Detecting stripe artifacts in ultrasound images.

PubMed

Maciak, Adam; Kier, Christian; Seidel, Günter; Meyer-Wiethe, Karsten; Hofmann, Ulrich G

2009-10-01

Brain perfusion diseases such as acute ischemic stroke are detectable through computed tomography (CT)-/magnetic resonance imaging (MRI)-based methods. An alternative approach makes use of ultrasound imaging. In this low-cost bedside method, noise and artifacts degrade the imaging process. Especially stripe artifacts show a similar signal behavior compared to acute stroke or brain perfusion diseases. This document describes how stripe artifacts can be detected and eliminated in ultrasound images obtained through harmonic imaging (HI). On the basis of this new method, both proper identification of areas with critically reduced brain tissue perfusion and classification between brain perfusion defects and ultrasound stripe artifacts are made possible.

Tissue thickness calculation in ocular optical coherence tomography

PubMed Central

Alonso-Caneiro, David; Read, Scott A.; Vincent, Stephen J.; Collins, Michael J.; Wojtkowski, Maciej

2016-01-01

Thickness measurements derived from optical coherence tomography (OCT) images of the eye are a fundamental clinical and research metric, since they provide valuable information regarding the eye’s anatomical and physiological characteristics, and can assist in the diagnosis and monitoring of numerous ocular conditions. Despite the importance of these measurements, limited attention has been given to the methods used to estimate thickness in OCT images of the eye. Most current studies employing OCT use an axial thickness metric, but there is evidence that axial thickness measures may be biased by tilt and curvature of the image. In this paper, standard axial thickness calculations are compared with a variety of alternative metrics for estimating tissue thickness. These methods were tested on a data set of wide-field chorio-retinal OCT scans (field of view (FOV) 60° x 25°) to examine their performance across a wide region of interest and to demonstrate the potential effect of curvature of the posterior segment of the eye on the thickness estimates. Similarly, the effect of image tilt was systematically examined with the same range of proposed metrics. The results demonstrate that image tilt and curvature of the posterior segment can affect axial tissue thickness calculations, while alternative metrics, which are not biased by these effects, should be considered. This study demonstrates the need to consider alternative methods to calculate tissue thickness in order to avoid measurement error due to image tilt and curvature. PMID:26977367

A three-image algorithm for hard x-ray grating interferometry.

PubMed

Pelliccia, Daniele; Rigon, Luigi; Arfelli, Fulvia; Menk, Ralf-Hendrik; Bukreeva, Inna; Cedola, Alessia

2013-08-12

A three-image method to extract absorption, refraction and scattering information for hard x-ray grating interferometry is presented. The method comprises a post-processing approach alternative to the conventional phase stepping procedure and is inspired by a similar three-image technique developed for analyzer-based x-ray imaging. Results obtained with this algorithm are quantitatively comparable with phase-stepping. This method can be further extended to samples with negligible scattering, where only two images are needed to separate absorption and refraction signal. Thanks to the limited number of images required, this technique is a viable route to bio-compatible imaging with x-ray grating interferometer. In addition our method elucidates and strengthens the formal and practical analogies between grating interferometry and the (non-interferometric) diffraction enhanced imaging technique.

A multiple-point spatially weighted k-NN method for object-based classification

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

2016-10-01

Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

Strain Rate Tensor Estimation in Cine Cardiac MRI Based on Elastic Image Registration

NASA Astrophysics Data System (ADS)

Sánchez-Ferrero, Gonzalo Vegas; Vega, Antonio Tristán; Grande, Lucilio Cordero; de La Higuera, Pablo Casaseca; Fernández, Santiago Aja; Fernández, Marcos Martín; López, Carlos Alberola

In this work we propose an alternative method to estimate and visualize the Strain Rate Tensor (SRT) in Magnetic Resonance Images (MRI) when Phase Contrast MRI (PCMRI) and Tagged MRI (TMRI) are not available. This alternative is based on image processing techniques. Concretely, image registration algorithms are used to estimate the movement of the myocardium at each point. Additionally, a consistency checking method is presented to validate the accuracy of the estimates when no golden standard is available. Results prove that the consistency checking method provides an upper bound of the mean squared error of the estimate. Our experiments with real data show that the registration algorithm provides a useful deformation field to estimate the SRT fields. A classification between regional normal and dysfunctional contraction patterns, as compared with experts diagnosis, points out that the parameters extracted from the estimated SRT can represent these patterns. Additionally, a scheme for visualizing and analyzing the local behavior of the SRT field is presented.

An Alternative Approach to Teaching Public Speaking

ERIC Educational Resources Information Center

Fetzer, Ronald C.

1977-01-01

Describes the visual image approach as an alternative method of public speaking instruction based on the principle that meaning is associated with the object that meaning represents. Presents a rationale, objectives, procedures and results of implementation of this approach. (MH)

Image-based reconstruction of three-dimensional myocardial infarct geometry for patient-specific modeling of cardiac electrophysiology

PubMed Central

Ukwatta, Eranga; Arevalo, Hermenegild; Rajchl, Martin; White, James; Pashakhanloo, Farhad; Prakosa, Adityo; Herzka, Daniel A.; McVeigh, Elliot; Lardo, Albert C.; Trayanova, Natalia A.; Vadakkumpadan, Fijoy

2015-01-01

Purpose: Accurate three-dimensional (3D) reconstruction of myocardial infarct geometry is crucial to patient-specific modeling of the heart aimed at providing therapeutic guidance in ischemic cardiomyopathy. However, myocardial infarct imaging is clinically performed using two-dimensional (2D) late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) techniques, and a method to build accurate 3D infarct reconstructions from the 2D LGE-CMR images has been lacking. The purpose of this study was to address this need. Methods: The authors developed a novel methodology to reconstruct 3D infarct geometry from segmented low-resolution (Lo-res) clinical LGE-CMR images. Their methodology employed the so-called logarithm of odds (LogOdds) function to implicitly represent the shape of the infarct in segmented image slices as LogOdds maps. These 2D maps were then interpolated into a 3D image, and the result transformed via the inverse of LogOdds to a binary image representing the 3D infarct geometry. To assess the efficacy of this method, the authors utilized 39 high-resolution (Hi-res) LGE-CMR images, including 36 in vivo acquisitions of human subjects with prior myocardial infarction and 3 ex vivo scans of canine hearts following coronary ligation to induce infarction. The infarct was manually segmented by trained experts in each slice of the Hi-res images, and the segmented data were downsampled to typical clinical resolution. The proposed method was then used to reconstruct 3D infarct geometry from the downsampled images, and the resulting reconstructions were compared with the manually segmented data. The method was extensively evaluated using metrics based on geometry as well as results of electrophysiological simulations of cardiac sinus rhythm and ventricular tachycardia in individual hearts. Several alternative reconstruction techniques were also implemented and compared with the proposed method. Results: The accuracy of the LogOdds method in reconstructing 3D infarct geometry, as measured by the Dice similarity coefficient, was 82.10% ± 6.58%, a significantly higher value than those of the alternative reconstruction methods. Among outcomes of electrophysiological simulations with infarct reconstructions generated by various methods, the simulation results corresponding to the LogOdds method showed the smallest deviation from those corresponding to the manual reconstructions, as measured by metrics based on both activation maps and pseudo-ECGs. Conclusions: The authors have developed a novel method for reconstructing 3D infarct geometry from segmented slices of Lo-res clinical 2D LGE-CMR images. This method outperformed alternative approaches in reproducing expert manual 3D reconstructions and in electrophysiological simulations. PMID:26233186

Image-based reconstruction of three-dimensional myocardial infarct geometry for patient-specific modeling of cardiac electrophysiology

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

Ukwatta, Eranga, E-mail: eukwatt1@jhu.edu; Arevalo, Hermenegild; Pashakhanloo, Farhad

Purpose: Accurate three-dimensional (3D) reconstruction of myocardial infarct geometry is crucial to patient-specific modeling of the heart aimed at providing therapeutic guidance in ischemic cardiomyopathy. However, myocardial infarct imaging is clinically performed using two-dimensional (2D) late-gadolinium enhanced cardiac magnetic resonance (LGE-CMR) techniques, and a method to build accurate 3D infarct reconstructions from the 2D LGE-CMR images has been lacking. The purpose of this study was to address this need. Methods: The authors developed a novel methodology to reconstruct 3D infarct geometry from segmented low-resolution (Lo-res) clinical LGE-CMR images. Their methodology employed the so-called logarithm of odds (LogOdds) function to implicitlymore » represent the shape of the infarct in segmented image slices as LogOdds maps. These 2D maps were then interpolated into a 3D image, and the result transformed via the inverse of LogOdds to a binary image representing the 3D infarct geometry. To assess the efficacy of this method, the authors utilized 39 high-resolution (Hi-res) LGE-CMR images, including 36 in vivo acquisitions of human subjects with prior myocardial infarction and 3 ex vivo scans of canine hearts following coronary ligation to induce infarction. The infarct was manually segmented by trained experts in each slice of the Hi-res images, and the segmented data were downsampled to typical clinical resolution. The proposed method was then used to reconstruct 3D infarct geometry from the downsampled images, and the resulting reconstructions were compared with the manually segmented data. The method was extensively evaluated using metrics based on geometry as well as results of electrophysiological simulations of cardiac sinus rhythm and ventricular tachycardia in individual hearts. Several alternative reconstruction techniques were also implemented and compared with the proposed method. Results: The accuracy of the LogOdds method in reconstructing 3D infarct geometry, as measured by the Dice similarity coefficient, was 82.10% ± 6.58%, a significantly higher value than those of the alternative reconstruction methods. Among outcomes of electrophysiological simulations with infarct reconstructions generated by various methods, the simulation results corresponding to the LogOdds method showed the smallest deviation from those corresponding to the manual reconstructions, as measured by metrics based on both activation maps and pseudo-ECGs. Conclusions: The authors have developed a novel method for reconstructing 3D infarct geometry from segmented slices of Lo-res clinical 2D LGE-CMR images. This method outperformed alternative approaches in reproducing expert manual 3D reconstructions and in electrophysiological simulations.« less

Spatial dependence of predictions from image segmentation: a methods to determine appropriate scales for producing land-management information

USDA-ARS?s Scientific Manuscript database

A challenge in ecological studies is defining scales of observation that correspond to relevant ecological scales for organisms or processes. Image segmentation has been proposed as an alternative to pixel-based methods for scaling remotely-sensed data into ecologically-meaningful units. However, to...

Application of qualitative biospeckle methods for the identification of scar region in a green orange

NASA Astrophysics Data System (ADS)

Retheesh, R.; Ansari, Md. Zaheer; Radhakrishnan, P.; Mujeeb, A.

2018-03-01

This study demonstrates the feasibility of a view-based method, the motion history image (MHI) to map biospeckle activity around the scar region in a green orange fruit. The comparison of MHI with the routine intensity-based methods validated the effectiveness of the proposed method. The results show that MHI can be implementated as an alternative online image processing tool in the biospeckle analysis.

Latent Image Processing Can Bolster the Value of Quizzes.

ERIC Educational Resources Information Center

Singer, David

1985-01-01

Latent image processing is a method which reveals hidden ink when marked with a special pen. Using multiple-choice items with commercially available latent image transfers can provide immediate feedback on take-home quizzes. Students benefitted from formative evaluation and were challenged to search for alternative solutions and explain unexpected…

Commercial Implementation of Ultrasonic Velocity Imaging Methods via Cooperative Agreement Between NASA Lewis Research Center and Sonix, Inc.

NASA Technical Reports Server (NTRS)

Roth, Don J.; Hendricks, J. Lynne; Whalen, Mike F.; Bodis, James R.; Martin, Katherine

1996-01-01

This article describes the commercial implementation of ultrasonic velocity imaging methods developed and refined at NASA Lewis Research Center on the Sonix c-scan inspection system. Two velocity imaging methods were implemented: thickness-based and non-thickness-based reflector plate methods. The article demonstrates capabilities of the commercial implementation and gives the detailed operating procedures required for Sonix customers to achieve optimum velocity imaging results. This commercial implementation of velocity imaging provides a 100x speed increase in scanning and processing over the lab-based methods developed at LeRC. The significance of this cooperative effort is that the aerospace and other materials development-intensive industries which use extensive ultrasonic inspection for process control and failure analysis will now have an alternative, highly accurate imaging method commercially available.

Data volume reduction for imaging radar polarimetry

NASA Technical Reports Server (NTRS)

Zebker, Howard A. (Inventor); Held, Daniel N. (Inventor); Vanzyl, Jakob J. (Inventor); Dubois, Pascale C. (Inventor); Norikane, Lynne (Inventor)

1988-01-01

Two alternative methods are presented for digital reduction of synthetic aperture multipolarized radar data using scattering matrices, or using Stokes matrices, of four consecutive along-track pixels to produce averaged data for generating a synthetic polarization image.

Data volume reduction for imaging radar polarimetry

NASA Technical Reports Server (NTRS)

Zebker, Howard A. (Inventor); Held, Daniel N. (Inventor); van Zul, Jakob J. (Inventor); Dubois, Pascale C. (Inventor); Norikane, Lynne (Inventor)

1989-01-01

Two alternative methods are disclosed for digital reduction of synthetic aperture multipolarized radar data using scattering matrices, or using Stokes matrices, of four consecutive along-track pixels to produce averaged data for generating a synthetic polarization image.

A Comparative Study of Microscopic Images Captured by a Box Type Digital Camera Versus a Standard Microscopic Photography Camera Unit

PubMed Central

Desai, Nandini J.; Gupta, B. D.; Patel, Pratik Narendrabhai

2014-01-01

Introduction: Obtaining images of slides viewed by a microscope can be invaluable for both diagnosis and teaching.They can be transferred among technologically-advanced hospitals for further consultation and evaluation. But a standard microscopic photography camera unit (MPCU)(MIPS-Microscopic Image projection System) is costly and not available in resource poor settings. The aim of our endeavour was to find a comparable and cheaper alternative method for photomicrography. Materials and Methods: We used a NIKON Coolpix S6150 camera (box type digital camera) with Olympus CH20i microscope and a fluorescent microscope for the purpose of this study. Results: We got comparable results for capturing images of light microscopy, but the results were not as satisfactory for fluorescent microscopy. Conclusion: A box type digital camera is a comparable, less expensive and convenient alternative to microscopic photography camera unit. PMID:25478350

Valuation of imaging centers: alternative methods and detailed description of the discounted cash flow approach.

PubMed

Russell, Philip J

2007-01-01

Medical imaging centers are an increasingly integral part of the medical services landscape in America. There are many instances in which owners and potential buyers of these enterprises want to ascertain the value of the businesses. There is an industry of professionals who provide expert valuation services for many types of businesses using various recognized alternative methods, some of which are more appropriate than others when valuing an imaging center. The federal government has prescribed parameters for all valuations if they lead to transactions in which fair market value is mandated, and it also expects transactions to adhere to more generalized laws relating to entities that provide services to Medicare patients. Radiologists who own, or who are contemplating ownership of, imaging center operations need to understand the principles of valuation, specifically the factors that are involved in a discounted cash flow determination of fair market value.

Optical sectioning and 3D reconstructions as an alternative to scanning electron microscopy for analysis of cell shape.

PubMed

Landis, Jacob B; Ventura, Kayla L; Soltis, Douglas E; Soltis, Pamela S; Oppenheimer, David G

2015-04-01

Visualizing flower epidermal cells is often desirable for investigating the interaction between flowers and their pollinators, in addition to the broader range of ecological interactions in which flowers are involved. We developed a protocol for visualizing petal epidermal cells without the limitations of the commonly used method of scanning electron microscopy (SEM). Flower material was collected and fixed in glutaraldehyde, followed by dehydration in an ethanol series. Flowers were dissected to collect petals, and subjected to a Histo-Clear series to remove the cuticle. Material was then stained with aniline blue, mounted on microscope slides, and imaged using a compound fluorescence microscope to obtain optical sections that were reconstructed into a 3D image. This optical sectioning method yielded high-quality images of the petal epidermal cells with virtually no damage to cells. Flowers were processed in larger batches than are possible using common SEM methods. Also, flower size was not a limiting factor as often observed in SEM studies. Flowers up to 5 cm in length were processed and mounted for visualization. This method requires no special equipment for sample preparation prior to imaging and should be seen as an alternative method to SEM.

Magnetic Resonance Imaging of the Lung as an Alternative for a Pregnant Woman with Pulmonary Tuberculosis.

PubMed

Schloß, Manuel; Heckrodt, Jan; Schneider, Christian; Discher, Thomas; Krombach, Gabriele Anja

2015-05-01

We report a case of a pregnant 21-year-old woman with pulmonary tuberculosis in which magnetic resonance imaging of the lung was used to assess the extent and characteristics of the pathological changes. Although the lung has been mostly ignored in magnetic resonance imaging for many decades, today technical development enables detailed examinations of the lung. The technique is now entering the clinical arena and its indications are increasing. Magnetic resonance imaging of the lung is not only an alternative method without radiation exposure, it can provide additional information in pulmonary imaging compared to other modalities including computed tomography. We describe a successful application of magnetic resonance imaging of the lung and the imaging appearance of post-primary tuberculosis. This case report indicates that magnetic resonance imaging of the lung can potentially be the first choice imaging technique in pregnant women with suspected pulmonary tuberculosis.

Constrained Total Generalized p-Variation Minimization for Few-View X-Ray Computed Tomography Image Reconstruction.

PubMed

Zhang, Hanming; Wang, Linyuan; Yan, Bin; Li, Lei; Cai, Ailong; Hu, Guoen

2016-01-01

Total generalized variation (TGV)-based computed tomography (CT) image reconstruction, which utilizes high-order image derivatives, is superior to total variation-based methods in terms of the preservation of edge information and the suppression of unfavorable staircase effects. However, conventional TGV regularization employs l1-based form, which is not the most direct method for maximizing sparsity prior. In this study, we propose a total generalized p-variation (TGpV) regularization model to improve the sparsity exploitation of TGV and offer efficient solutions to few-view CT image reconstruction problems. To solve the nonconvex optimization problem of the TGpV minimization model, we then present an efficient iterative algorithm based on the alternating minimization of augmented Lagrangian function. All of the resulting subproblems decoupled by variable splitting admit explicit solutions by applying alternating minimization method and generalized p-shrinkage mapping. In addition, approximate solutions that can be easily performed and quickly calculated through fast Fourier transform are derived using the proximal point method to reduce the cost of inner subproblems. The accuracy and efficiency of the simulated and real data are qualitatively and quantitatively evaluated to validate the efficiency and feasibility of the proposed method. Overall, the proposed method exhibits reasonable performance and outperforms the original TGV-based method when applied to few-view problems.

Global-Context Based Salient Region Detection in Nature Images

NASA Astrophysics Data System (ADS)

Bao, Hong; Xu, De; Tang, Yingjun

Visually saliency detection provides an alternative methodology to image description in many applications such as adaptive content delivery and image retrieval. One of the main aims of visual attention in computer vision is to detect and segment the salient regions in an image. In this paper, we employ matrix decomposition to detect salient object in nature images. To efficiently eliminate high contrast noise regions in the background, we integrate global context information into saliency detection. Therefore, the most salient region can be easily selected as the one which is globally most isolated. The proposed approach intrinsically provides an alternative methodology to model attention with low implementation complexity. Experiments show that our approach achieves much better performance than that from the existing state-of-art methods.

Evaluation of aortic contractility based on analysis of CT images of the heart

NASA Astrophysics Data System (ADS)

DzierŻak, RóŻa; Maciejewski, Ryszard; Uhlig, Sebastian

2017-08-01

The paper presents a method to assess the aortic contractility based on the analysis of CT images of the heart. This is an alternative method that can be used for patients who cannot be examined by using echocardiography. Usage of medical imaging application for DICOM file processing allows to evaluate the aortic cross section during systole and diastole. It makes possible to assess the level of aortic contractility.

Spatially adapted second-order total generalized variational image deblurring model under impulse noise

NASA Astrophysics Data System (ADS)

Zhong, Qiu-Xiang; Wu, Chuan-Sheng; Shu, Qiao-Ling; Liu, Ryan Wen

2018-04-01

Image deblurring under impulse noise is a typical ill-posed problem which requires regularization methods to guarantee high-quality imaging. L1-norm data-fidelity term and total variation (TV) regularizer have been combined to contribute the popular regularization method. However, the TV-regularized variational image deblurring model often suffers from the staircase-like artifacts leading to image quality degradation. To enhance image quality, the detailpreserving total generalized variation (TGV) was introduced to replace TV to eliminate the undesirable artifacts. The resulting nonconvex optimization problem was effectively solved using the alternating direction method of multipliers (ADMM). In addition, an automatic method for selecting spatially adapted regularization parameters was proposed to further improve deblurring performance. Our proposed image deblurring framework is able to remove blurring and impulse noise effects while maintaining the image edge details. Comprehensive experiments have been conducted to demonstrate the superior performance of our proposed method over several state-of-the-art image deblurring methods.

Evaluation of three methods for retrospective correction of vignetting on medical microscopy images utilizing two open source software tools.

PubMed

Babaloukas, Georgios; Tentolouris, Nicholas; Liatis, Stavros; Sklavounou, Alexandra; Perrea, Despoina

2011-12-01

Correction of vignetting on images obtained by a digital camera mounted on a microscope is essential before applying image analysis. The aim of this study is to evaluate three methods for retrospective correction of vignetting on medical microscopy images and compare them with a prospective correction method. One digital image from four different tissues was used and a vignetting effect was applied on each of these images. The resulted vignetted image was replicated four times and in each replica a different method for vignetting correction was applied with fiji and gimp software tools. The highest peak signal-to-noise ratio from the comparison of each method to the original image was obtained from the prospective method in all tissues. The morphological filtering method provided the highest peak signal-to-noise ratio value amongst the retrospective methods. The prospective method is suggested as the method of choice for correction of vignetting and if it is not applicable, then the morphological filtering may be suggested as the retrospective alternative method. © 2011 The Authors Journal of Microscopy © 2011 Royal Microscopical Society.

Using the Standard Deviation of a Region of Interest in an Image to Estimate Camera to Emitter Distance

PubMed Central

Cano-García, Angel E.; Lazaro, José Luis; Infante, Arturo; Fernández, Pedro; Pompa-Chacón, Yamilet; Espinoza, Felipe

2012-01-01

In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information. PMID:22778608

Using the standard deviation of a region of interest in an image to estimate camera to emitter distance.

PubMed

Cano-García, Angel E; Lazaro, José Luis; Infante, Arturo; Fernández, Pedro; Pompa-Chacón, Yamilet; Espinoza, Felipe

2012-01-01

In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information.

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction

PubMed Central

Lu, Hongyang; Wei, Jingbo; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values. PMID:27110235

A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.

PubMed

Lu, Hongyang; Wei, Jingbo; Liu, Qiegen; Wang, Yuhao; Deng, Xiaohua

2016-01-01

Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.

Accelerated High-Dimensional MR Imaging with Sparse Sampling Using Low-Rank Tensors

PubMed Central

He, Jingfei; Liu, Qiegen; Christodoulou, Anthony G.; Ma, Chao; Lam, Fan

2017-01-01

High-dimensional MR imaging often requires long data acquisition time, thereby limiting its practical applications. This paper presents a low-rank tensor based method for accelerated high-dimensional MR imaging using sparse sampling. This method represents high-dimensional images as low-rank tensors (or partially separable functions) and uses this mathematical structure for sparse sampling of the data space and for image reconstruction from highly undersampled data. More specifically, the proposed method acquires two datasets with complementary sampling patterns, one for subspace estimation and the other for image reconstruction; image reconstruction from highly undersampled data is accomplished by fitting the measured data with a sparsity constraint on the core tensor and a group sparsity constraint on the spatial coefficients jointly using the alternating direction method of multipliers. The usefulness of the proposed method is demonstrated in MRI applications; it may also have applications beyond MRI. PMID:27093543

Cloud-Induced Uncertainty for Visual Navigation

DTIC Science & Technology

2014-12-26

images at the pixel level. The result is a method that can overlay clouds with various structures on top of any desired image to produce realistic...cloud-shaped structures . The primary contribution of this research, however, is to investigate and quantify the errors in features due to clouds. The...of clouds types, this method does not emulate the true structure of clouds. An alternative popular modern method of creating synthetic clouds is known

Water-fat separation with parallel imaging based on BLADE.

PubMed

Weng, Dehe; Pan, Yanli; Zhong, Xiaodong; Zhuo, Yan

2013-06-01

Uniform suppression of fat signal is desired in clinical applications. Based on phase differences introduced by different chemical shift frequencies, Dixon method and its variations are used as alternatives of fat saturation methods, which are sensitive to B0 inhomogeneities. Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation (IDEAL) separates water and fat images with flexible echo shifting. Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER, alternatively termed as BLADE), in conjunction with IDEAL, yields Turboprop IDEAL (TP-IDEAL) and allows for decomposition of water and fat signal with motion correction. However, the flexibility of its parameter setting is limited, and the related phase correction is complicated. To address these problems, a novel method, BLADE-Dixon, is proposed in this study. This method used the same polarity readout gradients (fly-back gradients) to acquire in-phase and opposed-phases images, which led to less complicated phase correction and more flexible parameter setting compared to TP-IDEAL. Parallel imaging and undersampling were integrated to reduce scan time. Phantom, orbit, neck and knee images were acquired with BLADE-Dixon. Water-fat separation results were compared to those measured with conventional turbo spin echo (TSE) Dixon and TSE with fat saturation, respectively, to demonstrate the performance of BLADE-Dixon. Copyright © 2013 Elsevier Inc. All rights reserved.

Blind image deconvolution using the Fields of Experts prior

NASA Astrophysics Data System (ADS)

Dong, Wende; Feng, Huajun; Xu, Zhihai; Li, Qi

2012-11-01

In this paper, we present a method for single image blind deconvolution. To improve its ill-posedness, we formulate the problem under Bayesian probabilistic framework and use a prior named Fields of Experts (FoE) which is learnt from natural images to regularize the latent image. Furthermore, due to the sparse distribution of the point spread function (PSF), we adopt a Student-t prior to regularize it. An improved alternating minimization (AM) approach is proposed to solve the resulted optimization problem. Experiments on both synthetic and real world blurred images show that the proposed method can achieve results of high quality.

[Direct lymphography with special reference to peripheral lymphedema. Historical retrospect--technique--indications--alternative procedures--image documentation].

PubMed

Gregl, A

1991-06-01

Indication for direct lymphography during the past forty years shows a downward tendency, mainly because of new alternative modern imaging methods. Nevertheless, in agreement with the actual literature it can be shown by own investigations with 8000 patients from 1964 to 1989 that one cannot give up lymphography totally. On principle lymphography is still carried out in case of testicular tumors, malignant lymphomas, unclear fever, lymphatic vessel injury and facultative in peripheric lymph edemas.

Methodology for Image-Based Reconstruction of Ventricular Geometry for Patient-Specific Modeling of Cardiac Electrophysiology

PubMed Central

Prakosa, A.; Malamas, P.; Zhang, S.; Pashakhanloo, F.; Arevalo, H.; Herzka, D. A.; Lardo, A.; Halperin, H.; McVeigh, E.; Trayanova, N.; Vadakkumpadan, F.

2014-01-01

Patient-specific modeling of ventricular electrophysiology requires an interpolated reconstruction of the 3-dimensional (3D) geometry of the patient ventricles from the low-resolution (Lo-res) clinical images. The goal of this study was to implement a processing pipeline for obtaining the interpolated reconstruction, and thoroughly evaluate the efficacy of this pipeline in comparison with alternative methods. The pipeline implemented here involves contouring the epi- and endocardial boundaries in Lo-res images, interpolating the contours using the variational implicit functions method, and merging the interpolation results to obtain the ventricular reconstruction. Five alternative interpolation methods, namely linear, cubic spline, spherical harmonics, cylindrical harmonics, and shape-based interpolation were implemented for comparison. In the thorough evaluation of the processing pipeline, Hi-res magnetic resonance (MR), computed tomography (CT), and diffusion tensor (DT) MR images from numerous hearts were used. Reconstructions obtained from the Hi-res images were compared with the reconstructions computed by each of the interpolation methods from a sparse sample of the Hi-res contours, which mimicked Lo-res clinical images. Qualitative and quantitative comparison of these ventricular geometry reconstructions showed that the variational implicit functions approach performed better than others. Additionally, the outcomes of electrophysiological simulations (sinus rhythm activation maps and pseudo-ECGs) conducted using models based on the various reconstructions were compared. These electrophysiological simulations demonstrated that our implementation of the variational implicit functions-based method had the best accuracy. PMID:25148771

Low-cost printing of computerised tomography (CT) images where there is no dedicated CT camera.

PubMed

Tabari, Abdulkadir M

2007-01-01

Many developing countries still rely on conventional hard copy images to transfer information among physicians. We have developed a low-cost alternative method of printing computerised tomography (CT) scan images where there is no dedicated camera. A digital camera is used to photograph images from the CT scan screen monitor. The images are then transferred to a PC via a USB port, before being printed on glossy paper using an inkjet printer. The method can be applied to other imaging modalities like ultrasound and MRI and appears worthy of emulation elsewhere in the developing world where resources and technical expertise are scarce.

Interactive searching of facial image databases

NASA Astrophysics Data System (ADS)

Nicholls, Robert A.; Shepherd, John W.; Shepherd, Jean

1995-09-01

A set of psychological facial descriptors has been devised to enable computerized searching of criminal photograph albums. The descriptors have been used to encode image databased of up to twelve thousand images. Using a system called FACES, the databases are searched by translating a witness' verbal description into corresponding facial descriptors. Trials of FACES have shown that this coding scheme is more productive and efficient than searching traditional photograph albums. An alternative method of searching the encoded database using a genetic algorithm is currenly being tested. The genetic search method does not require the witness to verbalize a description of the target but merely to indicate a degree of similarity between the target and a limited selection of images from the database. The major drawback of FACES is that is requires a manual encoding of images. Research is being undertaken to automate the process, however, it will require an algorithm which can predict human descriptive values. Alternatives to human derived coding schemes exist using statistical classifications of images. Since databases encoded using statistical classifiers do not have an obvious direct mapping to human derived descriptors, a search method which does not require the entry of human descriptors is required. A genetic search algorithm is being tested for such a purpose.

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

NASA Technical Reports Server (NTRS)

Abbey, Craig K.; Eckstein, Miguel P.

2002-01-01

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Quantitative Mapping of the Spatial Distribution of Nanoparticles in Endo-Lysosomes by Local pH.

PubMed

Wang, Jing; MacEwan, Sarah R; Chilkoti, Ashutosh

2017-02-08

Understanding the intracellular distribution and trafficking of nanoparticle drug carriers is necessary to elucidate their mechanisms of drug delivery and is helpful in the rational design of novel nanoparticle drug delivery systems. The traditional immunofluorescence method to study intracellular distribution of nanoparticles using organelle-specific antibodies is laborious and subject to artifacts. As an alternative, we developed a new method that exploits ratiometric fluorescence imaging of a pH-sensitive Lysosensor dye to visualize and quantify the spatial distribution of nanoparticles in the endosomes and lysosomes of live cells. Using this method, we compared the endolysosomal distribution of cell-penetrating peptide (CPP)-functionalized micelles to unfunctionalized micelles and found that CPP-functionalized micelles exhibited faster endosome-to-lysosome trafficking than unfunctionalized micelles. Ratiometric fluorescence imaging of pH-sensitive Lysosensor dye allows rapid quantitative mapping of nanoparticle distribution in endolysosomes in live cells while minimizing artifacts caused by extensive sample manipulation typical of alternative approaches. This new method can thus serve as an alternative to traditional immunofluorescence approaches to study the intracellular distribution and trafficking of nanoparticles within endosomes and lysosomes.

A rigorous and simpler method of image charges

NASA Astrophysics Data System (ADS)

Ladera, C. L.; Donoso, G.

2016-07-01

The method of image charges relies on the proven uniqueness of the solution of the Laplace differential equation for an electrostatic potential which satisfies some specified boundary conditions. Granted by that uniqueness, the method of images is rightly described as nothing but shrewdly guessing which and where image charges are to be placed to solve the given electrostatics problem. Here we present an alternative image charges method that is based not on guessing but on rigorous and simpler theoretical grounds, namely the constant potential inside any conductor and the application of powerful geometric symmetries. The aforementioned required uniqueness and, more importantly, guessing are therefore both altogether dispensed with. Our two new theoretical fundaments also allow the image charges method to be introduced in earlier physics courses for engineering and sciences students, instead of its present and usual introduction in electromagnetic theory courses that demand familiarity with the Laplace differential equation and its boundary conditions.

Detection of Melanoma Skin Cancer in Dermoscopy Images

NASA Astrophysics Data System (ADS)

Eltayef, Khalid; Li, Yongmin; Liu, Xiaohui

2017-02-01

Malignant melanoma is the most hazardous type of human skin cancer and its incidence has been rapidly increasing. Early detection of malignant melanoma in dermoscopy images is very important and critical, since its detection in the early stage can be helpful to cure it. Computer Aided Diagnosis systems can be very helpful to facilitate the early detection of cancers for dermatologists. In this paper, we present a novel method for the detection of melanoma skin cancer. To detect the hair and several noises from images, pre-processing step is carried out by applying a bank of directional filters. And therefore, Image inpainting method is implemented to fill in the unknown regions. Fuzzy C-Means and Markov Random Field methods are used to delineate the border of the lesion area in the images. The method was evaluated on a dataset of 200 dermoscopic images, and superior results were produced compared to alternative methods.

Soft tissue examination of the fetal rat and rabbit head by magnetic resonance imaging.

PubMed

French, Julian M; Woodhouse, Neil

2013-01-01

The use of magnetic resonance imaging of the fetal rat and rabbit head, as an alternative to the traditional methods of fixation and preparation of serial sections, is described. Labeled magnetic resonance images of normal head anatomy have been provided as a reference for use when evaluating the internal structures of the head.

Constrained Total Generalized p-Variation Minimization for Few-View X-Ray Computed Tomography Image Reconstruction

PubMed Central

Zhang, Hanming; Wang, Linyuan; Yan, Bin; Li, Lei; Cai, Ailong; Hu, Guoen

2016-01-01

Total generalized variation (TGV)-based computed tomography (CT) image reconstruction, which utilizes high-order image derivatives, is superior to total variation-based methods in terms of the preservation of edge information and the suppression of unfavorable staircase effects. However, conventional TGV regularization employs l1-based form, which is not the most direct method for maximizing sparsity prior. In this study, we propose a total generalized p-variation (TGpV) regularization model to improve the sparsity exploitation of TGV and offer efficient solutions to few-view CT image reconstruction problems. To solve the nonconvex optimization problem of the TGpV minimization model, we then present an efficient iterative algorithm based on the alternating minimization of augmented Lagrangian function. All of the resulting subproblems decoupled by variable splitting admit explicit solutions by applying alternating minimization method and generalized p-shrinkage mapping. In addition, approximate solutions that can be easily performed and quickly calculated through fast Fourier transform are derived using the proximal point method to reduce the cost of inner subproblems. The accuracy and efficiency of the simulated and real data are qualitatively and quantitatively evaluated to validate the efficiency and feasibility of the proposed method. Overall, the proposed method exhibits reasonable performance and outperforms the original TGV-based method when applied to few-view problems. PMID:26901410

Adaptive and robust statistical methods for processing near-field scanning microwave microscopy images.

PubMed

Coakley, K J; Imtiaz, A; Wallis, T M; Weber, J C; Berweger, S; Kabos, P

2015-03-01

Near-field scanning microwave microscopy offers great potential to facilitate characterization, development and modeling of materials. By acquiring microwave images at multiple frequencies and amplitudes (along with the other modalities) one can study material and device physics at different lateral and depth scales. Images are typically noisy and contaminated by artifacts that can vary from scan line to scan line and planar-like trends due to sample tilt errors. Here, we level images based on an estimate of a smooth 2-d trend determined with a robust implementation of a local regression method. In this robust approach, features and outliers which are not due to the trend are automatically downweighted. We denoise images with the Adaptive Weights Smoothing method. This method smooths out additive noise while preserving edge-like features in images. We demonstrate the feasibility of our methods on topography images and microwave |S11| images. For one challenging test case, we demonstrate that our method outperforms alternative methods from the scanning probe microscopy data analysis software package Gwyddion. Our methods should be useful for massive image data sets where manual selection of landmarks or image subsets by a user is impractical. Published by Elsevier B.V.

Variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction

NASA Astrophysics Data System (ADS)

Li, Shuo; Wang, Hui; Wang, Liyong; Yu, Xiangzhou; Yang, Le

2018-01-01

The uneven illumination phenomenon reduces the quality of remote sensing image and causes interference in the subsequent processing and applications. A variational method based on Retinex with double-norm hybrid constraints for uneven illumination correction is proposed. The L1 norm and the L2 norm are adopted to constrain the textures and details of reflectance image and the smoothness of the illumination image, respectively. The problem of separating the illumination image from the reflectance image is transformed into the optimal solution of the variational model. In order to accelerate the solution, the split Bregman method is used to decompose the variational model into three subproblems, which are calculated by alternate iteration. Two groups of experiments are implemented on two synthetic images and three real remote sensing images. Compared with the variational Retinex method with single-norm constraint and the Mask method, the proposed method performs better in both visual evaluation and quantitative measurements. The proposed method can effectively eliminate the uneven illumination while maintaining the textures and details of the remote sensing image. Moreover, the proposed method using split Bregman method is more than 10 times faster than the method with the steepest descent method.

Micro-CT image reconstruction based on alternating direction augmented Lagrangian method and total variation.

PubMed

Gopi, Varun P; Palanisamy, P; Wahid, Khan A; Babyn, Paul; Cooper, David

2013-01-01

Micro-computed tomography (micro-CT) plays an important role in pre-clinical imaging. The radiation from micro-CT can result in excess radiation exposure to the specimen under test, hence the reduction of radiation from micro-CT is essential. The proposed research focused on analyzing and testing an alternating direction augmented Lagrangian (ADAL) algorithm to recover images from random projections using total variation (TV) regularization. The use of TV regularization in compressed sensing problems makes the recovered image quality sharper by preserving the edges or boundaries more accurately. In this work TV regularization problem is addressed by ADAL which is a variant of the classic augmented Lagrangian method for structured optimization. The per-iteration computational complexity of the algorithm is two fast Fourier transforms, two matrix vector multiplications and a linear time shrinkage operation. Comparison of experimental results indicate that the proposed algorithm is stable, efficient and competitive with the existing algorithms for solving TV regularization problems. Copyright © 2013 Elsevier Ltd. All rights reserved.

Discriminative Structured Dictionary Learning on Grassmann Manifolds and Its Application on Image Restoration.

PubMed

Pan, Han; Jing, Zhongliang; Qiao, Lingfeng; Li, Minzhe

2017-09-25

Image restoration is a difficult and challenging problem in various imaging applications. However, despite of the benefits of a single overcomplete dictionary, there are still several challenges for capturing the geometric structure of image of interest. To more accurately represent the local structures of the underlying signals, we propose a new problem formulation for sparse representation with block-orthogonal constraint. There are three contributions. First, a framework for discriminative structured dictionary learning is proposed, which leads to a smooth manifold structure and quotient search spaces. Second, an alternating minimization scheme is proposed after taking both the cost function and the constraints into account. This is achieved by iteratively alternating between updating the block structure of the dictionary defined on Grassmann manifold and sparsifying the dictionary atoms automatically. Third, Riemannian conjugate gradient is considered to track local subspaces efficiently with a convergence guarantee. Extensive experiments on various datasets demonstrate that the proposed method outperforms the state-of-the-art methods on the removal of mixed Gaussian-impulse noise.

Quantitative photoacoustic elasticity and viscosity imaging for cirrhosis detection

NASA Astrophysics Data System (ADS)

Wang, Qian; Shi, Yujiao; Yang, Fen; Yang, Sihua

2018-05-01

Elasticity and viscosity assessments are essential for understanding and characterizing the physiological and pathological states of tissue. In this work, by establishing a photoacoustic (PA) shear wave model, an approach for quantitative PA elasticity imaging based on measurement of the rise time of the thermoelastic displacement was developed. Thus, using an existing PA viscoelasticity imaging method that features a phase delay measurement, quantitative PA elasticity imaging and viscosity imaging can be obtained in a simultaneous manner. The method was tested and validated by imaging viscoelastic agar phantoms prepared at different agar concentrations, and the imaging data were in good agreement with rheometry results. Ex vivo experiments on liver pathological models demonstrated the capability for cirrhosis detection, and the results were consistent with the corresponding histological results. This method expands the scope of conventional PA imaging and has potential to become an important alternative imaging modality.

Quantitative Image Restoration in Bright Field Optical Microscopy.

PubMed

Gutiérrez-Medina, Braulio; Sánchez Miranda, Manuel de Jesús

2017-11-07

Bright field (BF) optical microscopy is regarded as a poor method to observe unstained biological samples due to intrinsic low image contrast. We introduce quantitative image restoration in bright field (QRBF), a digital image processing method that restores out-of-focus BF images of unstained cells. Our procedure is based on deconvolution, using a point spread function modeled from theory. By comparing with reference images of bacteria observed in fluorescence, we show that QRBF faithfully recovers shape and enables quantify size of individual cells, even from a single input image. We applied QRBF in a high-throughput image cytometer to assess shape changes in Escherichia coli during hyperosmotic shock, finding size heterogeneity. We demonstrate that QRBF is also applicable to eukaryotic cells (yeast). Altogether, digital restoration emerges as a straightforward alternative to methods designed to generate contrast in BF imaging for quantitative analysis. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Robust extraction of the aorta and pulmonary artery from 3D MDCT image data

NASA Astrophysics Data System (ADS)

Taeprasartsit, Pinyo; Higgins, William E.

2010-03-01

Accurate definition of the aorta and pulmonary artery from three-dimensional (3D) multi-detector CT (MDCT) images is important for pulmonary applications. This work presents robust methods for defining the aorta and pulmonary artery in the central chest. The methods work on both contrast enhanced and no-contrast 3D MDCT image data. The automatic methods use a common approach employing model fitting and selection and adaptive refinement. During the occasional event that more precise vascular extraction is desired or the method fails, we also have an alternate semi-automatic fail-safe method. The semi-automatic method extracts the vasculature by extending the medial axes into a user-guided direction. A ground-truth study over a series of 40 human 3D MDCT images demonstrates the efficacy, accuracy, robustness, and efficiency of the methods.

Statistical iterative reconstruction for streak artefact reduction when using multidetector CT to image the dento-alveolar structures.

PubMed

Dong, J; Hayakawa, Y; Kober, C

2014-01-01

When metallic prosthetic appliances and dental fillings exist in the oral cavity, the appearance of metal-induced streak artefacts is not avoidable in CT images. The aim of this study was to develop a method for artefact reduction using the statistical reconstruction on multidetector row CT images. Adjacent CT images often depict similar anatomical structures. Therefore, reconstructed images with weak artefacts were attempted using projection data of an artefact-free image in a neighbouring thin slice. Images with moderate and strong artefacts were continuously processed in sequence by successive iterative restoration where the projection data was generated from the adjacent reconstructed slice. First, the basic maximum likelihood-expectation maximization algorithm was applied. Next, the ordered subset-expectation maximization algorithm was examined. Alternatively, a small region of interest setting was designated. Finally, the general purpose graphic processing unit machine was applied in both situations. The algorithms reduced the metal-induced streak artefacts on multidetector row CT images when the sequential processing method was applied. The ordered subset-expectation maximization and small region of interest reduced the processing duration without apparent detriments. A general-purpose graphic processing unit realized the high performance. A statistical reconstruction method was applied for the streak artefact reduction. The alternative algorithms applied were effective. Both software and hardware tools, such as ordered subset-expectation maximization, small region of interest and general-purpose graphic processing unit achieved fast artefact correction.

A method to rapidly and accurately compare relative efficacies of non-invasive imaging reporter genes in a mouse model, and its application to luciferase reporters

PubMed Central

Gil, Jose S.; Machado, Hidevaldo B.; Herschman, Harvey R.

2013-01-01

Purpose Our goal is to develop a simple, quantitative, robust method to compare the efficacy of imaging reporter genes in culture and in vivo. We describe an adenoviral vector-liver transduction procedure, and compare the luciferase reporter efficacies. Procedures Alternative reporter genes are expressed in a common adenoviral vector. Vector amounts used in vivo are based on cell culture titrations, ensuring the same transduction efficacy is used for each vector. After imaging, in vivo and in vitro values are normalized to hepatic vector transduction using quantitative real-time PCR. Results We assayed standard firefly luciferase (FLuc), enhanced firefly luciferase (EFLuc), luciferase 2 (Luc2), humanized Renilla luciferase (hRLuc), Renilla luciferase 8.6-535 (RLuc8.6), and a membrane-bound Gaussia luciferase variant (extGLuc) in cell culture and in vivo. We observed a greater that 100-fold increase in bioluminescent signal for both EFLuc and Luc2 when compared to FLuc, and a greater than 106-fold increase for RLuc8.6 when compared to hRLuc. ExtGLuc was not detectable in liver. Conclusions Our findings contrast, in some cases, with conclusions drawn in prior comparisons of these reporter genes, and demonstrate the need for a standardized method to evaluate alternative reporter genes in vivo. Our procedure can be adapted for reporter genes that utilize alternative imaging modalities (fluorescence, bioluminescence, MRI, SPECT, PET). PMID:21850545

Thermal image analysis using the serpentine method

NASA Astrophysics Data System (ADS)

Koprowski, Robert; Wilczyński, Sławomir

2018-03-01

Thermal imaging is an increasingly widespread alternative to other imaging methods. As a supplementary method in diagnostics, it can be used both statically and with dynamic temperature changes. The paper proposes a new image analysis method that allows for the acquisition of new diagnostic information as well as object segmentation. The proposed serpentine analysis uses known and new methods of image analysis and processing proposed by the authors. Affine transformations of an image and subsequent Fourier analysis provide a new diagnostic quality. The method is fully repeatable and automatic and independent of inter-individual variability in patients. The segmentation results are by 10% better than those obtained from the watershed method and the hybrid segmentation method based on the Canny detector. The first and second harmonics of serpentine analysis enable to determine the type of temperature changes in the region of interest (gradient, number of heat sources etc.). The presented serpentine method provides new quantitative information on thermal imaging and more. Since it allows for image segmentation and designation of contact points of two and more heat sources (local minimum), it can be used to support medical diagnostics in many areas of medicine.

Alternating Direction Implicit (ADI) schemes for a PDE-based image osmosis model

NASA Astrophysics Data System (ADS)

Calatroni, L.; Estatico, C.; Garibaldi, N.; Parisotto, S.

2017-10-01

We consider Alternating Direction Implicit (ADI) splitting schemes to compute efficiently the numerical solution of the PDE osmosis model considered by Weickert et al. in [10] for several imaging applications. The discretised scheme is shown to preserve analogous properties to the continuous model. The dimensional splitting strategy traduces numerically into the solution of simple tridiagonal systems for which standard matrix factorisation techniques can be used to improve upon the performance of classical implicit methods, even for large time steps. Applications to the shadow removal problem are presented.

Methods for reverberation suppression utilizing dual frequency band imaging.

PubMed

Rau, Jochen M; Måsøy, Svein-Erik; Hansen, Rune; Angelsen, Bjørn; Tangen, Thor Andreas

2013-09-01

Reverberations impair the contrast resolution of diagnostic ultrasound images. Tissue harmonic imaging is a common method to reduce these artifacts, but does not remove all reverberations. Dual frequency band imaging (DBI), utilizing a low frequency pulse which manipulates propagation of the high frequency imaging pulse, has been proposed earlier for reverberation suppression. This article adds two different methods for reverberation suppression with DBI: the delay corrected subtraction (DCS) and the first order content weighting (FOCW) method. Both methods utilize the propagation delay of the imaging pulse of two transmissions with alternating manipulation pressure to extract information about its depth of first scattering. FOCW further utilizes this information to estimate the content of first order scattering in the received signal. Initial evaluation is presented where both methods are applied to simulated and in vivo data. Both methods yield visual and measurable substantial improvement in image contrast. Comparing DCS with FOCW, DCS produces sharper images and retains more details while FOCW achieves best suppression levels and, thus, highest image contrast. The measured improvement in contrast ranges from 8 to 27 dB for DCS and from 4 dB up to the dynamic range for FOCW.

Assessing the Potential of Metal-Assisted Imaging Mass Spectrometry in Cancer Research.

PubMed

Dufresne, M; Patterson, N H; Lauzon, N; Chaurand, P

2017-01-01

In the last decade, imaging mass spectrometry (IMS) has been the primary tool for biomolecular imaging. While it is possible to map a wide range of biomolecules using matrix-assisted laser desorption/ionization IMS ranging from high-molecular-weight proteins to small metabolites, more often than not only the most abundant easily ionisable species are detected. To better understand complex diseases such as cancer more specific and sensitive methods need to be developed to enable the detection of lower abundance molecules but also molecules that have yet to be imaged by IMS. In recent years, a big shift has occurred in the imaging community from developing wide reaching methods to developing targeted ones which increases sensitivity through the use of more specific sample preparations. This has been primarily marked by the advent of solvent-free matrix deposition methods for polar lipids, chemical derivatization for hormones and metabolites, and the use of alternative ionization agents for neutral lipids. In this chapter, we discuss two of the latest sample preparations which exploit the use of alternative ionization agents to enable the detection of certain classes of neutral lipids along with free fatty acids by high-sensitivity IMS as demonstrated within our lab. © 2017 Elsevier Inc. All rights reserved.

An image retrieval framework for real-time endoscopic image retargeting.

PubMed

Ye, Menglong; Johns, Edward; Walter, Benjamin; Meining, Alexander; Yang, Guang-Zhong

2017-08-01

Serial endoscopic examinations of a patient are important for early diagnosis of malignancies in the gastrointestinal tract. However, retargeting for optical biopsy is challenging due to extensive tissue variations between examinations, requiring the method to be tolerant to these changes whilst enabling real-time retargeting. This work presents an image retrieval framework for inter-examination retargeting. We propose both a novel image descriptor tolerant of long-term tissue changes and a novel descriptor matching method in real time. The descriptor is based on histograms generated from regional intensity comparisons over multiple scales, offering stability over long-term appearance changes at the higher levels, whilst remaining discriminative at the lower levels. The matching method then learns a hashing function using random forests, to compress the string and allow for fast image comparison by a simple Hamming distance metric. A dataset that contains 13 in vivo gastrointestinal videos was collected from six patients, representing serial examinations of each patient, which includes videos captured with significant time intervals. Precision-recall for retargeting shows that our new descriptor outperforms a number of alternative descriptors, whilst our hashing method outperforms a number of alternative hashing approaches. We have proposed a novel framework for optical biopsy in serial endoscopic examinations. A new descriptor, combined with a novel hashing method, achieves state-of-the-art retargeting, with validation on in vivo videos from six patients. Real-time performance also allows for practical integration without disturbing the existing clinical workflow.

Patch-based image reconstruction for PET using prior-image derived dictionaries

NASA Astrophysics Data System (ADS)

Tahaei, Marzieh S.; Reader, Andrew J.

2016-09-01

In PET image reconstruction, regularization is often needed to reduce the noise in the resulting images. Patch-based image processing techniques have recently been successfully used for regularization in medical image reconstruction through a penalized likelihood framework. Re-parameterization within reconstruction is another powerful regularization technique in which the object in the scanner is re-parameterized using coefficients for spatially-extensive basis vectors. In this work, a method for extracting patch-based basis vectors from the subject’s MR image is proposed. The coefficients for these basis vectors are then estimated using the conventional MLEM algorithm. Furthermore, using the alternating direction method of multipliers, an algorithm for optimizing the Poisson log-likelihood while imposing sparsity on the parameters is also proposed. This novel method is then utilized to find sparse coefficients for the patch-based basis vectors extracted from the MR image. The results indicate the superiority of the proposed methods to patch-based regularization using the penalized likelihood framework.

Total generalized variation-regularized variational model for single image dehazing

NASA Astrophysics Data System (ADS)

Shu, Qiao-Ling; Wu, Chuan-Sheng; Zhong, Qiu-Xiang; Liu, Ryan Wen

2018-04-01

Imaging quality is often significantly degraded under hazy weather condition. The purpose of this paper is to recover the latent sharp image from its hazy version. It is well known that the accurate estimation of depth information could assist in improving dehazing performance. In this paper, a detail-preserving variational model was proposed to simultaneously estimate haze-free image and depth map. In particular, the total variation (TV) and total generalized variation (TGV) regularizers were introduced to restrain haze-free image and depth map, respectively. The resulting nonsmooth optimization problem was efficiently solved using the alternating direction method of multipliers (ADMM). Comprehensive experiments have been conducted on realistic datasets to compare our proposed method with several state-of-the-art dehazing methods. Results have illustrated the superior performance of the proposed method in terms of visual quality evaluation.

Dental MRI using wireless intraoral coils

NASA Astrophysics Data System (ADS)

Ludwig, Ute; Eisenbeiss, Anne-Katrin; Scheifele, Christian; Nelson, Katja; Bock, Michael; Hennig, Jürgen; von Elverfeldt, Dominik; Herdt, Olga; Flügge, Tabea; Hövener, Jan-Bernd

2016-03-01

Currently, the gold standard for dental imaging is projection radiography or cone-beam computed tomography (CBCT). These methods are fast and cost-efficient, but exhibit poor soft tissue contrast and expose the patient to ionizing radiation (X-rays). The need for an alternative imaging modality e.g. for soft tissue management has stimulated a rising interest in dental magnetic resonance imaging (MRI) which provides superior soft tissue contrast. Compared to X-ray imaging, however, so far the spatial resolution of MRI is lower and the scan time is longer. In this contribution, we describe wireless, inductively-coupled intraoral coils whose local sensitivity enables high resolution MRI of dental soft tissue. In comparison to CBCT, a similar image quality with complementary contrast was obtained ex vivo. In-vivo, a voxel size of the order of 250•250•500 μm3 was achieved in 4 min only. Compared to dental MRI acquired with clinical equipment, the quality of the images was superior in the sensitive volume of the coils and is expected to improve the planning of interventions and monitoring thereafter. This method may enable a more accurate dental diagnosis and avoid unnecessary interventions, improving patient welfare and bringing MRI a step closer to becoming a radiation-free alternative for dental imaging.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

PubMed Central

Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

2013-01-01

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

Robust sparse image reconstruction of radio interferometric observations with PURIFY

NASA Astrophysics Data System (ADS)

Pratley, Luke; McEwen, Jason D.; d'Avezac, Mayeul; Carrillo, Rafael E.; Onose, Alexandru; Wiaux, Yves

2018-01-01

Next-generation radio interferometers, such as the Square Kilometre Array, will revolutionize our understanding of the Universe through their unprecedented sensitivity and resolution. However, to realize these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as CLEAN, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and scalability for big data. In this work, we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the PURIFY software package. In particular, we implement and apply the proximal alternating direction method of multipliers algorithm presented in a recent article. First, we assess the impact of the interpolation kernel used to perform gridding and degridding on sparse image reconstruction. We find that the Kaiser-Bessel interpolation kernel performs as well as prolate spheroidal wave functions while providing a computational saving and an analytic form. Secondly, we apply PURIFY to real interferometric observations from the Very Large Array and the Australia Telescope Compact Array and find that images recovered by PURIFY are of higher quality than those recovered by CLEAN. Thirdly, we discuss how PURIFY reconstructions exhibit additional advantages over those recovered by CLEAN. The latest version of PURIFY, with developments presented in this work, is made publicly available.

Low rank alternating direction method of multipliers reconstruction for MR fingerprinting.

PubMed

Assländer, Jakob; Cloos, Martijn A; Knoll, Florian; Sodickson, Daniel K; Hennig, Jürgen; Lattanzi, Riccardo

2018-01-01

The proposed reconstruction framework addresses the reconstruction accuracy, noise propagation and computation time for magnetic resonance fingerprinting. Based on a singular value decomposition of the signal evolution, magnetic resonance fingerprinting is formulated as a low rank (LR) inverse problem in which one image is reconstructed for each singular value under consideration. This LR approximation of the signal evolution reduces the computational burden by reducing the number of Fourier transformations. Also, the LR approximation improves the conditioning of the problem, which is further improved by extending the LR inverse problem to an augmented Lagrangian that is solved by the alternating direction method of multipliers. The root mean square error and the noise propagation are analyzed in simulations. For verification, in vivo examples are provided. The proposed LR alternating direction method of multipliers approach shows a reduced root mean square error compared to the original fingerprinting reconstruction, to a LR approximation alone and to an alternating direction method of multipliers approach without a LR approximation. Incorporating sensitivity encoding allows for further artifact reduction. The proposed reconstruction provides robust convergence, reduced computational burden and improved image quality compared to other magnetic resonance fingerprinting reconstruction approaches evaluated in this study. Magn Reson Med 79:83-96, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A Range Ambiguity Suppression Processing Method for Spaceborne SAR with Up and Down Chirp Modulation.

PubMed

Wen, Xuejiao; Qiu, Xiaolan; Han, Bing; Ding, Chibiao; Lei, Bin; Chen, Qi

2018-05-07

Range ambiguity is one of the factors which affect the SAR image quality. Alternately transmitting up and down chirp modulation pulses is one of the methods used to suppress the range ambiguity. However, the defocusing range ambiguous signal can still hold the stronger backscattering intensity than the mainlobe imaging area in some case, which has a severe impact on visual effects and subsequent applications. In this paper, a novel hybrid range ambiguity suppression method for up and down chirp modulation is proposed. The method can obtain the ambiguity area image and reduce the ambiguity signal power appropriately, by applying pulse compression using a contrary modulation rate and CFAR detecting method. The effectiveness and correctness of the approach is demonstrated by processing the archive images acquired by Chinese Gaofen-3 SAR sensor in full-polarization mode.

Experimental study of microwave-induced thermoacoustic imaging

NASA Astrophysics Data System (ADS)

Jacobs, Ryan T.

Microwave-Induced Thermoacoustic Imaging (TAI) is a noninvasive hybrid modality which improves contrast by using thermoelastic wave generation induced by microwave absorption. Ultrasonography is widely used in medical practice as a low-cost alternative and supplement to magnetic resonance imaging (MRI). Although ultrasonography has relatively high image resolution (depending on the ultrasonic wavelength at diagnostic frequencies), it suffers from low image contrast of soft tissues. In this work samples are irradiated with sub-microsecond electromagnetic pulses inducing acoustic waves in the sample that are then detected with an unfocused transducer. The advantage of this hybrid modality is the ability to take advantage of the microwave absorption coefficients which provide high contrast in tissue samples. This in combination with the superior spatial resolution of ultrasound waves is important to providing a low-cost alternative to MRI and early breast cancer detection methods. This work describes the implementation of a thermoacoustic experiment using a 5 kW peak power microwave source.

Compressive Sensing via Nonlocal Smoothed Rank Function

PubMed Central

Fan, Ya-Ru; Liu, Jun; Zhao, Xi-Le

2016-01-01

Compressive sensing (CS) theory asserts that we can reconstruct signals and images with only a small number of samples or measurements. Recent works exploiting the nonlocal similarity have led to better results in various CS studies. To better exploit the nonlocal similarity, in this paper, we propose a non-convex smoothed rank function based model for CS image reconstruction. We also propose an efficient alternating minimization method to solve the proposed model, which reduces a difficult and coupled problem to two tractable subproblems. Experimental results have shown that the proposed method performs better than several existing state-of-the-art CS methods for image reconstruction. PMID:27583683

A comparative study on generating simulated Landsat NDVI images using data fusion and regression method-the case of the Korean Peninsula.

PubMed

Lee, Mi Hee; Lee, Soo Bong; Eo, Yang Dam; Kim, Sun Woong; Woo, Jung-Hun; Han, Soo Hee

2017-07-01

Landsat optical images have enough spatial and spectral resolution to analyze vegetation growth characteristics. But, the clouds and water vapor degrade the image quality quite often, which limits the availability of usable images for the time series vegetation vitality measurement. To overcome this shortcoming, simulated images are used as an alternative. In this study, weighted average method, spatial and temporal adaptive reflectance fusion model (STARFM) method, and multilinear regression analysis method have been tested to produce simulated Landsat normalized difference vegetation index (NDVI) images of the Korean Peninsula. The test results showed that the weighted average method produced the images most similar to the actual images, provided that the images were available within 1 month before and after the target date. The STARFM method gives good results when the input image date is close to the target date. Careful regional and seasonal consideration is required in selecting input images. During summer season, due to clouds, it is very difficult to get the images close enough to the target date. Multilinear regression analysis gives meaningful results even when the input image date is not so close to the target date. Average R 2 values for weighted average method, STARFM, and multilinear regression analysis were 0.741, 0.70, and 0.61, respectively.

Time-alternating method based on single-sideband holography with half-zone-plate processing for the enlargement of viewing zones.

PubMed

Mishina, T; Okano, F; Yuyama, I

1999-06-10

The single-sideband method of holography, as is well known, cuts off beams that come from conjugate images for holograms produced in the Fraunhofer region and from objects with no phase components. The single-sideband method with half-zone-plate processing is also effective in the Fresnel region for beams from an object that has phase components. However, this method restricts the viewing zone to a narrow range. We propose a method to improve this restriction by time-alternating switching of hologram patterns and a spatial filter set on the focal plane of a reconstruction lens.

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

NASA Astrophysics Data System (ADS)

Qian, Tingting; Wang, Lianlian; Lu, Guanghua

2017-07-01

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

Imaging of the small bowel in Crohn's disease: A review of old and new techniques

PubMed Central

Saibeni, Simone; Rondonotti, Emanuele; Iozzelli, Andrea; Spina, Luisa; Tontini, Gian Eugenio; Cavallaro, Flaminia; Ciscato, Camilla; de Franchis, Roberto; Sardanelli, Francesco; Vecchi, Maurizio

2007-01-01

The investigation of small bowel morphology is often mandatory in many patients with Crohn’s disease. Traditional radiological techniques (small bowel enteroclysis and small bowel follow-through) have long been the only suitable methods for this purpose. In recent years, several alternative imaging techniques have been proposed. To review the most recent advances in imaging studies of the small bowel, with particular reference to their possible application in Crohn’s disease, we conducted a complete review of the most important studies in which traditional and newer imaging methods were performed and compared in patients with Crohn’s disease. Several radiological and endoscopic techniques are now available for the study of the small bowel; each of them is characterized by a distinct profile of favourable and unfavourable features. In some cases, they may also be used as complementary rather than alternative techniques. In everyday practice, the choice of the technique to be used stands upon its availability and a careful evaluation of diagnostic accuracy, clinical usefulness, safety and cost. The recent development of innovative imaging techniques has opened a new and exciting area in the exploration of the small bowel in Crohn’s disease patients. PMID:17659666

Reference-free ground truth metric for metal artifact evaluation in CT images.

PubMed

Kratz, Bärbel; Ens, Svitlana; Müller, Jan; Buzug, Thorsten M

2011-07-01

In computed tomography (CT), metal objects in the region of interest introduce data inconsistencies during acquisition. Reconstructing these data results in an image with star shaped artifacts induced by the metal inconsistencies. To enhance image quality, the influence of the metal objects can be reduced by different metal artifact reduction (MAR) strategies. For an adequate evaluation of new MAR approaches a ground truth reference data set is needed. In technical evaluations, where phantoms can be measured with and without metal inserts, ground truth data can easily be obtained by a second reference data acquisition. Obviously, this is not possible for clinical data. Here, an alternative evaluation method is presented without the need of an additionally acquired reference data set. The proposed metric is based on an inherent ground truth for metal artifacts as well as MAR methods comparison, where no reference information in terms of a second acquisition is needed. The method is based on the forward projection of a reconstructed image, which is compared to the actually measured projection data. The new evaluation technique is performed on phantom and on clinical CT data with and without MAR. The metric results are then compared with methods using a reference data set as well as an expert-based classification. It is shown that the new approach is an adequate quantification technique for artifact strength in reconstructed metal or MAR CT images. The presented method works solely on the original projection data itself, which yields some advantages compared to distance measures in image domain using two data sets. Beside this, no parameters have to be manually chosen. The new metric is a useful evaluation alternative when no reference data are available.

Sparse representations via learned dictionaries for x-ray angiogram image denoising

NASA Astrophysics Data System (ADS)

Shang, Jingfan; Huang, Zhenghua; Li, Qian; Zhang, Tianxu

2018-03-01

X-ray angiogram image denoising is always an active research topic in the field of computer vision. In particular, the denoising performance of many existing methods had been greatly improved by the widely use of nonlocal similar patches. However, the only nonlocal self-similar (NSS) patch-based methods can be still be improved and extended. In this paper, we propose an image denoising model based on the sparsity of the NSS patches to obtain high denoising performance and high-quality image. In order to represent the sparsely NSS patches in every location of the image well and solve the image denoising model more efficiently, we obtain dictionaries as a global image prior by the K-SVD algorithm over the processing image; Then the single and effectively alternating directions method of multipliers (ADMM) method is used to solve the image denoising model. The results of widely synthetic experiments demonstrate that, owing to learned dictionaries by K-SVD algorithm, a sparsely augmented lagrangian image denoising (SALID) model, which perform effectively, obtains a state-of-the-art denoising performance and better high-quality images. Moreover, we also give some denoising results of clinical X-ray angiogram images.

Noninvasive thermal ablation of hepatocellular carcinoma by using magnetic resonance imaging-guided focused ultrasound.

PubMed

Jolesz, Ferenc A; Hynynen, Kullervo; McDannold, Nathan; Freundlich, David; Kopelman, Doron

2004-11-01

A number of minimally invasive methods have been tested for the thermal ablation of liver tumors as an alternative to surgical resection. The use of focused ultrasound transducers to ablate deep tumors offers the first completely noninvasive alternative to these techniques. By increasing the flexibility of this technology with modern phased-array transducer design and by combining it with magnetic resonance imaging for targeting and online guidance, a powerful tool results with the potential to offer treatment to a larger population of patients, to reduce trauma to the patient, and to reduce the cost of treatment. In this article, we review previous work with focused ultrasound in the liver and recent experimental results with magnetic resonance imaging guidance.

Label-free identification of macrophage phenotype by fluorescence lifetime imaging microscopy

NASA Astrophysics Data System (ADS)

Alfonso-García, Alba; Smith, Tim D.; Datta, Rupsa; Luu, Thuy U.; Gratton, Enrico; Potma, Eric O.; Liu, Wendy F.

2016-04-01

Macrophages adopt a variety of phenotypes that are a reflection of the many functions they perform as part of the immune system. In particular, metabolism is a phenotypic trait that differs between classically activated, proinflammatory macrophages, and alternatively activated, prohealing macrophages. Inflammatory macrophages have a metabolism based on glycolysis while alternatively activated macrophages generally rely on oxidative phosphorylation to generate chemical energy. We employ this shift in metabolism as an endogenous marker to identify the phenotype of individual macrophages via live-cell fluorescence lifetime imaging microscopy (FLIM). We demonstrate that polarized macrophages can be readily discriminated with the aid of a phasor approach to FLIM, which provides a fast and model-free method for analyzing fluorescence lifetime images.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-05-25

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Methods for spectral image analysis by exploiting spatial simplicity

DOEpatents

Keenan, Michael R.

2010-11-23

Several full-spectrum imaging techniques have been introduced in recent years that promise to provide rapid and comprehensive chemical characterization of complex samples. One of the remaining obstacles to adopting these techniques for routine use is the difficulty of reducing the vast quantities of raw spectral data to meaningful chemical information. Multivariate factor analysis techniques, such as Principal Component Analysis and Alternating Least Squares-based Multivariate Curve Resolution, have proven effective for extracting the essential chemical information from high dimensional spectral image data sets into a limited number of components that describe the spectral characteristics and spatial distributions of the chemical species comprising the sample. There are many cases, however, in which those constraints are not effective and where alternative approaches may provide new analytical insights. For many cases of practical importance, imaged samples are "simple" in the sense that they consist of relatively discrete chemical phases. That is, at any given location, only one or a few of the chemical species comprising the entire sample have non-zero concentrations. The methods of spectral image analysis of the present invention exploit this simplicity in the spatial domain to make the resulting factor models more realistic. Therefore, more physically accurate and interpretable spectral and abundance components can be extracted from spectral images that have spatially simple structure.

Optical image encryption using multilevel Arnold transform and noninterferometric imaging

NASA Astrophysics Data System (ADS)

Chen, Wen; Chen, Xudong

2011-11-01

Information security has attracted much current attention due to the rapid development of modern technologies, such as computer and internet. We propose a novel method for optical image encryption using multilevel Arnold transform and rotatable-phase-mask noninterferometric imaging. An optical image encryption scheme is developed in the gyrator transform domain, and one phase-only mask (i.e., phase grating) is rotated and updated during image encryption. For the decryption, an iterative retrieval algorithm is proposed to extract high-quality plaintexts. Conventional encoding methods (such as digital holography) have been proven vulnerably to the attacks, and the proposed optical encoding scheme can effectively eliminate security deficiency and significantly enhance cryptosystem security. The proposed strategy based on the rotatable phase-only mask can provide a new alternative for data/image encryption in the noninterferometric imaging.

Setting local rank constraints by orthogonal projections for image resolution analysis: application to the determination of a low dose pharmaceutical compound.

PubMed

Boiret, Mathieu; de Juan, Anna; Gorretta, Nathalie; Ginot, Yves-Michel; Roger, Jean-Michel

2015-09-10

Raman chemical imaging provides chemical and spatial information about pharmaceutical drug product. By using resolution methods on acquired spectra, the objective is to calculate pure spectra and distribution maps of image compounds. With multivariate curve resolution-alternating least squares, constraints are used to improve the performance of the resolution and to decrease the ambiguity linked to the final solution. Non negativity and spatial local rank constraints have been identified as the most powerful constraints to be used. In this work, an alternative method to set local rank constraints is proposed. The method is based on orthogonal projections pretreatment. For each drug product compound, raw Raman spectra are orthogonally projected to a basis including all the variability from the formulation compounds other than the product of interest. Presence or absence of the compound of interest is obtained by observing the correlations between the orthogonal projected spectra and a pure spectrum orthogonally projected to the same basis. By selecting an appropriate threshold, maps of presence/absence of compounds can be set up for all the product compounds. This method appears as a powerful approach to identify a low dose compound within a pharmaceutical drug product. The maps of presence/absence of compounds can be used as local rank constraints in resolution methods, such as multivariate curve resolution-alternating least squares process in order to improve the resolution of the system. The method proposed is particularly suited for pharmaceutical systems, where the identity of all compounds in the formulations is known and, therefore, the space of interferences can be well defined. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of a semi-automated combined PET and CT lung lesion segmentation framework

NASA Astrophysics Data System (ADS)

Rossi, Farli; Mokri, Siti Salasiah; Rahni, Ashrani Aizzuddin Abd.

2017-03-01

Segmentation is one of the most important steps in automated medical diagnosis applications, which affects the accuracy of the overall system. In this paper, we propose a semi-automated segmentation method for extracting lung lesions from thoracic PET/CT images by combining low level processing and active contour techniques. The lesions are first segmented in PET images which are first converted to standardised uptake values (SUVs). The segmented PET images then serve as an initial contour for subsequent active contour segmentation of corresponding CT images. To evaluate its accuracy, the Jaccard Index (JI) was used as a measure of the accuracy of the segmented lesion compared to alternative segmentations from the QIN lung CT segmentation challenge, which is possible by registering the whole body PET/CT images to the corresponding thoracic CT images. The results show that our proposed technique has acceptable accuracy in lung lesion segmentation with JI values of around 0.8, especially when considering the variability of the alternative segmentations.

Crowdsourcing scoring of immunohistochemistry images: Evaluating Performance of the Crowd and an Automated Computational Method

NASA Astrophysics Data System (ADS)

Irshad, Humayun; Oh, Eun-Yeong; Schmolze, Daniel; Quintana, Liza M.; Collins, Laura; Tamimi, Rulla M.; Beck, Andrew H.

2017-02-01

The assessment of protein expression in immunohistochemistry (IHC) images provides important diagnostic, prognostic and predictive information for guiding cancer diagnosis and therapy. Manual scoring of IHC images represents a logistical challenge, as the process is labor intensive and time consuming. Since the last decade, computational methods have been developed to enable the application of quantitative methods for the analysis and interpretation of protein expression in IHC images. These methods have not yet replaced manual scoring for the assessment of IHC in the majority of diagnostic laboratories and in many large-scale research studies. An alternative approach is crowdsourcing the quantification of IHC images to an undefined crowd. The aim of this study is to quantify IHC images for labeling of ER status with two different crowdsourcing approaches, image-labeling and nuclei-labeling, and compare their performance with automated methods. Crowdsourcing- derived scores obtained greater concordance with the pathologist interpretations for both image-labeling and nuclei-labeling tasks (83% and 87%), as compared to the pathologist concordance achieved by the automated method (81%) on 5,338 TMA images from 1,853 breast cancer patients. This analysis shows that crowdsourcing the scoring of protein expression in IHC images is a promising new approach for large scale cancer molecular pathology studies.

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.

Improved classification and visualization of healthy and pathological hard dental tissues by modeling specular reflections in NIR hyperspectral images

NASA Astrophysics Data System (ADS)

Usenik, Peter; Bürmen, Miran; Fidler, Aleš; Pernuš, Franjo; Likar, Boštjan

2012-03-01

Despite major improvements in dental healthcare and technology, dental caries remains one of the most prevalent chronic diseases of modern society. The initial stages of dental caries are characterized by demineralization of enamel crystals, commonly known as white spots, which are difficult to diagnose. Near-infrared (NIR) hyperspectral imaging is a new promising technique for early detection of demineralization which can classify healthy and pathological dental tissues. However, due to non-ideal illumination of the tooth surface the hyperspectral images can exhibit specular reflections, in particular around the edges and the ridges of the teeth. These reflections significantly affect the performance of automated classification and visualization methods. Cross polarized imaging setup can effectively remove the specular reflections, however is due to the complexity and other imaging setup limitations not always possible. In this paper, we propose an alternative approach based on modeling the specular reflections of hard dental tissues, which significantly improves the classification accuracy in the presence of specular reflections. The method was evaluated on five extracted human teeth with corresponding gold standard for 6 different healthy and pathological hard dental tissues including enamel, dentin, calculus, dentin caries, enamel caries and demineralized regions. Principal component analysis (PCA) was used for multivariate local modeling of healthy and pathological dental tissues. The classification was performed by employing multiple discriminant analysis. Based on the obtained results we believe the proposed method can be considered as an effective alternative to the complex cross polarized imaging setups.

Region-based multifocus image fusion for the precise acquisition of Pap smear images.

PubMed

Tello-Mijares, Santiago; Bescós, Jesús

2018-05-01

A multifocus image fusion method to obtain a single focused image from a sequence of microscopic high-magnification Papanicolau source (Pap smear) images is presented. These images, captured each in a different position of the microscope lens, frequently show partially focused cells or parts of cells, which makes them unpractical for the direct application of image analysis techniques. The proposed method obtains a focused image with a high preservation of original pixels information while achieving a negligible visibility of the fusion artifacts. The method starts by identifying the best-focused image of the sequence; then, it performs a mean-shift segmentation over this image; the focus level of the segmented regions is evaluated in all the images of the sequence, and best-focused regions are merged in a single combined image; finally, this image is processed with an adaptive artifact removal process. The combination of a region-oriented approach, instead of block-based approaches, and a minimum modification of the value of focused pixels in the original images achieve a highly contrasted image with no visible artifacts, which makes this method especially convenient for the medical imaging domain. The proposed method is compared with several state-of-the-art alternatives over a representative dataset. The experimental results show that our proposal obtains the best and more stable quality indicators. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

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

PubMed

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

2017-10-17

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

Advanced Imaging Methods for Long-Baseline Optical Interferometry

NASA Astrophysics Data System (ADS)

Le Besnerais, G.; Lacour, S.; Mugnier, L. M.; Thiebaut, E.; Perrin, G.; Meimon, S.

2008-11-01

We address the data processing methods needed for imaging with a long baseline optical interferometer. We first describe parametric reconstruction approaches and adopt a general formulation of nonparametric image reconstruction as the solution of a constrained optimization problem. Within this framework, we present two recent reconstruction methods, Mira and Wisard, representative of the two generic approaches for dealing with the missing phase information. Mira is based on an implicit approach and a direct optimization of a Bayesian criterion while Wisard adopts a self-calibration approach and an alternate minimization scheme inspired from radio-astronomy. Both methods can handle various regularization criteria. We review commonly used regularization terms and introduce an original quadratic regularization called ldquosoft support constraintrdquo that favors the object compactness. It yields images of quality comparable to nonquadratic regularizations on the synthetic data we have processed. We then perform image reconstructions, both parametric and nonparametric, on astronomical data from the IOTA interferometer, and discuss the respective roles of parametric and nonparametric approaches for optical interferometric imaging.

Feature-based Alignment of Volumetric Multi-modal Images

PubMed Central

Toews, Matthew; Zöllei, Lilla; Wells, William M.

2014-01-01

This paper proposes a method for aligning image volumes acquired from different imaging modalities (e.g. MR, CT) based on 3D scale-invariant image features. A novel method for encoding invariant feature geometry and appearance is developed, based on the assumption of locally linear intensity relationships, providing a solution to poor repeatability of feature detection in different image modalities. The encoding method is incorporated into a probabilistic feature-based model for multi-modal image alignment. The model parameters are estimated via a group-wise alignment algorithm, that iteratively alternates between estimating a feature-based model from feature data, then realigning feature data to the model, converging to a stable alignment solution with few pre-processing or pre-alignment requirements. The resulting model can be used to align multi-modal image data with the benefits of invariant feature correspondence: globally optimal solutions, high efficiency and low memory usage. The method is tested on the difficult RIRE data set of CT, T1, T2, PD and MP-RAGE brain images of subjects exhibiting significant inter-subject variability due to pathology. PMID:24683955

Triceps stretch (image)

MedlinePlus

... shoulder. Hold for 10 to 20 seconds, then switch sides. Alternate method: raise your arm over your ... elbow. Hold for 10 to 20 seconds, then switch sides. You should feel either of these stretches ...

Low Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method.

PubMed

Yu, Xingjian; Wang, Chenye; Hu, Hongjie; Liu, Huafeng

2016-01-01

In this paper, a total variation (TV) minimization strategy is proposed to overcome the problem of sparse spatial resolution and large amounts of noise in low dose positron emission tomography (PET) imaging reconstruction. Two types of objective function were established based on two statistical models of measured PET data, least-square (LS) TV for the Gaussian distribution and Poisson-TV for the Poisson distribution. To efficiently obtain high quality reconstructed images, the alternating direction method (ADM) is used to solve these objective functions. As compared with the iterative shrinkage/thresholding (IST) based algorithms, the proposed ADM can make full use of the TV constraint and its convergence rate is faster. The performance of the proposed approach is validated through comparisons with the expectation-maximization (EM) method using synthetic and experimental biological data. In the comparisons, the results of both LS-TV and Poisson-TV are taken into consideration to find which models are more suitable for PET imaging, in particular low-dose PET. To evaluate the results quantitatively, we computed bias, variance, and the contrast recovery coefficient (CRC) and drew profiles of the reconstructed images produced by the different methods. The results show that both Poisson-TV and LS-TV can provide a high visual quality at a low dose level. The bias and variance of the proposed LS-TV and Poisson-TV methods are 20% to 74% less at all counting levels than those of the EM method. Poisson-TV gives the best performance in terms of high-accuracy reconstruction with the lowest bias and variance as compared to the ground truth (14.3% less bias and 21.9% less variance). In contrast, LS-TV gives the best performance in terms of the high contrast of the reconstruction with the highest CRC.

Low Dose PET Image Reconstruction with Total Variation Using Alternating Direction Method

PubMed Central

Yu, Xingjian; Wang, Chenye; Hu, Hongjie; Liu, Huafeng

2016-01-01

In this paper, a total variation (TV) minimization strategy is proposed to overcome the problem of sparse spatial resolution and large amounts of noise in low dose positron emission tomography (PET) imaging reconstruction. Two types of objective function were established based on two statistical models of measured PET data, least-square (LS) TV for the Gaussian distribution and Poisson-TV for the Poisson distribution. To efficiently obtain high quality reconstructed images, the alternating direction method (ADM) is used to solve these objective functions. As compared with the iterative shrinkage/thresholding (IST) based algorithms, the proposed ADM can make full use of the TV constraint and its convergence rate is faster. The performance of the proposed approach is validated through comparisons with the expectation-maximization (EM) method using synthetic and experimental biological data. In the comparisons, the results of both LS-TV and Poisson-TV are taken into consideration to find which models are more suitable for PET imaging, in particular low-dose PET. To evaluate the results quantitatively, we computed bias, variance, and the contrast recovery coefficient (CRC) and drew profiles of the reconstructed images produced by the different methods. The results show that both Poisson-TV and LS-TV can provide a high visual quality at a low dose level. The bias and variance of the proposed LS-TV and Poisson-TV methods are 20% to 74% less at all counting levels than those of the EM method. Poisson-TV gives the best performance in terms of high-accuracy reconstruction with the lowest bias and variance as compared to the ground truth (14.3% less bias and 21.9% less variance). In contrast, LS-TV gives the best performance in terms of the high contrast of the reconstruction with the highest CRC. PMID:28005929

A cost-efficient frequency-domain photoacoustic imaging system

PubMed Central

LeBoulluec, Peter; Liu, Hanli; Yuan, Baohong

2013-01-01

Photoacoustic (PA) imaging techniques have recently attracted much attention and can be used for noninvasive imaging of biological tissues. Most PA imaging systems in research laboratories use the time domain method with expensive nanosecond pulsed lasers that are not affordable for most educational laboratories. Using an intensity modulated light source to excite PA signals is an alternative technique, known as the frequency domain method, with a much lower cost. In this paper, we describe a simple frequency domain PA system and demonstrate its imaging capability. The system provides opportunities not only to observe PA signals in tissue phantoms, but also to acquire hands-on skills in PA signal detection. It also provides opportunities to explore the underlying mechanisms of the PA effect. PMID:24659823

Content-Based Medical Image Retrieval

NASA Astrophysics Data System (ADS)

Müller, Henning; Deserno, Thomas M.

This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.

Correction of aeroheating-induced intensity nonuniformity in infrared images

NASA Astrophysics Data System (ADS)

Liu, Li; Yan, Luxin; Zhao, Hui; Dai, Xiaobing; Zhang, Tianxu

2016-05-01

Aeroheating-induced intensity nonuniformity effects severely influence the effective performance of an infrared (IR) imaging system in high-speed flight. In this paper, we propose a new approach to the correction of intensity nonuniformity in IR images. The basic assumption is that the low-frequency intensity bias is additive and smoothly varying so that it can be modeled as a bivariate polynomial and estimated by using an isotropic total variation (TV) model. A half quadratic penalty method is applied to the isotropic form of TV discretization. And an alternating minimization algorithm is adopted for solving the optimization model. The experimental results of simulated and real aerothermal images show that the proposed correction method can effectively improve IR image quality.

A cost-efficient frequency-domain photoacoustic imaging system.

PubMed

Leboulluec, Peter; Liu, Hanli; Yuan, Baohong

2013-09-01

Photoacoustic (PA) imaging techniques have recently attracted much attention and can be used for noninvasive imaging of biological tissues. Most PA imaging systems in research laboratories use the time domain method with expensive nanosecond pulsed lasers that are not affordable for most educational laboratories. Using an intensity modulated light source to excite PA signals is an alternative technique, known as the frequency domain method, with a much lower cost. In this paper, we describe a simple frequency domain PA system and demonstrate its imaging capability. The system provides opportunities not only to observe PA signals in tissue phantoms, but also to acquire hands-on skills in PA signal detection. It also provides opportunities to explore the underlying mechanisms of the PA effect.

Joint sparse reconstruction of multi-contrast MRI images with graph based redundant wavelet transform.

PubMed

Lai, Zongying; Zhang, Xinlin; Guo, Di; Du, Xiaofeng; Yang, Yonggui; Guo, Gang; Chen, Zhong; Qu, Xiaobo

2018-05-03

Multi-contrast images in magnetic resonance imaging (MRI) provide abundant contrast information reflecting the characteristics of the internal tissues of human bodies, and thus have been widely utilized in clinical diagnosis. However, long acquisition time limits the application of multi-contrast MRI. One efficient way to accelerate data acquisition is to under-sample the k-space data and then reconstruct images with sparsity constraint. However, images are compromised at high acceleration factor if images are reconstructed individually. We aim to improve the images with a jointly sparse reconstruction and Graph-based redundant wavelet transform (GBRWT). First, a sparsifying transform, GBRWT, is trained to reflect the similarity of tissue structures in multi-contrast images. Second, joint multi-contrast image reconstruction is formulated as a ℓ 2, 1 norm optimization problem under GBRWT representations. Third, the optimization problem is numerically solved using a derived alternating direction method. Experimental results in synthetic and in vivo MRI data demonstrate that the proposed joint reconstruction method can achieve lower reconstruction errors and better preserve image structures than the compared joint reconstruction methods. Besides, the proposed method outperforms single image reconstruction with joint sparsity constraint of multi-contrast images. The proposed method explores the joint sparsity of multi-contrast MRI images under graph-based redundant wavelet transform and realizes joint sparse reconstruction of multi-contrast images. Experiment demonstrate that the proposed method outperforms the compared joint reconstruction methods as well as individual reconstructions. With this high quality image reconstruction method, it is possible to achieve the high acceleration factors by exploring the complementary information provided by multi-contrast MRI.

Automated Quality Assessment of Colour Fundus Images for Diabetic Retinopathy Screening in Telemedicine.

PubMed

Saha, Sajib Kumar; Fernando, Basura; Cuadros, Jorge; Xiao, Di; Kanagasingam, Yogesan

2018-04-27

Fundus images obtained in a telemedicine program are acquired at different sites that are captured by people who have varying levels of experience. These result in a relatively high percentage of images which are later marked as unreadable by graders. Unreadable images require a recapture which is time and cost intensive. An automated method that determines the image quality during acquisition is an effective alternative. To determine the image quality during acquisition, we describe here an automated method for the assessment of image quality in the context of diabetic retinopathy. The method explicitly applies machine learning techniques to access the image and to determine 'accept' and 'reject' categories. 'Reject' category image requires a recapture. A deep convolution neural network is trained to grade the images automatically. A large representative set of 7000 colour fundus images was used for the experiment which was obtained from the EyePACS that were made available by the California Healthcare Foundation. Three retinal image analysis experts were employed to categorise these images into 'accept' and 'reject' classes based on the precise definition of image quality in the context of DR. The network was trained using 3428 images. The method shows an accuracy of 100% to successfully categorise 'accept' and 'reject' images, which is about 2% higher than the traditional machine learning method. On a clinical trial, the proposed method shows 97% agreement with human grader. The method can be easily incorporated with the fundus image capturing system in the acquisition centre and can guide the photographer whether a recapture is necessary or not.

Color Histogram Diffusion for Image Enhancement

NASA Technical Reports Server (NTRS)

Kim, Taemin

2011-01-01

Various color histogram equalization (CHE) methods have been proposed to extend grayscale histogram equalization (GHE) for color images. In this paper a new method called histogram diffusion that extends the GHE method to arbitrary dimensions is proposed. Ranges in a histogram are specified as overlapping bars of uniform heights and variable widths which are proportional to their frequencies. This diagram is called the vistogram. As an alternative approach to GHE, the squared error of the vistogram from the uniform distribution is minimized. Each bar in the vistogram is approximated by a Gaussian function. Gaussian particles in the vistoram diffuse as a nonlinear autonomous system of ordinary differential equations. CHE results of color images showed that the approach is effective.

Evaluation of Alzheimer's disease by analysis of MR images using Objective Dialectical Classifiers as an alternative to ADC maps.

PubMed

Dos Santos, Wellington P; de Assis, Francisco M; de Souza, Ricardo E; Dos Santos Filho, Plinio B

2008-01-01

Alzheimer's disease is the most common cause of dementia, yet hard to diagnose precisely without invasive techniques, particularly at the onset of the disease. This work approaches image analysis and classification of synthetic multispectral images composed by diffusion-weighted (DW) magnetic resonance (MR) cerebral images for the evaluation of cerebrospinal fluid area and measuring the advance of Alzheimer's disease. A clinical 1.5 T MR imaging system was used to acquire all images presented. The classification methods are based on Objective Dialectical Classifiers, a new method based on Dialectics as defined in the Philosophy of Praxis. A 2-degree polynomial network with supervised training is used to generate the ground truth image. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map.

SIMULTANEOUS MULTISLICE MAGNETIC RESONANCE FINGERPRINTING WITH LOW-RANK AND SUBSPACE MODELING

PubMed Central

Zhao, Bo; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A.; Wald, Lawrence L.; Setsompop, Kawin

2018-01-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T1, T2, and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3x speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice. PMID:29060594

Simultaneous multislice magnetic resonance fingerprinting with low-rank and subspace modeling.

PubMed

Bo Zhao; Bilgic, Berkin; Adalsteinsson, Elfar; Griswold, Mark A; Wald, Lawrence L; Setsompop, Kawin

2017-07-01

Magnetic resonance fingerprinting (MRF) is a new quantitative imaging paradigm that enables simultaneous acquisition of multiple magnetic resonance tissue parameters (e.g., T 1 , T 2 , and spin density). Recently, MRF has been integrated with simultaneous multislice (SMS) acquisitions to enable volumetric imaging with faster scan time. In this paper, we present a new image reconstruction method based on low-rank and subspace modeling for improved SMS-MRF. Here the low-rank model exploits strong spatiotemporal correlation among contrast-weighted images, while the subspace model captures the temporal evolution of magnetization dynamics. With the proposed model, the image reconstruction problem is formulated as a convex optimization problem, for which we develop an algorithm based on variable splitting and the alternating direction method of multipliers. The performance of the proposed method has been evaluated by numerical experiments, and the results demonstrate that the proposed method leads to improved accuracy over the conventional approach. Practically, the proposed method has a potential to allow for a 3× speedup with minimal reconstruction error, resulting in less than 5 sec imaging time per slice.

[The application of X-ray imaging in forensic medicine].

PubMed

Kučerová, Stěpánka; Safr, Miroslav; Ublová, Michaela; Urbanová, Petra; Hejna, Petr

2014-07-01

X-ray is the most common, basic and essential imaging method used in forensic medicine. It serves to display and localize the foreign objects in the body and helps to detect various traumatic and pathological changes. X-ray imaging is valuable in anthropological assessment of an individual. X-ray allows non-invasive evaluation of important findings before the autopsy and thus selection of the optimal strategy for dissection. Basic indications for postmortem X-ray imaging in forensic medicine include gunshot and explosive fatalities (identification and localization of projectiles or other components of ammunition, visualization of secondary missiles), sharp force injuries (air embolism, identification of the weapon) and motor vehicle related deaths. The method is also helpful for complex injury evaluation in abused victims or in persons where abuse is suspected. Finally, X-ray imaging still remains the gold standard method for identification of unknown deceased. With time modern imaging methods, especially computed tomography and magnetic resonance imaging, are more and more applied in forensic medicine. Their application extends possibilities of the visualization the bony structures toward a more detailed imaging of soft tissues and internal organs. The application of modern imaging methods in postmortem body investigation is known as digital or virtual autopsy. At present digital postmortem imaging is considered as a bloodless alternative to the conventional autopsy.

Conductivity map from scanning tunneling potentiometry.

PubMed

Zhang, Hao; Li, Xianqi; Chen, Yunmei; Durand, Corentin; Li, An-Ping; Zhang, X-G

2016-08-01

We present a novel method for extracting two-dimensional (2D) conductivity profiles from large electrochemical potential datasets acquired by scanning tunneling potentiometry of a 2D conductor. The method consists of a data preprocessing procedure to reduce/eliminate noise and a numerical conductivity reconstruction. The preprocessing procedure employs an inverse consistent image registration method to align the forward and backward scans of the same line for each image line followed by a total variation (TV) based image restoration method to obtain a (nearly) noise-free potential from the aligned scans. The preprocessed potential is then used for numerical conductivity reconstruction, based on a TV model solved by accelerated alternating direction method of multiplier. The method is demonstrated on a measurement of the grain boundary of a monolayer graphene, yielding a nearly 10:1 ratio for the grain boundary resistivity over bulk resistivity.

Participatory Visual Methods: Revisioning the Future of Adult Education

ERIC Educational Resources Information Center

Lawrence, Randee Lipson

2017-01-01

This chapter brings together significant themes in the previous chapters, including collaborative research partnerships, voice and agency, self-image, relationships, multiple ways of knowing, difficult conversations, social change, and alternative adult education.

Spectral characterization and calibration of AOTF spectrometers and hyper-spectral imaging system

NASA Astrophysics Data System (ADS)

Katrašnik, Jaka; Pernuš, Franjo; Likar, Boštjan

2010-02-01

The goal of this article is to present a novel method for spectral characterization and calibration of spectrometers and hyper-spectral imaging systems based on non-collinear acousto-optical tunable filters. The method characterizes the spectral tuning curve (frequency-wavelength characteristic) of the AOTF (Acousto-Optic Tunable Filter) filter by matching the acquired and modeled spectra of the HgAr calibration lamp, which emits line spectrum that can be well modeled via AOTF transfer function. In this way, not only tuning curve characterization and corresponding spectral calibration but also spectral resolution assessment is performed. The obtained results indicated that the proposed method is efficient, accurate and feasible for routine calibration of AOTF spectrometers and hyper-spectral imaging systems and thereby a highly competitive alternative to the existing calibration methods.

Fisher's method of scoring in statistical image reconstruction: comparison of Jacobi and Gauss-Seidel iterative schemes.

PubMed

Hudson, H M; Ma, J; Green, P

1994-01-01

Many algorithms for medical image reconstruction adopt versions of the expectation-maximization (EM) algorithm. In this approach, parameter estimates are obtained which maximize a complete data likelihood or penalized likelihood, in each iteration. Implicitly (and sometimes explicitly) penalized algorithms require smoothing of the current reconstruction in the image domain as part of their iteration scheme. In this paper, we discuss alternatives to EM which adapt Fisher's method of scoring (FS) and other methods for direct maximization of the incomplete data likelihood. Jacobi and Gauss-Seidel methods for non-linear optimization provide efficient algorithms applying FS in tomography. One approach uses smoothed projection data in its iterations. We investigate the convergence of Jacobi and Gauss-Seidel algorithms with clinical tomographic projection data.

Position Accuracy Analysis of a Robust Vision-Based Navigation

NASA Astrophysics Data System (ADS)

Gaglione, S.; Del Pizzo, S.; Troisi, S.; Angrisano, A.

2018-05-01

Using images to determine camera position and attitude is a consolidated method, very widespread for application like UAV navigation. In harsh environment, where GNSS could be degraded or denied, image-based positioning could represent a possible candidate for an integrated or alternative system. In this paper, such method is investigated using a system based on single camera and 3D maps. A robust estimation method is proposed in order to limit the effect of blunders or noisy measurements on position solution. The proposed approach is tested using images collected in an urban canyon, where GNSS positioning is very unaccurate. A previous photogrammetry survey has been performed to build the 3D model of tested area. The position accuracy analysis is performed and the effect of the robust method proposed is validated.

Examination of Painting on Metal Support by Terahertz Time-Domain Imaging

NASA Astrophysics Data System (ADS)

Koch Dandolo, C. L.; Gomez-Sepulveda, A. M.; Hernandez-Serrano, A. I.; Castro-Camus, E.

2017-10-01

Two paintings on metal support have been imaged by terahertz time-domain imaging (THz-TDI) in a reflection setup and the X-ray radiographs were also recorded. The study was performed for testing the terahertz radiation (THz) as an imaging method alternative to X-ray radiography, which suffers several limitations in imaging paint layers on metal support. While the information regarding the paint layers of the paintings was almost lost in the records provided by the X-ray radiography, THz-TDI demonstrates the ability to provide important information about them, despite the presence of the underlying metal.

Multi data mode method as an alternative way for SPM studies of high relief surfaces

NASA Astrophysics Data System (ADS)

Abdullayeva, S. H.; Molchanov, S. P.; Mamedov, N. T.; Alekperov, S. D.

2006-09-01

In this paper we report the results of our studies of the high relief surfaces of Al oxide-based ceramic catalyst by SPM contact mode, and by so-called Multi Data Mode (MDM) method for comparison. We failed to obtain any reasonable image of the highly-developed surfaces of above material by the first method but were successful in doing so when applied the second one. The topographic and complimentary images obtained by MDM probing with high resolution are discussed to show a full range of the applications possible using MDM.

Could digital imaging be an alternative for digital colorimeters?

PubMed

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

2010-12-01

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

Virtual view image synthesis for eye-contact in TV conversation system

NASA Astrophysics Data System (ADS)

Murayama, Daisuke; Kimura, Keiichi; Hosaka, Tadaaki; Hamamoto, Takayuki; Shibuhisa, Nao; Tanaka, Seiichi; Sato, Shunichi; Saito, Sakae

2010-02-01

Eye-contact plays an important role for human communications in the sense that it can convey unspoken information. However, it is highly difficult to realize eye-contact in teleconferencing systems because of camera configurations. Conventional methods to overcome this difficulty mainly resorted to space-consuming optical devices such as half mirrors. In this paper, we propose an alternative approach to achieve eye-contact by techniques of arbitrary view image synthesis. In our method, multiple images captured by real cameras are converted to the virtual viewpoint (the center of the display) by homography, and evaluation of matching errors among these projected images provides the depth map and the virtual image. Furthermore, we also propose a simpler version of this method by using a single camera to save the computational costs, in which the only one real image is transformed to the virtual viewpoint based on the hypothesis that the subject is located at a predetermined distance. In this simple implementation, eye regions are separately generated by comparison with pre-captured frontal face images. Experimental results of both the methods show that the synthesized virtual images enable the eye-contact favorably.

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

PubMed

Kwak, In Hae; Son, Minjun; Hagen, Stephen J

2012-05-11

Studies of stochasticity in gene expression typically make use of fluorescent protein reporters, which permit the measurement of expression levels within individual cells by fluorescence microscopy. Analysis of such microscopy images is almost invariably based on a segmentation algorithm, where the image of a cell or cluster is analyzed mathematically to delineate individual cell boundaries. However segmentation can be ineffective for studying bacterial cells or clusters, especially at lower magnification, where outlines of individual cells are poorly resolved. Here we demonstrate an alternative method for analyzing such images without segmentation. The method employs a comparison between the pixel brightness in phase contrast vs fluorescence microscopy images. By fitting the correlation between phase contrast and fluorescence intensity to a physical model, we obtain well-defined estimates for the different levels of gene expression that are present in the cell or cluster. The method reveals the boundaries of the individual cells, even if the source images lack the resolution to show these boundaries clearly. Copyright © 2012 Elsevier Inc. All rights reserved.

Random forest regression for magnetic resonance image synthesis.

PubMed

Jog, Amod; Carass, Aaron; Roy, Snehashis; Pham, Dzung L; Prince, Jerry L

2017-01-01

By choosing different pulse sequences and their parameters, magnetic resonance imaging (MRI) can generate a large variety of tissue contrasts. This very flexibility, however, can yield inconsistencies with MRI acquisitions across datasets or scanning sessions that can in turn cause inconsistent automated image analysis. Although image synthesis of MR images has been shown to be helpful in addressing this problem, an inability to synthesize both T 2 -weighted brain images that include the skull and FLuid Attenuated Inversion Recovery (FLAIR) images has been reported. The method described herein, called REPLICA, addresses these limitations. REPLICA is a supervised random forest image synthesis approach that learns a nonlinear regression to predict intensities of alternate tissue contrasts given specific input tissue contrasts. Experimental results include direct image comparisons between synthetic and real images, results from image analysis tasks on both synthetic and real images, and comparison against other state-of-the-art image synthesis methods. REPLICA is computationally fast, and is shown to be comparable to other methods on tasks they are able to perform. Additionally REPLICA has the capability to synthesize both T 2 -weighted images of the full head and FLAIR images, and perform intensity standardization between different imaging datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

Total Variation with Overlapping Group Sparsity for Image Deblurring under Impulse Noise

PubMed Central

Liu, Gang; Huang, Ting-Zhu; Liu, Jun; Lv, Xiao-Guang

2015-01-01

The total variation (TV) regularization method is an effective method for image deblurring in preserving edges. However, the TV based solutions usually have some staircase effects. In order to alleviate the staircase effects, we propose a new model for restoring blurred images under impulse noise. The model consists of an ℓ1-fidelity term and a TV with overlapping group sparsity (OGS) regularization term. Moreover, we impose a box constraint to the proposed model for getting more accurate solutions. The solving algorithm for our model is under the framework of the alternating direction method of multipliers (ADMM). We use an inner loop which is nested inside the majorization minimization (MM) iteration for the subproblem of the proposed method. Compared with other TV-based methods, numerical results illustrate that the proposed method can significantly improve the restoration quality, both in terms of peak signal-to-noise ratio (PSNR) and relative error (ReE). PMID:25874860

Automatic correction of echo-planar imaging (EPI) ghosting artifacts in real-time interactive cardiac MRI using sensitivity encoding.

PubMed

Kim, Yoon-Chul; Nielsen, Jon-Fredrik; Nayak, Krishna S

2008-01-01

To develop a method that automatically corrects ghosting artifacts due to echo-misalignment in interleaved gradient-echo echo-planar imaging (EPI) in arbitrary oblique or double-oblique scan planes. An automatic ghosting correction technique was developed based on an alternating EPI acquisition and the phased-array ghost elimination (PAGE) reconstruction method. The direction of k-space traversal is alternated at every temporal frame, enabling lower temporal-resolution ghost-free coil sensitivity maps to be dynamically estimated. The proposed method was compared with conventional one-dimensional (1D) phase correction in axial, oblique, and double-oblique scan planes in phantom and cardiac in vivo studies. The proposed method was also used in conjunction with two-fold acceleration. The proposed method with nonaccelerated acquisition provided excellent suppression of ghosting artifacts in all scan planes, and was substantially more effective than conventional 1D phase correction in oblique and double-oblique scan planes. The feasibility of real-time reconstruction using the proposed technique was demonstrated in a scan protocol with 3.1-mm spatial and 60-msec temporal resolution. The proposed technique with nonaccelerated acquisition provides excellent ghost suppression in arbitrary scan orientations without a calibration scan, and can be useful for real-time interactive imaging, in which scan planes are frequently changed with arbitrary oblique orientations.

Utility of spatially-resolved atmospheric pressure surface sampling and ionization techniques as alternatives to mass spectrometric imaging (MSI) in drug metabolism.

PubMed

Blatherwick, Eleanor Q; Van Berkel, Gary J; Pickup, Kathryn; Johansson, Maria K; Beaudoin, Marie-Eve; Cole, Roderic O; Day, Jennifer M; Iverson, Suzanne; Wilson, Ian D; Scrivens, James H; Weston, Daniel J

2011-08-01

Tissue distribution studies of drug molecules play an essential role in the pharmaceutical industry and are commonly undertaken using quantitative whole body autoradiography (QWBA) methods. The growing need for complementary methods to address some scientific gaps around radiography methods has led to increased use of mass spectrometric imaging (MSI) technology over the last 5 to 10 years. More recently, the development of novel mass spectrometric techniques for ambient surface sampling has redefined what can be regarded as "fit-for-purpose" for MSI in a drug metabolism and disposition arena. Together with a review of these novel alternatives, this paper details the use of two liquid microjunction (LMJ)-based mass spectrometric surface sampling technologies. These approaches are used to provide qualitative determination of parent drug in rat liver tissue slices using liquid extraction surface analysis (LESA) and to assess the performance of a LMJ surface sampling probe (LMJ-SSP) interface for quantitative assessment of parent drug in brain, liver and muscle tissue slices. An assessment of the utility of these spatially-resolved sampling methods is given, showing interdependence between mass spectrometric and QWBA methods, in particular there emerges a reason to question typical MSI workflows for drug metabolism; suggesting the expedient use of profile or region analysis may be more appropriate, rather than generating time-intensive molecular images of the entire tissue section.

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.

Temperature imaging with ultrasonic transmission tomography for treatment control

NASA Astrophysics Data System (ADS)

Chu, Zheqi; Pinter, Stephen. Z.; Yuan, Jie; Scarpelli, Matthew L.; Kripfgans, Oliver D.; Fowlkes, J. Brian; Duric, Neb; Carson, Paul L.

2017-03-01

Hyperthermia is a promising method to enhance chemo- or radiation therapy of breast cancer and the time-temperature profile in the target and surrounding areas is the primary monitoring method. Unlike with thermal ablation of lesions, in hyperthermia there are not good alternative treatment monitoring quantities. However, there is less problem with non-monotonic thermal coefficients of speed of sound used with ultrasonic imaging of temperature. This paper tests a long discussed but little investigated method of imaging temperature using speed of sound and proposes methods of reducing edge enhancement artifacts in the temperature image. Normally, when directly using the speed of sound to reconstruct the temperature image around the tumor, there will be an abnormal bipolar edge enhancement along the boundary between two materials with different speeds of sound at a given temperature. This due to partial volume effects and can be diminished by regularized, weighted deconvolution. An initial, manual deconvolution is shown, as well as an EMD (Empirical Mode Decomposition) method. Here we use the continuity and other constraints to choose the coefficient, reprocess the temperature field image and take the mean variations of the temperature in the adjacent pixels as the judgment criteria. Both methods effectively reduce the edge enhancement and produce a more precise image of temperature.

Magneto acoustic tomography with short pulsed magnetic field for in-vivo imaging of magnetic iron oxide nanoparticles.

PubMed

Mariappan, Leo; Shao, Qi; Jiang, Chunlan; Yu, Kai; Ashkenazi, Shai; Bischof, John C; He, Bin

2016-04-01

Nanoparticles are widely used as contrast and therapeutic agents. As such, imaging modalities that can accurately estimate their distribution in-vivo are actively sought. We present here our method Magneto Acoustic Tomography (MAT), which uses magnetomotive force due to a short pulsed magnetic field to induce ultrasound in the magnetic nanoparticle labeled tissue and estimates an image of the distribution of the nanoparticles in-vivo with ultrasound imaging resolution. In this study, we image the distribution of superparamagnetic iron oxide nanoparticles (IONP) using MAT method. In-vivo imaging was performed on live, nude mice with IONP injected into LNCaP tumors grown subcutaneously within the hind limb of the mice. Our experimental results indicate that the MAT method is capable of imaging the distribution of IONPs in-vivo. Therefore, MAT could become an imaging modality for high resolution reconstruction of MNP distribution in the body. Many magnetic nanoparticles (MNPs) have been used as contrast agents in magnetic resonance imaging. In this study, the authors investigated the use of ultrasound to detect the presence of MNPs by magneto acoustic tomography. In-vivo experiments confirmed the imaging quality of this new approach, which hopefully would provide an alternative method for accurate tumor detection. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparative evaluation of RetCam vs. gonioscopy images in congenital glaucoma

PubMed Central

Azad, Raj V; Chandra, Parijat; Chandra, Anuradha; Gupta, Aparna; Gupta, Viney; Sihota, Ramanjit

2014-01-01

Purpose: To compare clarity, exposure and quality of anterior chamber angle visualization in congenital glaucoma patients, using RetCam and indirect gonioscopy images. Design: Cross-sectional study Participants. Congenital glaucoma patients over age of 5 years. Materials and Methods: A prospective consecutive pilot study was done in congenital glaucoma patients who were older than 5 years. Methods used are indirect gonioscopy and RetCam imaging. Clarity of the image, extent of angle visible and details of angle structures seen were graded for both methods, on digitally recorded images, in each eye, by two masked observers. Outcome Measures: Image clarity, interobserver agreement. Results: 40 eyes of 25 congenital glaucoma patients were studied. RetCam image had excellent clarity in 77.5% of patients versus 47.5% by gonioscopy. The extent of angle seen was similar by both methods. Agreement between RetCam and gonioscopy images regarding details of angle structures was 72.50% by observer 1 and 65.00% by observer 2. Conclusions: There was good agreement between RetCam and indirect gonioscopy images in detecting angle structures of congenital glaucoma patients. However, RetCam provided greater clarity, with better quality, and higher magnification images. RetCam can be a useful alternative to gonioscopy in infants and small children without the need for general anesthesia. PMID:24008788

Whole-heart magnetic resonance coronary angiography with multiple breath-holds and automatic breathing-level tracking

NASA Astrophysics Data System (ADS)

Kuhara, Shigehide; Ninomiya, Ayako; Okada, Tomohisa; Kanao, Shotaro; Kamae, Toshikazu; Togashi, Kaori

2010-05-01

Whole-heart (WH) magnetic resonance coronary angiography (MRCA) studies are usually performed during free breathing while monitoring the position of the diaphragm with real-time motion correction. However, this results in a long scan time and the patient's breathing pattern may change, causing the study to be aborted. Alternatively, WH MRCA can be performed with multiple breath-holds (mBH). However, one problem in the mBH method is that patients cannot hold their breath at the same position every time, leading to image degradation. We have developed a new WH MRCA imaging method that employs both the mBH method and automatic breathing-level tracking to permit automatic tracking of the changes in breathing or breath-hold levels. Evaluation of its effects on WH MRCA image quality showed that this method can provide high-quality images within a shorter scan time. This proposed method is expected to be very useful in clinical WH MRCA studies.

Sparsity-promoting orthogonal dictionary updating for image reconstruction from highly undersampled magnetic resonance data.

PubMed

Huang, Jinhong; Guo, Li; Feng, Qianjin; Chen, Wufan; Feng, Yanqiu

2015-07-21

Image reconstruction from undersampled k-space data accelerates magnetic resonance imaging (MRI) by exploiting image sparseness in certain transform domains. Employing image patch representation over a learned dictionary has the advantage of being adaptive to local image structures and thus can better sparsify images than using fixed transforms (e.g. wavelets and total variations). Dictionary learning methods have recently been introduced to MRI reconstruction, and these methods demonstrate significantly reduced reconstruction errors compared to sparse MRI reconstruction using fixed transforms. However, the synthesis sparse coding problem in dictionary learning is NP-hard and computationally expensive. In this paper, we present a novel sparsity-promoting orthogonal dictionary updating method for efficient image reconstruction from highly undersampled MRI data. The orthogonality imposed on the learned dictionary enables the minimization problem in the reconstruction to be solved by an efficient optimization algorithm which alternately updates representation coefficients, orthogonal dictionary, and missing k-space data. Moreover, both sparsity level and sparse representation contribution using updated dictionaries gradually increase during iterations to recover more details, assuming the progressively improved quality of the dictionary. Simulation and real data experimental results both demonstrate that the proposed method is approximately 10 to 100 times faster than the K-SVD-based dictionary learning MRI method and simultaneously improves reconstruction accuracy.

Tensor-based Dictionary Learning for Spectral CT Reconstruction

PubMed Central

Zhang, Yanbo; Wang, Ge

2016-01-01

Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628

Three-point Dixon method enables whole-body water and fat imaging of obese subjects.

PubMed

Berglund, Johan; Johansson, Lars; Ahlström, Håkan; Kullberg, Joel

2010-06-01

Dixon imaging techniques derive chemical shift-separated water and fat images, enabling the quantification of fat content and forming an alternative to fat suppression. Whole-body Dixon imaging is of interest in studies of obesity and the metabolic syndrome, and possibly in oncology. A three-point Dixon method is proposed where two solutions are found analytically in each voxel. The true solution is identified by a multiseed three-dimensional region-growing scheme with a dynamic path, allowing confident regions to be solved before unconfident regions, such as background noise. 2 pi-Phase unwrapping is not required. Whole-body datasets (256 x 184 x 252 voxels) were collected from 39 subjects (body mass index 19.8-45.4 kg/m(2)), in a mean scan time of 5 min 15 sec. Water and fat images were reconstructed offline, using the proposed method and two reference methods. The resulting images were subjectively graded on a four-grade scale by two radiologists, blinded to the method used. The proposed method was found superior to the reference methods. It exclusively received the two highest grades, implying that only mild reconstruction failures were found. The computation time for a whole-body dataset was 1 min 51.5 sec +/- 3.0 sec. It was concluded that whole-body water and fat imaging is feasible even for obese subjects, using the proposed method. (c) 2010 Wiley-Liss, Inc.

Magnetic domain observation of FeCo thin films fabricated by alternate monoatomic layer deposition

NASA Astrophysics Data System (ADS)

Ohtsuki, T.; Kojima, T.; Kotsugi, M.; Ohkochi, T.; Mizuguchi, M.; Takanashi, K.

2014-01-01

FeCo thin films are fabricated by alternate monoatomic layer deposition method on a Cu3Au buffer layer, which in-plane lattice constant is very close to the predicted value to obtain a large magnetic anisotropy constant. The variation of the in-plane lattice constant during the deposition process is investigated by reflection high-energy electron diffraction. The magnetic domain images are also observed by a photoelectron emission microscope in order to microscopically understand the magnetic structure. As a result, element-specific magnetic domain images show that Fe and Co magnetic moments align parallel. A series of images obtained with various azimuth reveal that the FeCo thin films show fourfold in-plane magnetic anisotropy along ⟨110⟩ direction, and that the magnetic domain structure is composed only of 90∘ wall.

Alternating phase-shifting masks: phase determination and impact of quartz defects--theoretical and experimental results

NASA Astrophysics Data System (ADS)

Griesinger, Uwe A.; Dettmann, Wolfgang; Hennig, Mario; Heumann, Jan P.; Koehle, Roderick; Ludwig, Ralf; Verbeek, Martin; Zarrabian, Mardjan

2002-07-01

In optical lithography balancing the aerial image of an alternating phase shifting mask (alt. PSM) is a major challenge. For the exposure wavelengths (currently 248nm and 193nm) an optimum etching method is necessary to overcome imbalance effects. Defects play an important role in the imbalances of the aerial image. In this contribution defects will be discussed by using the methodology of global phase imbalance control also for local imbalances which are a result of quartz defects. The effective phase error can be determined with an AIMS-system by measuring the CD width between the images of deep- and shallow trenches at different focus settings. The AIMS results are analyzed in comparison to the simulated and lithographic print results of the alternating structures. For the analysis of local aerial image imbalances it is necessary to investigate the capability of detecting these phase defects with state of the art inspection systems. Alternating PSMs containing programmed defects were inspected with different algorithms to investigate the capture rate of special phase defects in dependence on the defect size. Besides inspection also repair of phase defects is an important task. In this contribution we show the effect of repair on the optical behavior of phase defects. Due to the limited accuracy of the repair tools the repaired area still shows a certain local phase error. This error can be caused either by residual quartz material or a substrate damage. The influence of such repair induced phase errors on the aerial image were investigated.

Magnetic domain structure imaging near sample surface with alternating magnetic force microscopy by using AC magnetic field modulated superparamagnetic tip.

PubMed

Cao, Yongze; Nakayama, Shota; Kumar, Pawan; Zhao, Yue; Kinoshita, Yukinori; Yoshimura, Satoru; Saito, Hitoshi

2018-05-03

For magnetic domain imaging with a very high spatial resolution by magnetic force microscopy the tip-sample distance should be as small as possible. However, magnetic imaging near sample surface is very difficult with conventional MFM because the interactive forces between tip and sample includes van der Waals and electrostatic forces along with magnetic force. In this study, we proposed an alternating magnetic force microscopy (A-MFM) which extract only magnetic force near sample surface without any topographic and electrical crosstalk. In the present method, the magnetization of a FeCo-GdOx superparamagnetic tip is modulated by an external AC magnetic field in order to measure the magnetic domain structure without any perturbation from the other forces near the sample surface. Moreover, it is demonstrated that the proposed method can also measure the strength and identify the polarities of the second derivative of the perpendicular stray field from a thin-film permanent magnet with DC demagnetized state and remanent state. © 2018 IOP Publishing Ltd.

Optical flow estimation on image sequences with differently exposed frames

NASA Astrophysics Data System (ADS)

Bengtsson, Tomas; McKelvey, Tomas; Lindström, Konstantin

2015-09-01

Optical flow (OF) methods are used to estimate dense motion information between consecutive frames in image sequences. In addition to the specific OF estimation method itself, the quality of the input image sequence is of crucial importance to the quality of the resulting flow estimates. For instance, lack of texture in image frames caused by saturation of the camera sensor during exposure can significantly deteriorate the performance. An approach to avoid this negative effect is to use different camera settings when capturing the individual frames. We provide a framework for OF estimation on such sequences that contain differently exposed frames. Information from multiple frames are combined into a total cost functional such that the lack of an active data term for saturated image areas is avoided. Experimental results demonstrate that using alternate camera settings to capture the full dynamic range of an underlying scene can clearly improve the quality of flow estimates. When saturation of image data is significant, the proposed methods show superior performance in terms of lower endpoint errors of the flow vectors compared to a set of baseline methods. Furthermore, we provide some qualitative examples of how and when our method should be used.

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.

Preparation of scanning tunneling microscopy tips using pulsed alternating current etching

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

Valencia, Victor A.; Thaker, Avesh A.; Derouin, Jonathan

An electrochemical method using pulsed alternating current etching (PACE) to produce atomically sharp scanning tunneling microscopy (STM) tips is presented. An Arduino Uno microcontroller was used to control the number and duration of the alternating current (AC) pulses, allowing for ready optimization of the procedures for both Pt:Ir and W tips using a single apparatus. W tips prepared using constant and pulsed AC power were compared. Tips fashioned using PACE were sharper than those etched with continuous AC power alone. Pt:Ir tips were prepared with an initial coarse etching stage using continuous AC power followed by fine etching using PACE.more » The number and potential of the finishing AC pulses was varied and scanning electron microscope imaging was used to compare the results. Finally, tip quality using the optimized procedures was verified by UHV-STM imaging. With PACE, at least 70% of the W tips and 80% of the Pt:Ir tips were of sufficiently high quality to obtain atomically resolved images of HOPG or Ni(111)« less

Joint Prior Learning for Visual Sensor Network Noisy Image Super-Resolution

PubMed Central

Yue, Bo; Wang, Shuang; Liang, Xuefeng; Jiao, Licheng; Xu, Caijin

2016-01-01

The visual sensor network (VSN), a new type of wireless sensor network composed of low-cost wireless camera nodes, is being applied for numerous complex visual analyses in wild environments, such as visual surveillance, object recognition, etc. However, the captured images/videos are often low resolution with noise. Such visual data cannot be directly delivered to the advanced visual analysis. In this paper, we propose a joint-prior image super-resolution (JPISR) method using expectation maximization (EM) algorithm to improve VSN image quality. Unlike conventional methods that only focus on upscaling images, JPISR alternatively solves upscaling mapping and denoising in the E-step and M-step. To meet the requirement of the M-step, we introduce a novel non-local group-sparsity image filtering method to learn the explicit prior and induce the geometric duality between images to learn the implicit prior. The EM algorithm inherently combines the explicit prior and implicit prior by joint learning. Moreover, JPISR does not rely on large external datasets for training, which is much more practical in a VSN. Extensive experiments show that JPISR outperforms five state-of-the-art methods in terms of both PSNR, SSIM and visual perception. PMID:26927114

TH-EF-207A-05: Feasibility of Applying SMEIR Method On Small Animal 4D Cone Beam CT Imaging

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

Zhong, Y; Zhang, Y; Shao, Y

Purpose: Small animal cone beam CT imaging has been widely used in preclinical research. Due to the higher respiratory rate and heat beats of small animals, motion blurring is inevitable and needs to be corrected in the reconstruction. Simultaneous motion estimation and image reconstruction (SMEIR) method, which uses projection images of all phases, proved to be effective in motion model estimation and able to reconstruct motion-compensated images. We demonstrate the application of SMEIR for small animal 4D cone beam CT imaging by computer simulations on a digital rat model. Methods: The small animal CBCT imaging system was simulated with themore » source-to-detector distance of 300 mm and the source-to-object distance of 200 mm. A sequence of rat phantom were generated with 0.4 mm{sup 3} voxel size. The respiratory cycle was taken as 1.0 second and the motions were simulated with a diaphragm motion of 2.4mm and an anterior-posterior expansion of 1.6 mm. The projection images were calculated using a ray-tracing method, and 4D-CBCT were reconstructed using SMEIR and FDK methods. The SMEIR method iterates over two alternating steps: 1) motion-compensated iterative image reconstruction by using projections from all respiration phases and 2) motion model estimation from projections directly through a 2D-3D deformable registration of the image obtained in the first step to projection images of other phases. Results: The images reconstructed using SMEIR method reproduced the features in the original phantom. Projections from the same phase were also reconstructed using FDK method. Compared with the FDK results, the images from SMEIR method substantially improve the image quality with minimum artifacts. Conclusion: We demonstrate that it is viable to apply SMEIR method to reconstruct small animal 4D-CBCT images.« less

Rapid determination of particle velocity from space-time images using the Radon transform

PubMed Central

Drew, Patrick J.; Blinder, Pablo; Cauwenberghs, Gert; Shih, Andy Y.; Kleinfeld, David

2016-01-01

Laser-scanning methods are a means to observe streaming particles, such as the flow of red blood cells in a blood vessel. Typically, particle velocity is extracted from images formed from cyclically repeated line-scan data that is obtained along the center-line of the vessel; motion leads to streaks whose angle is a function of the velocity. Past methods made use of shearing or rotation of the images and a Singular Value Decomposition (SVD) to automatically estimate the average velocity in a temporal window of data. Here we present an alternative method that makes use of the Radon transform to calculate the velocity of streaming particles. We show that this method is over an order of magnitude faster than the SVD-based algorithm and is more robust to noise. PMID:19459038

Hierarchical Feature Extraction With Local Neural Response for Image Recognition.

PubMed

Li, Hong; Wei, Yantao; Li, Luoqing; Chen, C L P

2013-04-01

In this paper, a hierarchical feature extraction method is proposed for image recognition. The key idea of the proposed method is to extract an effective feature, called local neural response (LNR), of the input image with nontrivial discrimination and invariance properties by alternating between local coding and maximum pooling operation. The local coding, which is carried out on the locally linear manifold, can extract the salient feature of image patches and leads to a sparse measure matrix on which maximum pooling is carried out. The maximum pooling operation builds the translation invariance into the model. We also show that other invariant properties, such as rotation and scaling, can be induced by the proposed model. In addition, a template selection algorithm is presented to reduce computational complexity and to improve the discrimination ability of the LNR. Experimental results show that our method is robust to local distortion and clutter compared with state-of-the-art algorithms.

Half-quadratic variational regularization methods for speckle-suppression and edge-enhancement in SAR complex image

NASA Astrophysics Data System (ADS)

Zhao, Xia; Wang, Guang-xin

2008-12-01

Synthetic aperture radar (SAR) is an active remote sensing sensor. It is a coherent imaging system, the speckle is its inherent default, which affects badly the interpretation and recognition of the SAR targets. Conventional methods of removing the speckle is studied usually in real SAR image, which reduce the edges of the images at the same time as depressing the speckle. Morever, Conventional methods lost the information about images phase. Removing the speckle and enhancing the target and edge simultaneously are still a puzzle. To suppress the spckle and enhance the targets and the edges simultaneously, a half-quadratic variational regularization method in complex SAR image is presented, which is based on the prior knowledge of the targets and the edge. Due to the non-quadratic and non- convex quality and the complexity of the cost function, a half-quadratic variational regularization variation is used to construct a new cost function,which is solved by alternate optimization. In the proposed scheme, the construction of the model, the solution of the model and the selection of the model peremeters are studied carefully. In the end, we validate the method using the real SAR data.Theoretic analysis and the experimental results illustrate the the feasibility of the proposed method. Further more, the proposed method can preserve the information about images phase.

Enhancement of Satellite Image Compression Using a Hybrid (DWT-DCT) Algorithm

NASA Astrophysics Data System (ADS)

Shihab, Halah Saadoon; Shafie, Suhaidi; Ramli, Abdul Rahman; Ahmad, Fauzan

2017-12-01

Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) image compression techniques have been utilized in most of the earth observation satellites launched during the last few decades. However, these techniques have some issues that should be addressed. The DWT method has proven to be more efficient than DCT for several reasons. Nevertheless, the DCT can be exploited to improve the high-resolution satellite image compression when combined with the DWT technique. Hence, a proposed hybrid (DWT-DCT) method was developed and implemented in the current work, simulating an image compression system on-board on a small remote sensing satellite, with the aim of achieving a higher compression ratio to decrease the onboard data storage and the downlink bandwidth, while avoiding further complex levels of DWT. This method also succeeded in maintaining the reconstructed satellite image quality through replacing the standard forward DWT thresholding and quantization processes with an alternative process that employed the zero-padding technique, which also helped to reduce the processing time of DWT compression. The DCT, DWT and the proposed hybrid methods were implemented individually, for comparison, on three LANDSAT 8 images, using the MATLAB software package. A comparison was also made between the proposed method and three other previously published hybrid methods. The evaluation of all the objective and subjective results indicated the feasibility of using the proposed hybrid (DWT-DCT) method to enhance the image compression process on-board satellites.

Hyperspectral small animal fluorescence imaging: spectral selection imaging

NASA Astrophysics Data System (ADS)

Leavesley, Silas; Jiang, Yanan; Patsekin, Valery; Hall, Heidi; Vizard, Douglas; Robinson, J. Paul

2008-02-01

Molecular imaging is a rapidly growing area of research, fueled by needs in pharmaceutical drug-development for methods for high-throughput screening, pre-clinical and clinical screening for visualizing tumor growth and drug targeting, and a growing number of applications in the molecular biology fields. Small animal fluorescence imaging employs fluorescent probes to target molecular events in vivo, with a large number of molecular targeting probes readily available. The ease at which new targeting compounds can be developed, the short acquisition times, and the low cost (compared to microCT, MRI, or PET) makes fluorescence imaging attractive. However, small animal fluorescence imaging suffers from high optical scattering, absorption, and autofluorescence. Much of these problems can be overcome through multispectral imaging techniques, which collect images at different fluorescence emission wavelengths, followed by analysis, classification, and spectral deconvolution methods to isolate signals from fluorescence emission. We present an alternative to the current method, using hyperspectral excitation scanning (spectral selection imaging), a technique that allows excitation at any wavelength in the visible and near-infrared wavelength range. In many cases, excitation imaging may be more effective at identifying specific fluorescence signals because of the higher complexity of the fluorophore excitation spectrum. Because the excitation is filtered and not the emission, the resolution limit and image shift imposed by acousto-optic tunable filters have no effect on imager performance. We will discuss design of the imager, optimizing the imager for use in small animal fluorescence imaging, and application of spectral analysis and classification methods for identifying specific fluorescence signals.

Dynamic metabolic imaging of hyperpolarized [2-(13) C]pyruvate using spiral chemical shift imaging with alternating spectral band excitation.

PubMed

Josan, Sonal; Hurd, Ralph; Park, Jae Mo; Yen, Yi-Fen; Watkins, Ron; Pfefferbaum, Adolf; Spielman, Daniel; Mayer, Dirk

2014-06-01

In contrast to [1-(13) C]pyruvate, hyperpolarized [2-(13) C]pyruvate permits the ability to follow the (13) C label beyond flux through pyruvate dehydrogenase complex and investigate the incorporation of acetyl-coenzyme A into different metabolic pathways. However, chemical shift imaging (CSI) with [2-(13) C]pyruvate is challenging owing to the large spectral dispersion of the resonances, which also leads to severe chemical shift displacement artifacts for slice-selective acquisitions. This study introduces a sequence for three-dimensional CSI of [2-(13) C]pyruvate using spectrally selective excitation of limited frequency bands containing a subset of metabolites. Dynamic CSI data were acquired alternately from multiple frequency bands in phantoms for sequence testing and in vivo in rat heart. Phantom experiments verified the radiofrequency pulse design and demonstrated that the signal behavior of each group of resonances was unaffected by excitation of the other frequency bands. Dynamic three-dimensional (13) C CSI data demonstrated the sequence capability to image pyruvate, lactate, acetylcarnitine, glutamate, and acetoacetate, enabling the analysis of organ-specific spectra and metabolite time courses. The presented method allows CSI of widely separated resonances without chemical shift displacement artifact, acquiring multiple frequency bands alternately to obtain dynamic time-course information. This approach enables robust imaging of downstream metabolic products of acetyl-coenzyme A with hyperpolarized [2-(13) C]pyruvate. Copyright © 2013 Wiley Periodicals, Inc.

Radial magnetic resonance imaging (MRI) using a rotating radiofrequency (RF) coil at 9.4 T.

PubMed

Li, Mingyan; Weber, Ewald; Jin, Jin; Hugger, Thimo; Tesiram, Yasvir; Ullmann, Peter; Stark, Simon; Fuentes, Miguel; Junge, Sven; Liu, Feng; Crozier, Stuart

2018-02-01

The rotating radiofrequency coil (RRFC) has been developed recently as an alternative approach to multi-channel phased-array coils. The single-element RRFC avoids inter-channel coupling and allows a larger coil element with better B 1 field penetration when compared with an array counterpart. However, dedicated image reconstruction algorithms require accurate estimation of temporally varying coil sensitivities to remove artefacts caused by coil rotation. Various methods have been developed to estimate unknown sensitivity profiles from a few experimentally measured sensitivity maps, but these methods become problematic when the RRFC is used as a transceiver coil. In this work, a novel and practical radial encoding method is introduced for the RRFC to facilitate image reconstruction without the measurement or estimation of rotation-dependent sensitivity profiles. Theoretical analyses suggest that the rotation-dependent sensitivities of the RRFC can be used to create a uniform profile with careful choice of sampling positions and imaging parameters. To test this new imaging method, dedicated electronics were designed and built to control the RRFC speed and hence positions in synchrony with imaging parameters. High-quality phantom and animal images acquired on a 9.4 T pre-clinical scanner demonstrate the feasibility and potential of this new RRFC method. Copyright © 2017 John Wiley & Sons, Ltd.

Using Nonprinciple Rays to Form Images in Geometrical Optics

NASA Astrophysics Data System (ADS)

Marx, Jeff; Mian, Shabbir

2015-11-01

Constructing ray diagrams to locate the image of an object formed by thin lenses and mirrors is a staple of many introductory physics courses at the high school and college levels, and has been the subject of some pedagogy-related articles. Our review of textbooks distributed in the United States suggests that the singular approach involves drawing principle rays to locate an object's image. We were pleasantly surprised to read an article in this journal by Suppapittayaporn et al. in which they use an alternative method to construct rays for thin lenses based on a "tilted principle axis" (TPA). In particular, we were struck by the generality of the approach (a single rule for tracing rays as compared to the typical two or three rules), and how it could help students more easily tackle challenging situations, such as multi-lens systems and occluded lenses, where image construction using principle rays may be impractical. In this paper, we provide simple "proofs" for this alternative approach for the case of thin lenses and single refracting surfaces.

WE-G-18C-07: Accelerated Water/fat Separation in MRI for Radiotherapy Planning Using Multi-Band Imaging Techniques

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

Crijns, S; Stemkens, B; Sbrizzi, A

Purpose: Dixon sequences are used to characterize disease processes, obtain good fat or water separation in cases where fat suppression fails and to obtain pseudo-CT datasets. Dixon's method uses at least two images acquired with different echo times and thus requires prolonged acquisition times. To overcome associated problems (e.g., for DCE/cine-MRI), we propose to use a method for water/fat separation based on spectrally selective RF pulses. Methods: Two alternating RF pulses were used, that imposes a fat selective phase cycling over the phase encoding lines, which results in a spatial shift for fat in the reconstructed image, identical to thatmore » in CAIPIRINHA. Associated aliasing artefacts were resolved using the encoding power of a multi-element receiver array, analogous to SENSE. In vivo measurements were performed on a 1.5T clinical MR-scanner in a healthy volunteer's legs, using a four channel receiver coil. Gradient echo images were acquired with TE/TR = 2.3/4.7ms, flip angle 20°, FOV 45×22.5cm{sup 2}, matrix 480×216, slice thickness 5mm. Dixon images were acquired with TE,1/TE,2/TR=2.2/4.6/7ms. All image reconstructions were done in Matlab using the ReconFrame toolbox (Gyrotools, Zurich, CH). Results: RF pulse alternation yields a fat image offset from the water image. Hence the water and fat images fold over, which is resolved using in-plane SENSE reconstruction. Using the proposed technique, we achieved excellent water/fat separation comparable to Dixon images, while acquiring images at only one echo time. Conclusion: The proposed technique yields both inphase water and fat images at arbitrary echo times and requires only one measurement, thereby shortening the acquisition time by a factor 2. In future work the technique may be extended to a multi-band water/fat separation sequence that is able to achieve single point water/fat separation in multiple slices at once and hence yields higher speed-up factors.« less

A method for determining electrophoretic and electroosmotic mobilities using AC and DC electric field particle displacements.

PubMed

Oddy, M H; Santiago, J G

2004-01-01

We have developed a method for measuring the electrophoretic mobility of submicrometer, fluorescently labeled particles and the electroosmotic mobility of a microchannel. We derive explicit expressions for the unknown electrophoretic and the electroosmotic mobilities as a function of particle displacements resulting from alternating current (AC) and direct current (DC) applied electric fields. Images of particle displacements are captured using an epifluorescent microscope and a CCD camera. A custom image-processing code was developed to determine image streak lengths associated with AC measurements, and a custom particle tracking velocimetry (PTV) code was devised to determine DC particle displacements. Statistical analysis was applied to relate mobility estimates to measured particle displacement distributions.

A physical parameter method for the design of broad-band X-ray imaging systems to do coronal plasma diagnostics

NASA Technical Reports Server (NTRS)

Kahler, S.; Krieger, A. S.

1978-01-01

The technique commonly used for the analysis of data from broad-band X-ray imaging systems for plasma diagnostics is the filter ratio method. This requires the use of two or more broad-band filters to derive temperatures and line-of-sight emission integrals or emission measure distributions as a function of temperature. Here an alternative analytical approach is proposed in which the temperature response of the imaging system is matched to the physical parameter being investigated. The temperature response of a system designed to measure the total radiated power along the line of sight of any coronal structure is calculated. Other examples are discussed.

3D optic disc reconstruction via a global fundus stereo algorithm.

PubMed

Bansal, M; Sizintsev, M; Eledath, J; Sawhney, H; Pearson, D J; Stone, R A

2013-01-01

This paper presents a novel method to recover 3D structure of the optic disc in the retina from two uncalibrated fundus images. Retinal images are commonly uncalibrated when acquired clinically, creating rectification challenges as well as significant radiometric and blur differences within the stereo pair. By exploiting structural peculiarities of the retina, we modified the Graph Cuts computational stereo method (one of current state-of-the-art methods) to yield a high quality algorithm for fundus stereo reconstruction. Extensive qualitative and quantitative experimental evaluation (where OCT scans are used as 3D ground truth) on our and publicly available datasets shows the superiority of the proposed method in comparison to other alternatives.

Evaluation of the image quality of telescopes using the star test

NASA Astrophysics Data System (ADS)

Vazquez y Monteil, Sergio; Salazar Romero, Marcos A.; Gale, David M.

2004-10-01

The Point Spread Function (PSF) or star test is one of the main criteria to be considered in the quality of the image formed by a telescope. In a real system the distribution of irradiance in the image of a point source is given by the PSF, a function which is highly sensitive to aberrations. The PSF of a telescope may be determined by measuring the intensity distribution in the image of a star. Alternatively, if we already know the aberrations present in the optical system, then we may use diffraction theory to calculate the function. In this paper we propose a method for determining the wavefront aberrations from the PSF, using Genetic Algorithms to perform an optimization process starting from the PSF instead of the more traditional method of adjusting an aberration polynomial. We show that this method of phase recuperation is immune to noise-induced errors arising during image aquisition and registration. Some practical results are shown.

Three-dimensional visualization of geographical terrain data using temporal parallax difference induction

NASA Astrophysics Data System (ADS)

Mayhew, Christopher A.; Mayhew, Craig M.

2009-02-01

Vision III Imaging, Inc. (the Company) has developed Parallax Image Display (PIDTM) software tools to critically align and display aerial images with parallax differences. Terrain features are rendered obvious to the viewer when critically aligned images are presented alternately at 4.3 Hz. The recent inclusion of digital elevation models in geographic data browsers now allows true three-dimensional parallax to be acquired from virtual globe programs like Google Earth. The authors have successfully developed PID methods and code that allow three-dimensional geographical terrain data to be visualized using temporal parallax differences.

TU-CD-BRA-12: Coupling PET Image Restoration and Segmentation Using Variational Method with Multiple Regularizations

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

Li, L; Tan, S; Lu, W

Purpose: To propose a new variational method which couples image restoration with tumor segmentation for PET images using multiple regularizations. Methods: Partial volume effect (PVE) is a major degrading factor impacting tumor segmentation accuracy in PET imaging. The existing segmentation methods usually need to take prior calibrations to compensate PVE and they are highly system-dependent. Taking into account that image restoration and segmentation can promote each other and they are tightly coupled, we proposed a variational method to solve the two problems together. Our method integrated total variation (TV) semi-blind deconvolution and Mumford-Shah (MS) segmentation. The TV norm was usedmore » on edges to protect the edge information, and the L{sub 2} norm was used to avoid staircase effect in the no-edge area. The blur kernel was constrained to the Gaussian model parameterized by its variance and we assumed that the variances in the X-Y and Z directions are different. The energy functional was iteratively optimized by an alternate minimization algorithm. Segmentation performance was tested on eleven patients with non-Hodgkin’s lymphoma, and evaluated by Dice similarity index (DSI) and classification error (CE). For comparison, seven other widely used methods were also tested and evaluated. Results: The combination of TV and L{sub 2} regularizations effectively improved the segmentation accuracy. The average DSI increased by around 0.1 than using either the TV or the L{sub 2} norm. The proposed method was obviously superior to other tested methods. It has an average DSI and CE of 0.80 and 0.41, while the FCM method — the second best one — has only an average DSI and CE of 0.66 and 0.64. Conclusion: Coupling image restoration and segmentation can handle PVE and thus improves tumor segmentation accuracy in PET. Alternate use of TV and L2 regularizations can further improve the performance of the algorithm. This work was supported in part by National Natural Science Foundation of China (NNSFC), under Grant No.61375018, and Fundamental Research Funds for the Central Universities, under Grant No. 2012QN086. Wei Lu was supported in part by the National Institutes of Health (NIH) Grant No. R01 CA172638.« less

FT-IR imaging for quantitative determination of liver fat content in non-alcoholic fatty liver.

PubMed

Kochan, K; Maslak, E; Chlopicki, S; Baranska, M

2015-08-07

In this work we apply FT-IR imaging of large areas of liver tissue cross-section samples (∼5 cm × 5 cm) for quantitative assessment of steatosis in murine model of Non-Alcoholic Fatty Liver (NAFLD). We quantified the area of liver tissue occupied by lipid droplets (LDs) by FT-IR imaging and Oil Red O (ORO) staining for comparison. Two alternative FT-IR based approaches are presented. The first, straightforward method, was based on average spectra from tissues and provided values of the fat content by using a PLS regression model and the reference method. The second one – the chemometric-based method – enabled us to determine the values of the fat content, independently of the reference method by means of k-means cluster (KMC) analysis. In summary, FT-IR images of large size liver sections may prove to be useful for quantifying liver steatosis without the need of tissue staining.

Comparison of magnetic resonance imaging and computed tomography in suspected lesions in the posterior cranial fossa.

PubMed Central

Teasdale, G. M.; Hadley, D. M.; Lawrence, A.; Bone, I.; Burton, H.; Grant, R.; Condon, B.; Macpherson, P.; Rowan, J.

1989-01-01

OBJECTIVE--To compare computed tomography and magnetic resonance imaging in investigating patients suspected of having a lesion in the posterior cranial fossa. DESIGN--Randomised allocation of newly referred patients to undergo either computed tomography or magnetic resonance imaging; the alternative investigation was performed subsequently only in response to a request from the referring doctor. SETTING--A regional neuroscience centre serving 2.7 million. PATIENTS--1020 Patients recruited between April 1986 and December 1987, all suspected by neurologists, neurosurgeons, or other specialists of having a lesion in the posterior fossa and referred for neuroradiology. The groups allocated to undergo computed tomography or magnetic resonance imaging were well matched in distributions of age, sex, specialty of referring doctor, investigation as an inpatient or an outpatient, suspected site of lesion, and presumed disease process; the referring doctor's confidence in the initial clinical diagnosis was also similar. INTERVENTIONS--After the patients had been imaged by either computed tomography or magnetic resonance (using a resistive magnet of 0.15 T) doctors were given the radiologist's report and a form asking if they considered that imaging with the alternative technique was necessary and, if so, why; it also asked for their current diagnoses and their confidence in them. MAIN OUTCOME MEASURES--Number of requests for the alternative method of investigation. Assessment of characteristics of patients for whom further imaging was requested and lesions that were suspected initially and how the results of the second imaging affected clinicians' and radiologists' opinions. RESULTS--Ninety three of the 501 patients who initially underwent computed tomography were referred subsequently for magnetic resonance imaging whereas only 28 of the 493 patients who initially underwent magnetic resonance imaging were referred subsequently for computed tomography. Over the study the number of patients referred for magnetic resonance imaging after computed tomography increased but requests for computed tomography after magnetic resonance imaging decreased. The reason that clinicians gave most commonly for requesting further imaging by magnetic resonance was that the results of the initial computed tomography failed to exclude their suspected diagnosis (64 patients). This was less common in patients investigated initially by magnetic resonance imaging (eight patients). Management of 28 patients (6%) imaged initially with computed tomography and 12 patients (2%) imaged initially with magnetic resonance was changed on the basis of the results of the alternative imaging. CONCLUSIONS--Magnetic resonance imaging provided doctors with the information required to manage patients suspected of having a lesion in the posterior fossa more commonly than computed tomography, but computed tomography alone was satisfactory in 80% of cases... PMID:2506965

The Utility of the Extended Images in Ambient Seismic Wavefield Migration

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Optical multichannel room temperature magnetic field imaging system for clinical application

PubMed Central

Lembke, G.; Erné, S. N.; Nowak, H.; Menhorn, B.; Pasquarelli, A.

2014-01-01

Optically pumped magnetometers (OPM) are a very promising alternative to the superconducting quantum interference devices (SQUIDs) used nowadays for Magnetic Field Imaging (MFI), a new method of diagnosis based on the measurement of the magnetic field of the human heart. We present a first measurement combining a multichannel OPM-sensor with an existing MFI-system resulting in a fully functional room temperature MFI-system. PMID:24688820

Effects of light refraction on the accuracy of camera calibration and reconstruction in underwater motion analysis.

PubMed

Kwon, Young-Hoo; Casebolt, Jeffrey B

2006-01-01

One of the most serious obstacles to accurate quantification of the underwater motion of a swimmer's body is image deformation caused by refraction. Refraction occurs at the water-air interface plane (glass) owing to the density difference. Camera calibration-reconstruction algorithms commonly used in aquatic research do not have the capability to correct this refraction-induced nonlinear image deformation and produce large reconstruction errors. The aim of this paper is to provide a through review of: the nature of the refraction-induced image deformation and its behaviour in underwater object-space plane reconstruction; the intrinsic shortcomings of the Direct Linear Transformation (DLT) method in underwater motion analysis; experimental conditions that interact with refraction; and alternative algorithms and strategies that can be used to improve the calibration-reconstruction accuracy. Although it is impossible to remove the refraction error completely in conventional camera calibration-reconstruction methods, it is possible to improve the accuracy to some extent by manipulating experimental conditions or calibration frame characteristics. Alternative algorithms, such as the localized DLT and the double-plane method are also available for error reduction. The ultimate solution for the refraction problem is to develop underwater camera calibration and reconstruction algorithms that have the capability to correct refraction.

Effects of light refraction on the accuracy of camera calibration and reconstruction in underwater motion analysis.

PubMed

Kwon, Young-Hoo; Casebolt, Jeffrey B

2006-07-01

One of the most serious obstacles to accurate quantification of the underwater motion of a swimmer's body is image deformation caused by refraction. Refraction occurs at the water-air interface plane (glass) owing to the density difference. Camera calibration-reconstruction algorithms commonly used in aquatic research do not have the capability to correct this refraction-induced nonlinear image deformation and produce large reconstruction errors. The aim of this paper is to provide a thorough review of: the nature of the refraction-induced image deformation and its behaviour in underwater object-space plane reconstruction; the intrinsic shortcomings of the Direct Linear Transformation (DLT) method in underwater motion analysis; experimental conditions that interact with refraction; and alternative algorithms and strategies that can be used to improve the calibration-reconstruction accuracy. Although it is impossible to remove the refraction error completely in conventional camera calibration-reconstruction methods, it is possible to improve the accuracy to some extent by manipulating experimental conditions or calibration frame characteristics. Alternative algorithms, such as the localized DLT and the double-plane method are also available for error reduction. The ultimate solution for the refraction problem is to develop underwater camera calibration and reconstruction algorithms that have the capability to correct refraction.

Magnetic domain observation of FeCo thin films fabricated by alternate monoatomic layer deposition

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

Ohtsuki, T., E-mail: ohtsuki@spring8.or.jp; Kotsugi, M.; Ohkochi, T.

2014-01-28

FeCo thin films are fabricated by alternate monoatomic layer deposition method on a Cu{sub 3}Au buffer layer, which in-plane lattice constant is very close to the predicted value to obtain a large magnetic anisotropy constant. The variation of the in-plane lattice constant during the deposition process is investigated by reflection high-energy electron diffraction. The magnetic domain images are also observed by a photoelectron emission microscope in order to microscopically understand the magnetic structure. As a result, element-specific magnetic domain images show that Fe and Co magnetic moments align parallel. A series of images obtained with various azimuth reveal that themore » FeCo thin films show fourfold in-plane magnetic anisotropy along 〈110〉 direction, and that the magnetic domain structure is composed only of 90∘ wall.« less

TH-A-BRF-11: Image Intensity Non-Uniformities Between MRI Simulation and Diagnostic MRI

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

Paulson, E

2014-06-15

Purpose: MRI simulation for MRI-based radiotherapy demands that patients be setup in treatment position, which frequently involves use of alternative radiofrequency (RF) coil configurations to accommodate immobilized patients. However, alternative RF coil geometries may exacerbate image intensity non-uniformities (IINU) beyond those observed in diagnostic MRI, which may challenge image segmentation and registration accuracy as well as confound studies assessing radiotherapy response when MR simulation images are used as baselines for evaluation. The goal of this work was to determine whether differences in IINU exist between MR simulation and diagnostic MR images. Methods: ACR-MRI phantom images were acquired at 3T usingmore » a spin-echo sequence (TE/TR:20/500ms, rBW:62.5kHz, TH/skip:5/5mm). MR simulation images were obtained by wrapping two flexible phased-array RF coils around the phantom. Diagnostic MR images were obtained by placing the phantom into a commercial phased-array head coil. Pre-scan normalization was enabled in both cases. Images were transferred offline and corrected for IINU using the MNI N3 algorithm. Coefficients of variation (CV=σ/μ) were calculated for each slice. Wilcoxon matched-pairs and Mann-Whitney tests compared CV values between original and N3 images and between MR simulation and diagnostic MR images. Results: Significant differences in CV were detected between original and N3 images in both MRI simulation and diagnostic MRI groups (p=0.010, p=0.010). In addition, significant differences in CV were detected between original MR simulation and original and N3 diagnostic MR images (p=0.0256, p=0.0016). However, no significant differences in CV were detected between N3 MR simulation images and original or N3 diagnostic MR images, demonstrating the importance of correcting MR simulation images beyond pre-scan normalization prior to use in radiotherapy. Conclusions: Alternative RF coil configurations used in MRI simulation can Result in significant IINU differences compared to diagnostic MR images. The MNI N3 algorithm reduced MR simulation IINU to levels observed in diagnostic MR images. Funding provided by Advancing a Healthier Wisconsin.« less

Automatic segmentation of meningioma from non-contrasted brain MRI integrating fuzzy clustering and region growing.

PubMed

Hsieh, Thomas M; Liu, Yi-Min; Liao, Chun-Chih; Xiao, Furen; Chiang, I-Jen; Wong, Jau-Min

2011-08-26

In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images.This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for automated tumor image segmentation from patients with menigioma. Only non-contrasted T1 and T2 -weighted MR images are included in the analysis. The study's aims are to correctly locate tumors in the images, and to detect those situated in the midline position of the brain. The study used non-contrasted T1- and T2-weighted MR images from 29 patients with menigioma. After FCM clustering, 32 groups of images from each patient group were put through the region-growing procedure for pixels aggregation. Later, using knowledge-based information, the system selected tumor-containing images from these groups and merged them into one tumor image. An alternative semi-supervised method was added at this stage for comparison with the automatic method. Finally, the tumor image was optimized by a morphology operator. Results from automatic segmentation were compared to the "ground truth" (GT) on a pixel level. Overall data were then evaluated using a quantified system. The quantified parameters, including the "percent match" (PM) and "correlation ratio" (CR), suggested a high match between GT and the present study's system, as well as a fair level of correspondence. The results were compatible with those from other related studies. The system successfully detected all of the tumors situated at the midline of brain.Six cases failed in the automatic group. One also failed in the semi-supervised alternative. The remaining five cases presented noticeable edema inside the brain. In the 23 successful cases, the PM and CR values in the two groups were highly related. Results indicated that, even when using only two sets of non-contrasted MR images, the system is a reliable and efficient method of brain-tumor detection. With further development the system demonstrates high potential for practical clinical use.

Reprint of Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

NASA Astrophysics Data System (ADS)

D'Ambra, Pasqua; Tartaglione, Gaetano

2015-04-01

Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.

Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

NASA Astrophysics Data System (ADS)

D'Ambra, Pasqua; Tartaglione, Gaetano

2015-03-01

Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.

Extracting Information about the Rotator Cuff from Magnetic Resonance Images Using Deterministic and Random Techniques

PubMed Central

De Los Ríos, F. A.; Paluszny, M.

2015-01-01

We consider some methods to extract information about the rotator cuff based on magnetic resonance images; the study aims to define an alternative method of display that might facilitate the detection of partial tears in the supraspinatus tendon. Specifically, we are going to use families of ellipsoidal triangular patches to cover the humerus head near the affected area. These patches are going to be textured and displayed with the information of the magnetic resonance images using the trilinear interpolation technique. For the generation of points to texture each patch, we propose a new method that guarantees the uniform distribution of its points using a random statistical method. Its computational cost, defined as the average computing time to generate a fixed number of points, is significantly lower as compared with deterministic and other standard statistical techniques. PMID:25650281

A Nonlinear Diffusion Equation-Based Model for Ultrasound Speckle Noise Removal

NASA Astrophysics Data System (ADS)

Zhou, Zhenyu; Guo, Zhichang; Zhang, Dazhi; Wu, Boying

2018-04-01

Ultrasound images are contaminated by speckle noise, which brings difficulties in further image analysis and clinical diagnosis. In this paper, we address this problem in the view of nonlinear diffusion equation theories. We develop a nonlinear diffusion equation-based model by taking into account not only the gradient information of the image, but also the information of the gray levels of the image. By utilizing the region indicator as the variable exponent, we can adaptively control the diffusion type which alternates between the Perona-Malik diffusion and the Charbonnier diffusion according to the image gray levels. Furthermore, we analyze the proposed model with respect to the theoretical and numerical properties. Experiments show that the proposed method achieves much better speckle suppression and edge preservation when compared with the traditional despeckling methods, especially in the low gray level and low-contrast regions.

Parallel magnetic resonance imaging using coils with localized sensitivities.

PubMed

Goldfarb, James W; Holland, Agnes E

2004-09-01

The purpose of this study was to present clinical examples and illustrate the inefficiencies of a conventional reconstruction using a commercially available phased array coil with localized sensitivities. Five patients were imaged at 1.5 T using a cardiac-synchronized gadolinium-enhanced acquisition and a commercially available four-element phased array coil. Four unique sets of images were reconstructed from the acquired k-space data: (a) sum-of-squares image using four elements of the coil; localized sum-of-squares images from the (b) anterior coils and (c) posterior coils and a (c) local reconstruction. Images were analyzed for artifacts and usable field-of-view. Conventional image reconstruction produced images with fold-over artifacts in all cases spanning a portion of the image (mean 90 mm; range 36-126 mm). The local reconstruction removed fold-over artifacts and resulted in an effective increase in the field-of-view (mean 50%; range 20-70%). Commercially available phased array coils do not always have overlapping sensitivities. Fold-over artifacts can be removed using an alternate reconstruction method. When assessing the advantages of parallel imaging techniques, gains achieved using techniques such as SENSE and SMASH should be gauged against the acquisition time of the localized method rather than the conventional sum-of-squares method.

Comparative evaluation of RetCam vs. gonioscopy images in congenital glaucoma.

PubMed

Azad, Raj V; Chandra, Parijat; Chandra, Anuradha; Gupta, Aparna; Gupta, Viney; Sihota, Ramanjit

2014-02-01

To compare clarity, exposure and quality of anterior chamber angle visualization in congenital glaucoma patients, using RetCam and indirect gonioscopy images. Cross-sectional study Participants. Congenital glaucoma patients over age of 5 years. A prospective consecutive pilot study was done in congenital glaucoma patients who were older than 5 years. Methods used are indirect gonioscopy and RetCam imaging. Clarity of the image, extent of angle visible and details of angle structures seen were graded for both methods, on digitally recorded images, in each eye, by two masked observers. Image clarity, interobserver agreement. 40 eyes of 25 congenital glaucoma patients were studied. RetCam image had excellent clarity in 77.5% of patients versus 47.5% by gonioscopy. The extent of angle seen was similar by both methods. Agreement between RetCam and gonioscopy images regarding details of angle structures was 72.50% by observer 1 and 65.00% by observer 2. There was good agreement between RetCam and indirect gonioscopy images in detecting angle structures of congenital glaucoma patients. However, RetCam provided greater clarity, with better quality, and higher magnification images. RetCam can be a useful alternative to gonioscopy in infants and small children without the need for general anesthesia.

Steer-PROP: a GRASE-PROPELLER sequence with interecho steering gradient pulses.

PubMed

Srinivasan, Girish; Rangwala, Novena; Zhou, Xiaohong Joe

2018-05-01

This study demonstrates a novel PROPELLER (periodically rotated overlapping parallel lines with enhanced reconstruction) pulse sequence, termed Steer-PROP, based on gradient and spin echo (GRASE), to reduce the imaging times and address phase errors inherent to GRASE. The study also illustrates the feasibility of using Steer-PROP as an alternative to single-shot echo planar imaging (SS-EPI) to produce distortion-free diffusion images in all imaging planes. Steer-PROP uses a series of blip gradient pulses to produce N (N = 3-5) adjacent k-space blades in each repetition time, where N is the number of gradient echoes in a GRASE sequence. This sampling strategy enables a phase correction algorithm to systematically address the GRASE phase errors as well as the motion-induced phase inconsistency. Steer-PROP was evaluated on phantoms and healthy human subjects at both 1.5T and 3.0T for T 2 - and diffusion-weighted imaging. Steer-PROP produced similar image quality as conventional PROPELLER based on fast spin echo (FSE), while taking only a fraction (e.g., 1/3) of the scan time. The robustness against motion in Steer-PROP was comparable to that of FSE-based PROPELLER. Using Steer-PROP, high quality and distortion-free diffusion images were obtained from human subjects in all imaging planes, demonstrating a considerable advantage over SS-EPI. The proposed Steer-PROP sequence can substantially reduce the scan times compared with FSE-based PROPELLER while achieving adequate image quality. The novel k-space sampling strategy in Steer-PROP not only enables an integrated phase correction method that addresses various sources of phase errors, but also minimizes the echo spacing compared with alternative sampling strategies. Steer-PROP can also be a viable alternative to SS-EPI to decrease image distortion in all imaging planes. Magn Reson Med 79:2533-2541, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Smart light random memory sprays Retinex: a fast Retinex implementation for high-quality brightness adjustment and color correction.

PubMed

Banić, Nikola; Lončarić, Sven

2015-11-01

Removing the influence of illumination on image colors and adjusting the brightness across the scene are important image enhancement problems. This is achieved by applying adequate color constancy and brightness adjustment methods. One of the earliest models to deal with both of these problems was the Retinex theory. Some of the Retinex implementations tend to give high-quality results by performing local operations, but they are computationally relatively slow. One of the recent Retinex implementations is light random sprays Retinex (LRSR). In this paper, a new method is proposed for brightness adjustment and color correction that overcomes the main disadvantages of LRSR. There are three main contributions of this paper. First, a concept of memory sprays is proposed to reduce the number of LRSR's per-pixel operations to a constant regardless of the parameter values, thereby enabling a fast Retinex-based local image enhancement. Second, an effective remapping of image intensities is proposed that results in significantly higher quality. Third, the problem of LRSR's halo effect is significantly reduced by using an alternative illumination processing method. The proposed method enables a fast Retinex-based image enhancement by processing Retinex paths in a constant number of steps regardless of the path size. Due to the halo effect removal and remapping of the resulting intensities, the method outperforms many of the well-known image enhancement methods in terms of resulting image quality. The results are presented and discussed. It is shown that the proposed method outperforms most of the tested methods in terms of image brightness adjustment, color correction, and computational speed.

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

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

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

2012-05-11

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

Instrument performance enhancement and modification through an extended instrument paradigm

NASA Astrophysics Data System (ADS)

Mahan, Stephen Lee

An extended instrument paradigm is proposed, developed and shown in various applications. The CBM (Chin, Blass, Mahan) method is an extension to the linear systems model of observing systems. In the most obvious and practical application of image enhancement of an instrument characterized by a time-invariant instrumental response function, CBM can be used to enhance images or spectra through a simple convolution application of the CBM filter for a resolution improvement of as much as a factor of two. The CBM method can be used in many applications. We discuss several within this work including imaging through turbulent atmospheres, or what we've called Adaptive Imaging. Adaptive Imaging provides an alternative approach for the investigator desiring results similar to those obtainable with adaptive optics, however on a minimal budget. The CBM method is also used in a backprojected filtered image reconstruction method for Positron Emission Tomography. In addition, we can use information theoretic methods to aid in the determination of model instrumental response function parameters for images having an unknown origin. Another application presented herein involves the use of the CBM method for the determination of the continuum level of a Fourier transform spectrometer observation of ethylene, which provides a means for obtaining reliable intensity measurements in an automated manner. We also present the application of CBM to hyperspectral image data of the comet Shoemaker-Levy 9 impact with Jupiter taken with an acousto-optical tunable filter equipped CCD camera to an adaptive optics telescope.

Alternatively Constrained Dictionary Learning For Image Superresolution.

PubMed

Lu, Xiaoqiang; Yuan, Yuan; Yan, Pingkun

2014-03-01

Dictionaries are crucial in sparse coding-based algorithm for image superresolution. Sparse coding is a typical unsupervised learning method to study the relationship between the patches of high-and low-resolution images. However, most of the sparse coding methods for image superresolution fail to simultaneously consider the geometrical structure of the dictionary and the corresponding coefficients, which may result in noticeable superresolution reconstruction artifacts. In other words, when a low-resolution image and its corresponding high-resolution image are represented in their feature spaces, the two sets of dictionaries and the obtained coefficients have intrinsic links, which has not yet been well studied. Motivated by the development on nonlocal self-similarity and manifold learning, a novel sparse coding method is reported to preserve the geometrical structure of the dictionary and the sparse coefficients of the data. Moreover, the proposed method can preserve the incoherence of dictionary entries and provide the sparse coefficients and learned dictionary from a new perspective, which have both reconstruction and discrimination properties to enhance the learning performance. Furthermore, to utilize the model of the proposed method more effectively for single-image superresolution, this paper also proposes a novel dictionary-pair learning method, which is named as two-stage dictionary training. Extensive experiments are carried out on a large set of images comparing with other popular algorithms for the same purpose, and the results clearly demonstrate the effectiveness of the proposed sparse representation model and the corresponding dictionary learning algorithm.

Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators

PubMed Central

Bai, Xiangzhi

2015-01-01

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion. PMID:26184229

Infrared and Visual Image Fusion through Fuzzy Measure and Alternating Operators.

PubMed

Bai, Xiangzhi

2015-07-15

The crucial problem of infrared and visual image fusion is how to effectively extract the image features, including the image regions and details and combine these features into the final fusion result to produce a clear fused image. To obtain an effective fusion result with clear image details, an algorithm for infrared and visual image fusion through the fuzzy measure and alternating operators is proposed in this paper. Firstly, the alternating operators constructed using the opening and closing based toggle operator are analyzed. Secondly, two types of the constructed alternating operators are used to extract the multi-scale features of the original infrared and visual images for fusion. Thirdly, the extracted multi-scale features are combined through the fuzzy measure-based weight strategy to form the final fusion features. Finally, the final fusion features are incorporated with the original infrared and visual images using the contrast enlargement strategy. All the experimental results indicate that the proposed algorithm is effective for infrared and visual image fusion.

For geological investigations with airborne thermal infrared multispectral images: Transfer of calibration from laboratory spectrometer to TIMS as alternative for removing atmospheric effects

NASA Technical Reports Server (NTRS)

Edgett, Kenneth S.; Anderson, Donald L.

1995-01-01

This paper describes an empirical method to correct TIMS (Thermal Infrared Multispectral Scanner) data for atmospheric effects by transferring calibration from a laboratory thermal emission spectrometer to the TIMS multispectral image. The method does so by comparing the laboratory spectra of samples gathered in the field with TIMS 6-point spectra for pixels at the location of field sampling sites. The transference of calibration also makes it possible to use spectra from the laboratory as endmembers in unmixing studies of TIMS data.

Convex composite wavelet frame and total variation-based image deblurring using nonconvex penalty functions

NASA Astrophysics Data System (ADS)

Shen, Zhengwei; Cheng, Lishuang

2017-09-01

Total variation (TV)-based image deblurring method can bring on staircase artifacts in the homogenous region of the latent images recovered from the degraded images while a wavelet/frame-based image deblurring method will lead to spurious noise spikes and pseudo-Gibbs artifacts in the vicinity of discontinuities of the latent images. To suppress these artifacts efficiently, we propose a nonconvex composite wavelet/frame and TV-based image deblurring model. In this model, the wavelet/frame and the TV-based methods may complement each other, which are verified by theoretical analysis and experimental results. To further improve the quality of the latent images, nonconvex penalty function is used to be the regularization terms of the model, which may induce a stronger sparse solution and will more accurately estimate the relative large gradient or wavelet/frame coefficients of the latent images. In addition, by choosing a suitable parameter to the nonconvex penalty function, the subproblem that splits by the alternative direction method of multipliers algorithm from the proposed model can be guaranteed to be a convex optimization problem; hence, each subproblem can converge to a global optimum. The mean doubly augmented Lagrangian and the isotropic split Bregman algorithms are used to solve these convex subproblems where the designed proximal operator is used to reduce the computational complexity of the algorithms. Extensive numerical experiments indicate that the proposed model and algorithms are comparable to other state-of-the-art model and methods.

Visualization of anisotropic-isotropic phase transformation dynamics in battery electrode particles

DOE PAGES

Wang, Jiajun; Karen Chen-Wiegart, Yu-chen; Eng, Christopher; ...

2016-08-12

Anisotropy, or alternatively, isotropy of phase transformations extensively exist in a number of solid-state materials, with performance depending on the three-dimensional transformation features. Fundamental insights into internal chemical phase evolution allow manipulating materials with desired functionalities, and can be developed via real-time multi-dimensional imaging methods. In this paper, we report a five-dimensional imaging method to track phase transformation as a function of charging time in individual lithium iron phosphate battery cathode particles during delithiation. The electrochemically driven phase transformation is initially anisotropic with a preferred boundary migration direction, but becomes isotropic as delithiation proceeds further. We also observe the expectedmore » two-phase coexistence throughout the entire charging process. Finally, we expect this five-dimensional imaging method to be broadly applicable to problems in energy, materials, environmental and life sciences.« less

Open source tools for fluorescent imaging.

PubMed

Hamilton, Nicholas A

2012-01-01

As microscopy becomes increasingly automated and imaging expands in the spatial and time dimensions, quantitative analysis tools for fluorescent imaging are becoming critical to remove both bottlenecks in throughput as well as fully extract and exploit the information contained in the imaging. In recent years there has been a flurry of activity in the development of bio-image analysis tools and methods with the result that there are now many high-quality, well-documented, and well-supported open source bio-image analysis projects with large user bases that cover essentially every aspect from image capture to publication. These open source solutions are now providing a viable alternative to commercial solutions. More importantly, they are forming an interoperable and interconnected network of tools that allow data and analysis methods to be shared between many of the major projects. Just as researchers build on, transmit, and verify knowledge through publication, open source analysis methods and software are creating a foundation that can be built upon, transmitted, and verified. Here we describe many of the major projects, their capabilities, and features. We also give an overview of the current state of open source software for fluorescent microscopy analysis and the many reasons to use and develop open source methods. Copyright © 2012 Elsevier Inc. All rights reserved.

Revising the lower statistical limit of x-ray grating-based phase-contrast computed tomography.

PubMed

Marschner, Mathias; Birnbacher, Lorenz; Willner, Marian; Chabior, Michael; Herzen, Julia; Noël, Peter B; Pfeiffer, Franz

2017-01-01

Phase-contrast x-ray computed tomography (PCCT) is currently investigated as an interesting extension of conventional CT, providing high soft-tissue contrast even if examining weakly absorbing specimen. Until now, the potential for dose reduction was thought to be limited compared to attenuation CT, since meaningful phase retrieval fails for scans with very low photon counts when using the conventional phase retrieval method via phase stepping. In this work, we examine the statistical behaviour of the reverse projection method, an alternative phase retrieval approach and compare the results to the conventional phase retrieval technique. We investigate the noise levels in the projections as well as the image quality and quantitative accuracy of the reconstructed tomographic volumes. The results of our study show that this method performs better in a low-dose scenario than the conventional phase retrieval approach, resulting in lower noise levels, enhanced image quality and more accurate quantitative values. Overall, we demonstrate that the lower statistical limit of the phase stepping procedure as proposed by recent literature does not apply to this alternative phase retrieval technique. However, further development is necessary to overcome experimental challenges posed by this method which would enable mainstream or even clinical application of PCCT.

RESOLFT nanoscopy with photoswitchable organic fluorophores

NASA Astrophysics Data System (ADS)

Kwon, Jiwoong; Hwang, Jihee; Park, Jaewan; Han, Gi Rim; Han, Kyu Young; Kim, Seong Keun

2015-12-01

Far-field optical nanoscopy has been widely used to image small objects with sub-diffraction-limit spatial resolution. Particularly, reversible saturable optical fluorescence transition (RESOLFT) nanoscopy with photoswitchable fluorescent proteins is a powerful method for super-resolution imaging of living cells with low light intensity. Here we demonstrate for the first time the implementation of RESOLFT nanoscopy for a biological system using organic fluorophores, which are smaller in size and easier to be chemically modified. With a covalently-linked dye pair of Cy3 and Alexa647 to label subcellular structures in fixed cells and by optimizing the imaging buffer and optical parameters, our RESOLFT nanoscopy achieved a spatial resolution of ~74 nm in the focal plane. This method provides a powerful alternative for low light intensity RESOLFT nanoscopy, which enables biological imaging with small organic probes at nanoscale resolution.

Quantitative Frequency-Domain Passive Cavitation Imaging

PubMed Central

Haworth, Kevin J.; Bader, Kenneth B.; Rich, Kyle T.; Holland, Christy K.; Mast, T. Douglas

2017-01-01

Passive cavitation detection has been an instrumental technique for measuring cavitation dynamics, elucidating concomitant bioeffects, and guiding ultrasound therapies. Recently, techniques have been developed to create images of cavitation activity to provide investigators with a more complete set of information. These techniques use arrays to record and subsequently beamform received cavitation emissions, rather than processing emissions received on a single-element transducer. In this paper, the methods for performing frequency-domain delay, sum, and integrate passive imaging are outlined. The method can be applied to any passively acquired acoustic scattering or emissions, including cavitation emissions. In order to compare data across different systems, techniques for normalizing Fourier transformed data and converting the data to the acoustic energy received by the array are described. A discussion of hardware requirements and alternative imaging approaches are additionally outlined. Examples are provided in MATLAB. PMID:27992331

Joint estimation of high resolution images and depth maps from light field cameras

NASA Astrophysics Data System (ADS)

Ohashi, Kazuki; Takahashi, Keita; Fujii, Toshiaki

2014-03-01

Light field cameras are attracting much attention as tools for acquiring 3D information of a scene through a single camera. The main drawback of typical lenselet-based light field cameras is the limited resolution. This limitation comes from the structure where a microlens array is inserted between the sensor and the main lens. The microlens array projects 4D light field on a single 2D image sensor at the sacrifice of the resolution; the angular resolution and the position resolution trade-off under the fixed resolution of the image sensor. This fundamental trade-off remains after the raw light field image is converted to a set of sub-aperture images. The purpose of our study is to estimate a higher resolution image from low resolution sub-aperture images using a framework of super-resolution reconstruction. In this reconstruction, these sub-aperture images should be registered as accurately as possible. This registration is equivalent to depth estimation. Therefore, we propose a method where super-resolution and depth refinement are performed alternatively. Most of the process of our method is implemented by image processing operations. We present several experimental results using a Lytro camera, where we increased the resolution of a sub-aperture image by three times horizontally and vertically. Our method can produce clearer images compared to the original sub-aperture images and the case without depth refinement.

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

Di Domenico, Giovanni, E-mail: didomenico@fe.infn.it; Cardarelli, Paolo; Taibi, Angelo

Purpose: The quality of a radiography system is affected by several factors, a major one being the focal spot size of the x-ray tube. In fact, the measurement of such size is recognized to be of primary importance during acceptance tests and image quality evaluations of clinical radiography systems. The most common device providing an image of the focal spot emission distribution is a pin-hole camera, which requires a high tube loading in order to produce a measurable signal. This work introduces an alternative technique to obtain an image of the focal spot, through the processing of a single radiographmore » of a simple test object, acquired with a suitable magnification. Methods: The radiograph of a magnified sharp edge is a well-established method to evaluate the extension of the focal spot profile along the direction perpendicular to the edge. From a single radiograph of a circular x-ray absorber, it is possible to extract simultaneously the radial profiles of several sharp edges with different orientations. The authors propose a technique that allows to obtain an image of the focal spot through the processing of these radial profiles by means of a pseudo-CT reconstruction technique. In order to validate this technique, the reconstruction has been applied to the simulated radiographs of an ideal disk-shaped absorber, generated by various simulated focal spot distributions. Furthermore, the method has been applied to the focal spot of a commercially available mammography unit. Results: In the case of simulated radiographs, the results of the reconstructions have been compared to the original distributions, showing an excellent agreement for what regards both the overall distribution and the full width at half maximum measurements. In the case of the experimental test, the method allowed to obtain images of the focal spot that have been compared with the results obtained through standard techniques, namely, pin-hole camera and slit camera. Conclusions: The method was proven to be effective for simulated images and the results of the experimental test suggest that it could be considered as an alternative technique for focal spot distribution evaluation. The method offers the possibility to measure the actual focal spot size and emission distribution at the same exposure conditions as clinical routine, avoiding high tube loading as in the case of the pin-hole imaging technique.« less

Recent Advances in Microwave Imaging for Breast Cancer Detection

PubMed Central

Kwon, Sollip

2016-01-01

Breast cancer is a disease that occurs most often in female cancer patients. Early detection can significantly reduce the mortality rate. Microwave breast imaging, which is noninvasive and harmless to human, offers a promising alternative method to mammography. This paper presents a review of recent advances in microwave imaging for breast cancer detection. We conclude by introducing new research on a microwave imaging system with time-domain measurement that achieves short measurement time and low system cost. In the time-domain measurement system, scan time would take less than 1 sec, and it does not require very expensive equipment such as VNA. PMID:28096808

Robust w-Estimators for Cryo-EM Class Means

PubMed Central

Huang, Chenxi; Tagare, Hemant D.

2016-01-01

A critical step in cryogenic electron microscopy (cryo-EM) image analysis is to calculate the average of all images aligned to a projection direction. This average, called the “class mean”, improves the signal-to-noise ratio in single particle reconstruction (SPR). The averaging step is often compromised because of outlier images of ice, contaminants, and particle fragments. Outlier detection and rejection in the majority of current cryo-EM methods is done using cross-correlation with a manually determined threshold. Empirical assessment shows that the performance of these methods is very sensitive to the threshold. This paper proposes an alternative: a “w-estimator” of the average image, which is robust to outliers and which does not use a threshold. Various properties of the estimator, such as consistency and influence function are investigated. An extension of the estimator to images with different contrast transfer functions (CTFs) is also provided. Experiments with simulated and real cryo-EM images show that the proposed estimator performs quite well in the presence of outliers. PMID:26841397

Robust w-Estimators for Cryo-EM Class Means.

PubMed

Huang, Chenxi; Tagare, Hemant D

2016-02-01

A critical step in cryogenic electron microscopy (cryo-EM) image analysis is to calculate the average of all images aligned to a projection direction. This average, called the class mean, improves the signal-to-noise ratio in single-particle reconstruction. The averaging step is often compromised because of the outlier images of ice, contaminants, and particle fragments. Outlier detection and rejection in the majority of current cryo-EM methods are done using cross-correlation with a manually determined threshold. Empirical assessment shows that the performance of these methods is very sensitive to the threshold. This paper proposes an alternative: a w-estimator of the average image, which is robust to outliers and which does not use a threshold. Various properties of the estimator, such as consistency and influence function are investigated. An extension of the estimator to images with different contrast transfer functions is also provided. Experiments with simulated and real cryo-EM images show that the proposed estimator performs quite well in the presence of outliers.

Infrared and visible image fusion based on total variation and augmented Lagrangian.

PubMed

Guo, Hanqi; Ma, Yong; Mei, Xiaoguang; Ma, Jiayi

2017-11-01

This paper proposes a new algorithm for infrared and visible image fusion based on gradient transfer that achieves fusion by preserving the intensity of the infrared image and then transferring gradients in the corresponding visible one to the result. The gradient transfer suffers from the problems of low dynamic range and detail loss because it ignores the intensity from the visible image. The new algorithm solves these problems by providing additive intensity from the visible image to balance the intensity between the infrared image and the visible one. It formulates the fusion task as an l 1 -l 1 -TV minimization problem and then employs variable splitting and augmented Lagrangian to convert the unconstrained problem to a constrained one that can be solved in the framework of alternating the multiplier direction method. Experiments demonstrate that the new algorithm achieves better fusion results with a high computation efficiency in both qualitative and quantitative tests than gradient transfer and most state-of-the-art methods.

Determination of toxigenic fungi and aflatoxins in nuts and dried fruits using imaging and spectroscopic techniques.

PubMed

Wu, Qifang; Xie, Lijuan; Xu, Huirong

2018-06-30

Nuts and dried fruits contain rich nutrients and are thus highly vulnerable to contamination with toxigenic fungi and aflatoxins because of poor weather, processing and storage conditions. Imaging and spectroscopic techniques have proven to be potential alternative tools to wet chemistry methods for efficient and non-destructive determination of contamination with fungi and toxins. Thus, this review provides an overview of the current developments and applications in frequently used food safety testing techniques, including near infrared spectroscopy (NIRS), mid-infrared spectroscopy (MIRS), conventional imaging techniques (colour imaging (CI) and hyperspectral imaging (HSI)), and fluorescence spectroscopy and imaging (FS/FI). Interesting classification and determination results can be found in both static and on/in-line real-time detection for contaminated nuts and dried fruits. Although these techniques offer many benefits over conventional methods, challenges remain in terms of heterogeneous distribution of toxins, background constituent interference, model robustness, detection limits, sorting efficiency, as well as instrument development. Copyright © 2018 Elsevier Ltd. All rights reserved.

Region growing using superpixels with learned shape prior

NASA Astrophysics Data System (ADS)

Borovec, Jiří; Kybic, Jan; Sugimoto, Akihiro

2017-11-01

Region growing is a classical image segmentation method based on hierarchical region aggregation using local similarity rules. Our proposed method differs from classical region growing in three important aspects. First, it works on the level of superpixels instead of pixels, which leads to a substantial speed-up. Second, our method uses learned statistical shape properties that encourage plausible shapes. In particular, we use ray features to describe the object boundary. Third, our method can segment multiple objects and ensure that the segmentations do not overlap. The problem is represented as an energy minimization and is solved either greedily or iteratively using graph cuts. We demonstrate the performance of the proposed method and compare it with alternative approaches on the task of segmenting individual eggs in microscopy images of Drosophila ovaries.

Video Image Tracking Engine

NASA Technical Reports Server (NTRS)

Howard, Richard T. (Inventor); Bryan, ThomasC. (Inventor); Book, Michael L. (Inventor)

2004-01-01

A method and system for processing an image including capturing an image and storing the image as image pixel data. Each image pixel datum is stored in a respective memory location having a corresponding address. Threshold pixel data is selected from the image pixel data and linear spot segments are identified from the threshold pixel data selected.. Ihe positions of only a first pixel and a last pixel for each linear segment are saved. Movement of one or more objects are tracked by comparing the positions of fust and last pixels of a linear segment present in the captured image with respective first and last pixel positions in subsequent captured images. Alternatively, additional data for each linear data segment is saved such as sum of pixels and the weighted sum of pixels i.e., each threshold pixel value is multiplied by that pixel's x-location).

Psychophysical Reverse Correlation with Multiple Response Alternatives

ERIC Educational Resources Information Center

Dai, Huanping; Micheyl, Christophe

2010-01-01

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

Magnetic resonance neurography and diffusion tensor imaging: origins, history, and clinical impact of the first 50,000 cases with an assessment of efficacy and utility in a prospective 5000-patient study group.

PubMed

Filler, Aaron

2009-10-01

Methods were invented that made it possible to image peripheral nerves in the body and to image neural tracts in the brain. The history, physical basis, and dyadic tensor concept underlying the methods are reviewed. Over a 15-year period, these techniques-magnetic resonance neurography (MRN) and diffusion tensor imaging-were deployed in the clinical and research community in more than 2500 published research reports and applied to approximately 50,000 patients. Within this group, approximately 5000 patients having MRN were carefully tracked on a prospective basis. A uniform Neurography imaging methodology was applied in the study group, and all images were reviewed and registered by referral source, clinical indication, efficacy of imaging, and quality. Various classes of image findings were identified and subjected to a variety of small targeted prospective outcome studies. Those findings demonstrated to be clinically significant were then tracked in the larger clinical volume data set. MRN demonstrates mechanical distortion of nerves, hyperintensity consistent with nerve irritation, nerve swelling, discontinuity, relations of nerves to masses, and image features revealing distortion of nerves at entrapment points. These findings are often clinically relevant and warrant full consideration in the diagnostic process. They result in specific pathological diagnoses that are comparable to electrodiagnostic testing in clinical efficacy. A review of clinical outcome studies with diffusion tensor imaging also shows convincing utility. MRN and diffusion tensor imaging neural tract imaging have been validated as indispensable clinical diagnostic methods that provide reliable anatomic pathological information. There is no alternative diagnostic method in many situations. With the elapsing of 15 years, tens of thousands of imaging studies, and thousands of publications, these methods should no longer be considered experimental.

The challenges of studying visual expertise in medical image diagnosis.

PubMed

Gegenfurtner, Andreas; Kok, Ellen; van Geel, Koos; de Bruin, Anique; Jarodzka, Halszka; Szulewski, Adam; van Merriënboer, Jeroen Jg

2017-01-01

Visual expertise is the superior visual skill shown when executing domain-specific visual tasks. Understanding visual expertise is important in order to understand how the interpretation of medical images may be best learned and taught. In the context of this article, we focus on the visual skill of medical image diagnosis and, more specifically, on the methodological set-ups routinely used in visual expertise research. We offer a critique of commonly used methods and propose three challenges for future research to open up new avenues for studying characteristics of visual expertise in medical image diagnosis. The first challenge addresses theory development. Novel prospects in modelling visual expertise can emerge when we reflect on cognitive and socio-cultural epistemologies in visual expertise research, when we engage in statistical validations of existing theoretical assumptions and when we include social and socio-cultural processes in expertise development. The second challenge addresses the recording and analysis of longitudinal data. If we assume that the development of expertise is a long-term phenomenon, then it follows that future research can engage in advanced statistical modelling of longitudinal expertise data that extends the routine use of cross-sectional material through, for example, animations and dynamic visualisations of developmental data. The third challenge addresses the combination of methods. Alternatives to current practices can integrate qualitative and quantitative approaches in mixed-method designs, embrace relevant yet underused data sources and understand the need for multidisciplinary research teams. Embracing alternative epistemological and methodological approaches for studying visual expertise can lead to a more balanced and robust future for understanding superior visual skills in medical image diagnosis as well as other medical fields. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

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.

Blind retrospective motion correction of MR images.

PubMed

Loktyushin, Alexander; Nickisch, Hannes; Pohmann, Rolf; Schölkopf, Bernhard

2013-12-01

Subject motion can severely degrade MR images. A retrospective motion correction algorithm, Gradient-based motion correction, which significantly reduces ghosting and blurring artifacts due to subject motion was proposed. The technique uses the raw data of standard imaging sequences; no sequence modifications or additional equipment such as tracking devices are required. Rigid motion is assumed. The approach iteratively searches for the motion trajectory yielding the sharpest image as measured by the entropy of spatial gradients. The vast space of motion parameters is efficiently explored by gradient-based optimization with a convergence guarantee. The method has been evaluated on both synthetic and real data in two and three dimensions using standard imaging techniques. MR images are consistently improved over different kinds of motion trajectories. Using a graphics processing unit implementation, computation times are in the order of a few minutes for a full three-dimensional volume. The presented technique can be an alternative or a complement to prospective motion correction methods and is able to improve images with strong motion artifacts from standard imaging sequences without requiring additional data. Copyright © 2013 Wiley Periodicals, Inc., a Wiley company.

Metal-induced streak artifact reduction using iterative reconstruction algorithms in x-ray computed tomography image of the dentoalveolar region.

PubMed

Dong, Jian; Hayakawa, Yoshihiko; Kannenberg, Sven; Kober, Cornelia

2013-02-01

The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.

Four-dimensional MRI using an internal respiratory surrogate derived by dimensionality reduction

NASA Astrophysics Data System (ADS)

Uh, Jinsoo; Ayaz Khan, M.; Hua, Chiaho

2016-11-01

This study aimed to develop a practical and accurate 4-dimensional (4D) magnetic resonance imaging (MRI) method using a non-navigator, image-based internal respiratory surrogate derived by dimensionality reduction (DR). The use of DR has been previously suggested but not implemented for reconstructing 4D MRI, despite its practical advantages. We compared multiple image-acquisition schemes and refined a retrospective-sorting process to optimally implement a DR-derived surrogate. The comparison included an unconventional scheme that acquires paired slices alternately to mitigate the internal surrogate’s dependency on a specific slice location. We introduced ‘target-oriented sorting’, as opposed to conventional binning, to quantify the coherence in retrospectively sorted images, thereby determining the minimal scan time needed for sufficient coherence. This study focused on evaluating the proposed method using digital phantoms which provided unequivocal gold standard. The evaluation indicated that the DR-based respiratory surrogate is highly accurate: the error in amplitude percentile of the surrogate signal was less than 5% with the optimal scheme. Acquiring alternating paired slices was superior to the conventional scheme of acquiring individual slices; the advantage of the unconventional scheme was more pronounced when a substantial phase shift occurred across slice locations. The analysis of coherence across sorted images confirmed the advantage of higher sampling efficiencies in non-navigator respiratory surrogates. We determined that a scan time of 20 s per imaging slice was sufficient to achieve a mean coherence error of less than 1% for the tested respiratory patterns. The clinical applicability of the proposed 4D MRI has been demonstrated with volunteers and patients. The diaphragm motion in 4D MRI was consistent with that in dynamic 2D imaging which was regarded as the gold standard (difference within 1.8 mm on average).

Magnetic resonance imaging: A tool to monitor and optimize enzyme distribution during porcine pancreas distention for islet isolation

PubMed Central

Scott, WE; Weegman, BP; Balamurugan, AN; Ferrer-Fabrega, J; Anazawa, T; Karatzas, T; Jie, T; Hammer, BE; Matsumoto, S; Avgoustiniatos, ES; Maynard, KS; Sutherland, DER; Hering, BJ; Papas, KK

2014-01-01

Background Porcine islet xenotransplantation is emerging as a potential alternative for allogeneic clinical islet transplantation. Optimization of porcine islet isolation in terms of yield and quality is critical for the success and cost effectiveness of this approach. Incomplete pancreas distension and inhomogeneous enzyme distribution have been identified as key factors for limiting viable islet yield per porcine pancreas. The aim of this study was to explore the utility of Magnetic Resonance Imaging (MRI) as a tool to investigate the homogeneity of enzyme delivery in porcine pancreata. Traditional and novel methods for enzyme delivery aimed at optimizing enzyme distribution were examined. Methods Pancreata were procured from Landrace pigs via en bloc viscerectomy. The main pancreatic duct was then cannulated with an 18g winged catheter and MRI performed at 1.5 T. Images were collected before and after ductal infusion of chilled MRI contrast agent (gadolinium) in physiological saline. Results Regions of the distal aspect of the splenic lobe and portions of the connecting lobe and bridge exhibited reduced delivery of solution when traditional methods of distension were utilized. Use of alternative methods of delivery (such as selective re-cannulation and distension of identified problem regions) resolved these issues and MRI was successfully utilized as a guide and assessment tool for improved delivery. Conclusion Current methods of porcine pancreas distension do not consistently deliver enzyme uniformly or adequately to all regions of the pancreas. Novel methods of enzyme delivery should be investigated and implemented for improved enzyme distribution. MRI serves as a valuable tool to visualize and evaluate the efficacy of current and prospective methods of pancreas distension and enzyme delivery. PMID:24986758

Adaptive correction procedure for TVL1 image deblurring under impulse noise

NASA Astrophysics Data System (ADS)

Bai, Minru; Zhang, Xiongjun; Shao, Qianqian

2016-08-01

For the problem of image restoration of observed images corrupted by blur and impulse noise, the widely used TVL1 model may deviate from both the data-acquisition model and the prior model, especially for high noise levels. In order to seek a solution of high recovery quality beyond the reach of the TVL1 model, we propose an adaptive correction procedure for TVL1 image deblurring under impulse noise. Then, a proximal alternating direction method of multipliers (ADMM) is presented to solve the corrected TVL1 model and its convergence is also established under very mild conditions. It is verified by numerical experiments that our proposed approach outperforms the TVL1 model in terms of signal-to-noise ratio (SNR) values and visual quality, especially for high noise levels: it can handle salt-and-pepper noise as high as 90% and random-valued noise as high as 70%. In addition, a comparison with a state-of-the-art method, the two-phase method, demonstrates the superiority of the proposed approach.

Bayer Demosaicking with Polynomial Interpolation.

PubMed

Wu, Jiaji; Anisetti, Marco; Wu, Wei; Damiani, Ernesto; Jeon, Gwanggil

2016-08-30

Demosaicking is a digital image process to reconstruct full color digital images from incomplete color samples from an image sensor. It is an unavoidable process for many devices incorporating camera sensor (e.g. mobile phones, tablet, etc.). In this paper, we introduce a new demosaicking algorithm based on polynomial interpolation-based demosaicking (PID). Our method makes three contributions: calculation of error predictors, edge classification based on color differences, and a refinement stage using a weighted sum strategy. Our new predictors are generated on the basis of on the polynomial interpolation, and can be used as a sound alternative to other predictors obtained by bilinear or Laplacian interpolation. In this paper we show how our predictors can be combined according to the proposed edge classifier. After populating three color channels, a refinement stage is applied to enhance the image quality and reduce demosaicking artifacts. Our experimental results show that the proposed method substantially improves over existing demosaicking methods in terms of objective performance (CPSNR, S-CIELAB E, and FSIM), and visual performance.

Machine learning techniques for medical diagnosis of diabetes using iris images.

PubMed

Samant, Piyush; Agarwal, Ravinder

2018-04-01

Complementary and alternative medicine techniques have shown their potential for the treatment and diagnosis of chronical diseases like diabetes, arthritis etc. On the same time digital image processing techniques for disease diagnosis is reliable and fastest growing field in biomedical. Proposed model is an attempt to evaluate diagnostic validity of an old complementary and alternative medicine technique, iridology for diagnosis of type-2 diabetes using soft computing methods. Investigation was performed over a close group of total 338 subjects (180 diabetic and 158 non-diabetic). Infra-red images of both the eyes were captured simultaneously. The region of interest from the iris image was cropped as zone corresponds to the position of pancreas organ according to the iridology chart. Statistical, texture and discrete wavelength transformation features were extracted from the region of interest. The results show best classification accuracy of 89.63% calculated from RF classifier. Maximum specificity and sensitivity were absorbed as 0.9687 and 0.988, respectively. Results have revealed the effectiveness and diagnostic significance of proposed model for non-invasive and automatic diabetes diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.

Learning to rank using user clicks and visual features for image retrieval.

PubMed

Yu, Jun; Tao, Dacheng; Wang, Meng; Rui, Yong

2015-04-01

The inconsistency between textual features and visual contents can cause poor image search results. To solve this problem, click features, which are more reliable than textual information in justifying the relevance between a query and clicked images, are adopted in image ranking model. However, the existing ranking model cannot integrate visual features, which are efficient in refining the click-based search results. In this paper, we propose a novel ranking model based on the learning to rank framework. Visual features and click features are simultaneously utilized to obtain the ranking model. Specifically, the proposed approach is based on large margin structured output learning and the visual consistency is integrated with the click features through a hypergraph regularizer term. In accordance with the fast alternating linearization method, we design a novel algorithm to optimize the objective function. This algorithm alternately minimizes two different approximations of the original objective function by keeping one function unchanged and linearizing the other. We conduct experiments on a large-scale dataset collected from the Microsoft Bing image search engine, and the results demonstrate that the proposed learning to rank models based on visual features and user clicks outperforms state-of-the-art algorithms.

Assessing clutter reduction in parallel coordinates using image processing techniques

NASA Astrophysics Data System (ADS)

Alhamaydh, Heba; Alzoubi, Hussein; Almasaeid, Hisham

2018-01-01

Information visualization has appeared as an important research field for multidimensional data and correlation analysis in recent years. Parallel coordinates (PCs) are one of the popular techniques to visual high-dimensional data. A problem with the PCs technique is that it suffers from crowding, a clutter which hides important data and obfuscates the information. Earlier research has been conducted to reduce clutter without loss in data content. We introduce the use of image processing techniques as an approach for assessing the performance of clutter reduction techniques in PC. We use histogram analysis as our first measure, where the mean feature of the color histograms of the possible alternative orderings of coordinates for the PC images is calculated and compared. The second measure is the extracted contrast feature from the texture of PC images based on gray-level co-occurrence matrices. The results show that the best PC image is the one that has the minimal mean value of the color histogram feature and the maximal contrast value of the texture feature. In addition to its simplicity, the proposed assessment method has the advantage of objectively assessing alternative ordering of PC visualization.

Cellular neural networks, the Navier-Stokes equation, and microarray image reconstruction.

PubMed

Zineddin, Bachar; Wang, Zidong; Liu, Xiaohui

2011-11-01

Although the last decade has witnessed a great deal of improvements achieved for the microarray technology, many major developments in all the main stages of this technology, including image processing, are still needed. Some hardware implementations of microarray image processing have been proposed in the literature and proved to be promising alternatives to the currently available software systems. However, the main drawback of those proposed approaches is the unsuitable addressing of the quantification of the gene spot in a realistic way without any assumption about the image surface. Our aim in this paper is to present a new image-reconstruction algorithm using the cellular neural network that solves the Navier-Stokes equation. This algorithm offers a robust method for estimating the background signal within the gene-spot region. The MATCNN toolbox for Matlab is used to test the proposed method. Quantitative comparisons are carried out, i.e., in terms of objective criteria, between our approach and some other available methods. It is shown that the proposed algorithm gives highly accurate and realistic measurements in a fully automated manner within a remarkably efficient time.

Kriging in the Shadows: Geostatistical Interpolation for Remote Sensing

NASA Technical Reports Server (NTRS)

Rossi, Richard E.; Dungan, Jennifer L.; Beck, Louisa R.

1994-01-01

It is often useful to estimate obscured or missing remotely sensed data. Traditional interpolation methods, such as nearest-neighbor or bilinear resampling, do not take full advantage of the spatial information in the image. An alternative method, a geostatistical technique known as indicator kriging, is described and demonstrated using a Landsat Thematic Mapper image in southern Chiapas, Mexico. The image was first classified into pasture and nonpasture land cover. For each pixel that was obscured by cloud or cloud shadow, the probability that it was pasture was assigned by the algorithm. An exponential omnidirectional variogram model was used to characterize the spatial continuity of the image for use in the kriging algorithm. Assuming a cutoff probability level of 50%, the error was shown to be 17% with no obvious spatial bias but with some tendency to categorize nonpasture as pasture (overestimation). While this is a promising result, the method's practical application in other missing data problems for remotely sensed images will depend on the amount and spatial pattern of the unobscured pixels and missing pixels and the success of the spatial continuity model used.

A Bayesian Framework for Human Body Pose Tracking from Depth Image Sequences

PubMed Central

Zhu, Youding; Fujimura, Kikuo

2010-01-01

This paper addresses the problem of accurate and robust tracking of 3D human body pose from depth image sequences. Recovering the large number of degrees of freedom in human body movements from a depth image sequence is challenging due to the need to resolve the depth ambiguity caused by self-occlusions and the difficulty to recover from tracking failure. Human body poses could be estimated through model fitting using dense correspondences between depth data and an articulated human model (local optimization method). Although it usually achieves a high accuracy due to dense correspondences, it may fail to recover from tracking failure. Alternately, human pose may be reconstructed by detecting and tracking human body anatomical landmarks (key-points) based on low-level depth image analysis. While this method (key-point based method) is robust and recovers from tracking failure, its pose estimation accuracy depends solely on image-based localization accuracy of key-points. To address these limitations, we present a flexible Bayesian framework for integrating pose estimation results obtained by methods based on key-points and local optimization. Experimental results are shown and performance comparison is presented to demonstrate the effectiveness of the proposed approach. PMID:22399933

Multiple Representations-Based Face Sketch-Photo Synthesis.

PubMed

Peng, Chunlei; Gao, Xinbo; Wang, Nannan; Tao, Dacheng; Li, Xuelong; Li, Jie

2016-11-01

Face sketch-photo synthesis plays an important role in law enforcement and digital entertainment. Most of the existing methods only use pixel intensities as the feature. Since face images can be described using features from multiple aspects, this paper presents a novel multiple representations-based face sketch-photo-synthesis method that adaptively combines multiple representations to represent an image patch. In particular, it combines multiple features from face images processed using multiple filters and deploys Markov networks to exploit the interacting relationships between the neighboring image patches. The proposed framework could be solved using an alternating optimization strategy and it normally converges in only five outer iterations in the experiments. Our experimental results on the Chinese University of Hong Kong (CUHK) face sketch database, celebrity photos, CUHK Face Sketch FERET Database, IIIT-D Viewed Sketch Database, and forensic sketches demonstrate the effectiveness of our method for face sketch-photo synthesis. In addition, cross-database and database-dependent style-synthesis evaluations demonstrate the generalizability of this novel method and suggest promising solutions for face identification in forensic science.

Multi-test cervical cancer diagnosis with missing data estimation

NASA Astrophysics Data System (ADS)

Xu, Tao; Huang, Xiaolei; Kim, Edward; Long, L. Rodney; Antani, Sameer

2015-03-01

Cervical cancer is a leading most common type of cancer for women worldwide. Existing screening programs for cervical cancer suffer from low sensitivity. Using images of the cervix (cervigrams) as an aid in detecting pre-cancerous changes to the cervix has good potential to improve sensitivity and help reduce the number of cervical cancer cases. In this paper, we present a method that utilizes multi-modality information extracted from multiple tests of a patient's visit to classify the patient visit to be either low-risk or high-risk. Our algorithm integrates image features and text features to make a diagnosis. We also present two strategies to estimate the missing values in text features: Image Classifier Supervised Mean Imputation (ICSMI) and Image Classifier Supervised Linear Interpolation (ICSLI). We evaluate our method on a large medical dataset and compare it with several alternative approaches. The results show that the proposed method with ICSLI strategy achieves the best result of 83.03% specificity and 76.36% sensitivity. When higher specificity is desired, our method can achieve 90% specificity with 62.12% sensitivity.

Characterization of controlled bone defects using 2D and 3D ultrasound imaging techniques.

PubMed

Parmar, Biren J; Longsine, Whitney; Sabonghy, Eric P; Han, Arum; Tasciotti, Ennio; Weiner, Bradley K; Ferrari, Mauro; Righetti, Raffaella

2010-08-21

Ultrasound is emerging as an attractive alternative modality to standard x-ray and CT methods for bone assessment applications. As of today, however, there is a lack of systematic studies that investigate the performance of diagnostic ultrasound techniques in bone imaging applications. This study aims at understanding the performance limitations of new ultrasound techniques for imaging bones in controlled experiments in vitro. Experiments are performed on samples of mammalian and non-mammalian bones with controlled defects with size ranging from 400 microm to 5 mm. Ultrasound findings are statistically compared with those obtained from the same samples using standard x-ray imaging modalities and optical microscopy. The results of this study demonstrate that it is feasible to use diagnostic ultrasound imaging techniques to assess sub-millimeter bone defects in real time and with high accuracy and precision. These results also demonstrate that ultrasound imaging techniques perform comparably better than x-ray imaging and optical imaging methods, in the assessment of a wide range of controlled defects both in mammalian and non-mammalian bones. In the future, ultrasound imaging techniques might provide a cost-effective, real-time, safe and portable diagnostic tool for bone imaging applications.

Quantification of right ventricular volumes and function by real time three-dimensional echocardiographic longitudinal axial plane method: validation in the clinical setting.

PubMed

Endo, Yuka; Maddukuri, Prasad V; Vieira, Marcelo L C; Pandian, Natesa G; Patel, Ayan R

2006-11-01

Measurement of right ventricular (RV) volumes and right ventricular ejection fraction (RVEF) by three-dimensional echocardiographic (3DE) short-axis disc summation method has been validated in multiple studies. However, in some patients, short-axis images are of insufficient quality for accurate tracing of the RV endocardial border. This study examined the accuracy of long-axis analysis in multiple planes (longitudinal axial plane method) for assessment of RV volumes and RVEF. 3DE images were analyzed in 40 subjects with a broad range of RV function. RV end-diastolic (RVEDV) and end-systolic volumes (RVESV) and RVEF were calculated by both short-axis disc summation method and longitudinal axial plane method. Excellent correlation was obtained between the two methods for RVEDV, RVESV, and RVEF (r = 0.99, 0.99, 0.94, respectively; P < 0.0001 for all comparisons). 3DE longitudinal-axis analysis is a promising technique for the evaluation of RV function, and may provide an alternative method of assessment in patients with suboptimal short-axis images.

Using trainable segmentation and watershed transform for identifying unilocular and multilocular cysts from ultrasound images of ovarian tumour

NASA Astrophysics Data System (ADS)

Ibrahim, Dheyaa Ahmed; Al-Assam, Hisham; Du, Hongbo; Jassim, Sabah

2017-05-01

Ovarian masses are categorised into different types of malignant and benign. In order to optimize patient treatment, it is necessary to carry out pre-operational characterisation of the suspect ovarian mass to determine its category. Ultrasound imaging has been widely used in differentiating malignant from benign cases due to its safe and non-intrusive nature, and can be used for determining the number of cysts in the ovary. Presently, the gynaecologist is tasked with manually counting the number of cysts shown on the ultrasound image. This paper proposes, a new approach that automatically segments the ovarian masses and cysts from a static B-mode image. Initially, the method uses a trainable segmentation procedure and a trained neural network classifier to accurately identify the position of the masses and cysts. After that, the borders of the masses can be appraised using watershed transform. The effectiveness of the proposed method has been tested by comparing the number of cysts identified by the method against the manual examination by a gynaecologist. A total of 65 ultrasound images were used for the comparison, and the results showed that the proposed solution is a viable alternative to the manual counting method for accurately determining the number of cysts in a US ovarian image.

Accelerated Edge-Preserving Image Restoration Without Boundary Artifacts

PubMed Central

Matakos, Antonios; Ramani, Sathish; Fessler, Jeffrey A.

2013-01-01

To reduce blur in noisy images, regularized image restoration methods have been proposed that use non-quadratic regularizers (like l1 regularization or total-variation) that suppress noise while preserving edges in the image. Most of these methods assume a circulant blur (periodic convolution with a blurring kernel) that can lead to wraparound artifacts along the boundaries of the image due to the implied periodicity of the circulant model. Using a non-circulant model could prevent these artifacts at the cost of increased computational complexity. In this work we propose to use a circulant blur model combined with a masking operator that prevents wraparound artifacts. The resulting model is non-circulant, so we propose an efficient algorithm using variable splitting and augmented Lagrangian (AL) strategies. Our variable splitting scheme, when combined with the AL framework and alternating minimization, leads to simple linear systems that can be solved non-iteratively using FFTs, eliminating the need for more expensive CG-type solvers. The proposed method can also efficiently tackle a variety of convex regularizers including edge-preserving (e.g., total-variation) and sparsity promoting (e.g., l1 norm) regularizers. Simulation results show fast convergence of the proposed method, along with improved image quality at the boundaries where the circulant model is inaccurate. PMID:23372080

Correlative Imaging of Fluorescent Proteins in Resin-Embedded Plant Material1

PubMed Central

Bell, Karen; Mitchell, Steve; Paultre, Danae; Posch, Markus; Oparka, Karl

2013-01-01

Fluorescent proteins (FPs) were developed for live-cell imaging and have revolutionized cell biology. However, not all plant tissues are accessible to live imaging using confocal microscopy, necessitating alternative approaches for protein localization. An example is the phloem, a tissue embedded deep within plant organs and sensitive to damage. To facilitate accurate localization of FPs within recalcitrant tissues, we developed a simple method for retaining FPs after resin embedding. This method is based on low-temperature fixation and dehydration, followed by embedding in London Resin White, and avoids the need for cryosections. We show that a palette of FPs can be localized in plant tissues while retaining good structural cell preservation, and that the polymerized block face can be counterstained with cell wall probes. Using this method we have been able to image green fluorescent protein-labeled plasmodesmata to a depth of more than 40 μm beneath the resin surface. Using correlative light and electron microscopy of the phloem, we were able to locate the same FP-labeled sieve elements in semithin and ultrathin sections. Sections were amenable to antibody labeling, and allowed a combination of confocal and superresolution imaging (three-dimensional-structured illumination microscopy) on the same cells. These correlative imaging methods should find several uses in plant cell biology. PMID:23457228

Measurement of charge transfer potential barrier in pinned photodiode CMOS image sensors

NASA Astrophysics Data System (ADS)

Chen, Cao; Bing, Zhang; Junfeng, Wang; Longsheng, Wu

2016-05-01

The charge transfer potential barrier (CTPB) formed beneath the transfer gate causes a noticeable image lag issue in pinned photodiode (PPD) CMOS image sensors (CIS), and is difficult to measure straightforwardly since it is embedded inside the device. From an understanding of the CTPB formation mechanism, we report on an alternative method to feasibly measure the CTPB height by performing a linear extrapolation coupled with a horizontal left-shift on the sensor photoresponse curve under the steady-state illumination. The theoretical study was performed in detail on the principle of the proposed method. Application of the measurements on a prototype PPD-CIS chip with an array of 160 × 160 pixels is demonstrated. Such a method intends to shine new light on the guidance for the lag-free and high-speed sensors optimization based on PPD devices. Project supported by the National Defense Pre-Research Foundation of China (No. 51311050301095).

Sensory Interactive Teleoperator Robotic Grasping

NASA Technical Reports Server (NTRS)

Alark, Keli; Lumia, Ron

1997-01-01

As the technological world strives for efficiency, the need for economical equipment that increases operator proficiency in minimal time is fundamental. This system links a CCD camera, a controller and a robotic arm to a computer vision system to provide an alternative method of image analysis. The machine vision system which was employed possesses software tools for acquiring and analyzing images which are received through a CCD camera. After feature extraction on the object in the image was performed, information about the object's location, orientation and distance from the robotic gripper is sent to the robot controller so that the robot can manipulate the object.

Dynamic scan control in STEM: Spiral scans

DOE PAGES

Lupini, Andrew R.; Borisevich, Albina Y.; Kalinin, Sergei V.; ...

2016-06-13

Here, scanning transmission electron microscopy (STEM) has emerged as one of the foremost techniques to analyze materials at atomic resolution. However, two practical difficulties inherent to STEM imaging are: radiation damage imparted by the electron beam, which can potentially damage or otherwise modify the specimen and slow-scan image acquisition, which limits the ability to capture dynamic changes at high temporal resolution. Furthermore, due in part to scan flyback corrections, typical raster scan methods result in an uneven distribution of dose across the scanned area. A method to allow extremely fast scanning with a uniform residence time would enable imaging atmore » low electron doses, ameliorating radiation damage and at the same time permitting image acquisition at higher frame-rates while maintaining atomic resolution. The practical complication is that rastering the STEM probe at higher speeds causes significant image distortions. Non-square scan patterns provide a solution to this dilemma and can be tailored for low dose imaging conditions. Here, we develop a method for imaging with alternative scan patterns and investigate their performance at very high scan speeds. A general analysis for spiral scanning is presented here for the following spiral scan functions: Archimedean, Fermat, and constant linear velocity spirals, which were tested for STEM imaging. The quality of spiral scan STEM images is generally comparable with STEM images from conventional raster scans, and the dose uniformity can be improved.« less

Exploring the feasibility of iris recognition for visible spectrum iris images obtained using smartphone camera

NASA Astrophysics Data System (ADS)

Trokielewicz, Mateusz; Bartuzi, Ewelina; Michowska, Katarzyna; Andrzejewska, Antonina; Selegrat, Monika

2015-09-01

In the age of modern, hyperconnected society that increasingly relies on mobile devices and solutions, implementing a reliable and accurate biometric system employing iris recognition presents new challenges. Typical biometric systems employing iris analysis require expensive and complicated hardware. We therefore explore an alternative way using visible spectrum iris imaging. This paper aims at answering several questions related to applying iris biometrics for images obtained in the visible spectrum using smartphone camera. Can irides be successfully and effortlessly imaged using a smartphone's built-in camera? Can existing iris recognition methods perform well when presented with such images? The main advantage of using near-infrared (NIR) illumination in dedicated iris recognition cameras is good performance almost independent of the iris color and pigmentation. Are the images obtained from smartphone's camera of sufficient quality even for the dark irides? We present experiments incorporating simple image preprocessing to find the best visibility of iris texture, followed by a performance study to assess whether iris recognition methods originally aimed at NIR iris images perform well with visible light images. To our best knowledge this is the first comprehensive analysis of iris recognition performance using a database of high-quality images collected in visible light using the smartphones flashlight together with the application of commercial off-the-shelf (COTS) iris recognition methods.

Dynamic scan control in STEM: Spiral scans

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

Lupini, Andrew R.; Borisevich, Albina Y.; Kalinin, Sergei V.

Here, scanning transmission electron microscopy (STEM) has emerged as one of the foremost techniques to analyze materials at atomic resolution. However, two practical difficulties inherent to STEM imaging are: radiation damage imparted by the electron beam, which can potentially damage or otherwise modify the specimen and slow-scan image acquisition, which limits the ability to capture dynamic changes at high temporal resolution. Furthermore, due in part to scan flyback corrections, typical raster scan methods result in an uneven distribution of dose across the scanned area. A method to allow extremely fast scanning with a uniform residence time would enable imaging atmore » low electron doses, ameliorating radiation damage and at the same time permitting image acquisition at higher frame-rates while maintaining atomic resolution. The practical complication is that rastering the STEM probe at higher speeds causes significant image distortions. Non-square scan patterns provide a solution to this dilemma and can be tailored for low dose imaging conditions. Here, we develop a method for imaging with alternative scan patterns and investigate their performance at very high scan speeds. A general analysis for spiral scanning is presented here for the following spiral scan functions: Archimedean, Fermat, and constant linear velocity spirals, which were tested for STEM imaging. The quality of spiral scan STEM images is generally comparable with STEM images from conventional raster scans, and the dose uniformity can be improved.« less

Method of synthesis of abstract images with high self-similarity

NASA Astrophysics Data System (ADS)

Matveev, Nikolay V.; Shcheglov, Sergey A.; Romanova, Galina E.; Koneva, Ð.¢atiana A.

2017-06-01

Abstract images with high self-similarity could be used for drug-free stress therapy. This based on the fact that a complex visual environment has a high affective appraisal. To create such an image we can use the setup based on the three laser sources of small power and different colors (Red, Green, Blue), the image is the pattern resulting from the reflecting and refracting by the complicated form object placed into the laser ray paths. The images were obtained experimentally which showed the good therapy effect. However, to find and to choose the object which gives needed image structure is very difficult and requires many trials. The goal of the work is to develop a method and a procedure of finding the object form which if placed into the ray paths can provide the necessary structure of the image In fact the task means obtaining the necessary irradiance distribution on the given surface. Traditionally such problems are solved using the non-imaging optics methods. In the given case this task is very complicated because of the complicated structure of the illuminance distribution and its high non-linearity. Alternative way is to use the projected image of a mask with a given structure. We consider both ways and discuss how they can help to speed up the synthesis procedure for the given abstract image of the high self-similarity for the setups of drug-free therapy.

Image super-resolution via adaptive filtering and regularization

NASA Astrophysics Data System (ADS)

Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming

2014-11-01

Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.

Automatic correspondence detection in mammogram and breast tomosynthesis images

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Krüger, Julia; Bischof, Arpad; Barkhausen, Jörg; Handels, Heinz

2012-02-01

Two-dimensional mammography is the major imaging modality in breast cancer detection. A disadvantage of mammography is the projective nature of this imaging technique. Tomosynthesis is an attractive modality with the potential to combine the high contrast and high resolution of digital mammography with the advantages of 3D imaging. In order to facilitate diagnostics and treatment in the current clinical work-flow, correspondences between tomosynthesis images and previous mammographic exams of the same women have to be determined. In this paper, we propose a method to detect correspondences in 2D mammograms and 3D tomosynthesis images automatically. In general, this 2D/3D correspondence problem is ill-posed, because a point in the 2D mammogram corresponds to a line in the 3D tomosynthesis image. The goal of our method is to detect the "most probable" 3D position in the tomosynthesis images corresponding to a selected point in the 2D mammogram. We present two alternative approaches to solve this 2D/3D correspondence problem: a 2D/3D registration method and a 2D/2D mapping between mammogram and tomosynthesis projection images with a following back projection. The advantages and limitations of both approaches are discussed and the performance of the methods is evaluated qualitatively and quantitatively using a software phantom and clinical breast image data. Although the proposed 2D/3D registration method can compensate for moderate breast deformations caused by different breast compressions, this approach is not suitable for clinical tomosynthesis data due to the limited resolution and blurring effects perpendicular to the direction of projection. The quantitative results show that the proposed 2D/2D mapping method is capable of detecting corresponding positions in mammograms and tomosynthesis images automatically for 61 out of 65 landmarks. The proposed method can facilitate diagnosis, visual inspection and comparison of 2D mammograms and 3D tomosynthesis images for the physician.

A novel automated alternating current biosusceptometry method to characterization of controlled-release magnetic floating tablets of metronidazole.

PubMed

Ferrari, Priscileila Colerato; dos Santos Grossklauss, Dany Bruno Borella; Alvarez, Matheus; Paixão, Fabiano Carlos; Andreis, Uilian; Crispim, Alexandre Giordano; de Castro, Ana Dóris; Evangelista, Raul Cesar; de Arruda Miranda, José Ricardo

2014-08-01

Alternating Current Biosusceptometry is a magnetically method used to characterize drug delivery systems. This work presents a system composed by an automated ACB sensor to acquire magnetic images of floating tablets. The purpose of this study was to use an automated Alternating Current Biosusceptometry (ACB) to characterize magnetic floating tablets for controlled drug delivery. Floating tablets were prepared with hydroxypropyl methylcellulose (HPMC) as hydrophilic gel material, sodium bicarbonate as gas-generating agent and ferrite as magnetic marker. ACB was used to characterize the floating lag time and the tablet hydration rate, by quantification of the magnetic images to magnetic area. Besides the buoyancy, the floating tablets were evaluated for weight uniformity, hardness, swelling and in vitro drug release. The optimized tablets were prepared with equal amounts of HPMC and ferrite, and began to float within 4 min, maintaining the flotation during more than 24 h. The data of all physical parameters lied within the pharmacopeial limits. Drug release at 24 h was about 40%. The ACB results showed that this study provided a new approach for in vitro investigation of controlled-release dosage forms. Moreover, using automated ACB will also be possible to test these parameters in humans allowing to establish an in vitro.in vivo correlation (IVIVC).

Faxed document image restoration method based on local pixel patterns

NASA Astrophysics Data System (ADS)

Akiyama, Teruo; Miyamoto, Nobuo; Oguro, Masami; Ogura, Kenji

1998-04-01

A method for restoring degraded faxed document images using the patterns of pixels that construct small areas in a document is proposed. The method effectively restores faxed images that contain the halftone textures and/or density salt-and-pepper noise that degrade OCR system performance. The halftone image restoration process, white-centered 3 X 3 pixels, in which black-and-white pixels alternate, are identified first using the distribution of the pixel values as halftone textures, and then the white center pixels are inverted to black. To remove high-density salt- and-pepper noise, it is assumed that the degradation is caused by ill-balanced bias and inappropriate thresholding of the sensor output which results in the addition of random noise. Restored image can be estimated using an approximation that uses the inverse operation of the assumed original process. In order to process degraded faxed images, the algorithms mentioned above are combined. An experiment is conducted using 24 especially poor quality examples selected from data sets that exemplify what practical fax- based OCR systems cannot handle. The maximum recovery rate in terms of mean square error was 98.8 percent.

Temporal presentation protocols in stereoscopic displays: Flicker visibility, perceived motion, and perceived depth

PubMed Central

Hoffman, David M.; Karasev, Vasiliy I.; Banks, Martin S.

2011-01-01

Most stereoscopic displays rely on field-sequential presentation to present different images to the left and right eyes. With sequential presentation, images are delivered to each eye in alternation with dark intervals, and each eye receives its images in counter phase with the other eye. This type of presentation can exacerbate image artifacts including flicker, and the appearance of unsmooth motion. To address the flicker problem, some methods repeat images multiple times before updating to new ones. This greatly reduces flicker visibility, but makes motion appear less smooth. This paper describes an investigation of how different presentation methods affect the visibility of flicker, motion artifacts, and distortions in perceived depth. It begins with an examination of these methods in the spatio-temporal frequency domain. From this examination, it describes a series of predictions for how presentation rate, object speed, simultaneity of image delivery to the two eyes, and other properties ought to affect flicker, motion artifacts, and depth distortions, and reports a series of experiments that tested these predictions. The results confirmed essentially all of the predictions. The paper concludes with a summary and series of recommendations for the best approach to minimize these undesirable effects. PMID:21572544

Combining multiple thresholding binarization values to improve OCR output

NASA Astrophysics Data System (ADS)

Lund, William B.; Kennard, Douglas J.; Ringger, Eric K.

2013-01-01

For noisy, historical documents, a high optical character recognition (OCR) word error rate (WER) can render the OCR text unusable. Since image binarization is often the method used to identify foreground pixels, a body of research seeks to improve image-wide binarization directly. Instead of relying on any one imperfect binarization technique, our method incorporates information from multiple simple thresholding binarizations of the same image to improve text output. Using a new corpus of 19th century newspaper grayscale images for which the text transcription is known, we observe WERs of 13.8% and higher using current binarization techniques and a state-of-the-art OCR engine. Our novel approach combines the OCR outputs from multiple thresholded images by aligning the text output and producing a lattice of word alternatives from which a lattice word error rate (LWER) is calculated. Our results show a LWER of 7.6% when aligning two threshold images and a LWER of 6.8% when aligning five. From the word lattice we commit to one hypothesis by applying the methods of Lund et al. (2011) achieving an improvement over the original OCR output and a 8.41% WER result on this data set.

Bi-dimensional empirical mode decomposition based fringe-like pattern suppression in polarization interference imaging spectrometer

NASA Astrophysics Data System (ADS)

Ren, Wenyi; Cao, Qizhi; Wu, Dan; Jiang, Jiangang; Yang, Guoan; Xie, Yingge; Wang, Guodong; Zhang, Sheqi

2018-01-01

Many observers using interference imaging spectrometer were plagued by the fringe-like pattern(FP) that occurs for optical wavelengths in red and near-infrared region. It brings us more difficulties in the data processing such as the spectrum calibration, information retrieval, and so on. An adaptive method based on the bi-dimensional empirical mode decomposition was developed to suppress the nonlinear FP in polarization interference imaging spectrometer. The FP and corrected interferogram were separated effectively. Meanwhile, the stripes introduced by CCD mosaic was suppressed. The nonlinear interferogram background removal and the spectrum distortion correction were implemented as well. It provides us an alternative method to adaptively suppress the nonlinear FP without prior experimental data and knowledge. This approach potentially is a powerful tool in the fields of Fourier transform spectroscopy, holographic imaging, optical measurement based on moire fringe, etc.

Autofluorescence Imaging With Near-Infrared Excitation:Normalization by Reflectance to Reduce Signal From Choroidal Fluorophores

PubMed Central

Cideciyan, Artur V.; Swider, Malgorzata; Jacobson, Samuel G.

2015-01-01

Purpose. We previously developed reduced-illuminance autofluorescence imaging (RAFI) methods involving near-infrared (NIR) excitation to image melanin-based fluorophores and short-wavelength (SW) excitation to image lipofuscin-based flurophores. Here, we propose to normalize NIR-RAFI in order to increase the relative contribution of retinal pigment epithelium (RPE) fluorophores. Methods. Retinal imaging was performed with a standard protocol holding system parameters invariant in healthy subjects and in patients. Normalized NIR-RAFI was derived by dividing NIR-RAFI signal by NIR reflectance point-by-point after image registration. Results. Regions of RPE atrophy in Stargardt disease, AMD, retinitis pigmentosa, choroideremia, and Leber congenital amaurosis as defined by low signal on SW-RAFI could correspond to a wide range of signal on NIR-RAFI depending on the contribution from the choroidal component. Retinal pigment epithelium atrophy tended to always correspond to high signal on NIR reflectance. Normalizing NIR-RAFI reduced the choroidal component of the signal in regions of atrophy. Quantitative evaluation of RPE atrophy area showed no significant differences between SW-RAFI and normalized NIR-RAFI. Conclusions. Imaging of RPE atrophy using lipofuscin-based AF imaging has become the gold standard. However, this technique involves bright SW lights that are uncomfortable and may accelerate the rate of disease progression in vulnerable retinas. The NIR-RAFI method developed here is a melanin-based alternative that is not absorbed by opsins and bisretinoid moieties, and is comfortable to view. Further development of this method may result in a nonmydriatic and comfortable imaging method to quantify RPE atrophy extent and its expansion rate. PMID:26024124

Multiview Locally Linear Embedding for Effective Medical Image Retrieval

PubMed Central

Shen, Hualei; Tao, Dacheng; Ma, Dianfu

2013-01-01

Content-based medical image retrieval continues to gain attention for its potential to assist radiological image interpretation and decision making. Many approaches have been proposed to improve the performance of medical image retrieval system, among which visual features such as SIFT, LBP, and intensity histogram play a critical role. Typically, these features are concatenated into a long vector to represent medical images, and thus traditional dimension reduction techniques such as locally linear embedding (LLE), principal component analysis (PCA), or laplacian eigenmaps (LE) can be employed to reduce the “curse of dimensionality”. Though these approaches show promising performance for medical image retrieval, the feature-concatenating method ignores the fact that different features have distinct physical meanings. In this paper, we propose a new method called multiview locally linear embedding (MLLE) for medical image retrieval. Following the patch alignment framework, MLLE preserves the geometric structure of the local patch in each feature space according to the LLE criterion. To explore complementary properties among a range of features, MLLE assigns different weights to local patches from different feature spaces. Finally, MLLE employs global coordinate alignment and alternating optimization techniques to learn a smooth low-dimensional embedding from different features. To justify the effectiveness of MLLE for medical image retrieval, we compare it with conventional spectral embedding methods. We conduct experiments on a subset of the IRMA medical image data set. Evaluation results show that MLLE outperforms state-of-the-art dimension reduction methods. PMID:24349277

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

PubMed

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

The plant virus microscope image registration method based on mismatches removing.

PubMed

Wei, Lifang; Zhou, Shucheng; Dong, Heng; Mao, Qianzhuo; Lin, Jiaxiang; Chen, Riqing

2016-01-01

The electron microscopy is one of the major means to observe the virus. The view of virus microscope images is limited by making specimen and the size of the camera's view field. To solve this problem, the virus sample is produced into multi-slice for information fusion and image registration techniques are applied to obtain large field and whole sections. Image registration techniques have been developed in the past decades for increasing the camera's field of view. Nevertheless, these approaches typically work in batch mode and rely on motorized microscopes. Alternatively, the methods are conceived just to provide visually pleasant registration for high overlap ratio image sequence. This work presents a method for virus microscope image registration acquired with detailed visual information and subpixel accuracy, even when overlap ratio of image sequence is 10% or less. The method proposed focus on the correspondence set and interimage transformation. A mismatch removal strategy is proposed by the spatial consistency and the components of keypoint to enrich the correspondence set. And the translation model parameter as well as tonal inhomogeneities is corrected by the hierarchical estimation and model select. In the experiments performed, we tested different registration approaches and virus images, confirming that the translation model is not always stationary, despite the fact that the images of the sample come from the same sequence. The mismatch removal strategy makes building registration of virus microscope images at subpixel accuracy easier and optional parameters for building registration according to the hierarchical estimation and model select strategies make the proposed method high precision and reliable for low overlap ratio image sequence. Copyright © 2015 Elsevier Ltd. All rights reserved.

SU-E-J-237: Image Feature Based DRR and Portal Image Registration

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

Wang, X; Chang, J

Purpose: Two-dimensional (2D) matching of the kV X-ray and digitally reconstructed radiography (DRR) images is an important setup technique for image-guided radiotherapy (IGRT). In our clinics, mutual information based methods are used for this purpose on commercial linear accelerators, but with often needs for manual corrections. This work proved the feasibility that feature based image transform can be used to register kV and DRR images. Methods: The scale invariant feature transform (SIFT) method was implemented to detect the matching image details (or key points) between the kV and DRR images. These key points represent high image intensity gradients, and thusmore » the scale invariant features. Due to the poor image contrast from our kV image, direct application of the SIFT method yielded many detection errors. To assist the finding of key points, the center coordinates of the kV and DRR images were read from the DICOM header, and the two groups of key points with similar relative positions to their corresponding centers were paired up. Using these points, a rigid transform (with scaling, horizontal and vertical shifts) was estimated. We also artificially introduced vertical and horizontal shifts to test the accuracy of our registration method on anterior-posterior (AP) and lateral pelvic images. Results: The results provided a satisfactory overlay of the transformed kV onto the DRR image. The introduced vs. detected shifts were fit into a linear regression. In the AP image experiments, linear regression analysis showed a slope of 1.15 and 0.98 with an R2 of 0.89 and 0.99 for the horizontal and vertical shifts, respectively. The results are 1.2 and 1.3 with R2 of 0.72 and 0.82 for the lateral image shifts. Conclusion: This work provided an alternative technique for kV to DRR alignment. Further improvements in the estimation accuracy and image contrast tolerance are underway.« less

Selective spectroscopic imaging of hyperpolarized pyruvate and its metabolites using a single-echo variable phase advance method in balanced SSFP

PubMed Central

Varma, Gopal; Wang, Xiaoen; Vinogradov, Elena; Bhatt, Rupal S.; Sukhatme, Vikas; Seth, Pankaj; Lenkinski, Robert E.; Alsop, David C.; Grant, Aaron K.

2015-01-01

Purpose In balanced steady state free precession (bSSFP), the signal intensity has a well-known dependence on the off-resonance frequency, or, equivalently, the phase advance between successive radiofrequency (RF) pulses. The signal profile can be used to resolve the contributions from the spectrally separated metabolites. This work describes a method based on use of a variable RF phase advance to acquire spatial and spectral data in a time-efficient manner for hyperpolarized 13C MRI. Theory and Methods The technique relies on the frequency response from a bSSFP acquisition to acquire relatively rapid, high-resolution images that may be reconstructed to separate contributions from different metabolites. The ability to produce images from spectrally separated metabolites was demonstrated in-vitro, as well as in-vivo following administration of hyperpolarized 1-13C pyruvate in mice with xenograft tumors. Results In-vivo images of pyruvate, alanine, pyruvate hydrate and lactate were reconstructed from 4 images acquired in 2 seconds with an in-plane resolution of 1.25 × 1.25mm2 and 5mm slice thickness. Conclusions The phase advance method allowed acquisition of spectroscopically selective images with high spatial and temporal resolution. This method provides an alternative approach to hyperpolarized 13C spectroscopic MRI that can be combined with other techniques such as multi-echo or fluctuating equilibrium bSSFP. PMID:26507361

What automated age estimation of hand and wrist MRI data tells us about skeletal maturation in male adolescents.

PubMed

Urschler, Martin; Grassegger, Sabine; Štern, Darko

2015-01-01

Age estimation of individuals is important in human biology and has various medical and forensic applications. Recent interest in MR-based methods aims to investigate alternatives for established methods involving ionising radiation. Automatic, software-based methods additionally promise improved estimation objectivity. To investigate how informative automatically selected image features are regarding their ability to discriminate age, by exploring a recently proposed software-based age estimation method for MR images of the left hand and wrist. One hundred and two MR datasets of left hand images are used to evaluate age estimation performance, consisting of bone and epiphyseal gap volume localisation, computation of one age regression model per bone mapping image features to age and fusion of individual bone age predictions to a final age estimate. Quantitative results of the software-based method show an age estimation performance with a mean absolute difference of 0.85 years (SD = 0.58 years) to chronological age, as determined by a cross-validation experiment. Qualitatively, it is demonstrated how feature selection works and which image features of skeletal maturation are automatically chosen to model the non-linear regression function. Feasibility of automatic age estimation based on MRI data is shown and selected image features are found to be informative for describing anatomical changes during physical maturation in male adolescents.

Cone Beam X-ray Luminescence Computed Tomography Based on Bayesian Method.

PubMed

Zhang, Guanglei; Liu, Fei; Liu, Jie; Luo, Jianwen; Xie, Yaoqin; Bai, Jing; Xing, Lei

2017-01-01

X-ray luminescence computed tomography (XLCT), which aims to achieve molecular and functional imaging by X-rays, has recently been proposed as a new imaging modality. Combining the principles of X-ray excitation of luminescence-based probes and optical signal detection, XLCT naturally fuses functional and anatomical images and provides complementary information for a wide range of applications in biomedical research. In order to improve the data acquisition efficiency of previously developed narrow-beam XLCT, a cone beam XLCT (CB-XLCT) mode is adopted here to take advantage of the useful geometric features of cone beam excitation. Practically, a major hurdle in using cone beam X-ray for XLCT is that the inverse problem here is seriously ill-conditioned, hindering us to achieve good image quality. In this paper, we propose a novel Bayesian method to tackle the bottleneck in CB-XLCT reconstruction. The method utilizes a local regularization strategy based on Gaussian Markov random field to mitigate the ill-conditioness of CB-XLCT. An alternating optimization scheme is then used to automatically calculate all the unknown hyperparameters while an iterative coordinate descent algorithm is adopted to reconstruct the image with a voxel-based closed-form solution. Results of numerical simulations and mouse experiments show that the self-adaptive Bayesian method significantly improves the CB-XLCT image quality as compared with conventional methods.

Cone Beam X-ray Luminescence Computed Tomography Based on Bayesian Method

PubMed Central

Liu, Fei; Luo, Jianwen; Xie, Yaoqin; Bai, Jing

2017-01-01

X-ray luminescence computed tomography (XLCT), which aims to achieve molecular and functional imaging by X-rays, has recently been proposed as a new imaging modality. Combining the principles of X-ray excitation of luminescence-based probes and optical signal detection, XLCT naturally fuses functional and anatomical images and provides complementary information for a wide range of applications in biomedical research. In order to improve the data acquisition efficiency of previously developed narrow-beam XLCT, a cone beam XLCT (CB-XLCT) mode is adopted here to take advantage of the useful geometric features of cone beam excitation. Practically, a major hurdle in using cone beam X-ray for XLCT is that the inverse problem here is seriously ill-conditioned, hindering us to achieve good image quality. In this paper, we propose a novel Bayesian method to tackle the bottleneck in CB-XLCT reconstruction. The method utilizes a local regularization strategy based on Gaussian Markov random field to mitigate the ill-conditioness of CB-XLCT. An alternating optimization scheme is then used to automatically calculate all the unknown hyperparameters while an iterative coordinate descent algorithm is adopted to reconstruct the image with a voxel-based closed-form solution. Results of numerical simulations and mouse experiments show that the self-adaptive Bayesian method significantly improves the CB-XLCT image quality as compared with conventional methods. PMID:27576245

Steganalysis using logistic regression

NASA Astrophysics Data System (ADS)

Lubenko, Ivans; Ker, Andrew D.

2011-02-01

We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods - it estimates class probabilities as well as providing a simple classification - and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classification, and it shows comparable classification accuracy to SVM methods. This work is a case study, comparing accuracy and speed of SVM and LR classifiers in detection of LSB Matching and other related spatial-domain image steganography, through the state-of-art 686-dimensional SPAM feature set, in three image sets.

3D printing scanning electron microscopy sample holders: A quick and cost effective alternative for custom holder fabrication.

PubMed

Meloni, Gabriel N; Bertotti, Mauro

2017-01-01

A simple and cost effective alternative for fabricating custom Scanning Electron Microscope (SEM) sample holders using 3D printers and conductive polylactic acid filament is presented. The flexibility of the 3D printing process allowed for the fabrication of sample holders with specific features that enable the high-resolution imaging of nanoelectrodes and nanopipettes. The precise value of the inner semi cone angle of the nanopipettes taper was extracted from the acquired images and used for calculating their radius using electrochemical methods. Because of the low electrical resistivity presented by the 3D printed holder, the imaging of non-conductive nanomaterials, such as alumina powder, was found to be possible. The fabrication time for each sample holder was under 30 minutes and the average cost was less than $0.50 per piece. Despite being quick and economical to fabricate, the sample holders were found to be sufficiently resistant, allowing for multiple uses of the same holder.

3D printing scanning electron microscopy sample holders: A quick and cost effective alternative for custom holder fabrication

PubMed Central

Bertotti, Mauro

2017-01-01

A simple and cost effective alternative for fabricating custom Scanning Electron Microscope (SEM) sample holders using 3D printers and conductive polylactic acid filament is presented. The flexibility of the 3D printing process allowed for the fabrication of sample holders with specific features that enable the high-resolution imaging of nanoelectrodes and nanopipettes. The precise value of the inner semi cone angle of the nanopipettes taper was extracted from the acquired images and used for calculating their radius using electrochemical methods. Because of the low electrical resistivity presented by the 3D printed holder, the imaging of non-conductive nanomaterials, such as alumina powder, was found to be possible. The fabrication time for each sample holder was under 30 minutes and the average cost was less than $0.50 per piece. Despite being quick and economical to fabricate, the sample holders were found to be sufficiently resistant, allowing for multiple uses of the same holder. PMID:28753638

X-ray focal spot reconstruction by circular penumbra analysis-Application to digital radiography systems.

PubMed

Di Domenico, Giovanni; Cardarelli, Paolo; Contillo, Adriano; Taibi, Angelo; Gambaccini, Mauro

2016-01-01

The quality of a radiography system is affected by several factors, a major one being the focal spot size of the x-ray tube. In fact, the measurement of such size is recognized to be of primary importance during acceptance tests and image quality evaluations of clinical radiography systems. The most common device providing an image of the focal spot emission distribution is a pin-hole camera, which requires a high tube loading in order to produce a measurable signal. This work introduces an alternative technique to obtain an image of the focal spot, through the processing of a single radiograph of a simple test object, acquired with a suitable magnification. The radiograph of a magnified sharp edge is a well-established method to evaluate the extension of the focal spot profile along the direction perpendicular to the edge. From a single radiograph of a circular x-ray absorber, it is possible to extract simultaneously the radial profiles of several sharp edges with different orientations. The authors propose a technique that allows to obtain an image of the focal spot through the processing of these radial profiles by means of a pseudo-CT reconstruction technique. In order to validate this technique, the reconstruction has been applied to the simulated radiographs of an ideal disk-shaped absorber, generated by various simulated focal spot distributions. Furthermore, the method has been applied to the focal spot of a commercially available mammography unit. In the case of simulated radiographs, the results of the reconstructions have been compared to the original distributions, showing an excellent agreement for what regards both the overall distribution and the full width at half maximum measurements. In the case of the experimental test, the method allowed to obtain images of the focal spot that have been compared with the results obtained through standard techniques, namely, pin-hole camera and slit camera. The method was proven to be effective for simulated images and the results of the experimental test suggest that it could be considered as an alternative technique for focal spot distribution evaluation. The method offers the possibility to measure the actual focal spot size and emission distribution at the same exposure conditions as clinical routine, avoiding high tube loading as in the case of the pin-hole imaging technique.

Magnetic resonance imaging: a tool to monitor and optimize enzyme distribution during porcine pancreas distention for islet isolation.

PubMed

Scott, William E; Weegman, Bradley P; Balamurugan, Appakalai N; Ferrer-Fabrega, Joana; Anazawa, Takayuki; Karatzas, Theodore; Jie, Tun; Hammer, Bruce E; Matsumoto, Shuchiro; Avgoustiniatos, Efstathios S; Maynard, Kristen S; Sutherland, David E R; Hering, Bernhard J; Papas, Klearchos K

2014-01-01

Porcine islet xenotransplantation is emerging as a potential alternative for allogeneic clinical islet transplantation. Optimization of porcine islet isolation in terms of yield and quality is critical for the success and cost-effectiveness of this approach. Incomplete pancreas distention and inhomogeneous enzyme distribution have been identified as key factors for limiting viable islet yield per porcine pancreas. The aim of this study was to explore the utility of magnetic resonance imaging (MRI) as a tool to investigate the homogeneity of enzyme delivery in porcine pancreata. Traditional and novel methods for enzyme delivery aimed at optimizing enzyme distribution were examined. Pancreata were procured from Landrace pigs via en bloc viscerectomy. The main pancreatic duct was then cannulated with an 18-g winged catheter and MRI performed at 1.5-T. Images were collected before and after ductal infusion of chilled MRI contrast agent (gadolinium) in physiological saline. Regions of the distal aspect of the splenic lobe and portions of the connecting lobe and bridge exhibited reduced delivery of solution when traditional methods of distention were utilized. Use of alternative methods of delivery (such as selective re-cannulation and distention of identified problem regions) resolved these issues, and MRI was successfully utilized as a guide and assessment tool for improved delivery. Current methods of porcine pancreas distention do not consistently deliver enzyme uniformly or adequately to all regions of the pancreas. Novel methods of enzyme delivery should be investigated and implemented for improved enzyme distribution. MRI serves as a valuable tool to visualize and evaluate the efficacy of current and prospective methods of pancreas distention and enzyme delivery. © 2014 John Wiley & Sons A/S Published by John Wiley & Sons Ltd.

Photoacoustic tomography of foreign bodies in soft biological tissue.

PubMed

Cai, Xin; Kim, Chulhong; Pramanik, Manojit; Wang, Lihong V

2011-04-01

In detecting small foreign bodies in soft biological tissue, ultrasound imaging suffers from poor sensitivity (52.6%) and specificity (47.2%). Hence, alternative imaging methods are needed. Photoacoustic (PA) imaging takes advantage of strong optical absorption contrast and high ultrasonic resolution. A PA imaging system is employed to detect foreign bodies in biological tissues. To achieve deep penetration, we use near-infrared light ranging from 750 to 800 nm and a 5-MHz spherically focused ultrasonic transducer. PA images were obtained from various targets including glass, wood, cloth, plastic, and metal embedded more than 1 cm deep in chicken tissue. The locations and sizes of the targets from the PA images agreed well with those of the actual samples. Spectroscopic PA imaging was also performed on the objects. These results suggest that PA imaging can potentially be a useful intraoperative imaging tool to identify foreign bodies.

Nanophotonic Image Sensors

PubMed Central

Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R. S.

2016-01-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial‐based THz image sensors, filter‐free nanowire image sensors and nanostructured‐based multispectral image sensors. This novel combination of cutting edge photonics research and well‐developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. PMID:27239941

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.

A simple method for low-contrast detectability, image quality and dose optimisation with CT iterative reconstruction algorithms and model observers.

PubMed

Bellesi, Luca; Wyttenbach, Rolf; Gaudino, Diego; Colleoni, Paolo; Pupillo, Francesco; Carrara, Mauro; Braghetti, Antonio; Puligheddu, Carla; Presilla, Stefano

2017-01-01

The aim of this work was to evaluate detection of low-contrast objects and image quality in computed tomography (CT) phantom images acquired at different tube loadings (i.e. mAs) and reconstructed with different algorithms, in order to find appropriate settings to reduce the dose to the patient without any image detriment. Images of supraslice low-contrast objects of a CT phantom were acquired using different mAs values. Images were reconstructed using filtered back projection (FBP), hybrid and iterative model-based methods. Image quality parameters were evaluated in terms of modulation transfer function; noise, and uniformity using two software resources. For the definition of low-contrast detectability, studies based on both human (i.e. four-alternative forced-choice test) and model observers were performed across the various images. Compared to FBP, image quality parameters were improved by using iterative reconstruction (IR) algorithms. In particular, IR model-based methods provided a 60% noise reduction and a 70% dose reduction, preserving image quality and low-contrast detectability for human radiological evaluation. According to the model observer, the diameters of the minimum detectable detail were around 2 mm (up to 100 mAs). Below 100 mAs, the model observer was unable to provide a result. IR methods improve CT protocol quality, providing a potential dose reduction while maintaining a good image detectability. Model observer can in principle be useful to assist human performance in CT low-contrast detection tasks and in dose optimisation.

Low-cost camera modifications and methodologies for very-high-resolution digital images

USDA-ARS?s Scientific Manuscript database

Aerial color and color-infrared photography are usually acquired at high altitude so the ground resolution of the photographs is < 1 m. Moreover, current color-infrared cameras and manned aircraft flight time are expensive, so the objective is the development of alternative methods for obtaining ve...

Changing Attitudes Through Behavior Modification.

ERIC Educational Resources Information Center

Whipple, W. Scott

This article describes the philosophy and methods used by the staff at the Granite Alternative School in changing student attitudes through behavior modification. The students involved all have a failure syndrome or low self-image, and are dropouts from traditional high schools. Among the techniques used are: (1) reinforcing good behavior (praise…

Audiographics for Distance Education: An Alternative Technology.

ERIC Educational Resources Information Center

Fredrickson, Scott

Audiographics is the merging of microcomputer graphics, telephone communications systems, and teaching strategies into a cost effective method of delivering distance education classes. The teacher creates visual images that are sent to and stored on computers at the remote sites. At the appropriate time the teacher and the remote site assistants…

Learning a Dictionary of Shape Epitomes with Applications to Image Labeling

PubMed Central

Chen, Liang-Chieh; Papandreou, George; Yuille, Alan L.

2015-01-01

The first main contribution of this paper is a novel method for representing images based on a dictionary of shape epitomes. These shape epitomes represent the local edge structure of the image and include hidden variables to encode shift and rotations. They are learnt in an unsupervised manner from groundtruth edges. This dictionary is compact but is also able to capture the typical shapes of edges in natural images. In this paper, we illustrate the shape epitomes by applying them to the image labeling task. In other work, described in the supplementary material, we apply them to edge detection and image modeling. We apply shape epitomes to image labeling by using Conditional Random Field (CRF) Models. They are alternatives to the superpixel or pixel representations used in most CRFs. In our approach, the shape of an image patch is encoded by a shape epitome from the dictionary. Unlike the superpixel representation, our method avoids making early decisions which cannot be reversed. Our resulting hierarchical CRFs efficiently capture both local and global class co-occurrence properties. We demonstrate its quantitative and qualitative properties of our approach with image labeling experiments on two standard datasets: MSRC-21 and Stanford Background. PMID:26321886

A Simple Method Based on the Application of a CCD Camera as a Sensor to Detect Low Concentrations of Barium Sulfate in Suspension

PubMed Central

de Sena, Rodrigo Caciano; Soares, Matheus; Pereira, Maria Luiza Oliveira; da Silva, Rogério Cruz Domingues; do Rosário, Francisca Ferreira; da Silva, Joao Francisco Cajaiba

2011-01-01

The development of a simple, rapid and low cost method based on video image analysis and aimed at the detection of low concentrations of precipitated barium sulfate is described. The proposed system is basically composed of a webcam with a CCD sensor and a conventional dichroic lamp. For this purpose, software for processing and analyzing the digital images based on the RGB (Red, Green and Blue) color system was developed. The proposed method had shown very good repeatability and linearity and also presented higher sensitivity than the standard turbidimetric method. The developed method is presented as a simple alternative for future applications in the study of precipitations of inorganic salts and also for detecting the crystallization of organic compounds. PMID:22346607

Investigation of self-adaptive LED surgical lighting based on entropy contrast enhancing method

NASA Astrophysics Data System (ADS)

Liu, Peng; Wang, Huihui; Zhang, Yaqin; Shen, Junfei; Wu, Rengmao; Zheng, Zhenrong; Li, Haifeng; Liu, Xu

2014-05-01

Investigation was performed to explore the possibility of enhancing contrast by varying the spectral distribution (SPD) of the surgical lighting. The illumination scenes with different SPDs were generated by the combination of a self-adaptive white light optimization method and the LED ceiling system, the images of biological sample are taken by a CCD camera and then processed by an 'Entropy' based contrast evaluation model which is proposed specific for surgery occasion. Compared with the neutral white LED based and traditional algorithm based image enhancing methods, the illumination based enhancing method turns out a better performance in contrast enhancing and improves the average contrast value about 9% and 6%, respectively. This low cost method is simple, practicable, and thus may provide an alternative solution for the expensive visual facility medical instruments.

Advanced two-layer level set with a soft distance constraint for dual surfaces segmentation in medical images

NASA Astrophysics Data System (ADS)

Ji, Yuanbo; van der Geest, Rob J.; Nazarian, Saman; Lelieveldt, Boudewijn P. F.; Tao, Qian

2018-03-01

Anatomical objects in medical images very often have dual contours or surfaces that are highly correlated. Manually segmenting both of them by following local image details is tedious and subjective. In this study, we proposed a two-layer region-based level set method with a soft distance constraint, which not only regularizes the level set evolution at two levels, but also imposes prior information on wall thickness in an effective manner. By updating the level set function and distance constraint functions alternatingly, the method simultaneously optimizes both contours while regularizing their distance. The method was applied to segment the inner and outer wall of both left atrium (LA) and left ventricle (LV) from MR images, using a rough initialization from inside the blood pool. Compared to manual annotation from experience observers, the proposed method achieved an average perpendicular distance (APD) of less than 1mm for the LA segmentation, and less than 1.5mm for the LV segmentation, at both inner and outer contours. The method can be used as a practical tool for fast and accurate dual wall annotations given proper initialization.

3-D ultrasound volume reconstruction using the direct frame interpolation method.

PubMed

Scheipers, Ulrich; Koptenko, Sergei; Remlinger, Rachel; Falco, Tony; Lachaine, Martin

2010-11-01

A new method for 3-D ultrasound volume reconstruction using tracked freehand 3-D ultrasound is proposed. The method is based on solving the forward volume reconstruction problem using direct interpolation of high-resolution ultrasound B-mode image frames. A series of ultrasound B-mode image frames (an image series) is acquired using the freehand scanning technique and position sensing via optical tracking equipment. The proposed algorithm creates additional intermediate image frames by directly interpolating between two or more adjacent image frames of the original image series. The target volume is filled using the original frames in combination with the additionally constructed frames. Compared with conventional volume reconstruction methods, no additional filling of empty voxels or holes within the volume is required, because the whole extent of the volume is defined by the arrangement of the original and the additionally constructed B-mode image frames. The proposed direct frame interpolation (DFI) method was tested on two different data sets acquired while scanning the head and neck region of different patients. The first data set consisted of eight B-mode 2-D frame sets acquired under optimal laboratory conditions. The second data set consisted of 73 image series acquired during a clinical study. Sample volumes were reconstructed for all 81 image series using the proposed DFI method with four different interpolation orders, as well as with the pixel nearest-neighbor method using three different interpolation neighborhoods. In addition, volumes based on a reduced number of image frames were reconstructed for comparison of the different methods' accuracy and robustness in reconstructing image data that lies between the original image frames. The DFI method is based on a forward approach making use of a priori information about the position and shape of the B-mode image frames (e.g., masking information) to optimize the reconstruction procedure and to reduce computation times and memory requirements. The method is straightforward, independent of additional input or parameters, and uses the high-resolution B-mode image frames instead of usually lower-resolution voxel information for interpolation. The DFI method can be considered as a valuable alternative to conventional 3-D ultrasound reconstruction methods based on pixel or voxel nearest-neighbor approaches, offering better quality and competitive reconstruction time.

Nonlinear image registration with bidirectional metric and reciprocal regularization

PubMed Central

Ying, Shihui; Li, Dan; Xiao, Bin; Peng, Yaxin; Du, Shaoyi; Xu, Meifeng

2017-01-01

Nonlinear registration is an important technique to align two different images and widely applied in medical image analysis. In this paper, we develop a novel nonlinear registration framework based on the diffeomorphic demons, where a reciprocal regularizer is introduced to assume that the deformation between two images is an exact diffeomorphism. In detail, first, we adopt a bidirectional metric to improve the symmetry of the energy functional, whose variables are two reciprocal deformations. Secondly, we slack these two deformations into two independent variables and introduce a reciprocal regularizer to assure the deformations being the exact diffeomorphism. Then, we utilize an alternating iterative strategy to decouple the model into two minimizing subproblems, where a new closed form for the approximate velocity of deformation is calculated. Finally, we compare our proposed algorithm on two data sets of real brain MR images with two relative and conventional methods. The results validate that our proposed method improves accuracy and robustness of registration, as well as the gained bidirectional deformations are actually reciprocal. PMID:28231342

Simultaneous CT-MRI Reconstruction for Constrained Imaging Geometries using Structural Coupling and Compressive Sensing

PubMed Central

Xi, Yan; Zhao, Jun; Bennett, James R.; Stacy, Mitchel R.; Sinusas, Albert J.; Wang, Ge

2016-01-01

Objective A unified reconstruction framework is presented for simultaneous CT-MRI reconstruction. Significance Combined CT-MRI imaging has the potential for improved results in existing preclinical and clinical applications, as well as opening novel research directions for future applications. Methods In an ideal CT-MRI scanner, CT and MRI acquisitions would occur simultaneously, and hence would be inherently registered in space and time. Alternatively, separately acquired CT and MRI scans can be fused to simulate an instantaneous acquisition. In this study, structural coupling and compressive sensing techniques are combined to unify CT and MRI reconstructions. A bidirectional image estimation method was proposed to connect images from different modalities. Hence, CT and MRI data serve as prior knowledge to each other for better CT and MRI image reconstruction than what could be achieved with separate reconstruction. Results Our integrated reconstruction methodology is demonstrated with numerical phantom and real-dataset based experiments, and has yielded promising results. PMID:26672028

Imaging of targeted lipid microbubbles to detect cancer cells using third harmonic generation microscopy

PubMed Central

Harpel, Kaitlin; Baker, Robert Dawson; Amirsolaimani, Babak; Mehravar, Soroush; Vagner, Josef; Matsunaga, Terry O.; Banerjee, Bhaskar; Kieu, Khanh

2016-01-01

The use of receptor-targeted lipid microbubbles imaged by ultrasound is an innovative method of detecting and localizing disease. However, since ultrasound requires a medium between the transducer and the object being imaged, it is impractical to apply to an exposed surface in a surgical setting where sterile fields need be maintained and ultrasound gel may cause the bubbles to collapse. Multiphoton microscopy (MPM) is an emerging tool for accurate, label-free imaging of tissues and cells with high resolution and contrast. We have recently determined a novel application of MPM to be used for detecting targeted microbubble adherence to the upregulated plectin-receptor on pancreatic tumor cells. Specifically, the third-harmonic generation response can be used to detect bound microbubbles to various cell types presenting MPM as an alternative and useful imaging method. This is an interesting technique that can potentially be translated as a diagnostic tool for the early detection of cancer and inflammatory disorders. PMID:27446711

Estimating False Positive Contamination in Crater Annotations from Citizen Science Data

NASA Astrophysics Data System (ADS)

Tar, P. D.; Bugiolacchi, R.; Thacker, N. A.; Gilmour, J. D.

2017-01-01

Web-based citizen science often involves the classification of image features by large numbers of minimally trained volunteers, such as the identification of lunar impact craters under the Moon Zoo project. Whilst such approaches facilitate the analysis of large image data sets, the inexperience of users and ambiguity in image content can lead to contamination from false positive identifications. We give an approach, using Linear Poisson Models and image template matching, that can quantify levels of false positive contamination in citizen science Moon Zoo crater annotations. Linear Poisson Models are a form of machine learning which supports predictive error modelling and goodness-of-fits, unlike most alternative machine learning methods. The proposed supervised learning system can reduce the variability in crater counts whilst providing predictive error assessments of estimated quantities of remaining true verses false annotations. In an area of research influenced by human subjectivity, the proposed method provides a level of objectivity through the utilisation of image evidence, guided by candidate crater identifications.

Cone beam volume tomography: an imaging option for diagnosis of complex mandibular third molar anatomical relationships.

PubMed

Danforth, Robert A; Peck, Jerry; Hall, Paul

2003-11-01

Complex impacted third molars present potential treatment complications and possible patient morbidity. Objectives of diagnostic imaging are to facilitate diagnosis, decision making, and enhance treatment outcomes. As cases become more complex, advanced multiplane imaging methods allowing for a 3-D view are more likely to meet these objectives than traditional 2-D radiography. Until recently, advanced imaging options were somewhat limited to standard film tomography or medical CT, but development of cone beam volume tomography (CBVT) multiplane 3-D imaging systems specifically for dental use now provides an alternative imaging option. Two cases were utilized to compare the role of CBVT to these other imaging options and to illustrate how multiplane visualization can assist the pretreatment evaluation and decision-making process for complex impacted mandibular third molar cases.

In-situ visualisation of hyphal structure and arrangement in mycoprotein pastes.

PubMed

Miri, Taghi; Cox, Philip W; Fryer, Peter J

2003-02-01

A novel method to examine the morphology and structure of fungal hyphae in solid pastes used for the production of meat alternative product is presented. A sample of fermentation broth was fluorescently stained with Calcofluor White and added back to the broth, mixed and then a paste made using ultra-filtration. Fibre visualisation was by fluorescence microscopy and quantification by manual image analysis. This method enables the determination of fibre length and orientation within the paste. Imaging of the hypha fibre paste proved that its structure was 'isotropic', i.e. that fibres were randomly oriented in all directions. Processing of the paste altered the orientation of the fibres, the method was able to identify and quantify the changes in fibre position.

Communication: Three-fold covariance imaging of laser-induced Coulomb explosions

NASA Astrophysics Data System (ADS)

Pickering, James D.; Amini, Kasra; Brouard, Mark; Burt, Michael; Bush, Ian J.; Christensen, Lauge; Lauer, Alexandra; Nielsen, Jens H.; Slater, Craig S.; Stapelfeldt, Henrik

2016-04-01

We apply a three-fold covariance imaging method to analyse previously acquired data [C. S. Slater et al., Phys. Rev. A 89, 011401(R) (2014)] on the femtosecond laser-induced Coulomb explosion of spatially pre-aligned 3,5-dibromo-3',5'-difluoro-4'-cyanobiphenyl molecules. The data were acquired using the "Pixel Imaging Mass Spectrometry" camera. We show how three-fold covariance imaging of ionic photofragment recoil trajectories can be used to provide new information about the parent ion's molecular structure prior to its Coulomb explosion. In particular, we show how the analysis may be used to obtain information about molecular conformation and provide an alternative route for enantiomer determination.

Fast conjugate phase image reconstruction based on a Chebyshev approximation to correct for B0 field inhomogeneity and concomitant gradients.

PubMed

Chen, Weitian; Sica, Christopher T; Meyer, Craig H

2008-11-01

Off-resonance effects can cause image blurring in spiral scanning and various forms of image degradation in other MRI methods. Off-resonance effects can be caused by both B0 inhomogeneity and concomitant gradient fields. Previously developed off-resonance correction methods focus on the correction of a single source of off-resonance. This work introduces a computationally efficient method of correcting for B0 inhomogeneity and concomitant gradients simultaneously. The method is a fast alternative to conjugate phase reconstruction, with the off-resonance phase term approximated by Chebyshev polynomials. The proposed algorithm is well suited for semiautomatic off-resonance correction, which works well even with an inaccurate or low-resolution field map. The proposed algorithm is demonstrated using phantom and in vivo data sets acquired by spiral scanning. Semiautomatic off-resonance correction alone is shown to provide a moderate amount of correction for concomitant gradient field effects, in addition to B0 imhomogeneity effects. However, better correction is provided by the proposed combined method. The best results were produced using the semiautomatic version of the proposed combined method.

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

PubMed

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

2018-04-01

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

Advanced and Conventional Magnetic Resonance Imaging in Neuropsychiatric Lupus

PubMed Central

Sarbu, Nicolae; Bargalló, Núria; Cervera, Ricard

2015-01-01

Neuropsychiatric lupus is a major diagnostic challenge, and a main cause of morbidity and mortality in patients with systemic lupus erythematosus (SLE). Magnetic resonance imaging (MRI) is, by far, the main tool for assessing the brain in this disease. Conventional and advanced MRI techniques are used to help establishing the diagnosis, to rule out alternative diagnoses, and recently, to monitor the evolution of the disease. This review explores the neuroimaging findings in SLE, including the recent advances in new MRI methods. PMID:26236469

Dem Generation from Close-Range Photogrammetry Using Extended Python Photogrammetry Toolbox

NASA Astrophysics Data System (ADS)

Belmonte, A. A.; Biong, M. M. P.; Macatulad, E. G.

2017-10-01

Digital elevation models (DEMs) are widely used raster data for different applications concerning terrain, such as for flood modelling, viewshed analysis, mining, land development, engineering design projects, to name a few. DEMs can be obtained through various methods, including topographic survey, LiDAR or photogrammetry, and internet sources. Terrestrial close-range photogrammetry is one of the alternative methods to produce DEMs through the processing of images using photogrammetry software. There are already powerful photogrammetry software that are commercially-available and can produce high-accuracy DEMs. However, this entails corresponding cost. Although, some of these software have free or demo trials, these trials have limits in their usable features and usage time. One alternative is the use of free and open-source software (FOSS), such as the Python Photogrammetry Toolbox (PPT), which provides an interface for performing photogrammetric processes implemented through python script. For relatively small areas such as in mining or construction excavation, a relatively inexpensive, fast and accurate method would be advantageous. In this study, PPT was used to generate 3D point cloud data from images of an open pit excavation. The PPT was extended to add an algorithm converting the generated point cloud data into a usable DEM.

Evaluation of image features and classification methods for Barrett's cancer detection using VLE imaging

NASA Astrophysics Data System (ADS)

Klomp, Sander; van der Sommen, Fons; Swager, Anne-Fré; Zinger, Svitlana; Schoon, Erik J.; Curvers, Wouter L.; Bergman, Jacques J.; de With, Peter H. N.

2017-03-01

Volumetric Laser Endomicroscopy (VLE) is a promising technique for the detection of early neoplasia in Barrett's Esophagus (BE). VLE generates hundreds of high resolution, grayscale, cross-sectional images of the esophagus. However, at present, classifying these images is a time consuming and cumbersome effort performed by an expert using a clinical prediction model. This paper explores the feasibility of using computer vision techniques to accurately predict the presence of dysplastic tissue in VLE BE images. Our contribution is threefold. First, a benchmarking is performed for widely applied machine learning techniques and feature extraction methods. Second, three new features based on the clinical detection model are proposed, having superior classification accuracy and speed, compared to earlier work. Third, we evaluate automated parameter tuning by applying simple grid search and feature selection methods. The results are evaluated on a clinically validated dataset of 30 dysplastic and 30 non-dysplastic VLE images. Optimal classification accuracy is obtained by applying a support vector machine and using our modified Haralick features and optimal image cropping, obtaining an area under the receiver operating characteristic of 0.95 compared to the clinical prediction model at 0.81. Optimal execution time is achieved using a proposed mean and median feature, which is extracted at least factor 2.5 faster than alternative features with comparable performance.

Visual Search with Image Modification in Age-Related Macular Degeneration

PubMed Central

Wiecek, Emily; Jackson, Mary Lou; Dakin, Steven C.; Bex, Peter

2012-01-01

Purpose. AMD results in loss of central vision and a dependence on low-resolution peripheral vision. While many image enhancement techniques have been proposed, there is a lack of quantitative comparison of the effectiveness of enhancement. We developed a natural visual search task that uses patients' eye movements as a quantitative and functional measure of the efficacy of image modification. Methods. Eye movements of 17 patients (mean age = 77 years) with AMD were recorded while they searched for target objects in natural images. Eight different image modification methods were implemented and included manipulations of local image or edge contrast, color, and crowding. In a subsequent task, patients ranked their preference of the image modifications. Results. Within individual participants, there was no significant difference in search duration or accuracy across eight different image manipulations. When data were collapsed across all image modifications, a multivariate model identified six significant predictors for normalized search duration including scotoma size and acuity, as well as interactions among scotoma size, age, acuity, and contrast (P < 0.05). Additionally, an analysis of image statistics showed no correlation with search performance across all image modifications. Rank ordering of enhancement methods based on participants' preference revealed a trend that participants preferred the least modified images (P < 0.05). Conclusions. There was no quantitative effect of image modification on search performance. A better understanding of low- and high-level components of visual search in natural scenes is necessary to improve future attempts at image enhancement for low vision patients. Different search tasks may require alternative image modifications to improve patient functioning and performance. PMID:22930725

A Constraint Generation Approach to Learning Stable Linear Dynamical Systems

DTIC Science & Technology

2008-01-01

task of learning dynamic textures from image sequences as well as to modeling biosurveillance drug-sales data. The constraint generation approach...previous methods in our experiments. One application of LDSs in computer vision is learning dynamic textures from video data [8]. An advantage of...over-the-counter (OTC) drug sales for biosurveillance , and sunspot numbers from the UCR archive [9]. Comparison to the best alternative methods [7, 10

Virtual simulation as a learning method in interventional radiology.

PubMed

Avramov, Predrag; Avramov, Milena; Juković, Mirela; Kadić, Vuk; Till, Viktor

2013-01-01

Radiology is the fastest growing discipline of medicine thanks to the implementation of new technologies and very rapid development of imaging diagnostic procedures in the last few decades. On the other hand, the development of imaging diagnostic procedures has put aside the traditional gaining of experience by working on real patients, and the need for other alternatives of learning interventional radiology procedures has emerged. A new method of virtual approach was added as an excellent alternative to the currently known methods of training on physical models and animals. Virtual reality represents a computer-generated reconstruction of anatomical environment with tactile interactions and it enables operators not only to learn on their own mistakes without compromising the patient's safety, but also to enhance their knowledge and experience. It is true that studies published so far on the validity of endovascular simulators have shown certain improvement of operator's technical skills and reduction in time needed for the procedure, but on the other hand, it is still a question whether these skills are transferable to the real patients in the angio room. With further improvement of technology, shortcomings of virtual approach to interventional procedures learning will be less significant and this procedure is likely to become the only method of learning in the near future.

Advanced Forensic Format: an Open Extensible Format for Disk Imaging

NASA Astrophysics Data System (ADS)

Garfinkel, Simson; Malan, David; Dubec, Karl-Alexander; Stevens, Christopher; Pham, Cecile

This paper describes the Advanced Forensic Format (AFF), which is designed as an alternative to current proprietary disk image formats. AFF offers two significant benefits. First, it is more flexible because it allows extensive metadata to be stored with images. Second, AFF images consume less disk space than images in other formats (e.g., EnCase images). This paper also describes the Advanced Disk Imager, a new program for acquiring disk images that compares favorably with existing alternatives.

Elastic models: a comparative study applied to retinal images.

PubMed

Karali, E; Lambropoulou, S; Koutsouris, D

2011-01-01

In this work various methods of parametric elastic models are compared, namely the classical snake, the gradient vector field snake (GVF snake) and the topology-adaptive snake (t-snake), as well as the method of self-affine mapping system as an alternative to elastic models. We also give a brief overview of the methods used. The self-affine mapping system is implemented using an adapting scheme and minimum distance as optimization criterion, which is more suitable for weak edges detection. All methods are applied to glaucomatic retinal images with the purpose of segmenting the optical disk. The methods are compared in terms of segmentation accuracy and speed, as these are derived from cross-correlation coefficients between real and algorithm extracted contours and segmentation time, respectively. As a result, the method of self-affine mapping system presents adequate segmentation time and segmentation accuracy, and significant independence from initialization.

Method and system to synchronize acoustic therapy with ultrasound imaging

NASA Technical Reports Server (NTRS)

Hossack, James (Inventor); Owen, Neil (Inventor); Bailey, Michael R. (Inventor)

2009-01-01

Interference in ultrasound imaging when used in connection with high intensity focused ultrasound (HIFU) is avoided by employing a synchronization signal to control the HIFU signal. Unless the timing of the HIFU transducer is controlled, its output will substantially overwhelm the signal produced by ultrasound imaging system and obscure the image it produces. The synchronization signal employed to control the HIFU transducer is obtained without requiring modification of the ultrasound imaging system. Signals corresponding to scattered ultrasound imaging waves are collected using either the HIFU transducer or a dedicated receiver. A synchronization processor manipulates the scattered ultrasound imaging signals to achieve the synchronization signal, which is then used to control the HIFU bursts so as to substantially reduce or eliminate HIFU interference in the ultrasound image. The synchronization processor can alternatively be implemented using a computing device or an application-specific circuit.

Comparison of Filters Dedicated to Speckle Suppression in SAR Images

NASA Astrophysics Data System (ADS)

Kupidura, P.

2016-06-01

This paper presents the results of research on the effectiveness of different filtering methods dedicated to speckle suppression in SAR images. The tests were performed on RadarSat-2 images and on an artificial image treated with simulated speckle noise. The research analysed the performance of particular filters related to the effectiveness of speckle suppression and to the ability to preserve image details and edges. Speckle is a phenomenon inherent to radar images - a deterministic noise connected with land cover type, but also causing significant changes in digital numbers of pixels. As a result, it may affect interpretation, classification and other processes concerning radar images. Speckle, resembling "salt and pepper" noise, has the form of a set of relatively small groups of pixels of values markedly different from values of other pixels representing the same type of land cover. Suppression of this noise may also cause suppression of small image details, therefore the ability to preserve the important parts of an image, was analysed as well. In the present study, selected filters were tested, and methods dedicated particularly to speckle noise suppression: Frost, Gamma-MAP, Lee, Lee-Sigma, Local Region, general filtering methods which might be effective in this respect: Mean, Median, in addition to morphological filters (alternate sequential filters with multiple structuring element and by reconstruction). The analysis presented in this paper compared the effectiveness of different filtering methods. It proved that some of the dedicated radar filters are efficient tools for speckle suppression, but also demonstrated a significant efficiency of the morphological approach, especially its ability to preserve image details.

Solvent replacement for green processing.

PubMed Central

Sherman, J; Chin, B; Huibers, P D; Garcia-Valls, R; Hatton, T A

1998-01-01

The implementation of the Montreal Protocol, the Clean Air Act, and the Pollution Prevention Act of 1990 has resulted in increased awareness of organic solvent use in chemical processing. The advances made in the search to find "green" replacements for traditional solvents are reviewed, with reference to solvent alternatives for cleaning, coatings, and chemical reaction and separation processes. The development of solvent databases and computational methods that aid in the selection and/or design of feasible or optimal environmentally benign solvent alternatives for specific applications is also discussed. Images Figure 2 Figure 3 PMID:9539018

Imaging through turbulence using a plenoptic sensor

NASA Astrophysics Data System (ADS)

Wu, Chensheng; Ko, Jonathan; Davis, Christopher C.

2015-09-01

Atmospheric turbulence can significantly affect imaging through paths near the ground. Atmospheric turbulence is generally treated as a time varying inhomogeneity of the refractive index of the air, which disrupts the propagation of optical signals from the object to the viewer. Under circumstances of deep or strong turbulence, the object is hard to recognize through direct imaging. Conventional imaging methods can't handle those problems efficiently. The required time for lucky imaging can be increased significantly and the image processing approaches require much more complex and iterative de-blurring algorithms. We propose an alternative approach using a plenoptic sensor to resample and analyze the image distortions. The plenoptic sensor uses a shared objective lens and a microlens array to form a mini Keplerian telescope array. Therefore, the image obtained by a conventional method will be separated into an array of images that contain multiple copies of the object's image and less correlated turbulence disturbances. Then a highdimensional lucky imaging algorithm can be performed based on the collected video on the plenoptic sensor. The corresponding algorithm will select the most stable pixels from various image cells and reconstruct the object's image as if there is only weak turbulence effect. Then, by comparing the reconstructed image with the recorded images in each MLA cell, the difference can be regarded as the turbulence effects. As a result, the retrieval of the object's image and extraction of turbulence effect can be performed simultaneously.

A four-alternative forced choice (4AFC) software for observer performance evaluation in radiology

NASA Astrophysics Data System (ADS)

Zhang, Guozhi; Cockmartin, Lesley; Bosmans, Hilde

2016-03-01

Four-alternative forced choice (4AFC) test is a psychophysical method that can be adopted for observer performance evaluation in radiological studies. While the concept of this method is well established, difficulties to handle large image data, perform unbiased sampling, and keep track of the choice made by the observer have restricted its application in practice. In this work, we propose an easy-to-use software that can help perform 4AFC tests with DICOM images. The software suits for any experimental design that follows the 4AFC approach. It has a powerful image viewing system that favorably simulates the clinical reading environment. The graphical interface allows the observer to adjust various viewing parameters and perform the selection with very simple operations. The sampling process involved in 4AFC as well as the speed and accuracy of the choice made by the observer is precisely monitored in the background and can be easily exported for test analysis. The software has also a defensive mechanism for data management and operation control that minimizes the possibility of mistakes from user during the test. This software can largely facilitate the use of 4AFC approach in radiological observer studies and is expected to have widespread applicability.

Evaluation of MRI sequences for quantitative T1 brain mapping

NASA Astrophysics Data System (ADS)

Tsialios, P.; Thrippleton, M.; Glatz, A.; Pernet, C.

2017-11-01

T1 mapping constitutes a quantitative MRI technique finding significant application in brain imaging. It allows evaluation of contrast uptake, blood perfusion, volume, providing a more specific biomarker of disease progression compared to conventional T1-weighted images. While there are many techniques for T1-mapping there is a wide range of reported T1-values in tissues, raising the issue of protocols reproducibility and standardization. The gold standard for obtaining T1-maps is based on acquiring IR-SE sequence. Widely used alternative sequences are IR-SE-EPI, VFA (DESPOT), DESPOT-HIFI and MP2RAGE that speed up scanning and fitting procedures. A custom MRI phantom was used to assess the reproducibility and accuracy of the different methods. All scans were performed using a 3T Siemens Prisma scanner. The acquired data processed using two different codes. The main difference was observed for VFA (DESPOT) which grossly overestimated T1 relaxation time by 214 ms [126 270] compared to the IR-SE sequence. MP2RAGE and DESPOT-HIFI sequences gave slightly shorter time than IR-SE (~20 to 30ms) and can be considered as alternative and time-efficient methods for acquiring accurate T1 maps of the human brain, while IR-SE-EPI gave identical result, at a cost of a lower image quality.

An Assessment of Iterative Reconstruction Methods for Sparse Ultrasound Imaging

PubMed Central

Valente, Solivan A.; Zibetti, Marcelo V. W.; Pipa, Daniel R.; Maia, Joaquim M.; Schneider, Fabio K.

2017-01-01

Ultrasonic image reconstruction using inverse problems has recently appeared as an alternative to enhance ultrasound imaging over beamforming methods. This approach depends on the accuracy of the acquisition model used to represent transducers, reflectivity, and medium physics. Iterative methods, well known in general sparse signal reconstruction, are also suited for imaging. In this paper, a discrete acquisition model is assessed by solving a linear system of equations by an ℓ1-regularized least-squares minimization, where the solution sparsity may be adjusted as desired. The paper surveys 11 variants of four well-known algorithms for sparse reconstruction, and assesses their optimization parameters with the goal of finding the best approach for iterative ultrasound imaging. The strategy for the model evaluation consists of using two distinct datasets. We first generate data from a synthetic phantom that mimics real targets inside a professional ultrasound phantom device. This dataset is contaminated with Gaussian noise with an estimated SNR, and all methods are assessed by their resulting images and performances. The model and methods are then assessed with real data collected by a research ultrasound platform when scanning the same phantom device, and results are compared with beamforming. A distinct real dataset is finally used to further validate the proposed modeling. Although high computational effort is required by iterative methods, results show that the discrete model may lead to images closer to ground-truth than traditional beamforming. However, computing capabilities of current platforms need to evolve before frame rates currently delivered by ultrasound equipments are achievable. PMID:28282862

Evaluation of a HDR image sensor with logarithmic response for mobile video-based applications

NASA Astrophysics Data System (ADS)

Tektonidis, Marco; Pietrzak, Mateusz; Monnin, David

2017-10-01

The performance of mobile video-based applications using conventional LDR (Low Dynamic Range) image sensors highly depends on the illumination conditions. As an alternative, HDR (High Dynamic Range) image sensors with logarithmic response are capable to acquire illumination-invariant HDR images in a single shot. We have implemented a complete image processing framework for a HDR sensor, including preprocessing methods (nonuniformity correction (NUC), cross-talk correction (CTC), and demosaicing) as well as tone mapping (TM). We have evaluated the HDR sensor for video-based applications w.r.t. the display of images and w.r.t. image analysis techniques. Regarding the display we have investigated the image intensity statistics over time, and regarding image analysis we assessed the number of feature correspondences between consecutive frames of temporal image sequences. For the evaluation we used HDR image data recorded from a vehicle on outdoor or combined outdoor/indoor itineraries, and we performed a comparison with corresponding conventional LDR image data.

Spectral embedding based active contour (SEAC) for lesion segmentation on breast dynamic contrast enhanced magnetic resonance imaging.

PubMed

Agner, Shannon C; Xu, Jun; Madabhushi, Anant

2013-03-01

Segmentation of breast lesions on dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is the first step in lesion diagnosis in a computer-aided diagnosis framework. Because manual segmentation of such lesions is both time consuming and highly susceptible to human error and issues of reproducibility, an automated lesion segmentation method is highly desirable. Traditional automated image segmentation methods such as boundary-based active contour (AC) models require a strong gradient at the lesion boundary. Even when region-based terms are introduced to an AC model, grayscale image intensities often do not allow for clear definition of foreground and background region statistics. Thus, there is a need to find alternative image representations that might provide (1) strong gradients at the margin of the object of interest (OOI); and (2) larger separation between intensity distributions and region statistics for the foreground and background, which are necessary to halt evolution of the AC model upon reaching the border of the OOI. In this paper, the authors introduce a spectral embedding (SE) based AC (SEAC) for lesion segmentation on breast DCE-MRI. SE, a nonlinear dimensionality reduction scheme, is applied to the DCE time series in a voxelwise fashion to reduce several time point images to a single parametric image where every voxel is characterized by the three dominant eigenvectors. This parametric eigenvector image (PrEIm) representation allows for better capture of image region statistics and stronger gradients for use with a hybrid AC model, which is driven by both boundary and region information. They compare SEAC to ACs that employ fuzzy c-means (FCM) and principal component analysis (PCA) as alternative image representations. Segmentation performance was evaluated by boundary and region metrics as well as comparing lesion classification using morphological features from SEAC, PCA+AC, and FCM+AC. On a cohort of 50 breast DCE-MRI studies, PrEIm yielded overall better region and boundary-based statistics compared to the original DCE-MR image, FCM, and PCA based image representations. Additionally, SEAC outperformed a hybrid AC applied to both PCA and FCM image representations. Mean dice similarity coefficient (DSC) for SEAC was significantly better (DSC = 0.74 ± 0.21) than FCM+AC (DSC = 0.50 ± 0.32) and similar to PCA+AC (DSC = 0.73 ± 0.22). Boundary-based metrics of mean absolute difference and Hausdorff distance followed the same trends. Of the automated segmentation methods, breast lesion classification based on morphologic features derived from SEAC segmentation using a support vector machine classifier also performed better (AUC = 0.67 ± 0.05; p < 0.05) than FCM+AC (AUC = 0.50 ± 0.07), and PCA+AC (AUC = 0.49 ± 0.07). In this work, we presented SEAC, an accurate, general purpose AC segmentation tool that could be applied to any imaging domain that employs time series data. SE allows for projection of time series data into a PrEIm representation so that every voxel is characterized by the dominant eigenvectors, capturing the global and local time-intensity curve similarities in the data. This PrEIm allows for the calculation of strong tensor gradients and better region statistics than the original image intensities or alternative image representations such as PCA and FCM. The PrEIm also allows for building a more accurate hybrid AC scheme.

A novel color image encryption scheme using alternate chaotic mapping structure

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Zhao, Yuanyuan; Zhang, Huili; Guo, Kang

2016-07-01

This paper proposes an color image encryption algorithm using alternate chaotic mapping structure. Initially, we use the R, G and B components to form a matrix. Then one-dimension logistic and two-dimension logistic mapping is used to generate a chaotic matrix, then iterate two chaotic mappings alternately to permute the matrix. For every iteration, XOR operation is adopted to encrypt plain-image matrix, then make further transformation to diffuse the matrix. At last, the encrypted color image is obtained from the confused matrix. Theoretical analysis and experimental results has proved the cryptosystem is secure and practical, and it is suitable for encrypting color images.

Image database for digital hand atlas

NASA Astrophysics Data System (ADS)

Cao, Fei; Huang, H. K.; Pietka, Ewa; Gilsanz, Vicente; Dey, Partha S.; Gertych, Arkadiusz; Pospiech-Kurkowska, Sywia

2003-05-01

Bone age assessment is a procedure frequently performed in pediatric patients to evaluate their growth disorder. A commonly used method is atlas matching by a visual comparison of a hand radiograph with a small reference set of old Greulich-Pyle atlas. We have developed a new digital hand atlas with a large set of clinically normal hand images of diverse ethnic groups. In this paper, we will present our system design and implementation of the digital atlas database to support the computer-aided atlas matching for bone age assessment. The system consists of a hand atlas image database, a computer-aided diagnostic (CAD) software module for image processing and atlas matching, and a Web user interface. Users can use a Web browser to push DICOM images, directly or indirectly from PACS, to the CAD server for a bone age assessment. Quantitative features on the examined image, which reflect the skeletal maturity, are then extracted and compared with patterns from the atlas image database to assess the bone age. The digital atlas method built on a large image database and current Internet technology provides an alternative to supplement or replace the traditional one for a quantitative, accurate and cost-effective assessment of bone age.

Polymeric endovascular strut and lumen detection algorithm for intracoronary optical coherence tomography images

NASA Astrophysics Data System (ADS)

Amrute, Junedh M.; Athanasiou, Lambros S.; Rikhtegar, Farhad; de la Torre Hernández, José M.; Camarero, Tamara García; Edelman, Elazer R.

2018-03-01

Polymeric endovascular implants are the next step in minimally invasive vascular interventions. As an alternative to traditional metallic drug-eluting stents, these often-erodible scaffolds present opportunities and challenges for patients and clinicians. Theoretically, as they resorb and are absorbed over time, they obviate the long-term complications of permanent implants, but in the short-term visualization and therefore positioning is problematic. Polymeric scaffolds can only be fully imaged using optical coherence tomography (OCT) imaging-they are relatively invisible via angiography-and segmentation of polymeric struts in OCT images is performed manually, a laborious and intractable procedure for large datasets. Traditional lumen detection methods using implant struts as boundary limits fail in images with polymeric implants. Therefore, it is necessary to develop an automated method to detect polymeric struts and luminal borders in OCT images; we present such a fully automated algorithm. Accuracy was validated using expert annotations on 1140 OCT images with a positive predictive value of 0.93 for strut detection and an R2 correlation coefficient of 0.94 between detected and expert-annotated lumen areas. The proposed algorithm allows for rapid, accurate, and automated detection of polymeric struts and the luminal border in OCT images.

Active learning approach for detection of hard exudates, cotton wool spots, and drusen in retinal images

NASA Astrophysics Data System (ADS)

Sánchez, Clara I.; Niemeijer, Meindert; Kockelkorn, Thessa; Abràmoff, Michael D.; van Ginneken, Bram

2009-02-01

Computer-aided Diagnosis (CAD) systems for the automatic identification of abnormalities in retinal images are gaining importance in diabetic retinopathy screening programs. A huge amount of retinal images are collected during these programs and they provide a starting point for the design of machine learning algorithms. However, manual annotations of retinal images are scarce and expensive to obtain. This paper proposes a dynamic CAD system based on active learning for the automatic identification of hard exudates, cotton wool spots and drusen in retinal images. An uncertainty sampling method is applied to select samples that need to be labeled by an expert from an unlabeled set of 4000 retinal images. It reduces the number of training samples needed to obtain an optimum accuracy by dynamically selecting the most informative samples. Results show that the proposed method increases the classification accuracy compared to alternative techniques, achieving an area under the ROC curve of 0.87, 0.82 and 0.78 for the detection of hard exudates, cotton wool spots and drusen, respectively.

Registration of angiographic image on real-time fluoroscopic image for image-guided percutaneous coronary intervention.

PubMed

Kim, Dongkue; Park, Sangsoo; Jeong, Myung Ho; Ryu, Jeha

2018-02-01

In percutaneous coronary intervention (PCI), cardiologists must study two different X-ray image sources: a fluoroscopic image and an angiogram. Manipulating a guidewire while alternately monitoring the two separate images on separate screens requires a deep understanding of the anatomy of coronary vessels and substantial training. We propose 2D/2D spatiotemporal image registration of the two images in a single image in order to provide cardiologists with enhanced visual guidance in PCI. The proposed 2D/2D spatiotemporal registration method uses a cross-correlation of two ECG series in each image to temporally synchronize two separate images and register an angiographic image onto the fluoroscopic image. A guidewire centerline is then extracted from the fluoroscopic image in real time, and the alignment of the centerline with vessel outlines of the chosen angiographic image is optimized using the iterative closest point algorithm for spatial registration. A proof-of-concept evaluation with a phantom coronary vessel model with engineering students showed an error reduction rate greater than 74% on wrong insertion to nontarget branches compared to the non-registration method and more than 47% reduction in the task completion time in performing guidewire manipulation for very difficult tasks. Evaluation with a small number of experienced doctors shows a potentially significant reduction in both task completion time and error rate for difficult tasks. The total registration time with real procedure X-ray (angiographic and fluoroscopic) images takes [Formula: see text] 60 ms, which is within the fluoroscopic image acquisition rate of 15 Hz. By providing cardiologists with better visual guidance in PCI, the proposed spatiotemporal image registration method is shown to be useful in advancing the guidewire to the coronary vessel branches, especially those difficult to insert into.

A Precise Visual Method for Narrow Butt Detection in Specular Reflection Workpiece Welding

PubMed Central

Zeng, Jinle; Chang, Baohua; Du, Dong; Hong, Yuxiang; Chang, Shuhe; Zou, Yirong

2016-01-01

During the complex path workpiece welding, it is important to keep the welding torch aligned with the groove center using a visual seam detection method, so that the deviation between the torch and the groove can be corrected automatically. However, when detecting the narrow butt of a specular reflection workpiece, the existing methods may fail because of the extremely small groove width and the poor imaging quality. This paper proposes a novel detection method to solve these issues. We design a uniform surface light source to get high signal-to-noise ratio images against the specular reflection effect, and a double-line laser light source is used to obtain the workpiece surface equation relative to the torch. Two light sources are switched on alternately and the camera is synchronized to capture images when each light is on; then the position and pose between the torch and the groove can be obtained nearly at the same time. Experimental results show that our method can detect the groove effectively and efficiently during the welding process. The image resolution is 12.5 μm and the processing time is less than 10 ms per frame. This indicates our method can be applied to real-time narrow butt detection during high-speed welding process. PMID:27649173

A Precise Visual Method for Narrow Butt Detection in Specular Reflection Workpiece Welding.

PubMed

Zeng, Jinle; Chang, Baohua; Du, Dong; Hong, Yuxiang; Chang, Shuhe; Zou, Yirong

2016-09-13

During the complex path workpiece welding, it is important to keep the welding torch aligned with the groove center using a visual seam detection method, so that the deviation between the torch and the groove can be corrected automatically. However, when detecting the narrow butt of a specular reflection workpiece, the existing methods may fail because of the extremely small groove width and the poor imaging quality. This paper proposes a novel detection method to solve these issues. We design a uniform surface light source to get high signal-to-noise ratio images against the specular reflection effect, and a double-line laser light source is used to obtain the workpiece surface equation relative to the torch. Two light sources are switched on alternately and the camera is synchronized to capture images when each light is on; then the position and pose between the torch and the groove can be obtained nearly at the same time. Experimental results show that our method can detect the groove effectively and efficiently during the welding process. The image resolution is 12.5 μm and the processing time is less than 10 ms per frame. This indicates our method can be applied to real-time narrow butt detection during high-speed welding process.

Skimming Digits: Neuromorphic Classification of Spike-Encoded Images

PubMed Central

Cohen, Gregory K.; Orchard, Garrick; Leng, Sio-Hoi; Tapson, Jonathan; Benosman, Ryad B.; van Schaik, André

2016-01-01

The growing demands placed upon the field of computer vision have renewed the focus on alternative visual scene representations and processing paradigms. Silicon retinea provide an alternative means of imaging the visual environment, and produce frame-free spatio-temporal data. This paper presents an investigation into event-based digit classification using N-MNIST, a neuromorphic dataset created with a silicon retina, and the Synaptic Kernel Inverse Method (SKIM), a learning method based on principles of dendritic computation. As this work represents the first large-scale and multi-class classification task performed using the SKIM network, it explores different training patterns and output determination methods necessary to extend the original SKIM method to support multi-class problems. Making use of SKIM networks applied to real-world datasets, implementing the largest hidden layer sizes and simultaneously training the largest number of output neurons, the classification system achieved a best-case accuracy of 92.87% for a network containing 10,000 hidden layer neurons. These results represent the highest accuracies achieved against the dataset to date and serve to validate the application of the SKIM method to event-based visual classification tasks. Additionally, the study found that using a square pulse as the supervisory training signal produced the highest accuracy for most output determination methods, but the results also demonstrate that an exponential pattern is better suited to hardware implementations as it makes use of the simplest output determination method based on the maximum value. PMID:27199646

New regularization scheme for blind color image deconvolution

NASA Astrophysics Data System (ADS)

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

2011-01-01

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

Scanning electron microscopy of bone.

PubMed

Boyde, Alan

2012-01-01

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

Combination of Complex-Based and Magnitude-Based Multiecho Water-Fat Separation for Accurate Quantification of Fat-Fraction

PubMed Central

Yu, Huanzhou; Shimakawa, Ann; Hines, Catherine D. G.; McKenzie, Charles A.; Hamilton, Gavin; Sirlin, Claude B.; Brittain, Jean H.; Reeder, Scott B.

2011-01-01

Multipoint water–fat separation techniques rely on different water–fat phase shifts generated at multiple echo times to decompose water and fat. Therefore, these methods require complex source images and allow unambiguous separation of water and fat signals. However, complex-based water–fat separation methods are sensitive to phase errors in the source images, which may lead to clinically important errors. An alternative approach to quantify fat is through “magnitude-based” methods that acquire multiecho magnitude images. Magnitude-based methods are insensitive to phase errors, but cannot estimate fat-fraction greater than 50%. In this work, we introduce a water–fat separation approach that combines the strengths of both complex and magnitude reconstruction algorithms. A magnitude-based reconstruction is applied after complex-based water–fat separation to removes the effect of phase errors. The results from the two reconstructions are then combined. We demonstrate that using this hybrid method, 0–100% fat-fraction can be estimated with improved accuracy at low fat-fractions. PMID:21695724

Exploring three faint source detections methods for aperture synthesis radio images

NASA Astrophysics Data System (ADS)

Peracaula, M.; Torrent, A.; Masias, M.; Lladó, X.; Freixenet, J.; Martí, J.; Sánchez-Sutil, J. R.; Muñoz-Arjonilla, A. J.; Paredes, J. M.

2015-04-01

Wide-field radio interferometric images often contain a large population of faint compact sources. Due to their low intensity/noise ratio, these objects can be easily missed by automated detection methods, which have been classically based on thresholding techniques after local noise estimation. The aim of this paper is to present and analyse the performance of several alternative or complementary techniques to thresholding. We compare three different algorithms to increase the detection rate of faint objects. The first technique consists of combining wavelet decomposition with local thresholding. The second technique is based on the structural behaviour of the neighbourhood of each pixel. Finally, the third algorithm uses local features extracted from a bank of filters and a boosting classifier to perform the detections. The methods' performances are evaluated using simulations and radio mosaics from the Giant Metrewave Radio Telescope and the Australia Telescope Compact Array. We show that the new methods perform better than well-known state of the art methods such as SEXTRACTOR, SAD and DUCHAMP at detecting faint sources of radio interferometric images.

Optical Imaging of Ionizing Radiation from Clinical Sources

PubMed Central

Shaffer, Travis M.; Drain, Charles Michael

2016-01-01

Nuclear medicine uses ionizing radiation for both in vivo diagnosis and therapy. Ionizing radiation comes from a variety of sources, including x-rays, beam therapy, brachytherapy, and various injected radionuclides. Although PET and SPECT remain clinical mainstays, optical readouts of ionizing radiation offer numerous benefits and complement these standard techniques. Furthermore, for ionizing radiation sources that cannot be imaged using these standard techniques, optical imaging offers a unique imaging alternative. This article reviews optical imaging of both radionuclide- and beam-based ionizing radiation from high-energy photons and charged particles through mechanisms including radioluminescence, Cerenkov luminescence, and scintillation. Therapeutically, these visible photons have been combined with photodynamic therapeutic agents preclinically for increasing therapeutic response at depths difficult to reach with external light sources. Last, new microscopy methods that allow single-cell optical imaging of radionuclides are reviewed. PMID:27688469

Visualizing deep neural network by alternately image blurring and deblurring.

PubMed

Wang, Feng; Liu, Haijun; Cheng, Jian

2018-01-01

Visualization from trained deep neural networks has drawn massive public attention in recent. One of the visualization approaches is to train images maximizing the activation of specific neurons. However, directly maximizing the activation would lead to unrecognizable images, which cannot provide any meaningful information. In this paper, we introduce a simple but effective technique to constrain the optimization route of the visualization. By adding two totally inverse transformations, image blurring and deblurring, to the optimization procedure, recognizable images can be created. Our algorithm is good at extracting the details in the images, which are usually filtered by previous methods in the visualizations. Extensive experiments on AlexNet, VGGNet and GoogLeNet illustrate that we can better understand the neural networks utilizing the knowledge obtained by the visualization. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial resolution recovery utilizing multi-ray tracing and graphic processing unit in PET image reconstruction.

PubMed

Liang, Yicheng; Peng, Hao

2015-02-07

Depth-of-interaction (DOI) poses a major challenge for a PET system to achieve uniform spatial resolution across the field-of-view, particularly for small animal and organ-dedicated PET systems. In this work, we implemented an analytical method to model system matrix for resolution recovery, which was then incorporated in PET image reconstruction on a graphical processing unit platform, due to its parallel processing capacity. The method utilizes the concepts of virtual DOI layers and multi-ray tracing to calculate the coincidence detection response function for a given line-of-response. The accuracy of the proposed method was validated for a small-bore PET insert to be used for simultaneous PET/MR breast imaging. In addition, the performance comparisons were studied among the following three cases: 1) no physical DOI and no resolution modeling; 2) two physical DOI layers and no resolution modeling; and 3) no physical DOI design but with a different number of virtual DOI layers. The image quality was quantitatively evaluated in terms of spatial resolution (full-width-half-maximum and position offset), contrast recovery coefficient and noise. The results indicate that the proposed method has the potential to be used as an alternative to other physical DOI designs and achieve comparable imaging performances, while reducing detector/system design cost and complexity.

Visualizing Tensions in an Ethnographic Moment: Images and Intersubjectivity.

PubMed

Crowder, Jerome W

2017-01-01

Images function as sources of data and influence our thinking about fieldwork, representation, and intersubjectivity. In this article, I show how both the ethnographic relationships and the working method of photography lead to a more nuanced understanding of a healing event. I systematically analyze 33 photographs made over a 15-minute period during the preparation and application of a poultice (topical cure) in a rural Andean home. The images chronicle the event, revealing my initial reaction and the decisions I made when tripping the shutter. By unpacking the relationship between ethnographer and subject, I reveal the constant negotiation of positions, assumptions, and expectations that make up intersubjectivity. For transparency, I provide thumbnails of all images, including metadata, so that readers may consider alternative interpretations of the images and event.

The effects of exposure to feminist ideology on women's body image.

PubMed

Peterson, Rachel D; Tantleff-Dunn, Stacey; Bedwell, Jeffrey S

2006-09-01

Body image disturbance has become a common problem among women and there is a need to focus on creating empirically supported treatments. Psychoeducational interventions have reduced body image dissatisfaction, but their impact is limited because they do not offer women adaptive methods of interpreting the many appearance-related messages they receive. This study examined if exposure to a feminist perspective may provide alternative interpretations of cultural messages, thereby increasing body image satisfaction. Participants were randomly assigned to a feminist or psychoeducational intervention, or a control group. Exposure to the feminist condition resulted in increased self-identification as a feminist and greater appearance satisfaction, and changes in feminist identity were related to positive changes in body image. The findings indicate that exposure to feminist theories may serve as an effective intervention strategy.

Striping artifact reduction in lunar orbiter mosaic images

USGS Publications Warehouse

Mlsna, P.A.; Becker, T.

2006-01-01

Photographic images of the moon from the 1960s Lunar Orbiter missions are being processed into maps for visual use. The analog nature of the images has produced numerous artifacts, the chief of which causes a vertical striping pattern in mosaic images formed from a series of filmstrips. Previous methods of stripe removal tended to introduce ringing and aliasing problems in the image data. This paper describes a recently developed alternative approach that succeeds at greatly reducing the striping artifacts while avoiding the creation of ringing and aliasing artifacts. The algorithm uses a one dimensional frequency domain step to deal with the periodic component of the striping artifact and a spatial domain step to handle the aperiodic residue. Several variations of the algorithm have been explored. Results, strengths, and remaining challenges are presented. ?? 2006 IEEE.

Towards quantitative PET/MRI: a review of MR-based attenuation correction techniques.

PubMed

Hofmann, Matthias; Pichler, Bernd; Schölkopf, Bernhard; Beyer, Thomas

2009-03-01

Positron emission tomography (PET) is a fully quantitative technology for imaging metabolic pathways and dynamic processes in vivo. Attenuation correction of raw PET data is a prerequisite for quantification and is typically based on separate transmission measurements. In PET/CT attenuation correction, however, is performed routinely based on the available CT transmission data. Recently, combined PET/magnetic resonance (MR) has been proposed as a viable alternative to PET/CT. Current concepts of PET/MRI do not include CT-like transmission sources and, therefore, alternative methods of PET attenuation correction must be found. This article reviews existing approaches to MR-based attenuation correction (MR-AC). Most groups have proposed MR-AC algorithms for brain PET studies and more recently also for torso PET/MR imaging. Most MR-AC strategies require the use of complementary MR and transmission images, or morphology templates generated from transmission images. We review and discuss these algorithms and point out challenges for using MR-AC in clinical routine. MR-AC is work-in-progress with potentially promising results from a template-based approach applicable to both brain and torso imaging. While efforts are ongoing in making clinically viable MR-AC fully automatic, further studies are required to realize the potential benefits of MR-based motion compensation and partial volume correction of the PET data.

Noise and analyzer-crystal angular position analysis for analyzer-based phase-contrast imaging

NASA Astrophysics Data System (ADS)

Majidi, Keivan; Li, Jun; Muehleman, Carol; Brankov, Jovan G.

2014-04-01

The analyzer-based phase-contrast x-ray imaging (ABI) method is emerging as a potential alternative to conventional radiography. Like many of the modern imaging techniques, ABI is a computed imaging method (meaning that images are calculated from raw data). ABI can simultaneously generate a number of planar parametric images containing information about absorption, refraction, and scattering properties of an object. These images are estimated from raw data acquired by measuring (sampling) the angular intensity profile of the x-ray beam passed through the object at different angular positions of the analyzer crystal. The noise in the estimated ABI parametric images depends upon imaging conditions like the source intensity (flux), measurements angular positions, object properties, and the estimation method. In this paper, we use the Cramér-Rao lower bound (CRLB) to quantify the noise properties in parametric images and to investigate the effect of source intensity, different analyzer-crystal angular positions and object properties on this bound, assuming a fixed radiation dose delivered to an object. The CRLB is the minimum bound for the variance of an unbiased estimator and defines the best noise performance that one can obtain regardless of which estimation method is used to estimate ABI parametric images. The main result of this paper is that the variance (hence the noise) in parametric images is directly proportional to the source intensity and only a limited number of analyzer-crystal angular measurements (eleven for uniform and three for optimal non-uniform) are required to get the best parametric images. The following angular measurements only spread the total dose to the measurements without improving or worsening CRLB, but the added measurements may improve parametric images by reducing estimation bias. Next, using CRLB we evaluate the multiple-image radiography, diffraction enhanced imaging and scatter diffraction enhanced imaging estimation techniques, though the proposed methodology can be used to evaluate any other ABI parametric image estimation technique.

Noise and Analyzer-Crystal Angular Position Analysis for Analyzer-Based Phase-Contrast Imaging

PubMed Central

Majidi, Keivan; Li, Jun; Muehleman, Carol; Brankov, Jovan G.

2014-01-01

The analyzer-based phase-contrast X-ray imaging (ABI) method is emerging as a potential alternative to conventional radiography. Like many of the modern imaging techniques, ABI is a computed imaging method (meaning that images are calculated from raw data). ABI can simultaneously generate a number of planar parametric images containing information about absorption, refraction, and scattering properties of an object. These images are estimated from raw data acquired by measuring (sampling) the angular intensity profile (AIP) of the X-ray beam passed through the object at different angular positions of the analyzer crystal. The noise in the estimated ABI parametric images depends upon imaging conditions like the source intensity (flux), measurements angular positions, object properties, and the estimation method. In this paper, we use the Cramér-Rao lower bound (CRLB) to quantify the noise properties in parametric images and to investigate the effect of source intensity, different analyzer-crystal angular positions and object properties on this bound, assuming a fixed radiation dose delivered to an object. The CRLB is the minimum bound for the variance of an unbiased estimator and defines the best noise performance that one can obtain regardless of which estimation method is used to estimate ABI parametric images. The main result of this manuscript is that the variance (hence the noise) in parametric images is directly proportional to the source intensity and only a limited number of analyzer-crystal angular measurements (eleven for uniform and three for optimal non-uniform) are required to get the best parametric images. The following angular measurements only spread the total dose to the measurements without improving or worsening CRLB, but the added measurements may improve parametric images by reducing estimation bias. Next, using CRLB we evaluate the Multiple-Image Radiography (MIR), Diffraction Enhanced Imaging (DEI) and Scatter Diffraction Enhanced Imaging (S-DEI) estimation techniques, though the proposed methodology can be used to evaluate any other ABI parametric image estimation technique. PMID:24651402

Minimising back reflections from the common path objective in a fundus camera

NASA Astrophysics Data System (ADS)

Swat, A.

2016-11-01

Eliminating back reflections is critical in the design of a fundus camera with internal illuminating system. As there is very little light reflected from the retina, even excellent antireflective coatings are not sufficient suppression of ghost reflections, therefore the number of surfaces in the common optics in illuminating and imaging paths shall be minimised. Typically a single aspheric objective is used. In the paper an alternative approach, an objective with all spherical surfaces, is presented. As more surfaces are required, more sophisticated method is needed to get rid of back reflections. Typically back reflections analysis, comprise treating subsequent objective surfaces as mirrors, and reflections from the objective surfaces are traced back through the imaging path. This approach can be applied in both sequential and nonsequential ray tracing. It is good enough for system check but not very suitable for early optimisation process in the optical system design phase. There are also available standard ghost control merit function operands in the sequential ray-trace, for example in Zemax system, but these don't allow back ray-trace in an alternative optical path, illumination vs. imaging. What is proposed in the paper, is a complete method to incorporate ghost reflected energy into the raytracing system merit function for sequential mode which is more efficient in optimisation process. Although developed for the purpose of specific case of fundus camera, the method might be utilised in a wider range of applications where ghost control is critical.

PET imaging: implications for the future of therapy monitoring with PET/CT in oncology.

PubMed

Tomasi, Giampaolo; Rosso, Lula

2012-10-01

Among the methods based on molecular imaging, the measure of the tracer uptake variation between a baseline and follow-up scan with the SUV and [(18)F]FDG-PET/CT is a very powerful tool for assessing response to treatment in oncology. However, the development of new targeted therapeutics and tissue pharmacokinetic evaluation of existing ones are increasingly requiring therapy monitoring with alternative tracers and indicators. In parallel, the potential predictive and prognostic value of other image-derived parameters, such as tumour volume and textural features, relating to tumoral heterogeneity, has recently emerged from several works. Copyright © 2012 Elsevier Ltd. All rights reserved.

Imaging in living cells using νB-H Raman spectroscopy: monitoring COSAN uptake.

PubMed

Tarrés, Màrius; Canetta, Elisabetta; Viñas, Clara; Teixidor, Francesc; Harwood, Adrian J

2014-03-28

The boron-rich cobaltabisdicarbollide (COSAN) and its 8,8'-I2 derivative (I2-COSAN), both of purely inorganic nature, are shown to accumulate within living cells, where they can be detected using νB-H Raman microspectroscopy. This demonstrates an alternative method for cell labelling and detection.

Imaging brain tumour microstructure.

PubMed

Nilsson, Markus; Englund, Elisabet; Szczepankiewicz, Filip; van Westen, Danielle; Sundgren, Pia C

2018-05-08

Imaging is an indispensable tool for brain tumour diagnosis, surgical planning, and follow-up. Definite diagnosis, however, often demands histopathological analysis of microscopic features of tissue samples, which have to be obtained by invasive means. A non-invasive alternative may be to probe corresponding microscopic tissue characteristics by MRI, or so called 'microstructure imaging'. The promise of microstructure imaging is one of 'virtual biopsy' with the goal to offset the need for invasive procedures in favour of imaging that can guide pre-surgical planning and can be repeated longitudinally to monitor and predict treatment response. The exploration of such methods is motivated by the striking link between parameters from MRI and tumour histology, for example the correlation between the apparent diffusion coefficient and cellularity. Recent microstructure imaging techniques probe even more subtle and specific features, providing parameters associated to cell shape, size, permeability, and volume distributions. However, the range of scenarios in which these techniques provide reliable imaging biomarkers that can be used to test medical hypotheses or support clinical decisions is yet unknown. Accurate microstructure imaging may moreover require acquisitions that go beyond conventional data acquisition strategies. This review covers a wide range of candidate microstructure imaging methods based on diffusion MRI and relaxometry, and explores advantages, challenges, and potential pitfalls in brain tumour microstructure imaging. Copyright © 2018. Published by Elsevier Inc.

Validation of an improved abnormality insertion method for medical image perception investigations

NASA Astrophysics Data System (ADS)

Madsen, Mark T.; Durst, Gregory R.; Caldwell, Robert T.; Schartz, Kevin M.; Thompson, Brad H.; Berbaum, Kevin S.

2009-02-01

The ability to insert abnormalities in clinical tomographic images makes image perception studies with medical images practical. We describe a new insertion technique and its experimental validation that uses complementary image masks to select an abnormality from a library and place it at a desired location. The method was validated using a 4-alternative forced-choice experiment. For each case, four quadrants were simultaneously displayed consisting of 5 consecutive frames of a chest CT with a pulmonary nodule. One quadrant was unaltered, while the other 3 had the nodule from the unaltered quadrant artificially inserted. 26 different sets were generated and repeated with order scrambling for a total of 52 cases. The cases were viewed by radiology staff and residents who ranked each quadrant by realistic appearance. On average, the observers were able to correctly identify the unaltered quadrant in 42% of cases, and identify the unaltered quadrant both times it appeared in 25% of cases. Consensus, defined by a majority of readers, correctly identified the unaltered quadrant in only 29% of 52 cases. For repeats, the consensus observer successfully identified the unaltered quadrant only once. We conclude that the insertion method can be used to reliably place abnormalities in perception experiments.

Pattern-histogram-based temporal change detection using personal chest radiographs

NASA Astrophysics Data System (ADS)

Ugurlu, Yucel; Obi, Takashi; Hasegawa, Akira; Yamaguchi, Masahiro; Ohyama, Nagaaki

1999-05-01

An accurate and reliable detection of temporal changes from a pair of images has considerable interest in the medical science. Traditional registration and subtraction techniques can be applied to extract temporal differences when,the object is rigid or corresponding points are obvious. However, in radiological imaging, loss of the depth information, the elasticity of object, the absence of clearly defined landmarks and three-dimensional positioning differences constraint the performance of conventional registration techniques. In this paper, we propose a new method in order to detect interval changes accurately without using an image registration technique. The method is based on construction of so-called pattern histogram and comparison procedure. The pattern histogram is a graphic representation of the frequency counts of all allowable patterns in the multi-dimensional pattern vector space. K-means algorithm is employed to partition pattern vector space successively. Any differences in the pattern histograms imply that different patterns are involved in the scenes. In our experiment, a pair of chest radiographs of pneumoconiosis is employed and the changing histogram bins are visualized on both of the images. We found that the method can be used as an alternative way of temporal change detection, particularly when the precise image registration is not available.

Reduced-illuminance autofluorescence imaging in ABCA4-associated retinal degenerations

NASA Astrophysics Data System (ADS)

Cideciyan, Artur V.; Swider, Malgorzata; Aleman, Tomas S.; Roman, Marisa I.; Sumaroka, Alexander; Schwartz, Sharon B.; Stone, Edwin M.; Jacobson, Samuel G.

2007-05-01

The health of the retinal pigment epithelium (RPE) can be estimated with autofluorescence (AF) imaging of lipofuscin, which accumulates as a byproduct of retinal exposure to light. Lipofuscin may be toxic to the RPE, and its toxicity may be enhanced by short-wavelength (SW) illumination. The high-intensity and SW excitation light used in conventional AF imaging could, at least in principle, increase the rate of lipofuscin accumulation and/or increase its toxicity. We considered two reduced-illuminance AF imaging (RAFI) methods as alternatives to conventional AF imaging. RAFI methods use either near-infrared (NIR) light or reduced-radiance SW illumination for excitation of fluorophores. We quantified the distribution of RAFI signals in relation to retinal structure and function in patients with the prototypical lipofuscin accumulation disease caused by mutations in ABCA4. There was evidence for two subclinical stages of macular ABCA4 disease involving hyperautofluorescence of both SW- and NIR-RAFI with and without associated loss of visual function. Use of RAFI methods and microperimetry in future clinical trials involving lipofuscinopathies should allow quantification of subclinical disease expression and progression without subjecting the diseased retina/RPE to undue light exposure.

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.

Thermal Imaging Is a Noninvasive Alternative to PET/CT for Measurement of Brown Adipose Tissue Activity in Humans

PubMed Central

Law, James; Morris, David E.; Izzi-Engbeaya, Chioma; Salem, Victoria; Coello, Christopher; Robinson, Lindsay; Jayasinghe, Maduka; Scott, Rebecca; Gunn, Roger; Rabiner, Eugenii; Tan, Tricia; Dhillo, Waljit S.; Bloom, Stephen; Budge, Helen

2018-01-01

Obesity and its metabolic consequences are a major cause of morbidity and mortality. Brown adipose tissue (BAT) utilizes glucose and free fatty acids to produce heat, thereby increasing energy expenditure. Effective evaluation of human BAT stimulators is constrained by the current standard method of assessing BAT—PET/CT—as it requires exposure to high doses of ionizing radiation. Infrared thermography (IRT) is a potential noninvasive, safe alternative, although direct corroboration with PET/CT has not been established. Methods: IRT and 18F-FDG PET/CT data from 8 healthy men subjected to water-jacket cooling were directly compared. Thermal images were geometrically transformed to overlay PET/CT-derived maximum intensity projection (MIP) images from each subject, and the areas with the most intense temperature and glucose uptake within the supraclavicular regions were compared. Relationships between supraclavicular temperatures (TSCR) from IRT and the metabolic rate of glucose uptake (MR(gluc)) from PET/CT were determined. Results: Glucose uptake on MR(gluc)MIP was found to correlate positively with a change in TSCR relative to a reference region (r2 = 0.721; P = 0.008). Spatial overlap between areas of maximal MR(gluc)MIP and maximal TSCR was 29.5% ± 5.1%. Prolonged cooling, for 60 min, was associated with a further TSCR rise, compared with cooling for 10 min. Conclusion: The supraclavicular hotspot identified on IRT closely corresponded to the area of maximal uptake on PET/CT-derived MR(gluc)MIP images. Greater increases in relative TSCR were associated with raised glucose uptake. IRT should now be considered a suitable method for measuring BAT activation, especially in populations for whom PET/CT is not feasible, practical, or repeatable. PMID:28912148

Algorithm and Application of Gcp-Independent Block Adjustment for Super Large-Scale Domestic High Resolution Optical Satellite Imagery

NASA Astrophysics Data System (ADS)

Sun, Y. S.; Zhang, L.; Xu, B.; Zhang, Y.

2018-04-01

The accurate positioning of optical satellite image without control is the precondition for remote sensing application and small/medium scale mapping in large abroad areas or with large-scale images. In this paper, aiming at the geometric features of optical satellite image, based on a widely used optimization method of constraint problem which is called Alternating Direction Method of Multipliers (ADMM) and RFM least-squares block adjustment, we propose a GCP independent block adjustment method for the large-scale domestic high resolution optical satellite image - GISIBA (GCP-Independent Satellite Imagery Block Adjustment), which is easy to parallelize and highly efficient. In this method, the virtual "average" control points are built to solve the rank defect problem and qualitative and quantitative analysis in block adjustment without control. The test results prove that the horizontal and vertical accuracy of multi-covered and multi-temporal satellite images are better than 10 m and 6 m. Meanwhile the mosaic problem of the adjacent areas in large area DOM production can be solved if the public geographic information data is introduced as horizontal and vertical constraints in the block adjustment process. Finally, through the experiments by using GF-1 and ZY-3 satellite images over several typical test areas, the reliability, accuracy and performance of our developed procedure will be presented and studied in this paper.

Mismatch removal via coherent spatial relations

NASA Astrophysics Data System (ADS)

Chen, Jun; Ma, Jiayi; Yang, Changcai; Tian, Jinwen

2014-07-01

We propose a method for removing mismatches from the given putative point correspondences in image pairs based on "coherent spatial relations." Under the Bayesian framework, we formulate our approach as a maximum likelihood problem and solve a coherent spatial relation between the putative point correspondences using an expectation-maximization (EM) algorithm. Our approach associates each point correspondence with a latent variable indicating it as being either an inlier or an outlier, and alternatively estimates the inlier set and recovers the coherent spatial relation. It can handle not only the case of image pairs with rigid motions but also the case of image pairs with nonrigid motions. To parameterize the coherent spatial relation, we choose two-view geometry and thin-plate spline as models for rigid and nonrigid cases, respectively. The mismatches could be successfully removed via the coherent spatial relations after the EM algorithm converges. The quantitative results on various experimental data demonstrate that our method outperforms many state-of-the-art methods, it is not affected by low initial correct match percentages, and is robust to most geometric transformations including a large viewing angle, image rotation, and affine transformation.

Non-contact method of search and analysis of pulsating vessels

NASA Astrophysics Data System (ADS)

Avtomonov, Yuri N.; Tsoy, Maria O.; Postnov, Dmitry E.

2018-04-01

Despite the variety of existing methods of recording the human pulse and a solid history of their development, there is still considerable interest in this topic. The development of new non-contact methods, based on advanced image processing, caused a new wave of interest in this issue. We present a simple but quite effective method for analyzing the mechanical pulsations of blood vessels lying close to the surface of the skin. Our technique is a modification of imaging (or remote) photoplethysmography (i-PPG). We supplemented this method with the addition of a laser light source, which made it possible to use other methods of searching for the proposed pulsation zone. During the testing of the method, several series of experiments were carried out with both artificial oscillating objects as well as with the target signal source (human wrist). The obtained results show that our method allows correct interpretation of complex data. To summarize, we proposed and tested an alternative method for the search and analysis of pulsating vessels.

Functional Cardiac Magnetic Resonance Imaging (MRI) in the Assessment of Myocardial Viability and Perfusion

PubMed Central

2003-01-01

Executive Summary Objective The objective of this health technology policy assessment was to determine the effectiveness safety and cost-effectiveness of using functional cardiac magnetic resonance imaging (MRI) for the assessment of myocardial viability and perfusion in patients with coronary artery disease and left ventricular dysfunction. Results Functional MRI has become increasingly investigated as a noninvasive method for assessing myocardial viability and perfusion. Most patients in the published literature have mild to moderate impaired LV function. It is possible that the severity of LV dysfunction may be an important factor that can alter the diagnostic accuracy of imaging techniques. There is some evidence of comparable or better performance of functional cardiac MRI for the assessment of myocardial viability and perfusion compared with other imaging techniques. However limitations to most of the studies included: Functional cardiac MRI studies that assess myocardial viability and perfusion have had small sample sizes. Some studies assessed myocardial viability/perfusion in patients who had already undergone revascularization, or excluded patients with a prior MI (Schwitter et al., 2001). Lack of explicit detail of patient recruitment. Patients with LVEF >35%. Interstudy variability in post MI imaging time(including acute or chronic MI), when patients with a prior MI were included. Poor interobserver agreement (kappa statistic) in the interpretation of the results. Traditionally, 0.80 is considered “good”. Cardiac MRI measurement of myocardial perfusion to as an adjunct tool to help diagnose CAD (prior to a definitive coronary angiography) has also been examined in some studies, with methodological limitations, yielding comparable results. Many studies examining myocardial viability and perfusion report on the accuracy of imaging methods with limited data on long-term patient outcome and management. Kim et al. (2000) revealed that the transmural extent of hyperenhancement was significantly related to the likelihood of improvement in contractility after revascularization. However, the LVEF in the patient population was 43% prior to revascularization. It is important to know whether the technique has the same degree of accuracy in patients who have more severe LV dysfunction and who would most benefit from an assessment of myocardial viability. “Substantial” viability used as a measure of a patient’s ability to recover after revascularization has not been definitively reported (how much viability is enough?). Patients with severe LV dysfunction are more likely to have mixtures of surviving myocardium, including normal, infarcted, stunned and hibernating myocardium (Cowley et al., 1999). This may lead to a lack of homogeneity of response to testing and to revascularization and contribute to inter- and intra-study differences. There is a need for a large prospective study with adequate follow-up time for patients with CAD and LV dysfunction (LVEF<35%) comparing MRI and an alternate imaging technique. There is some evidence that MRI has comparable sensitivity, specificity and accuracy to PET for determining myocardial viability. However, there is a lack of evidence comparing the accuracy of these two techniques to predict LV function recovery. In addition, some studies refer to PET as the gold standard for the assessment of myocardial viability. Therefore, PET may be an ideal noninvasive imaging comparator to MRI for a prospective study with follow-up. To date, there is a lack of cost-effectiveness analyses (or any economic analyses) of functional cardiac MRI versus an alternate noninvasive imaging method for the assessment of myocardial viability/perfusion. Conclusion There is some evidence that the accuracy of functional cardiac MRI compares favourably with alternate imaging techniques for the assessment of myocardial viability and perfusion. There is insufficient evidence whether functional cardiac MRI can better select which patients [who have CAD and severe LV dysfunction (LVEF <35%)] may benefit from revascularization compared with an alternate noninvasive imaging technology. There is insufficient evidence whether functional cardiac MRI can better select which patients should proceed to invasive coronary angiography for the definitive diagnosis of CAD, compared with an alternate noninvasive imaging technology. There is a need for a large prospective (potentially multicentre) study with adequate follow-up time for patients with CAD and LV dysfunction (LVEF<35%) comparing MRI and PET. Since longer follow-up time may be associated with restenosis or graft occlusion, it has been suggested to have serial measurements after revascularization (Cowley et al., 1999). PMID:23074446

Distributed deep learning networks among institutions for medical imaging.

PubMed

Chang, Ken; Balachandar, Niranjan; Lam, Carson; Yi, Darvin; Brown, James; Beers, Andrew; Rosen, Bruce; Rubin, Daniel L; Kalpathy-Cramer, Jayashree

2018-03-29

Deep learning has become a promising approach for automated support for clinical diagnosis. When medical data samples are limited, collaboration among multiple institutions is necessary to achieve high algorithm performance. However, sharing patient data often has limitations due to technical, legal, or ethical concerns. In this study, we propose methods of distributing deep learning models as an attractive alternative to sharing patient data. We simulate the distribution of deep learning models across 4 institutions using various training heuristics and compare the results with a deep learning model trained on centrally hosted patient data. The training heuristics investigated include ensembling single institution models, single weight transfer, and cyclical weight transfer. We evaluated these approaches for image classification in 3 independent image collections (retinal fundus photos, mammography, and ImageNet). We find that cyclical weight transfer resulted in a performance that was comparable to that of centrally hosted patient data. We also found that there is an improvement in the performance of cyclical weight transfer heuristic with a high frequency of weight transfer. We show that distributing deep learning models is an effective alternative to sharing patient data. This finding has implications for any collaborative deep learning study.

High energy X-ray phase and dark-field imaging using a random absorption mask.

PubMed

Wang, Hongchang; Kashyap, Yogesh; Cai, Biao; Sawhney, Kawal

2016-07-28

High energy X-ray imaging has unique advantage over conventional X-ray imaging, since it enables higher penetration into materials with significantly reduced radiation damage. However, the absorption contrast in high energy region is considerably low due to the reduced X-ray absorption cross section for most materials. Even though the X-ray phase and dark-field imaging techniques can provide substantially increased contrast and complementary information, fabricating dedicated optics for high energies still remain a challenge. To address this issue, we present an alternative X-ray imaging approach to produce transmission, phase and scattering signals at high X-ray energies by using a random absorption mask. Importantly, in addition to the synchrotron radiation source, this approach has been demonstrated for practical imaging application with a laboratory-based microfocus X-ray source. This new imaging method could be potentially useful for studying thick samples or heavy materials for advanced research in materials science.

Optical Imaging of Ionizing Radiation from Clinical Sources.

PubMed

Shaffer, Travis M; Drain, Charles Michael; Grimm, Jan

2016-11-01

Nuclear medicine uses ionizing radiation for both in vivo diagnosis and therapy. Ionizing radiation comes from a variety of sources, including x-rays, beam therapy, brachytherapy, and various injected radionuclides. Although PET and SPECT remain clinical mainstays, optical readouts of ionizing radiation offer numerous benefits and complement these standard techniques. Furthermore, for ionizing radiation sources that cannot be imaged using these standard techniques, optical imaging offers a unique imaging alternative. This article reviews optical imaging of both radionuclide- and beam-based ionizing radiation from high-energy photons and charged particles through mechanisms including radioluminescence, Cerenkov luminescence, and scintillation. Therapeutically, these visible photons have been combined with photodynamic therapeutic agents preclinically for increasing therapeutic response at depths difficult to reach with external light sources. Last, new microscopy methods that allow single-cell optical imaging of radionuclides are reviewed. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Detection systems for mass spectrometry imaging: a perspective on novel developments with a focus on active pixel detectors.

PubMed

Jungmann, Julia H; Heeren, Ron M A

2013-01-15

Instrumental developments for imaging and individual particle detection for biomolecular mass spectrometry (imaging) and fundamental atomic and molecular physics studies are reviewed. Ion-counting detectors, array detection systems and high mass detectors for mass spectrometry (imaging) are treated. State-of-the-art detection systems for multi-dimensional ion, electron and photon detection are highlighted. Their application and performance in three different imaging modes--integrated, selected and spectral image detection--are described. Electro-optical and microchannel-plate-based systems are contrasted. The analytical capabilities of solid-state pixel detectors--both charge coupled device (CCD) and complementary metal oxide semiconductor (CMOS) chips--are introduced. The Medipix/Timepix detector family is described as an example of a CMOS hybrid active pixel sensor. Alternative imaging methods for particle detection and their potential for future applications are investigated. Copyright © 2012 John Wiley & Sons, Ltd.

A Novel Pairwise Comparison-Based Method to Determine Radiation Dose Reduction Potentials of Iterative Reconstruction Algorithms, Exemplified Through Circle of Willis Computed Tomography Angiography.

PubMed

Ellmann, Stephan; Kammerer, Ferdinand; Brand, Michael; Allmendinger, Thomas; May, Matthias S; Uder, Michael; Lell, Michael M; Kramer, Manuel

2016-05-01

The aim of this study was to determine the dose reduction potential of iterative reconstruction (IR) algorithms in computed tomography angiography (CTA) of the circle of Willis using a novel method of evaluating the quality of radiation dose-reduced images. This study relied on ReconCT, a proprietary reconstruction software that allows simulating CT scans acquired with reduced radiation dose based on the raw data of true scans. To evaluate the performance of ReconCT in this regard, a phantom study was performed to compare the image noise of true and simulated scans within simulated vessels of a head phantom. That followed, 10 patients scheduled for CTA of the circle of Willis were scanned according to our institute's standard protocol (100 kV, 145 reference mAs). Subsequently, CTA images of these patients were reconstructed as either a full-dose weighted filtered back projection or with radiation dose reductions down to 10% of the full-dose level and Sinogram-Affirmed Iterative Reconstruction (SAFIRE) with either strength 3 or 5. Images were marked with arrows pointing on vessels of different sizes, and image pairs were presented to observers. Five readers assessed image quality with 2-alternative forced choice comparisons. In the phantom study, no significant differences were observed between the noise levels of simulated and true scans in filtered back projection, SAFIRE 3, and SAFIRE 5 reconstructions.The dose reduction potential for patient scans showed a strong dependence on IR strength as well as on the size of the vessel of interest. Thus, the potential radiation dose reductions ranged from 84.4% for the evaluation of great vessels reconstructed with SAFIRE 5 to 40.9% for the evaluation of small vessels reconstructed with SAFIRE 3. This study provides a novel image quality evaluation method based on 2-alternative forced choice comparisons. In CTA of the circle of Willis, higher IR strengths and greater vessel sizes allowed higher degrees of radiation dose reduction.

Super-Resolution Image Reconstruction Applied to Medical Ultrasound

NASA Astrophysics Data System (ADS)

Ellis, Michael

Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in vivo images of a human testicle. In all instances, the methods presented here outperform conventional image reconstruction methods by a significant margin. As TONE and its variants are general image reconstruction techniques, the theories and research presented here have the potential to significantly improve not only ultrasound's clinical utility, but that of other imaging modalities as well.

The L0 Regularized Mumford-Shah Model for Bias Correction and Segmentation of Medical Images.

PubMed

Duan, Yuping; Chang, Huibin; Huang, Weimin; Zhou, Jiayin; Lu, Zhongkang; Wu, Chunlin

2015-11-01

We propose a new variant of the Mumford-Shah model for simultaneous bias correction and segmentation of images with intensity inhomogeneity. First, based on the model of images with intensity inhomogeneity, we introduce an L0 gradient regularizer to model the true intensity and a smooth regularizer to model the bias field. In addition, we derive a new data fidelity using the local intensity properties to allow the bias field to be influenced by its neighborhood. Second, we use a two-stage segmentation method, where the fast alternating direction method is implemented in the first stage for the recovery of true intensity and bias field and a simple thresholding is used in the second stage for segmentation. Different from most of the existing methods for simultaneous bias correction and segmentation, we estimate the bias field and true intensity without fixing either the number of the regions or their values in advance. Our method has been validated on medical images of various modalities with intensity inhomogeneity. Compared with the state-of-art approaches and the well-known brain software tools, our model is fast, accurate, and robust with initializations.

In vivo mapping of current density distribution in brain tissues during deep brain stimulation (DBS)

NASA Astrophysics Data System (ADS)

Sajib, Saurav Z. K.; Oh, Tong In; Kim, Hyung Joong; Kwon, Oh In; Woo, Eung Je

2017-01-01

New methods for in vivo mapping of brain responses during deep brain stimulation (DBS) are indispensable to secure clinical applications. Assessment of current density distribution, induced by internally injected currents, may provide an alternative method for understanding the therapeutic effects of electrical stimulation. The current flow and pathway are affected by internal conductivity, and can be imaged using magnetic resonance-based conductivity imaging methods. Magnetic resonance electrical impedance tomography (MREIT) is an imaging method that can enable highly resolved mapping of electromagnetic tissue properties such as current density and conductivity of living tissues. In the current study, we experimentally imaged current density distribution of in vivo canine brains by applying MREIT to electrical stimulation. The current density maps of three canine brains were calculated from the measured magnetic flux density data. The absolute current density values of brain tissues, including gray matter, white matter, and cerebrospinal fluid were compared to assess the active regions during DBS. The resulting current density in different tissue types may provide useful information about current pathways and volume activation for adjusting surgical planning and understanding the therapeutic effects of DBS.

Detection of fresh bruises in apples by structured-illumination reflectance imaging

NASA Astrophysics Data System (ADS)

Lu, Yuzhen; Li, Richard; Lu, Renfu

2016-05-01

Detection of fresh bruises in apples remains a challenging task due to the absence of visual symptoms and significant chemical alterations of fruit tissues during the initial stage after the fruit have been bruised. This paper reports on a new structured-illumination reflectance imaging (SIRI) technique for enhanced detection of fresh bruises in apples. Using a digital light projector engine, sinusoidally-modulated illumination at the spatial frequencies of 50, 100, 150 and 200 cycles/m was generated. A digital camera was then used to capture the reflectance images from `Gala' and `Jonagold' apples, immediately after they had been subjected to two levels of bruising by impact tests. A conventional three-phase demodulation (TPD) scheme was applied to the acquired images for obtaining the planar (direct component or DC) and amplitude (alternating component or AC) images. Bruises were identified in the amplitude images with varying image contrasts, depending on spatial frequency. The bruise visibility was further enhanced through post-processing of the amplitude images. Furthermore, three spiral phase transform (SPT)-based demodulation methods, using single and two images and two phase-shifted images, were proposed for obtaining AC images. Results showed that the demodulation methods greatly enhanced the contrast and spatial resolution of the AC images, making it feasible to detect the fresh bruises that, otherwise, could not be achieved by conventional imaging technique with planar or uniform illumination. The effectiveness of image enhancement, however, varied with spatial frequency. Both 2-image and 2-phase SPT methods achieved the performance similar to that by conventional TPD. SIRI technique has demonstrated the capability of detecting fresh bruises in apples, and it has the potential as a new imaging modality for enhancing food quality and safety detection.

GPU-Based Real-Time Volumetric Ultrasound Image Reconstruction for a Ring Array

PubMed Central

Choe, Jung Woo; Nikoozadeh, Amin; Oralkan, Ömer; Khuri-Yakub, Butrus T.

2014-01-01

Synthetic phased array (SPA) beamforming with Hadamard coding and aperture weighting is an optimal option for real-time volumetric imaging with a ring array, a particularly attractive geometry in intracardiac and intravascular applications. However, the imaging frame rate of this method is limited by the immense computational load required in synthetic beamforming. For fast imaging with a ring array, we developed graphics processing unit (GPU)-based, real-time image reconstruction software that exploits massive data-level parallelism in beamforming operations. The GPU-based software reconstructs and displays three cross-sectional images at 45 frames per second (fps). This frame rate is 4.5 times higher than that for our previously-developed multi-core CPU-based software. In an alternative imaging mode, it shows one B-mode image rotating about the axis and its maximum intensity projection (MIP), processed at a rate of 104 fps. This paper describes the image reconstruction procedure on the GPU platform and presents the experimental images obtained using this software. PMID:23529080

Low-cost high-resolution fast spin-echo MR of acoustic schwannoma: an alternative to enhanced conventional spin-echo MR?

PubMed

Allen, R W; Harnsberger, H R; Shelton, C; King, B; Bell, D A; Miller, R; Parkin, J L; Apfelbaum, R I; Parker, D

1996-08-01

To determine whether unenhanced high-resolution T2-weighted fast spin-echo MR imaging provides an acceptable and less expensive alternative to contrast-enhanced conventional T1-weighted spin-echo MR techniques in the diagnosis of acoustic schwannoma. We reviewed in a blinded fashion the records of 25 patients with pathologically documented acoustic schwannoma and of 25 control subjects, all of whom had undergone both enhanced conventional spin-echo MR imaging and unenhanced fast spin-echo MR imaging of the cerebellopontine angle/internal auditory canal region. The patients were imaged with the use of a quadrature head receiver coil for the conventional spin-echo sequences and dual 3-inch phased-array receiver coils for the fast spin-echo sequences. The size of the acoustic schwannomas ranged from 2 to 40 mm in maximum dimension. The mean maximum diameter was 12 mm, and 12 neoplasms were less than 10 mm in diameter. Acoustic schwannoma was correctly diagnosed on 98% of the fast spin-echo images and on 100% of the enhanced conventional spin-echo images. Statistical analysis of the data using the kappa coefficient demonstrated agreement beyond chance between these two imaging techniques for the diagnosis of acoustic schwannoma. There is no statistically significant difference in the sensitivity and specificity of unenhanced high-resolution fast spin-echo imaging and enhance T1-weighted conventional spin-echo imaging in the detection of acoustic schwannoma. We believe that the unenhanced high-resolution fast spin-echo technique provides a cost-effective method for the diagnosis of acoustic schwannoma.

Rapid contrast evaluation method based on affinity beads and backscattered electron imaging for the screening of electron stains.

PubMed

Kaku, Hiroki; Inoue, Kanako; Muranaka, Yoshinori; Park, Pyoyun; Ikeda, Kenichi

2015-10-01

Uranyl salts are toxic and radioactive; therefore, several studies have been conducted to screen for substitutes of electron stains. In this regard, the contrast evaluation process is time consuming and the results obtained are inconsistent. In this study, we developed a novel contrast evaluation method using affinity beads and a backscattered electron image (BSEI), obtained using scanning electron microscopy. The contrast ratios of BSEI in each electron stain treatment were correlated with those of transmission electron microscopic images. The affinity beads bound to cell components independently. Protein and DNA samples were enhanced by image contrast treated with electron stains; however, this was not observed for sugars. Protein-conjugated beads showed an additive effect of image contrast when double-stained with lead. However, additive effect of double staining was not observed in DNA-conjugated beads. The varying chemical properties of oligopeptides showed differences in image contrast when treated with each electron stain. This BSEI-based evaluation method not only enables screening for alternate electron stains, but also helps analyze the underlying mechanisms of electron staining of cellular structures. © The Author 2015. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Fast segmentation of industrial quality pavement images using Laws texture energy measures and k -means clustering

NASA Astrophysics Data System (ADS)

Mathavan, Senthan; Kumar, Akash; Kamal, Khurram; Nieminen, Michael; Shah, Hitesh; Rahman, Mujib

2016-09-01

Thousands of pavement images are collected by road authorities daily for condition monitoring surveys. These images typically have intensity variations and texture nonuniformities that make their segmentation challenging. The automated segmentation of such pavement images is crucial for accurate, thorough, and expedited health monitoring of roads. In the pavement monitoring area, well-known texture descriptors, such as gray-level co-occurrence matrices and local binary patterns, are often used for surface segmentation and identification. These, despite being the established methods for texture discrimination, are inherently slow. This work evaluates Laws texture energy measures as a viable alternative for pavement images for the first time. k-means clustering is used to partition the feature space, limiting the human subjectivity in the process. Data classification, hence image segmentation, is performed by the k-nearest neighbor method. Laws texture energy masks are shown to perform well with resulting accuracy and precision values of more than 80%. The implementations of the algorithm, in both MATLAB® and OpenCV/C++, are extensively compared against the state of the art for execution speed, clearly showing the advantages of the proposed method. Furthermore, the OpenCV-based segmentation shows a 100% increase in processing speed when compared to the fastest algorithm available in literature.

Robust registration of sparsely sectioned histology to ex-vivo MRI of temporal lobe resections

NASA Astrophysics Data System (ADS)

Goubran, Maged; Khan, Ali R.; Crukley, Cathie; Buchanan, Susan; Santyr, Brendan; deRibaupierre, Sandrine; Peters, Terry M.

2012-02-01

Surgical resection of epileptic foci is a typical treatment for drug-resistant epilepsy, however, accurate preoperative localization is challenging and often requires invasive sub-dural or intra-cranial electrode placement. The presence of cellular abnormalities in the resected tissue can be used to validate the effectiveness of multispectralMagnetic Resonance Imaging (MRI) in pre-operative foci localization and surgical planning. If successful, these techniques can lead to improved surgical outcomes and less invasive procedures. Towards this goal, a novel pipeline is presented here for post-operative imaging of temporal lobe specimens involving MRI and digital histology, and present and evaluate methods for bringing these images into spatial correspondence. The sparsely-sectioned histology images of resected tissue represents a challenge for 3D reconstruction which we address with a combined 3D and 2D rigid registration algorithm that alternates between slice-based and volume-based registration with the ex-vivo MRI. We also evaluate four methods for non-rigid within-plane registration using both images and fiducials, with the top performing method resulting in a target registration error of 0.87 mm. This work allows for the spatially-local comparison of histology with post-operative MRI and paves the way for eventual registration with pre-operative MRI images.

F-18 Choline PET angiography of the pelvic arteries: evaluation of image quality and comparison with contrast-enhanced CT.

PubMed

Freesmeyer, Martin; Drescher, Robert

2015-01-01

The purpose was to show the feasibility of F-18 choline positron emission tomography (PET) angiography for the evaluation of abdominal and iliac arteries. Thirty-five patients were examined and image quality was scored. Findings were correlated with contrast-enhanced computed tomography. Image quality was best in the aorta and common iliac arteries (100% and 93% of vessels). Negative predictive values of PET angiography were excellent (100%), and positive predictive values were impaired by disease overestimation. PET angiography is technically feasible and of good image quality in large arteries. In selected cases, it may become an alternative to established angiographic methods. Copyright © 2015 Elsevier Inc. All rights reserved.

Spherical gradient-index lenses as perfect imaging and maximum power transfer devices.

PubMed

Gordon, J M

2000-08-01

Gradient-index lenses can be viewed from the perspectives of both imaging and nonimaging optics, that is, in terms of both image fidelity and achievable flux concentration. The simple class of gradient-index lenses with spherical symmetry, often referred to as modified Luneburg lenses, is revisited. An alternative derivation for established solutions is offered; the method of Fermat's strings and the principle of skewness conservation are invoked. Then these nominally perfect imaging devices are examined from the additional vantage point of power transfer, and the degree to which they realize the thermodynamic limit to flux concentration is determined. Finally, the spherical gradient-index lens of the fish eye is considered as a modified Luneburg lens optimized subject to material constraints.

Polycrystalline lead selenide: the resurgence of an old infrared detector

NASA Astrophysics Data System (ADS)

Vergara, G.; Montojo, M. T.; Torquemada, M. C.; Rodrigo, M. T.; Sánchez, F. J.; Gómez, L. J.; Almazán, R. M.; Verdú, M.; Rodríguez, P.; Villamayor, V.; Álvarez, M.; Diezhandino, J.; Plaza, J.; Catalán, I.

2007-06-01

The existing technology for uncooled MWIR photon detectors based on polycrystalline lead salts is stigmatized for being a 50-year-old technology. It has been traditionally relegated to single-element detectors and relatively small linear arrays due to the limitations imposed by its standard manufacture process based on a chemical bath deposition technique (CBD) developed more than 40 years ago. Recently, an innovative method for processing detectors, based on a vapour phase deposition (VPD) technique, has allowed manufacturing the first 2D array of polycrystalline PbSe with good electro optical characteristics. The new method of processing PbSe is an all silicon technology and it is compatible with standard CMOS circuitry. In addition to its affordability, VPD PbSe constitutes a perfect candidate to fill the existing gap in the photonic and uncooled IR imaging detectors sensitive to the MWIR photons. The perspectives opened are numerous and very important, converting the old PbSe detector in a serious alternative to others uncooled technologies in the low cost IR detection market. The number of potential applications is huge, some of them with high commercial impact such as personal IR imagers, enhanced vision systems for automotive applications and other not less important in the security/defence domain such as sensors for active protection systems (APS) or low cost seekers. Despite the fact, unanimously accepted, that uncooled will dominate the majority of the future IR detection applications, today, thermal detectors are the unique plausible alternative. There is plenty of room for photonic uncooled and complementary alternatives are needed. This work allocates polycrystalline PbSe in the current panorama of the uncooled IR detectors, underlining its potentiality in two areas of interest, i.e., very low cost imaging IR detectors and MWIR fast uncooled detectors for security and defence applications. The new method of processing again converts PbSe into an emerging technology.

Towards automatic computer-aided knee surgery by innovative methods for processing the femur surface model.

PubMed

Cerveri, Pietro; Marchente, Mario; Bartels, Ward; Corten, Kristoff; Simon, Jean-Pierre; Manzotti, Alfonso

2010-09-01

The femoral shaft (FDA) and transepicondylar (TA), anterior-posterior (WL) and posterior condylar (PCL) axes are fundamental quantities in planning knee arthroplasty surgery. As an alternative to the TA, we introduce the anatomical flexion axis (AFA). Obtaining such axes from image data without any manual supervision remains a practical objective. We propose a novel method that automatically computes the axes of the distal femur by processing the femur mesh surface. Surface data were processed by exploiting specific geometric, anatomical and functional properties. Robust ellipse fitting of the two-dimensional (2D) condylar profiles was utilized to determine the AFA alternative to the TA. The repeatability of the method was tested upon 20 femur surfaces reconstructed from CT scans taken on cadavers. At the highest surface resolutions, the relative median error in the direction of the FDA, AFA, PCL, WL and TA was < 0.50 degrees, 1.20 degrees, 1.0 degrees, 1.30 degrees and 1.50 degrees, respectively. As expected, at the lowest surface resolution, the repeatability decreased to 1.20 degrees, 2.70 degrees, 3.30 degrees, 3.0 degrees and 4.70 degrees, respectively. The computed directions of the FDA, PCL, WL and TA were in agreement (0.60 degrees, 1.55 degrees, 1.90 degrees, 2.40 degrees) with the corresponding reference parameters manually identified in the original CT images by medical experts and with the literature. The proposed method proved that: (a) the AFA can be robustly computed by a geometrical analysis of the posterior profiles of the two condyles and can be considered a useful alternative to the TA; (b) higher surface resolutions leads to higher repeatability of all computed quantities; (c) the TA is less repeatable than the other axes. Copyright 2010 John Wiley & Sons, Ltd.

Task-based statistical image reconstruction for high-quality cone-beam CT

NASA Astrophysics Data System (ADS)

Dang, Hao; Webster Stayman, J.; Xu, Jennifer; Zbijewski, Wojciech; Sisniega, Alejandro; Mow, Michael; Wang, Xiaohui; Foos, David H.; Aygun, Nafi; Koliatsos, Vassilis E.; Siewerdsen, Jeffrey H.

2017-11-01

Task-based analysis of medical imaging performance underlies many ongoing efforts in the development of new imaging systems. In statistical image reconstruction, regularization is often formulated in terms to encourage smoothness and/or sharpness (e.g. a linear, quadratic, or Huber penalty) but without explicit formulation of the task. We propose an alternative regularization approach in which a spatially varying penalty is determined that maximizes task-based imaging performance at every location in a 3D image. We apply the method to model-based image reconstruction (MBIR—viz., penalized weighted least-squares, PWLS) in cone-beam CT (CBCT) of the head, focusing on the task of detecting a small, low-contrast intracranial hemorrhage (ICH), and we test the performance of the algorithm in the context of a recently developed CBCT prototype for point-of-care imaging of brain injury. Theoretical predictions of local spatial resolution and noise are computed via an optimization by which regularization (specifically, the quadratic penalty strength) is allowed to vary throughout the image to maximize local task-based detectability index ({{d}\\prime} ). Simulation studies and test-bench experiments were performed using an anthropomorphic head phantom. Three PWLS implementations were tested: conventional (constant) penalty; a certainty-based penalty derived to enforce constant point-spread function, PSF; and the task-based penalty derived to maximize local detectability at each location. Conventional (constant) regularization exhibited a fairly strong degree of spatial variation in {{d}\\prime} , and the certainty-based method achieved uniform PSF, but each exhibited a reduction in detectability compared to the task-based method, which improved detectability up to ~15%. The improvement was strongest in areas of high attenuation (skull base), where the conventional and certainty-based methods tended to over-smooth the data. The task-driven reconstruction method presents a promising regularization method in MBIR by explicitly incorporating task-based imaging performance as the objective. The results demonstrate improved ICH conspicuity and support the development of high-quality CBCT systems.

General phase regularized reconstruction using phase cycling.

PubMed

Ong, Frank; Cheng, Joseph Y; Lustig, Michael

2018-07-01

To develop a general phase regularized image reconstruction method, with applications to partial Fourier imaging, water-fat imaging and flow imaging. The problem of enforcing phase constraints in reconstruction was studied under a regularized inverse problem framework. A general phase regularized reconstruction algorithm was proposed to enable various joint reconstruction of partial Fourier imaging, water-fat imaging and flow imaging, along with parallel imaging (PI) and compressed sensing (CS). Since phase regularized reconstruction is inherently non-convex and sensitive to phase wraps in the initial solution, a reconstruction technique, named phase cycling, was proposed to render the overall algorithm invariant to phase wraps. The proposed method was applied to retrospectively under-sampled in vivo datasets and compared with state of the art reconstruction methods. Phase cycling reconstructions showed reduction of artifacts compared to reconstructions without phase cycling and achieved similar performances as state of the art results in partial Fourier, water-fat and divergence-free regularized flow reconstruction. Joint reconstruction of partial Fourier + water-fat imaging + PI + CS, and partial Fourier + divergence-free regularized flow imaging + PI + CS were demonstrated. The proposed phase cycling reconstruction provides an alternative way to perform phase regularized reconstruction, without the need to perform phase unwrapping. It is robust to the choice of initial solutions and encourages the joint reconstruction of phase imaging applications. Magn Reson Med 80:112-125, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations

PubMed Central

Li, Laquan; Wang, Jian; Lu, Wei; Tan, Shan

2016-01-01

Accurate tumor segmentation from PET images is crucial in many radiation oncology applications. Among others, partial volume effect (PVE) is recognized as one of the most important factors degrading imaging quality and segmentation accuracy in PET. Taking into account that image restoration and tumor segmentation are tightly coupled and can promote each other, we proposed a variational method to solve both problems simultaneously in this study. The proposed method integrated total variation (TV) semi-blind de-convolution and Mumford-Shah segmentation with multiple regularizations. Unlike many existing energy minimization methods using either TV or L2 regularization, the proposed method employed TV regularization over tumor edges to preserve edge information, and L2 regularization inside tumor regions to preserve the smooth change of the metabolic uptake in a PET image. The blur kernel was modeled as anisotropic Gaussian to address the resolution difference in transverse and axial directions commonly seen in a clinic PET scanner. The energy functional was rephrased using the Γ-convergence approximation and was iteratively optimized using the alternating minimization (AM) algorithm. The performance of the proposed method was validated on a physical phantom and two clinic datasets with non-Hodgkin’s lymphoma and esophageal cancer, respectively. Experimental results demonstrated that the proposed method had high performance for simultaneous image restoration, tumor segmentation and scanner blur kernel estimation. Particularly, the recovery coefficients (RC) of the restored images of the proposed method in the phantom study were close to 1, indicating an efficient recovery of the original blurred images; for segmentation the proposed method achieved average dice similarity indexes (DSIs) of 0.79 and 0.80 for two clinic datasets, respectively; and the relative errors of the estimated blur kernel widths were less than 19% in the transversal direction and 7% in the axial direction. PMID:28603407

Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately?

PubMed

Khalifé, Maya; Fernandez, Brice; Jaubert, Olivier; Soussan, Michael; Brulon, Vincent; Buvat, Irène; Comtat, Claude

2017-09-21

In brain PET/MR applications, accurate attenuation maps are required for accurate PET image quantification. An implemented attenuation correction (AC) method for brain imaging is the single-atlas approach that estimates an AC map from an averaged CT template. As an alternative, we propose to use a zero echo time (ZTE) pulse sequence to segment bone, air and soft tissue. A linear relationship between histogram normalized ZTE intensity and measured CT density in Hounsfield units ([Formula: see text]) in bone has been established thanks to a CT-MR database of 16 patients. Continuous AC maps were computed based on the segmented ZTE by setting a fixed linear attenuation coefficient (LAC) to air and soft tissue and by using the linear relationship to generate continuous μ values for the bone. Additionally, for the purpose of comparison, four other AC maps were generated: a ZTE derived AC map with a fixed LAC for the bone, an AC map based on the single-atlas approach as provided by the PET/MR manufacturer, a soft-tissue only AC map and, finally, the CT derived attenuation map used as the gold standard (CTAC). All these AC maps were used with different levels of smoothing for PET image reconstruction with and without time-of-flight (TOF). The subject-specific AC map generated by combining ZTE-based segmentation and linear scaling of the normalized ZTE signal into [Formula: see text] was found to be a good substitute for the measured CTAC map in brain PET/MR when used with a Gaussian smoothing kernel of [Formula: see text] corresponding to the PET scanner intrinsic resolution. As expected TOF reduces AC error regardless of the AC method. The continuous ZTE-AC performed better than the other alternative MR derived AC methods, reducing the quantification error between the MRAC corrected PET image and the reference CTAC corrected PET image.

Subject-specific bone attenuation correction for brain PET/MR: can ZTE-MRI substitute CT scan accurately?

NASA Astrophysics Data System (ADS)

Khalifé, Maya; Fernandez, Brice; Jaubert, Olivier; Soussan, Michael; Brulon, Vincent; Buvat, Irène; Comtat, Claude

2017-10-01

In brain PET/MR applications, accurate attenuation maps are required for accurate PET image quantification. An implemented attenuation correction (AC) method for brain imaging is the single-atlas approach that estimates an AC map from an averaged CT template. As an alternative, we propose to use a zero echo time (ZTE) pulse sequence to segment bone, air and soft tissue. A linear relationship between histogram normalized ZTE intensity and measured CT density in Hounsfield units (HU ) in bone has been established thanks to a CT-MR database of 16 patients. Continuous AC maps were computed based on the segmented ZTE by setting a fixed linear attenuation coefficient (LAC) to air and soft tissue and by using the linear relationship to generate continuous μ values for the bone. Additionally, for the purpose of comparison, four other AC maps were generated: a ZTE derived AC map with a fixed LAC for the bone, an AC map based on the single-atlas approach as provided by the PET/MR manufacturer, a soft-tissue only AC map and, finally, the CT derived attenuation map used as the gold standard (CTAC). All these AC maps were used with different levels of smoothing for PET image reconstruction with and without time-of-flight (TOF). The subject-specific AC map generated by combining ZTE-based segmentation and linear scaling of the normalized ZTE signal into HU was found to be a good substitute for the measured CTAC map in brain PET/MR when used with a Gaussian smoothing kernel of 4~mm corresponding to the PET scanner intrinsic resolution. As expected TOF reduces AC error regardless of the AC method. The continuous ZTE-AC performed better than the other alternative MR derived AC methods, reducing the quantification error between the MRAC corrected PET image and the reference CTAC corrected PET image.

Thermography based diagnosis of ruptured anterior cruciate ligament (ACL) in canines

NASA Astrophysics Data System (ADS)

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

2016-09-01

Anterior cruciate ligament (ACL) rupture in canines is a common orthopedic injury in veterinary medicine. Veterinarians use both imaging and non-imaging methods to diagnose the disease. Common imaging methods such as radiography, computed tomography (CT scan) and magnetic resonance imaging (MRI) have some disadvantages: expensive setup, high dose of radiation, and time-consuming. In this paper, we present an alternative diagnostic method based on feature extraction and pattern classification (FEPC) to diagnose abnormal patterns in ACL thermograms. The proposed method was experimented with a total of 30 thermograms for each camera view (anterior, lateral and posterior) including 14 disease and 16 non-disease cases provided from Long Island Veterinary Specialists. The normal and abnormal patterns in thermograms are analyzed in two steps: feature extraction and pattern classification. Texture features based on gray level co-occurrence matrices (GLCM), histogram features and spectral features are extracted from the color normalized thermograms and the computed feature vectors are applied to Nearest Neighbor (NN) classifier, K-Nearest Neighbor (KNN) classifier and Support Vector Machine (SVM) classifier with leave-one-out validation method. The algorithm gives the best classification success rate of 86.67% with a sensitivity of 85.71% and a specificity of 87.5% in ACL rupture detection using NN classifier for the lateral view and Norm-RGB-Lum color normalization method. Our results show that the proposed method has the potential to detect ACL rupture in canines.

Development and validation of a combined phased acoustical radiosity and image source model for predicting sound fields in rooms.

PubMed

Marbjerg, Gerd; Brunskog, Jonas; Jeong, Cheol-Ho; Nilsson, Erling

2015-09-01

A model, combining acoustical radiosity and the image source method, including phase shifts on reflection, has been developed. The model is denoted Phased Acoustical Radiosity and Image Source Method (PARISM), and it has been developed in order to be able to model both specular and diffuse reflections with complex-valued and angle-dependent boundary conditions. This paper mainly describes the combination of the two models and the implementation of the angle-dependent boundary conditions. It furthermore describes how a pressure impulse response is obtained from the energy-based acoustical radiosity by regarding the model as being stochastic. Three methods of implementation are proposed and investigated, and finally, recommendations are made for their use. Validation of the image source method is done by comparison with finite element simulations of a rectangular room with a porous absorber ceiling. Results from the full model are compared with results from other simulation tools and with measurements. The comparisons of the full model are done for real-valued and angle-independent surface properties. The proposed model agrees well with both the measured results and the alternative theories, and furthermore shows a more realistic spatial variation than energy-based methods due to the fact that interference is considered.

Iterative normalization method for improved prostate cancer localization with multispectral magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Liu, Xin; Samil Yetik, Imam

2012-04-01

Use of multispectral magnetic resonance imaging has received a great interest for prostate cancer localization in research and clinical studies. Manual extraction of prostate tumors from multispectral magnetic resonance imaging is inefficient and subjective, while automated segmentation is objective and reproducible. For supervised, automated segmentation approaches, learning is essential to obtain the information from training dataset. However, in this procedure, all patients are assumed to have similar properties for the tumor and normal tissues, and the segmentation performance suffers since the variations across patients are ignored. To conquer this difficulty, we propose a new iterative normalization method based on relative intensity values of tumor and normal tissues to normalize multispectral magnetic resonance images and improve segmentation performance. The idea of relative intensity mimics the manual segmentation performed by human readers, who compare the contrast between regions without knowing the actual intensity values. We compare the segmentation performance of the proposed method with that of z-score normalization followed by support vector machine, local active contours, and fuzzy Markov random field. Our experimental results demonstrate that our method outperforms the three other state-of-the-art algorithms, and was found to have specificity of 0.73, sensitivity of 0.69, and accuracy of 0.79, significantly better than alternative methods.

Exploring the Leishmania Hydrophilic Acylated Surface Protein B (HASPB) Export Pathway by Live Cell Imaging Methods.

PubMed

MacLean, Lorna; Price, Helen; O'Toole, Peter

2016-01-01

Leishmania major is a human-infective protozoan parasite transmitted by the bite of the female phlebotomine sand fly. The L. major hydrophilic acylated surface protein B (HASPB) is only expressed in infective parasite stages suggesting a role in parasite virulence. HASPB is a "nonclassically" secreted protein that lacks a conventional signal peptide, reaching the cell surface by an alternative route to the classical ER-Golgi pathway. Instead HASPB trafficking to and exposure on the parasite plasma membrane requires dual N-terminal acylation. Here, we use live cell imaging methods to further explore this pathway allowing visualization of key events in real time at the individual cell level. These methods include live cell imaging using fluorescent reporters to determine the subcellular localization of wild type and acylation site mutation HASPB18-GFP fusion proteins, fluorescence recovery after photobleaching (FRAP) to analyze the dynamics of HASPB in live cells, and live antibody staining to detect surface exposure of HASPB by confocal microscopy.

Multiple Illuminant Colour Estimation via Statistical Inference on Factor Graphs.

PubMed

Mutimbu, Lawrence; Robles-Kelly, Antonio

2016-08-31

This paper presents a method to recover a spatially varying illuminant colour estimate from scenes lit by multiple light sources. Starting with the image formation process, we formulate the illuminant recovery problem in a statistically datadriven setting. To do this, we use a factor graph defined across the scale space of the input image. In the graph, we utilise a set of illuminant prototypes computed using a data driven approach. As a result, our method delivers a pixelwise illuminant colour estimate being devoid of libraries or user input. The use of a factor graph also allows for the illuminant estimates to be recovered making use of a maximum a posteriori (MAP) inference process. Moreover, we compute the probability marginals by performing a Delaunay triangulation on our factor graph. We illustrate the utility of our method for pixelwise illuminant colour recovery on widely available datasets and compare against a number of alternatives. We also show sample colour correction results on real-world images.

Segmentation of Image Ensembles via Latent Atlases

PubMed Central

Van Leemput, Koen; Menze, Bjoern H.; Wells, William M.; Golland, Polina

2010-01-01

Spatial priors, such as probabilistic atlases, play an important role in MRI segmentation. However, the availability of comprehensive, reliable and suitable manual segmentations for atlas construction is limited. We therefore propose a method for joint segmentation of corresponding regions of interest in a collection of aligned images that does not require labeled training data. Instead, a latent atlas, initialized by at most a single manual segmentation, is inferred from the evolving segmentations of the ensemble. The algorithm is based on probabilistic principles but is solved using partial differential equations (PDEs) and energy minimization criteria. We evaluate the method on two datasets, segmenting subcortical and cortical structures in a multi-subject study and extracting brain tumors in a single-subject multi-modal longitudinal experiment. We compare the segmentation results to manual segmentations, when those exist, and to the results of a state-of-the-art atlas-based segmentation method. The quality of the results supports the latent atlas as a promising alternative when existing atlases are not compatible with the images to be segmented. PMID:20580305

Multiwavelength active-optics Shack-Hartmann sensor for monitoring seeing and turbulence outer scale

NASA Astrophysics Data System (ADS)

Martinez, P.

2014-12-01

Context. Real-time seeing and outer-scale estimation at the location of the focus of a telescope is fundamental for predicting the adaptive-optics system's dimensioning and performance, as well as for the operational aspects of instruments. Aims: This study attempts to take advantage of multiwavelength long-exposure images to instantaneously and simultaneously derive the turbulence outer scale and seeing from the full width at half maximum (FWHM) of seeing-limited images taken at the focus of a telescope. These atmospheric parameters are commonly measured in most observatories by different methods located away from the telescope platform, thus differing from the effective estimates at the focus of a telescope, mainly because of differences in pointing orientation, height above the ground, or local seeing bias (dome contribution). Methods: Long-exposure images can either be provided directly by any multiwavelength scientific imager or spectrograph or, alternatively from a modified active-optics Shack-Hartmann sensor (AOSH). From measuring the AOSH sensor spot point spread function FWHMs simultaneously at different wavelengths, one can estimate the instantaneous outer scale in addition to seeing. Results: Multiwavelength long-exposure images provide access to accurate estimates of r0 and L0 by adequate means as long as precise FWHMs can be obtained. Although AOSH sensors are specified to measure not spot sizes but slopes, real-time r0, and L0 measurements from spot FWHMs can be obtained at the critical location where they are needed with major advantages over scientific instrument images: insensitivity to the telescope field stabilization, and continuous availability. Conclusions: Assuming an alternative optical design that allows simultaneous multiwavelength images, the AOSH sensor benefits from all the advantages of real-time seeing and outer scale monitoring. With the substantial interest in the design of extremely large telescopes, such a system could be of considerable importance.

Nanophotonic Image Sensors.

PubMed

Chen, Qin; Hu, Xin; Wen, Long; Yu, Yan; Cumming, David R S

2016-09-01

The increasing miniaturization and resolution of image sensors bring challenges to conventional optical elements such as spectral filters and polarizers, the properties of which are determined mainly by the materials used, including dye polymers. Recent developments in spectral filtering and optical manipulating techniques based on nanophotonics have opened up the possibility of an alternative method to control light spectrally and spatially. By integrating these technologies into image sensors, it will become possible to achieve high compactness, improved process compatibility, robust stability and tunable functionality. In this Review, recent representative achievements on nanophotonic image sensors are presented and analyzed including image sensors with nanophotonic color filters and polarizers, metamaterial-based THz image sensors, filter-free nanowire image sensors and nanostructured-based multispectral image sensors. This novel combination of cutting edge photonics research and well-developed commercial products may not only lead to an important application of nanophotonics but also offer great potential for next generation image sensors beyond Moore's Law expectations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improved field free line magnetic particle imaging using saddle coils.

PubMed

Erbe, Marlitt; Sattel, Timo F; Buzug, Thorsten M

2013-12-01

Magnetic particle imaging (MPI) is a novel tracer-based imaging method detecting the distribution of superparamagnetic iron oxide (SPIO) nanoparticles in vivo in three dimensions and in real time. Conventionally, MPI uses the signal emitted by SPIO tracer material located at a field free point (FFP). To increase the sensitivity of MPI, however, an alternative encoding scheme collecting the particle signal along a field free line (FFL) was proposed. To provide the magnetic fields needed for line imaging in MPI, a very efficient scanner setup regarding electrical power consumption is needed. At the same time, the scanner needs to provide a high magnetic field homogeneity along the FFL as well as parallel to its alignment to prevent the appearance of artifacts, using efficient radon-based reconstruction methods arising for a line encoding scheme. This work presents a dynamic FFL scanner setup for MPI that outperforms all previously presented setups in electrical power consumption as well as magnetic field quality.

Apparatus and method for imaging metallic objects using an array of giant magnetoresistive sensors

DOEpatents

Chaiken, Alison

2000-01-01

A portable, low-power, metallic object detector and method for providing an image of a detected metallic object. In one embodiment, the present portable low-power metallic object detector an array of giant magnetoresistive (GMR) sensors. The array of GMR sensors is adapted for detecting the presence of and compiling image data of a metallic object. In the embodiment, the array of GMR sensors is arranged in a checkerboard configuration such that axes of sensitivity of alternate GMR sensors are orthogonally oriented. An electronics portion is coupled to the array of GMR sensors. The electronics portion is adapted to receive and process the image data of the metallic object compiled by the array of GMR sensors. The embodiment also includes a display unit which is coupled to the electronics portion. The display unit is adapted to display a graphical representation of the metallic object detected by the array of GMR sensors. In so doing, a graphical representation of the detected metallic object is provided.

Raman Hyperspectral Imaging for Detection of Watermelon Seeds Infected with Acidovorax citrulli.

PubMed

Lee, Hoonsoo; Kim, Moon S; Qin, Jianwei; Park, Eunsoo; Song, Yu-Rim; Oh, Chang-Sik; Cho, Byoung-Kwan

2017-09-23

The bacterial infection of seeds is one of the most important quality factors affecting yield. Conventional detection methods for bacteria-infected seeds, such as biological, serological, and molecular tests, are not feasible since they require expensive equipment, and furthermore, the testing processes are also time-consuming. In this study, we use the Raman hyperspectral imaging technique to distinguish bacteria-infected seeds from healthy seeds as a rapid, accurate, and non-destructive detection tool. We utilize Raman hyperspectral imaging data in the spectral range of 400-1800 cm -1 to determine the optimal band-ratio for the discrimination of watermelon seeds infected by the bacteria Acidovorax citrulli using ANOVA. Two bands at 1076.8 cm -1 and 437 cm -1 are selected as the optimal Raman peaks for the detection of bacteria-infected seeds. The results demonstrate that the Raman hyperspectral imaging technique has a good potential for the detection of bacteria-infected watermelon seeds and that it could form a suitable alternative to conventional methods.

Super-resolved linear fluorescence localization microscopy using photostable fluorophores: A virtual microscopy study

NASA Astrophysics Data System (ADS)

Birk, Udo; Szczurek, Aleksander; Cremer, Christoph

2017-12-01

Current approaches to overcome the conventional limit of the resolution potential of light microscopy (of about 200 nm for visible light), often suffer from non-linear effects, which render the quantification of the image intensities in the reconstructions difficult, and also affect the quantification of the biological structure under investigation. As an attempt to face these difficulties, we discuss a particular method of localization microscopy which is based on photostable fluorescent dyes. The proposed method can potentially be implemented as a fast alternative for quantitative localization microscopy, circumventing the need for the acquisition of thousands of image frames and complex, highly dye-specific imaging buffers. Although the need for calibration remains in order to extract quantitative data (such as the number of emitters), multispectral approaches are largely facilitated due to the much less stringent requirements on imaging buffers. Furthermore, multispectral acquisitions can be readily obtained using commercial instrumentation such as e.g. the conventional confocal laser scanning microscope.

Raman Hyperspectral Imaging for Detection of Watermelon Seeds Infected with Acidovorax citrulli

PubMed Central

Lee, Hoonsoo; Kim, Moon S.; Qin, Jianwei; Park, Eunsoo; Song, Yu-Rim; Oh, Chang-Sik

2017-01-01

The bacterial infection of seeds is one of the most important quality factors affecting yield. Conventional detection methods for bacteria-infected seeds, such as biological, serological, and molecular tests, are not feasible since they require expensive equipment, and furthermore, the testing processes are also time-consuming. In this study, we use the Raman hyperspectral imaging technique to distinguish bacteria-infected seeds from healthy seeds as a rapid, accurate, and non-destructive detection tool. We utilize Raman hyperspectral imaging data in the spectral range of 400–1800 cm−1 to determine the optimal band-ratio for the discrimination of watermelon seeds infected by the bacteria Acidovorax citrulli using ANOVA. Two bands at 1076.8 cm−1 and 437 cm−1 are selected as the optimal Raman peaks for the detection of bacteria-infected seeds. The results demonstrate that the Raman hyperspectral imaging technique has a good potential for the detection of bacteria-infected watermelon seeds and that it could form a suitable alternative to conventional methods. PMID:28946608

Environmental Scanning Electron Microscope Imaging of Vesicle Systems.

PubMed

Perrie, Yvonne; Ali, Habib; Kirby, Daniel J; Mohammed, Afzal U R; McNeil, Sarah E; Vangala, Anil

2017-01-01

The structural characteristics of liposomes have been widely investigated and there is certainly a strong understanding of their morphological characteristics. Imaging of these systems, using techniques such as freeze-fracturing methods, transmission electron microscopy, and cryo-electron imaging, has allowed us to appreciate their bilayer structures and factors which can influence this. However, there are few methods which all us to study these systems in their natural hydrated state; commonly the liposomes are visualized after drying, staining, and/or fixation of the vesicles. Environmental Scanning Electron Microscopy (ESEM) offers the ability to image a liposome in its hydrated state without the need for prior sample preparation. Within our studies we were the first to use ESEM to study liposomes and niosomes and we have been able to dynamically follow the hydration of lipid films and changes in liposome suspensions as water condenses on to, or evaporates from, the sample in real time. This provides insight into the resistance of liposomes to coalescence during dehydration, thereby providing an alternative assay of liposome formulation and stability.

Simultaneous 99mtc/111in spect reconstruction using accelerated convolution-based forced detection monte carlo

NASA Astrophysics Data System (ADS)

Karamat, Muhammad I.; Farncombe, Troy H.

2015-10-01

Simultaneous multi-isotope Single Photon Emission Computed Tomography (SPECT) imaging has a number of applications in cardiac, brain, and cancer imaging. The major concern however, is the significant crosstalk contamination due to photon scatter between the different isotopes. The current study focuses on a method of crosstalk compensation between two isotopes in simultaneous dual isotope SPECT acquisition applied to cancer imaging using 99mTc and 111In. We have developed an iterative image reconstruction technique that simulates the photon down-scatter from one isotope into the acquisition window of a second isotope. Our approach uses an accelerated Monte Carlo (MC) technique for the forward projection step in an iterative reconstruction algorithm. The MC estimated scatter contamination of a radionuclide contained in a given projection view is then used to compensate for the photon contamination in the acquisition window of other nuclide. We use a modified ordered subset-expectation maximization (OS-EM) algorithm named simultaneous ordered subset-expectation maximization (Sim-OSEM), to perform this step. We have undertaken a number of simulation tests and phantom studies to verify this approach. The proposed reconstruction technique was also evaluated by reconstruction of experimentally acquired phantom data. Reconstruction using Sim-OSEM showed very promising results in terms of contrast recovery and uniformity of object background compared to alternative reconstruction methods implementing alternative scatter correction schemes (i.e., triple energy window or separately acquired projection data). In this study the evaluation is based on the quality of reconstructed images and activity estimated using Sim-OSEM. In order to quantitate the possible improvement in spatial resolution and signal to noise ratio (SNR) observed in this study, further simulation and experimental studies are required.

Fast conjugate phase image reconstruction based on a Chebyshev approximation to correct for B0 field inhomogeneity and concomitant gradients

PubMed Central

Chen, Weitian; Sica, Christopher T.; Meyer, Craig H.

2008-01-01

Off-resonance effects can cause image blurring in spiral scanning and various forms of image degradation in other MRI methods. Off-resonance effects can be caused by both B0 inhomogeneity and concomitant gradient fields. Previously developed off-resonance correction methods focus on the correction of a single source of off-resonance. This work introduces a computationally efficient method of correcting for B0 inhomogeneity and concomitant gradients simultaneously. The method is a fast alternative to conjugate phase reconstruction, with the off-resonance phase term approximated by Chebyshev polynomials. The proposed algorithm is well suited for semiautomatic off-resonance correction, which works well even with an inaccurate or low-resolution field map. The proposed algorithm is demonstrated using phantom and in vivo data sets acquired by spiral scanning. Semiautomatic off-resonance correction alone is shown to provide a moderate amount of correction for concomitant gradient field effects, in addition to B0 imhomogeneity effects. However, better correction is provided by the proposed combined method. The best results were produced using the semiautomatic version of the proposed combined method. PMID:18956462

Objects Grouping for Segmentation of Roads Network in High Resolution Images of Urban Areas

NASA Astrophysics Data System (ADS)

Maboudi, M.; Amini, J.; Hahn, M.

2016-06-01

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors - as the main source of large scale mapping applications - was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of "Object-based Image Analysis (OBIA)" as an alternative to pixel-based image analysis methods. Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

Method for accurately positioning a device at a desired area of interest

DOEpatents

Jones, Gary D.; Houston, Jack E.; Gillen, Kenneth T.

2000-01-01

A method for positioning a first device utilizing a surface having a viewing translation stage, the surface being movable between a first position where the viewing stage is in operational alignment with a first device and a second position where the viewing stage is in operational alignment with a second device. The movable surface is placed in the first position and an image is produced with the first device of an identifiable characteristic of a calibration object on the viewing stage. The moveable surface is then placed in the second position and only the second device is moved until an image of the identifiable characteristic in the second device matches the image from the first device. The calibration object is then replaced on the stage of the surface with a test object, and the viewing translation stage is adjusted until the second device images the area of interest. The surface is then moved to the first position where the test object is scanned with the first device to image the area of interest. An alternative embodiment where the devices move is also disclosed.

Active browsing using similarity pyramids

NASA Astrophysics Data System (ADS)

Chen, Jau-Yuen; Bouman, Charles A.; Dalton, John C.

1998-12-01

In this paper, we describe a new approach to managing large image databases, which we call active browsing. Active browsing integrates relevance feedback into the browsing environment, so that users can modify the database's organization to suit the desired task. Our method is based on a similarity pyramid data structure, which hierarchically organizes the database, so that it can be efficiently browsed. At coarse levels, the similarity pyramid allows users to view the database as large clusters of similar images. Alternatively, users can 'zoom into' finer levels to view individual images. We discuss relevance feedback for the browsing process, and argue that it is fundamentally different from relevance feedback for more traditional search-by-query tasks. We propose two fundamental operations for active browsing: pruning and reorganization. Both of these operations depend on a user-defined relevance set, which represents the image or set of images desired by the user. We present statistical methods for accurately pruning the database, and we propose a new 'worm hole' distance metric for reorganizing the database, so that members of the relevance set are grouped together.

Personal authentication using hand vein triangulation and knuckle shape.

PubMed

Kumar, Ajay; Prathyusha, K Venkata

2009-09-01

This paper presents a new approach to authenticate individuals using triangulation of hand vein images and simultaneous extraction of knuckle shape information. The proposed method is fully automated and employs palm dorsal hand vein images acquired from the low-cost, near infrared, contactless imaging. The knuckle tips are used as key points for the image normalization and extraction of region of interest. The matching scores are generated in two parallel stages: (i) hierarchical matching score from the four topologies of triangulation in the binarized vein structures and (ii) from the geometrical features consisting of knuckle point perimeter distances in the acquired images. The weighted score level combination from these two matching scores are used to authenticate the individuals. The achieved experimental results from the proposed system using contactless palm dorsal-hand vein images are promising (equal error rate of 1.14%) and suggest more user friendly alternative for user identification.

Isotropic scalar image visualization of vector differential image data using the inverse Riesz transform.

PubMed

Larkin, Kieran G; Fletcher, Peter A

2014-03-01

X-ray Talbot moiré interferometers can now simultaneously generate two differential phase images of a specimen. The conventional approach to integrating differential phase is unstable and often leads to images with loss of visible detail. We propose a new reconstruction method based on the inverse Riesz transform. The Riesz approach is stable and the final image retains visibility of high resolution detail without directional bias. The outline Riesz theory is developed and an experimentally acquired X-ray differential phase data set is presented for qualitative visual appraisal. The inverse Riesz phase image is compared with two alternatives: the integrated (quantitative) phase and the modulus of the gradient of the phase. The inverse Riesz transform has the computational advantages of a unitary linear operator, and is implemented directly as a complex multiplication in the Fourier domain also known as the spiral phase transform.

Isotropic scalar image visualization of vector differential image data using the inverse Riesz transform

PubMed Central

Larkin, Kieran G.; Fletcher, Peter A.

2014-01-01

X-ray Talbot moiré interferometers can now simultaneously generate two differential phase images of a specimen. The conventional approach to integrating differential phase is unstable and often leads to images with loss of visible detail. We propose a new reconstruction method based on the inverse Riesz transform. The Riesz approach is stable and the final image retains visibility of high resolution detail without directional bias. The outline Riesz theory is developed and an experimentally acquired X-ray differential phase data set is presented for qualitative visual appraisal. The inverse Riesz phase image is compared with two alternatives: the integrated (quantitative) phase and the modulus of the gradient of the phase. The inverse Riesz transform has the computational advantages of a unitary linear operator, and is implemented directly as a complex multiplication in the Fourier domain also known as the spiral phase transform. PMID:24688823

Blind image deblurring based on trained dictionary and curvelet using sparse representation

NASA Astrophysics Data System (ADS)

Feng, Liang; Huang, Qian; Xu, Tingfa; Li, Shao

2015-04-01

Motion blur is one of the most significant and common artifacts causing poor image quality in digital photography, in which many factors resulted. In imaging process, if the objects are moving quickly in the scene or the camera moves in the exposure interval, the image of the scene would blur along the direction of relative motion between the camera and the scene, e.g. camera shake, atmospheric turbulence. Recently, sparse representation model has been widely used in signal and image processing, which is an effective method to describe the natural images. In this article, a new deblurring approach based on sparse representation is proposed. An overcomplete dictionary learned from the trained image samples via the KSVD algorithm is designed to represent the latent image. The motion-blur kernel can be treated as a piece-wise smooth function in image domain, whose support is approximately a thin smooth curve, so we employed curvelet to represent the blur kernel. Both of overcomplete dictionary and curvelet system have high sparsity, which improves the robustness to the noise and more satisfies the observer's visual demand. With the two priors, we constructed restoration model of blurred images and succeeded to solve the optimization problem with the help of alternating minimization technique. The experiment results prove the method can preserve the texture of original images and suppress the ring artifacts effectively.

Novel Fourier-domain constraint for fast phase retrieval in coherent diffraction imaging.

PubMed

Latychevskaia, Tatiana; Longchamp, Jean-Nicolas; Fink, Hans-Werner

2011-09-26

Coherent diffraction imaging (CDI) for visualizing objects at atomic resolution has been realized as a promising tool for imaging single molecules. Drawbacks of CDI are associated with the difficulty of the numerical phase retrieval from experimental diffraction patterns; a fact which stimulated search for better numerical methods and alternative experimental techniques. Common phase retrieval methods are based on iterative procedures which propagate the complex-valued wave between object and detector plane. Constraints in both, the object and the detector plane are applied. While the constraint in the detector plane employed in most phase retrieval methods requires the amplitude of the complex wave to be equal to the squared root of the measured intensity, we propose a novel Fourier-domain constraint, based on an analogy to holography. Our method allows achieving a low-resolution reconstruction already in the first step followed by a high-resolution reconstruction after further steps. In comparison to conventional schemes this Fourier-domain constraint results in a fast and reliable convergence of the iterative reconstruction process. © 2011 Optical Society of America

Intravital microscopy of biosensor activities and intrinsic metabolic states

PubMed Central

Winfree, Seth; Hato, Takashi; Day, Richard N.

2018-01-01

Intravital microscopy (IVM) is an imaging tool that is capable of detecting subcellular signaling or metabolic events as they occur in tissues in the living animal. Imaging in highly scattering biological tissues, however, is challenging because of the attenuation of signal in images acquired at increasing depths. Depth-dependent signal attenuation is the major impediment to IVM, limiting the depth from which significant data can be obtained. Therefore, making quantitative measurements by IVM requires methods that use internal calibration, or alternatively, a completely different way of evaluating the signals. Here, we describe how ratiometric imaging of genetically encoded biosensor probes can be used to make quantitative measurements of changes in the activity of cell signaling pathways. Then, we describe how fluorescence lifetime imaging can be used for label-free measurements of the metabolic states of cells within the living animal. PMID:28434902

Secrets of the Chinese magic mirror replica

NASA Astrophysics Data System (ADS)

Mak, Se-yuen; Yip, Din-yan

2001-03-01

We examine the structure of five Chinese magic mirror replicas using a special imaging technique developed by the authors. All mirrors are found to have a two-layered structure. The reflecting surface that gives rise to a projected magic pattern on the screen is hidden under a polished half-reflecting top layer. An alternative method of making the magic mirror using ancient technology has been proposed. Finally, we suggest a simple method of reconstructing a mirror replica in the laboratory.

1975 Memorial Award Paper. Image generation and display techniques for CT scan data. Thin transverse and reconstructed coronal and sagittal planes.

PubMed

Glenn, W V; Johnston, R J; Morton, P E; Dwyer, S J

1975-01-01

The various limitations to computerized axial tomographic (CT) interpretation are due in part to the 8-13 mm standard tissue plane thickness and in part to the absence of alternative planes of view, such as coronal or sagittal images. This paper describes a method for gathering multiple overlapped 8 mm transverse sections, subjecting these data to a deconvolution process, and then displaying thin (1 mm) transverse as well as reconstructed coronal and sagittal CT images. Verification of the deconvolution technique with phantom experiments is described. Application of the phantom results to human post mortem CT scan data illustrates this method's faithful reconstruction of coronal and sagittal tissue densities when correlated with actual specimen photographs of a sectioned brain. A special CT procedure, limited basal overlap scanning, is proposed for use on current first generation CT scanners without hardware modification.

Terahertz imaging and tomography as efficient instruments for testing polymer additive manufacturing objects.

PubMed

Perraud, J B; Obaton, A F; Bou-Sleiman, J; Recur, B; Balacey, H; Darracq, F; Guillet, J P; Mounaix, P

2016-05-01

Additive manufacturing (AM) technology is not only used to make 3D objects but also for rapid prototyping. In industry and laboratories, quality controls for these objects are necessary though difficult to implement compared to classical methods of fabrication because the layer-by-layer printing allows for very complex object manufacturing that is unachievable with standard tools. Furthermore, AM can induce unknown or unexpected defects. Consequently, we demonstrate terahertz (THz) imaging as an innovative method for 2D inspection of polymer materials. Moreover, THz tomography may be considered as an alternative to x-ray tomography and cheaper 3D imaging for routine control. This paper proposes an experimental study of 3D polymer objects obtained by additive manufacturing techniques. This approach allows us to characterize defects and to control dimensions by volumetric measurements on 3D data reconstructed by tomography.

Using High-Content Imaging to Analyze Toxicological Tipping ...

EPA Pesticide Factsheets

Presentation at International Conference on Toxicological Alternatives & Translational Toxicology (ICTATT) held in China and Discussing the possibility of using High Content Imaging to Analyze Toxicological Tipping Points Slide Presentation at International Conference on Toxicological Alternatives & Translational Toxicology (ICTATT) held in China and Discussing the possibility of using High Content Imaging to Analyze Toxicological Tipping Points

Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic

NASA Astrophysics Data System (ADS)

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.-A.

2010-10-01

The retrieval of sea ice motion with the Maximum Cross-Correlation (MCC) method from low-resolution (10-15 km) spaceborne imaging sensors is challenged by a dominating quantization noise as the time span of displacement vectors is shortened. To allow investigating shorter displacements from these instruments, we introduce an alternative sea ice motion tracking algorithm that builds on the MCC method but relies on a continuous optimization step for computing the motion vector. The prime effect of this method is to effectively dampen the quantization noise, an artifact of the MCC. It allows for retrieving spatially smooth 48 h sea ice motion vector fields in the Arctic. Strategies to detect and correct erroneous vectors as well as to optimally merge several polarization channels of a given instrument are also described. A test processing chain is implemented and run with several active and passive microwave imagers (Advanced Microwave Scanning Radiometer-EOS (AMSR-E), Special Sensor Microwave Imager, and Advanced Scatterometer) during three Arctic autumn, winter, and spring seasons. Ice motion vectors are collocated to and compared with GPS positions of in situ drifters. Error statistics are shown to be ranging from 2.5 to 4.5 km (standard deviation for components of the vectors) depending on the sensor, without significant bias. We discuss the relative contribution of measurement and representativeness errors by analyzing monthly validation statistics. The 37 GHz channels of the AMSR-E instrument allow for the best validation statistics. The operational low-resolution sea ice drift product of the EUMETSAT OSI SAF (European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility) is based on the algorithms presented in this paper.

Automated detection of extended sources in radio maps: progress from the SCORPIO survey

NASA Astrophysics Data System (ADS)

Riggi, S.; Ingallinera, A.; Leto, P.; Cavallaro, F.; Bufano, F.; Schillirò, F.; Trigilio, C.; Umana, G.; Buemi, C. S.; Norris, R. P.

2016-08-01

Automated source extraction and parametrization represents a crucial challenge for the next-generation radio interferometer surveys, such as those performed with the Square Kilometre Array (SKA) and its precursors. In this paper, we present a new algorithm, called CAESAR (Compact And Extended Source Automated Recognition), to detect and parametrize extended sources in radio interferometric maps. It is based on a pre-filtering stage, allowing image denoising, compact source suppression and enhancement of diffuse emission, followed by an adaptive superpixel clustering stage for final source segmentation. A parametrization stage provides source flux information and a wide range of morphology estimators for post-processing analysis. We developed CAESAR in a modular software library, also including different methods for local background estimation and image filtering, along with alternative algorithms for both compact and diffuse source extraction. The method was applied to real radio continuum data collected at the Australian Telescope Compact Array (ATCA) within the SCORPIO project, a pathfinder of the Evolutionary Map of the Universe (EMU) survey at the Australian Square Kilometre Array Pathfinder (ASKAP). The source reconstruction capabilities were studied over different test fields in the presence of compact sources, imaging artefacts and diffuse emission from the Galactic plane and compared with existing algorithms. When compared to a human-driven analysis, the designed algorithm was found capable of detecting known target sources and regions of diffuse emission, outperforming alternative approaches over the considered fields.

Temporal resolution improvement using PICCS in MDCT cardiac imaging

PubMed Central

Chen, Guang-Hong; Tang, Jie; Hsieh, Jiang

2009-01-01

The current paradigm for temporal resolution improvement is to add more source-detector units and∕or increase the gantry rotation speed. The purpose of this article is to present an innovative alternative method to potentially improve temporal resolution by approximately a factor of 2 for all MDCT scanners without requiring hardware modification. The central enabling technology is a most recently developed image reconstruction method: Prior image constrained compressed sensing (PICCS). Using the method, cardiac CT images can be accurately reconstructed using the projection data acquired in an angular range of about 120°, which is roughly 50% of the standard short-scan angular range (∼240° for an MDCT scanner). As a result, the temporal resolution of MDCT cardiac imaging can be universally improved by approximately a factor of 2. In order to validate the proposed method, two in vivo animal experiments were conducted using a state-of-the-art 64-slice CT scanner (GE Healthcare, Waukesha, WI) at different gantry rotation times and different heart rates. One animal was scanned at heart rate of 83 beats per minute (bpm) using 400 ms gantry rotation time and the second animal was scanned at 94 bpm using 350 ms gantry rotation time, respectively. Cardiac coronary CT imaging can be successfully performed at high heart rates using a single-source MDCT scanner and projection data from a single heart beat with gantry rotation times of 400 and 350 ms. Using the proposed PICCS method, the temporal resolution of cardiac CT imaging can be effectively improved by approximately a factor of 2 without modifying any scanner hardware. This potentially provides a new method for single-source MDCT scanners to achieve reliable coronary CT imaging for patients at higher heart rates than the current heart rate limit of 70 bpm without using the well-known multisegment FBP reconstruction algorithm. This method also enables dual-source MDCT scanner to achieve higher temporal resolution without further hardware modifications. PMID:19610302

Temporal resolution improvement using PICCS in MDCT cardiac imaging.

PubMed

Chen, Guang-Hong; Tang, Jie; Hsieh, Jiang

2009-06-01

The current paradigm for temporal resolution improvement is to add more source-detector units and/or increase the gantry rotation speed. The purpose of this article is to present an innovative alternative method to potentially improve temporal resolution by approximately a factor of 2 for all MDCT scanners without requiring hardware modification. The central enabling technology is a most recently developed image reconstruction method: Prior image constrained compressed sensing (PICCS). Using the method, cardiac CT images can be accurately reconstructed using the projection data acquired in an angular range of about 120 degrees, which is roughly 50% of the standard short-scan angular range (approximately 240 degrees for an MDCT scanner). As a result, the temporal resolution of MDCT cardiac imaging can be universally improved by approximately a factor of 2. In order to validate the proposed method, two in vivo animal experiments were conducted using a state-of-the-art 64-slice CT scanner (GE Healthcare, Waukesha, WI) at different gantry rotation times and different heart rates. One animal was scanned at heart rate of 83 beats per minute (bpm) using 400 ms gantry rotation time and the second animal was scanned at 94 bpm using 350 ms gantry rotation time, respectively. Cardiac coronary CT imaging can be successfully performed at high heart rates using a single-source MDCT scanner and projection data from a single heart beat with gantry rotation times of 400 and 350 ms. Using the proposed PICCS method, the temporal resolution of cardiac CT imaging can be effectively improved by approximately a factor of 2 without modifying any scanner hardware. This potentially provides a new method for single-source MDCT scanners to achieve reliable coronary CT imaging for patients at higher heart rates than the current heart rate limit of 70 bpm without using the well-known multisegment FBP reconstruction algorithm. This method also enables dual-source MDCT scanner to achieve higher temporal resolution without further hardware modifications.

Histopathological Image Classification using Discriminative Feature-oriented Dictionary Learning

PubMed Central

Vu, Tiep Huu; Mousavi, Hojjat Seyed; Monga, Vishal; Rao, Ganesh; Rao, UK Arvind

2016-01-01

In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structures. In this paper, we propose an automatic feature discovery framework via learning class-specific dictionaries and present a low-complexity method for classification and disease grading in histopathology. Essentially, our Discriminative Feature-oriented Dictionary Learning (DFDL) method learns class-specific dictionaries such that under a sparsity constraint, the learned dictionaries allow representing a new image sample parsimoniously via the dictionary corresponding to the class identity of the sample. At the same time, the dictionary is designed to be poorly capable of representing samples from other classes. Experiments on three challenging real-world image databases: 1) histopathological images of intraductal breast lesions, 2) mammalian kidney, lung and spleen images provided by the Animal Diagnostics Lab (ADL) at Pennsylvania State University, and 3) brain tumor images from The Cancer Genome Atlas (TCGA) database, reveal the merits of our proposal over state-of-the-art alternatives. Moreover, we demonstrate that DFDL exhibits a more graceful decay in classification accuracy against the number of training images which is highly desirable in practice where generous training is often not available. PMID:26513781

Fast periodic stimulation (FPS): a highly effective approach in fMRI brain mapping.

PubMed

Gao, Xiaoqing; Gentile, Francesco; Rossion, Bruno

2018-06-01

Defining the neural basis of perceptual categorization in a rapidly changing natural environment with low-temporal resolution methods such as functional magnetic resonance imaging (fMRI) is challenging. Here, we present a novel fast periodic stimulation (FPS)-fMRI approach to define face-selective brain regions with natural images. Human observers are presented with a dynamic stream of widely variable natural object images alternating at a fast rate (6 images/s). Every 9 s, a short burst of variable face images contrasting with object images in pairs induces an objective face-selective neural response at 0.111 Hz. A model-free Fourier analysis achieves a twofold increase in signal-to-noise ratio compared to a conventional block-design approach with identical stimuli and scanning duration, allowing to derive a comprehensive map of face-selective areas in the ventral occipito-temporal cortex, including the anterior temporal lobe (ATL), in all individual brains. Critically, periodicity of the desired category contrast and random variability among widely diverse images effectively eliminates the contribution of low-level visual cues, and lead to the highest values (80-90%) of test-retest reliability in the spatial activation map yet reported in imaging higher level visual functions. FPS-fMRI opens a new avenue for understanding brain function with low-temporal resolution methods.

Laryngeal High-Speed Videoendoscopy: Rationale and Recommendation for Accurate and Consistent Terminology

PubMed Central

Deliyski, Dimitar D.; Hillman, Robert E.

2015-01-01

Purpose The authors discuss the rationale behind the term laryngeal high-speed videoendoscopy to describe the application of high-speed endoscopic imaging techniques to the visualization of vocal fold vibration. Method Commentary on the advantages of using accurate and consistent terminology in the field of voice research is provided. Specific justification is described for each component of the term high-speed videoendoscopy, which is compared and contrasted with alternative terminologies in the literature. Results In addition to the ubiquitous high-speed descriptor, the term endoscopy is necessary to specify the appropriate imaging technology and distinguish among modalities such as ultrasound, magnetic resonance imaging, and nonendoscopic optical imaging. Furthermore, the term video critically indicates the electronic recording of a sequence of optical still images representing scenes in motion, in contrast to strobed images using high-speed photography and non-optical high-speed magnetic resonance imaging. High-speed videoendoscopy thus concisely describes the technology and can be appended by the desired anatomical nomenclature such as laryngeal. Conclusions Laryngeal high-speed videoendoscopy strikes a balance between conciseness and specificity when referring to the typical high-speed imaging method performed on human participants. Guidance for the creation of future terminology provides clarity and context for current and future experiments and the dissemination of results among researchers. PMID:26375398

In vivo photoacoustic and ultrasonic mapping of rat sentinel lymph nodes with a modified commercial ultrasound imaging system

NASA Astrophysics Data System (ADS)

Erpelding, Todd N.; Kim, Chulhong; Pramanik, Manojit; Guo, Zijian; Dean, John; Jankovic, Ladislav; Maslov, Konstantin; Wang, Lihong V.

2010-02-01

Sentinel lymph node biopsy (SLNB) has become the standard method for axillary staging in breast cancer patients, relying on invasive identification of sentinel lymph nodes (SLNs) following injection of blue dye and radioactive tracers. While SLNB achieves a low false negative rate (5-10%), it is an invasive procedure requiring ionizing radiation. As an alternative to SLNB, ultrasound-guided fine needle aspiration biopsy has been tested clinically. However, ultrasound alone is unable to accurately identify which lymph nodes are sentinel. Therefore, a non-ionizing and noninvasive detection method for accurate SLN mapping is needed. In this study, we successfully imaged methylene blue dye accumulation in vivo in rat axillary lymph nodes using a Phillips iU22 ultrasound imaging system adapted for photoacoustic imaging with an Nd:YAG pumped, tunable dye laser. Photoacoustic images of rat SLNs clearly identify methylene blue dye accumulation within minutes following intradermal dye injection and co-registered photoacoustic/ultrasound images illustrate lymph node position relative to surrounding anatomy. To investigate clinical translation, the imaging depth was extended up to 2.5 cm by adding chicken breast tissue on top of the rat skin surface. These results raise confidence that photoacoustic imaging can be used clinically for accurate, noninvasive SLN mapping.

Evaluation of image quality in terahertz pulsed imaging using test objects.

PubMed

Fitzgerald, A J; Berry, E; Miles, R E; Zinovev, N N; Smith, M A; Chamberlain, J M

2002-11-07

As with other imaging modalities, the performance of terahertz (THz) imaging systems is limited by factors of spatial resolution, contrast and noise. The purpose of this paper is to introduce test objects and image analysis methods to evaluate and compare THz image quality in a quantitative and objective way, so that alternative terahertz imaging system configurations and acquisition techniques can be compared, and the range of image parameters can be assessed. Two test objects were designed and manufactured, one to determine the modulation transfer functions (MTF) and the other to derive image signal to noise ratio (SNR) at a range of contrasts. As expected the higher THz frequencies had larger MTFs, and better spatial resolution as determined by the spatial frequency at which the MTF dropped below the 20% threshold. Image SNR was compared for time domain and frequency domain image parameters and time delay based images consistently demonstrated higher SNR than intensity based parameters such as relative transmittance because the latter are more strongly affected by the sources of noise in the THz system such as laser fluctuations and detector shot noise.

Photogrammetric Point Clouds Generation in Urban Areas from Integrated Image Matching and Segmentation

NASA Astrophysics Data System (ADS)

Ye, L.; Wu, B.

2017-09-01

High-resolution imagery is an attractive option for surveying and mapping applications due to the advantages of high quality imaging, short revisit time, and lower cost. Automated reliable and dense image matching is essential for photogrammetric 3D data derivation. Such matching, in urban areas, however, is extremely difficult, owing to the complexity of urban textures and severe occlusion problems on the images caused by tall buildings. Aimed at exploiting high-resolution imagery for 3D urban modelling applications, this paper presents an integrated image matching and segmentation approach for reliable dense matching of high-resolution imagery in urban areas. The approach is based on the framework of our existing self-adaptive triangulation constrained image matching (SATM), but incorporates three novel aspects to tackle the image matching difficulties in urban areas: 1) occlusion filtering based on image segmentation, 2) segment-adaptive similarity correlation to reduce the similarity ambiguity, 3) improved dense matching propagation to provide more reliable matches in urban areas. Experimental analyses were conducted using aerial images of Vaihingen, Germany and high-resolution satellite images in Hong Kong. The photogrammetric point clouds were generated, from which digital surface models (DSMs) were derived. They were compared with the corresponding airborne laser scanning data and the DSMs generated from the Semi-Global matching (SGM) method. The experimental results show that the proposed approach is able to produce dense and reliable matches comparable to SGM in flat areas, while for densely built-up areas, the proposed method performs better than SGM. The proposed method offers an alternative solution for 3D surface reconstruction in urban areas.

Deep Convolutional Neural Networks for Multi-Modality Isointense Infant Brain Image Segmentation

PubMed Central

Zhang, Wenlu; Li, Rongjian; Deng, Houtao; Wang, Li; Lin, Weili; Ji, Shuiwang; Shen, Dinggang

2015-01-01

The segmentation of infant brain tissue images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) plays an important role in studying early brain development in health and disease. In the isointense stage (approximately 6–8 months of age), WM and GM exhibit similar levels of intensity in both T1 and T2 MR images, making the tissue segmentation very challenging. Only a small number of existing methods have been designed for tissue segmentation in this isointense stage; however, they only used a single T1 or T2 images, or the combination of T1 and T2 images. In this paper, we propose to use deep convolutional neural networks (CNNs) for segmenting isointense stage brain tissues using multi-modality MR images. CNNs are a type of deep models in which trainable filters and local neighborhood pooling operations are applied alternatingly on the raw input images, resulting in a hierarchy of increasingly complex features. Specifically, we used multimodality information from T1, T2, and fractional anisotropy (FA) images as inputs and then generated the segmentation maps as outputs. The multiple intermediate layers applied convolution, pooling, normalization, and other operations to capture the highly nonlinear mappings between inputs and outputs. We compared the performance of our approach with that of the commonly used segmentation methods on a set of manually segmented isointense stage brain images. Results showed that our proposed model significantly outperformed prior methods on infant brain tissue segmentation. In addition, our results indicated that integration of multi-modality images led to significant performance improvement. PMID:25562829

Two-Step Cycle for Producing Multiple Anodic Aluminum Oxide (AAO) Films with Increasing Long-Range Order

PubMed Central

2017-01-01

Nanoporous anodic aluminum oxide (AAO) membranes are being used for an increasing number of applications. However, the original two-step anodization method in which the first anodization is sacrificial to pre-pattern the second is still widely used to produce them. This method provides relatively low throughput and material utilization as half of the films are discarded. An alternative scheme that relies on alternating anodization and cathodic delamination is demonstrated that allows for the fabrication of several AAO films with only one sacrificial layer thus greatly improving total aluminum to alumina yield. The thickness for which the cathodic delamination performs best to yield full, unbroken AAO sheets is around 85 μm. Additionally, an image analysis method is used to quantify the degree of long-range ordering of the unit cells in the AAO films which was found to increase with each successive iteration of the fabrication cycle. PMID:28630684

Two-Step Cycle for Producing Multiple Anodic Aluminum Oxide (AAO) Films with Increasing Long-Range Order.

PubMed

Choudhary, Eric; Szalai, Veronika

2016-01-01

Nanoporous anodic aluminum oxide (AAO) membranes are being used for an increasing number of applications. However, the original two-step anodization method in which the first anodization is sacrificial to pre-pattern the second is still widely used to produce them. This method provides relatively low throughput and material utilization as half of the films are discarded. An alternative scheme that relies on alternating anodization and cathodic delamination is demonstrated that allows for the fabrication of several AAO films with only one sacrificial layer thus greatly improving total aluminum to alumina yield. The thickness for which the cathodic delamination performs best to yield full, unbroken AAO sheets is around 85 μm. Additionally, an image analysis method is used to quantify the degree of long-range ordering of the unit cells in the AAO films which was found to increase with each successive iteration of the fabrication cycle.

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

PubMed

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

2016-07-01

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

A three-dimensional parabolic equation model of sound propagation using higher-order operator splitting and Padé approximants.

PubMed

Lin, Ying-Tsong; Collis, Jon M; Duda, Timothy F

2012-11-01

An alternating direction implicit (ADI) three-dimensional fluid parabolic equation solution method with enhanced accuracy is presented. The method uses a square-root Helmholtz operator splitting algorithm that retains cross-multiplied operator terms that have been previously neglected. With these higher-order cross terms, the valid angular range of the parabolic equation solution is improved. The method is tested for accuracy against an image solution in an idealized wedge problem. Computational efficiency improvements resulting from the ADI discretization are also discussed.

Evaluation of Alternative Conceptual Models Using Interdisciplinary Information: An Application in Shallow Groundwater Recharge and Discharge

NASA Astrophysics Data System (ADS)

Lin, Y.; Bajcsy, P.; Valocchi, A. J.; Kim, C.; Wang, J.

2007-12-01

Natural systems are complex, thus extensive data are needed for their characterization. However, data acquisition is expensive; consequently we develop models using sparse, uncertain information. When all uncertainties in the system are considered, the number of alternative conceptual models is large. Traditionally, the development of a conceptual model has relied on subjective professional judgment. Good judgment is based on experience in coordinating and understanding auxiliary information which is correlated to the model but difficult to be quantified into the mathematical model. For example, groundwater recharge and discharge (R&D) processes are known to relate to multiple information sources such as soil type, river and lake location, irrigation patterns and land use. Although hydrologists have been trying to understand and model the interaction between each of these information sources and R&D processes, it is extremely difficult to quantify their correlations using a universal approach due to the complexity of the processes, the spatiotemporal distribution and uncertainty. There is currently no single method capable of estimating R&D rates and patterns for all practical applications. Chamberlin (1890) recommended use of "multiple working hypotheses" (alternative conceptual models) for rapid advancement in understanding of applied and theoretical problems. Therefore, cross analyzing R&D rates and patterns from various estimation methods and related field information will likely be superior to using only a single estimation method. We have developed the Pattern Recognition Utility (PRU), to help GIS users recognize spatial patterns from noisy 2D image. This GIS plug-in utility has been applied to help hydrogeologists establish alternative R&D conceptual models in a more efficient way than conventional methods. The PRU uses numerical methods and image processing algorithms to estimate and visualize shallow R&D patterns and rates. It can provide a fast initial estimate prior to planning labor intensive and time consuming field R&D measurements. Furthermore, the Spatial Pattern 2 Learn (SP2L) was developed to cross analyze results from the PRU with ancillary field information, such as land coverage, soil type, topographic maps and previous estimates. The learning process of SP2L cross examines each initially recognized R&D pattern with the ancillary spatial dataset, and then calculates a quantifiable reliability index for each R&D map using a supervised machine learning technique called decision tree. This JAVA based software package is capable of generating alternative R&D maps if the user decides to apply certain conditions recognized by the learning process. The reliability indices from SP2L will improve the traditionally subjective approach to initiating conceptual models by providing objectively quantifiable conceptual bases for further probabilistic and uncertainty analyses. Both the PRU and SP2L have been designed to be user-friendly and universal utilities for pattern recognition and learning to improve model predictions from sparse measurements by computer-assisted integration of spatially dense geospatial image data and machine learning of model dependencies.

Jansen-MIDAS: A multi-level photomicrograph segmentation software based on isotropic undecimated wavelets.

PubMed

de Siqueira, Alexandre Fioravante; Cabrera, Flávio Camargo; Nakasuga, Wagner Massayuki; Pagamisse, Aylton; Job, Aldo Eloizo

2018-01-01

Image segmentation, the process of separating the elements within a picture, is frequently used for obtaining information from photomicrographs. Segmentation methods should be used with reservations, since incorrect results can mislead when interpreting regions of interest (ROI). This decreases the success rate of extra procedures. Multi-Level Starlet Segmentation (MLSS) and Multi-Level Starlet Optimal Segmentation (MLSOS) were developed to be an alternative for general segmentation tools. These methods gave rise to Jansen-MIDAS, an open-source software. A scientist can use it to obtain several segmentations of hers/his photomicrographs. It is a reliable alternative to process different types of photomicrographs: previous versions of Jansen-MIDAS were used to segment ROI in photomicrographs of two different materials, with an accuracy superior to 89%. © 2017 Wiley Periodicals, Inc.

Optimization-based image reconstruction in x-ray computed tomography by sparsity exploitation of local continuity and nonlocal spatial self-similarity

NASA Astrophysics Data System (ADS)

Han-Ming, Zhang; Lin-Yuan, Wang; Lei, Li; Bin, Yan; Ai-Long, Cai; Guo-En, Hu

2016-07-01

The additional sparse prior of images has been the subject of much research in problems of sparse-view computed tomography (CT) reconstruction. A method employing the image gradient sparsity is often used to reduce the sampling rate and is shown to remove the unwanted artifacts while preserve sharp edges, but may cause blocky or patchy artifacts. To eliminate this drawback, we propose a novel sparsity exploitation-based model for CT image reconstruction. In the presented model, the sparse representation and sparsity exploitation of both gradient and nonlocal gradient are investigated. The new model is shown to offer the potential for better results by introducing a similarity prior information of the image structure. Then, an effective alternating direction minimization algorithm is developed to optimize the objective function with a robust convergence result. Qualitative and quantitative evaluations have been carried out both on the simulation and real data in terms of accuracy and resolution properties. The results indicate that the proposed method can be applied for achieving better image-quality potential with the theoretically expected detailed feature preservation. Project supported by the National Natural Science Foundation of China (Grant No. 61372172).

Tensor Factorization for Low-Rank Tensor Completion.

PubMed

Zhou, Pan; Lu, Canyi; Lin, Zhouchen; Zhang, Chao

2018-03-01

Recently, a tensor nuclear norm (TNN) based method was proposed to solve the tensor completion problem, which has achieved state-of-the-art performance on image and video inpainting tasks. However, it requires computing tensor singular value decomposition (t-SVD), which costs much computation and thus cannot efficiently handle tensor data, due to its natural large scale. Motivated by TNN, we propose a novel low-rank tensor factorization method for efficiently solving the 3-way tensor completion problem. Our method preserves the low-rank structure of a tensor by factorizing it into the product of two tensors of smaller sizes. In the optimization process, our method only needs to update two smaller tensors, which can be more efficiently conducted than computing t-SVD. Furthermore, we prove that the proposed alternating minimization algorithm can converge to a Karush-Kuhn-Tucker point. Experimental results on the synthetic data recovery, image and video inpainting tasks clearly demonstrate the superior performance and efficiency of our developed method over state-of-the-arts including the TNN and matricization methods.

A fast method for the detection of vascular structure in images, based on the continuous wavelet transform with the Morlet wavelet having a low central frequency

NASA Astrophysics Data System (ADS)

Postnikov, Eugene B.; Tsoy, Maria O.; Kurochkin, Maxim A.; Postnov, Dmitry E.

2017-04-01

A manual measurement of blood vessels diameter is a conventional component of routine visual assessment of microcirculation, say, during optical capillaroscopy. However, many modern optical methods for blood flow measurements demand the reliable procedure for a fully automated detection of vessels and estimation of their diameter that is a challenging task. Specifically, if one measure the velocity of red blood cells by means of laser speckle imaging, then visual measurements become impossible, while the velocity-based estimation has their own limitations. One of promising approaches is based on fast switching of illumination type, but it drastically reduces the observation time, and hence, the achievable quality of images. In the present work we address this problem proposing an alternative method for the processing of noisy images of vascular structure, which extracts the mask denoting locations of vessels, based on the application of the continuous wavelet transform with the Morlet wavelet having small central frequencies. Such a method combines a reasonable accuracy with the possibility of fast direct implementation to images. Discussing the latter, we describe in details a new MATLAB program code realization for the CWT with the Morlet wavelet, which does not use loops completely replaced with element-by-element operations that drastically reduces the computation time.

Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data.

PubMed

Veganzones, Miguel A; Simoes, Miguel; Licciardi, Giorgio; Yokoya, Naoto; Bioucas-Dias, Jose M; Chanussot, Jocelyn

2016-01-01

Remote sensing hyperspectral images (HSIs) are quite often low rank, in the sense that the data belong to a low dimensional subspace/manifold. This has been recently exploited for the fusion of low spatial resolution HSI with high spatial resolution multispectral images in order to obtain super-resolution HSI. Most approaches adopt an unmixing or a matrix factorization perspective. The derived methods have led to state-of-the-art results when the spectral information lies in a low-dimensional subspace/manifold. However, if the subspace/manifold dimensionality spanned by the complete data set is large, i.e., larger than the number of multispectral bands, the performance of these methods mainly decreases because the underlying sparse regression problem is severely ill-posed. In this paper, we propose a local approach to cope with this difficulty. Fundamentally, we exploit the fact that real world HSIs are locally low rank, that is, pixels acquired from a given spatial neighborhood span a very low-dimensional subspace/manifold, i.e., lower or equal than the number of multispectral bands. Thus, we propose to partition the image into patches and solve the data fusion problem independently for each patch. This way, in each patch the subspace/manifold dimensionality is low enough, such that the problem is not ill-posed anymore. We propose two alternative approaches to define the hyperspectral super-resolution through local dictionary learning using endmember induction algorithms. We also explore two alternatives to define the local regions, using sliding windows and binary partition trees. The effectiveness of the proposed approaches is illustrated with synthetic and semi real data.

Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model

PubMed Central

Abdelnour, A. Farras; Huppert, Theodore

2009-01-01

Near-infrared spectroscopy is a non-invasive neuroimaging method which uses light to measure changes in cerebral blood oxygenation associated with brain activity. In this work, we demonstrate the ability to record and analyze images of brain activity in real-time using a 16-channel continuous wave optical NIRS system. We propose a novel real-time analysis framework using an adaptive Kalman filter and a state–space model based on a canonical general linear model of brain activity. We show that our adaptive model has the ability to estimate single-trial brain activity events as we apply this method to track and classify experimental data acquired during an alternating bilateral self-paced finger tapping task. PMID:19457389

Non-invasive neuroimaging using near-infrared light

NASA Technical Reports Server (NTRS)

Strangman, Gary; Boas, David A.; Sutton, Jeffrey P.

2002-01-01

This article reviews diffuse optical brain imaging, a technique that employs near-infrared light to non-invasively probe the brain for changes in parameters relating to brain function. We describe the general methodology, including types of measurements and instrumentation (including the tradeoffs inherent in the various instrument components), and the basic theory required to interpret the recorded data. A brief review of diffuse optical applications is included, with an emphasis on research that has been done with psychiatric populations. Finally, we discuss some practical issues and limitations that are relevant when conducting diffuse optical experiments. We find that, while diffuse optics can provide substantial advantages to the psychiatric researcher relative to the alternative brain imaging methods, the method remains substantially underutilized in this field.

Ultrafast Pulse Sequencing for Fast Projective Measurements of Atomic Hyperfine Qubits

NASA Astrophysics Data System (ADS)

Ip, Michael; Ransford, Anthony; Campbell, Wesley

2015-05-01

Projective readout of quantum information stored in atomic hyperfine structure typically uses state-dependent CW laser-induced fluorescence. This method requires an often sophisticated imaging system to spatially filter out the background CW laser light. We present an alternative approach that instead uses simple pulse sequences from a mode-locked laser to affect the same state-dependent excitations in less than 1 ns. The resulting atomic fluorescence occurs in the dark, allowing the placement of non-imaging detectors right next to the atom to improve the qubit state detection efficiency and speed. We also discuss methods of Doppler cooling with mode-locked lasers for trapped ions, where the creation of the necessary UV light is often difficult with CW lasers.

Multiple velocity encoding in the phase of an MRI signal

NASA Astrophysics Data System (ADS)

Benitez-Read, E. E.

2017-01-01

The measurement of fluid velocity by encoding it in the phase of a magnetic resonance imaging (MRI) signal could allow the discrimination of the stationary spins signals from those of moving spins. This results in a wide variety of applications i.e. in medicine, in order to obtain more than angiograms, blood velocity images of veins, arteries and other vessels without having static tissue perturbing the signal of fluid in motion. The work presented in this paper is a theoretical analysis of some novel methods for multiple fluid velocity encoding in the phase of an MRI signal. These methods are based on a tripolar gradient (TPG) and can be an alternative to the conventional methods based on a bipolar gradient (BPG) and could be more suitable for multiple velocity encoding in the phase of an MRI signal.

Phased array ghost elimination (PAGE) for segmented SSFP imaging with interrupted steady-state.

PubMed

Kellman, Peter; Guttman, Michael A; Herzka, Daniel A; McVeigh, Elliot R

2002-12-01

Steady-state free precession (SSFP) has recently proven to be valuable for cardiac imaging due to its high signal-to-noise ratio and blood-myocardium contrast. Data acquired using ECG-triggered, segmented sequences during the approach to steady-state, or return to steady-state after interruption, may have ghost artifacts due to periodic k-space distortion. Schemes involving several preparatory RF pulses have been proposed to restore steady-state, but these consume imaging time during early systole. Alternatively, the phased-array ghost elimination (PAGE) method may be used to remove ghost artifacts from the first several frames. PAGE was demonstrated for cardiac cine SSFP imaging with interrupted steady-state using a simple alpha/2 magnetization preparation and storage scheme and a spatial tagging preparation.

Failure Analysis of CCD Image Sensors Using SQUID and GMR Magnetic Current Imaging

NASA Technical Reports Server (NTRS)

Felt, Frederick S.

2005-01-01

During electrical testing of a Full Field CCD Image Senor, electrical shorts were detected on three of six devices. These failures occurred after the parts were soldered to the PCB. Failure analysis was performed to determine the cause and locations of these failures on the devices. After removing the fiber optic faceplate, optical inspection was performed on the CCDs to understand the design and package layout. Optical inspection revealed that the device had a light shield ringing the CCD array. This structure complicated the failure analysis. Alternate methods of analysis were considered, including liquid crystal, light and thermal emission, LT/A, TT/A SQUID, and MP. Of these, SQUID and MP techniques were pursued for further analysis. Also magnetoresistive current imaging technology is discussed and compared to SQUID.

Image processing and analysis using neural networks for optometry area

NASA Astrophysics Data System (ADS)

Netto, Antonio V.; Ferreira de Oliveira, Maria C.

2002-11-01

In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

Investigation of two methods to quantify noise in digital images based on the perception of the human eye

NASA Astrophysics Data System (ADS)

Kleinmann, Johanna; Wueller, Dietmar

2007-01-01

Since the signal to noise measuring method as standardized in the normative part of ISO 15739:2002(E)1 does not quantify noise in a way that matches the perception of the human eye, two alternative methods have been investigated which may be appropriate to quantify the noise perception in a physiological manner: - the model of visual noise measurement proposed by Hung et al2 (as described in the informative annex of ISO 15739:20021) which tries to simulate the process of human vision by using the opponent space and contrast sensitivity functions and uses the CIEL*u*v*1976 colour space for the determination of a so called visual noise value. - The S-CIELab model and CIEDE2000 colour difference proposed by Fairchild et al 3 which simulates human vision approximately the same way as Hung et al2 but uses an image comparison afterwards based on CIEDE2000. With a psychophysical experiment based on just noticeable difference (JND), threshold images could be defined, with which the two approaches mentioned above were tested. The assumption is that if the method is valid, the different threshold images should get the same 'noise value'. The visual noise measurement model results in similar visual noise values for all the threshold images. The method is reliable to quantify at least the JND for noise in uniform areas of digital images. While the visual noise measurement model can only evaluate uniform colour patches in images, the S-CIELab model can be used on images with spatial content as well. The S-CIELab model also results in similar colour difference values for the set of threshold images, but with some limitations: for images which contain spatial structures besides the noise, the colour difference varies depending on the contrast of the spatial content.

Four-Dimensional Respiratory Motion-Resolved Whole Heart Coronary MR Angiography

PubMed Central

Piccini, Davide; Feng, Li; Bonanno, Gabriele; Coppo, Simone; Yerly, Jérôme; Lim, Ruth P.; Schwitter, Juerg; Sodickson, Daniel K.; Otazo, Ricardo; Stuber, Matthias

2016-01-01

Purpose Free-breathing whole-heart coronary MR angiography (MRA) commonly uses navigators to gate respiratory motion, resulting in lengthy and unpredictable acquisition times. Conversely, self-navigation has 100% scan efficiency, but requires motion correction over a broad range of respiratory displacements, which may introduce image artifacts. We propose replacing navigators and self-navigation with a respiratory motion-resolved reconstruction approach. Methods Using a respiratory signal extracted directly from the imaging data, individual signal-readouts are binned according to their respiratory states. The resultant series of undersampled images are reconstructed using an extradimensional golden-angle radial sparse parallel imaging (XD-GRASP) algorithm, which exploits sparsity along the respiratory dimension. Whole-heart coronary MRA was performed in 11 volunteers and four patients with the proposed methodology. Image quality was compared with that obtained with one-dimensional respiratory self-navigation. Results Respiratory-resolved reconstruction effectively suppressed respiratory motion artifacts. The quality score for XD-GRASP reconstructions was greater than or equal to self-navigation in 80/88 coronary segments, reaching diagnostic quality in 61/88 segments versus 41/88. Coronary sharpness and length were always superior for the respiratory-resolved datasets, reaching statistical significance (P < 0.05) in most cases. Conclusion XD-GRASP represents an attractive alternative for handling respiratory motion in free-breathing whole heart MRI and provides an effective alternative to self-navigation. PMID:27052418

Sparse-coding denoising applied to reversible conformational switching of a porphyrin self-assembled monolayer induced by scanning tunnelling microscopy.

PubMed

Oliveira, J; Bragança, A M; Alcácer, L; Morgado, J; Figueiredo, M; Bioucas-Dias, J; Ferreira, Q

2018-04-14

Scanning tunnelling microscopy (STM) was used to induce conformational molecular switching on a self-assembled monolayer of zinc-octaethylporphyrin on a graphite/tetradecane interface at room temperature. A reversible conformational change controlled by applying a tip voltage was observed. Consecutive STM images acquired at alternating tip voltages showed that at 0.4 V the porphyrin monolayer presents a molecular arrangement formed by alternate rows with two different types of structural conformations and when the potential is increased to 0.7 V the monolayer presents only one type of conformation. In this paper, we characterize these porphyrin conformational dynamics by analyzing the STM images, which were improved for better quality and interpretation by means of a denoising algorithm, adapted to process STM images from state of the art image processing and analysis methods. STM remains the best technique to 'see' and to manipulate the matter at atomic scale. A very sharp tip a few angstroms of the surface can provide images of molecules and atoms with a powerful resolution. However, these images are strongly affected by noise which is necessary to correct and eliminate. This paper is about new computational tools specifically developed to denoise the images acquired with STM. The new algorithms were tested in STM images, obtained at room temperature, of porphyrin monolayer which presents reversible conformational change in function of the tip bias voltage. Images with high resolution, acquired in real time, show that the porphyrins have different molecular arrangements whether the tip voltage is 0.4 V or 0.7 V. © 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.

A computed tomography-based spatial normalization for the analysis of [18F] fluorodeoxyglucose positron emission tomography of the brain.

PubMed

Cho, Hanna; Kim, Jin Su; Choi, Jae Yong; Ryu, Young Hoon; Lyoo, Chul Hyoung

2014-01-01

We developed a new computed tomography (CT)-based spatial normalization method and CT template to demonstrate its usefulness in spatial normalization of positron emission tomography (PET) images with [(18)F] fluorodeoxyglucose (FDG) PET studies in healthy controls. Seventy healthy controls underwent brain CT scan (120 KeV, 180 mAs, and 3 mm of thickness) and [(18)F] FDG PET scans using a PET/CT scanner. T1-weighted magnetic resonance (MR) images were acquired for all subjects. By averaging skull-stripped and spatially-normalized MR and CT images, we created skull-stripped MR and CT templates for spatial normalization. The skull-stripped MR and CT images were spatially normalized to each structural template. PET images were spatially normalized by applying spatial transformation parameters to normalize skull-stripped MR and CT images. A conventional perfusion PET template was used for PET-based spatial normalization. Regional standardized uptake values (SUV) measured by overlaying the template volume of interest (VOI) were compared to those measured with FreeSurfer-generated VOI (FSVOI). All three spatial normalization methods underestimated regional SUV values by 0.3-20% compared to those measured with FSVOI. The CT-based method showed slightly greater underestimation bias. Regional SUV values derived from all three spatial normalization methods were correlated significantly (p < 0.0001) with those measured with FSVOI. CT-based spatial normalization may be an alternative method for structure-based spatial normalization of [(18)F] FDG PET when MR imaging is unavailable. Therefore, it is useful for PET/CT studies with various radiotracers whose uptake is expected to be limited to specific brain regions or highly variable within study population.

A Method for 3D-Reconstruction of a Muscle Thick Filament Using the Tilt Series Images of a Single Filament Electron Tomogram

PubMed Central

Márquez, G.; Pinto, A.; Alamo, L.; Baumann, B.; Ye, F.; Winkler, H.; Taylor, K.; Padrón, R.

2014-01-01

Summary Myosin interacting-heads (MIH) motifs are visualized in 3D-reconstructions of thick filaments from striated muscle. These reconstructions are calculated by averaging methods using images from electron micrographs of grids prepared using numerous filament preparations. Here we propose an alternative method to calculate the 3D-reconstruction of a single thick filament using only a tilt series images recorded by electron tomography. Relaxed thick filaments, prepared from tarantula leg muscle homogenates, were negatively stained. Single-axis tilt series of single isolated thick filaments were obtained with the electron microscope at a low electron dose, and recorded on a CCD camera by electron tomography. An IHRSR 3D-recontruction was calculated from the tilt series images of a single thick filament. The reconstruction was enhanced by including in the search stage dual tilt image segments while only single tilt along the filament axis is usually used, as well as applying a band pass filter just before the back projection. The reconstruction from a single filament has a 40 Å resolution and clearly shows the presence of MIH motifs. In contrast, the electron tomogram 3D-reconstruction of the same thick filament –calculated without any image averaging and/or imposition of helical symmetry- only reveals MIH motifs infrequently. This is –to our knowledge- the first application of the IHRSR method to calculate a 3D reconstruction from tilt series images. This single filament IHRSR reconstruction method (SF-IHRSR) should provide a new tool to assess structural differences between well-ordered thick (or thin) filaments in a grid by recording separately their electron tomograms. PMID:24727133

A method for 3D-reconstruction of a muscle thick filament using the tilt series images of a single filament electron tomogram.

PubMed

Márquez, G; Pinto, A; Alamo, L; Baumann, B; Ye, F; Winkler, H; Taylor, K; Padrón, R

2014-05-01

Myosin interacting-heads (MIH) motifs are visualized in 3D-reconstructions of thick filaments from striated muscle. These reconstructions are calculated by averaging methods using images from electron micrographs of grids prepared using numerous filament preparations. Here we propose an alternative method to calculate the 3D-reconstruction of a single thick filament using only a tilt series images recorded by electron tomography. Relaxed thick filaments, prepared from tarantula leg muscle homogenates, were negatively stained. Single-axis tilt series of single isolated thick filaments were obtained with the electron microscope at a low electron dose, and recorded on a CCD camera by electron tomography. An IHRSR 3D-recontruction was calculated from the tilt series images of a single thick filament. The reconstruction was enhanced by including in the search stage dual tilt image segments while only single tilt along the filament axis is usually used, as well as applying a band pass filter just before the back projection. The reconstruction from a single filament has a 40 Å resolution and clearly shows the presence of MIH motifs. In contrast, the electron tomogram 3D-reconstruction of the same thick filament - calculated without any image averaging and/or imposition of helical symmetry - only reveals MIH motifs infrequently. This is - to our knowledge - the first application of the IHRSR method to calculate a 3D reconstruction from tilt series images. This single filament IHRSR reconstruction method (SF-IHRSR) should provide a new tool to assess structural differences between well-ordered thick (or thin) filaments in a grid by recording separately their electron tomograms. Copyright © 2014 Elsevier Inc. All rights reserved.

SNR-optimized phase-sensitive dual-acquisition turbo spin echo imaging: a fast alternative to FLAIR.

PubMed

Lee, Hyunyeol; Park, Jaeseok

2013-07-01

Phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo imaging was recently introduced, producing high-resolution isotropic cerebrospinal fluid attenuated brain images without long inversion recovery preparation. Despite the advantages, the weighted-averaging-based technique suffers from noise amplification resulting from different levels of cerebrospinal fluid signal modulations over the two acquisitions. The purpose of this work is to develop a signal-to-noise ratio-optimized version of the phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo. Variable refocusing flip angles in the first acquisition are calculated using a three-step prescribed signal evolution while those in the second acquisition are calculated using a two-step pseudo-steady state signal transition with a high flip-angle pseudo-steady state at a later portion of the echo train, balancing the levels of cerebrospinal fluid signals in both the acquisitions. Low spatial frequency signals are sampled during the high flip-angle pseudo-steady state to further suppress noise. Numerical simulations of the Bloch equations were performed to evaluate signal evolutions of brain tissues along the echo train and optimize imaging parameters. In vivo studies demonstrate that compared with conventional phase-sensitive dual-acquisition single-slab three-dimensional turbo spin echo, the proposed optimization yields 74% increase in apparent signal-to-noise ratio for gray matter and 32% decrease in imaging time. The proposed method can be a potential alternative to conventional fluid-attenuated imaging. Copyright © 2012 Wiley Periodicals, Inc.

Spotting East African mammals in open savannah from space.

PubMed

Yang, Zheng; Wang, Tiejun; Skidmore, Andrew K; de Leeuw, Jan; Said, Mohammed Y; Freer, Jim

2014-01-01

Knowledge of population dynamics is essential for managing and conserving wildlife. Traditional methods of counting wild animals such as aerial survey or ground counts not only disturb animals, but also can be labour intensive and costly. New, commercially available very high-resolution satellite images offer great potential for accurate estimates of animal abundance over large open areas. However, little research has been conducted in the area of satellite-aided wildlife census, although computer processing speeds and image analysis algorithms have vastly improved. This paper explores the possibility of detecting large animals in the open savannah of Maasai Mara National Reserve, Kenya from very high-resolution GeoEye-1 satellite images. A hybrid image classification method was employed for this specific purpose by incorporating the advantages of both pixel-based and object-based image classification approaches. This was performed in two steps: firstly, a pixel-based image classification method, i.e., artificial neural network was applied to classify potential targets with similar spectral reflectance at pixel level; and then an object-based image classification method was used to further differentiate animal targets from the surrounding landscapes through the applications of expert knowledge. As a result, the large animals in two pilot study areas were successfully detected with an average count error of 8.2%, omission error of 6.6% and commission error of 13.7%. The results of the study show for the first time that it is feasible to perform automated detection and counting of large wild animals in open savannahs from space, and therefore provide a complementary and alternative approach to the conventional wildlife survey techniques.

Visual Estimation of Bacterial Growth Level in Microfluidic Culture Systems.

PubMed

Kim, Kyukwang; Kim, Seunggyu; Jeon, Jessie S

2018-02-03

Microfluidic devices are an emerging platform for a variety of experiments involving bacterial cell culture, and has advantages including cost and convenience. One inevitable step during bacterial cell culture is the measurement of cell concentration in the channel. The optical density measurement technique is generally used for bacterial growth estimation, but it is not applicable to microfluidic devices due to the small sample volumes in microfluidics. Alternately, cell counting or colony-forming unit methods may be applied, but these do not work in situ; nor do these methods show measurement results immediately. To this end, we present a new vision-based method to estimate the growth level of the bacteria in microfluidic channels. We use Fast Fourier transform (FFT) to detect the frequency level change of the microscopic image, focusing on the fact that the microscopic image becomes rough as the number of cells in the field of view increases, adding high frequencies to the spectrum of the image. Two types of microfluidic devices are used to culture bacteria in liquid and agar gel medium, and time-lapsed images are captured. The images obtained are analyzed using FFT, resulting in an increase in high-frequency noise proportional to the time passed. Furthermore, we apply the developed method in the microfluidic antibiotics susceptibility test by recognizing the regional concentration change of the bacteria that are cultured in the antibiotics gradient. Finally, a deep learning-based data regression is performed on the data obtained by the proposed vision-based method for robust reporting of data.

Optical aberration correction for simple lenses via sparse representation

NASA Astrophysics Data System (ADS)

Cui, Jinlin; Huang, Wei

2018-04-01

Simple lenses with spherical surfaces are lightweight, inexpensive, highly flexible, and can be easily processed. However, they suffer from optical aberrations that lead to limitations in high-quality photography. In this study, we propose a set of computational photography techniques based on sparse signal representation to remove optical aberrations, thereby allowing the recovery of images captured through a single-lens camera. The primary advantage of the proposed method is that many prior point spread functions calibrated at different depths are successfully used for restoring visual images in a short time, which can be generally applied to nonblind deconvolution methods for solving the problem of the excessive processing time caused by the number of point spread functions. The optical software CODE V is applied for examining the reliability of the proposed method by simulation. The simulation results reveal that the suggested method outperforms the traditional methods. Moreover, the performance of a single-lens camera is significantly enhanced both qualitatively and perceptually. Particularly, the prior information obtained by CODE V can be used for processing the real images of a single-lens camera, which provides an alternative approach to conveniently and accurately obtain point spread functions of single-lens cameras.

Quantitative in vivo cell-surface receptor imaging in oncology: kinetic modeling & paired-agent principles from nuclear medicine and optical imaging

PubMed Central

Tichauer, Kenneth M.; Wang, Yu; Pogue, Brian W.; Liu, Jonathan T. C.

2015-01-01

The development of methods to accurately quantify cell-surface receptors in living tissues would have a seminal impact in oncology. For example, accurate measures of receptor density in vivo could enhance early detection or surgical resection of tumors via protein-based contrast, allowing removal of cancer with high phenotype specificity. Alternatively, accurate receptor expression estimation could be used as a biomarker to guide patient-specific clinical oncology targeting of the same molecular pathway. Unfortunately, conventional molecular contrast-based imaging approaches are not well adapted to accurately estimating the nanomolar-level cell-surface receptor concentrations in tumors, as most images are dominated by nonspecific sources of contrast such as high vascular permeability and lymphatic inhibition. This article reviews approaches for overcoming these limitations based upon tracer kinetic modeling and the use of emerging protocols to estimate binding potential and the related receptor concentration. Methods such as using single time point imaging or a reference-tissue approach tend to have low accuracy in tumors, whereas paired-agent methods or advanced kinetic analyses are more promising to eliminate the dominance of interstitial space in the signals. Nuclear medicine and optical molecular imaging are the primary modalities used, as they have the nanomolar level sensitivity needed to quantify cell-surface receptor concentrations present in tissue, although each likely has a different clinical niche. PMID:26134619

An alternative approach to account for patient organ doses from imaging guidance procedures.

PubMed

Nelson, Alan P; Ding, George X

2014-07-01

To investigate the feasibility of an alternative method of accounting for additional organ doses resulting from image guidance procedures during patient treatment planning through tabulated values based on scan protocol and scan site. Patient-specific imaging dose to 30 patients resulting from Varian OBI kV-CBCT scans using the Standard Head (17 patients), Low-dose Thorax (8 patients), and Pelvic (5 patients) scan protocols were retrospectively calculated using Monte Carlo methods. Dose dependence on scan location and patient geometry was explored. Patient organ doses were analyzed by using dose-volume histograms and expressed by the mean, minimum dose delivered to 50% of the organ volume, D50. The reported doses are dose-to-medium instead of dose-to-water. The organ doses from all patient-specific calculations show predictable and limited ranges across patients. For brain isocenters using Standard Head Scans: Bone: 0.7-1.1 cGy, Brain: 0.2-0.3 cGy, Brainstem: 0.2-0.3 cGy, Skin: 0.3-0.4 cGy, Eye: 0.03-0.3 cGy. For head and neck patients using the Standard Head Scan: Bone: 0.3-0.6 cGy, Parotids: 0.3-0.4 cGy, Spinal Cord: 0.15-0.25 cGy, Thyroid: 0.1-0.25 cGy, Skin: 0.2-0.3 cGy, Trachea-Esophagus: 0.1-0.2 cGy. For chest using Thorax Scans: Bone: 1.1-1.8 cGy, Soft tissue organs (Bowel, Lung, Heart, Kidney, Esophagus, and Spinal Cord): 0.3-0.6 cGy. For abdominal site using Pelvic Scans: Bone: 3.2-4.2 cGy. Soft tissue organs (Bladder, Bowel, Rectum, Prostate, and Skin) D50s fell between 1.2 and 2.2 cGy. Femoral Heads: 2.5-3.4 cGy. It is adequate to estimate and account for organ dose by using tabulated values based on scan procedure and site because organ doses from imaging procedures are only modestly dependent upon scan location and body size. Considering the dose variation and magnitude of dose from each scan protocol in comparison to therapeutic doses, this approach provides a simple alternative to account for additional imaging guidance doses during patient treatment planning. Clinicians can use these tabulated values to make informed decisions in selecting the appropriate imaging procedures and imaging frequency during radiotherapy treatment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Face recognition in the thermal infrared domain

NASA Astrophysics Data System (ADS)

Kowalski, M.; Grudzień, A.; Palka, N.; Szustakowski, M.

2017-10-01

Biometrics refers to unique human characteristics. Each unique characteristic may be used to label and describe individuals and for automatic recognition of a person based on physiological or behavioural properties. One of the most natural and the most popular biometric trait is a face. The most common research methods on face recognition are based on visible light. State-of-the-art face recognition systems operating in the visible light spectrum achieve very high level of recognition accuracy under controlled environmental conditions. Thermal infrared imagery seems to be a promising alternative or complement to visible range imaging due to its relatively high resistance to illumination changes. A thermal infrared image of the human face presents its unique heat-signature and can be used for recognition. The characteristics of thermal images maintain advantages over visible light images, and can be used to improve algorithms of human face recognition in several aspects. Mid-wavelength or far-wavelength infrared also referred to as thermal infrared seems to be promising alternatives. We present the study on 1:1 recognition in thermal infrared domain. The two approaches we are considering are stand-off face verification of non-moving person as well as stop-less face verification on-the-move. The paper presents methodology of our studies and challenges for face recognition systems in the thermal infrared domain.

Off-resonance artifacts correction with convolution in k-space (ORACLE).

PubMed

Lin, Wei; Huang, Feng; Simonotto, Enrico; Duensing, George R; Reykowski, Arne

2012-06-01

Off-resonance artifacts hinder the wider applicability of echo-planar imaging and non-Cartesian MRI methods such as radial and spiral. In this work, a general and rapid method is proposed for off-resonance artifacts correction based on data convolution in k-space. The acquired k-space is divided into multiple segments based on their acquisition times. Off-resonance-induced artifact within each segment is removed by applying a convolution kernel, which is the Fourier transform of an off-resonance correcting spatial phase modulation term. The field map is determined from the inverse Fourier transform of a basis kernel, which is calibrated from data fitting in k-space. The technique was demonstrated in phantom and in vivo studies for radial, spiral and echo-planar imaging datasets. For radial acquisitions, the proposed method allows the self-calibration of the field map from the imaging data, when an alternating view-angle ordering scheme is used. An additional advantage for off-resonance artifacts correction based on data convolution in k-space is the reusability of convolution kernels to images acquired with the same sequence but different contrasts. Copyright © 2011 Wiley-Liss, Inc.

A Wigner-based ray-tracing method for imaging simulations

NASA Astrophysics Data System (ADS)

Mout, B. M.; Wick, M.; Bociort, F.; Urbach, H. P.

2015-09-01

The Wigner Distribution Function (WDF) forms an alternative representation of the optical field. It can be a valuable tool for understanding and classifying optical systems. Furthermore, it possesses properties that make it suitable for optical simulations: both the intensity and the angular spectrum can be easily obtained from the WDF and the WDF remains constant along the paths of paraxial geometrical rays. In this study we use these properties by implementing a numerical Wigner-Based Ray-Tracing method (WBRT) to simulate diffraction effects at apertures in free-space and in imaging systems. Both paraxial and non-paraxial systems are considered and the results are compared with numerical implementations of the Rayleigh-Sommerfeld and Fresnel diffraction integrals to investigate the limits of the applicability of this approach. The results of the different methods are in good agreement when simulating free-space diffraction or calculating point spread functions (PSFs) for aberration-free imaging systems, even at numerical apertures exceeding the paraxial regime. For imaging systems with aberrations, the PSFs of WBRT diverge from the results using diffraction integrals. For larger aberrations WBRT predicts negative intensities, suggesting that this model is unable to deal with aberrations.

Towards fast and accurate temperature mapping with proton resonance frequency-based MR thermometry

PubMed Central

Yuan, Jing; Mei, Chang-Sheng; Panych, Lawrence P.; McDannold, Nathan J.; Madore, Bruno

2012-01-01

The capability to image temperature is a very attractive feature of MRI and has been actively exploited for guiding minimally-invasive thermal therapies. Among many MR-based temperature-sensitive approaches, proton resonance frequency (PRF) thermometry provides the advantage of excellent linearity of signal with temperature over a large temperature range. Furthermore, the PRF shift has been shown to be fairly independent of tissue type and thermal history. For these reasons, PRF method has evolved into the most widely used MR-based thermometry method. In the present paper, the basic principles of PRF-based temperature mapping will be reviewed, along with associated pulse sequence designs. Technical advancements aimed at increasing the imaging speed and/or temperature accuracy of PRF-based thermometry sequences, such as image acceleration, fat suppression, reduced field-of-view imaging, as well as motion tracking and correction, will be discussed. The development of accurate MR thermometry methods applicable to moving organs with non-negligible fat content represents a very challenging goal, but recent developments suggest that this goal may be achieved. If so, MR-guided thermal therapies may be expected to play an increasingly-important therapeutic and palliative role, as a minimally-invasive alternative to surgery. PMID:22773966

Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction

NASA Astrophysics Data System (ADS)

Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing

2018-02-01

Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.

Detection of explosives on the surface of banknotes by Raman hyperspectral imaging and independent component analysis.

PubMed

Almeida, Mariana R; Correa, Deleon N; Zacca, Jorge J; Logrado, Lucio Paulo Lima; Poppi, Ronei J

2015-02-20

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50 μg cm(-2). Copyright © 2014 Elsevier B.V. All rights reserved.

Global high-frequency source imaging accounting for complexity in Green's functions

NASA Astrophysics Data System (ADS)

Lambert, V.; Zhan, Z.

2017-12-01

The general characterization of earthquake source processes at long periods has seen great success via seismic finite fault inversion/modeling. Complementary techniques, such as seismic back-projection, extend the capabilities of source imaging to higher frequencies and reveal finer details of the rupture process. However, such high frequency methods are limited by the implicit assumption of simple Green's functions, which restricts the use of global arrays and introduces artifacts (e.g., sweeping effects, depth/water phases) that require careful attention. This motivates the implementation of an imaging technique that considers the potential complexity of Green's functions at high frequencies. We propose an alternative inversion approach based on the modest assumption that the path effects contributing to signals within high-coherency subarrays share a similar form. Under this assumption, we develop a method that can combine multiple high-coherency subarrays to invert for a sparse set of subevents. By accounting for potential variability in the Green's functions among subarrays, our method allows for the utilization of heterogeneous global networks for robust high resolution imaging of the complex rupture process. The approach also provides a consistent framework for examining frequency-dependent radiation across a broad frequency spectrum.

The variability of software scoring of the CDMAM phantom associated with a limited number of images

NASA Astrophysics Data System (ADS)

Yang, Chang-Ying J.; Van Metter, Richard

2007-03-01

Software scoring approaches provide an attractive alternative to human evaluation of CDMAM images from digital mammography systems, particularly for annual quality control testing as recommended by the European Protocol for the Quality Control of the Physical and Technical Aspects of Mammography Screening (EPQCM). Methods for correlating CDCOM-based results with human observer performance have been proposed. A common feature of all methods is the use of a small number (at most eight) of CDMAM images to evaluate the system. This study focuses on the potential variability in the estimated system performance that is associated with these methods. Sets of 36 CDMAM images were acquired under carefully controlled conditions from three different digital mammography systems. The threshold visibility thickness (TVT) for each disk diameter was determined using previously reported post-analysis methods from the CDCOM scorings for a randomly selected group of eight images for one measurement trial. This random selection process was repeated 3000 times to estimate the variability in the resulting TVT values for each disk diameter. The results from using different post-analysis methods, different random selection strategies and different digital systems were compared. Additional variability of the 0.1 mm disk diameter was explored by comparing the results from two different image data sets acquired under the same conditions from the same system. The magnitude and the type of error estimated for experimental data was explained through modeling. The modeled results also suggest a limitation in the current phantom design for the 0.1 mm diameter disks. Through modeling, it was also found that, because of the binomial statistic nature of the CDMAM test, the true variability of the test could be underestimated by the commonly used method of random re-sampling.

Magnetic resonance imaging in experimental stroke and comparison with histology: systematic review and meta-analysis.

PubMed

Milidonis, Xenios; Marshall, Ian; Macleod, Malcolm R; Sena, Emily S

2015-03-01

Because the new era of preclinical stroke research demands improvements in validity and generalizability of findings, moving from single site to multicenter studies could be pivotal. However, the conduct of magnetic resonance imaging (MRI) in stroke remains ill-defined. We sought to assess the variability in the use of MRI for evaluating lesions post stroke and to examine the possibility as an alternative to gold standard histology for measuring the infarct size. We identified animal studies of ischemic stroke reporting lesion sizes using MRI. We assessed the degree of heterogeneity and reporting of scanning protocols, postprocessing methods, study design characteristics, and study quality. Studies performing histological evaluation of infarct size were further selected to compare with corresponding MRI using meta-regression. Fifty-four articles undertaking a total of 78 different MRI scanning protocols met the inclusion criteria. T2-weighted imaging was most frequently used (83% of the studies), followed by diffusion-weighted imaging (43%). Reporting of the imaging parameters was adequate, but heterogeneity between studies was high. Twelve studies assessed the infarct size using both MRI and histology at corresponding time points, with T2-weighted imaging-based treatment effect having a significant positive correlation with histology (; P<0.001). Guidelines for standardized use and reporting of MRI in preclinical stroke are urgently needed. T2-weighted imaging could be used as an effective in vivo alternative to histology for estimating treatment effects based on the extent of infarction; however, additional studies are needed to explore the effect of individual parameters. © 2015 American Heart Association, Inc.

Comparison of Hemispheric Activation during Mental Word and Rhyme Generation Using Transcranial Doppler Sonography

ERIC Educational Resources Information Center

Krach, Soren; Hartje, Wolfgang

2006-01-01

The Wada test is at present the method of choice for preoperative assessment of patients who require surgery close to cortical language areas. It is, however, an invasive test with an attached morbidity risk. By now, an alternative to the Wada test is to combine a lexical word generation paradigm with non-invasive imaging techniques. However,…

Decoupling Intensity Radiated by the Emitter in Distance Estimation from Camera to IR Emitter

PubMed Central

Cano-García, Angel E.; Galilea, José Luis Lázaro; Fernández, Pedro; Infante, Arturo Luis; Pompa-Chacón, Yamilet; Vázquez, Carlos Andrés Luna

2013-01-01

Various models using radiometric approach have been proposed to solve the problem of estimating the distance between a camera and an infrared emitter diode (IRED). They depend directly on the radiant intensity of the emitter, set by the IRED bias current. As is known, this current presents a drift with temperature, which will be transferred to the distance estimation method. This paper proposes an alternative approach to remove temperature drift in the distance estimation method by eliminating the dependence on radiant intensity. The main aim was to use the relative accumulated energy together with other defined models, such as the zeroth-frequency component of the FFT of the IRED image and the standard deviation of pixel gray level intensities in the region of interest containing the IRED image. By using the abovementioned models, an expression free of IRED radiant intensity was obtained. Furthermore, the final model permitted simultaneous estimation of the distance between the IRED and the camera and the IRED orientation angle. The alternative presented in this paper gave a 3% maximum relative error over a range of distances up to 3 m. PMID:23727954

TU-H-CAMPUS-IeP3-01: Simultaneous PET Restoration and PET/CT Co-Segmentation Using a Variational Method

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

Li, L; Tan, S; Lu, W

Purpose: PET images are usually blurred due to the finite spatial resolution, while CT images suffer from low contrast. Segment a tumor from either a single PET or CT image is thus challenging. To make full use of the complementary information between PET and CT, we propose a novel variational method for simultaneous PET image restoration and PET/CT images co-segmentation. Methods: The proposed model was constructed based on the Γ-convergence approximation of Mumford-Shah (MS) segmentation model for PET/CT co-segmentation. Moreover, a PET de-blur process was integrated into the MS model to improve the segmentation accuracy. An interaction edge constraint termmore » over the two modalities were specially designed to share the complementary information. The energy functional was iteratively optimized using an alternate minimization (AM) algorithm. The performance of the proposed method was validated on ten lung cancer cases and five esophageal cancer cases. The ground truth were manually delineated by an experienced radiation oncologist using the complementary visual features of PET and CT. The segmentation accuracy was evaluated by Dice similarity index (DSI) and volume error (VE). Results: The proposed method achieved an expected restoration result for PET image and satisfactory segmentation results for both PET and CT images. For lung cancer dataset, the average DSI (0.72) increased by 0.17 and 0.40 than single PET and CT segmentation. For esophageal cancer dataset, the average DSI (0.85) increased by 0.07 and 0.43 than single PET and CT segmentation. Conclusion: The proposed method took full advantage of the complementary information from PET and CT images. This work was supported in part by the National Cancer Institute Grants R01CA172638. Shan Tan and Laquan Li were supported in part by the National Natural Science Foundation of China, under Grant Nos. 60971112 and 61375018.« less

Automated detection and labeling of high-density EEG electrodes from structural MR images.

PubMed

Marino, Marco; Liu, Quanying; Brem, Silvia; Wenderoth, Nicole; Mantini, Dante

2016-10-01

Accurate knowledge about the positions of electrodes in electroencephalography (EEG) is very important for precise source localizations. Direct detection of electrodes from magnetic resonance (MR) images is particularly interesting, as it is possible to avoid errors of co-registration between electrode and head coordinate systems. In this study, we propose an automated MR-based method for electrode detection and labeling, particularly tailored to high-density montages. Anatomical MR images were processed to create an electrode-enhanced image in individual space. Image processing included intensity non-uniformity correction, background noise and goggles artifact removal. Next, we defined a search volume around the head where electrode positions were detected. Electrodes were identified as local maxima in the search volume and registered to the Montreal Neurological Institute standard space using an affine transformation. This allowed the matching of the detected points with the specific EEG montage template, as well as their labeling. Matching and labeling were performed by the coherent point drift method. Our method was assessed on 8 MR images collected in subjects wearing a 256-channel EEG net, using the displacement with respect to manually selected electrodes as performance metric. Average displacement achieved by our method was significantly lower compared to alternative techniques, such as the photogrammetry technique. The maximum displacement was for more than 99% of the electrodes lower than 1 cm, which is typically considered an acceptable upper limit for errors in electrode positioning. Our method showed robustness and reliability, even in suboptimal conditions, such as in the case of net rotation, imprecisely gathered wires, electrode detachment from the head, and MR image ghosting. We showed that our method provides objective, repeatable and precise estimates of EEG electrode coordinates. We hope our work will contribute to a more widespread use of high-density EEG as a brain-imaging tool.

Automated detection and labeling of high-density EEG electrodes from structural MR images

NASA Astrophysics Data System (ADS)

Marino, Marco; Liu, Quanying; Brem, Silvia; Wenderoth, Nicole; Mantini, Dante

2016-10-01

Objective. Accurate knowledge about the positions of electrodes in electroencephalography (EEG) is very important for precise source localizations. Direct detection of electrodes from magnetic resonance (MR) images is particularly interesting, as it is possible to avoid errors of co-registration between electrode and head coordinate systems. In this study, we propose an automated MR-based method for electrode detection and labeling, particularly tailored to high-density montages. Approach. Anatomical MR images were processed to create an electrode-enhanced image in individual space. Image processing included intensity non-uniformity correction, background noise and goggles artifact removal. Next, we defined a search volume around the head where electrode positions were detected. Electrodes were identified as local maxima in the search volume and registered to the Montreal Neurological Institute standard space using an affine transformation. This allowed the matching of the detected points with the specific EEG montage template, as well as their labeling. Matching and labeling were performed by the coherent point drift method. Our method was assessed on 8 MR images collected in subjects wearing a 256-channel EEG net, using the displacement with respect to manually selected electrodes as performance metric. Main results. Average displacement achieved by our method was significantly lower compared to alternative techniques, such as the photogrammetry technique. The maximum displacement was for more than 99% of the electrodes lower than 1 cm, which is typically considered an acceptable upper limit for errors in electrode positioning. Our method showed robustness and reliability, even in suboptimal conditions, such as in the case of net rotation, imprecisely gathered wires, electrode detachment from the head, and MR image ghosting. Significance. We showed that our method provides objective, repeatable and precise estimates of EEG electrode coordinates. We hope our work will contribute to a more widespread use of high-density EEG as a brain-imaging tool.

Breast Volume Measurement by Recycling the Data Obtained From 2 Routine Modalities, Mammography and Magnetic Resonance Imaging.

PubMed

Itsukage, Shizu; Sowa, Yoshihiro; Goto, Mariko; Taguchi, Tetsuya; Numajiri, Toshiaki

2017-01-01

Objective: Preoperative prediction of breast volume is important in the planning of breast reconstructive surgery. In this study, we prospectively estimated the accuracy of measurement of breast volume using data from 2 routine modalities, mammography and magnetic resonance imaging, by comparison with volumes of mastectomy specimens. Methods: The subjects were 22 patients (24 breasts) who were scheduled to undergo total mastectomy for breast cancer. Preoperatively, magnetic resonance imaging volume measurement was performed using a medical imaging system and the mammographic volume was calculated using a previously proposed formula. Volumes of mastectomy specimens were measured intraoperatively using a method based on Archimedes' principle and Newton's third law. Results: The average breast volumes measured on magnetic resonance imaging and mammography were 318.47 ± 199.4 mL and 325.26 ± 217.36 mL, respectively. The correlation coefficients with mastectomy specimen volumes were 0.982 for magnetic resonance imaging and 0.911 for mammography. Conclusions: Breast volume measurement using magnetic resonance imaging was highly accurate but requires data analysis software. In contrast, breast volume measurement with mammography requires only a simple formula and is sufficiently accurate, although the accuracy was lower than that obtained with magnetic resonance imaging. These results indicate that mammography could be an alternative modality for breast volume measurement as a substitute for magnetic resonance imaging.

Breast Volume Measurement by Recycling the Data Obtained From 2 Routine Modalities, Mammography and Magnetic Resonance Imaging

PubMed Central

Itsukage, Shizu; Goto, Mariko; Taguchi, Tetsuya; Numajiri, Toshiaki

2017-01-01

Objective: Preoperative prediction of breast volume is important in the planning of breast reconstructive surgery. In this study, we prospectively estimated the accuracy of measurement of breast volume using data from 2 routine modalities, mammography and magnetic resonance imaging, by comparison with volumes of mastectomy specimens. Methods: The subjects were 22 patients (24 breasts) who were scheduled to undergo total mastectomy for breast cancer. Preoperatively, magnetic resonance imaging volume measurement was performed using a medical imaging system and the mammographic volume was calculated using a previously proposed formula. Volumes of mastectomy specimens were measured intraoperatively using a method based on Archimedes’ principle and Newton's third law. Results: The average breast volumes measured on magnetic resonance imaging and mammography were 318.47 ± 199.4 mL and 325.26 ± 217.36 mL, respectively. The correlation coefficients with mastectomy specimen volumes were 0.982 for magnetic resonance imaging and 0.911 for mammography. Conclusions: Breast volume measurement using magnetic resonance imaging was highly accurate but requires data analysis software. In contrast, breast volume measurement with mammography requires only a simple formula and is sufficiently accurate, although the accuracy was lower than that obtained with magnetic resonance imaging. These results indicate that mammography could be an alternative modality for breast volume measurement as a substitute for magnetic resonance imaging. PMID:29308107

Total variation-based method for radar coincidence imaging with model mismatch for extended target

NASA Astrophysics Data System (ADS)

Cao, Kaicheng; Zhou, Xiaoli; Cheng, Yongqiang; Fan, Bo; Qin, Yuliang

2017-11-01

Originating from traditional optical coincidence imaging, radar coincidence imaging (RCI) is a staring/forward-looking imaging technique. In RCI, the reference matrix must be computed precisely to reconstruct the image as preferred; unfortunately, such precision is almost impossible due to the existence of model mismatch in practical applications. Although some conventional sparse recovery algorithms are proposed to solve the model-mismatch problem, they are inapplicable to nonsparse targets. We therefore sought to derive the signal model of RCI with model mismatch by replacing the sparsity constraint item with total variation (TV) regularization in the sparse total least squares optimization problem; in this manner, we obtain the objective function of RCI with model mismatch for an extended target. A more robust and efficient algorithm called TV-TLS is proposed, in which the objective function is divided into two parts and the perturbation matrix and scattering coefficients are updated alternately. Moreover, due to the ability of TV regularization to recover sparse signal or image with sparse gradient, TV-TLS method is also applicable to sparse recovering. Results of numerical experiments demonstrate that, for uniform extended targets, sparse targets, and real extended targets, the algorithm can achieve preferred imaging performance both in suppressing noise and in adapting to model mismatch.

Evaluation of image deblurring methods via a classification metric

NASA Astrophysics Data System (ADS)

Perrone, Daniele; Humphreys, David; Lamb, Robert A.; Favaro, Paolo

2012-09-01

The performance of single image deblurring algorithms is typically evaluated via a certain discrepancy measure between the reconstructed image and the ideal sharp image. The choice of metric, however, has been a source of debate and has also led to alternative metrics based on human visual perception. While fixed metrics may fail to capture some small but visible artifacts, perception-based metrics may favor reconstructions with artifacts that are visually pleasant. To overcome these limitations, we propose to assess the quality of reconstructed images via a task-driven metric. In this paper we consider object classification as the task and therefore use the rate of classification as the metric to measure deblurring performance. In our evaluation we use data with different types of blur in two cases: Optical Character Recognition (OCR), where the goal is to recognise characters in a black and white image, and object classification with no restrictions on pose, illumination and orientation. Finally, we show how off-the-shelf classification algorithms benefit from working with deblurred images.

Fourier-interpolation superresolution optical fluctuation imaging (fSOFi) (Conference Presentation)

NASA Astrophysics Data System (ADS)

Enderlein, Joerg; Stein, Simon C.; Huss, Anja; Hähnel, Dirk; Gregor, Ingo

2016-02-01

Stochastic Optical Fluctuation Imaging (SOFI) is a superresolution fluorescence microscopy technique which allows to enhance the spatial resolution of an image by evaluating the temporal fluctuations of blinking fluorescent emitters. SOFI is not based on the identification and localization of single molecules such as in the widely used Photoactivation Localization Microsopy (PALM) or Stochastic Optical Reconstruction Microscopy (STORM), but computes a superresolved image via temporal cumulants from a recorded movie. A technical challenge hereby is that, when directly applying the SOFI algorithm to a movie of raw images, the pixel size of the final SOFI image is the same as that of the original images, which becomes problematic when the final SOFI resolution is much smaller than this value. In the past, sophisticated cross-correlation schemes have been used for tackling this problem. Here, we present an alternative, exact, straightforward, and simple solution using an interpolation scheme based on Fourier transforms. We exemplify the method on simulated and experimental data.

Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface

PubMed Central

Miyawaki, Shinjiro; Tawhai, Merryn H.; Hoffman, Eric A.; Wenzel, Sally E.; Lin, Ching-Long

2016-01-01

We propose a method to construct three-dimensional airway geometric models based on airway skeletons, or centerlines (CLs). Given a CT-segmented airway skeleton and surface, the proposed CL-based method automatically constructs subject-specific models that contain anatomical information regarding branches, include bifurcations and trifurcations, and extend from the trachea to terminal bronchioles. The resulting model can be anatomically realistic with the assistance of an image-based surface; alternatively a model with an idealized skeleton and/or branch diameters is also possible. This method systematically identifies and classifies trifurcations to successfully construct the models, which also provides the number and type of trifurcations for the analysis of the airways from an anatomical point of view. We applied this method to 16 normal and 16 severe asthmatic subjects using their computed tomography images. The average distance between the surface of the model and the image-based surface was 11% of the average voxel size of the image. The four most frequent locations of trifurcations were the left upper division bronchus, left lower lobar bronchus, right upper lobar bronchus, and right intermediate bronchus. The proposed method automatically constructed accurate subject-specific three-dimensional airway geometric models that contain anatomical information regarding branches using airway skeleton, diameters, and image-based surface geometry. The proposed method can construct (i) geometry automatically for population-based studies, (ii) trifurcations to retain the original airway topology, (iii) geometry that can be used for automatic generation of computational fluid dynamics meshes, and (iv) geometry based only on a skeleton and diameters for idealized branches. PMID:27704229

Optical cryptography topology based on a three-dimensional particle-like distribution and diffractive imaging.

PubMed

Chen, Wen; Chen, Xudong

2011-05-09

In recent years, coherent diffractive imaging has been considered as a promising alternative for information retrieval instead of conventional interference methods. Coherent diffractive imaging using the X-ray light source has opened up a new research perspective for the measurement of non-crystalline and biological specimens, and can achieve unprecedentedly high resolutions. In this paper, we show how a three-dimensional (3D) particle-like distribution and coherent diffractive imaging can be applied for a study of optical cryptography. An optical multiple-random-phase-mask encoding approach is used, and the plaintext is considered as a series of particles distributed in a 3D space. A topology concept is also introduced into the proposed optical cryptosystem. During image decryption, a retrieval algorithm is developed to extract the plaintext from the ciphertexts. In addition, security and advantages of the proposed optical cryptography topology are also analyzed. © 2011 Optical Society of America

Interstitial ablation and imaging of soft tissue using miniaturized ultrasound arrays

NASA Astrophysics Data System (ADS)

Makin, Inder R. S.; Gallagher, Laura A.; Mast, T. Douglas; Runk, Megan M.; Faidi, Waseem; Barthe, Peter G.; Slayton, Michael H.

2004-05-01

A potential alternative to extracorporeal, noninvasive HIFU therapy is minimally invasive, interstitial ultrasound ablation that can be performed laparoscopically or percutaneously. Research in this area at Guided Therapy Systems and Ethicon Endo-Surgery has included development of miniaturized (~3 mm diameter) linear ultrasound arrays capable of high power for bulk tissue ablation as well as broad bandwidth for imaging. An integrated control system allows therapy planning and automated treatment guided by real-time interstitial B-scan imaging. Image quality, challenging because of limited probe dimensions and channel count, is aided by signal processing techniques that improve image definition and contrast. Simulations of ultrasonic heat deposition, bio-heat transfer, and tissue modification provide understanding and guidance for development of treatment strategies. Results from in vitro and in vivo ablation experiments, together with corresponding simulations, will be described. Using methods of rotational scanning, this approach is shown to be capable of clinically relevant ablation rates and volumes.

Sprectroscopic and time-resolved optical methods and apparatus for imaging objects in turbed media

NASA Technical Reports Server (NTRS)

Alfano, Robert R. (Inventor); Zevallos, Manuel E. (Inventor); Gayen, Swapan Kumar (Inventor)

2003-01-01

Method and apparatus for imaging objects in turbid media. In one embodiment, the method comprises illuminating at least a portion of the turbid medium with substantially monochromatic light of at least two wavelengths in the 600-1500 nm spectral range. A first of the at least two wavelengths is equal to a resonance wavelength for an optical property of an object in the illuminated portion of the turbid medium but is not equal to a resonance wavelength for the turbid medium. A second of the at least two wavelengths is not equal to a resonance wavelength for either the object or the turbid medium. Light emergent from the turbid medium following each of the foregoing illuminations comprises a ballistic component, a snake component and a diffuse component. A direct shadowgram image may be obtained by preferentially passing from the emergent light, following each illumination. the ballistic and snake components thereof and detecting the preferentially passed light. Alternatively, an inverse reconstruction image may be obtained by determining, following each illumination, the intensity of the diffuse component at a plurality of points in time and then using these pluralities of intensity determinations and a mathematical inversion algorithm to form an image of the object in the turbid medium. An image of the object with higher contrast and better quality may be obtained by using the ratio or difference of the images recorded with resonant light and non-resonant light.

SPECT reconstruction using DCT-induced tight framelet regularization

NASA Astrophysics Data System (ADS)

Zhang, Jiahan; Li, Si; Xu, Yuesheng; Schmidtlein, C. R.; Lipson, Edward D.; Feiglin, David H.; Krol, Andrzej

2015-03-01

Wavelet transforms have been successfully applied in many fields of image processing. Yet, to our knowledge, they have never been directly incorporated to the objective function in Emission Computed Tomography (ECT) image reconstruction. Our aim has been to investigate if the ℓ1-norm of non-decimated discrete cosine transform (DCT) coefficients of the estimated radiotracer distribution could be effectively used as the regularization term for the penalized-likelihood (PL) reconstruction, where a regularizer is used to enforce the image smoothness in the reconstruction. In this study, the ℓ1-norm of 2D DCT wavelet decomposition was used as a regularization term. The Preconditioned Alternating Projection Algorithm (PAPA), which we proposed in earlier work to solve penalized likelihood (PL) reconstruction with non-differentiable regularizers, was used to solve this optimization problem. The DCT wavelet decompositions were performed on the transaxial reconstructed images. We reconstructed Monte Carlo simulated SPECT data obtained for a numerical phantom with Gaussian blobs as hot lesions and with a warm random lumpy background. Reconstructed images using the proposed method exhibited better noise suppression and improved lesion conspicuity, compared with images reconstructed using expectation maximization (EM) algorithm with Gaussian post filter (GPF). Also, the mean square error (MSE) was smaller, compared with EM-GPF. A critical and challenging aspect of this method was selection of optimal parameters. In summary, our numerical experiments demonstrated that the ℓ1-norm of discrete cosine transform (DCT) wavelet frame transform DCT regularizer shows promise for SPECT image reconstruction using PAPA method.

Noniterative approach to the missing data problem in coherent diffraction imaging by phase retrieval.

PubMed

Nakajima, Nobuharu

2010-07-20

When a very intense beam is used for illuminating an object in coherent x-ray diffraction imaging, the intensities at the center of the diffraction pattern for the object are cut off by a beam stop that is utilized to block the intense beam. Until now, only iterative phase-retrieval methods have been applied to object reconstruction from a single diffraction pattern with a deficiency of central data due to a beam stop. As an alternative method, I present a noniterative solution in which an interpolation method based on the sampling theorem for the missing data is used for object reconstruction with our previously proposed phase-retrieval method using an aperture-array filter. Computer simulations demonstrate the reconstruction of a complex-amplitude object from a single diffraction pattern with a missing data area, which is generally difficult to treat with the iterative methods because a nonnegativity constraint cannot be used for such an object.

Near Infrared Imaging as a Diagnostic Tool for Detecting Enamel Demineralization: An in vivo Study

NASA Astrophysics Data System (ADS)

Lucas, Seth Adam

Background and Objectives: For decades there has been an effort to develop alternative optical methods of imaging dental decay utilizing non-ionizing radiation methods. The purpose of this in-vivo study was to demonstrate whether NIR can be used as a diagnostic tool to evaluate dental caries and to compare the sensitivity and specificity of this method with that of conventional methods, including bitewing x-rays and visual inspection. Materials and Methods: 31 test subjects (n=31) from the UCSF orthodontic clinic undergoing orthodontic treatment with planned premolar extractions were recruited. Calibrated examiners performed caries detection examinations using conventional methods: bitewing radiographs and visual inspection. These findings were compared with the results from NIR examinations: transillumination and reflectance. To confirm the results found in the two different detection methods, a gold standard was used. After teeth were extracted, polarized light microscopy and transverse microradiography were performed. Results: A total of 87 premolars were used in the study. NIR identified the occlusal lesions with a sensitivity of 71% and a specificity of 77%, whereas, the visual examination had a sensitivity of only 40% and a specifity of 39%. For interproximal lesions halfway to DEJ, specificity remained constant, but sensitivity improved to 100% for NIR and 75% for x-rays. Conclusions: The results of this preliminary study demonstrate that NIR is just as effective at detecting enamel interproximal lesions as standard dental x-rays. NIR was more effective at detecting occlusal lesions than visual examination alone. NIR shows promise as an alternative diagnostic tool to the conventional methods of x-rays and visual examination and provides a non-ionizing radiation technique.

MRI for peripheral artery disease: Introductory physics for vascular physicians.

PubMed

Roy, Trisha L; Forbes, Thomas L; Dueck, Andrew D; Wright, Graham A

2018-04-01

Magnetic resonance imaging (MRI) has advanced significantly in the past decade and provides a safe and non-invasive method of evaluating peripheral artery disease (PAD), with and without using exogenous contrast agents. MRI offers a promising alternative for imaging patients but the complexity of MRI can make it less accessible for physicians to understand or use. This article provides a brief introduction to the technical principles of MRI for physicians who manage PAD patients. We discuss the basic principles of how MRI works and tailor the discussion to how MRI can evaluate anatomic characteristics of peripheral arterial lesions.

Potency backprojection

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Efficient l1 -norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method.

PubMed

Kim, Eunwoo; Lee, Minsik; Choi, Chong-Ho; Kwak, Nojun; Oh, Songhwai

2015-02-01

Low-rank matrix approximation plays an important role in the area of computer vision and image processing. Most of the conventional low-rank matrix approximation methods are based on the l2 -norm (Frobenius norm) with principal component analysis (PCA) being the most popular among them. However, this can give a poor approximation for data contaminated by outliers (including missing data), because the l2 -norm exaggerates the negative effect of outliers. Recently, to overcome this problem, various methods based on the l1 -norm, such as robust PCA methods, have been proposed for low-rank matrix approximation. Despite the robustness of the methods, they require heavy computational effort and substantial memory for high-dimensional data, which is impractical for real-world problems. In this paper, we propose two efficient low-rank factorization methods based on the l1 -norm that find proper projection and coefficient matrices using the alternating rectified gradient method. The proposed methods are applied to a number of low-rank matrix approximation problems to demonstrate their efficiency and robustness. The experimental results show that our proposals are efficient in both execution time and reconstruction performance unlike other state-of-the-art methods.

Comparative study of pulsed-continuous arterial spin labeling and dynamic susceptibility contrast imaging by histogram analysis in evaluation of glial tumors.

PubMed

Arisawa, Atsuko; Watanabe, Yoshiyuki; Tanaka, Hisashi; Takahashi, Hiroto; Matsuo, Chisato; Fujiwara, Takuya; Fujiwara, Masahiro; Fujimoto, Yasunori; Tomiyama, Noriyuki

2018-06-01

Arterial spin labeling (ASL) is a non-invasive perfusion technique that may be an alternative to dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) for assessment of brain tumors. To our knowledge, there have been no reports on histogram analysis of ASL. The purpose of this study was to determine whether ASL is comparable with DSC-MRI in terms of differentiating high-grade and low-grade gliomas by evaluating the histogram analysis of cerebral blood flow (CBF) in the entire tumor. Thirty-four patients with pathologically proven glioma underwent ASL and DSC-MRI. High-signal areas on contrast-enhanced T 1 -weighted images or high-intensity areas on fluid-attenuated inversion recovery images were designated as the volumes of interest (VOIs). ASL-CBF, DSC-CBF, and DSC-cerebral blood volume maps were constructed and co-registered to the VOI. Perfusion histogram analyses of the whole VOI and statistical analyses were performed to compare the ASL and DSC images. There was no significant difference in the mean values for any of the histogram metrics in both of the low-grade gliomas (n = 15) and the high-grade gliomas (n = 19). Strong correlations were seen in the 75th percentile, mean, median, and standard deviation values between the ASL and DSC images. The area under the curve values tended to be greater for the DSC images than for the ASL images. DSC-MRI is superior to ASL for distinguishing high-grade from low-grade glioma. ASL could be an alternative evaluation method when DSC-MRI cannot be used, e.g., in patients with renal failure, those in whom repeated examination is required, and in children.

Micro-optical artificial compound eyes.

PubMed

Duparré, J W; Wippermann, F C

2006-03-01

Natural compound eyes combine small eye volumes with a large field of view at the cost of comparatively low spatial resolution. For small invertebrates such as flies or moths, compound eyes are the perfectly adapted solution to obtaining sufficient visual information about their environment without overloading their brains with the necessary image processing. However, to date little effort has been made to adopt this principle in optics. Classical imaging always had its archetype in natural single aperture eyes which, for example, human vision is based on. But a high-resolution image is not always required. Often the focus is on very compact, robust and cheap vision systems. The main question is consequently: what is the better approach for extremely miniaturized imaging systems-just scaling of classical lens designs or being inspired by alternative imaging principles evolved by nature in the case of small insects? In this paper, it is shown that such optical systems can be achieved using state-of-the-art micro-optics technology. This enables the generation of highly precise and uniform microlens arrays and their accurate alignment to the subsequent optics-, spacing- and optoelectronics structures. The results are thin, simple and monolithic imaging devices with a high accuracy of photolithography. Two different artificial compound eye concepts for compact vision systems have been investigated in detail: the artificial apposition compound eye and the cluster eye. Novel optical design methods and characterization tools were developed to allow the layout and experimental testing of the planar micro-optical imaging systems, which were fabricated for the first time by micro-optics technology. The artificial apposition compound eye can be considered as a simple imaging optical sensor while the cluster eye is capable of becoming a valid alternative to classical bulk objectives but is much more complex than the first system.

Multiattribute selection of acute stroke imaging software platform for Extending the Time for Thrombolysis in Emergency Neurological Deficits (EXTEND) clinical trial.

PubMed

Churilov, Leonid; Liu, Daniel; Ma, Henry; Christensen, Soren; Nagakane, Yoshinari; Campbell, Bruce; Parsons, Mark W; Levi, Christopher R; Davis, Stephen M; Donnan, Geoffrey A

2013-04-01

The appropriateness of a software platform for rapid MRI assessment of the amount of salvageable brain tissue after stroke is critical for both the validity of the Extending the Time for Thrombolysis in Emergency Neurological Deficits (EXTEND) Clinical Trial of stroke thrombolysis beyond 4.5 hours and for stroke patient care outcomes. The objective of this research is to develop and implement a methodology for selecting the acute stroke imaging software platform most appropriate for the setting of a multi-centre clinical trial. A multi-disciplinary decision making panel formulated the set of preferentially independent evaluation attributes. Alternative Multi-Attribute Value Measurement methods were used to identify the best imaging software platform followed by sensitivity analysis to ensure the validity and robustness of the proposed solution. Four alternative imaging software platforms were identified. RApid processing of PerfusIon and Diffusion (RAPID) software was selected as the most appropriate for the needs of the EXTEND trial. A theoretically grounded generic multi-attribute selection methodology for imaging software was developed and implemented. The developed methodology assured both a high quality decision outcome and a rational and transparent decision process. This development contributes to stroke literature in the area of comprehensive evaluation of MRI clinical software. At the time of evaluation, RAPID software presented the most appropriate imaging software platform for use in the EXTEND clinical trial. The proposed multi-attribute imaging software evaluation methodology is based on sound theoretical foundations of multiple criteria decision analysis and can be successfully used for choosing the most appropriate imaging software while ensuring both robust decision process and outcomes. © 2012 The Authors. International Journal of Stroke © 2012 World Stroke Organization.

An improved robust blind motion de-blurring algorithm for remote sensing images

NASA Astrophysics Data System (ADS)

He, Yulong; Liu, Jin; Liang, Yonghui

2016-10-01

Shift-invariant motion blur can be modeled as a convolution of the true latent image and the blur kernel with additive noise. Blind motion de-blurring estimates a sharp image from a motion blurred image without the knowledge of the blur kernel. This paper proposes an improved edge-specific motion de-blurring algorithm which proved to be fit for processing remote sensing images. We find that an inaccurate blur kernel is the main factor to the low-quality restored images. To improve image quality, we do the following contributions. For the robust kernel estimation, first, we adapt the multi-scale scheme to make sure that the edge map could be constructed accurately; second, an effective salient edge selection method based on RTV (Relative Total Variation) is used to extract salient structure from texture; third, an alternative iterative method is introduced to perform kernel optimization, in this step, we adopt l1 and l0 norm as the priors to remove noise and ensure the continuity of blur kernel. For the final latent image reconstruction, an improved adaptive deconvolution algorithm based on TV-l2 model is used to recover the latent image; we control the regularization weight adaptively in different region according to the image local characteristics in order to preserve tiny details and eliminate noise and ringing artifacts. Some synthetic remote sensing images are used to test the proposed algorithm, and results demonstrate that the proposed algorithm obtains accurate blur kernel and achieves better de-blurring results.

Multi-Reader ROC studies with Split-Plot Designs: A Comparison of Statistical Methods

PubMed Central

Obuchowski, Nancy A.; Gallas, Brandon D.; Hillis, Stephen L.

2012-01-01

Rationale and Objectives Multi-reader imaging trials often use a factorial design, where study patients undergo testing with all imaging modalities and readers interpret the results of all tests for all patients. A drawback of the design is the large number of interpretations required of each reader. Split-plot designs have been proposed as an alternative, in which one or a subset of readers interprets all images of a sample of patients, while other readers interpret the images of other samples of patients. In this paper we compare three methods of analysis for the split-plot design. Materials and Methods Three statistical methods are presented: Obuchowski-Rockette method modified for the split-plot design, a newly proposed marginal-mean ANOVA approach, and an extension of the three-sample U-statistic method. A simulation study using the Roe-Metz model was performed to compare the type I error rate, power and confidence interval coverage of the three test statistics. Results The type I error rates for all three methods are close to the nominal level but tend to be slightly conservative. The statistical power is nearly identical for the three methods. The coverage of 95% CIs fall close to the nominal coverage for small and large sample sizes. Conclusions The split-plot MRMC study design can be statistically efficient compared with the factorial design, reducing the number of interpretations required per reader. Three methods of analysis, shown to have nominal type I error rate, similar power, and nominal CI coverage, are available for this study design. PMID:23122570

Statistical analysis of particle trajectories in living cells

NASA Astrophysics Data System (ADS)

Briane, Vincent; Kervrann, Charles; Vimond, Myriam

2018-06-01

Recent advances in molecular biology and fluorescence microscopy imaging have made possible the inference of the dynamics of molecules in living cells. Such inference allows us to understand and determine the organization and function of the cell. The trajectories of particles (e.g., biomolecules) in living cells, computed with the help of object tracking methods, can be modeled with diffusion processes. Three types of diffusion are considered: (i) free diffusion, (ii) subdiffusion, and (iii) superdiffusion. The mean-square displacement (MSD) is generally used to discriminate the three types of particle dynamics. We propose here a nonparametric three-decision test as an alternative to the MSD method. The rejection of the null hypothesis, i.e., free diffusion, is accompanied by claims of the direction of the alternative (subdiffusion or superdiffusion). We study the asymptotic behavior of the test statistic under the null hypothesis and under parametric alternatives which are currently considered in the biophysics literature. In addition, we adapt the multiple-testing procedure of Benjamini and Hochberg to fit with the three-decision-test setting, in order to apply the test procedure to a collection of independent trajectories. The performance of our procedure is much better than the MSD method as confirmed by Monte Carlo experiments. The method is demonstrated on real data sets corresponding to protein dynamics observed in fluorescence microscopy.

Microwave and Millimeter Wave Imaging Using Synthetic Aperture Focusing and Holographical Techniques

NASA Technical Reports Server (NTRS)

Case, Joseph Tobias

2005-01-01

Microwave and millimeter wave nondestructive testing and evaluation (NDT&E) methods have shown great potential for determining material composition in composite structures, determining material thickness or debond thickness between two layers, and determining the location and size of flaws, defects, and anomalies. The same testing methods have also shown great potential to produce relatively high-resolution images of voids inside Spray On Foam Insulation (SOFI) test panels using real focused methods employing lens antennas. An alternative to real focusing methods are synthetic focusing methods. The essence of synthetic focusing is to match the phase of the scattered signal to measured points spaced regularly on a plane. Many variations of synthetic focusing methods have already been developed for radars, ultrasonic testing applications, and microwave concealed weapon detection. Two synthetic focusing methods were investigated; namely, a) frequency-domain synthetic aperture focusing technique (FDSAFT), and b) wide-band microwave holography. These methods were applied towards materials whose defects were of low dielectric contrast like air void in SOFI. It is important to note that this investigation used relatively low frequencies from 8.2 GHz to 26.5 GHz that are not conducive for direct imaging of the SOFI. The ultimate goal of this work has been to demonstrate the capability of these methods before they are applied to much higher frequencies such as the millimeter wave frequency spectrum (e.g., 30-300 GHz).

Object recognition through turbulence with a modified plenoptic camera

NASA Astrophysics Data System (ADS)

Wu, Chensheng; Ko, Jonathan; Davis, Christopher

2015-03-01

Atmospheric turbulence adds accumulated distortion to images obtained by cameras and surveillance systems. When the turbulence grows stronger or when the object is further away from the observer, increasing the recording device resolution helps little to improve the quality of the image. Many sophisticated methods to correct the distorted images have been invented, such as using a known feature on or near the target object to perform a deconvolution process, or use of adaptive optics. However, most of the methods depend heavily on the object's location, and optical ray propagation through the turbulence is not directly considered. Alternatively, selecting a lucky image over many frames provides a feasible solution, but at the cost of time. In our work, we propose an innovative approach to improving image quality through turbulence by making use of a modified plenoptic camera. This type of camera adds a micro-lens array to a traditional high-resolution camera to form a semi-camera array that records duplicate copies of the object as well as "superimposed" turbulence at slightly different angles. By performing several steps of image reconstruction, turbulence effects will be suppressed to reveal more details of the object independently (without finding references near the object). Meanwhile, the redundant information obtained by the plenoptic camera raises the possibility of performing lucky image algorithmic analysis with fewer frames, which is more efficient. In our work, the details of our modified plenoptic cameras and image processing algorithms will be introduced. The proposed method can be applied to coherently illuminated object as well as incoherently illuminated objects. Our result shows that the turbulence effect can be effectively suppressed by the plenoptic camera in the hardware layer and a reconstructed "lucky image" can help the viewer identify the object even when a "lucky image" by ordinary cameras is not achievable.

Combining a wavelet transform with a channelized Hotelling observer for tumor detection in 3D PET oncology imaging

NASA Astrophysics Data System (ADS)

Lartizien, Carole; Tomei, Sandrine; Maxim, Voichita; Odet, Christophe

2007-03-01

This study evaluates new observer models for 3D whole-body Positron Emission Tomography (PET) imaging based on a wavelet sub-band decomposition and compares them with the classical constant-Q CHO model. Our final goal is to develop an original method that performs guided detection of abnormal activity foci in PET oncology imaging based on these new observer models. This computer-aided diagnostic method would highly benefit to clinicians for diagnostic purpose and to biologists for massive screening of rodents populations in molecular imaging. Method: We have previously shown good correlation of the channelized Hotelling observer (CHO) using a constant-Q model with human observer performance for 3D PET oncology imaging. We propose an alternate method based on combining a CHO observer with a wavelet sub-band decomposition of the image and we compare it to the standard CHO implementation. This method performs an undecimated transform using a biorthogonal B-spline 4/4 wavelet basis to extract the features set for input to the Hotelling observer. This work is based on simulated 3D PET images of an extended MCAT phantom with randomly located lesions. We compare three evaluation criteria: classification performance using the signal-to-noise ratio (SNR), computation efficiency and visual quality of the derived 3D maps of the decision variable λ. The SNR is estimated on a series of test images for a variable number of training images for both observers. Results: Results show that the maximum SNR is higher with the constant-Q CHO observer, especially for targets located in the liver, and that it is reached with a smaller number of training images. However, preliminary analysis indicates that the visual quality of the 3D maps of the decision variable λ is higher with the wavelet-based CHO and the computation time to derive a 3D λ-map is about 350 times shorter than for the standard CHO. This suggests that the wavelet-CHO observer is a good candidate for use in our guided detection method.

Design of Multishell Sampling Schemes with Uniform Coverage in Diffusion MRI

PubMed Central

Caruyer, Emmanuel; Lenglet, Christophe; Sapiro, Guillermo; Deriche, Rachid

2017-01-01

Purpose In diffusion MRI, a technique known as diffusion spectrum imaging reconstructs the propagator with a discrete Fourier transform, from a Cartesian sampling of the diffusion signal. Alternatively, it is possible to directly reconstruct the orientation distribution function in q-ball imaging, providing so-called high angular resolution diffusion imaging. In between these two techniques, acquisitions on several spheres in q-space offer an interesting trade-off between the angular resolution and the radial information gathered in diffusion MRI. A careful design is central in the success of multishell acquisition and reconstruction techniques. Methods The design of acquisition in multishell is still an open and active field of research, however. In this work, we provide a general method to design multishell acquisition with uniform angular coverage. This method is based on a generalization of electrostatic repulsion to multishell. Results We evaluate the impact of our method using simulations, on the angular resolution in one and two bundles of fiber configurations. Compared to more commonly used radial sampling, we show that our method improves the angular resolution, as well as fiber crossing discrimination. Discussion We propose a novel method to design sampling schemes with optimal angular coverage and show the positive impact on angular resolution in diffusion MRI. PMID:23625329

NearSense - Advances Towards a Silicon-Based Terahertz Near-Field Imaging Sensor for Ex Vivo Breast Tumour Identification

NASA Astrophysics Data System (ADS)

Mavarani, Laven; Hillger, Philipp; Bücher, Thomas; Grzyb, Janusz; Pfeiffer, Ullrich R.; Cassar, Quentin; Al-Ibadi, Amel; Zimmer, Thomas; Guillet, Jean-Paul; Mounaix, Patrick; MacGrogan, Gaëtan

2018-03-01

Breast Cancer is one of the most frequently diagnosed cancer diseases worldwide, and the most common invasive tumour for women. As with all cancers, early detection plays a major role in reducing the mortality and morbidity rate. Currently, most breast cancers are detected due to clinical symptoms, or by screening mammography. The limitations of these techniques have resulted in research of alternative methods for imaging and detecting breast cancer. Apart from this, it is essential to define precise tumour margins during breast-conserving surgeries to reduce the re-excision rate. This study presents the advances in the development of a silicon-based THz sub-wavelength imager usable in life science applications, especially for tumour margin identification.

Three-Dimensional Imaging and Quantification of Biomass and Biofilms in Porous Media

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

Dorthe Wildenschild

2012-10-10

A new method to resolve biofilms in three dimensions in porous media using high-resolution synchrotron-based x-ray computed microtomography (CMT) has been developed. Imaging biofilms in porous media without disturbing the natural spatial arrangement of the porous media and associated biofilm has been a challenging task, primarily because porous media generally precludes conventional imaging via optical microscopy; x-ray tomography offers a potential alternative. One challenge for using this method is that most conventional x-ray contrast agents are water-soluble and easily diffuse into biofilms. To overcome this problem, silver-coated microspheres were added to the fluid phase to create an x-ray contrast thatmore » does not diffuse into the biofilm mass. Using this approach, biofilm imaging in porous media was accomplished with sufficient contrast to differentiate between the biomass- and fluid-filled pore spaces. The method was validated by using a two-dimensional micro-model flow cell where both light microscopy and CMT imaging were used to im age the biofilm. The results of this work has been published in Water Resources Research (Iltis et al., 2010). Additional work needs to be done to optimize this imaging approach, specifically, we find that the quality of the images are highly dependent on the coverage of the biofilm with Ag particles, - which means that we may have issues in dead-end pore space and for very low density (fluffy) biofilms. What we can image for certain with this technique is the biofilm surface that is well-connected to flow paths and thus well-supplied with nutrients etc.« less

High-order distance-based multiview stochastic learning in image classification.

PubMed

Yu, Jun; Rui, Yong; Tang, Yuan Yan; Tao, Dacheng

2014-12-01

How do we find all images in a larger set of images which have a specific content? Or estimate the position of a specific object relative to the camera? Image classification methods, like support vector machine (supervised) and transductive support vector machine (semi-supervised), are invaluable tools for the applications of content-based image retrieval, pose estimation, and optical character recognition. However, these methods only can handle the images represented by single feature. In many cases, different features (or multiview data) can be obtained, and how to efficiently utilize them is a challenge. It is inappropriate for the traditionally concatenating schema to link features of different views into a long vector. The reason is each view has its specific statistical property and physical interpretation. In this paper, we propose a high-order distance-based multiview stochastic learning (HD-MSL) method for image classification. HD-MSL effectively combines varied features into a unified representation and integrates the labeling information based on a probabilistic framework. In comparison with the existing strategies, our approach adopts the high-order distance obtained from the hypergraph to replace pairwise distance in estimating the probability matrix of data distribution. In addition, the proposed approach can automatically learn a combination coefficient for each view, which plays an important role in utilizing the complementary information of multiview data. An alternative optimization is designed to solve the objective functions of HD-MSL and obtain different views on coefficients and classification scores simultaneously. Experiments on two real world datasets demonstrate the effectiveness of HD-MSL in image classification.

Ultrahigh-definition dynamic 3D holographic display by active control of volume speckle fields

NASA Astrophysics Data System (ADS)

Yu, Hyeonseung; Lee, Kyeoreh; Park, Jongchan; Park, Yongkeun

2017-01-01

Holographic displays generate realistic 3D images that can be viewed without the need for any visual aids. They operate by generating carefully tailored light fields that replicate how humans see an actual environment. However, the realization of high-performance, dynamic 3D holographic displays has been hindered by the capabilities of present wavefront modulator technology. In particular, spatial light modulators have a small diffraction angle range and limited pixel number limiting the viewing angle and image size of a holographic 3D display. Here, we present an alternative method to generate dynamic 3D images by controlling volume speckle fields significantly enhancing image definition. We use this approach to demonstrate a dynamic display of micrometre-sized optical foci in a volume of 8 mm × 8 mm × 20 mm.

Scanning Probe Microscopy for Identifying the Component Materials of a Nanostripe Structure

NASA Astrophysics Data System (ADS)

Mizuno, Akira; Ando, Yasuhisa

2010-08-01

The authors prepared a nanostripe structure in which two types of metal are arranged alternately, and successfully identified the component materials using scanning probe microscopy (SPM) to measure the lateral force distribution image. The nanostripe structure was prepared using a new method developed by the authors and joint development members. The lateral force distribution image was measured in both friction force microscopy (FFM) and lateral modulation friction force microscopy (LM-FFM) modes. In FFM mode, the effect of slope angle appeared in the lateral force distribution image; therefore, no difference in the type of material was observed. On the other hand, in LM-FFM mode, the effect of surface curvature was observed in the lateral force distribution image. A higher friction force on chromium than on gold was identified, enabling material identification.

Quantifying the pattern of beta/A4 amyloid protein distribution in Alzheimer's disease by image analysis.

PubMed

Bruce, C V; Clinton, J; Gentleman, S M; Roberts, G W; Royston, M C

1992-04-01

We have undertaken a study of the distribution of the beta/A4 amyloid deposited in the cerebral cortex in Alzheimer's disease. Previous studies which have examined the differential distribution of amyloid in the cortex in order to determine the laminar pattern of cortical pathology have not proved to be conclusive. We have developed an alternative method for the solution of this problem. It involves the immunostaining of sections followed by computer-enhanced image analysis. A mathematical model is then used to describe both the amount and the pattern of amyloid across the cortex. This method is both accurate and reliable and also removes many of the problems concerning inter and intra-rater variability in measurement. This method will provide the basis for further quantitative studies on the differential distribution of amyloid in Alzheimer's disease and other cases of dementia where cerebral amyloidosis occurs.

With Geospatial in Path of Smart City

NASA Astrophysics Data System (ADS)

Homainejad, A. S.

2015-04-01

With growth of urbanisation, there is a requirement for using the leverage of smart city in city management. The core of smart city is Information and Communication Technologies (ICT), and one of its elements is smart transport which includes sustainable transport and Intelligent Transport Systems (ITS). Cities and especially megacities are facing urgent transport challenge in traffic management. Geospatial can provide reliable tools for monitoring and coordinating traffic. In this paper a method for monitoring and managing the ongoing traffic in roads using aerial images and CCTV will be addressed. In this method, the road network was initially extracted and geo-referenced and captured in a 3D model. The aim is to detect and geo-referenced any vehicles on the road from images in order to assess the density and the volume of vehicles on the roads. If a traffic jam was recognised from the images, an alternative route would be suggested for easing the traffic jam. In a separate test, a road network was replicated in the computer and a simulated traffic was implemented in order to assess the traffic management during a pick time using this method.

A method of directly extracting multiwave angle-domain common-image gathers

NASA Astrophysics Data System (ADS)

Han, Jianguang; Wang, Yun

2017-10-01

Angle-domain common-image gathers (ADCIGs) can provide an effective way for migration velocity analysis and amplitude versus angle analysis in oil-gas seismic exploration. On the basis of multi-component Gaussian beam prestack depth migration (GB-PSDM), an alternative method of directly extracting multiwave ADCIGs is presented in this paper. We first introduce multi-component GB-PSDM, where a wavefield separation is proceeded to obtain the separated PP- and PS-wave seismic records before migration imaging for multiwave seismic data. Then, the principle of extracting PP- and PS-ADCIGs using GB-PSDM is presented. The propagation angle can be obtained using the real-value travel time of Gaussian beam in the course of GB-PSDM, which can be used to calculate the incidence and reflection angles. Two kinds of ADCIGs can be extracted for the PS-wave, one of which is P-wave incidence ADCIGs and the other one is S-wave reflection ADCIGs. In this paper, we use the incident angle to plot the ADCIGs for both PP- and PS-waves. Finally, tests of synthetic examples show that the method introduced here is accurate and effective.

Recognition of finger flexion motion from ultrasound image: a feasibility study.

PubMed

Shi, Jun; Guo, Jing-Yi; Hu, Shu-Xian; Zheng, Yong-Ping

2012-10-01

Muscle contraction results in structural and morphologic changes of the related muscle. Therefore, finger flexion can be monitored from measurements of these morphologic changes. We used ultrasound imaging to record muscle activities during finger flexion and extracted features to discriminate different fingers' flexions using a support vector machine (SVM). Registration of ultrasound images before and after finger flexion was performed to generate a deformation field, from which angle features and wavelet-based features were extracted. The SVM was then used to classify the motions of different fingers. The experimental results showed that the overall mean recognition accuracy was 94.05% ± 4.10%, with the highest for the thumb (97%) and the lowest for the ring finger (92%) and the mean F value was 0.94 ± 0.02, indicating high accuracy and reliability of this method. The results suggest that the proposed method has the potential to be used as an alternative method of surface electromyography in differentiating the motions of different fingers. Copyright © 2012 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Nonparametric Hierarchical Bayesian Model for Functional Brain Parcellation

PubMed Central

Lashkari, Danial; Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina

2011-01-01

We develop a method for unsupervised analysis of functional brain images that learns group-level patterns of functional response. Our algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over the sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to simultaneously learn the patterns of response that are shared across the group, and to estimate the number of these patterns supported by data. Inference based on this model enables automatic discovery and characterization of salient and consistent patterns in functional signals. We apply our method to data from a study that explores the response of the visual cortex to a collection of images. The discovered profiles of activation correspond to selectivity to a number of image categories such as faces, bodies, and scenes. More generally, our results appear superior to the results of alternative data-driven methods in capturing the category structure in the space of stimuli. PMID:21841977

Glioblastoma cells labeled by robust Raman tags for enhancing imaging contrast.

PubMed

Huang, Li-Ching; Chang, Yung-Ching; Wu, Yi-Syuan; Sun, Wei-Lun; Liu, Chan-Chuan; Sze, Chun-I; Chen, Shiuan-Yeh

2018-05-01

Complete removal of a glioblastoma multiforme (GBM), a highly malignant brain tumor, is challenging due to its infiltrative characteristics. Therefore, utilizing imaging agents such as fluorophores to increase the contrast between GBM and normal cells can help neurosurgeons to locate residual cancer cells during image guided surgery. In this work, Raman tag based labeling and imaging for GBM cells in vitro is described and evaluated. The cell membrane of a GBM adsorbs a substantial amount of functionalized Raman tags through overexpression of the epidermal growth factor receptor (EGFR) and "broadcasts" stronger pre-defined Raman signals than normal cells. The average ratio between Raman signals from a GBM cell and autofluorescence from a normal cell can be up to 15. In addition, the intensity of these images is stable under laser illuminations without suffering from the severe photo-bleaching that usually occurs in fluorescent imaging. Our results show that labeling and imaging GBM cells via robust Raman tags is a viable alternative method to distinguish them from normal cells. This Raman tag based method can be used solely or integrated into an existing fluorescence system to improve the identification of infiltrative glial tumor cells around the boundary, which will further reduce GBM recurrence. In addition, it can also be applied/extended to other types of cancer to improve the effectiveness of image guided surgery.

Glioblastoma cells labeled by robust Raman tags for enhancing imaging contrast

PubMed Central

Huang, Li-Ching; Chang, Yung-Ching; Wu, Yi-Syuan; Sun, Wei-Lun; Liu, Chan-Chuan; Sze, Chun-I; Chen, Shiuan-Yeh

2018-01-01

Complete removal of a glioblastoma multiforme (GBM), a highly malignant brain tumor, is challenging due to its infiltrative characteristics. Therefore, utilizing imaging agents such as fluorophores to increase the contrast between GBM and normal cells can help neurosurgeons to locate residual cancer cells during image guided surgery. In this work, Raman tag based labeling and imaging for GBM cells in vitro is described and evaluated. The cell membrane of a GBM adsorbs a substantial amount of functionalized Raman tags through overexpression of the epidermal growth factor receptor (EGFR) and “broadcasts” stronger pre-defined Raman signals than normal cells. The average ratio between Raman signals from a GBM cell and autofluorescence from a normal cell can be up to 15. In addition, the intensity of these images is stable under laser illuminations without suffering from the severe photo-bleaching that usually occurs in fluorescent imaging. Our results show that labeling and imaging GBM cells via robust Raman tags is a viable alternative method to distinguish them from normal cells. This Raman tag based method can be used solely or integrated into an existing fluorescence system to improve the identification of infiltrative glial tumor cells around the boundary, which will further reduce GBM recurrence. In addition, it can also be applied/extended to other types of cancer to improve the effectiveness of image guided surgery. PMID:29760976

Recent developments in spectroscopic imaging techniques for historical paintings - A review

NASA Astrophysics Data System (ADS)

Alfeld, M.; de Viguerie, L.

2017-10-01

This paper provides an overview over the application of scanning macro-XRF with mobile instruments for the investigation of historical paintings. The method is compared to synchrotron based macro-XRF imaging and Neutron Activation Auto-Radiography. Full-Field XRF imaging instruments, a potential future alternative to scanning macro-XRF, and confocal XRF, providing complementary depth profiles and developing into a 3D imaging technique itself, are described with the focus on investigations of historical paintings. Recent developments of X-ray radiography are presented and the investigation of cultural heritage objects other than paintings by MA-XRF is summarized. In parallel to XRF, hyperspectral imaging in the visible and range has developed into a technique with comparable capabilities, providing insight in chemical compounds, where XRF imaging identifies the distribution of elements. Due to the complementary nature of these techniques the latter is summarized. Further, progress and state of the art in data evaluation for spectroscopic imaging is discussed. In general it could be observed that technical capabilities in MA-XRF and hyperspectral imaging have reached a plateau and that with the availability of commercial instruments the focus of recent studies has shifted from the development of methods to applications of the instruments. Further, that while simple instruments are easily available with medium budgets only few groups have high-end instrumentation available, bought or in-house built.

On Applications of Pyramid Doubly Joint Bilateral Filtering in Dense Disparity Propagation

NASA Astrophysics Data System (ADS)

Abadpour, Arash

2014-06-01

Stereopsis is the basis for numerous tasks in machine vision, robotics, and 3D data acquisition and processing. In order for the subsequent algorithms to function properly, it is important that an affordable method exists that, given a pair of images taken by two cameras, can produce a representation of disparity or depth. This topic has been an active research field since the early days of work on image processing problems and rich literature is available on the topic. Joint bilateral filters have been recently proposed as a more affordable alternative to anisotropic diffusion. This class of image operators utilizes correlation in multiple modalities for purposes such as interpolation and upscaling. In this work, we develop the application of bilateral filtering for converting a large set of sparse disparity measurements into a dense disparity map. This paper develops novel methods for utilizing bilateral filters in joint, pyramid, and doubly joint settings, for purposes including missing value estimation and upscaling. We utilize images of natural and man-made scenes in order to exhibit the possibilities offered through the use of pyramid doubly joint bilateral filtering for stereopsis.

Hessian-based norm regularization for image restoration with biomedical applications.

PubMed

Lefkimmiatis, Stamatios; Bourquard, Aurélien; Unser, Michael

2012-03-01

We present nonquadratic Hessian-based regularization methods that can be effectively used for image restoration problems in a variational framework. Motivated by the great success of the total-variation (TV) functional, we extend it to also include second-order differential operators. Specifically, we derive second-order regularizers that involve matrix norms of the Hessian operator. The definition of these functionals is based on an alternative interpretation of TV that relies on mixed norms of directional derivatives. We show that the resulting regularizers retain some of the most favorable properties of TV, i.e., convexity, homogeneity, rotation, and translation invariance, while dealing effectively with the staircase effect. We further develop an efficient minimization scheme for the corresponding objective functions. The proposed algorithm is of the iteratively reweighted least-square type and results from a majorization-minimization approach. It relies on a problem-specific preconditioned conjugate gradient method, which makes the overall minimization scheme very attractive since it can be applied effectively to large images in a reasonable computational time. We validate the overall proposed regularization framework through deblurring experiments under additive Gaussian noise on standard and biomedical images.

Bayesian nonparametric dictionary learning for compressed sensing MRI.

PubMed

Huang, Yue; Paisley, John; Lin, Qin; Ding, Xinghao; Fu, Xueyang; Zhang, Xiao-Ping

2014-12-01

We develop a Bayesian nonparametric model for reconstructing magnetic resonance images (MRIs) from highly undersampled k -space data. We perform dictionary learning as part of the image reconstruction process. To this end, we use the beta process as a nonparametric dictionary learning prior for representing an image patch as a sparse combination of dictionary elements. The size of the dictionary and patch-specific sparsity pattern are inferred from the data, in addition to other dictionary learning variables. Dictionary learning is performed directly on the compressed image, and so is tailored to the MRI being considered. In addition, we investigate a total variation penalty term in combination with the dictionary learning model, and show how the denoising property of dictionary learning removes dependence on regularization parameters in the noisy setting. We derive a stochastic optimization algorithm based on Markov chain Monte Carlo for the Bayesian model, and use the alternating direction method of multipliers for efficiently performing total variation minimization. We present empirical results on several MRI, which show that the proposed regularization framework can improve reconstruction accuracy over other methods.

Potential end-to-end imaging information rate advantages of various alternative communication systems

NASA Technical Reports Server (NTRS)

Rice, R. F.

1978-01-01

Various communication systems were considered which are required to transmit both imaging and a typically error sensitive, class of data called general science/engineering (gse) over a Gaussian channel. The approach jointly treats the imaging and gse transmission problems, allowing comparisons of systems which include various channel coding and data compression alternatives. Actual system comparisons include an Advanced Imaging Communication System (AICS) which exhibits the rather significant potential advantages of sophisticated data compression coupled with powerful yet practical channel coding.

Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

PubMed

Peng, Tao; Bonamy, Ghislain M C; Glory-Afshar, Estelle; Rines, Daniel R; Chanda, Sumit K; Murphy, Robert F

2010-02-16

Many proteins or other biological macromolecules are localized to more than one subcellular structure. The fraction of a protein in different cellular compartments is often measured by colocalization with organelle-specific fluorescent markers, requiring availability of fluorescent probes for each compartment and acquisition of images for each in conjunction with the macromolecule of interest. Alternatively, tailored algorithms allow finding particular regions in images and quantifying the amount of fluorescence they contain. Unfortunately, this approach requires extensive hand-tuning of algorithms and is often cell type-dependent. Here we describe a machine-learning approach for estimating the amount of fluorescent signal in different subcellular compartments without hand tuning, requiring only the acquisition of separate training images of markers for each compartment. In testing on images of cells stained with mixtures of probes for different organelles, we achieved a 93% correlation between estimated and expected amounts of probes in each compartment. We also demonstrated that the method can be used to quantify drug-dependent protein translocations. The method enables automated and unbiased determination of the distributions of protein across cellular compartments, and will significantly improve imaging-based high-throughput assays and facilitate proteome-scale localization efforts.

Practical human abdominal fat imaging utilizing electrical impedance tomography.

PubMed

Yamaguchi, T; Maki, K; Katashima, M

2010-07-01

The fundamental cause of metabolic syndrome is thought to be abdominal obesity. Accurate diagnosis of abdominal obesity can be done by an x-ray computed tomography (CT) scan. But CT is expensive, bulky and entails the risks involved with radiation. To overcome such disadvantages, we attempted to develop a measuring device that could apply electrical impedance tomography to abdominal fat imaging. The device has 32 electrodes that can be attached to a subject's abdomen by a pneumatic mechanism. That way, electrode position data can be acquired simultaneously. An applied alternating current of 1.0 mArms was used at a frequency of 500 kHz. Sensed voltage data were carefully filtered to remove noise and processed to satisfy the reciprocal theorem. The image reconstruction software was developed concurrently, applying standard finite element methods and the Marquardt method to solve the mathematical inverse problem. The results of preliminary experiments showed that abdominal subcutaneous fat and the muscle surrounding the viscera could be imaged in humans. While our imaging of visceral fat was not of sufficient quality, it was suggested that we will be able to develop a safe and practical abdominal fat scanner through future improvements.

Hybrid Microscopy: Enabling Inexpensive High-Performance Imaging through Combined Physical and Optical Magnifications.

PubMed

Zhang, Yu Shrike; Chang, Jae-Byum; Alvarez, Mario Moisés; Trujillo-de Santiago, Grissel; Aleman, Julio; Batzaya, Byambaa; Krishnadoss, Vaishali; Ramanujam, Aishwarya Aravamudhan; Kazemzadeh-Narbat, Mehdi; Chen, Fei; Tillberg, Paul W; Dokmeci, Mehmet Remzi; Boyden, Edward S; Khademhosseini, Ali

2016-03-15

To date, much effort has been expended on making high-performance microscopes through better instrumentation. Recently, it was discovered that physical magnification of specimens was possible, through a technique called expansion microscopy (ExM), raising the question of whether physical magnification, coupled to inexpensive optics, could together match the performance of high-end optical equipment, at a tiny fraction of the price. Here we show that such "hybrid microscopy" methods--combining physical and optical magnifications--can indeed achieve high performance at low cost. By physically magnifying objects, then imaging them on cheap miniature fluorescence microscopes ("mini-microscopes"), it is possible to image at a resolution comparable to that previously attainable only with benchtop microscopes that present costs orders of magnitude higher. We believe that this unprecedented hybrid technology that combines expansion microscopy, based on physical magnification, and mini-microscopy, relying on conventional optics--a process we refer to as Expansion Mini-Microscopy (ExMM)--is a highly promising alternative method for performing cost-effective, high-resolution imaging of biological samples. With further advancement of the technology, we believe that ExMM will find widespread applications for high-resolution imaging particularly in research and healthcare scenarios in undeveloped countries or remote places.

Large Margin Multi-Modal Multi-Task Feature Extraction for Image Classification.

PubMed

Yong Luo; Yonggang Wen; Dacheng Tao; Jie Gui; Chao Xu

2016-01-01

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We, therefore, propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features, so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization, and each subproblem can be efficiently solved. Experiments on two challenging real-world image data sets demonstrate the effectiveness and superiority of the proposed method.

Efficient airport detection using region-based fully convolutional neural networks

NASA Astrophysics Data System (ADS)

Xin, Peng; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Lv, Chao

2018-04-01

This paper presents a model for airport detection using region-based fully convolutional neural networks. To achieve fast detection with high accuracy, we shared the conv layers between the region proposal procedure and the airport detection procedure and used graphics processing units (GPUs) to speed up the training and testing time. For lack of labeled data, we transferred the convolutional layers of ZF net pretrained by ImageNet to initialize the shared convolutional layers, then we retrained the model using the alternating optimization training strategy. The proposed model has been tested on an airport dataset consisting of 600 images. Experiments show that the proposed method can distinguish airports in our dataset from similar background scenes almost real-time with high accuracy, which is much better than traditional methods.

3D chemical imaging in the laboratory by hyperspectral X-ray computed tomography

PubMed Central

Egan, C. K.; Jacques, S. D. M.; Wilson, M. D.; Veale, M. C.; Seller, P.; Beale, A. M.; Pattrick, R. A. D.; Withers, P. J.; Cernik, R. J.

2015-01-01

We report the development of laboratory based hyperspectral X-ray computed tomography which allows the internal elemental chemistry of an object to be reconstructed and visualised in three dimensions. The method employs a spectroscopic X-ray imaging detector with sufficient energy resolution to distinguish individual elemental absorption edges. Elemental distributions can then be made by K-edge subtraction, or alternatively by voxel-wise spectral fitting to give relative atomic concentrations. We demonstrate its application to two material systems: studying the distribution of catalyst material on porous substrates for industrial scale chemical processing; and mapping of minerals and inclusion phases inside a mineralised ore sample. The method makes use of a standard laboratory X-ray source with measurement times similar to that required for conventional computed tomography. PMID:26514938

Application of preconditioned alternating direction method of multipliers in depth from focal stack

NASA Astrophysics Data System (ADS)

Javidnia, Hossein; Corcoran, Peter

2018-03-01

Postcapture refocusing effect in smartphone cameras is achievable using focal stacks. However, the accuracy of this effect is totally dependent on the combination of the depth layers in the stack. The accuracy of the extended depth of field effect in this application can be improved significantly by computing an accurate depth map, which has been an open issue for decades. To tackle this issue, a framework is proposed based on a preconditioned alternating direction method of multipliers for depth from the focal stack and synthetic defocus application. In addition to its ability to provide high structural accuracy, the optimization function of the proposed framework can, in fact, converge faster and better than state-of-the-art methods. The qualitative evaluation has been done on 21 sets of focal stacks and the optimization function has been compared against five other methods. Later, 10 light field image sets have been transformed into focal stacks for quantitative evaluation purposes. Preliminary results indicate that the proposed framework has a better performance in terms of structural accuracy and optimization in comparison to the current state-of-the-art methods.

Comparison of three methods of calculating strain in the mouse ulna in exogenous loading studies.

PubMed

Norman, Stephanie C; Wagner, David W; Beaupre, Gary S; Castillo, Alesha B

2015-01-02

Axial compression of mouse limbs is commonly used to induce bone formation in a controlled, non-invasive manner. Determination of peak strains caused by loading is central to interpreting results. Load-strain calibration is typically performed using uniaxial strain gauges attached to the diaphyseal, periosteal surface of a small number of sacrificed animals. Strain is measured as the limb is loaded to a range of physiological loads known to be anabolic to bone. The load-strain relationship determined by this subgroup is then extrapolated to a larger group of experimental mice. This method of strain calculation requires the challenging process of strain gauging very small bones which is subject to variability in placement of the strain gauge. We previously developed a method to estimate animal-specific periosteal strain during axial ulnar loading using an image-based computational approach that does not require strain gauges. The purpose of this study was to compare the relationship between load-induced bone formation rates and periosteal strain at ulnar midshaft using three different methods to estimate strain: (A) Nominal strain values based solely on load-strain calibration; (B) Strains calculated from load-strain calibration, but scaled for differences in mid-shaft cross-sectional geometry among animals; and (C) An alternative image-based computational method for calculating strains based on beam theory and animal-specific bone geometry. Our results show that the alternative method (C) provides comparable correlation between strain and bone formation rates in the mouse ulna relative to the strain gauge-dependent methods (A and B), while avoiding the need to use strain gauges. Published by Elsevier Ltd.

Mini-Sosie high-resolution seismic method aids hazards studies

USGS Publications Warehouse

Stephenson, W.J.; Odum, J.; Shedlock, K.M.; Pratt, T.L.; Williams, R.A.

1992-01-01

The Mini-Sosie high-resolution seismic method has been effective in imaging shallow-structure and stratigraphic features that aid in seismic-hazard and neotectonic studies. The method is not an alternative to Vibroseis acquisition for large-scale studies. However, it has two major advantages over Vibroseis as it is being used by the USGS in its seismic-hazards program. First, the sources are extremely portable and can be used in both rural and urban environments. Second, the shifting-and-summation process during acquisition improves the signal-to-noise ratio and cancels out seismic noise sources such as cars and pedestrians. -from Authors

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

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

Castillo, S; Castillo, R; Castillo, E

2014-06-15

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

Alternative method for VIIRS Moon in space view process

NASA Astrophysics Data System (ADS)

Anderson, Samuel; Chiang, Kwofu V.; Xiong, Xiaoxiong

2013-09-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a radiometric sensing instrument currently operating onboard the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft. It provides high spatial-resolution images of the emitted and reflected radiation from the Earth and its atmosphere in 22 spectral bands (16 moderate resolution bands M1-M16, 5 imaging bands I1-I5, and 1 day/night pan band DNB) spanning the visible and infrared wavelengths from 412 nm to 12 μm. Just prior to each scan it makes of the Earth, the VIIRS instrument makes a measurement of deep space to serve as a background reference. These space view (SV) measurements form a crucial input to the VIIRS calibration process and are a major determinant of its accuracy. On occasion, the orientation of the Suomi NPP spacecraft coincides with the position of the moon in such a fashion that the SV measurements include light from the moon, rendering the SV measurements unusable for calibration. This paper investigates improvements to the existing baseline SV data processing algorithm of the Sensor Data Record (SDR) processing software. The proposed method makes use of a Moon-in-SV detection algorithm that identifies moon-contaminated SV data on a scan-by-scan basis. Use of this algorithm minimizes the number of SV scans that are rejected initially, so that subsequent substitution processes are always able to find alternative substitute SV scans in the near vicinity of detected moon-contaminated scans.

Parametrically defined cerebral blood vessels as non-invasive blood input functions for brain PET studies

NASA Astrophysics Data System (ADS)

Asselin, Marie-Claude; Cunningham, Vincent J.; Amano, Shigeko; Gunn, Roger N.; Nahmias, Claude

2004-03-01

A non-invasive alternative to arterial blood sampling for the generation of a blood input function for brain positron emission tomography (PET) studies is presented. The method aims to extract the dimensions of the blood vessel directly from PET images and to simultaneously correct the radioactivity concentration for partial volume and spillover. This involves simulation of the tomographic imaging process to generate images of different blood vessel and background geometries and selecting the one that best fits, in a least-squares sense, the acquired PET image. A phantom experiment was conducted to validate the method which was then applied to eight subjects injected with 6-[18F]fluoro-L-DOPA and one subject injected with [11C]CO-labelled red blood cells. In the phantom study, the diameter of syringes filled with an 11C solution and inserted into a water-filled cylinder were estimated with an accuracy of half a pixel (1 mm). The radioactivity concentration was recovered to 100 ± 4% in the 8.7 mm diameter syringe, the one that most closely approximated the superior sagittal sinus. In the human studies, the method systematically overestimated the calibre of the superior sagittal sinus by 2-3 mm compared to measurements made in magnetic resonance venograms on the same subjects. Sources of discrepancies related to the anatomy of the blood vessel were found not to be fundamental limitations to the applicability of the method to human subjects. This method has the potential to provide accurate quantification of blood radioactivity concentration from PET images without the need for blood samples, corrections for delay and dispersion, co-registered anatomical images, or manually defined regions of interest.

Identification and characterization of neutrophil extracellular trap shapes in flow cytometry

NASA Astrophysics Data System (ADS)

Ginley, Brandon; Emmons, Tiffany; Sasankan, Prabhu; Urban, Constantin; Segal, Brahm H.; Sarder, Pinaki

2017-03-01

Neutrophil extracellular trap (NET) formation is an alternate immunologic weapon used mainly by neutrophils. Chromatin backbones fused with proteins derived from granules are shot like projectiles onto foreign invaders. It is thought that this mechanism is highly anti-microbial, aids in preventing bacterial dissemination, is used to break down structures several sizes larger than neutrophils themselves, and may have several more uses yet unknown. NETs have been implied to be involved in a wide array of systemic host immune defenses, including sepsis, autoimmune diseases, and cancer. Existing methods used to visually quantify NETotic versus non-NETotic shapes are extremely time-consuming and subject to user bias. These limitations are obstacles to developing NETs as prognostic biomarkers and therapeutic targets. We propose an automated pipeline for quantitatively detecting neutrophil and NET shapes captured using a flow cytometry-imaging system. Our method uses contrast limited adaptive histogram equalization to improve signal intensity in dimly illuminated NETs. From the contrast improved image, fixed value thresholding is applied to convert the image to binary. Feature extraction is performed on the resulting binary image, by calculating region properties of the resulting foreground structures. Classification of the resulting features is performed using Support Vector Machine. Our method classifies NETs from neutrophils without traps at 0.97/0.96 sensitivity/specificity on n = 387 images, and is 1500X faster than manual classification, per sample. Our method can be extended to rapidly analyze whole-slide immunofluorescence tissue images for NET classification, and has potential to streamline the quantification of NETs for patients with diseases associated with cancer and autoimmunity.

Highly accelerated acquisition and homogeneous image reconstruction with rotating RF coil array at 7T-A phantom based study.

PubMed

Li, Mingyan; Zuo, Zhentao; Jin, Jin; Xue, Rong; Trakic, Adnan; Weber, Ewald; Liu, Feng; Crozier, Stuart

2014-03-01

Parallel imaging (PI) is widely used for imaging acceleration by means of coil spatial sensitivities associated with phased array coils (PACs). By employing a time-division multiplexing technique, a single-channel rotating radiofrequency coil (RRFC) provides an alternative method to reduce scan time. Strategically combining these two concepts could provide enhanced acceleration and efficiency. In this work, the imaging acceleration ability and homogeneous image reconstruction strategy of 4-element rotating radiofrequency coil array (RRFCA) was numerically investigated and experimental validated at 7T with a homogeneous phantom. Each coil of RRFCA was capable of acquiring a large number of sensitivity profiles, leading to a better acceleration performance illustrated by the improved geometry-maps that have lower maximum values and more uniform distributions compared to 4- and 8-element stationary arrays. A reconstruction algorithm, rotating SENSitivity Encoding (rotating SENSE), was proposed to provide image reconstruction. Additionally, by optimally choosing the angular sampling positions and transmit profiles under the rotating scheme, phantom images could be faithfully reconstructed. The results indicate that, the proposed technique is able to provide homogeneous reconstructions with overall higher and more uniform signal-to-noise ratio (SNR) distributions at high reduction factors. It is hoped that, by employing the high imaging acceleration and homogeneous imaging reconstruction ability of RRFCA, the proposed method will facilitate human imaging for ultra high field MRI. Copyright © 2013 Elsevier Inc. All rights reserved.

An alternative method for the analysis of melanin production in Cryptococcus neoformans sensu lato and Cryptococcus gattii sensu lato.

PubMed

Brilhante, Raimunda S N; España, Jaime D A; de Alencar, Lucas P; Pereira, Vandbergue S; Castelo-Branco, Débora de S C M; Pereira-Neto, Waldemiro de A; Cordeiro, Rossana de A; Sidrim, José J C; Rocha, Marcos F G

2017-10-01

Melanin is an important virulence factor for several microorganisms, including Cryptococcus neoformans sensu lato and Cryptococcus gattii sensu lato, thus, the assessment of melanin production and its quantification may contribute to the understanding of microbial pathogenesis. The objective of this study was to standardise an alternative method for the production and indirect quantification of melanin in C. neoformans sensu lato and C. gattii sensu lato. Eight C. neoformans sensu lato and three C. gattii sensu lato, identified through URA5 methodology, Candida parapsilosis ATCC 22019 (negative control) and one Hortaea werneckii (positive control) were inoculated on minimal medium agar with or without L-DOPA, in duplicate, and incubated at 35°C, for 7 days. Pictures were taken from the third to the seventh day, under standardised conditions in a photographic chamber. Then, photographs were analysed using grayscale images. All Cryptococcus spp. strains produced melanin after growth on minimal medium agar containing L-DOPA. C. parapsilosis ATCC 22019 did not produce melanin on medium containing L-DOPA, while H. werneckii presented the strongest pigmentation. This new method allows the indirect analysis of melanin production through pixel quantification in grayscale images, enabling the study of substances that can modulate melanin production. © 2017 Blackwell Verlag GmbH.

Automated retinal vessel type classification in color fundus images

NASA Astrophysics Data System (ADS)

Yu, H.; Barriga, S.; Agurto, C.; Nemeth, S.; Bauman, W.; Soliz, P.

2013-02-01

Automated retinal vessel type classification is an essential first step toward machine-based quantitative measurement of various vessel topological parameters and identifying vessel abnormalities and alternations in cardiovascular disease risk analysis. This paper presents a new and accurate automatic artery and vein classification method developed for arteriolar-to-venular width ratio (AVR) and artery and vein tortuosity measurements in regions of interest (ROI) of 1.5 and 2.5 optic disc diameters from the disc center, respectively. This method includes illumination normalization, automatic optic disc detection and retinal vessel segmentation, feature extraction, and a partial least squares (PLS) classification. Normalized multi-color information, color variation, and multi-scale morphological features are extracted on each vessel segment. We trained the algorithm on a set of 51 color fundus images using manually marked arteries and veins. We tested the proposed method in a previously unseen test data set consisting of 42 images. We obtained an area under the ROC curve (AUC) of 93.7% in the ROI of AVR measurement and 91.5% of AUC in the ROI of tortuosity measurement. The proposed AV classification method has the potential to assist automatic cardiovascular disease early detection and risk analysis.

Testing the performance of pure spectrum resolution from Raman hyperspectral images of differently manufactured pharmaceutical tablets.

PubMed

Vajna, Balázs; Farkas, Attila; Pataki, Hajnalka; Zsigmond, Zsolt; Igricz, Tamás; Marosi, György

2012-01-27

Chemical imaging is a rapidly emerging analytical method in pharmaceutical technology. Due to the numerous chemometric solutions available, characterization of pharmaceutical samples with unknown components present has also become possible. This study compares the performance of current state-of-the-art curve resolution methods (multivariate curve resolution-alternating least squares, positive matrix factorization, simplex identification via split augmented Lagrangian and self-modelling mixture analysis) in the estimation of pure component spectra from Raman maps of differently manufactured pharmaceutical tablets. The batches of different technologies differ in the homogeneity level of the active ingredient, thus, the curve resolution methods are tested under different conditions. An empirical approach is shown to determine the number of components present in a sample. The chemometric algorithms are compared regarding the number of detected components, the quality of the resolved spectra and the accuracy of scores (spectral concentrations) compared to those calculated with classical least squares, using the true pure component (reference) spectra. It is demonstrated that using appropriate multivariate methods, Raman chemical imaging can be a useful tool in the non-invasive characterization of unknown (e.g. illegal or counterfeit) pharmaceutical products. Copyright © 2011 Elsevier B.V. All rights reserved.

A PET reconstruction formulation that enforces non-negativity in projection space for bias reduction in Y-90 imaging

NASA Astrophysics Data System (ADS)

Lim, Hongki; Dewaraja, Yuni K.; Fessler, Jeffrey A.

2018-02-01

Most existing PET image reconstruction methods impose a nonnegativity constraint in the image domain that is natural physically, but can lead to biased reconstructions. This bias is particularly problematic for Y-90 PET because of the low probability positron production and high random coincidence fraction. This paper investigates a new PET reconstruction formulation that enforces nonnegativity of the projections instead of the voxel values. This formulation allows some negative voxel values, thereby potentially reducing bias. Unlike the previously reported NEG-ML approach that modifies the Poisson log-likelihood to allow negative values, the new formulation retains the classical Poisson statistical model. To relax the non-negativity constraint embedded in the standard methods for PET reconstruction, we used an alternating direction method of multipliers (ADMM). Because choice of ADMM parameters can greatly influence convergence rate, we applied an automatic parameter selection method to improve the convergence speed. We investigated the methods using lung to liver slices of XCAT phantom. We simulated low true coincidence count-rates with high random fractions corresponding to the typical values from patient imaging in Y-90 microsphere radioembolization. We compared our new methods with standard reconstruction algorithms and NEG-ML and a regularized version thereof. Both our new method and NEG-ML allow more accurate quantification in all volumes of interest while yielding lower noise than the standard method. The performance of NEG-ML can degrade when its user-defined parameter is tuned poorly, while the proposed algorithm is robust to any count level without requiring parameter tuning.

Multi-reader ROC studies with split-plot designs: a comparison of statistical methods.

PubMed

Obuchowski, Nancy A; Gallas, Brandon D; Hillis, Stephen L

2012-12-01

Multireader imaging trials often use a factorial design, in which study patients undergo testing with all imaging modalities and readers interpret the results of all tests for all patients. A drawback of this design is the large number of interpretations required of each reader. Split-plot designs have been proposed as an alternative, in which one or a subset of readers interprets all images of a sample of patients, while other readers interpret the images of other samples of patients. In this paper, the authors compare three methods of analysis for the split-plot design. Three statistical methods are presented: the Obuchowski-Rockette method modified for the split-plot design, a newly proposed marginal-mean analysis-of-variance approach, and an extension of the three-sample U-statistic method. A simulation study using the Roe-Metz model was performed to compare the type I error rate, power, and confidence interval coverage of the three test statistics. The type I error rates for all three methods are close to the nominal level but tend to be slightly conservative. The statistical power is nearly identical for the three methods. The coverage of 95% confidence intervals falls close to the nominal coverage for small and large sample sizes. The split-plot multireader, multicase study design can be statistically efficient compared to the factorial design, reducing the number of interpretations required per reader. Three methods of analysis, shown to have nominal type I error rates, similar power, and nominal confidence interval coverage, are available for this study design. Copyright © 2012 AUR. All rights reserved.

Complementary frame reconstruction: a low-biased dynamic PET technique for low count density data in projection space

NASA Astrophysics Data System (ADS)

Hong, Inki; Cho, Sanghee; Michel, Christian J.; Casey, Michael E.; Schaefferkoetter, Joshua D.

2014-09-01

A new data handling method is presented for improving the image noise distribution and reducing bias when reconstructing very short frames from low count dynamic PET acquisition. The new method termed ‘Complementary Frame Reconstruction’ (CFR) involves the indirect formation of a count-limited emission image in a short frame through subtraction of two frames with longer acquisition time, where the short time frame data is excluded from the second long frame data before the reconstruction. This approach can be regarded as an alternative to the AML algorithm recently proposed by Nuyts et al, as a method to reduce the bias for the maximum likelihood expectation maximization (MLEM) reconstruction of count limited data. CFR uses long scan emission data to stabilize the reconstruction and avoids modification of algorithms such as MLEM. The subtraction between two long frame images, naturally allows negative voxel values and significantly reduces bias introduced in the final image. Simulations based on phantom and clinical data were used to evaluate the accuracy of the reconstructed images to represent the true activity distribution. Applicability to determine the arterial input function in human and small animal studies is also explored. In situations with limited count rate, e.g. pediatric applications, gated abdominal, cardiac studies, etc., or when using limited doses of short-lived isotopes such as 15O-water, the proposed method will likely be preferred over independent frame reconstruction to address bias and noise issues.

Limited-angle multi-energy CT using joint clustering prior and sparsity regularization

NASA Astrophysics Data System (ADS)

Zhang, Huayu; Xing, Yuxiang

2016-03-01

In this article, we present an easy-to-implement Multi-energy CT scanning strategy and a corresponding reconstruction method, which facilitate spectral CT imaging by improving the data efficiency the number-of-energy- channel fold without introducing visible limited-angle artifacts caused by reducing projection views. Leveraging the structure coherence at different energies, we first pre-reconstruct a prior structure information image using projection data from all energy channels. Then, we perform a k-means clustering on the prior image to generate a sparse dictionary representation for the image, which severs as a structure information constraint. We com- bine this constraint with conventional compressed sensing method and proposed a new model which we referred as Joint Clustering Prior and Sparsity Regularization (CPSR). CPSR is a convex problem and we solve it by Alternating Direction Method of Multipliers (ADMM). We verify our CPSR reconstruction method with a numerical simulation experiment. A dental phantom with complicate structures of teeth and soft tissues is used. X-ray beams from three spectra of different peak energies (120kVp, 90kVp, 60kVp) irradiate the phantom to form tri-energy projections. Projection data covering only 75◦ from each energy spectrum are collected for reconstruction. Independent reconstruction for each energy will cause severe limited-angle artifacts even with the help of compressed sensing approaches. Our CPSR provides us with images free of the limited-angle artifact. All edge details are well preserved in our experimental study.

Cardiac-gated parametric images from 82 Rb PET from dynamic frames and direct 4D reconstruction.

PubMed

Germino, Mary; Carson, Richard E

2018-02-01

Cardiac perfusion PET data can be reconstructed as a dynamic sequence and kinetic modeling performed to quantify myocardial blood flow, or reconstructed as static gated images to quantify function. Parametric images from dynamic PET are conventionally not gated, to allow use of all events with lower noise. An alternative method for dynamic PET is to incorporate the kinetic model into the reconstruction algorithm itself, bypassing the generation of a time series of emission images and directly producing parametric images. So-called "direct reconstruction" can produce parametric images with lower noise than the conventional method because the noise distribution is more easily modeled in projection space than in image space. In this work, we develop direct reconstruction of cardiac-gated parametric images for 82 Rb PET with an extension of the Parametric Motion compensation OSEM List mode Algorithm for Resolution-recovery reconstruction for the one tissue model (PMOLAR-1T). PMOLAR-1T was extended to accommodate model terms to account for spillover from the left and right ventricles into the myocardium. The algorithm was evaluated on a 4D simulated 82 Rb dataset, including a perfusion defect, as well as a human 82 Rb list mode acquisition. The simulated list mode was subsampled into replicates, each with counts comparable to one gate of a gated acquisition. Parametric images were produced by the indirect (separate reconstructions and modeling) and direct methods for each of eight low-count and eight normal-count replicates of the simulated data, and each of eight cardiac gates for the human data. For the direct method, two initialization schemes were tested: uniform initialization, and initialization with the filtered iteration 1 result of the indirect method. For the human dataset, event-by-event respiratory motion compensation was included. The indirect and direct methods were compared for the simulated dataset in terms of bias and coefficient of variation as a function of iteration. Convergence of direct reconstruction was slow with uniform initialization; lower bias was achieved in fewer iterations by initializing with the filtered indirect iteration 1 images. For most parameters and regions evaluated, the direct method achieved the same or lower absolute bias at matched iteration as the indirect method, with 23%-65% lower noise. Additionally, the direct method gave better contrast between the perfusion defect and surrounding normal tissue than the indirect method. Gated parametric images from the human dataset had comparable relative performance of indirect and direct, in terms of mean parameter values per iteration. Changes in myocardial wall thickness and blood pool size across gates were readily visible in the gated parametric images, with higher contrast between myocardium and left ventricle blood pool in parametric images than gated SUV images. Direct reconstruction can produce parametric images with less noise than the indirect method, opening the potential utility of gated parametric imaging for perfusion PET. © 2017 American Association of Physicists in Medicine.

Image processing system and method for recognizing and removing shadows from the image of a monitored scene

DOEpatents

Osbourn, Gordon C.

1996-01-01

The shadow contrast sensitivity of the human vision system is simulated by configuring information obtained from an image sensor so that the information may be evaluated with multiple pixel widths in order to produce a machine vision system able to distinguish between shadow edges and abrupt object edges. A second difference of the image intensity for each line of the image is developed and this second difference is used to screen out high frequency noise contributions from the final edge detection signals. These edge detection signals are constructed from first differences of the image intensity where the screening conditions are satisfied. The positional coincidence of oppositely signed maxima in the first difference signal taken from the right and the second difference signal taken from the left is used to detect the presence of an object edge. Alternatively, the effective number of responding operators (ENRO) may be utilized to determine the presence of object edges.

Near-common-path interferometer for imaging Fourier-transform spectroscopy in wide-field microscopy

PubMed Central

Wadduwage, Dushan N.; Singh, Vijay Raj; Choi, Heejin; Yaqoob, Zahid; Heemskerk, Hans; Matsudaira, Paul; So, Peter T. C.

2017-01-01

Imaging Fourier-transform spectroscopy (IFTS) is a powerful method for biological hyperspectral analysis based on various imaging modalities, such as fluorescence or Raman. Since the measurements are taken in the Fourier space of the spectrum, it can also take advantage of compressed sensing strategies. IFTS has been readily implemented in high-throughput, high-content microscope systems based on wide-field imaging modalities. However, there are limitations in existing wide-field IFTS designs. Non-common-path approaches are less phase-stable. Alternatively, designs based on the common-path Sagnac interferometer are stable, but incompatible with high-throughput imaging. They require exhaustive sequential scanning over large interferometric path delays, making compressive strategic data acquisition impossible. In this paper, we present a novel phase-stable, near-common-path interferometer enabling high-throughput hyperspectral imaging based on strategic data acquisition. Our results suggest that this approach can improve throughput over those of many other wide-field spectral techniques by more than an order of magnitude without compromising phase stability. PMID:29392168

Image-Based 2D Re-Projection for Attenuation Substitution in PET Neuroimaging.

PubMed

Laymon, Charles M; Minhas, Davneet S; Becker, Carl R; Matan, Cristy; Oborski, Matthew J; Price, Julie C; Mountz, James M

2018-02-27

In dual modality positron emission tomography (PET)/magnetic resonance imaging (MRI), attenuation correction (AC) methods are continually improving. Although a new AC can sometimes be generated from existing MR data, its application requires a new reconstruction. We evaluate an approximate 2D projection method that allows offline image-based reprocessing. 2-Deoxy-2-[ 18 F]fluoro-D-glucose ([ 18 F]FDG) brain scans were acquired (Siemens HR+) for six subjects. Attenuation data were obtained using the scanner's transmission source (SAC). Additional scanning was performed on a Siemens mMR including production of a Dixon-based MR AC (MRAC). The MRAC was imported to the HR+ and the PET data were reconstructed twice: once using native SAC (ground truth); once using the imported MRAC (imperfect AC). The re-projection method was implemented as follows. The MRAC PET was forward projected to approximately reproduce attenuation-corrected sinograms. The SAC and MRAC images were forward projected and converted to attenuation-correction factors (ACFs). The MRAC ACFs were removed from the MRAC PET sinograms by division; the SAC ACFs were applied by multiplication. The regenerated sinograms were reconstructed by filtered back projection to produce images (SUBAC PET) in which SAC has been substituted for MRAC. Ideally SUBAC PET should match SAC PET. Via coregistered T1 images, FreeSurfer (FS; MGH, Boston) was used to define a set of cortical gray matter regions of interest. Regional activity concentrations were extracted for SAC PET, MRAC PET, and SUBAC PET. SUBAC PET showed substantially smaller root mean square error than MRAC PET with averaged values of 1.5 % versus 8.1 %. Re-projection is a viable image-based method for the application of an alternate attenuation correction in neuroimaging.

Land use mapping from CBERS-2 images with open source tools by applying different classification algorithms

NASA Astrophysics Data System (ADS)

Sanhouse-García, Antonio J.; Rangel-Peraza, Jesús Gabriel; Bustos-Terrones, Yaneth; García-Ferrer, Alfonso; Mesas-Carrascosa, Francisco J.

2016-02-01

Land cover classification is often based on different characteristics between their classes, but with great homogeneity within each one of them. This cover is obtained through field work or by mean of processing satellite images. Field work involves high costs; therefore, digital image processing techniques have become an important alternative to perform this task. However, in some developing countries and particularly in Casacoima municipality in Venezuela, there is a lack of geographic information systems due to the lack of updated information and high costs in software license acquisition. This research proposes a low cost methodology to develop thematic mapping of local land use and types of coverage in areas with scarce resources. Thematic mapping was developed from CBERS-2 images and spatial information available on the network using open source tools. The supervised classification method per pixel and per region was applied using different classification algorithms and comparing them among themselves. Classification method per pixel was based on Maxver algorithms (maximum likelihood) and Euclidean distance (minimum distance), while per region classification was based on the Bhattacharya algorithm. Satisfactory results were obtained from per region classification, where overall reliability of 83.93% and kappa index of 0.81% were observed. Maxver algorithm showed a reliability value of 73.36% and kappa index 0.69%, while Euclidean distance obtained values of 67.17% and 0.61% for reliability and kappa index, respectively. It was demonstrated that the proposed methodology was very useful in cartographic processing and updating, which in turn serve as a support to develop management plans and land management. Hence, open source tools showed to be an economically viable alternative not only for forestry organizations, but for the general public, allowing them to develop projects in economically depressed and/or environmentally threatened areas.

Validation of a Projection-domain Insertion of Liver Lesions into CT Images

PubMed Central

Chen, Baiyu; Ma, Chi; Leng, Shuai; Fidler, Jeff L.; Sheedy, Shannon P.; McCollough, Cynthia H.; Fletcher, Joel G.; Yu, Lifeng

2016-01-01

Rationale and Objectives The aim of this study was to validate a projection-domain lesion-insertion method with observer studies. Materials and Methods A total of 51 proven liver lesions were segmented from computed tomography images, forward projected, and inserted into patient projection data. The images containing inserted and real lesions were then reconstructed and examined in consensus by two radiologists. First, 102 lesions (51 original, 51 inserted) were viewed in a randomized, blinded fashion and scored from 1 (absolutely inserted) to 10 (absolutely real). Statistical tests were performed to compare the scores for inserted and real lesions. Subsequently, a two-alternative-forced-choice test was conducted, with lesions viewed in pairs (real vs. inserted) in a blinded fashion. The radiologists selected the inserted lesion and provided a confidence level of 1 (no confidence) to 5 (completely certain). The number of lesion pairs that were incorrectly classified was calculated. Results The scores for inserted and proven lesions had the same median (8) and similar interquartile ranges (inserted, 5.5–8; real, 6.5–8). The means scores were not significantly different between real and inserted lesions (P value = 0.17). The receiver operating characteristic curve was nearly diagonal, with an area under the curve of 0.58 ± 0.06. For the two-alternative-forced-choice study, the inserted lesions were incorrectly identified in 49% (25 out of 51) of pairs; radiologists were incorrect in 38% (3 out of 8) of pairs even when they felt very confident in identifying the inserted lesion (confidence level ≥4). Conclusions Radiologists could not distinguish between inserted and real lesions, thereby validating the lesion-insertion technique, which may be useful for conducting virtual clinical trials to optimize image quality and radiation dose. PMID:27432267

BioXTAS RAW: improvements to a free open-source program for small-angle X-ray scattering data reduction and analysis.

PubMed

Hopkins, Jesse Bennett; Gillilan, Richard E; Skou, Soren

2017-10-01

BioXTAS RAW is a graphical-user-interface-based free open-source Python program for reduction and analysis of small-angle X-ray solution scattering (SAXS) data. The software is designed for biological SAXS data and enables creation and plotting of one-dimensional scattering profiles from two-dimensional detector images, standard data operations such as averaging and subtraction and analysis of radius of gyration and molecular weight, and advanced analysis such as calculation of inverse Fourier transforms and envelopes. It also allows easy processing of inline size-exclusion chromatography coupled SAXS data and data deconvolution using the evolving factor analysis method. It provides an alternative to closed-source programs such as Primus and ScÅtter for primary data analysis. Because it can calibrate, mask and integrate images it also provides an alternative to synchrotron beamline pipelines that scientists can install on their own computers and use both at home and at the beamline.

Ultrafast state detection and 2D ion crystals in a Paul trap

NASA Astrophysics Data System (ADS)

Ip, Michael; Ransford, Anthony; Campbell, Wesley

2016-05-01

Projective readout of quantum information stored in atomic qubits typically uses state-dependent CW laser-induced fluorescence. This method requires an often sophisticated imaging system to spatially filter out the background CW laser light. We present an alternative approach that instead uses simple pulse sequences from a mode-locked laser to affect the same state-dependent excitations in less than 1 ns. The resulting atomic fluorescence occurs in the dark, allowing the placement of non-imaging detectors right next to the atom to improve the qubit state detection efficiency and speed. We also study 2D Coulomb crystals of atomic ions in an oblate Paul trap. We find that crystals with hundreds of ions can be held in the trap, potentially offering an alternative to the use of Penning traps for the quantum simulation of 2D lattice spin models. We discuss the classical physics of these crystals and the metastable states that are supported in 2D. This work is supported by the US Army Research Office.