Experimental results show improvement in terms of performance and complexity compared to recently proposed methods.

An Efficient Framework for Compressed Sensing Reconstruction of Highly Accelerated Dynamic Cardiac MRI

NASA Astrophysics Data System (ADS)

Ting, Samuel T.

The research presented in this work seeks to develop, validate, and deploy practical techniques for improving diagnosis of cardiovascular disease. In the philosophy of biomedical engineering, we seek to identify an existing medical problem having significant societal and economic effects and address this problem using engineering approaches. Cardiovascular disease is the leading cause of mortality in the United States, accounting for more deaths than any other major cause of death in every year since 1900 with the exception of the year 1918. Cardiovascular disease is estimated to account for almost one-third of all deaths in the United States, with more than 2150 deaths each day, or roughly 1 death every 40 seconds. In the past several decades, a growing array of imaging modalities have proven useful in aiding the diagnosis and evaluation of cardiovascular disease, including computed tomography, single photon emission computed tomography, and echocardiography. In particular, cardiac magnetic resonance imaging is an excellent diagnostic tool that can provide within a single exam a high quality evaluation of cardiac function, blood flow, perfusion, viability, and edema without the use of ionizing radiation. The scope of this work focuses on the application of engineering techniques for improving imaging using cardiac magnetic resonance with the goal of improving the utility of this powerful imaging modality. Dynamic cine imaging, or the capturing of movies of a single slice or volume within the heart or great vessel region, is used in nearly every cardiac magnetic resonance imaging exam, and adequate evaluation of cardiac function and morphology for diagnosis and evaluation of cardiovascular disease depends heavily on both the spatial and temporal resolution as well as the image quality of the reconstruction cine images. This work focuses primarily on image reconstruction techniques utilized in cine imaging; however, the techniques discussed are also relevant to other dynamic and static imaging techniques based on cardiac magnetic resonance. Conventional segmented techniques for cardiac cine imaging require breath-holding as well as regular cardiac rhythm, and can be time-consuming to acquire. Inadequate breath-holding or irregular cardiac rhythm can result in completely non-diagnostic images, limiting the utility of these techniques in a significant patient population. Real-time single-shot cardiac cine imaging enables free-breathing acquisition with significantly shortened imaging time and promises to significantly improve the utility of cine imaging for diagnosis and evaluation of cardiovascular disease. However, utility of real-time cine images depends heavily on the successful reconstruction of final cine images from undersampled data. Successful reconstruction of images from more highly undersampled data results directly in images exhibiting finer spatial and temporal resolution provided that image quality is sufficient. This work focuses primarily on the development, validation, and deployment of practical techniques for enabling the reconstruction of real-time cardiac cine images at the spatial and temporal resolutions and image quality needed for diagnostic utility. Particular emphasis is placed on the development of reconstruction approaches resulting in with short computation times that can be used in the clinical environment. Specifically, the use of compressed sensing signal recovery techniques is considered; such techniques show great promise in allowing successful reconstruction of highly undersampled data. The scope of this work concerns two primary topics related to signal recovery using compressed sensing: (1) long reconstruction times of these techniques, and (2) improved sparsity models for signal recovery from more highly undersampled data. Both of these aspects are relevant to the practical application of compressed sensing techniques in the context of improving image reconstruction of real-time cardiac cine images. First, algorithmic and implementational approaches are proposed for reducing the computational time for a compressed sensing reconstruction framework. Specific optimization algorithms based on the fast iterative/shrinkage algorithm (FISTA) are applied in the context of real-time cine image reconstruction to achieve efficient per-iteration computation time. Implementation within a code framework utilizing commercially available graphics processing units (GPUs) allows for practical and efficient implementation directly within the clinical environment. Second, patch-based sparsity models are proposed to enable compressed sensing signal recovery from highly undersampled data. Numerical studies demonstrate that this approach can help improve image quality at higher undersampling ratios, enabling real-time cine imaging at higher acceleration rates. In this work, it is shown that these techniques yield a holistic framework for achieving efficient reconstruction of real-time cine images with spatial and temporal resolution sufficient for use in the clinical environment. A thorough description of these techniques from both a theoretical and practical view is provided - both of which may be of interest to the reader in terms of future work.

High-resolution label-free vascular imaging using a commercial, clinically approved dermatological OCT scanner

NASA Astrophysics Data System (ADS)

Byers, R. A.; Tozer, G.; Brown, N. J.; Matcher, S. J.

2016-02-01

Background and Aim: Recently developed decorrelative techniques such as speckle-variance optical coherence tomography (svOCT) have demonstrated non-invasive depth-resolved imaging of the microcirculation in-vivo. However, bulk tissue motion (BTM) originating from the subject's breathing or heartbeat remains problematic at low imaging speeds, often resulting in full frame decorrelation and a loss of vascular contrast. The aim of this study was to build upon existing svOCT techniques through utilisation of a commercially available, probe-based VivoSight OCT system running at 20 kHz Axial-scan rate. Methods and results: Custom four-dimensional scanning strategies were developed and utilised in order to maximise the interframe correlation during image acquisition. Volumes of structural OCT data were collected from various anatomical regions and processed using the aforementioned svOCT algorithm to reveal angiographic information. Following data collection, three dimensional image registration and novel filtering algorithms were applied to each volume in order to ensure that BTM artefacts were sufficiently suppressed. This enabled accurate visualisation of the microcirculation within the papillary dermis, to a depth of approximately 2mm. Applications of this technique, including quantitative capillary loop density measurement and visualisation of wound healing are demonstrated and enhanced through widefield mosaicing of the svOCT data. Conclusions: Non-invasive microcirculation imaging using an FDA 510(k) approved OCT scanner such as the VivoSight allows direct clinical utilisation of these techniques, in particular for the pathological analysis of skin diseases. This research was supported by BBSRC Doctoral Training Grant: BB/F016840/1. The authors also gratefully acknowledge the use of equipment funded by MRC grant: MR/L012669/1.

Diffusion-weighted imaging in cancer: Physical foundations and applications of Restriction Spectrum Imaging

PubMed Central

White, Nathan S.; McDonald, Carrie; Farid, Niky; Kuperman, Josh; Karow, David; Schenker-Ahmed, Natalie M.; Bartsch, Hauke; Rakow-Penner, Rebecca; Holland, Dominic; Shabaik, Ahmed; Bjørnerud, Atle; Hope, Tuva; Hattangadi-Gluth, Jona; Liss, Michael; Parsons, J. Kellogg; Chen, Clark C.; Raman, Steve; Margolis, Daniel; Reiter, Robert E.; Marks, Leonard; Kesari, Santosh; Mundt, Arno J.; Kane, Chris J.; Carter, Bob S.; Bradley, William G.; Dale, Anders M.

2014-01-01

Diffusion weighted imaging (DWI) has been at the forefront of cancer imaging since the early 2000’s. Prior to its application in clinical oncology, this powerful technique had already achieved widespread recognition due to its utility in the diagnosis of cerebral infarction. Following this initial success, the ability of DWI to detect inherent tissue contrast began to be exploited in the field of oncology. Although the initial oncologic applications for tumor detection and characterization, assessing treatment response, and predicting survival were primarily in the field of neuro-oncology, the scope of DWI has since broadened to include oncologic imaging of the prostate gland, breast, and liver. Despite its growing success and application, misconceptions as to the underlying physical basis of the DWI signal exist among researchers and clinicians alike. In this review, we provide a detailed explanation of the biophysical basis of diffusion contrast, emphasizing the difference between hindered and restricted diffusion, and elucidating how diffusion parameters in tissue are derived from the measurements via the diffusion model. We describe one advanced DWI modeling technique, called Restriction Spectrum Imaging (RSI). This technique offers a more direct in vivo measure of tumor cells, due to its ability to distinguish separable pools of water within tissue based on their intrinsic diffusion characteristics. Using RSI as an example, we then highlight the ability of advanced DWI techniques to address key clinical challenges in neuro-oncology, including improved tumor conspicuity, distinguishing actual response to therapy from pseudoresponse, and delineation of white matter tracts in regions of peritumoral edema. We also discuss how RSI, combined with new methods for correction of spatial distortions inherent diffusion MRI scans, may enable more precise spatial targeting of lesions, with implications for radiation oncology, and surgical planning. PMID:25183788

Automated Segmentation of Nuclei in Breast Cancer Histopathology Images.

PubMed

Paramanandam, Maqlin; O'Byrne, Michael; Ghosh, Bidisha; Mammen, Joy John; Manipadam, Marie Therese; Thamburaj, Robinson; Pakrashi, Vikram

2016-01-01

The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods-Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets.

Automated Segmentation of Nuclei in Breast Cancer Histopathology Images

PubMed Central

Paramanandam, Maqlin; O’Byrne, Michael; Ghosh, Bidisha; Mammen, Joy John; Manipadam, Marie Therese; Thamburaj, Robinson; Pakrashi, Vikram

2016-01-01

The process of Nuclei detection in high-grade breast cancer images is quite challenging in the case of image processing techniques due to certain heterogeneous characteristics of cancer nuclei such as enlarged and irregularly shaped nuclei, highly coarse chromatin marginalized to the nuclei periphery and visible nucleoli. Recent reviews state that existing techniques show appreciable segmentation accuracy on breast histopathology images whose nuclei are dispersed and regular in texture and shape; however, typical cancer nuclei are often clustered and have irregular texture and shape properties. This paper proposes a novel segmentation algorithm for detecting individual nuclei from Hematoxylin and Eosin (H&E) stained breast histopathology images. This detection framework estimates a nuclei saliency map using tensor voting followed by boundary extraction of the nuclei on the saliency map using a Loopy Back Propagation (LBP) algorithm on a Markov Random Field (MRF). The method was tested on both whole-slide images and frames of breast cancer histopathology images. Experimental results demonstrate high segmentation performance with efficient precision, recall and dice-coefficient rates, upon testing high-grade breast cancer images containing several thousand nuclei. In addition to the optimal performance on the highly complex images presented in this paper, this method also gave appreciable results in comparison with two recently published methods—Wienert et al. (2012) and Veta et al. (2013), which were tested using their own datasets. PMID:27649496

Compressive Sampling based Image Coding for Resource-deficient Visual Communication.

PubMed

Liu, Xianming; Zhai, Deming; Zhou, Jiantao; Zhang, Xinfeng; Zhao, Debin; Gao, Wen

2016-04-14

In this paper, a new compressive sampling based image coding scheme is developed to achieve competitive coding efficiency at lower encoder computational complexity, while supporting error resilience. This technique is particularly suitable for visual communication with resource-deficient devices. At the encoder, compact image representation is produced, which is a polyphase down-sampled version of the input image; but the conventional low-pass filter prior to down-sampling is replaced by a local random binary convolution kernel. The pixels of the resulting down-sampled pre-filtered image are local random measurements and placed in the original spatial configuration. The advantages of local random measurements are two folds: 1) preserve high-frequency image features that are otherwise discarded by low-pass filtering; 2) remain a conventional image and can therefore be coded by any standardized codec to remove statistical redundancy of larger scales. Moreover, measurements generated by different kernels can be considered as multiple descriptions of the original image and therefore the proposed scheme has the advantage of multiple description coding. At the decoder, a unified sparsity-based soft-decoding technique is developed to recover the original image from received measurements in a framework of compressive sensing. Experimental results demonstrate that the proposed scheme is competitive compared with existing methods, with a unique strength of recovering fine details and sharp edges at low bit-rates.

4K x 2K pixel color video pickup system

NASA Astrophysics Data System (ADS)

Sugawara, Masayuki; Mitani, Kohji; Shimamoto, Hiroshi; Fujita, Yoshihiro; Yuyama, Ichiro; Itakura, Keijirou

1998-12-01

This paper describes the development of an experimental super- high-definition color video camera system. During the past several years there has been much interest in super-high- definition images as the next generation image media. One of the difficulties in implementing a super-high-definition motion imaging system is constructing the image-capturing section (camera). Even the state-of-the-art semiconductor technology can not realize the image sensor which has enough pixels and output data rate for super-high-definition images. The present study is an attempt to fill the gap in this respect. The authors intend to solve the problem by using new imaging method in which four HDTV sensors are attached on a new color separation optics so that their pixel sample pattern forms checkerboard pattern. A series of imaging experiments demonstrate that this technique is an effective approach to capturing super-high-definition moving images in the present situation where no image sensors exist for such images.

Graphene Nanopore Support System for Simultaneous High-Resolution AFM Imaging and Conductance Measurements

PubMed Central

2015-01-01

Accurately defining the nanoporous structure and sensing the ionic flow across nanoscale pores in thin films and membranes has a wide range of applications, including characterization of biological ion channels and receptors, DNA sequencing, molecule separation by nanoparticle films, sensing by block co-polymers films, and catalysis through metal–organic frameworks. Ionic conductance through nanopores is often regulated by their 3D structures, a relationship that can be accurately determined only by their simultaneous measurements. However, defining their structure–function relationships directly by any existing techniques is still not possible. Atomic force microscopy (AFM) can image the structures of these pores at high resolution in an aqueous environment, and electrophysiological techniques can measure ion flow through individual nanoscale pores. Combining these techniques is limited by the lack of nanoscale interfaces. We have designed a graphene-based single-nanopore support (∼5 nm thick with ∼20 nm pore diameter) and have integrated AFM imaging and ionic conductance recording using our newly designed double-chamber recording system to study an overlaid thin film. The functionality of this integrated system is demonstrated by electrical recording (<10 pS conductance) of suspended lipid bilayers spanning a nanopore and simultaneous AFM imaging of the bilayer. PMID:24581087

Differential X-ray phase contrast tomography of Alzheimer plaques in mouse models: perspectives for drug development and clinical imaging techniques

NASA Astrophysics Data System (ADS)

Pinzer, B. R.; Cacquevel, M.; Modregger, P.; Thuering, T.; Stampanoni, M.

2013-05-01

Alzheimer's disease (AD) is a looming threat on an ever-ageing population, with devastating effects on the human intellect. A particular characteristic lesion — the extracellular amyloid plaque — accumulates in the brain of AD patients during the course of the disease, and could therefore be used to monitor the progression of the disease, years before the first neurological symptoms appear. In addition, strategies for drug intervention in AD are often based on amyloid reduction, since amyloid plaques are hypothesized to be involved in a chain of reactions leading to the death of neurons. Developments in both fields would benefit from a microscopic technique that is capable of single plaque imaging, ideally in 3D. While such a non-destructive, single-plaque imaging technique does not yet exist for humans, it has been recently shown that synchrotron based differential X-ray phase contrast imaging can be used to visualize individual plaques at μm resolution in mouse models of AD ex-vivo. This method, which relies on a grating interferometer to measure refraction angles induced by fluctuations in the refractive index, yields a precise three-dimensional distribution of single plaques. These data could not only improve the understanding of the evolution of AD or the effectiveness of drugs, but could also help to improve reliable markers for current and future non-invasive clinical imaging techniques. In particular, validation of PET markers with small animal models could be rapidly carried out by co-registration of PET and DPC signals.

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

Imaging the inside of thick structures using cosmic rays

DOE PAGES

Guardincerri, E.; Durham, J. M.; Morris, C.; ...

2016-01-01

Here, we present a new method to image reinforcement elements inside thick structures and the results of a demonstration measurement performed on a mock-up wall built at Los Alamos National Laboratory. The method, referred to as “multiple scattering muon radiography”, relies on the use of cosmic-ray muons as probes. Our work was performed to prove the viability of the technique as a means to image the interior of the dome of Florence Cathedral Santa Maria del Fiore, one of the UNESCO World Heritage sites and among the highest profile buildings in existence. This result shows the effectiveness of the techniquemore » as a tool to radiograph thick structures and image denser object inside them.« less

Earth resources sensor data handling system: NASA JSC version

NASA Technical Reports Server (NTRS)

1974-01-01

The design of the NASA JSC data handling system is presented. Data acquisition parameters and computer display formats and the flow of image data through the system, with recommendations for improving system efficiency are discussed along with modifications to existing data handling procedures which will allow utilization of data duplication techniques and the accurate identification of imagery.

The effects of water and lipids on NIR optical breast measurements

NASA Astrophysics Data System (ADS)

Cerussi, Albert E.; Bevilacqua, Frederic; Shah, Natasha; Jakubowski, Dorota B.; Berger, Andrew J.; Lanning, Ryan M.; Tromberg, Bruce J.

2001-06-01

Near infrared diffuse optical spectroscopy and imaging may enhance existing technologies for breast cancer screening, diagnosis, and treatment. NIR spectroscopy yields quantitative functional information that cannot be obtained with other non-invasive radiological techniques. In this study we focused upon the origins of this contrast in healthy breast, especially from water and lipids.

An overview of computer vision

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1982-01-01

An overview of computer vision is provided. Image understanding and scene analysis are emphasized, and pertinent aspects of pattern recognition are treated. The basic approach to computer vision systems, the techniques utilized, applications, the current existing systems and state-of-the-art issues and research requirements, who is doing it and who is funding it, and future trends and expectations are reviewed.

A novel technique to measure intensity fluctuations in EUV images and to detect coronal sound waves nearby active regions

NASA Astrophysics Data System (ADS)

Stenborg, G.; Marsch, E.; Vourlidas, A.; Howard, R.; Baldwin, K.

2011-02-01

Context. In the past years, evidence for the existence of outward-moving (Doppler blue-shifted) plasma and slow-mode magneto-acoustic propagating waves in various magnetic field structures (loops in particular) in the solar corona has been found in ultraviolet images and spectra. Yet their origin and possible connection to and importance for the mass and energy supply to the corona and solar wind is still unclear. There has been increasing interest in this problem thanks to the high-resolution observations available from the extreme ultraviolet (EUV) imagers on the Solar TErrestrial RElationships Observatory (STEREO) and the EUV spectrometer on the Hinode mission. Aims: Flows and waves exist in the corona, and their signatures appear in EUV imaging observations but are extremely difficult to analyse quantitatively because of their weak intensity. Hence, such information is currently available mostly from spectroscopic observations that are restricted in their spatial and temporal coverage. To understand the nature and origin of these fluctuations, imaging observations are essential. Here, we present measurements of the speed of intensity fluctuations observed along apparently open field lines with the Extreme UltraViolet Imagers (EUVI) onboard the STEREO mission. One aim of our paper is to demonstrate that we can make reliable kinematic measurements from these EUV images, thereby complementing and extending the spectroscopic measurements and opening up the full corona for such an analysis. Another aim is to examine the assumptions that lead to flow versus wave interpretation for these fluctuations. Methods: We have developed a novel image-processing method by fusing well established techniques for the kinematic analysis of coronal mass ejections (CME) with standard wavelet analysis. The power of our method lies with its ability to recover weak intensity fluctuations along individual magnetic structures at any orientation , anywhere within the full solar disk , and using standard synoptic observing sequences (cadence <3 min) without the need for special observation plans. Results: Using information from both EUVI imagers, we obtained wave phase speeds with values on the order of 60-90 km s-1, compatible with those obtained by other previous measurements. Moreover, we studied the periodicity of the observed fluctuations and established a predominance of a 16-min period, and other periods that seem to be multiples of an underlying 8-min period. Conclusions: The validation of our analysis technique opens up new possibilities for the study of coronal flows and waves, by extending it to the full disk and to a larger number of coronal structures than has been possible previously. It opens up a new scientific capability for the EUV observations from the recently launched Solar Dynamics Observatory. Here we clearly establish the ubiquitous existence of sound waves which continuously propagate along apparently open magnetic field lines. Movies 1 and 2 (Figs. 12 and 13) are only available in electronic form at http://www.aanda.org

Processing MALDI mass spectra to improve mass spectral direct tissue analysis

NASA Astrophysics Data System (ADS)

Norris, Jeremy L.; Cornett, Dale S.; Mobley, James A.; Andersson, Malin; Seeley, Erin H.; Chaurand, Pierre; Caprioli, Richard M.

2007-02-01

Profiling and imaging biological specimens using MALDI mass spectrometry has significant potential to contribute to our understanding and diagnosis of disease. The technique is efficient and high-throughput providing a wealth of data about the biological state of the sample from a very simple and direct experiment. However, in order for these techniques to be put to use for clinical purposes, the approaches used to process and analyze the data must improve. This study examines some of the existing tools to baseline subtract, normalize, align, and remove spectral noise for MALDI data, comparing the advantages of each. A preferred workflow is presented that can be easily implemented for data in ASCII format. The advantages of using such an approach are discussed for both molecular profiling and imaging mass spectrometry.

Pilot Study to Confirm that Fat and Liver can be Distinguished by Spectroscopic Tissue Response on a Medipix-All-Resolution System-CT (MARS-CT)

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

Berg, Kyra B.; Anderson, Nigel G.; Butler, Alexandra P.

2009-07-23

NAFLD, liver component of the 'metabolic' syndrome, has become the most common liver disease in western nations. Non-invasive imaging techniques exist, but have limitations, especially in detection and quantification of mild to moderate fatty liver. In this pilot study, we produced attenuation curves from biomedical-quality projection images of liver and fat using the MARS spectroscopic-CT scanner. Difficulties obtaining attenuation spectra after reconstruction demonstrated that standard reconstruction programs do not preserve spectral information.

Pilot Study to Confirm that Fat and Liver can be Distinguished by Spectroscopic Tissue Response on a Medipix-All-Resolution System-CT (MARS-CT)

NASA Astrophysics Data System (ADS)

Berg, Kyra B.; Carr, James M.; Clark, Michael J.; Cook, Nick J.; Anderson, Nigel G.; Scott, Nicola J.; Butler, Alexandra P.; Butler, Philip H.; Butler, Anthony P.

2009-07-01

NAFLD, liver component of the "metabolic" syndrome, has become the most common liver disease in western nations. Non-invasive imaging techniques exist, but have limitations, especially in detection and quantification of mild to moderate fatty liver. In this pilot study, we produced attenuation curves from biomedical-quality projection images of liver and fat using the MARS spectroscopic-CT scanner. Difficulties obtaining attenuation spectra after reconstruction demonstrated that standard reconstruction programs do not preserve spectral information.

Restoration of hot pixels in digital imagers using lossless approximation techniques

NASA Astrophysics Data System (ADS)

Hadar, O.; Shleifer, A.; Cohen, E.; Dotan, Y.

2015-09-01

During the last twenty years, digital imagers have spread into industrial and everyday devices, such as satellites, security cameras, cell phones, laptops and more. "Hot pixels" are the main defects in remote digital cameras. In this paper we prove an improvement of existing restoration methods that use (solely or as an auxiliary tool) some average of the surrounding single pixel, such as the method of the Chapman-Koren study 1,2. The proposed method uses the CALIC algorithm and adapts it to a full use of the surrounding pixels.

Fusion of Geophysical Images in the Study of Archaeological Sites

NASA Astrophysics Data System (ADS)

Karamitrou, A. A.; Petrou, M.; Tsokas, G. N.

2011-12-01

This paper presents results from different fusion techniques between geophysical images from different modalities in order to combine them into one image with higher information content than the two original images independently. The resultant image will be useful for the detection and mapping of buried archaeological relics. The examined archaeological area is situated in Kampana site (NE Greece) near the ancient theater of Maronia city. Archaeological excavations revealed an ancient theater, an aristocratic house and the temple of the ancient Greek God Dionysus. Numerous ceramic objects found in the broader area indicated the probability of the existence of buried urban structure. In order to accurately locate and map the latter, geophysical measurements performed with the use of the magnetic method (vertical gradient of the magnetic field) and of the electrical method (apparent resistivity). We performed a semi-stochastic pixel based registration method between the geophysical images in order to fine register them by correcting their local spatial offsets produced by the use of hand held devices. After this procedure we applied to the registered images three different fusion approaches. Image fusion is a relatively new technique that not only allows integration of different information sources, but also takes advantage of the spatial and spectral resolution as well as the orientation characteristics of each image. We have used three different fusion techniques, fusion with mean values, with wavelets by enhancing selected frequency bands and curvelets giving emphasis at specific bands and angles (according the expecting orientation of the relics). In all three cases the fused images gave significantly better results than each of the original geophysical images separately. The comparison of the results of the three different approaches showed that the fusion with the use of curvelets, giving emphasis at the features' orientation, seems to give the best fused image. In the resultant image appear clear linear and ellipsoid features corresponding to potential archaeological relics.

Multi-scale Pore Imaging Techniques to Characterise Heterogeneity Effects on Flow in Carbonate Rock

NASA Astrophysics Data System (ADS)

Shah, S. M.

2017-12-01

Digital rock analysis and pore-scale studies have become an essential tool in the oil and gas industry to understand and predict the petrophysical and multiphase flow properties for the assessment and exploitation of hydrocarbon reserves. Carbonate reservoirs, accounting for majority of the world's hydrocarbon reserves, are well known for their heterogeneity and multiscale pore characteristics. The pore sizes in carbonate rock can vary over orders of magnitudes, the geometry and topology parameters of pores at different scales have a great impact on flow properties. A pore-scale study is often comprised of two key procedures: 3D pore-scale imaging and numerical modelling techniques. The fundamental problem in pore-scale imaging and modelling is how to represent and model the different range of scales encountered in porous media, from the pore-scale to macroscopic petrophysical and multiphase flow properties. However, due to the restrictions of image size vs. resolution, the desired detail is rarely captured at the relevant length scales using any single imaging technique. Similarly, direct simulations of transport properties in heterogeneous rocks with broad pore size distributions are prohibitively expensive computationally. In this study, we present the advances and review the practical limitation of different imaging techniques varying from core-scale (1mm) using Medical Computed Tomography (CT) to pore-scale (10nm - 50µm) using Micro-CT, Confocal Laser Scanning Microscopy (CLSM) and Focussed Ion Beam (FIB) to characterise the complex pore structure in Ketton carbonate rock. The effect of pore structure and connectivity on the flow properties is investigated using the obtained pore scale images of Ketton carbonate using Pore Network and Lattice-Boltzmann simulation methods in comparison with experimental data. We also shed new light on the existence and size of the Representative Element of Volume (REV) capturing the different scales of heterogeneity from the pore-scale imaging.

Bouguer Images of the North American Craton

NASA Technical Reports Server (NTRS)

Arvidson, R. E.; Bindschadler, D.; Bowring, S.; Eddy, M.; Guinness, E.; Leff, C.

1985-01-01

Processing of existing gravity and aeromagnetic data with modern methods is providing new insights into crustal and mantle structures for large parts of the United States and Canada. More than three-quarters of a million ground station readings of gravity are now available for this region. These data offer a wealth of information on crustal and mantle structures when reduced and displayed as Bouguer anomalies, where lateral variations are controlled by the size, shape and densities of underlying materials. Digital image processing techniques were used to generate Bouguer images that display more of the granularity inherent in the data as compared with existing contour maps. A dominant NW-SE linear trend of highs and lows can be seen extending from South Dakota, through Nebaska, and into Missouri. This trend is probably related to features created during an early and perhaps initial episode of crustal assembly by collisional processes. The younger granitic materials are probably a thin cover over an older crust.

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.

The correlation study of parallel feature extractor and noise reduction approaches

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

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

2015-05-15

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

Clinical applications of textural analysis in non-small cell lung cancer.

PubMed

Phillips, Iain; Ajaz, Mazhar; Ezhil, Veni; Prakash, Vineet; Alobaidli, Sheaka; McQuaid, Sarah J; South, Christopher; Scuffham, James; Nisbet, Andrew; Evans, Philip

2018-01-01

Lung cancer is the leading cause of cancer mortality worldwide. Treatment pathways include regular cross-sectional imaging, generating large data sets which present intriguing possibilities for exploitation beyond standard visual interpretation. This additional data mining has been termed "radiomics" and includes semantic and agnostic approaches. Textural analysis (TA) is an example of the latter, and uses a range of mathematically derived features to describe an image or region of an image. Often TA is used to describe a suspected or known tumour. TA is an attractive tool as large existing image sets can be submitted to diverse techniques for data processing, presentation, interpretation and hypothesis testing with annotated clinical outcomes. There is a growing anthology of published data using different TA techniques to differentiate between benign and malignant lung nodules, differentiate tissue subtypes of lung cancer, prognosticate and predict outcome and treatment response, as well as predict treatment side effects and potentially aid radiotherapy planning. The aim of this systematic review is to summarize the current published data and understand the potential future role of TA in managing lung cancer.

Performance analysis of robust road sign identification

NASA Astrophysics Data System (ADS)

Ali, Nursabillilah M.; Mustafah, Y. M.; Rashid, N. K. A. M.

2013-12-01

This study describes performance analysis of a robust system for road sign identification that incorporated two stages of different algorithms. The proposed algorithms consist of HSV color filtering and PCA techniques respectively in detection and recognition stages. The proposed algorithms are able to detect the three standard types of colored images namely Red, Yellow and Blue. The hypothesis of the study is that road sign images can be used to detect and identify signs that are involved with the existence of occlusions and rotational changes. PCA is known as feature extraction technique that reduces dimensional size. The sign image can be easily recognized and identified by the PCA method as is has been used in many application areas. Based on the experimental result, it shows that the HSV is robust in road sign detection with minimum of 88% and 77% successful rate for non-partial and partial occlusions images. For successful recognition rates using PCA can be achieved in the range of 94-98%. The occurrences of all classes are recognized successfully is between 5% and 10% level of occlusions.

Imaging a Large Sample with Selective Plane Illumination Microscopy Based on Multiple Fluorescent Microsphere Tracking

NASA Astrophysics Data System (ADS)

Ryu, Inkeon; Kim, Daekeun

2018-04-01

A typical selective plane illumination microscopy (SPIM) image size is basically limited by the field of view, which is a characteristic of the objective lens. If an image larger than the imaging area of the sample is to be obtained, image stitching, which combines step-scanned images into a single panoramic image, is required. However, accurately registering the step-scanned images is very difficult because the SPIM system uses a customized sample mount where uncertainties for the translational and the rotational motions exist. In this paper, an image registration technique based on multiple fluorescent microsphere tracking is proposed in the view of quantifying the constellations and measuring the distances between at least two fluorescent microspheres embedded in the sample. Image stitching results are demonstrated for optically cleared large tissue with various staining methods. Compensation for the effect of the sample rotation that occurs during the translational motion in the sample mount is also discussed.

D Reconstruction from Multi-View Medical X-Ray Images - Review and Evaluation of Existing Methods

NASA Astrophysics Data System (ADS)

Hosseinian, S.; Arefi, H.

2015-12-01

The 3D concept is extremely important in clinical studies of human body. Accurate 3D models of bony structures are currently required in clinical routine for diagnosis, patient follow-up, surgical planning, computer assisted surgery and biomechanical applications. However, 3D conventional medical imaging techniques such as computed tomography (CT) scan and magnetic resonance imaging (MRI) have serious limitations such as using in non-weight-bearing positions, costs and high radiation dose(for CT). Therefore, 3D reconstruction methods from biplanar X-ray images have been taken into consideration as reliable alternative methods in order to achieve accurate 3D models with low dose radiation in weight-bearing positions. Different methods have been offered for 3D reconstruction from X-ray images using photogrammetry which should be assessed. In this paper, after demonstrating the principles of 3D reconstruction from X-ray images, different existing methods of 3D reconstruction of bony structures from radiographs are classified and evaluated with various metrics and their advantages and disadvantages are mentioned. Finally, a comparison has been done on the presented methods with respect to several metrics such as accuracy, reconstruction time and their applications. With regards to the research, each method has several advantages and disadvantages which should be considered for a specific application.

Intraoperative Magnetic Resonance Imaging for Cranial and Spinal Cases Using Preexisting "C" Shaped Three Side Open 0.2 Tesla Magnetic Resonance Imaging.

PubMed

Tewari, Vinod Kumar; Tripathi, Ravindra; Aggarwal, Subodh; Hussain, Mazhar; Das Gupta, Hari Kishan

2017-01-01

The existing Intraoperative MRI (IMRI) of developed countries is too costly to be affordable in any developing country and out of the reach of common and poor people of developing country at remote areas. We have used the pre-existing (refurbished) 3 side open "C" shaped 0.2 Tesla MRI for IMRI in a very remote area. In this technique the 0.2 Tesla MRI and the operating theatre were merged. MRI table was used as an operation table. We have operated 36 cases via IMRI from November 2005 to till date. First case operated was on 13 th nov 2005. Low (0.2) Tesla open setup costs very low (around Rs 40 lakhs) so highly affordable to management and thus to patients, used for diagnostic and therapeutic purposes both, the equipments like Nitrous, oxygen and suction is outside the MRI room so no noise inside operative room, positioning the patient didn't take much time due to manual adjustments, no special training to nurses and technicians required because of low (0.2) Tesla power of magnet and same instruments and techniques, sequencing took only 1.31 mints per sequence and re registration is not required since we always note down the two orthogonal axis in x and y axis in preoperative imaging and we were able to operate on posterior fossa tumors as well because of no head fixation except with leucoplast strap. Moreover the images we got intraoperative are highly acceptable. Three side open 0.2 Tesla MRI system, if used for intraoperative guidance, is highly affordable and overcomes the limitations of western setup of IMRI. Postoperative MRI images were highly acceptable and also highly affordable too.

Integrating passive seismicity with Web-Based GIS for a new perspective on volcano imaging and monitoring: the case study of Mt. Etna

NASA Astrophysics Data System (ADS)

Guardo, Roberto; De Siena, Luca

2017-04-01

The timely estimation of short- and long-term volcanic hazard relies on the existence of detailed 3D geophysical images of volcanic structures. High-resolution seismic models of the absorbing uppermost conduit systems and highly-heterogeneous shallowest volcanic layers, while particularly challenging to obtain, provide important data to locate feasible eruptive centers and forecast flank collapses and lava ascending paths. Here, we model the volcanic structures of Mt. Etna (Sicily, Italy) and its outskirts using the Horizontal to Vertical Spectral Ratio method, generally applied to industrial and engineering settings. The integration of this technique with Web-based Geographic Information System improves precision during the acquisition phase. It also integrates geological and geophysical visualization of 3D surface and subsurface structures in a queryable environment representing their exact three-dimensional geographic position, enhancing interpretation. The results show high-resolution 3D images of the shallowest volcanic and feeding systems, which complement (1) deeper seismic tomography imaging and (2) the results of recent remote sensing imaging. The main novelty with respect to previous model is the presence of a vertical structure that divides the pre-existing volcanic complexes of Ellittico and Cuvigghiuni. This could be interpreted as a transitional phase between the two systems. A comparison with recent remote sensing and geological results, however, shows clear connections between the anomaly and dynamic active during the last 15 years. We infer that seismic noise measurements from miniaturized instruments, when combined with remote sensing techniques, represent an important resource when monitoring volcanic media and eruptions, reducing the risk of loss of human lives and instrumentation.

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.

Automatic evaluation of skin histopathological images for melanocytic features

NASA Astrophysics Data System (ADS)

Koosha, Mohaddeseh; Hoseini Alinodehi, S. Pourya; Nicolescu, Mircea; Safaei Naraghi, Zahra

2017-03-01

Successfully detecting melanocyte cells in the skin epidermis has great significance in skin histopathology. Because of the existence of cells with similar appearance to melanocytes in hematoxylin and eosin (HE) images of the epidermis, detecting melanocytes becomes a challenging task. This paper proposes a novel technique for the detection of melanocytes in HE images of the epidermis, based on the melanocyte color features, in the HSI color domain. Initially, an effective soft morphological filter is applied to the HE images in the HSI color domain to remove noise. Then a novel threshold-based technique is applied to distinguish the candidate melanocytes' nuclei. Similarly, the method is applied to find the candidate surrounding halos of the melanocytes. The candidate nuclei are associated with their surrounding halos using the suggested logical and statistical inferences. Finally, a fuzzy inference system is proposed, based on the HSI color information of a typical melanocyte in the epidermis, to calculate the similarity ratio of each candidate cell to a melanocyte. As our review on the literature shows, this is the first method evaluating epidermis cells for melanocyte similarity ratio. Experimental results on various images with different zooming factors show that the proposed method improves the results of previous works.

Tomographic imaging of bone composition using coherently scattered x rays

NASA Astrophysics Data System (ADS)

Batchelar, Deidre L.; Dabrowski, W.; Cunningham, Ian A.

2000-04-01

Bone tissue consists primarily of calcium hydroxyapatite crystals (bone mineral) and collagen fibrils. Bone mineral density (BMD) is commonly used as an indicator of bone health. Techniques available at present for assessing bone health provide a measure of BMD, but do not provide information about the degree of mineralization of the bone tissue. This may be adequate for assessing diseases in which the collagen-mineral ratio remains constant, as assumed in osteoporosis, but is insufficient when the mineralization state is known to change, as in osteomalacia. No tool exists for the in situ examination of collagen and hydroxyapatite density distributions independently. Coherent-scatter computed tomography (CSCT) is a technique we are developing that produces images of the low- angle scatter properties of tissue. These depend on the molecular structure of the scatterer making it possible to produce material-specific maps of each component in a conglomerate. After corrections to compensate for exposure fluctuations, self-attenuation of scatter and the temporal response of the image intensifier, material-specific images of mineral, collagen, fat and water distributions are obtained. The gray-level in these images provides the volumetric density of each component independently.

Qualitative and quantitative interpretation of SEM image using digital image processing.

PubMed

Saladra, Dawid; Kopernik, Magdalena

2016-10-01

The aim of the this study is improvement of qualitative and quantitative analysis of scanning electron microscope micrographs by development of computer program, which enables automatic crack analysis of scanning electron microscopy (SEM) micrographs. Micromechanical tests of pneumatic ventricular assist devices result in a large number of micrographs. Therefore, the analysis must be automatic. Tests for athrombogenic titanium nitride/gold coatings deposited on polymeric substrates (Bionate II) are performed. These tests include microshear, microtension and fatigue analysis. Anisotropic surface defects observed in the SEM micrographs require support for qualitative and quantitative interpretation. Improvement of qualitative analysis of scanning electron microscope images was achieved by a set of computational tools that includes binarization, simplified expanding, expanding, simple image statistic thresholding, the filters Laplacian 1, and Laplacian 2, Otsu and reverse binarization. Several modifications of the known image processing techniques and combinations of the selected image processing techniques were applied. The introduced quantitative analysis of digital scanning electron microscope images enables computation of stereological parameters such as area, crack angle, crack length, and total crack length per unit area. This study also compares the functionality of the developed computer program of digital image processing with existing applications. The described pre- and postprocessing may be helpful in scanning electron microscopy and transmission electron microscopy surface investigations. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Contextual analysis of immunological response through whole-organ fluorescent imaging.

PubMed

Woodruff, Matthew C; Herndon, Caroline N; Heesters, B A; Carroll, Michael C

2013-09-01

As fluorescent microscopy has developed, significant insights have been gained into the establishment of immune response within secondary lymphoid organs, particularly in draining lymph nodes. While established techniques such as confocal imaging and intravital multi-photon microscopy have proven invaluable, they provide limited insight into the architectural and structural context in which these responses occur. To interrogate the role of the lymph node environment in immune response effectively, a new set of imaging tools taking into account broader architectural context must be implemented into emerging immunological questions. Using two different methods of whole-organ imaging, optical clearing and three-dimensional reconstruction of serially sectioned lymph nodes, fluorescent representations of whole lymph nodes can be acquired at cellular resolution. Using freely available post-processing tools, images of unlimited size and depth can be assembled into cohesive, contextual snapshots of immunological response. Through the implementation of robust iterative analysis techniques, these highly complex three-dimensional images can be objectified into sortable object data sets. These data can then be used to interrogate complex questions at the cellular level within the broader context of lymph node biology. By combining existing imaging technology with complex methods of sample preparation and capture, we have developed efficient systems for contextualizing immunological phenomena within lymphatic architecture. In combination with robust approaches to image analysis, these advances provide a path to integrating scientific understanding of basic lymphatic biology into the complex nature of immunological response.

Efficient morse decompositions of vector fields.

PubMed

Chen, Guoning; Mischaikow, Konstantin; Laramee, Robert S; Zhang, Eugene

2008-01-01

Existing topology-based vector field analysis techniques rely on the ability to extract the individual trajectories such as fixed points, periodic orbits, and separatrices that are sensitive to noise and errors introduced by simulation and interpolation. This can make such vector field analysis unsuitable for rigorous interpretations. We advocate the use of Morse decompositions, which are robust with respect to perturbations, to encode the topological structures of a vector field in the form of a directed graph, called a Morse connection graph (MCG). While an MCG exists for every vector field, it need not be unique. Previous techniques for computing MCG's, while fast, are overly conservative and usually results in MCG's that are too coarse to be useful for the applications. To address this issue, we present a new technique for performing Morse decomposition based on the concept of tau-maps, which typically provides finer MCG's than existing techniques. Furthermore, the choice of tau provides a natural tradeoff between the fineness of the MCG's and the computational costs. We provide efficient implementations of Morse decomposition based on tau-maps, which include the use of forward and backward mapping techniques and an adaptive approach in constructing better approximations of the images of the triangles in the meshes used for simulation.. Furthermore, we propose the use of spatial tau-maps in addition to the original temporal tau-maps. These techniques provide additional trade-offs between the quality of the MCGs and the speed of computation. We demonstrate the utility of our technique with various examples in the plane and on surfaces including engine simulation data sets.

Dual-energy-based metal segmentation for metal artifact reduction in dental computed tomography.

PubMed

Hegazy, Mohamed A A; Eldib, Mohamed Elsayed; Hernandez, Daniel; Cho, Myung Hye; Cho, Min Hyoung; Lee, Soo Yeol

2018-02-01

In a dental CT scan, the presence of dental fillings or dental implants generates severe metal artifacts that often compromise readability of the CT images. Many metal artifact reduction (MAR) techniques have been introduced, but dental CT scans still suffer from severe metal artifacts particularly when multiple dental fillings or implants exist around the region of interest. The high attenuation coefficient of teeth often causes erroneous metal segmentation, compromising the MAR performance. We propose a metal segmentation method for a dental CT that is based on dual-energy imaging with a narrow energy gap. Unlike a conventional dual-energy CT, we acquire two projection data sets at two close tube voltages (80 and 90 kV p ), and then, we compute the difference image between the two projection images with an optimized weighting factor so as to maximize the contrast of the metal regions. We reconstruct CT images from the weighted difference image to identify the metal region with global thresholding. We forward project the identified metal region to designate metal trace on the projection image. We substitute the pixel values on the metal trace with the ones computed by the region filling method. The region filling in the metal trace removes high-intensity data made by the metallic objects from the projection image. We reconstruct final CT images from the region-filled projection image with the fusion-based approach. We have done imaging experiments on a dental phantom and a human skull phantom using a lab-built micro-CT and a commercial dental CT system. We have corrected the projection images of a dental phantom and a human skull phantom using the single-energy and dual-energy-based metal segmentation methods. The single-energy-based method often failed in correcting the metal artifacts on the slices on which tooth enamel exists. The dual-energy-based method showed better MAR performances in all cases regardless of the presence of tooth enamel on the slice of interest. We have compared the MAR performances between both methods in terms of the relative error (REL), the sum of squared difference (SSD) and the normalized absolute difference (NAD). For the dental phantom images corrected by the single-energy-based method, the metric values were 95.3%, 94.5%, and 90.6%, respectively, while they were 90.1%, 90.05%, and 86.4%, respectively, for the images corrected by the dual-energy-based method. For the human skull phantom images, the metric values were improved from 95.6%, 91.5%, and 89.6%, respectively, to 88.2%, 82.5%, and 81.3%, respectively. The proposed dual-energy-based method has shown better performance in metal segmentation leading to better MAR performance in dental imaging. We expect the proposed metal segmentation method can be used to improve the MAR performance of existing MAR techniques that have metal segmentation steps in their correction procedures. © 2017 American Association of Physicists in Medicine.

Cross-calibration of Medium Resolution Earth Observing Satellites by Using EO-1 Hyperion-derived Spectral Surface Reflectance from "Lunar Cal Sites"

NASA Astrophysics Data System (ADS)

Ungar, S.

2017-12-01

Over the past 3 years, the Earth Observing-one (EO-1) Hyperion imaging spectrometer was used to slowly scan the lunar surface at a rate which results in up to 32X oversampling to effectively increase the SNR. Several strategies, including comparison against the USGS RObotic Lunar Observatory (ROLO) mode,l are being employed to estimate the absolute and relative accuracy of the measurement set. There is an existing need to resolve discrepancies as high as 10% between ROLO and solar based calibration of current NASA EOS assets. Although the EO-1 mission was decommissioned at the end of March 2017, the development of a well-characterized exoatmospheric spectral radiometric database, for a range of lunar phase angles surrounding the fully illuminated moon, continues. Initial studies include a comprehensive analysis of the existing 17-year collection of more than 200 monthly lunar acquisitions. Specific lunar surface areas, such as a lunar mare, are being characterized as potential "lunar calibration sites" in terms of their radiometric stability in the presence of lunar nutation and libration. Site specific Hyperion-derived lunar spectral reflectance are being compared against spectrographic measurements made during the Apollo program. Techniques developed through this activity can be employed by future high-quality orbiting imaging spectrometers (such as HyspIRI and EnMap) to further refine calibration accuracies. These techniques will enable the consistent cross calibration of existing and future earth observing systems (spectral and multi-spectral) including those that do not have lunar viewing capability. When direct lunar viewing is not an option for an earth observing asset, orbiting imaging spectrometers can serve as transfer radiometers relating that asset's sensor response to lunar values through near contemporaneous observations of well characterized stable CEOS test sites. Analysis of this dataset will lead to the development of strategies to ensure more accurate cross calibrations when employing the more capable, future imaging spectrometers.

Location of planar targets in three space from monocular images

NASA Technical Reports Server (NTRS)

Cornils, Karin; Goode, Plesent W.

1987-01-01

Many pieces of existing and proposed space hardware that would be targets of interest for a telerobot can be represented as planar or near-planar surfaces. Examples include the biostack modules on the Long Duration Exposure Facility, the panels on Solar Max, large diameter struts, and refueling receptacles. Robust and temporally efficient methods for locating such objects with sufficient accuracy are therefore worth developing. Two techniques that derive the orientation and location of an object from its monocular image are discussed and the results of experiments performed to determine translational and rotational accuracy are presented. Both the quadrangle projection and elastic matching techniques extract three-space information using a minimum of four identifiable target points and the principles of the perspective transformation. The selected points must describe a convex polygon whose geometric characteristics are prespecified in a data base. The rotational and translational accuracy of both techniques was tested at various ranges. This experiment is representative of the sensing requirements involved in a typical telerobot target acquisition task. Both techniques determined target location to an accuracy sufficient for consistent and efficient acquisition by the telerobot.

From air to rubber: New techniques for measuring and replicating mouthpieces, bocals, and bores

NASA Astrophysics Data System (ADS)

Fuks, Leonardo

2002-11-01

The history of musical instruments comprises a long genealogy of models and prototypes that results from a combination of copying existing specimens with the change in constructive parameters, and the addition of new devices. In making wind instruments, several techniques have been traditionally employed for extracting the external and internal dimensions of toneholes, air columns, bells, and mouthpieces. In the twentieth century, methods such as pulse reflectometry, x-ray, magnetic resonance, and ultrasound imaging have been made available for bore measurement. Advantages and drawbacks of the existing methods are discussed and a new method is presented that makes use of the injection and coating of silicon rubber, for accurate molding of the instrument. This technique is harmless to all traditional materials, being indicated also for measurements of historical instruments. The paper presents dimensional data obtained from clarinet and saxophone mouthpieces. A set of replicas of top quality clarinet and saxophone mouthpieces, trombone bocals, and flute headjoints is shown, with comparative acoustical and performance analyses. The application of such techniques for historical and modern instrument analysis, restoration, and manufacturing is proposed.

Medical imaging: examples of clinical applications

NASA Astrophysics Data System (ADS)

Meinzer, H. P.; Thorn, M.; Vetter, M.; Hassenpflug, P.; Hastenteufel, M.; Wolf, I.

Clinical routine is currently producing a multitude of diagnostic digital images but only a few are used in therapy planning and treatment. Medical imaging is involved in both diagnosis and therapy. Using a computer, existing 2D images can be transformed into interactive 3D volumes and results from different modalities can be merged. Furthermore, it is possible to calculate functional areas that were not visible in the primary images. This paper presents examples of clinical applications that are integrated into clinical routine and are based on medical imaging fundamentals. In liver surgery, the importance of virtual planning is increasing because surgery is still the only possible curative procedure. Visualisation and analysis of heart defects are also gaining in significance due to improved surgery techniques. Finally, an outlook is provided on future developments in medical imaging using navigation to support the surgeon's work. The paper intends to give an impression of the wide range of medical imaging that goes beyond the mere calculation of medical images.

Three-dimensional ghost imaging lidar via sparsity constraint

NASA Astrophysics Data System (ADS)

Gong, Wenlin; Zhao, Chengqiang; Yu, Hong; Chen, Mingliang; Xu, Wendong; Han, Shensheng

2016-05-01

Three-dimensional (3D) remote imaging attracts increasing attentions in capturing a target’s characteristics. Although great progress for 3D remote imaging has been made with methods such as scanning imaging lidar and pulsed floodlight-illumination imaging lidar, either the detection range or application mode are limited by present methods. Ghost imaging via sparsity constraint (GISC), enables the reconstruction of a two-dimensional N-pixel image from much fewer than N measurements. By GISC technique and the depth information of targets captured with time-resolved measurements, we report a 3D GISC lidar system and experimentally show that a 3D scene at about 1.0 km range can be stably reconstructed with global measurements even below the Nyquist limit. Compared with existing 3D optical imaging methods, 3D GISC has the capability of both high efficiency in information extraction and high sensitivity in detection. This approach can be generalized in nonvisible wavebands and applied to other 3D imaging areas.

Image-Guided Surgery using Invisible Near-Infrared Light: Fundamentals of Clinical Translation

PubMed Central

Gioux, Sylvain; Choi, Hak Soo; Frangioni, John V.

2011-01-01

The field of biomedical optics has matured rapidly over the last decade and is poised to make a significant impact on patient care. In particular, wide-field (typically > 5 cm), planar, near-infrared (NIR) fluorescence imaging has the potential to revolutionize human surgery by providing real-time image guidance to surgeons for tissue that needs to be resected, such as tumors, and tissue that needs to be avoided, such as blood vessels and nerves. However, to become a clinical reality, optimized imaging systems and NIR fluorescent contrast agents will be needed. In this review, we introduce the principles of NIR fluorescence imaging, analyze existing NIR fluorescence imaging systems, and discuss the key parameters that guide contrast agent development. We also introduce the complexities surrounding clinical translation using our experience with the Fluorescence-Assisted Resection and Exploration (FLARE™) imaging system as an example. Finally, we introduce state-of-the-art optical imaging techniques that might someday improve image-guided surgery even further. PMID:20868625

Non-invasive pressure difference estimation from PC-MRI using the work-energy equation

PubMed Central

Donati, Fabrizio; Figueroa, C. Alberto; Smith, Nicolas P.; Lamata, Pablo; Nordsletten, David A.

2015-01-01

Pressure difference is an accepted clinical biomarker for cardiovascular disease conditions such as aortic coarctation. Currently, measurements of pressure differences in the clinic rely on invasive techniques (catheterization), prompting development of non-invasive estimates based on blood flow. In this work, we propose a non-invasive estimation procedure deriving pressure difference from the work-energy equation for a Newtonian fluid. Spatial and temporal convergence is demonstrated on in silico Phase Contrast Magnetic Resonance Image (PC-MRI) phantoms with steady and transient flow fields. The method is also tested on an image dataset generated in silico from a 3D patient-specific Computational Fluid Dynamics (CFD) simulation and finally evaluated on a cohort of 9 subjects. The performance is compared to existing approaches based on steady and unsteady Bernoulli formulations as well as the pressure Poisson equation. The new technique shows good accuracy, robustness to noise, and robustness to the image segmentation process, illustrating the potential of this approach for non-invasive pressure difference estimation. PMID:26409245

IMAGE-GUIDED TREATMENT USING AN X-RAY THERAPY UNIT AND GOLD NANOPARTICLES: TEST OF CONCEPT.

PubMed

Le Loirec, Cindy; Chambellan, Dominique; Tisseur, David

2016-06-01

Gold nanoparticles (GNPs) have the potential to enhance the radiation dose locally in conjunction with kV X-rays used for radiation therapy. As for other radiotherapy modalities, the absorbed dose needs to be controlled. To do that, it is an advantage to know the distribution of GNPs. However, no effective imaging tool exists to determine the GNP distribution in vivo. Various approaches have been proposed to determine the concentration of GNPs and its distribution in a tumour and in other organs and tissues. X-ray fluorescence computed tomography (XFCT) is a promising imaging technique to do that. A new experimental device based on the XFCT technique allowing the in vivo control of GNP radiotherapy treatments is proposed. As a test of concept, experimental acquisitions and Monte Carlo simulations were performed to determine the performance that a XFCT detector has to fulfil. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A fully automatic three-step liver segmentation method on LDA-based probability maps for multiple contrast MR images.

PubMed

Gloger, Oliver; Kühn, Jens; Stanski, Adam; Völzke, Henry; Puls, Ralf

2010-07-01

Automatic 3D liver segmentation in magnetic resonance (MR) data sets has proven to be a very challenging task in the domain of medical image analysis. There exist numerous approaches for automatic 3D liver segmentation on computer tomography data sets that have influenced the segmentation of MR images. In contrast to previous approaches to liver segmentation in MR data sets, we use all available MR channel information of different weightings and formulate liver tissue and position probabilities in a probabilistic framework. We apply multiclass linear discriminant analysis as a fast and efficient dimensionality reduction technique and generate probability maps then used for segmentation. We develop a fully automatic three-step 3D segmentation approach based upon a modified region growing approach and a further threshold technique. Finally, we incorporate characteristic prior knowledge to improve the segmentation results. This novel 3D segmentation approach is modularized and can be applied for normal and fat accumulated liver tissue properties. Copyright 2010 Elsevier Inc. All rights reserved.

Applications of holographic on-chip microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Ozcan, Aydogan

2017-02-01

My research focuses on the use of computation/algorithms to create new optical microscopy, sensing, and diagnostic techniques, significantly improving existing tools for probing micro- and nano-objects while also simplifying the designs of these analysis tools. In this presentation, I will introduce a set of computational microscopes which use lens-free on-chip imaging to replace traditional lenses with holographic reconstruction algorithms. Basically, 3D images of specimens are reconstructed from their "shadows" providing considerably improved field-of-view (FOV) and depth-of-field, thus enabling large sample volumes to be rapidly imaged, even at nanoscale. These new computational microscopes routinely generate <1-2 billion pixels (giga-pixels), where even single viruses can be detected with a FOV that is <100 fold wider than other techniques. At the heart of this leapfrog performance lie self-assembled liquid nano-lenses that are computationally imaged on a chip. The field-of-view of these computational microscopes is equal to the active-area of the sensor-array, easily reaching, for example, <20 mm^2 or <10 cm^2 by employing state-of-the-art CMOS or CCD imaging chips, respectively. In addition to this remarkable increase in throughput, another major benefit of this technology is that it lends itself to field-portable and cost-effective designs which easily integrate with smartphones to conduct giga-pixel tele-pathology and microscopy even in resource-poor and remote settings where traditional techniques are difficult to implement and sustain, thus opening the door to various telemedicine applications in global health. Through the development of similar computational imagers, I will also report the discovery of new 3D swimming patterns observed in human and animal sperm. One of this newly discovered and extremely rare motion is in the form of "chiral ribbons" where the planar swings of the sperm head occur on an osculating plane creating in some cases a helical ribbon and in some others a twisted ribbon. Shedding light onto the statistics and biophysics of various micro-swimmers' 3D motion, these results provide an important example of how biomedical imaging significantly benefits from emerging computational algorithms/theories, revolutionizing existing tools for observing various micro- and nano-scale phenomena in innovative, high-throughput, and yet cost-effective ways.

Mapping and spatiotemporal characterization of degraded forests in the Brazilian Amazon through remote sensing

NASA Astrophysics Data System (ADS)

de Souza, Carlos Moreira, Jr.

Large forested areas have recently been impoverished by degradation caused by selective logging, forest fires and fragmentation in the Amazon region, causing partial change of the original forest structure and composition. As opposed to deforestation that has been monitored with Landsat images since the late 70's, degraded forests have not been monitored in the Amazon region. In this dissertation, remote sensing techniques for identifying and mapping unambiguously degraded forests with Landsat images are proposed. The test area was the region of Sinop, located in the state of Mato Grosso, Brazil. This region was selected because a gradient of degraded forest environments exist and a robust time-series of Landsat images and forest transect data were available. First, statistical analyses were applied to identify the best set of spectral information extracted from Landsat images to detect several types of degraded forest environments. Fraction images derived from Spectral Mixture Analysis (SMA) were the best type of information for that purpose. A new spectral index based on fraction images---Normalized Difference Fraction Index (NDFI)---was proposed to enhance the detection of canopy damaged areas in degraded forests. Second, a contextual classification algorithm was implemented to separate unambiguously forest degradation caused by anthropogenic activities from natural forest disturbances. These techniques were validated using forest transects and high resolution aerial videography images and proved to be highly accurate. Next, these techniques were applied to a time-series data set of Landsat images, encompassing 20 years, to evaluate the relationship between forest degradation and deforestation. The most important finding of the forest change detection analysis was that forest degradation and deforestation are independent events in the study area, making worse the current forest impacts in the Amazon region. Finally, the techniques developed and tested in the Sinop region were successfully applied to forty Landsat images covering other regions of the Brazilian Amazon. Standard fractions and NDFI images were computed for these other regions and both physically and spatially consistent results were obtained. An automated decision tree classification using genetic algorithm was implemented successfully to classify land cover types and sub-classes of degraded forests. The remote sensing techniques proposed in this dissertation are fully automated and have the potential to be used in tropical forest monitoring programs.

Clinical Study of Orthogonal-View Phase-Matched Digital Tomosynthesis for Lung Tumor Localization.

PubMed

Zhang, You; Ren, Lei; Vergalasova, Irina; Yin, Fang-Fang

2017-01-01

Compared to cone-beam computed tomography, digital tomosynthesis imaging has the benefits of shorter scanning time, less imaging dose, and better mechanical clearance for tumor localization in radiation therapy. However, for lung tumors, the localization accuracy of the conventional digital tomosynthesis technique is affected by the lack of depth information and the existence of lung tumor motion. This study investigates the clinical feasibility of using an orthogonal-view phase-matched digital tomosynthesis technique to improve the accuracy of lung tumor localization. The proposed orthogonal-view phase-matched digital tomosynthesis technique benefits from 2 major features: (1) it acquires orthogonal-view projections to improve the depth information in reconstructed digital tomosynthesis images and (2) it applies respiratory phase-matching to incorporate patient motion information into the synthesized reference digital tomosynthesis sets, which helps to improve the localization accuracy of moving lung tumors. A retrospective study enrolling 14 patients was performed to evaluate the accuracy of the orthogonal-view phase-matched digital tomosynthesis technique. Phantom studies were also performed using an anthropomorphic phantom to investigate the feasibility of using intratreatment aggregated kV and beams' eye view cine MV projections for orthogonal-view phase-matched digital tomosynthesis imaging. The localization accuracy of the orthogonal-view phase-matched digital tomosynthesis technique was compared to that of the single-view digital tomosynthesis techniques and the digital tomosynthesis techniques without phase-matching. The orthogonal-view phase-matched digital tomosynthesis technique outperforms the other digital tomosynthesis techniques in tumor localization accuracy for both the patient study and the phantom study. For the patient study, the orthogonal-view phase-matched digital tomosynthesis technique localizes the tumor to an average (± standard deviation) error of 1.8 (0.7) mm for a 30° total scan angle. For the phantom study using aggregated kV-MV projections, the orthogonal-view phase-matched digital tomosynthesis localizes the tumor to an average error within 1 mm for varying magnitudes of scan angles. The pilot clinical study shows that the orthogonal-view phase-matched digital tomosynthesis technique enables fast and accurate localization of moving lung tumors.

A Study of Feature Combination for Vehicle Detection Based on Image Processing

PubMed Central

2014-01-01

Video analytics play a critical role in most recent traffic monitoring and driver assistance systems. In this context, the correct detection and classification of surrounding vehicles through image analysis has been the focus of extensive research in the last years. Most of the pieces of work reported for image-based vehicle verification make use of supervised classification approaches and resort to techniques, such as histograms of oriented gradients (HOG), principal component analysis (PCA), and Gabor filters, among others. Unfortunately, existing approaches are lacking in two respects: first, comparison between methods using a common body of work has not been addressed; second, no study of the combination potentiality of popular features for vehicle classification has been reported. In this study the performance of the different techniques is first reviewed and compared using a common public database. Then, the combination capabilities of these techniques are explored and a methodology is presented for the fusion of classifiers built upon them, taking into account also the vehicle pose. The study unveils the limitations of single-feature based classification and makes clear that fusion of classifiers is highly beneficial for vehicle verification. PMID:24672299

Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry.

PubMed

Oetjen, Janina; Veselkov, Kirill; Watrous, Jeramie; McKenzie, James S; Becker, Michael; Hauberg-Lotte, Lena; Kobarg, Jan Hendrik; Strittmatter, Nicole; Mróz, Anna K; Hoffmann, Franziska; Trede, Dennis; Palmer, Andrew; Schiffler, Stefan; Steinhorst, Klaus; Aichler, Michaela; Goldin, Robert; Guntinas-Lichius, Orlando; von Eggeling, Ferdinand; Thiele, Herbert; Maedler, Kathrin; Walch, Axel; Maass, Peter; Dorrestein, Pieter C; Takats, Zoltan; Alexandrov, Theodore

2015-01-01

Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms. High-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma. With the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets.

Parallel-multiplexed excitation light-sheet microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Xu, Dongli; Zhou, Weibin; Peng, Leilei

2017-02-01

Laser scanning light-sheet imaging allows fast 3D image of live samples with minimal bleach and photo-toxicity. Existing light-sheet techniques have very limited capability in multi-label imaging. Hyper-spectral imaging is needed to unmix commonly used fluorescent proteins with large spectral overlaps. However, the challenge is how to perform hyper-spectral imaging without sacrificing the image speed, so that dynamic and complex events can be captured live. We report wavelength-encoded structured illumination light sheet imaging (λ-SIM light-sheet), a novel light-sheet technique that is capable of parallel multiplexing in multiple excitation-emission spectral channels. λ-SIM light-sheet captures images of all possible excitation-emission channels in true parallel. It does not require compromising the imaging speed and is capable of distinguish labels by both excitation and emission spectral properties, which facilitates unmixing fluorescent labels with overlapping spectral peaks and will allow more labels being used together. We build a hyper-spectral light-sheet microscope that combined λ-SIM with an extended field of view through Bessel beam illumination. The system has a 250-micron-wide field of view and confocal level resolution. The microscope, equipped with multiple laser lines and an unlimited number of spectral channels, can potentially image up to 6 commonly used fluorescent proteins from blue to red. Results from in vivo imaging of live zebrafish embryos expressing various genetic markers and sensors will be shown. Hyper-spectral images from λ-SIM light-sheet will allow multiplexed and dynamic functional imaging in live tissue and animals.

Dual-Particle Imaging System with Neutron Spectroscopy for Safeguard Applications

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

Hamel, Michael C.; Weber, Thomas M.

2017-11-01

A dual-particle imager (DPI) has been designed that is capable of detecting gamma-ray and neutron signatures from shielded SNM. The system combines liquid organic and NaI(Tl) scintillators to form a combined Compton and neutron scatter camera. Effective image reconstruction of detected particles is a crucial component for maximizing the performance of the system; however, a key deficiency exists in the widely used iterative list-mode maximum-likelihood estimation-maximization (MLEM) image reconstruction technique. For MLEM a stopping condition is required to achieve a good quality solution but these conditions fail to achieve maximum image quality. Stochastic origin ensembles (SOE) imaging is a goodmore » candidate to address this problem as it uses Markov chain Monte Carlo to reach a stochastic steady-state solution. The application of SOE to the DPI is presented in this work.« less

Single-image-based solution for optics temperature-dependent nonuniformity correction in an uncooled long-wave infrared camera.

PubMed

Cao, Yanpeng; Tisse, Christel-Loic

2014-02-01

In this Letter, we propose an efficient and accurate solution to remove temperature-dependent nonuniformity effects introduced by the imaging optics. This single-image-based approach computes optics-related fixed pattern noise (FPN) by fitting the derivatives of correction model to the gradient components, locally computed on an infrared image. A modified bilateral filtering algorithm is applied to local pixel output variations, so that the refined gradients are most likely caused by the nonuniformity associated with optics. The estimated bias field is subtracted from the raw infrared imagery to compensate the intensity variations caused by optics. The proposed method is fundamentally different from the existing nonuniformity correction (NUC) techniques developed for focal plane arrays (FPAs) and provides an essential image processing functionality to achieve completely shutterless NUC for uncooled long-wave infrared (LWIR) imaging systems.

Small-animal research imaging devices.

PubMed

Fine, Eugene J; Herbst, Lawrence; Jelicks, Linda A; Koba, Wade; Theele, Daniel

2014-01-01

The scientific study of living animals may be dated to Aristotle's original dissections, but modern animal studies are perhaps a century in the making, and advanced animal imaging has emerged only during the past few decades. In vivo imaging now occupies a growing role in the scientific research paradigm. Imaging of small animals has been particularly useful to help understand human molecular biology and pathophysiology using rodents, especially using genetically engineered mice (GEM) with spontaneous diseases that closely mimic human diseases. Specific examples of GEM models of veterinary diseases exist, but in general, GEM for veterinary research has lagged behind human research applications. However, the development of spontaneous disease models from GEM may also hold potential for veterinary research. The imaging techniques most widely used in small-animal research are CT, PET, single-photon emission CT, MRI, and optical fluorescent and luminescent imaging. Copyright © 2014 Elsevier Inc. All rights reserved.

Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

Sub-Selective Quantization for Learning Binary Codes in Large-Scale Image Search.

PubMed

Li, Yeqing; Liu, Wei; Huang, Junzhou

2018-06-01

Recently with the explosive growth of visual content on the Internet, large-scale image search has attracted intensive attention. It has been shown that mapping high-dimensional image descriptors to compact binary codes can lead to considerable efficiency gains in both storage and performing similarity computation of images. However, most existing methods still suffer from expensive training devoted to large-scale binary code learning. To address this issue, we propose a sub-selection based matrix manipulation algorithm, which can significantly reduce the computational cost of code learning. As case studies, we apply the sub-selection algorithm to several popular quantization techniques including cases using linear and nonlinear mappings. Crucially, we can justify the resulting sub-selective quantization by proving its theoretic properties. Extensive experiments are carried out on three image benchmarks with up to one million samples, corroborating the efficacy of the sub-selective quantization method in terms of image retrieval.

A dictionary learning approach for Poisson image deblurring.

PubMed

Ma, Liyan; Moisan, Lionel; Yu, Jian; Zeng, Tieyong

2013-07-01

The restoration of images corrupted by blur and Poisson noise is a key issue in medical and biological image processing. While most existing methods are based on variational models, generally derived from a maximum a posteriori (MAP) formulation, recently sparse representations of images have shown to be efficient approaches for image recovery. Following this idea, we propose in this paper a model containing three terms: a patch-based sparse representation prior over a learned dictionary, the pixel-based total variation regularization term and a data-fidelity term capturing the statistics of Poisson noise. The resulting optimization problem can be solved by an alternating minimization technique combined with variable splitting. Extensive experimental results suggest that in terms of visual quality, peak signal-to-noise ratio value and the method noise, the proposed algorithm outperforms state-of-the-art methods.

High resolution light-sheet based high-throughput imaging cytometry system enables visualization of intra-cellular organelles

NASA Astrophysics Data System (ADS)

Regmi, Raju; Mohan, Kavya; Mondal, Partha Pratim

2014-09-01

Visualization of intracellular organelles is achieved using a newly developed high throughput imaging cytometry system. This system interrogates the microfluidic channel using a sheet of light rather than the existing point-based scanning techniques. The advantages of the developed system are many, including, single-shot scanning of specimens flowing through the microfluidic channel at flow rate ranging from micro- to nano- lit./min. Moreover, this opens-up in-vivo imaging of sub-cellular structures and simultaneous cell counting in an imaging cytometry system. We recorded a maximum count of 2400 cells/min at a flow-rate of 700 nl/min, and simultaneous visualization of fluorescently-labeled mitochondrial network in HeLa cells during flow. The developed imaging cytometry system may find immediate application in biotechnology, fluorescence microscopy and nano-medicine.

Mapping gray-scale image to 3D surface scanning data by ray tracing

NASA Astrophysics Data System (ADS)

Li, Peng; Jones, Peter R. M.

1997-03-01

The extraction and location of feature points from range imaging is an important but difficult task in machine vision based measurement systems. There exist some feature points which are not able to be detected from pure geometric characteristics, particularly in those measurement tasks related to the human body. The Loughborough Anthropometric Shadow Scanner (LASS) is a whole body surface scanner based on structured light technique. Certain applications of LASS require accurate location of anthropometric landmarks from the scanned data. This is sometimes impossible from existing raw data because some landmarks do not appear in the scanned data. Identification of these landmarks has to resort to surface texture of the scanned object. Modifications to LASS were made to allow gray-scale images to be captured before or after the object was scanned. Two-dimensional gray-scale image must be mapped to the scanned data to acquire the 3D coordinates of a landmark. The method to map 2D images to the scanned data is based on the colinearity conditions and ray-tracing method. If the camera center and image coordinates are known, the corresponding object point must lie on a ray starting from the camera center and connecting to the image coordinate. By intersecting the ray with the scanned surface of the object, the 3D coordinates of a point can be solved. Experimentation has demonstrated the feasibility of the method.

Comparative analysis of semantic localization accuracies between adult and pediatric DICOM CT images

NASA Astrophysics Data System (ADS)

Robertson, Duncan; Pathak, Sayan D.; Criminisi, Antonio; White, Steve; Haynor, David; Chen, Oliver; Siddiqui, Khan

2012-02-01

Existing literature describes a variety of techniques for semantic annotation of DICOM CT images, i.e. the automatic detection and localization of anatomical structures. Semantic annotation facilitates enhanced image navigation, linkage of DICOM image content and non-image clinical data, content-based image retrieval, and image registration. A key challenge for semantic annotation algorithms is inter-patient variability. However, while the algorithms described in published literature have been shown to cope adequately with the variability in test sets comprising adult CT scans, the problem presented by the even greater variability in pediatric anatomy has received very little attention. Most existing semantic annotation algorithms can only be extended to work on scans of both adult and pediatric patients by adapting parameters heuristically in light of patient size. In contrast, our approach, which uses random regression forests ('RRF'), learns an implicit model of scale variation automatically using training data. In consequence, anatomical structures can be localized accurately in both adult and pediatric CT studies without the need for parameter adaptation or additional information about patient scale. We show how the RRF algorithm is able to learn scale invariance from a combined training set containing a mixture of pediatric and adult scans. Resulting localization accuracy for both adult and pediatric data remains comparable with that obtained using RRFs trained and tested using only adult data.

Plans for a new rio-imager experiment in Northern Scandinavia

NASA Astrophysics Data System (ADS)

Nielsen, E.; Hagfors, T.

1997-05-01

To observe the spatial variations and dynamics of charged particle precipitation in the high latitude ionosphere, a riometer experiment is planned, which from the ground will image the precipitation regions over an area of 300 × 300 km with a spatial resolution of 6 km in the zenith, increasing to 12 km at 60° zenith angle. The time resolution is one second. The spatial resolution represents a considerable improvement over existing imaging systems. The experiment employs a Mill's Cross technique not used before in riometer work: two 32 element rows of antennas form the antenna array, two 32 element Butler Matrices achieve directionality, and cross-correlation yield the directional intensities.

Bouguer images of the North American craton and its structural evolution

NASA Technical Reports Server (NTRS)

Arvidson, R. E.; Bowring, S.; Eddy, M.; Guinness, E.; Leff, C.; Bindschadler, D.

1984-01-01

Digital image processing techniques have been used to generate Bouguer images of the North American craton that diplay more of the granularity inherent in the data as compared with existing contour maps. A dominant NW-SE linear trend of highs and lows can be seen extending from South Dakota, through Nebraska, and into Missouri. The structural trend cuts across the major Precambrian boundary in Missouri, separating younger granites and rhyolites from older sheared granites and gneisses. This trend is probably related to features created during an early and perhaps initial episode of crustal assembly by collisional processes. The younger granitic materials are probably a thin cover over an older crust.

Cardiac fluid dynamics meets deformation imaging.

PubMed

Dal Ferro, Matteo; Stolfo, Davide; De Paris, Valerio; Lesizza, Pierluigi; Korcova, Renata; Collia, Dario; Tonti, Giovanni; Sinagra, Gianfranco; Pedrizzetti, Gianni

2018-02-20

Cardiac function is about creating and sustaining blood in motion. This is achieved through a proper sequence of myocardial deformation whose final goal is that of creating flow. Deformation imaging provided valuable contributions to understanding cardiac mechanics; more recently, several studies evidenced the existence of an intimate relationship between cardiac function and intra-ventricular fluid dynamics. This paper summarizes the recent advances in cardiac flow evaluations, highlighting its relationship with heart wall mechanics assessed through the newest techniques of deformation imaging and finally providing an opinion of the most promising clinical perspectives of this emerging field. It will be shown how fluid dynamics can integrate volumetric and deformation assessments to provide a further level of knowledge of cardiac mechanics.

Automated Prescription of Oblique Brain 3D MRSI

PubMed Central

Ozhinsky, Eugene; Vigneron, Daniel B.; Chang, Susan M.; Nelson, Sarah J.

2012-01-01

Two major difficulties encountered in implementing Magnetic Resonance Spectroscopic Imaging (MRSI) in a clinical setting are limited coverage and difficulty in prescription. The goal of this project was to completely automate the process of 3D PRESS MRSI prescription, including placement of the selection box, saturation bands and shim volume, while maximizing the coverage of the brain. The automated prescription technique included acquisition of an anatomical MRI image, optimization of the oblique selection box parameters, optimization of the placement of OVS saturation bands, and loading of the calculated parameters into a customized 3D MRSI pulse sequence. To validate the technique and compare its performance with existing protocols, 3D MRSI data were acquired from 6 exams from 3 healthy volunteers. To assess the performance of the automated 3D MRSI prescription for patients with brain tumors, the data were collected from 16 exams from 8 subjects with gliomas. This technique demonstrated robust coverage of the tumor, high consistency of prescription and very good data quality within the T2 lesion. PMID:22692829

Fractional order integration and fuzzy logic based filter for denoising of echocardiographic image.

PubMed

Saadia, Ayesha; Rashdi, Adnan

2016-12-01

Ultrasound is widely used for imaging due to its cost effectiveness and safety feature. However, ultrasound images are inherently corrupted with speckle noise which severely affects the quality of these images and create difficulty for physicians in diagnosis. To get maximum benefit from ultrasound imaging, image denoising is an essential requirement. To perform image denoising, a two stage methodology using fuzzy weighted mean and fractional integration filter has been proposed in this research work. In stage-1, image pixels are processed by applying a 3 × 3 window around each pixel and fuzzy logic is used to assign weights to the pixels in each window, replacing central pixel of the window with weighted mean of all neighboring pixels present in the same window. Noise suppression is achieved by assigning weights to the pixels while preserving edges and other important features of an image. In stage-2, the resultant image is further improved by fractional order integration filter. Effectiveness of the proposed methodology has been analyzed for standard test images artificially corrupted with speckle noise and real ultrasound B-mode images. Results of the proposed technique have been compared with different state-of-the-art techniques including Lsmv, Wiener, Geometric filter, Bilateral, Non-local means, Wavelet, Perona et al., Total variation (TV), Global Adaptive Fractional Integral Algorithm (GAFIA) and Improved Fractional Order Differential (IFD) model. Comparison has been done on quantitative and qualitative basis. For quantitative analysis different metrics like Peak Signal to Noise Ratio (PSNR), Speckle Suppression Index (SSI), Structural Similarity (SSIM), Edge Preservation Index (β) and Correlation Coefficient (ρ) have been used. Simulations have been done using Matlab. Simulation results of artificially corrupted standard test images and two real Echocardiographic images reveal that the proposed method outperforms existing image denoising techniques reported in the literature. The proposed method for denoising of Echocardiographic images is effective in noise suppression/removal. It not only removes noise from an image but also preserves edges and other important structure. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Definition of spatial patterns of bark beetle Ips typographus (L.) outbreak spreading in Tatra Mountains (Central Europe), using GIS

Treesearch

Rastislav Jakus; Wojciech Grodzki; Marek Jezik; Marcin Jachym

2003-01-01

The spread of bark beetle outbreaks in the Tatra Mountains was explored by using both terrestrial and remote sensing techniques. Both approaches have proven to be useful for studying spatial patterns of bark beetle population dynamics. The terrestrial methods were applied on existing forestry databases. Vegetation change analysis (image differentiation), digital...

Automatic initialization and quality control of large-scale cardiac MRI segmentations.

PubMed

Albà, Xènia; Lekadir, Karim; Pereañez, Marco; Medrano-Gracia, Pau; Young, Alistair A; Frangi, Alejandro F

2018-01-01

Continuous advances in imaging technologies enable ever more comprehensive phenotyping of human anatomy and physiology. Concomitant reduction of imaging costs has resulted in widespread use of imaging in large clinical trials and population imaging studies. Magnetic Resonance Imaging (MRI), in particular, offers one-stop-shop multidimensional biomarkers of cardiovascular physiology and pathology. A wide range of analysis methods offer sophisticated cardiac image assessment and quantification for clinical and research studies. However, most methods have only been evaluated on relatively small databases often not accessible for open and fair benchmarking. Consequently, published performance indices are not directly comparable across studies and their translation and scalability to large clinical trials or population imaging cohorts is uncertain. Most existing techniques still rely on considerable manual intervention for the initialization and quality control of the segmentation process, becoming prohibitive when dealing with thousands of images. The contributions of this paper are three-fold. First, we propose a fully automatic method for initializing cardiac MRI segmentation, by using image features and random forests regression to predict an initial position of the heart and key anatomical landmarks in an MRI volume. In processing a full imaging database, the technique predicts the optimal corrective displacements and positions in relation to the initial rough intersections of the long and short axis images. Second, we introduce for the first time a quality control measure capable of identifying incorrect cardiac segmentations with no visual assessment. The method uses statistical, pattern and fractal descriptors in a random forest classifier to detect failures to be corrected or removed from subsequent statistical analysis. Finally, we validate these new techniques within a full pipeline for cardiac segmentation applicable to large-scale cardiac MRI databases. The results obtained based on over 1200 cases from the Cardiac Atlas Project show the promise of fully automatic initialization and quality control for population studies. Copyright © 2017 Elsevier B.V. All rights reserved.

On the Multi-Modal Object Tracking and Image Fusion Using Unsupervised Deep Learning Methodologies

NASA Astrophysics Data System (ADS)

LaHaye, N.; Ott, J.; Garay, M. J.; El-Askary, H. M.; Linstead, E.

2017-12-01

The number of different modalities of remote-sensors has been on the rise, resulting in large datasets with different complexity levels. Such complex datasets can provide valuable information separately, yet there is a bigger value in having a comprehensive view of them combined. As such, hidden information can be deduced through applying data mining techniques on the fused data. The curse of dimensionality of such fused data, due to the potentially vast dimension space, hinders our ability to have deep understanding of them. This is because each dataset requires a user to have instrument-specific and dataset-specific knowledge for optimum and meaningful usage. Once a user decides to use multiple datasets together, deeper understanding of translating and combining these datasets in a correct and effective manner is needed. Although there exists data centric techniques, generic automated methodologies that can potentially solve this problem completely don't exist. Here we are developing a system that aims to gain a detailed understanding of different data modalities. Such system will provide an analysis environment that gives the user useful feedback and can aid in research tasks. In our current work, we show the initial outputs our system implementation that leverages unsupervised deep learning techniques so not to burden the user with the task of labeling input data, while still allowing for a detailed machine understanding of the data. Our goal is to be able to track objects, like cloud systems or aerosols, across different image-like data-modalities. The proposed system is flexible, scalable and robust to understand complex likenesses within multi-modal data in a similar spatio-temporal range, and also to be able to co-register and fuse these images when needed.

High-performance compression of astronomical images

NASA Technical Reports Server (NTRS)

White, Richard L.

1993-01-01

Astronomical images have some rather unusual characteristics that make many existing image compression techniques either ineffective or inapplicable. A typical image consists of a nearly flat background sprinkled with point sources and occasional extended sources. The images are often noisy, so that lossless compression does not work very well; furthermore, the images are usually subjected to stringent quantitative analysis, so any lossy compression method must be proven not to discard useful information, but must instead discard only the noise. Finally, the images can be extremely large. For example, the Space Telescope Science Institute has digitized photographic plates covering the entire sky, generating 1500 images each having 14000 x 14000 16-bit pixels. Several astronomical groups are now constructing cameras with mosaics of large CCD's (each 2048 x 2048 or larger); these instruments will be used in projects that generate data at a rate exceeding 100 MBytes every 5 minutes for many years. An effective technique for image compression may be based on the H-transform (Fritze et al. 1977). The method that we have developed can be used for either lossless or lossy compression. The digitized sky survey images can be compressed by at least a factor of 10 with no noticeable losses in the astrometric and photometric properties of the compressed images. The method has been designed to be computationally efficient: compression or decompression of a 512 x 512 image requires only 4 seconds on a Sun SPARCstation 1. The algorithm uses only integer arithmetic, so it is completely reversible in its lossless mode, and it could easily be implemented in hardware for space applications.

What We Do and Do Not Know about Teaching Medical Image Interpretation.

PubMed

Kok, Ellen M; van Geel, Koos; van Merriënboer, Jeroen J G; Robben, Simon G F

2017-01-01

Educators in medical image interpretation have difficulty finding scientific evidence as to how they should design their instruction. We review and comment on 81 papers that investigated instructional design in medical image interpretation. We distinguish between studies that evaluated complete offline courses and curricula, studies that evaluated e-learning modules, and studies that evaluated specific educational interventions. Twenty-three percent of all studies evaluated the implementation of complete courses or curricula, and 44% of the studies evaluated the implementation of e-learning modules. We argue that these studies have encouraging results but provide little information for educators: too many differences exist between conditions to unambiguously attribute the learning effects to specific instructional techniques. Moreover, concepts are not uniformly defined and methodological weaknesses further limit the usefulness of evidence provided by these studies. Thirty-two percent of the studies evaluated a specific interventional technique. We discuss three theoretical frameworks that informed these studies: diagnostic reasoning, cognitive schemas and study strategies. Research on diagnostic reasoning suggests teaching students to start with non-analytic reasoning and subsequently applying analytic reasoning, but little is known on how to train non-analytic reasoning. Research on cognitive schemas investigated activities that help the development of appropriate cognitive schemas. Finally, research on study strategies supports the effectiveness of practice testing, but more study strategies could be applicable to learning medical image interpretation. Our commentary highlights the value of evaluating specific instructional techniques, but further evidence is required to optimally inform educators in medical image interpretation.

Color Image Enhancement Using Multiscale Retinex Based on Particle Swarm Optimization Method

NASA Astrophysics Data System (ADS)

Matin, F.; Jeong, Y.; Kim, K.; Park, K.

2018-01-01

This paper introduces, a novel method for the image enhancement using multiscale retinex and practical swarm optimization. Multiscale retinex is widely used image enhancement technique which intemperately pertains on parameters such as Gaussian scales, gain and offset, etc. To achieve the privileged effect, the parameters need to be tuned manually according to the image. In order to handle this matter, a developed retinex algorithm based on PSO has been used. The PSO method adjusted the parameters for multiscale retinex with chromaticity preservation (MSRCP) attains better outcome to compare with other existing methods. The experimental result indicates that the proposed algorithm is an efficient one and not only provides true color loyalty in low light conditions but also avoid color distortion at the same time.

Effects of empty bins on image upscaling in capsule endoscopy

NASA Astrophysics Data System (ADS)

Rukundo, Olivier

2017-07-01

This paper presents a preliminary study of the effect of empty bins on image upscaling in capsule endoscopy. The presented study was conducted based on results of existing contrast enhancement and interpolation methods. A low contrast enhancement method based on pixels consecutiveness and modified bilinear weighting scheme has been developed to distinguish between necessary empty bins and unnecessary empty bins in the effort to minimize the number of empty bins in the input image, before further processing. Linear interpolation methods have been used for upscaling input images with stretched histograms. Upscaling error differences and similarity indices between pairs of interpolation methods have been quantified using the mean squared error and feature similarity index techniques. Simulation results demonstrated more promising effects using the developed method than other contrast enhancement methods mentioned.

Real-time speckle reduction in optical coherence tomography using the dual window method.

PubMed

Zhao, Yang; Chu, Kengyeh K; Eldridge, Will J; Jelly, Evan T; Crose, Michael; Wax, Adam

2018-02-01

Speckle is an intrinsic noise of interferometric signals which reduces contrast and degrades the quality of optical coherence tomography (OCT) images. Here, we present a frequency compounding speckle reduction technique using the dual window (DW) method. Using the DW method, speckle noise is reduced without the need to acquire multiple frames. A ~25% improvement in the contrast-to-noise ratio (CNR) was achieved using the DW speckle reduction method with only minimal loss (~17%) in axial resolution. We also demonstrate that real-time speckle reduction can be achieved at a B-scan rate of ~21 frames per second using a graphic processing unit (GPU). The DW speckle reduction technique can work on any existing OCT instrument without further system modification or extra components. This makes it applicable both in real-time imaging systems and during post-processing.

Production and delivery of polarized Xenon-129 for in vivo MRS/MRI.

NASA Astrophysics Data System (ADS)

Rosen, Matthew S.; Chupp, Timothy E.; Coulter, Kevin P.; Welsh, Robert C.; Swanson, Scott

1998-05-01

Laser polarized ^129Xe can be used as an entirely new magnetic tracer, and is a powerful enhancement to currently existing MRI techniques. Inert laser polarized ^129Xe is inhaled and transported via blood flow where it is detected using MR spectroscopy and imaging techniques. The time-dependent distribution patterns of ^129Xe signal intensity directly reflect local blood volume, blood flow rates, and the efficiency of perfusion and diffusive transport in tissues. We have developed a uniquely constructed laser polarized ^129Xe production and delivery system that is used in both our in vitro and in vivo imaging experiments with rats. This reliable, effective, and relatively simple production method for large volumes of laser polarized ^129Xe is the key to all other areas of research involving use of laser polarized gases.

Analyzing the effect of the distortion compensation in reversible watermarking

NASA Astrophysics Data System (ADS)

Kim, Suah; Kim, Hyoung Joong

2014-01-01

Reversible watermarking is used to hide information in images for medical and military uses. Reversible watermarking in images using distortion compensation proposed by Vasily et al [5] embeds each pixel twice such that distortion caused by the first embedding is reduced or removed by the distortion introduced by the second embedding. In their paper, because it is not applied in its most basic form, it is not clear whether improving it can achieve better results than the existing state of the art techniques. In this paper we first provide a novel basic distortion compensation technique that uses same prediction method as Tian's [2] difference expansion method (DE), in order to measure the effect of the distortion compensation more accurately. In the second part, we will analyze what kind of improvements can be made in distortion compensation.

Advanced MR Imaging of the Placenta: Exploring the in utero placenta-brain connection

PubMed Central

Andescavage, Nickie Niforatos; DuPlessis, Adre; Limperopoulos, Catherine

2015-01-01

The placenta is a vital organ necessary for the healthy neurodevelopment of the fetus. Despite the known associations between placental dysfunction and neurologic impairment, there is a paucity of tools available to reliably assess in vivo placental health and function. Existing clinical tools for placental assessment remain insensitive in predicting and assessing placental well-being. Advanced MRI techniques hold significant promise for the dynamic, non-invasive, real-time assessment of placental health and identification of early placental-based disorders. In this review, we summarize the available clinical tools for placental assessment including ultrasound, Doppler, and conventional MRI. We then explore the emerging role of advanced placental MR imaging techniques for supporting the developing fetus, appraise the strengths and limitations of quantitative MRI in identifying early markers of placental dysfunction for improved pregnancy monitoring and fetal outcomes. PMID:25765905

Cell-Detection Technique for Automated Patch Clamping

NASA Technical Reports Server (NTRS)

McDowell, Mark; Gray, Elizabeth

2008-01-01

A unique and customizable machinevision and image-data-processing technique has been developed for use in automated identification of cells that are optimal for patch clamping. [Patch clamping (in which patch electrodes are pressed against cell membranes) is an electrophysiological technique widely applied for the study of ion channels, and of membrane proteins that regulate the flow of ions across the membranes. Patch clamping is used in many biological research fields such as neurobiology, pharmacology, and molecular biology.] While there exist several hardware techniques for automated patch clamping of cells, very few of those techniques incorporate machine vision for locating cells that are ideal subjects for patch clamping. In contrast, the present technique is embodied in a machine-vision algorithm that, in practical application, enables the user to identify good and bad cells for patch clamping in an image captured by a charge-coupled-device (CCD) camera attached to a microscope, within a processing time of one second. Hence, the present technique can save time, thereby increasing efficiency and reducing cost. The present technique involves the utilization of cell-feature metrics to accurately make decisions on the degree to which individual cells are "good" or "bad" candidates for patch clamping. These metrics include position coordinates (x,y) in the image plane, major-axis length, minor-axis length, area, elongation, roundness, smoothness, angle of orientation, and degree of inclusion in the field of view. The present technique does not require any special hardware beyond commercially available, off-the-shelf patch-clamping hardware: A standard patchclamping microscope system with an attached CCD camera, a personal computer with an imagedata- processing board, and some experience in utilizing imagedata- processing software are all that are needed. A cell image is first captured by the microscope CCD camera and image-data-processing board, then the image data are analyzed by software that implements the present machine-vision technique. This analysis results in the identification of cells that are "good" candidates for patch clamping (see figure). Once a "good" cell is identified, a patch clamp can be effected by an automated patchclamping apparatus or by a human operator. This technique has been shown to enable reliable identification of "good" and "bad" candidate cells for patch clamping. The ultimate goal in further development of this technique is to combine artificial-intelligence processing with instrumentation and controls in order to produce a complete "turnkey" automated patch-clamping system capable of accurately and reliably patch clamping cells with a minimum intervention by a human operator. Moreover, this technique can be adapted to virtually any cellular-analysis procedure that includes repetitive operation of microscope hardware by a human.

FFT-enhanced IHS transform method for fusing high-resolution satellite images

USGS Publications Warehouse

Ling, Y.; Ehlers, M.; Usery, E.L.; Madden, M.

2007-01-01

Existing image fusion techniques such as the intensity-hue-saturation (IHS) transform and principal components analysis (PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as Ikonos and QuickBird. One problem is color distortion in the fused image, which causes visual changes as well as spectral differences between the original and fused images. In this paper, a fast Fourier transform (FFT)-enhanced IHS method is developed for fusing new generation high-resolution satellite images. This method combines a standard IHS transform with FFT filtering of both the panchromatic image and the intensity component of the original multispectral image. Ikonos and QuickBird data are used to assess the FFT-enhanced IHS transform method. Experimental results indicate that the FFT-enhanced IHS transform method may improve upon the standard IHS transform and the PCA methods in preserving spectral and spatial information. ?? 2006 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Automated railroad reconstruction from remote sensing image based on texture filter

NASA Astrophysics Data System (ADS)

Xiao, Jie; Lu, Kaixia

2018-03-01

Techniques of remote sensing have been improved incredibly in recent years and very accurate results and high resolution images can be acquired. There exist possible ways to use such data to reconstruct railroads. In this paper, an automated railroad reconstruction method from remote sensing images based on Gabor filter was proposed. The method is divided in three steps. Firstly, the edge-oriented railroad characteristics (such as line features) in a remote sensing image are detected using Gabor filter. Secondly, two response images with the filtering orientations perpendicular to each other are fused to suppress the noise and acquire a long stripe smooth region of railroads. Thirdly, a set of smooth regions can be extracted by firstly computing global threshold for the previous result image using Otsu's method and then converting it to a binary image based on the previous threshold. This workflow is tested on a set of remote sensing images and was found to deliver very accurate results in a quickly and highly automated manner.

Using fuzzy fractal features of digital images for the material surface analisys

NASA Astrophysics Data System (ADS)

Privezentsev, D. G.; Zhiznyakov, A. L.; Astafiev, A. V.; Pugin, E. V.

2018-01-01

Edge detection is an important task in image processing. There are a lot of approaches in this area: Sobel, Canny operators and others. One of the perspective techniques in image processing is the use of fuzzy logic and fuzzy sets theory. They allow us to increase processing quality by representing information in its fuzzy form. Most of the existing fuzzy image processing methods switch to fuzzy sets on very late stages, so this leads to some useful information loss. In this paper, a novel method of edge detection based on fuzzy image representation and fuzzy pixels is proposed. With this approach, we convert the image to fuzzy form on the first step. Different approaches to this conversion are described. Several membership functions for fuzzy pixel description and requirements for their form and view are given. A novel approach to edge detection based on Sobel operator and fuzzy image representation is proposed. Experimental testing of developed method was performed on remote sensing images.

MLESAC Based Localization of Needle Insertion Using 2D Ultrasound Images

NASA Astrophysics Data System (ADS)

Xu, Fei; Gao, Dedong; Wang, Shan; Zhanwen, A.

2018-04-01

In the 2D ultrasound image of ultrasound-guided percutaneous needle insertions, it is difficult to determine the positions of needle axis and tip because of the existence of artifacts and other noises. In this work the speckle is regarded as the noise of an ultrasound image, and a novel algorithm is presented to detect the needle in a 2D ultrasound image. Firstly, the wavelet soft thresholding technique based on BayesShrink rule is used to denoise the speckle of ultrasound image. Secondly, we add Otsu’s thresholding method and morphologic operations to pre-process the ultrasound image. Finally, the localization of the needle is identified and positioned in the 2D ultrasound image based on the maximum likelihood estimation sample consensus (MLESAC) algorithm. The experimental results show that it is valid for estimating the position of needle axis and tip in the ultrasound images with the proposed algorithm. The research work is hopeful to be used in the path planning and robot-assisted needle insertion procedures.

Planar small-angle x-ray scattering imaging of phantoms and biological samples

NASA Astrophysics Data System (ADS)

Choi, M.; Badano, A.

2017-04-01

Coherent small-angle x-ray scattering (SAXS) provides molecular and nanometer-scale structural information. By capturing SAXS data at multiple locations across a sample, we obtained planar images and observed improved contrast given by the difference in the material scattering cross sections. We use phantoms made with 3D printing techniques, with tissue-mimicking plastic (PMMA), and with a highly scattering reference material (AgBe), which were chosen because of their well characterized scattering cross section to demonstrate and characterize the planar imaging of a laboratory SAXS system. We measure 1.07 and 2.14 nm-1 angular intensity maps for AgBe, 9.5 nm-1 for PMMA, and 12.3 nm-1 for Veroclear. The planar SAXS images show material discrimination based on their cross sectional features. The image signal-to-noise ratio (SNR) of each q image was dependent on exposure time and x-ray flux. We observed a lower SNR (91 ± 48) at q angles where no characteristic peaks for either material exist. To improve the visualization of the acquired data by utilizing all q-binned data, we describe a weighted-sum presentation method with a priori knowledge of relevant cross sections to improve the SNR (10 000 ± 6400) over the SNR from a single q-image at 1.07 nm-1 (1100 ± 620). In addition, we describe planar SAXS imaging of a mouse brain slice showing differentiation of tissue types as compared to a conventional absorption-based x-ray imaging technique.

Investigating the effect of pixel size of high spatial resolution FTIR imaging for detection of colorectal cancer

NASA Astrophysics Data System (ADS)

Lloyd, G. R.; Nallala, J.; Stone, N.

2016-03-01

FTIR is a well-established technique and there is significant interest in applying this technique to medical diagnostics e.g. to detect cancer. The introduction of focal plane array (FPA) detectors means that FTIR is particularly suited to rapid imaging of biopsy sections as an adjunct to digital pathology. Until recently however each pixel in the image has been limited to a minimum of 5.5 µm which results in a comparatively low magnification image or histology applications and potentially the loss of important diagnostic information. The recent introduction of higher magnification optics gives image pixels that cover approx. 1.1 µm. This reduction in image pixel size gives images of higher magnification and improved spatial detail can be observed. However, the effect of increasing the magnification on spectral quality and the ability to discriminate between disease states is not well studied. In this work we test the discriminatory performance of FTIR imaging using both standard (5.5 µm) and high (1.1 µm) magnification for the detection of colorectal cancer and explore the effect of binning to degrade high resolution images to determine whether similar diagnostic information and performance can be obtained using both magnifications. Results indicate that diagnostic performance using high magnification may be reduced as compared to standard magnification when using existing multivariate approaches. Reduction of the high magnification data to standard magnification via binning can potentially recover some of the lost performance.

A new, open-source, multi-modality digital breast phantom

NASA Astrophysics Data System (ADS)

Graff, Christian G.

2016-03-01

An anthropomorphic digital breast phantom has been developed with the goal of generating random voxelized breast models that capture the anatomic variability observed in vivo. This is a new phantom and is not based on existing digital breast phantoms or segmentation of patient images. It has been designed at the outset to be modality agnostic (i.e., suitable for use in modeling x-ray based imaging systems, magnetic resonance imaging, and potentially other imaging systems) and open source so that users may freely modify the phantom to suit a particular study. In this work we describe the modeling techniques that have been developed, the capabilities and novel features of this phantom, and study simulated images produced from it. Starting from a base quadric, a series of deformations are performed to create a breast with a particular volume and shape. Initial glandular compartments are generated using a Voronoi technique and a ductal tree structure with terminal duct lobular units is grown from the nipple into each compartment. An additional step involving the creation of fat and glandular lobules using a Perlin noise function is performed to create more realistic glandular/fat tissue interfaces and generate a Cooper's ligament network. A vascular tree is grown from the chest muscle into the breast tissue. Breast compression is performed using a neo-Hookean elasticity model. We show simulated mammographic and T1-weighted MRI images and study properties of these images.

Clustering of Farsi sub-word images for whole-book recognition

NASA Astrophysics Data System (ADS)

Soheili, Mohammad Reza; Kabir, Ehsanollah; Stricker, Didier

2015-01-01

Redundancy of word and sub-word occurrences in large documents can be effectively utilized in an OCR system to improve recognition results. Most OCR systems employ language modeling techniques as a post-processing step; however these techniques do not use important pictorial information that exist in the text image. In case of large-scale recognition of degraded documents, this information is even more valuable. In our previous work, we proposed a subword image clustering method for the applications dealing with large printed documents. In our clustering method, the ideal case is when all equivalent sub-word images lie in one cluster. To overcome the issues of low print quality, the clustering method uses an image matching algorithm for measuring the distance between two sub-word images. The measured distance with a set of simple shape features were used to cluster all sub-word images. In this paper, we analyze the effects of adding more shape features on processing time, purity of clustering, and the final recognition rate. Previously published experiments have shown the efficiency of our method on a book. Here we present extended experimental results and evaluate our method on another book with totally different font face. Also we show that the number of the new created clusters in a page can be used as a criteria for assessing the quality of print and evaluating preprocessing phases.

Passive forensics for copy-move image forgery using a method based on DCT and SVD.

PubMed

Zhao, Jie; Guo, Jichang

2013-12-10

As powerful image editing tools are widely used, the demand for identifying the authenticity of an image is much increased. Copy-move forgery is one of the tampering techniques which are frequently used. Most existing techniques to expose this forgery need to improve the robustness for common post-processing operations and fail to precisely locate the tampering region especially when there are large similar or flat regions in the image. In this paper, a robust method based on DCT and SVD is proposed to detect this specific artifact. Firstly, the suspicious image is divided into fixed-size overlapping blocks and 2D-DCT is applied to each block, then the DCT coefficients are quantized by a quantization matrix to obtain a more robust representation of each block. Secondly, each quantized block is divided non-overlapping sub-blocks and SVD is applied to each sub-block, then features are extracted to reduce the dimension of each block using its largest singular value. Finally, the feature vectors are lexicographically sorted, and duplicated image blocks will be matched by predefined shift frequency threshold. Experiment results demonstrate that our proposed method can effectively detect multiple copy-move forgery and precisely locate the duplicated regions, even when an image was distorted by Gaussian blurring, AWGN, JPEG compression and their mixed operations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Digital image modification detection using color information and its histograms.

PubMed

Zhou, Haoyu; Shen, Yue; Zhu, Xinghui; Liu, Bo; Fu, Zigang; Fan, Na

2016-09-01

The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping blocks. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring. Copyright © 2016. Published by Elsevier Ireland Ltd.

Bio-inspired color image enhancement

NASA Astrophysics Data System (ADS)

Meylan, Laurence; Susstrunk, Sabine

2004-06-01

Capturing and rendering an image that fulfills the observer's expectations is a difficult task. This is due to the fact that the signal reaching the eye is processed by a complex mechanism before forming a percept, whereas a capturing device only retains the physical value of light intensities. It is especially difficult to render complex scenes with highly varying luminances. For example, a picture taken inside a room where objects are visible through the windows will not be rendered correctly by a global technique. Either details in the dim room will be hidden in shadow or the objects viewed through the window will be too bright. The image has to be treated locally to resemble more closely to what the observer remembers. The purpose of this work is to develop a technique for rendering images based on human local adaptation. We take inspiration from a model of color vision called Retinex. This model determines the perceived color given spatial relationships of the captured signals. Retinex has been used as a computational model for image rendering. In this article, we propose a new solution inspired by Retinex that is based on a single filter applied to the luminance channel. All parameters are image-dependent so that the process requires no parameter tuning. That makes the method more flexible than other existing ones. The presented results show that our method suitably enhances high dynamic range images.

Studies on image compression and image reconstruction

NASA Technical Reports Server (NTRS)

Sayood, Khalid; Nori, Sekhar; Araj, A.

1994-01-01

During this six month period our works concentrated on three, somewhat different areas. We looked at and developed a number of error concealment schemes for use in a variety of video coding environments. This work is described in an accompanying (draft) Masters thesis. In the thesis we describe application of this techniques to the MPEG video coding scheme. We felt that the unique frame ordering approach used in the MPEG scheme would be a challenge to any error concealment/error recovery technique. We continued with our work in the vector quantization area. We have also developed a new type of vector quantizer, which we call a scan predictive vector quantization. The scan predictive VQ was tested on data processed at Goddard to approximate Landsat 7 HRMSI resolution and compared favorably with existing VQ techniques. A paper describing this work is included. The third area is concerned more with reconstruction than compression. While there is a variety of efficient lossless image compression schemes, they all have a common property that they use past data to encode future data. This is done either via taking differences, context modeling, or by building dictionaries. When encoding large images, this common property becomes a common flaw. When the user wishes to decode just a portion of the image, the requirement that the past history be available forces the decoding of a significantly larger portion of the image than desired by the user. Even with intelligent partitioning of the image dataset, the number of pixels decoded may be four times the number of pixels requested. We have developed an adaptive scanning strategy which can be used with any lossless compression scheme and which lowers the additional number of pixels to be decoded to about 7 percent of the number of pixels requested! A paper describing these results is included.

Noncontrast MR Angiography (MRA) of Infragenual Arteries Using Flow-Sensitive Dephasing (FSD)-Prepared Steady-State Free Precession (SSFP) at 3.0T: Comparison with Contrast-Enhanced MRA

PubMed Central

Zhang, Nan; Fan, Zhaoyang; Luo, Nan; Bi, Xiaoming; Zhao, Yike; An, Jing; Liu, Jiayi; Chen, Zhong; Fan, Zhanming; Li, Debiao

2015-01-01

Purpose To evaluate the feasibility and diagnostic performance of flow-sensitive dephasing (FSD)-prepared steady-state free precession (SSFP) MR angiography (MRA) for imaging infragenual arteries at 3.0T, with contrast enhanced MR angiography (CE MRA) as reference. Materials And Methods Twenty consecutive patients with suspicion of lower extremity arterial disease undergoing routine CE MRA were recruited. FSD MRA was performed at calf before CE MRA. Image quality and stenosis degree of infragenual arteries from both techniques were independently evaluated and compared. Six patients in this study underwent DSA examination. Results Three undiagnostic segments were excluded with severe venous contamination in CE MRA. A total of 197 calf arterial segments images were analyzed. No significant difference existed in the relative signal intensity (rSI) of arterial segments between FSD MRA and CE MRA techniques (0.92±0.09 vs. 0.93±0.05; P=0.207). However, the subjective image quality score was slightly higher in FSD MRA (3.66±0.81 vs. 3.49±0.87; P=0.050). With CE MRA images as reference standard, slight overestimation existed in FSD MRA (2.19±1.24 vs. 2.09±1.18; P=0.019), with total agreement of 84.3% on the basis of all arterial segments. The sensitivity, specificity, NPV, and PPV of FSD MRA was 96.4%, 93.0%, 98.5%, and 84.1%. No significant difference in the stenosis degree score was detected between MRA (FSD MRA and CE MRA) and DSA (P > 0.05). Conclusion FSD MRA performed on at 3.0Twithout the use of contrast medium provides diagnostic images allowing for arterial stenosis assessment of calf arteries that was highly comparable with CE MRA. Moreover, venous contamination was less problematic with FSD MRA. PMID:26185106

Evaluating methods for controlling depth perception in stereoscopic cinematography

NASA Astrophysics Data System (ADS)

Sun, Geng; Holliman, Nick

2009-02-01

Existing stereoscopic imaging algorithms can create static stereoscopic images with perceived depth control function to ensure a compelling 3D viewing experience without visual discomfort. However, current algorithms do not normally support standard Cinematic Storytelling techniques. These techniques, such as object movement, camera motion, and zooming, can result in dynamic scene depth change within and between a series of frames (shots) in stereoscopic cinematography. In this study, we empirically evaluate the following three types of stereoscopic imaging approaches that aim to address this problem. (1) Real-Eye Configuration: set camera separation equal to the nominal human eye interpupillary distance. The perceived depth on the display is identical to the scene depth without any distortion. (2) Mapping Algorithm: map the scene depth to a predefined range on the display to avoid excessive perceived depth. A new method that dynamically adjusts the depth mapping from scene space to display space is presented in addition to an existing fixed depth mapping method. (3) Depth of Field Simulation: apply Depth of Field (DOF) blur effect to stereoscopic images. Only objects that are inside the DOF are viewed in full sharpness. Objects that are far away from the focus plane are blurred. We performed a human-based trial using the ITU-R BT.500-11 Recommendation to compare the depth quality of stereoscopic video sequences generated by the above-mentioned imaging methods. Our results indicate that viewers' practical 3D viewing volumes are different for individual stereoscopic displays and viewers can cope with much larger perceived depth range in viewing stereoscopic cinematography in comparison to static stereoscopic images. Our new dynamic depth mapping method does have an advantage over the fixed depth mapping method in controlling stereo depth perception. The DOF blur effect does not provide the expected improvement for perceived depth quality control in 3D cinematography. We anticipate the results will be of particular interest to 3D filmmaking and real time computer games.

Compression techniques in tele-radiology

NASA Astrophysics Data System (ADS)

Lu, Tianyu; Xiong, Zixiang; Yun, David Y.

1999-10-01

This paper describes a prototype telemedicine system for remote 3D radiation treatment planning. Due to voluminous medical image data and image streams generated in interactive frame rate involved in the application, the importance of deploying adjustable lossy to lossless compression techniques is emphasized in order to achieve acceptable performance via various kinds of communication networks. In particular, the compression of the data substantially reduces the transmission time and therefore allows large-scale radiation distribution simulation and interactive volume visualization using remote supercomputing resources in a timely fashion. The compression algorithms currently used in the software we developed are JPEG and H.263 lossy methods and Lempel-Ziv (LZ77) lossless methods. Both objective and subjective assessment of the effect of lossy compression methods on the volume data are conducted. Favorable results are obtained showing that substantial compression ratio is achievable within distortion tolerance. From our experience, we conclude that 30dB (PSNR) is about the lower bound to achieve acceptable quality when applying lossy compression to anatomy volume data (e.g. CT). For computer simulated data, much higher PSNR (up to 100dB) is expectable. This work not only introduces such novel approach for delivering medical services that will have significant impact on the existing cooperative image-based services, but also provides a platform for the physicians to assess the effects of lossy compression techniques on the diagnostic and aesthetic appearance of medical imaging.

Commodity cluster and hardware-based massively parallel implementations of hyperspectral imaging algorithms

NASA Astrophysics Data System (ADS)

Plaza, Antonio; Chang, Chein-I.; Plaza, Javier; Valencia, David

2006-05-01

The incorporation of hyperspectral sensors aboard airborne/satellite platforms is currently producing a nearly continual stream of multidimensional image data, and this high data volume has soon introduced new processing challenges. The price paid for the wealth spatial and spectral information available from hyperspectral sensors is the enormous amounts of data that they generate. Several applications exist, however, where having the desired information calculated quickly enough for practical use is highly desirable. High computing performance of algorithm analysis is particularly important in homeland defense and security applications, in which swift decisions often involve detection of (sub-pixel) military targets (including hostile weaponry, camouflage, concealment, and decoys) or chemical/biological agents. In order to speed-up computational performance of hyperspectral imaging algorithms, this paper develops several fast parallel data processing techniques. Techniques include four classes of algorithms: (1) unsupervised classification, (2) spectral unmixing, and (3) automatic target recognition, and (4) onboard data compression. A massively parallel Beowulf cluster (Thunderhead) at NASA's Goddard Space Flight Center in Maryland is used to measure parallel performance of the proposed algorithms. In order to explore the viability of developing onboard, real-time hyperspectral data compression algorithms, a Xilinx Virtex-II field programmable gate array (FPGA) is also used in experiments. Our quantitative and comparative assessment of parallel techniques and strategies may help image analysts in selection of parallel hyperspectral algorithms for specific applications.

International Veterinary Epilepsy Task Force recommendations for a veterinary epilepsy-specific MRI protocol.

PubMed

Rusbridge, Clare; Long, Sam; Jovanovik, Jelena; Milne, Marjorie; Berendt, Mette; Bhatti, Sofie F M; De Risio, Luisa; Farqhuar, Robyn G; Fischer, Andrea; Matiasek, Kaspar; Muñana, Karen; Patterson, Edward E; Pakozdy, Akos; Penderis, Jacques; Platt, Simon; Podell, Michael; Potschka, Heidrun; Stein, Veronika M; Tipold, Andrea; Volk, Holger A

2015-08-28

Epilepsy is one of the most common chronic neurological diseases in veterinary practice. Magnetic resonance imaging (MRI) is regarded as an important diagnostic test to reach the diagnosis of idiopathic epilepsy. However, given that the diagnosis requires the exclusion of other differentials for seizures, the parameters for MRI examination should allow the detection of subtle lesions which may not be obvious with existing techniques. In addition, there are several differentials for idiopathic epilepsy in humans, for example some focal cortical dysplasias, which may only apparent with special sequences, imaging planes and/or particular techniques used in performing the MRI scan. As a result, there is a need to standardize MRI examination in veterinary patients with techniques that reliably diagnose subtle lesions, identify post-seizure changes, and which will allow for future identification of underlying causes of seizures not yet apparent in the veterinary literature.There is a need for a standardized veterinary epilepsy-specific MRI protocol which will facilitate more detailed examination of areas susceptible to generating and perpetuating seizures, is cost efficient, simple to perform and can be adapted for both low and high field scanners. Standardisation of imaging will improve clinical communication and uniformity of case definition between research studies. A 6-7 sequence epilepsy-specific MRI protocol for veterinary patients is proposed and further advanced MR and functional imaging is reviewed.

Using InSAR to Observe Sinkhole Activity in Central Florida

NASA Astrophysics Data System (ADS)

Oliver-Cabrera, T.; Wdowinski, S.; Kruse, S.; Kiflu, H. G.

2017-12-01

Sinkhole collapse in Florida is a major geologic hazard, threatening human life and causing substantial damage to property. Detecting sinkhole deformation before a collapse is an important but difficult task; most techniques used to monitor sinkholes are spatially constrained to relatively small areas (tens to hundred meters). To overcome this limitation, we use Interferometric Synthetic Aperture Radar (InSAR), which is a very useful technique for detecting localized deformation while covering vast areas. InSAR results show localized deformation at several houses and commercial buildings in different locations along the study sites. We use a subsurface imaging technique, ground penetrating radar, to verify sinkhole existence beneath the observed deforming areas.

Infrared Imagery of Shuttle (IRIS). Task 1, summary report

NASA Technical Reports Server (NTRS)

Chocol, C. J.

1977-01-01

The feasibility of remote, high-resolution infrared imagery of the Shuttle Orbiter lower surface during entry to obtain accurate measurements of aerodynamic heat transfer was demonstrated. Using available technology, such images can be taken from an existing aircraft/telescope system (the C141 AIRO) with minimum modification or addition of systems. Images with a spatial resolution of 1 m or better and a temperature resolution of 2.5% between temperatures of 800 and 1900 K can be obtained. Data reconstruction techniques can provide a geometrically and radiometrically corrected array on addressable magnetic tape ready for display by NASA.

Removing sun glint from optical remote sensing images of shallow rivers

USGS Publications Warehouse

Overstreet, Brandon T.; Legleiter, Carl

2017-01-01

Sun glint is the specular reflection of light from the water surface, which often causes unusually bright pixel values that can dominate fluvial remote sensing imagery and obscure the water-leaving radiance signal of interest for mapping bathymetry, bottom type, or water column optical characteristics. Although sun glint is ubiquitous in fluvial remote sensing imagery, river-specific methods for removing sun glint are not yet available. We show that existing sun glint-removal methods developed for multispectral images of marine shallow water environments over-correct shallow portions of fluvial remote sensing imagery resulting in regions of unreliable data along channel margins. We build on existing marine glint-removal methods to develop a river-specific technique that removes sun glint from shallow areas of the channel without overcorrection by accounting for non-negligible water-leaving near-infrared radiance. This new sun glint-removal method can improve the accuracy of spectrally-based depth retrieval in cases where sun glint dominates the at-sensor radiance. For an example image of the gravel-bed Snake River, Wyoming, USA, observed-vs.-predicted R2 values for depth retrieval improved from 0.66 to 0.76 following sun glint removal. The methodology presented here is straightforward to implement and could be incorporated into image processing workflows for multispectral images that include a near-infrared band.

A compressed sensing X-ray camera with a multilayer architecture

DOE PAGES

Wang, Zhehui; Laroshenko, O.; Li, S.; ...

2018-01-25

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. In this work, wemore » first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.« less

Random On-Board Pixel Sampling (ROPS) X-Ray Camera

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

Wang, Zhehui; Iaroshenko, O.; Li, S.

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. Here we first illustratemore » the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.« less

A compressed sensing X-ray camera with a multilayer architecture

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

Wang, Zhehui; Laroshenko, O.; Li, S.

Recent advances in compressed sensing theory and algorithms offer new possibilities for high-speed X-ray camera design. In many CMOS cameras, each pixel has an independent on-board circuit that includes an amplifier, noise rejection, signal shaper, an analog-to-digital converter (ADC), and optional in-pixel storage. When X-ray images are sparse, i.e., when one of the following cases is true: (a.) The number of pixels with true X-ray hits is much smaller than the total number of pixels; (b.) The X-ray information is redundant; or (c.) Some prior knowledge about the X-ray images exists, sparse sampling may be allowed. In this work, wemore » first illustrate the feasibility of random on-board pixel sampling (ROPS) using an existing set of X-ray images, followed by a discussion about signal to noise as a function of pixel size. Next, we describe a possible circuit architecture to achieve random pixel access and in-pixel storage. The combination of a multilayer architecture, sparse on-chip sampling, and computational image techniques, is expected to facilitate the development and applications of high-speed X-ray camera technology.« less

Dynamic time warping-based averaging framework for functional near-infrared spectroscopy brain imaging studies

NASA Astrophysics Data System (ADS)

Zhu, Li; Najafizadeh, Laleh

2017-06-01

We investigate the problem related to the averaging procedure in functional near-infrared spectroscopy (fNIRS) brain imaging studies. Typically, to reduce noise and to empower the signal strength associated with task-induced activities, recorded signals (e.g., in response to repeated stimuli or from a group of individuals) are averaged through a point-by-point conventional averaging technique. However, due to the existence of variable latencies in recorded activities, the use of the conventional averaging technique can lead to inaccuracies and loss of information in the averaged signal, which may result in inaccurate conclusions about the functionality of the brain. To improve the averaging accuracy in the presence of variable latencies, we present an averaging framework that employs dynamic time warping (DTW) to account for the temporal variation in the alignment of fNIRS signals to be averaged. As a proof of concept, we focus on the problem of localizing task-induced active brain regions. The framework is extensively tested on experimental data (obtained from both block design and event-related design experiments) as well as on simulated data. In all cases, it is shown that the DTW-based averaging technique outperforms the conventional-based averaging technique in estimating the location of task-induced active regions in the brain, suggesting that such advanced averaging methods should be employed in fNIRS brain imaging studies.

Wallerian Degeneration Beyond the Corticospinal Tracts: Conventional and Advanced MRI Findings.

PubMed

Chen, Yin Jie; Nabavizadeh, Seyed Ali; Vossough, Arastoo; Kumar, Sunil; Loevner, Laurie A; Mohan, Suyash

2017-05-01

Wallerian degeneration (WD) is defined as progressive anterograde disintegration of axons and accompanying demyelination after an injury to the proximal axon or cell body. Since the 1980s and 1990s, conventional magnetic resonance imaging (MRI) sequences have been shown to be sensitive to changes of WD in the subacute to chronic phases. More recently, advanced MRI techniques, such as diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI), have demonstrated some of earliest changes attributed to acute WD, typically on the order of days. In addition, there is increasing evidence on the value of advanced MRI techniques in providing important prognostic information related to WD. This article reviews the utility of conventional and advanced MRI techniques for assessing WD, by focusing not only on the corticospinal tract but also other neural tracts less commonly thought of, including corticopontocerebellar tract, dentate-rubro-olivary pathway, posterior column of the spinal cord, corpus callosum, limbic circuit, and optic pathway. The basic anatomy of these neural pathways will be discussed, followed by a comprehensive review of existing literature supported by instructive clinical examples. The goal of this review is for readers to become more familiar with both conventional and advanced MRI findings of WD involving important neural pathways, as well as to illustrate increasing utility of advanced MRI techniques in providing important prognostic information for various pathologies. Copyright © 2016 by the American Society of Neuroimaging.

Dual-scanning optical coherence elastography for rapid imaging of two tissue volumes (Conference Presentation)

NASA Astrophysics Data System (ADS)

Fang, Qi; Frewer, Luke; Wijesinghe, Philip; Hamzah, Juliana; Ganss, Ruth; Allen, Wes M.; Sampson, David D.; Curatolo, Andrea; Kennedy, Brendan F.

2017-02-01

In many applications of optical coherence elastography (OCE), it is necessary to rapidly acquire images in vivo, or within intraoperative timeframes, over fields-of-view far greater than can be achieved in one OCT image acquisition. For example, tumour margin assessment in breast cancer requires acquisition over linear dimensions of 4-5 centimetres in under 20 minutes. However, the majority of existing techniques are not compatible with these requirements, which may present a hurdle to the effective translation of OCE. To increase throughput, we have designed and developed an OCE system that simultaneously captures two 3D elastograms from opposite sides of a sample. The optical system comprises two interferometers: a common-path interferometer on one side of the sample and a dual-arm interferometer on the other side. This optical system is combined with scanning mechanisms and compression loading techniques to realize dual-scanning OCE. The optical signals scattered from two volumes are simultaneously detected on a single spectrometer by depth-encoding the interference signal from each interferometer. To demonstrate dual-scanning OCE, we performed measurements on tissue-mimicking phantoms containing rigid inclusions and freshly isolated samples of murine hepatocellular carcinoma, highlighting the use of this technique to visualise 3D tumour stiffness. These findings indicate that our technique holds promise for in vivo and intraoperative applications.

Localizing ECoG electrodes on the cortical anatomy without post-implantation imaging

PubMed Central

Gupta, Disha; Hill, N. Jeremy; Adamo, Matthew A.; Ritaccio, Anthony; Schalk, Gerwin

2014-01-01

Introduction Electrocorticographic (ECoG) grids are placed subdurally on the cortex in people undergoing cortical resection to delineate eloquent cortex. ECoG signals have high spatial and temporal resolution and thus can be valuable for neuroscientific research. The value of these data is highest when they can be related to the cortical anatomy. Existing methods that establish this relationship rely either on post-implantation imaging using computed tomography (CT), magnetic resonance imaging (MRI) or X-Rays, or on intra-operative photographs. For research purposes, it is desirable to localize ECoG electrodes on the brain anatomy even when post-operative imaging is not available or when intra-operative photographs do not readily identify anatomical landmarks. Methods We developed a method to co-register ECoG electrodes to the underlying cortical anatomy using only a pre-operative MRI, a clinical neuronavigation device (such as BrainLab VectorVision), and fiducial markers. To validate our technique, we compared our results to data collected from six subjects who also had post-grid implantation imaging available. We compared the electrode coordinates obtained by our fiducial-based method to those obtained using existing methods, which are based on co-registering pre- and post-grid implantation images. Results Our fiducial-based method agreed with the MRI–CT method to within an average of 8.24 mm (mean, median = 7.10 mm) across 6 subjects in 3 dimensions. It showed an average discrepancy of 2.7 mm when compared to the results of the intra-operative photograph method in a 2D coordinate system. As this method does not require post-operative imaging such as CTs, our technique should prove useful for research in intra-operative single-stage surgery scenarios. To demonstrate the use of our method, we applied our method during real-time mapping of eloquent cortex during a single-stage surgery. The results demonstrated that our method can be applied intra-operatively in the absence of post-operative imaging to acquire ECoG signals that can be valuable for neuroscientific investigations. PMID:25379417

Localizing ECoG electrodes on the cortical anatomy without post-implantation imaging.

PubMed

Gupta, Disha; Hill, N Jeremy; Adamo, Matthew A; Ritaccio, Anthony; Schalk, Gerwin

2014-01-01

Electrocorticographic (ECoG) grids are placed subdurally on the cortex in people undergoing cortical resection to delineate eloquent cortex. ECoG signals have high spatial and temporal resolution and thus can be valuable for neuroscientific research. The value of these data is highest when they can be related to the cortical anatomy. Existing methods that establish this relationship rely either on post-implantation imaging using computed tomography (CT), magnetic resonance imaging (MRI) or X-Rays, or on intra-operative photographs. For research purposes, it is desirable to localize ECoG electrodes on the brain anatomy even when post-operative imaging is not available or when intra-operative photographs do not readily identify anatomical landmarks. We developed a method to co-register ECoG electrodes to the underlying cortical anatomy using only a pre-operative MRI, a clinical neuronavigation device (such as BrainLab VectorVision), and fiducial markers. To validate our technique, we compared our results to data collected from six subjects who also had post-grid implantation imaging available. We compared the electrode coordinates obtained by our fiducial-based method to those obtained using existing methods, which are based on co-registering pre- and post-grid implantation images. Our fiducial-based method agreed with the MRI-CT method to within an average of 8.24 mm (mean, median = 7.10 mm) across 6 subjects in 3 dimensions. It showed an average discrepancy of 2.7 mm when compared to the results of the intra-operative photograph method in a 2D coordinate system. As this method does not require post-operative imaging such as CTs, our technique should prove useful for research in intra-operative single-stage surgery scenarios. To demonstrate the use of our method, we applied our method during real-time mapping of eloquent cortex during a single-stage surgery. The results demonstrated that our method can be applied intra-operatively in the absence of post-operative imaging to acquire ECoG signals that can be valuable for neuroscientific investigations.

Simultaneous multiple view high resolution surface geometry acquisition using structured light and mirrors.

PubMed

Basevi, Hector R A; Guggenheim, James A; Dehghani, Hamid; Styles, Iain B

2013-03-25

Knowledge of the surface geometry of an imaging subject is important in many applications. This information can be obtained via a number of different techniques, including time of flight imaging, photogrammetry, and fringe projection profilometry. Existing systems may have restrictions on instrument geometry, require expensive optics, or require moving parts in order to image the full surface of the subject. An inexpensive generalised fringe projection profilometry system is proposed that can account for arbitrarily placed components and use mirrors to expand the field of view. It simultaneously acquires multiple views of an imaging subject, producing a cloud of points that lie on its surface, which can then be processed to form a three dimensional model. A prototype of this system was integrated into an existing Diffuse Optical Tomography and Bioluminescence Tomography small animal imaging system and used to image objects including a mouse-shaped plastic phantom, a mouse cadaver, and a coin. A surface mesh generated from surface capture data of the mouse-shaped plastic phantom was compared with ideal surface points provided by the phantom manufacturer, and 50% of points were found to lie within 0.1mm of the surface mesh, 82% of points were found to lie within 0.2mm of the surface mesh, and 96% of points were found to lie within 0.4mm of the surface mesh.

Imaging of Brown Adipose Tissue: State of the Art

PubMed Central

Sampath, Srihari C.; Sampath, Srinath C.; Bredella, Miriam A.; Cypess, Aaron M.

2016-01-01

The rates of diabetes, obesity, and metabolic disease have reached epidemic proportions worldwide. In recent years there has been renewed interest in combating these diseases not only by modifying energy intake and lifestyle factors, but also by inducing endogenous energy expenditure. This approach has largely been stimulated by the recent recognition that brown adipose tissue (BAT)—long known to promote heat production and energy expenditure in infants and hibernating mammals—also exists in adult humans. This landmark finding relied on the use of clinical fluorine 18 fluorodeoxyglucose positron emission tomography/computed tomography, and imaging techniques continue to play a crucial and increasingly central role in understanding BAT physiology and function. Herein, the authors review the origins of BAT imaging, discuss current preclinical and clinical strategies for imaging BAT, and discuss imaging methods that will provide crucial insight into metabolic disease and how it may be treated by modulating BAT activity. © RSNA, 2016 PMID:27322970

Imaging of Brown Adipose Tissue: State of the Art.

PubMed

Sampath, Srihari C; Sampath, Srinath C; Bredella, Miriam A; Cypess, Aaron M; Torriani, Martin

2016-07-01

The rates of diabetes, obesity, and metabolic disease have reached epidemic proportions worldwide. In recent years there has been renewed interest in combating these diseases not only by modifying energy intake and lifestyle factors, but also by inducing endogenous energy expenditure. This approach has largely been stimulated by the recent recognition that brown adipose tissue (BAT)-long known to promote heat production and energy expenditure in infants and hibernating mammals-also exists in adult humans. This landmark finding relied on the use of clinical fluorine 18 fluorodeoxyglucose positron emission tomography/computed tomography, and imaging techniques continue to play a crucial and increasingly central role in understanding BAT physiology and function. Herein, the authors review the origins of BAT imaging, discuss current preclinical and clinical strategies for imaging BAT, and discuss imaging methods that will provide crucial insight into metabolic disease and how it may be treated by modulating BAT activity. (©) RSNA, 2016.

Digital photogrammetry at the U.S. Geological Survey

USGS Publications Warehouse

Greve, Clifford W.

1995-01-01

The U.S. Geological Survey is converting its primary map production and revision operations to use digital photogrammetric techniques. The primary source of data for these operations is the digital orthophoto quadrangle derived from National Aerial Photography Program images. These digital orthophotos are used on workstations that permit comparison of existing vector and raster data with the orthophoto and interactive collection and revision of the vector data.

A survey of GPU-based medical image computing techniques

PubMed Central

Shi, Lin; Liu, Wen; Zhang, Heye; Xie, Yongming

2012-01-01

Medical imaging currently plays a crucial role throughout the entire clinical applications from medical scientific research to diagnostics and treatment planning. However, medical imaging procedures are often computationally demanding due to the large three-dimensional (3D) medical datasets to process in practical clinical applications. With the rapidly enhancing performances of graphics processors, improved programming support, and excellent price-to-performance ratio, the graphics processing unit (GPU) has emerged as a competitive parallel computing platform for computationally expensive and demanding tasks in a wide range of medical image applications. The major purpose of this survey is to provide a comprehensive reference source for the starters or researchers involved in GPU-based medical image processing. Within this survey, the continuous advancement of GPU computing is reviewed and the existing traditional applications in three areas of medical image processing, namely, segmentation, registration and visualization, are surveyed. The potential advantages and associated challenges of current GPU-based medical imaging are also discussed to inspire future applications in medicine. PMID:23256080

Intelligent Interfaces for Mining Large-Scale RNAi-HCS Image Databases

PubMed Central

Lin, Chen; Mak, Wayne; Hong, Pengyu; Sepp, Katharine; Perrimon, Norbert

2010-01-01

Recently, High-content screening (HCS) has been combined with RNA interference (RNAi) to become an essential image-based high-throughput method for studying genes and biological networks through RNAi-induced cellular phenotype analyses. However, a genome-wide RNAi-HCS screen typically generates tens of thousands of images, most of which remain uncategorized due to the inadequacies of existing HCS image analysis tools. Until now, it still requires highly trained scientists to browse a prohibitively large RNAi-HCS image database and produce only a handful of qualitative results regarding cellular morphological phenotypes. For this reason we have developed intelligent interfaces to facilitate the application of the HCS technology in biomedical research. Our new interfaces empower biologists with computational power not only to effectively and efficiently explore large-scale RNAi-HCS image databases, but also to apply their knowledge and experience to interactive mining of cellular phenotypes using Content-Based Image Retrieval (CBIR) with Relevance Feedback (RF) techniques. PMID:21278820

Liver diffusion-weighted MR imaging: reproducibility comparison of ADC measurements obtained with multiple breath-hold, free-breathing, respiratory-triggered, and navigator-triggered techniques.

PubMed

Chen, Xin; Qin, Lei; Pan, Dan; Huang, Yanqi; Yan, Lifen; Wang, Guangyi; Liu, Yubao; Liang, Changhong; Liu, Zaiyi

2014-04-01

To prospectively compare the reproducibility of normal liver apparent diffusion coefficient (ADC) measurements by using different respiratory motion compensation techniques with multiple breath-hold (MBH), free-breathing (FB), respiratory-triggered (RT), and navigator-triggered (NT) diffusion-weighted (DW) imaging and to compare the ADCs at different liver anatomic locations. The study protocol was approved by the institutional review board, and written informed consent was obtained from each participant. Thirty-nine volunteers underwent liver DW imaging twice. Imaging was performed with a 1.5-T MR imager with MBH, FB, RT, and NT techniques (b = 0, 100, and 500 sec/mm(2)). Three representative sections--superior, central, and inferior--were selected on left and right liver lobes, respectively. On each selected section, three regions of interest were drawn, and ADCs were measured. Analysis of variance was used to assess ADCs among the four techniques and various anatomic locations. Reproducibility of ADCs was assessed with the Bland-Altman method. ADCs obtained with MBH (range: right lobe, [1.641-1.662] × 10(-3)mm(2)/sec; left lobe, [2.034-2.054] ×10(-3)mm(2)/sec) were higher than those obtained with FB (right, [1.349-1.391] ×10(-3)mm(2)/sec; left, [1.630-1.700] ×10(-3)mm(2)/sec), RT (right, [1.439-1.455] ×10(-3)mm(2)/sec; left, [1.720-1.755] ×10(-3)mm(2)/sec), or NT (right, [1.387-1.400] ×10(-3)mm(2)/sec; left, [1.661-1.736] ×10(-3)mm(2)/sec) techniques (P < .001); however, no significant difference was observed between ADCs obtained with FB, RT, and NT techniques (P = .130 to P >.99). ADCs showed a trend to decrease moving from left to right. Reproducibility in the left liver lobe was inferior to that in the right, and the central middle segment in the right lobe had the most reproducible ADC. Statistical differences in ADCs were observed in the left-right direction in the right lobe (P < .001), but they were not observed in the superior-inferior direction (P = .144-.450). However, in the left liver lobe, statistical differences existed in both directions (P = .001 to P = .016 in the left-right direction, P < .001 in the superior-inferior direction). Both anatomic location and DW imaging technique influence liver ADC measurements and their reproducibility. FB DW imaging is recommended for liver DW imaging because of its good reproducibility and shorter acquisition time compared with that of MBH, RT, and NT techniques. RSNA, 2014

Intravital hybrid optical-optoacoustic microscopy based on fiber-Bragg interferometry

NASA Astrophysics Data System (ADS)

Shnaiderman, Rami; Wissmeyer, Georg; Seeger, Markus; Estrada, Hector; Ntziachristos, Vasilis

2018-02-01

Optoacoustic microscopy (OAM) has enabled high-resolution, label-free imaging of tissues at depths not achievable with purely optical microscopy. However, widespread implementation of OAM into existing epi-illumination microscopy setups is often constrained by the performance and size of the commonly used piezoelectric ultrasound detectors. In this work, we introduce a novel acoustic detector based on a π-phase-shifted fiber Bragg grating (π-FBG) interferometer embedded inside an ellipsoidal acoustic cavity. The cavity enables seamless integration of epi-illumination OAM into existing microscopy setups by decoupling the acoustic and optical paths between the microscope objective and the sample. The cavity also acts as an acoustic condenser, boosting the sensitivity of the π-FBG and enabling cost effective CW-laser interrogation technique. We characterize the sensor's sensitivity and bandwidth and demonstrate hybrid OAM and second-harmonic imaging of phantoms and mouse tissue in vivo.

A Description for Rock Joint Roughness Based on Terrestrial Laser Scanner and Image Analysis

PubMed Central

Ge, Yunfeng; Tang, Huiming; Eldin, M. A. M Ez; Chen, Pengyu; Wang, Liangqing; Wang, Jinge

2015-01-01

Shear behavior of rock mass greatly depends upon the rock joint roughness which is generally characterized by anisotropy, scale effect and interval effect. A new index enabling to capture all the three features, namely brightness area percentage (BAP), is presented to express the roughness based on synthetic illumination of a digital terrain model derived from terrestrial laser scanner (TLS). Since only tiny planes facing opposite to shear direction make contribution to resistance during shear failure, therefore these planes are recognized through the image processing technique by taking advantage of the fact that they appear brighter than other ones under the same light source. Comparison with existing roughness indexes and two case studies were illustrated to test the performance of BAP description. The results reveal that the rock joint roughness estimated by the presented description has a good match with existing roughness methods and displays a wider applicability. PMID:26585247

Environmental Recognition and Guidance Control for Autonomous Vehicles using Dual Vision Sensor and Applications

NASA Astrophysics Data System (ADS)

Moriwaki, Katsumi; Koike, Issei; Sano, Tsuyoshi; Fukunaga, Tetsuya; Tanaka, Katsuyuki

We propose a new method of environmental recognition around an autonomous vehicle using dual vision sensor and navigation control based on binocular images. We consider to develop a guide robot that can play the role of a guide dog as the aid to people such as the visually impaired or the aged, as an application of above-mentioned techniques. This paper presents a recognition algorithm, which finds out the line of a series of Braille blocks and the boundary line between a sidewalk and a roadway where a difference in level exists by binocular images obtained from a pair of parallelarrayed CCD cameras. This paper also presents a tracking algorithm, with which the guide robot traces along a series of Braille blocks and avoids obstacles and unsafe areas which exist in the way of a person with the guide robot.

Expansion Mini-Microscopy: An Enabling Alternative in Point-of-Care Diagnostics

PubMed Central

Zhang, Yu Shrike; Santiago, Grissel Trujillo-de; Alvarez, Mario Moisés; Schiff, Steven J.; Boyden, Edward S.; Khademhosseini, Ali

2017-01-01

Diagnostics play a significant role in health care. In the developing world and low-resource regions the utility for point-of-care (POC) diagnostics becomes even greater. This need has long been recognized, and diagnostic technology has seen tremendous progress with the development of portable instrumentation such as miniature imagers featuring low complexity and cost. However, such inexpensive devices have not been able to achieve a resolution sufficient for POC detection of pathogens at very small scales, such as single-cell parasites, bacteria, fungi, and viruses. To this end, expansion microscopy (ExM) is a recently developed technique that, by physically expanding preserved biological specimens through a chemical process, enables super-resolution imaging on conventional microscopes and improves imaging resolution of a given microscope without the need to modify the existing microscope hardware. Here we review recent advances in ExM and portable imagers, respectively, and discuss the rational combination of the two technologies, that we term expansion mini-microscopy (ExMM). In ExMM, the physical expansion of a biological sample followed by imaging on a mini-microscope achieves a resolution as high as that attainable by conventional high-end microscopes imaging non-expanded samples, at significant reduction in cost. We believe that this newly developed ExMM technique is likely to find widespread applications in POC diagnostics in resource-limited and remote regions by expanded-scale imaging of biological specimens that are otherwise not resolvable using low-cost imagers. PMID:29062977

Clinical application of indocyanine green-fluorescence imaging during hepatectomy

PubMed Central

Ishizawa, Takeaki; Saiura, Akio

2016-01-01

In hepatobiliary surgery, the fluorescence and bile excretion of indocyanine green (ICG) can be used for real-time visualization of biological structure. Fluorescence cholangiography is used to obtain fluorescence images of the bile ducts following intrabiliary injection of 0.025−0.5 mg/mL ICG or intravenous injection of 2.5 mg ICG. Recently, the latter technique has been used in laparoscopic/robotic cholecystectomy. Intraoperative fluorescence imaging can be used to identify subcapsular hepatic tumors. Primary and secondary hepatic malignancy can be identified by intraoperative fluorescence imaging using preoperative intravenous injection of ICG through biliary excretion disorders that exist in cancerous tissues of hepatocellular carcinoma (HCC) and in non-cancerous hepatic parenchyma around adenocarcinoma foci. Intraoperative fluorescence imaging may help detect tumors to be removed, especially during laparoscopic hepatectomy, in which visual inspection and palpation are limited, compared with open surgery. Fluorescence imaging can also be used to identify hepatic segments. Boundaries of hepatic segments can be visualized following injection of 0.25−2.5 mg/mL ICG into the portal veins or by intravenous injection of 2.5 mg ICG following closure of the proximal portal pedicle toward hepatic regions to be removed. These techniques enable identification of hepatic segments before hepatectomy and during parenchymal transection for anatomic resection. Advances in imaging systems will increase the use of fluorescence imaging as an intraoperative navigation tool that can enhance the safety and accuracy of open and laparoscopic/robotic hepatobiliary surgery. PMID:27500144

Radar studies of the atmosphere using spatial and frequency diversity

NASA Astrophysics Data System (ADS)

Yu, Tian-You

This work provides results from a thorough investigation of atmospheric radar imaging including theory, numerical simulations, observational verification, and applications. The theory is generalized to include the existing imaging techniques of coherent radar imaging (CRI) and range imaging (RIM), which are shown to be special cases of three-dimensional imaging (3D Imaging). Mathematically, the problem of atmospheric radar imaging is posed as an inverse problem. In this study, the Fourier, Capon, and maximum entropy (MaxEnt) methods are proposed to solve the inverse problem. After the introduction of the theory, numerical simulations are used to test, validate, and exercise these techniques. Statistical comparisons of the three methods of atmospheric radar imaging are presented for various signal-to-noise ratio (SNR), receiver configuration, and frequency sampling. The MaxEnt method is shown to generally possess the best performance for low SNR. The performance of the Capon method approaches the performance of the MaxEnt method for high SNR. In limited cases, the Capon method actually outperforms the MaxEnt method. The Fourier method generally tends to distort the model structure due to its limited resolution. Experimental justification of CRI and RIM is accomplished using the Middle and Upper (MU) Atmosphere Radar in Japan and the SOUnding SYstem (SOUSY) in Germany, respectively. A special application of CRI to the observation of polar mesosphere summer echoes (PMSE) is used to show direct evidence of wave steepening and possibly explain gravity wave variations associated with PMSE.

Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

PubMed

Ashraf, Rehan; Ahmed, Mudassar; Jabbar, Sohail; Khalid, Shehzad; Ahmad, Awais; Din, Sadia; Jeon, Gwangil

2018-01-25

Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is a open research problem. Content-Based Image Retrieval (CBIR) is a process that provides a framework for image search and low-level visual features are commonly used to retrieve the images from the image database. The basic requirement in any image retrieval process is to sort the images with a close similarity in term of visually appearance. The color, shape and texture are the examples of low-level image features. The feature plays a significant role in image processing. The powerful representation of an image is known as feature vector and feature extraction techniques are applied to get features that will be useful in classifying and recognition of images. As features define the behavior of an image, they show its place in terms of storage taken, efficiency in classification and obviously in time consumption also. In this paper, we are going to discuss various types of features, feature extraction techniques and explaining in what scenario, which features extraction technique will be better. The effectiveness of the CBIR approach is fundamentally based on feature extraction. In image processing errands like object recognition and image retrieval feature descriptor is an immense among the most essential step. The main idea of CBIR is that it can search related images to an image passed as query from a dataset got by using distance metrics. The proposed method is explained for image retrieval constructed on YCbCr color with canny edge histogram and discrete wavelet transform. The combination of edge of histogram and discrete wavelet transform increase the performance of image retrieval framework for content based search. The execution of different wavelets is additionally contrasted with discover the suitability of specific wavelet work for image retrieval. The proposed algorithm is prepared and tried to implement for Wang image database. For Image Retrieval Purpose, Artificial Neural Networks (ANN) is used and applied on standard dataset in CBIR domain. The execution of the recommended descriptors is assessed by computing both Precision and Recall values and compared with different other proposed methods with demonstrate the predominance of our method. The efficiency and effectiveness of the proposed approach outperforms the existing research in term of average precision and recall values.

Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

NASA Astrophysics Data System (ADS)

Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

2015-10-01

The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

3D shape measurement of moving object with FFT-based spatial matching

NASA Astrophysics Data System (ADS)

Guo, Qinghua; Ruan, Yuxi; Xi, Jiangtao; Song, Limei; Zhu, Xinjun; Yu, Yanguang; Tong, Jun

2018-03-01

This work presents a new technique for 3D shape measurement of moving object in translational motion, which finds applications in online inspection, quality control, etc. A low-complexity 1D fast Fourier transform (FFT)-based spatial matching approach is devised to obtain accurate object displacement estimates, and it is combined with single shot fringe pattern prolometry (FPP) techniques to achieve high measurement performance with multiple captured images through coherent combining. The proposed technique overcomes some limitations of existing ones. Specifically, the placement of marks on object surface and synchronization between projector and camera are not needed, the velocity of the moving object is not required to be constant, and there is no restriction on the movement trajectory. Both simulation and experimental results demonstrate the effectiveness of the proposed technique.

Performance assessment of 3D surface imaging technique for medical imaging applications

NASA Astrophysics Data System (ADS)

Li, Tuotuo; Geng, Jason; Li, Shidong

2013-03-01

Recent development in optical 3D surface imaging technologies provide better ways to digitalize the 3D surface and its motion in real-time. The non-invasive 3D surface imaging approach has great potential for many medical imaging applications, such as motion monitoring of radiotherapy, pre/post evaluation of plastic surgery and dermatology, to name a few. Various commercial 3D surface imaging systems have appeared on the market with different dimension, speed and accuracy. For clinical applications, the accuracy, reproducibility and robustness across the widely heterogeneous skin color, tone, texture, shape properties, and ambient lighting is very crucial. Till now, a systematic approach for evaluating the performance of different 3D surface imaging systems still yet exist. In this paper, we present a systematic performance assessment approach to 3D surface imaging system assessment for medical applications. We use this assessment approach to exam a new real-time surface imaging system we developed, dubbed "Neo3D Camera", for image-guided radiotherapy (IGRT). The assessments include accuracy, field of view, coverage, repeatability, speed and sensitivity to environment, texture and color.

Method of Improved Fuzzy Contrast Combined Adaptive Threshold in NSCT for Medical Image Enhancement

PubMed Central

Yang, Jie; Kasabov, Nikola

2017-01-01

Noises and artifacts are introduced to medical images due to acquisition techniques and systems. This interference leads to low contrast and distortion in images, which not only impacts the effectiveness of the medical image but also seriously affects the clinical diagnoses. This paper proposes an algorithm for medical image enhancement based on the nonsubsampled contourlet transform (NSCT), which combines adaptive threshold and an improved fuzzy set. First, the original image is decomposed into the NSCT domain with a low-frequency subband and several high-frequency subbands. Then, a linear transformation is adopted for the coefficients of the low-frequency component. An adaptive threshold method is used for the removal of high-frequency image noise. Finally, the improved fuzzy set is used to enhance the global contrast and the Laplace operator is used to enhance the details of the medical images. Experiments and simulation results show that the proposed method is superior to existing methods of image noise removal, improves the contrast of the image significantly, and obtains a better visual effect. PMID:28744464

Radar fall detection using principal component analysis

NASA Astrophysics Data System (ADS)

Jokanovic, Branka; Amin, Moeness; Ahmad, Fauzia; Boashash, Boualem

2016-05-01

Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant parameter tuning in order to provide successful detections. In this paper, we employ principal component analysis for fall detection, wherein eigen images of observed motions are employed for classification. Using real data, we demonstrate that the PCA based technique provides performance improvement over the conventional feature extraction methods.

Final Project Report: Imaging Fault Zones Using a Novel Elastic Reverse-Time Migration Imaging Technique

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

Huang, Lianjie; Chen, Ting; Tan, Sirui

Imaging fault zones and fractures is crucial for geothermal operators, providing important information for reservoir evaluation and management strategies. However, there are no existing techniques available for directly and clearly imaging fault zones, particularly for steeply dipping faults and fracture zones. In this project, we developed novel acoustic- and elastic-waveform inversion methods for high-resolution velocity model building. In addition, we developed acoustic and elastic reverse-time migration methods for high-resolution subsurface imaging of complex subsurface structures and steeply-dipping fault/fracture zones. We first evaluated and verified the improved capabilities of our newly developed seismic inversion and migration imaging methods using synthetic seismicmore » data. Our numerical tests verified that our new methods directly image subsurface fracture/fault zones using surface seismic reflection data. We then applied our novel seismic inversion and migration imaging methods to a field 3D surface seismic dataset acquired at the Soda Lake geothermal field using Vibroseis sources. Our migration images of the Soda Lake geothermal field obtained using our seismic inversion and migration imaging algorithms revealed several possible fault/fracture zones. AltaRock Energy, Inc. is working with Cyrq Energy, Inc. to refine the geologic interpretation at the Soda Lake geothermal field. Trenton Cladouhos, Senior Vice President R&D of AltaRock, was very interested in our imaging results of 3D surface seismic data from the Soda Lake geothermal field. He planed to perform detailed interpretation of our images in collaboration with James Faulds and Holly McLachlan of University of Nevada at Reno. Using our high-resolution seismic inversion and migration imaging results can help determine the optimal locations to drill wells for geothermal energy production and reduce the risk of geothermal exploration.« less

[In vivo reflectance confocal microscopy in dermatology: a proposal concerning French terminology].

PubMed

Kanitakis, J; Bahadoran, P; Braun, R; Debarbieux, S; Labeille, B; Perrot, J-L; Vabres, P

2013-11-01

Reflectance confocal microscopy (RCM) is a recently introduced non-invasive imaging technique allowing real-time examination of the skin in vivo. Whereas a substantial literature concerning RCM exists in English, so far there is no official terminology in French, despite the fact that an ever-growing number of French-speaking dermatologists now use this new imaging technique. The aim of the present study is to propose a French terminology for RCM in order to allow French-speaking dermatologists to communicate in a precise and homogeneous language on this topic. A group of French-speaking dermatologists with solid experience of RCM, members of the Non-invasive Cutaneous Imaging group of the French Society of Dermatology, endeavored to suggest terms in French concerning RCM. Each group member dealt with a specific paragraph. The members exchanged comments via email and the terminology was finalized during a meeting of the group members in Paris in June 2012. Descriptive terms referring to the RCM aspects of normal and diseased skin were proposed. Some of these already existed, being used in routine dermatopathology, while other specific terms were created or adapted from the English terminology. This terminology will allow French-speaking dermatologists using RCM to communicate their findings in a homogeneous language. It may be enriched in the future by the introduction of additional terms describing new aspects of both normal and, especially, diseased skin. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Conjunctive patches subspace learning with side information for collaborative image retrieval.

PubMed

Zhang, Lining; Wang, Lipo; Lin, Weisi

2012-08-01

Content-Based Image Retrieval (CBIR) has attracted substantial attention during the past few years for its potential practical applications to image management. A variety of Relevance Feedback (RF) schemes have been designed to bridge the semantic gap between the low-level visual features and the high-level semantic concepts for an image retrieval task. Various Collaborative Image Retrieval (CIR) schemes aim to utilize the user historical feedback log data with similar and dissimilar pairwise constraints to improve the performance of a CBIR system. However, existing subspace learning approaches with explicit label information cannot be applied for a CIR task, although the subspace learning techniques play a key role in various computer vision tasks, e.g., face recognition and image classification. In this paper, we propose a novel subspace learning framework, i.e., Conjunctive Patches Subspace Learning (CPSL) with side information, for learning an effective semantic subspace by exploiting the user historical feedback log data for a CIR task. The CPSL can effectively integrate the discriminative information of labeled log images, the geometrical information of labeled log images and the weakly similar information of unlabeled images together to learn a reliable subspace. We formally formulate this problem into a constrained optimization problem and then present a new subspace learning technique to exploit the user historical feedback log data. Extensive experiments on both synthetic data sets and a real-world image database demonstrate the effectiveness of the proposed scheme in improving the performance of a CBIR system by exploiting the user historical feedback log data.

Bioluminescent magnetic nanoparticles as potential imaging agents for mammalian spermatozoa.

PubMed

Vasquez, Erick S; Feugang, Jean M; Willard, Scott T; Ryan, Peter L; Walters, Keisha B

2016-03-17

Nanoparticles have emerged as key materials for developing applications in nanomedicine, nanobiotechnology, bioimaging and theranostics. Existing bioimaging technologies include bioluminescent resonance energy transfer-conjugated quantum dots (BRET-QDs). Despite the current use of BRET-QDs for bioimaging, there are strong concerns about QD nanocomposites containing cadmium which exhibits potential cellular toxicity. In this study, bioluminescent composites comprised of magnetic nanoparticles and firefly luciferase (Photinus pyralis) are examined as potential light-emitting agents for imaging, detection, and tracking mammalian spermatozoa. Characterization was carried out using infrared spectroscopy, TEM and cryo-TEM imaging, and ζ-potential measurements to demonstrate the successful preparation of these nanocomposites. Binding interactions between the synthesized nanoparticles and spermatozoon were characterized using confocal and atomic/magnetic force microscopy. Bioluminescence imaging and UV-visible-NIR microscopy results showed light emission from sperm samples incubated with the firefly luciferase-modified nanoparticles. Therefore, these newly synthesized luciferase-modified magnetic nanoparticles show promise as substitutes for QD labeling, and can potentially also be used for in vivo manipulation and tracking, as well as MRI techniques. These preliminary data indicate that luciferase-magnetic nanoparticle composites can potentially be used for spermatozoa detection and imaging. Their magnetic properties add additional functionality to allow for manipulation, sorting, or tracking of cells using magnetic techniques.

LA-iMageS: a software for elemental distribution bioimaging using LA-ICP-MS data.

PubMed

López-Fernández, Hugo; de S Pessôa, Gustavo; Arruda, Marco A Z; Capelo-Martínez, José L; Fdez-Riverola, Florentino; Glez-Peña, Daniel; Reboiro-Jato, Miguel

2016-01-01

The spatial distribution of chemical elements in different types of samples is an important field in several research areas such as biology, paleontology or biomedicine, among others. Elemental distribution imaging by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) is an effective technique for qualitative and quantitative imaging due to its high spatial resolution and sensitivity. By applying this technique, vast amounts of raw data are generated to obtain high-quality images, essentially making the use of specific LA-ICP-MS imaging software that can process such data absolutely mandatory. Since existing solutions are usually commercial or hard-to-use for average users, this work introduces LA-iMageS, an open-source, free-to-use multiplatform application for fast and automatic generation of high-quality elemental distribution bioimages from LA-ICP-MS data in the PerkinElmer Elan XL format, whose results can be directly exported to external applications for further analysis. A key strength of LA-iMageS is its substantial added value for users, with particular regard to the customization of the elemental distribution bioimages, which allows, among other features, the ability to change color maps, increase image resolution or toggle between 2D and 3D visualizations.

Wireless fluorescence capsule for endoscopy using single photon-based detection

NASA Astrophysics Data System (ADS)

Al-Rawhani, Mohammed A.; Beeley, James; Cumming, David R. S.

2015-12-01

Fluorescence Imaging (FI) is a powerful technique in biological science and clinical medicine. Current FI devices that are used either for in-vivo or in-vitro studies are expensive, bulky and consume substantial power, confining the technique to laboratories and hospital examination rooms. Here we present a miniaturised wireless fluorescence endoscope capsule with low power consumption that will pave the way for future FI systems and applications. With enhanced sensitivity compared to existing technology we have demonstrated that the capsule can be successfully used to image tissue autofluorescence and targeted fluorescence via fluorophore labelling of tissues. The capsule incorporates a state-of-the-art complementary metal oxide semiconductor single photon avalanche detector imaging array, miniaturised optical isolation, wireless technology and low power design. When in use the capsule consumes only 30.9 mW, and deploys very low-level 468 nm illumination. The device has the potential to replace highly power-hungry intrusive optical fibre based endoscopes and to extend the range of clinical examination below the duodenum. To demonstrate the performance of our capsule, we imaged fluorescence phantoms incorporating principal tissue fluorophores (flavins) and absorbers (haemoglobin). We also demonstrated the utility of marker identification by imaging a 20 μM fluorescein isothiocyanate (FITC) labelling solution on mammalian tissue.

Surpassing Humans and Computers with JellyBean: Crowd-Vision-Hybrid Counting Algorithms.

PubMed

Sarma, Akash Das; Jain, Ayush; Nandi, Arnab; Parameswaran, Aditya; Widom, Jennifer

2015-11-01

Counting objects is a fundamental image processisng primitive, and has many scientific, health, surveillance, security, and military applications. Existing supervised computer vision techniques typically require large quantities of labeled training data, and even with that, fail to return accurate results in all but the most stylized settings. Using vanilla crowd-sourcing, on the other hand, can lead to significant errors, especially on images with many objects. In this paper, we present our JellyBean suite of algorithms, that combines the best of crowds and computer vision to count objects in images, and uses judicious decomposition of images to greatly improve accuracy at low cost. Our algorithms have several desirable properties: (i) they are theoretically optimal or near-optimal , in that they ask as few questions as possible to humans (under certain intuitively reasonable assumptions that we justify in our paper experimentally); (ii) they operate under stand-alone or hybrid modes, in that they can either work independent of computer vision algorithms, or work in concert with them, depending on whether the computer vision techniques are available or useful for the given setting; (iii) they perform very well in practice, returning accurate counts on images that no individual worker or computer vision algorithm can count correctly, while not incurring a high cost.

Balanced steady state free precession for arterial spin labeling MRI: Initial experience for blood flow mapping in human brain, retina, and kidney.

PubMed

Park, Sung-Hong; Wang, Danny J J; Duong, Timothy Q

2013-09-01

We implemented pseudo-continuous ASL (pCASL) with 2D and 3D balanced steady state free precession (bSSFP) readout for mapping blood flow in the human brain, retina, and kidney, free of distortion and signal dropout, which are typically observed in the most commonly used echo-planar imaging acquisition. High resolution functional brain imaging in the human visual cortex was feasible with 3D bSSFP pCASL. Blood flow of the human retina could be imaged with pCASL and bSSFP in conjunction with a phase cycling approach to suppress the banding artifacts associated with bSSFP. Furthermore, bSSFP based pCASL enabled us to map renal blood flow within a single breath hold. Control and test-retest experiments suggested that the measured blood flow values in retina and kidney were reliable. Because there is no specific imaging tool for mapping human retina blood flow and the standard contrast agent technique for mapping renal blood flow can cause problems for patients with kidney dysfunction, bSSFP based pCASL may provide a useful tool for the diagnosis of retinal and renal diseases and can complement existing imaging techniques. Copyright © 2013 Elsevier Inc. All rights reserved.

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

Baker, Kevin L.

The purpose of this LDRD project was to demonstrate high spatial and temporal resolution x-ray imaging using optical detectors, and in particular the VISAR and OHRV diagnostics on the OMEGA laser. The x-ray source being imaged was a backlighter capsule being imploded by 39 beams of the OMEGA laser. In particular this approach utilized a semiconductor with the side facing the backlighter capsule coated with a thin aluminum layer to allow x rays to pass through the metal layer and then get absorbed in the semiconductor. The other side of the semiconductor was AR coated to allow the VISAR ormore » OHRV probe beam to sample the phase change of the semiconductor as the x rays were absorbed in the semiconductor. This technique is capable of acquiring sub-picosecond 2-D or 1-D x-ray images, detector spatial resolution of better than 10 um and the ability to operate in a high neutron flux environment expected on ignition shots with burning plasmas. In addition to demonstrating this technique on the OMEGA laser, several designs were made to improve the phase sensitivity, temporal resolution and number of frames over the existing diagnostics currently implemented on the OMEGA laser. These designs included both 2-d imaging diagnostics as well as improved 1-D imaging diagnostics which were streaked in time.« less

Depth of focus extended microscope configuration for imaging of incorporated groups of molecules, DNA constructs and clusters inside bacterial cells

NASA Astrophysics Data System (ADS)

Fessl, Tomas; Ben-Yaish, Shai; Vacha, Frantisek; Adamec, Frantisek; Zalevsky, Zeev

2009-07-01

Imaging of small objects such as single molecules, DNA clusters and single bacterial cells is problematic not only due to the lateral resolution that is obtainable in currently existing microscopy but also, and as much fundamentally limiting, due to the lack of sufficient axial depth of focus to have the full object focused simultaneously. Extension in depth of focus is helpful also for single molecule steady state FRET measurements. In this technique it is crucial to obtain data from many well focused molecules, which are often located in different axial depths. In this paper we present the implementation of an all-optical and a real time technique of extension in the depth of focus that may be incorporated in any high NA microscope system and to be used for the above mentioned applications. We demonstrate experimentally how after the integration of special optical element in high NA 100× objective lens of a single molecule imaging microscope system, the depth of focus is significantly improved while maintaining the same lateral resolution in imaging applications of incorporated groups of molecules, DNA constructs and clusters inside bacterial cells.

Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation

NASA Astrophysics Data System (ADS)

Irshad, Mehreen; Muhammad, Nazeer; Sharif, Muhammad; Yasmeen, Mussarat

2018-04-01

Conventionally, cardiac MR image analysis is done manually. Automatic examination for analyzing images can replace the monotonous tasks of massive amounts of data to analyze the global and regional functions of the cardiac left ventricle (LV). This task is performed using MR images to calculate the analytic cardiac parameter like end-systolic volume, end-diastolic volume, ejection fraction, and myocardial mass, respectively. These analytic parameters depend upon genuine delineation of epicardial, endocardial, papillary muscle, and trabeculations contours. In this paper, we propose an automatic segmentation method using the sum of absolute differences technique to localize the left ventricle. Blind morphological operations are proposed to segment and detect the LV contours of the epicardium and endocardium, automatically. We test the benchmark Sunny Brook dataset for evaluation of the proposed work. Contours of epicardium and endocardium are compared quantitatively to determine contour's accuracy and observe high matching values. Similarity or overlapping of an automatic examination to the given ground truth analysis by an expert are observed with high accuracy as with an index value of 91.30% . The proposed method for automatic segmentation gives better performance relative to existing techniques in terms of accuracy.

PubMed Central

Hackethal, Andreas; Hirschburger, Markus; Eicker, Sven Oliver; Mücke, Thomas; Lindner, Christoph; Buchweitz, Olaf

2018-01-01

Modern surgical strategies aim to reduce trauma by using functional imaging to improve surgical outcomes. This reviews considers and evaluates the importance of the fluorescent dye indocyanine green (ICG) to visualize lymph nodes, lymphatic pathways and vessels and tissue borders in an interdisciplinary setting. The work is based on a selective search of the literature in PubMed, Scopus, and Google Scholar and the authorsʼ own clinical experience. Because of its simple, radiation-free and uncomplicated application, ICG has become an important clinical indicator in recent years. In oncologic surgery ICG is used extensively to identify sentinel lymph nodes with promising results. In some studies, the detection rates with ICG have been better than the rates obtained with established procedures. When ICG is used for visualization and the quantification of tissue perfusion, it can lead to fewer cases of anastomotic insufficiency or transplant necrosis. The use of ICG for the imaging of organ borders, flap plasty borders and postoperative vascularization has also been scientifically evaluated. Combining the easily applied ICG dye with technical options for intraoperative and interventional visualization has the potential to create new functional imaging procedures which, in future, could expand or even replace existing established surgical techniques, particularly the techniques used for sentinel lymph node and anastomosis imaging. PMID:29375146

State of the art survey on MRI brain tumor segmentation.

PubMed

Gordillo, Nelly; Montseny, Eduard; Sobrevilla, Pilar

2013-10-01

Brain tumor segmentation consists of separating the different tumor tissues (solid or active tumor, edema, and necrosis) from normal brain tissues: gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). In brain tumor studies, the existence of abnormal tissues may be easily detectable most of the time. However, accurate and reproducible segmentation and characterization of abnormalities are not straightforward. In the past, many researchers in the field of medical imaging and soft computing have made significant survey in the field of brain tumor segmentation. Both semiautomatic and fully automatic methods have been proposed. Clinical acceptance of segmentation techniques has depended on the simplicity of the segmentation, and the degree of user supervision. Interactive or semiautomatic methods are likely to remain dominant in practice for some time, especially in these applications where erroneous interpretations are unacceptable. This article presents an overview of the most relevant brain tumor segmentation methods, conducted after the acquisition of the image. Given the advantages of magnetic resonance imaging over other diagnostic imaging, this survey is focused on MRI brain tumor segmentation. Semiautomatic and fully automatic techniques are emphasized. Copyright © 2013 Elsevier Inc. All rights reserved.

Gen-2 hand-held optical imager towards cancer imaging: reflectance and transillumination phantom studies.

PubMed

Gonzalez, Jean; Roman, Manuela; Hall, Michael; Godavarty, Anuradha

2012-01-01

Hand-held near-infrared (NIR) optical imagers are developed by various researchers towards non-invasive clinical breast imaging. Unlike these existing imagers that can perform only reflectance imaging, a generation-2 (Gen-2) hand-held optical imager has been recently developed to perform both reflectance and transillumination imaging. The unique forked design of the hand-held probe head(s) allows for reflectance imaging (as in ultrasound) and transillumination or compressed imaging (as in X-ray mammography). Phantom studies were performed to demonstrate two-dimensional (2D) target detection via reflectance and transillumination imaging at various target depths (1-5 cm deep) and using simultaneous multiple point illumination approach. It was observed that 0.45 cc targets were detected up to 5 cm deep during transillumination, but limited to 2.5 cm deep during reflectance imaging. Additionally, implementing appropriate data post-processing techniques along with a polynomial fitting approach, to plot 2D surface contours of the detected signal, yields distinct target detectability and localization. The ability of the gen-2 imager to perform both reflectance and transillumination imaging allows its direct comparison to ultrasound and X-ray mammography results, respectively, in future clinical breast imaging studies.

Using the EXIST Active Shields for Earth Occultation Observations of X-Ray Sources

NASA Technical Reports Server (NTRS)

Wilson, Colleen A.; Fishman, Gerald; Hong, Jae-Sub; Gridlay, Jonathan; Krawczynski, Henric

2005-01-01

The EXIST active shields, now being planned for the main detectors of the coded aperture telescope, will have approximately 15 times the area of the BATSE detectors; and they will have a good geometry on the spacecraft for viewing both the leading and training Earth's limb for occultation observations. These occultation observations will complement the imaging observations of EXIST and can extend them to higher energies. Earth occultatio observations of the hard X-ray sky with BATSE on the Compton Gamma Ray Observatory developed and demonstrated the capabilities of large, flat, uncollimated detectors for this method. With BATSE, a catalog of 179 X-ray sources was monitored twice every spacecraft orbit for 9 years at energies above about 25 keV, resulting in 83 definite detections and 36 possible detections with 5-sigma detection sensitivities of 3.5-20 mcrab (20-430 keV) depending on the sky location. This catalog included four transients discovered with this technique and many variable objects (galactic and extragalactic). This poster will describe the Earth occultation technique, summarize the BATSE occultation observations, and compare the basic observational parameters of the occultation detector elements of BATSE and EXIST.